Methods in Actinobacteriology (Springer Protocols Handbooks) 1071617273, 9781071617274

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Dhanasekaran Dharumadurai Editor

Methods in Actinobacteriology

SPRINGER PROTOCOLS HANDBOOKS

For further volumes: http://www.springer.com/series/8623

Springer Protocols Handbooks collects a diverse range of step-by-step laboratory methods and protocols from across the life and biomedical sciences. Each protocol is provided in the Springer Protocol format: readily-reproducible in a step-by-step fashion. Each protocol opens with an introductory overview, a list of the materials and reagents needed to complete the experiment, and is followed by a detailed procedure supported by a helpful notes section offering tips and tricks of the trade as well as troubleshooting advice. With a focus on large comprehensive protocol collections and an international authorship, Springer Protocols Handbooks are a valuable addition to the laboratory.

Methods in Actinobacteriology Edited by

Dhanasekaran Dharumadurai Department of Microbiology, Bharathidasan University, Tiruchirappalli, Tamil Nadu, India

Editor Dhanasekaran Dharumadurai Department of Microbiology Bharathidasan University Tiruchirappalli, Tamil Nadu, India

ISSN 1949-2448 ISSN 1949-2456 (electronic) Springer Protocols Handbooks ISBN 978-1-0716-1727-4 ISBN 978-1-0716-1728-1 (eBook) https://doi.org/10.1007/978-1-0716-1728-1 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Humana imprint is published by the registered company Springer Science+Business Media, LLC, part of Springer Nature. The registered company address is: 1 New York Plaza, New York, NY 10004, U.S.A.

Foreword

This book is valuable for everyone that includes university students, postdoctoral fellows, researchers, biotechnologists, and professors that are into actinobacteria research and its potential biotechnological applications. The information covered in the book will make it enjoyable and useful for every person that reads it. Reading through the pages in this book, one will expound on the knowledge of actinobacteria and comprehend better their taxonomical, physiological, and genomics status, and the biotechnological potential of this important group of bacteria for the production of metabolites that are of industrial applications. This year 2021 is a notable one on a comprehensive study of actinobacteria. In order to gain more insight into actinobacteria, there is a need to focus on isolation, identification, genomics and proteomics characterization, and the biological prospect of actinobacteria for improving plant growth, production of antibiotics, enzyme production, and biological control of diseases. Actinobacteria are Gram-positive bacteria that have shared characteristics of bacteria and fungi. They are associated with terrestrial and aquatic habitats contributing great economic importance to humans and plants. Besides plants and humans, the metabolites and enzymes produced by this beneficial microorganism help food, agricultural, and pharmaceutical industries. However, this book is written to provide comprehensive knowledge on laboratory techniques associated with actinobacteriology and bridge the gap in the previous books written on actinobacteria. The authors involved in the writing of this great book have made the experimental protocols and methodologies involved in the research into actinobacteria experiments easier to decipher. The sectionalization of the book into three parts is well thought out and starts with the most basic rudiments of isolating actinobacteria from different ecological niches. This section, which deals with protocols and methods that are involved in isolating actinobacteria from diverse habitats, will make it easier for students and beginners in the field of actinobacteriology to start from the basics for better comprehension of different isolation techniques and mechanisms involved in conducting this. Furthermore, I found the second section more advanced and suited for the wellgrounded researchers in the field of actinobacteria research. This section of the book is multidisciplinary, comprising genomics, transcriptomics, genome mining, MALDI-TOF analysis, preclinical evaluation, and molecular docking of metabolites from actinobacteria, which is well expounded. Noteworthy is the fact that the experimental procedures involved in this section are well explained and clearly described. As with all beneficial microbes, different methodologies on the isolation of actinobacteria from the soil, water, plants, and animals such as marine sediment, estuary, deep sea,

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sponges, shrimp, coral reef, earthworm cast, compost, termites, fecal, tissue samples, fishes, mangrove plants, hill, seaweeds, and seeds of the higher plant are highlighted in this book. Additionally, the genomic and proteomic characterizations of actinobacteria are achieved by different techniques such as chemotaxonomy, application of bioinformatics tools for phylogenetic analysis, whole-genome analysis of actinobacteria through bioinformatics approaches, nanopore-based long read sequencing technology to obtain highly contiguous whole-genome sequence of actinobacterial genomes like Streptomyces, comparative genomics of actinobacteria, mining the genomes of actinobacteria, biosynthetic gene cluster analysis in Micromonospora species using ANTISMASH : secondary metabolite genome mining pipeline, biosynthetic gene cluster analysis in actinobacterial genera—Streptomyces spp., PCR-based determination of secondary metabolite genes in actinobacterial cultures, molecular mass determination of bacteriocin by SDS-PAGE analysis, MALDI-TOF analysis of actinobacterial peptides with respect to MASCOT database, protocols for preclinical evaluation and molecular docking of antimicrobial compounds from Streptomyces spp.drug likeliness evaluation, docking modes between the ligand and the target enzyme and active site prediction, receptor cavity-based approach combined with autodock protocol for the screening of antiviral compounds from Streptomyces spp., and pharmacophore-based hypothesis combined with molecular docking protocol for the screening of anticancer compounds from Streptomyces spp. Therefore people of all educational standing can comprehend this section of the book as well. The third section focuses on the techniques involved in exploring bioactive compounds present in actinobacteria, which can be developed into valuable products in the industrial sector such as the pharmaceutical industry, food industry, and agriculture, which are comprehensively highlighted in this book. Among the topics discussed in this book are the purification of the pure bioactive compound from actinobacteria by bioassay-guided separation approach, production of vitamin B12 from Streptomyces species, screening of actinobacteria for anti-TB activity by Microplate Alamar Blue Assay (MABA), screening for anticancer activity: neutral red uptake assay, in vitro evaluation of actinobacterial extracts for anti-inflammatory properties, screening of actinobacteria for quorum sensing inhibition, production of lipase by actinobacteria, screening and analysis of actinobacterial bioherbicides for weed management, qualitative and quantitative estimation of phosphatesolubilizing actinobacteria, biocontrol activity of actinobacteria against plant pathogens, screening of actinobacteria for mosquitocidal activity, and biosynthesis and characterization of silver nanoparticles from actinobacteria. In this context, actinobacteria are known for their usefulness in the pharmaceutical, food, and agricultural sector, and the secondary metabolites they produce can be used as a biological agent to reduce the application of chemical agents that are detrimental to the environment. Such metabolites can fill the demand for biocontrol agents, vitamins, phytohormones, pigments, biosurfactants, biolarvicides, phytohormone production, enhancement of plant growth, actinobacterial probiotics screening methods, biocontrol plant pathogens, dye decolorization, bioleaching of heavy metals from e-waste, and nanoparticle synthesis. I commend all authors and editors who have contributed their expertise from isolation, genomics, and proteomics characterization to actinobacterial bioprospecting. This book contains 108 chapters explaining different laboratory techniques on isolation, genomics, and proteomics characterization and bioprospecting of actinobacterial research with

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methodology and data that have been critically assessed. This book is well written, and the experimental protocols are well expounded to ignite the flame of curiosity in students and upcoming young researchers’ minds. This book is highly recommended for everyone involved in microbial biotechnology, and it will motivate young students and scientists to explore further the increasingly important and evolving field of actinobacteriology.

Preface Actinobacteriology is the subject to understand the actinobacteria taxonomy, ecology, physiology, genomics, proteomics, and biotechnological applications. Actinobacteria, which share the characteristics of both bacteria and fungi, are widely distributed in both terrestrial and aquatic ecosystems, mainly in soil, where they play an essential role in recycling refractory biomaterials by decomposing complex mixtures of polymers in dead plants and animals and fungal materials. It is an economically important group of bacteria and explored for industrially important metabolites production like antibiotics, vitamins, probiotics, and plant growth promoters. They are considered as the biotechnologically valuable bacteria that are exploited for its secondary metabolite production. Approximately, 10,000 bioactive metabolites are produced by Actinobacteria, which is 45% of all bioactive microbial metabolites discovered. Especially Streptomyces species produce industrially important microorganisms as they are a rich source of several useful bioactive natural products with potential applications. There are very few books available for taxonomic identifications and bioprospecting of actinobacteria. However, there are inadequate books on experimental protocol on actinobacteriology; hence the present protocol on Methods in Actinobacteriology is essentially necessary for the actinobacteriologist. In this book, collectively 108 experimental protocols are placed under three different sections: Section I: Isolation of actinobacteria from terrestrial, freshwater, and marine habitat: Actinobacteria association in plants and animals, Section II: Genomics and proteomics of actinobacteria, Section III: Bioprospecting of actinobacteria. The first section describes the isolation methods of epiphytic, endophytic, psychrophilic, thermophilic, halophilic, symbiotic, and gut actinobacteria. It defines the isolation protocol from different habitat, including soil, sediment, water, estuary, deep sea plant flower, seeds, root, root nodule, sea weeds, mangroves, lichen fish, shrimp, termites, coral reef, earthworm, and compost. It also illustrates the cultivation techniques of rare actinobacteria and stone dwelling actinobacteria. The second section describes genome mining, comparative genomics of actinobacteria, methods for whole-genome analysis of actinobacteria through bioinformatics approaches, nanopore-based long read sequencing technology to obtain highly contiguous whole genome sequence, transcriptome profiles of Streptomyces sp., biosynthetic gene cluster analysis, MALDI-TOF analysis of actinobacterial peptides, molecular mass determination of bacteriocin, preclinical evaluation, and molecular docking of compounds from Streptomyces. The bioprospecting section describes the protocol on screening of primary and secondary metabolites from actinobacteria including antibacterial, antifungal, antiviral, anticancer, antioxidant, anti-inflammatory, immunostimulatory, herbicidal, nematicidal, antiplasmodial, biofilm inhibitory compounds, detection of enzymes, vitamins, pigments, biosurfactants, biolarvicides, phytohormone production, enhancement of plant growth, actinobacterial probiotics screening methods, biocontrol plant pathogens, dye decolorization, bioleaching of heavy metals from e-waste, and nanoparticle synthesis. The book is contributed by 152 authors across the globe including Brazil, China, Czech Republic, Egypt, Korea, Italy, India, Malaysia, Saudi Arabia, Taiwan, and USA. This book is used as a source of information in different fields like microbiology, biotechnology, and

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molecular biology. I strongly believe that in future course more research will to be carried out in actinobacteria. I am extremely thankful to all the authors who contributed protocols for their prompt and timely responses. I extend my earnest appreciation to Monica Suchy, Editor, Springer Protocols, Springer Nature group, and their team for their constant encouragement and help in bringing out the volume in the present form. I also record my gratitude to Prof. Olubukola O. Babalola, Department of Biological Sciences, North-West University, Private Bag X2046, Mmabatho 2735, South Africa, for her support. We are also indebted to Springer Protocols, Springer Nature, New York, USA, and the Authorities of Bharathidasan University, Tiruchirappalli, Tamil Nadu, India, for their support in the task of publishing the protocols. Tiruchirappalli, Tamil Nadu, India

Dhanasekaran Dharumadurai

Contents Foreword. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Contributors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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1 Isolation of Actinobacteria from Soil and Marine Sediment Samples. . . . . . . . . . . T. Savitha, Ashraf Khalifa, and A. Sankaranarayanan 2 Isolation of Actinobacteria from Water Sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Tamalika Chakraborty, Sumana Roy, Dipanjan Mandal, Jeenatara Begum, and Abhijit Sengupta 3 Isolation of Actinobacteria from Deep Sea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Aparana Kumari and K. V. Bhaskara Rao 4 Isolation of Actinobacteria from Estuaries. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ashraf Khalifa and A. Sankaranarayanan 5 Isolation of Actinobacteria from Sponges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Neethu Kamarudheen and Kokati Venkata Bhaskara Rao 6 Isolation of Actinobacteria from Shrimp . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. S. Shijila Rani, S. Babu, A. Anbukumaran, P. Prakash, S. Veeramani, and V. Ambikapathy 7 Isolation of Actinobacteria from Coral Reef . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . S. Babu, A. S. Shijila Rani, V. Ambikapathy, P. Prakash, and A. Anbukumaran 8 Isolation of Actinobacteria from Earthworm Cast . . . . . . . . . . . . . . . . . . . . . . . . . . . V. Ambikapathy, A. S. Shijila Rani, A. Anbukumaran, R. Shanmugapriya, and S. Babu 9 Isolation of Actinobacteria from Compost Samples. . . . . . . . . . . . . . . . . . . . . . . . . . T. Savitha, Ashraf Khalifa, and A. Sankaranarayanan 10 Isolation of Gut Actinobacteria from Fecal and Tissue Samples . . . . . . . . . . . . . . . Priyanka Sarkar 11 Isolation of Gut Actinobacteria from Termites. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . S. Malavika, Sahana Kranthi, H. S. Shishira Rao, Shreyanka S. Moily, and A. Martin Paul 12 Isolation of Gut Actinobacteria from Fishes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . S. Thejaswini, Sruthy Jojy, Aditi Vijayan, and A. Martin Paul 13 Isolation of Actinobacteria from Mangrove Plants . . . . . . . . . . . . . . . . . . . . . . . . . . V. Ambikapathy, S. Babu, A. Anbukumaran, A. S. Shijila Rani, and P. Prakash 14 Isolation of Actinobacteria from Seaweeds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Apsara S. Babu and Kokati Venkata Bhaskara Rao 15 Isolation of Actinobacteria from Hills . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . M. Veerapagu, K. R. Jeya, and A. Sankaranarayanan

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Isolation of Endophytic Actinobacteria from Flowers, Fruits, and Seeds of Higher Plants. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . D. Jayanthi, A. Martin Paul, and Leena Sebastian Isolation Actinobacteria from Desert Soils . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ashraf Khalifa and A. Sankaranarayanan Methods for Isolation of Epiphytic Actinobacteria from Rhizosphere of Spermatophytes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . S. Shravya, S. J. Meghana, and D. Jayanthi Isolation of Epiphytic Actinobacteria from Lichens. . . . . . . . . . . . . . . . . . . . . . . . . . M. S. Shabeena Banu, T. Nargis Begum, G. Vinothini, D. Dhanasekaran, and N. Thajuddin Isolation of Endophytic Actinobacteria from Lichens. . . . . . . . . . . . . . . . . . . . . . . . M. S. Shabeena Banu, T. Nargis Begum, D. Dhanasekaran, and N. Thajuddin Isolation of Psychrophilic and Psychrotolerant Actinobacteria . . . . . . . . . . . . . . . . Manigundan Kaari, Abirami Baskaran, Gopikrishnan Venugopal, Radhakrishnan Manikkam, and Parli V. Bhaskar Isolation of Halophilic Actinobacteria from Different Habitats . . . . . . . . . . . . . . . A. Martin Paul and D. Jayanthi Isolation of Thermophilic Actinobacteria from Different Habitats . . . . . . . . . . . . Pranjali Chole, Lokesh Ravi, and Kannabiran Krishnan Isolation of Stone-Dwelling Actinobacteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Shabari Girish, Lokesh Ravi, and Kannabiran Krishnan Cultivation Techniques of Rare Actinobacteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Vijayakumar Ramasamy, Thirumurugan Durairaj, Cholarajan Alagappan, and Raja Suresh Selvapuram Sudalaimuthu Chemotaxonomical Characterization of Actinobacteria . . . . . . . . . . . . . . . . . . . . . . Vijayakumar Ramasamy and Raja Suresh Selvapuram Sudalaimuthu Application of Bioinformatic Tools for Phylogenetic Analysis. . . . . . . . . . . . . . . . . Manigundan Kaari, Jerrine Joseph, Radhakrishnan Manikkam, Mary Shamya, and Wilson Aruni Methods for Whole-Genome Analysis of Actinobacteria Through Bioinformatics Approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . I. Sarkar, G. Sen, and A. Sen Nanopore-Based Long-Read Sequencing Technology to Obtain Highly Contiguous Whole-Genome Sequence of Actinobacterial Genomes like Streptomyces Sp.: A Complete Guide for Actinobacterial Whole Genome Sequencing Project Using Nanopore . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sankaranarayanan Gomathinayagam, Loganathan Karthik, and Kodiveri Muthukaliannan Gothandam Mining Genomes of Actinobacteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ` , and Federico Bussolino Sushant Parab, Davide Cora Comparative Genomics of Actinobacteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ` , and Federico Bussolino Sushant Parab, Davide Cora

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Biosynthetic Gene Cluster Analysis in Micromonospora Species Using ANTISMASH: Secondary Metabolite Genome Mining Pipeline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mukesh Kumar Manickasamy, Rajagopal Narayanan, and Dhanasekaran Dharmadurai Biosynthetic Gene Cluster Analysis in Actinobacterial Genus Streptomyces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Marke´ta Macho, Daniela Ewe, Vishal Ahuja, Jihen Thabet, Avik Banerjee, Kumar Saurav, and Subhasish Saha PCR-Based Determination of Secondary Metabolite Genes in Actinobacterial Cultures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Manigundan Kaari, Abirami Baskaran, Gopikrishnan Venugopal, Jerrine Joseph, and Radhakrishnan Manikkam Molecular Mass Determination of Bacteriocin by SDS-PAGE Analysis. . . . . . . . . Santhosh Arul, M. Jayashankar, and Haripriya Dayalan MALDI-TOF Analysis of Actinobacterial Peptides with Respect to MASCOT Database . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Shanmugaraj Gowrishankar, Arumugam Kamaladevi, and Shunmugiah Karutha Pandian Protocols for Preclinical Evaluation and Molecular Docking of Antimicrobial Compounds from Streptomyces sp., Drug Likeliness Evaluation, ADME-Toxicity Investigation, Docking Modes Between the Ligand and the Target Enzyme, and Active Site Prediction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. K. Anirudh Sreenivas, B. Akshaya, Lokesh Ravi, and Kannabiran Krishnan Energy-Based Pharmacophore Hypothesis Combined with Molecular Simulation Protocol for the Screening of Bioactive Compounds from the Class of Actinobacteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Muthu Kumar Thirunavukkarasu and Ramanathan Karuppasamy Receptor Cavity-Based Approach Combined with Autodock Protocol for the Screening of Antiviral Compounds from Streptomyces sp. . . . . . . . . . . . . . . Rohini K and Shanthi V Pharmacophore-Based Hypothesis Combined with Molecular Docking Protocol for the Screening of Anticancer Compounds from Streptomyces sp. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Saranyadevi Subburaj, Priyanka Ramesh, and Shanthi Veerappapillai Methods of Identification and Validation of Drug Target . . . . . . . . . . . . . . . . . . . . Jerrine Joseph, Radhakrishnan Manikkam, Manigundan Kaari, Gopikrishnan Venugopal, Mary Shamya, and Wilson Aruni Transcriptome Profiles of Streptomyces sp. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ` , and Federico Bussolino Sushant Parab, Davide Cora Culture of Actinobacteria, Isolation and Characterization of their Bioactive Compounds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Charles Santhanaraju Vairappan

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Miniaturized Production of Bioactive Extracts from Actinobacteria . . . . . . . . . . . Abirami Baskaran, Radhakrishnan Manikkam, Manigundan Kaari, Jerrine Joseph, Gopikrishnan Venugopal, and Balagurunathan Ramasamy Screening, Characterization, and Identification of Antibacterial Compounds from Actinobacteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . T. Savitha, Ashraf Khalifa, and A. Sankaranarayanan Isolation, Identification, and Screening of Polyene Antifungal Compound Producing Streptomyces sampsonii MDCE7 from Agroforestry Soil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Srinivasan Radhakrishnan and Mohan Varadharajan Screening of Actinobacterial Cultures for Antimycobacterial Activity Using Mycobacterium smegmatis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ramachandran Chelliah and Deog-Hwan Oh Screening of Actinobacterial Extracts/Compounds for Antimycobacterial Activity by Luciferase Reporter Phage (LRP) Assay . . . . . . . . . . . . . . . . . . . . . . . . . Shuai Wei, Shucheng Liu, Ramachandran Chelliah, and Deog-Hwan Oh Screening of Actinobacteria for Anti-TB Activity by Microplate Alamar Blue Assay (MABA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Shuai Wei, Shucheng Liu, Ramachandran Chelliah, and Deog-Hwan Oh Screening of Actinobacteria for Anti-TB Activity by Agar Dilution Assay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ramachandran Chelliah and Deog-Hwan Oh Antiplasmodial Activity of Halophilic Actinobacteria . . . . . . . . . . . . . . . . . . . . . . . . Dharumadurai Dhanasekaran and Saravanan Karthikeyan An In Vitro Antiamoebic Activity of Actinobacteria . . . . . . . . . . . . . . . . . . . . . . . . . Karthiyayini Balakrishnan, Dhanasekaran Dharumadurai, Thirumurugan Ramasamy, and Muthuselvam Manickam Screening for Antiviral Activity: MTT Assay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ramachandran Chelliah, Fazle Elahi, and Deog-Hwan Oh Screening for Anticancer Activity: 3-(4,5-Dimethylthiazol-2-yl)-2, 5-Diphenyltetrazolium (MTT) Assay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ramachandran Chelliah and Deog-Hwan Oh Screening for Anticancer Activity: Dual Staining Method . . . . . . . . . . . . . . . . . . . . Ramachandran Chelliah and Deog-Hwan Oh Screening for Anticancer Activity: Neutral Red Uptake Assay. . . . . . . . . . . . . . . . . Ramachandran Chelliah and Deog-Hwan Oh Screening for Anticancer Activity: Lactic Acid Dehydrogenase Assay. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ramachandran Chelliah and Deog-Hwan Oh Screening for Anticancer Activity: DNA Fragmentation Assay . . . . . . . . . . . . . . . . InamulHasan Madar, Ghazala Sultan, Ramachandran Chelliah, and Deog-Hwan Oh

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Screening for Anticancer Activity: Trypan Blue Exclusion Assay . . . . . . . . . . . . . . InamulHasan Madar, Ghazala Sultan, Ramachandran Chelliah, and Deog-Hwan Oh In Vitro Evaluation of Antimitotic Properties of Actinobacterial Extracts Using Onion Root Tip Assay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Gopikrishnan Venugopal, Radhakrishnan Manikkam, Manigundan Kaari, Shanmugasundaram Thangavel, and Jerrine Joseph Screening for Antioxidant Activity: Diphenylpicrylhydrazine (DPPH) Assay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Momna Rubab, Ramachandran Chelliah, and Deog-Hwan Oh Screening for Antioxidant Activity: Nitric Oxide Scavenging Assay . . . . . . . . . . . . Ramachandran Chelliah, Eric Banan-MwineDaliri, and Deog-Hwan Oh Screening for Antioxidant Activity: Metal Chelating Assay . . . . . . . . . . . . . . . . . . . Ramachandran Chelliah and Deog-Hwan Oh Screening for Antioxidant Activity: Total Antioxidant Assay . . . . . . . . . . . . . . . . . . Ramachandran Chelliah, Eric Banan-MwineDaliri, and Deog-Hwan Oh Screening for Antioxidant Activity: Hydrogen Peroxide Scavenging Assay . . . . . Ramachandran Chelliah, Eric Banan-MwineDaliri, and Deog-Hwan Oh In Vitro Evaluation of Actinobacterial Extracts for Anti-Inflammatory Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Abirami Baskaran, Manigundan Kaari, Mary Shamya, Jerrine Joseph, Shanmugasundaram Thangavel, and Radhakrishnan Manikkam Screening and Production of Antifreeze Proteins from Actinobacteria . . . . . . . . . Abirami Baskaran, Radhakrishnan Manikkam, Manigundan Kaari, Gopikrishnan Venugopal, Somasundaram Thirugnanasambandham, and Parli V. Bhaskar In Vitro Evaluation of Actinobacterial Extracts for Immunomodulatory Properties. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Abirami Baskaran, Manigundan Kaari, Radhakrishnan Manikkam, Gopikrishnan Venugopal, Jerrine Joseph, Shanmugasundaram Thangavel, and Somasundaram Thirugnanasambandham Screening of Actinobacteria for Enzyme Inhibitor Activity . . . . . . . . . . . . . . . . . . . Ramachandran Chelliah, Eric Banan-MwineDaliri, and Deog-Hwan Oh Screening of Actinobacteria for Quorum Sensing Inhibition . . . . . . . . . . . . . . . . . Ramachandran Chelliah, Eric Banan-MwineDaliri, and Deog-Hwan Oh Screening of Actinobacterial Extracts for Anti-biofilm Activity . . . . . . . . . . . . . . . . Ramachandran Chelliah, Eric Banan-MwineDaliri, and Deog-Hwan Oh

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Screening of Actinobacteria for Microbial Induced Calcium Precipitation (MICP). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Manigundan Kaari, Abirami Baskaran, Gopikrishnan Venugopal, and Radhakrishnan Manikkam Immobilization of Actinobacterial Cells: Sodium Alginate and Calcium Chloride Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Gopikrishnan Venugopal, Manigundan Kaari, Abirami Baskaran, and Radhakrishnan Manikkam Production of Actinobacteria Amylase by Fermentation in Solid State Using Residues of Licuri Palm (Syagrus coronata). . . . . . . . . . . . . . . . . . . . . . Milena Santos Aguiar, Rafael Resende Maldonado, Andrea Limoeiro Carvalho, and Elizama Aguiar-Oliveira Production of Lipase by Actinobacteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Isabely Fernanda Pizarro, Handray Fernandes de Souza, Janaı´na dos Santos Ferreira, Rafael Resende Maldonado, Eliana Setsuko Kamimura, and Elizama Aguiar-Oliveira Isolation and Cultivation of Actinobacteria by Submerged Fermentation for the Production of Keratinase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Rafael Resende Maldonado, Taı´s Rosaˆngela Correia Souza, Simone Kubeneck, Elizama Aguiar-Oliveira, and Helen Treichel Screening of Cellulase from Actinobacteria. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Varsha N. Swamy, M. A. Haneen, and M. Jayashankar Screening of Pectinase from Actinobacteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . M. A. Haneen, M. Jayashankar, and Varsha N. Swamy Screening of Protease from Actinobacteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ashwitha Gopal, Varsha N. Swamy, Santhosh Arul, and Jayashankar M Screening and Analysis of Actinobacterial Bioherbicides for Weed Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . K. Prem Anand and K. Suthindhiran In Vitro Assessment of Actinobacteria for Survivability Under Simulated Gastrointestinal Transit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Vinothini Gopal, M. S. Shabeena Banu, Seema Siddharthan, and Dhanasekaran Dharumadurai In Vitro Assessment of Actinobacterial Isolates for Probiotic Properties Assessment of Actinobacteria for Safety Traits . . . . . . . . . . . . . . . . . . . . Vinothini Gopal and Dhanasekaran Dharumadurai Screening of Actinobacterial Probiotics by Anti-Pathogenic Activity Test. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Peng Chen, Zhongkun Zhou, Yunhao Ma, Rentao Zhang, and Mengze Sun Screening and Analysis of Probiotic Actinobacteria in Poultry Farming. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Moˆnica Roberta Mazalli, Rafael Resende Maldonado, and Elizama Aguiar-Oliveira

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Vitamin B12 Producing Actinobacteria as Probiotics for Poultry Production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Firdosh Shah and Mitesh Dwivedi Qualitative and Quantitative Estimation of Phosphate Solubilizing Actinobacteria. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Shreya Desai and Natarajan Amaresan Estimation of Nitrogen Production by Actinobacteria . . . . . . . . . . . . . . . . . . . . . . . Shreya Desai and Natarajan Amaresan Screening of Actinobacteria for Siderophore Production. . . . . . . . . . . . . . . . . . . . . Caroline Mercy Andrew Swamidoss, Ramachandran Chelliah, and Deog-Hwan Oh Isolation and Screening of Symbiotic Actinobacteria from Root Nodules of Actinorhizal Plant Casuarina sp. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Dhanasekaran Dharumadurai and Karthikeyan Saravanan Biocontrol Activity of Actinobacteria Against Plant Pathogens. . . . . . . . . . . . . . . . Shreya Desai and Natarajan Amaresan An In Vitro Nematicidal Activity of Actinobacteria: Juvenile Mortality and Egg Hatching Inhibition . . . . . . . . . . . . . . . . . . . . . . . . . . . . Vijayakumar Vishnu Raja and Dharumadurai Dhanasekaran Estimation of Auxin Production by Actinobacteria . . . . . . . . . . . . . . . . . . . . . . . . . . Shreya Desai and Natarajan Amaresan Screening of Actinobacteria for Mosquitocidal Activity . . . . . . . . . . . . . . . . . . . . . . Caroline Mercy Andrew Swamidoss, Ramachandran Chelliah, and Deog-Hwan Oh Extraction, Characterization, and Identification of Odorous Metabolites from Streptomyces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Dhanasekaran Dharumadurai, Karthikeyan Saravanan, Chandraleka Saravanan, Sivaranjani Govindhan, and Latha Selvanathan Screening of Actinobacteria for Biosurfactant Production . . . . . . . . . . . . . . . . . . . . Ramachandran Chelliah, Eric Banan-Mwine Daliri, and Deog-Hwan Oh Optimization and Characterization of Biosurfactant from Streptomyces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Vishal Ahuja, Marke´ta Macho, Jihen Thabet, Avik Banerjee, Daniela Ewe, Subhasish Saha, and Kumar Saurav Production of Vitamin B12 from Streptomyces Species. . . . . . . . . . . . . . . . . . . . . . . . M. Camil Rex, B. Akshaya, Lokesh Ravi, and Kannabiran Krishnan Screening of Microbes for the Production of Pigment (Melanin) . . . . . . . . . . . . . Ramachandran Chelliah and Deog-Hwan Oh Exploration and Characterization of Melanin Pigment Produced by Actinomycetes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Puja Gupta, Madangchanok Imchen, and Ranjith Kumavath

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Contents

100 Isolation and Production of Prodigiosin Pigments from Streptomyces spp. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Leena Sebastian, A. Martin Paul, and D. Jayanthi 101 Aerobic and Anaerobic Decolorization of Textile Dyes Using Actinobacteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Vijayakumar Ramasamy and Raja Suresh Selvapuram Sudalaimuhu 102 Bioleaching of Heavy Metals from e-Waste Using Actinobacteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Gopikrishnan Venugopal, Manigundan Kaari, Meganathan P. Ramakodi, and Radhakrishnan Manikkam 103 Biosynthesis and Characterization of Silver Nanoparticles from Actinobacteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . R. T. V. Vimala, G. Rajivgandhi, S. Sridharan, M. Jayapriya, G. Ramachandran, C. Chenthis Kanisha, N. Manoharan, and Wen-Jun Li 104 Biosynthesis and Characterization of Gold Nanoparticles from Actinobacteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . R. T. V. Vimala, G. Rajivgandhi, S. Sridharan, M. Jayapriya, G. Ramachandran, C. Chenthis Kanisha, N. Manoharan, and Wen-Jun Li 105 Antimicrobial Activity of Extracellular Green-Synthesized Nanoparticles by Actinobacteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . R. T. V. Vimala, G. Rajivgandhi, S. Sridharan, M. Jayapriya, G. Ramachandran, C. Chenthis Kanisha, N. Manoharan, and Wen-Jun Li 106 Antibiofilm Activity of Extracellular Green-Synthesized Nanoparticles by Actinobacteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . R. T. V. Vimala, G. Rajivgandhi, S. Sridharan, M. Jayapriya, G. Ramachandran, C. Chenthis Kanisha, N. Manoharan, and Wen-Jun Li 107 Cytotoxic Activity of Extracellular Green Synthesized Nanoparticles by Actinobacteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . R. T. V. Vimala, G. Rajivgandhi, S. Sridharan, M. Jayapriya, G. Ramachandran, C. Chenthis Kanisha, N. Manoharan, and Wen-Jun Li 108 Sporicidal Activity of Extracellular Green-Synthesized Nanoparticles by Actinobacteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . R. T. V. Vimala, G. Rajivgandhi, S. Sridharan, M. Jayapriya, G. Ramachandran, C. Chenthis Kanisha, N. Manoharan, and Wen-Jun Li Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Contributors MILENA SANTOS AGUIAR • State University of Santa Cruz, Ilhe´us, Bahia, Brazil ELIZAMA AGUIAR-OLIVEIRA • Exact Sciences and Technology Department, State University of Santa Cruz, Ilhe´us, Bahia, Brazil VISHAL AHUJA • Department of Biotechnology, Himachal Pradesh University, Shimla, Himachal Pradesh, India B. AKSHAYA • Department of Botany, St. Joseph’s College (Autonomous), Bengaluru, Karnataka, India CHOLARAJAN ALAGAPPAN • P.G. Department of Microbiology, Srinivasan College of Arts and Science, Perambalur, Tamil Nadu, India NATARAJAN AMARESAN • C. G. Bhakta Institute of Biotechnology, Uka Tarsadia University, Surat, Gujarat, India V. AMBIKAPATHY • Department of Botany, A.V.V.M. Sri Pushpam College (Autonomous), (Affiliated to Bharathidasan University, Trichy), Thanjavur, Tamil Nadu, India A. ANBUKUMARAN • Department of Microbiology, Urumu Dhanalakshmi College, (Affiliated to Bharathidasan University), Trichy, Tamil Nadu, India B. K. ANIRUDH SREENIVAS • Department of Botany, St. Joseph’s College (Autonomous), Bengaluru, Karnataka, India SANTHOSH ARUL • Department of Biotechnology, Rajalakshmi Engineering College (Anna University), Chennai, India WILSON ARUNI • Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu, India; School of Medicine, Loma Linda University, Loma Linda, CA, USA; Musculoskeletal Disease Research Laboratory US Department of Veteran Affairs, Loma Linda, CA, USA ASHWITHA GOPAL • ICAR-National Bureau of Agricultural Insect Resources, Bengaluru, India APSARA S. BABU • Marine Biotechnology Laboratory, Vellore Institute of Technology, Vellore, Tamil Nadu, India S. BABU • Department of Botany, A.V.V.M. Sri Pushpam College (Autonomous), (Affiliated to Bharathidasan University, Trichy), Thanjavur, Tamil Nadu, India KARTHIYAYINI BALAKRISHNAN • National Centre for alternatives to Animal Experiments, Bharathidasan University, Tiruchirappalli, Tamil Nadu, India; Department of Microbiology, Bharathidasan University, Tiruchirappalli, Tamil Nadu, India ERIC BANAN-MWINEDALIRI • Department of Food Science and Biotechnology, College of Agriculture and Life Sciences, Kangwon National University, Chuncheon, Gangwon-do, South Korea AVIK BANERJEE • Laboratory of Algal Biotechnology, Centre Algatech, Institute of Microbiology of the Czech Academy of Sciences, Trˇebonˇ, Czech Republic M. S. SHABEENA BANU • PG & Research Department of Biotechnology, Jamal Mohamed College, Affiliated to Bharathidasan University, Tiruchirappalli, Tamil Nadu, India ABIRAMI BASKARAN • Centre for Drug Discovery and Development, Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu, India JEENATARA BEGUM • Division of Pharmaceutics, Guru Nanak Institute of Pharmaceutical Science and Technology, Kolkata, West Bengal, India

xix

xx

Contributors

PARLI V. BHASKAR • National Centre for Polar and Ocean Research, Ministry of Earth Sciences, Vasco da Gama, Goa, India KOKATI VENKATA BHASKARA RAO • Marine Biotechnology Laboratory, Vellore Institute of Technology, Vellore, Tamil Nadu, India FEDERICO BUSSOLINO • Department of Oncology, University of Turin, Turin, Italy; Department of Oncology, Candiolo Cancer Institute FPO–IRCCS, Candiolo, Italy ANDREA LIMOEIRO CARVALHO • State University of Feira de Santana, Feira de Santana, Bahia, Brazil TAMALIKA CHAKRABORTY • Division of Life Science, Guru Nanak Institute of Pharmaceutical Science and Technology, Kolkata, West Bengal, India SARAVANAN CHANDRALEKA • Department of Chemistry, Urumu Dhanalakshmi College, Tiruchirappalli, Tamil Nadu, India RAMACHANDRAN CHELLIAH • Department of Food Science and Biotechnology, College of Agriculture and Life Sciences, Kangwon National University, Chuncheon, Gangwon-do, South Korea PENG CHEN • School of Pharmacy, Lanzhou University, Lanzhou, Gansu, People’s Republic of China PRANJALI CHOLE • Department of Botany, St. Joseph’s College (Autonomous), Bengaluru, Karnataka, India DAVIDE CORA` • Department of Translational Medicine, Piemonte Orientale University, Novara, Italy; Center for Translational Research on Autoimmune and Allergic Diseases – CAAD, Novara, Italy HARIPRIYA DAYALAN • Department of Biotechnology, Rajalakshmi Engineering College (Anna University), Chennai, India HANDRAY FERNANDES DE SOUZA • Faculty of Animal Science and Food Engineering, University of Sa˜o Paulo, Pirassununga, Sa˜o Paulo, Brazil SHREYA DESAI • C. G. Bhakta Institute of Biotechnology, Uka Tarsadia University, Surat, Gujarat, India DHANASEKARAN DHARUMADURAI • Department of Microbiology, School of Life Sciences, Bharathidasan University, Tiruchirappalli, Tamil Nadu, India JANAI´NA DOS SANTOS FERREIRA • Department of Chemistry and Food Engineering, Federal University of Santa Catarina, Florianopolis, Santa Catarina, Brazil THIRUMURUGAN DURAIRAJ • Department of Biotechnology, College of Science and Humanities, SRM Institute of Science and Technology, Chennai, India MITESH DWIVEDI • C. G. Bhakta Institute of Biotechnology, Faculty of Science, Uka Tarsadia University, Surat, Gujarat, India FAZLE ELAHI • Department of Food Science and Biotechnology, College of Agriculture and Life Sciences, Kangwon National University, Chuncheon, Gangwon-do, South Korea DANIELA EWE • Laboratory of Algal Biotechnology, Centre Algatech, Institute of Microbiology of the Czech Academy of Sciences, Trˇebonˇ, Czech Republic SHABARI GIRISH • Department of Botany, St. Joseph’s College (Autonomous), Bengaluru, Karnataka, India SANKARANARAYANAN GOMATHINAYAGAM • School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India VINOTHINI GOPAL • Department of Microbiology, School of Life Sciences, Bharathidasan University, Tiruchirappalli, Tamil Nadu, India KODIVERI MUTHUKALIANNAN GOTHANDAM • School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India

Contributors

xxi

SHANMUGARAJ GOWRISHANKAR • Department of Biotechnology, Science Campus, Alagappa University, Karaikudi, Tamil Nadu, India PUJA GUPTA • School of Biotechnology, University of Jammu, Jammu, Jammu and Kashmir, India M. A. HANEEN • Department of Microbiology, Dayananda Sagar University, Bengaluru, India MADANGCHANOK IMCHEN • Department of Genomic Science, Central University of Kerala, Kasaragod, Kerala, India D. JAYANTHI • Mount Carmel College, Autonomous, Bengaluru, Karnataka, India M. JAYAPRIYA • Department of Petrochemical Technology, Anna University-BIT Campus, Tiruchirappalli, Tamil Nadu, India K. R. JEYA • Department of Biotechnology, Government Arts and Science College (Women), Perambalur, Tamil Nadu, India SRUTHY JOJY • Government Science College, Bengaluru, Karnataka, India JERRINE JOSEPH • Centre for Drug Discovery and Development, Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu, India ROHINI K • Department of Biotechnology, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India MANIGUNDAN KAARI • Centre for Drug Discovery and Development, Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu, India ARUMUGAM KAMALADEVI • Department of Animal Science, Bharathidasan University, Tiruchirappalli, Tamil Nadu, India NEETHU KAMARUDHEEN • Marine Biotechnology Laboratory, Vellore Institute of Technology, Vellore, Tamil Nadu, India ELIANA SETSUKO KAMIMURA • Faculty of Animal Science and Food Engineering, University of Sa˜o Paulo, Pirassununga, Sa˜o Paulo, Brazil C. CHENTHIS KANISHA • Marine Pharmacology and Toxicology Laboratory, Department of Marine Science, Bharathidasan University, Tiruchirappalli, Tamil Nadu, India LOGANATHAN KARTHIK • Research and Development, Salem Microbes Private Limited, Salem, Tamil Nadu, India SARAVANAN KARTHIKEYAN • Department of Microbiology, School of Life Sciences, Bharathidasan University, Tiruchirappalli, Tamil Nadu, India RAMANATHAN KARUPPASAMY • Department of Biotechnology, School of Bio Sciences and Technology, Vellore, Tamil Nadu, India ASHRAF KHALIFA • Department of Biological Sciences, College of Sciences, King Faisal University, Al-Ahsa, Saudi Arabia; Botany and Microbiology Department, Faculty of Sciences, Beni-Suef University, Beni-Suef, Egypt SAHANA KRANTHI • St. Joseph’s College (Autonomous), Bengaluru, Karnataka, India KANNABIRAN KRISHNAN • School of Biosciences and Technology, Vellore Institute of Technology (Deemed to be University), Vellore, Tamil Nadu, India SIMONE KUBENECK • Laboratory of Microbiology and Bioprocesses, Federal University of FronteiraSul, Erechim, Rio Grande do Sul, Brazil APARANA KUMARI • Marine Biotechnology Laboratory, Vellore Institute of Technology, Vellore, Tamil Nadu, India RANJITH KUMAVATH • Department of Genomic Science, Central University of Kerala, Kasaragod, Kerala, India SELVANATHAN LATHA • Department of Microbiology, School of Life Sciences, Bharathidasan University, Tiruchirappalli, Tamil Nadu, India

xxii

Contributors

WEN-JUN LI • State Key Laboratory of Biocontrol, Guangdong Provincial Key Laboratory of Plant Resources and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), School of Life Sciences, Sun Yat-Sen University, Guangzhou, People’s Republic of China SHUCHENG LIU • College of Food Science and Technology, Guangdong Provincial Key Laboratory of Aquatic Products Processing and Safety, Guangdong Province Engineering Laboratory for Marine Biological Products, Guangdong Provincial Engineering Technology Research Center of Marine Food, Key Laboratory of Advanced Processing of Aquatic Product of Guangdong Higher Education Institution, Guangdong Ocean University, Zhanjiang, China; Collaborative Innovation Center of Seafood Deep Processing, Dalian Polytechnic, Liaoning, China JAYASHANKAR M • Department of Zoology, St. Joseph’s College (Autonomous), Bengaluru, India YUNHAO MA • School of Pharmacy, Lanzhou University, Lanzhou, Gansu, People’s Republic of China ˇ eske´ Budeˇjovice, Czech MARKE´TA MACHO • Faculty of Science, University of South Bohemia, C Republic; Laboratory of Algal Biotechnology, Centre Algatech, Institute of Microbiology of the Czech Academy of Sciences, Trˇebonˇ, Czech Republic INAMULHASAN MADAR • Department of Biomedical Science and Environmental Biology, Kaohsiung Medical University, Kaohsiung, Taiwan S. MALAVIKA • St. Joseph’s College (Autonomous), Bengaluru, Karnataka, India RAFAEL RESENDE MALDONADO • Food Department, Technical College of Campinas, University of Campinas, Campinas, Sa˜o Paulo, Brazil DIPANJAN MANDAL • Division of Pharmacology, Guru Nanak Institute of Pharmaceutical Science and Technology, Kolkata, West Bengal, India MUTHUSELVAM MANICKAM • Department of Biotechnology, Bharathidasan University, Tiruchirappalli, Tamil Nadu, India MUKESH KUMAR MANICKASAMY • School of Life Sciences, Department of Microbiology, Bharathidasan University, Tiruchirappalli, Tamil Nadu, India RADHAKRISHNAN MANIKKAM • Centre for Drug Discovery and Development, Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu, India N. MANOHARAN • Marine Pharmacology and Toxicology Laboratory, Department of Marine Science, Bharathidasan University, Tiruchirappalli, Tamil Nadu, India A. MARTIN PAUL • St. Joseph’s College (Autonomous), Bengaluru, Karnataka, India MOˆNICA ROBERTA MAZALLI • Faculty of Animal Science and Food Engineering, University of Sa˜o Paulo, Pirassununga, Brazil S. J. MEGHANA • Mount Carmel College, Autonomous, Bengaluru, Karnataka, India SHREYANKA S. MOILY • St. Joseph’s College (Autonomous), Bengaluru, Karnataka, India VARSHA N. SWAMY • Department of Microbiology, DayanandaSagar University, Bengaluru, India RAJAGOPAL NARAYANAN • School of Life Sciences, Department of Microbiology, Bharathidasan University, Tiruchirappalli, Tamil Nadu, India T. NARGIS BEGUM • PG & Research Department of Biotechnology, Jamal Mohamed College, Affiliated to Bharathidasan University, Tiruchirappalli, Tamil Nadu, India DEOG-HWAN OH • Department of Food Science and Biotechnology, College of Agriculture and Life Sciences, Kangwon National University, Chuncheon, Gangwon-do, South Korea SHUNMUGIAH KARUTHA PANDIAN • Department of Biotechnology, Science Campus, Alagappa University, Karaikudi, Tamil Nadu, India

Contributors

xxiii

SUSHANT PARAB • Department of Oncology, University of Turin, Turin, Italy; Department of Oncology, Candiolo Cancer Institute FPO–IRCCS, Candiolo, Italy ISABELY FERNANDA PIZARRO • Faculty of Animal Science and Food Engineering, University of Sa˜o Paulo, Pirassununga, Sa˜o Paulo, Brazil P. PRAKASH • Indian Biotrack Research Institute, Thanjavur, Tamil Nadu, India K. PREM ANAND • Marine Biotechnology and Bioproducts Laboratory, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India SRINIVASAN RADHAKRISHNAN • R&D Centre, T-Stanes and Company Ltd, Coimbatore, Tamil Nadu, India VIJAYAKUMAR VISHNU RAJA • Department of Microbiology, School of Life Sciences, Bharathidasan University, Tiruchirappalli, Tamil Nadu, India G. RAJIVGANDHI • State Key Laboratory of Biocontrol, Guangdong Provincial Key Laboratory of Plant Resources and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), School of Life Sciences, Sun Yat-Sen University, Guangzhou, People’s Republic of China; Marine Pharmacology and Toxicology Laboratory, Department of Marine Science, Bharathidasan University, Tiruchirappalli, Tamil Nadu, India G. RAMACHANDRAN • Marine Pharmacology and Toxicology Laboratory, Department of Marine Science, Bharathidasan University, Tiruchirappalli, Tamil Nadu, India MEGANATHAN P. RAMAKODI • CSIR-National Environmental Engineering Research Institute, Hyderabad Zonal Centre, Hyderabad, Telangana, India BALAGURUNATHAN RAMASAMY • Department of Microbiology, Periyar University, Salem, Tamil Nadu, India THIRUMURUGAN RAMASAMY • National Centre for alternatives to Animal Experiments, Bharathidasan University, Tiruchirappalli, Tamil Nadu, India; Department of Animal Science, Bharathidasan University, Tiruchirappalli, Tamil Nadu, India VIJAYAKUMAR RAMASAMY • Department of Microbiology, Government Arts and Science College, Perambalur, Tamil Nadu, India PRIYANKA RAMESH • Department of Biotechnology, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India LOKESH RAVI • Department of Botany, St. Joseph’s College (Autonomous), Bengaluru, Karnataka, India M. CAMIL REX • Department of Botany, St. Joseph’s College (Autonomous), Bengaluru, Karnataka, India SUMANA ROY • Division of Pharmaceutics, Guru Nanak Institute of Pharmaceutical Science and Technology, Kolkata, West Bengal, India MOMNA RUBAB • Department of Food Science and Biotechnology, College of Agriculture and Life Sciences, Kangwon National University, Chuncheon, Gangwon-do, South Korea SUBHASISH SAHA • Laboratory of Algal Biotechnology, Centre Algatech, Institute of Microbiology of the Czech Academy of Sciences, Trˇebonˇ, Czech Republic A. SANKARANARAYANAN • C.G. Bhakta Institute of Biotechnology, Uka Tarsadia University, Surat, Gujarat, India; Department of Life Sciences, Sri Sathya Sai University for Human Excellence, Kalaburagi, Karnataka, India KARTHIKEYAN SARAVANAN • Department of Microbiology, School of Life Sciences, Bharathidasan University, Tiruchirappalli, Tamil Nadu, India I. SARKAR • Bioinformatics Facility, Department of Botany, University of North Bengal, Raja Rammohunpur, West Bengal, India PRIYANKA SARKAR • Wellcome/DBT (Indian Alliance) Lab, Asian Healthcare Foundation, Asian Institute of Gastroenterology, Hyderabad, India

xxiv

Contributors

KUMAR SAURAV • Laboratory of Algal Biotechnology, Centre Algatech, Institute of Microbiology of the Czech Academy of Sciences, Trˇebonˇ, Czech Republic T. SAVITHA • Department of Microbiology, Tiruppur Kumaran College for Women, Tiruppur, Tamil Nadu, India LEENA SEBASTIAN • St. Joseph’s College (Autonomous), Bengaluru, Karnataka, India A. SEN • Bioinformatics Facility, Department of Botany, University of North Bengal, Raja Rammohunpur, West Bengal, India G. SEN • Bioinformatics Facility, Department of Botany, University of North Bengal, Raja Rammohunpur, West Bengal, India ABHIJIT SENGUPTA • Guru Nanak Institute of Pharmaceutical Science and Technology, Kolkata, West Bengal, India FIRDOSH SHAH • C. G. Bhakta Institute of Biotechnology, Faculty of Science, Uka Tarsadia University, Surat, Gujarat, India MARY SHAMYA • Centre for Drug Discovery and Development, Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu, India R. SHANMUGAPRIYA • Department of Botany, A.V.V.M. Sri Pushpam College (Autonomous), (Affiliated to Bharathidasan University), Thanjavur, Tamil Nadu, India A. S. SHIJILA RANI • Department of Microbiology, Marudupandiyar College, (Affiliated to Bharathidasan University), Thanjavur, Tamil Nadu, India H. S. SHISHIRA RAO • St. Joseph’s College (Autonomous), Bengaluru, Karnataka, India S. SHRAVYA • Mount Carmel College, Autonomous, Bengaluru, Karnataka, India SEEMA SIDDHARTHAN • Molecular and Nanomedicine Research Unit, Center for Nanoscience and Nanotechnology, Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu, India GOVINDHAN SIVARANJANI • Department of Microbiology, School of Life Sciences, Bharathidasan University, Tiruchirappalli, Tamil Nadu, India TAI´S ROSAˆNGELA CORREIA SOUZA • Laboratory of Microbiology and Bioprocesses, Federal University of FronteiraSul, Erechim, Rio Grande do Sul, Brazil S. SRIDHARAN • Department of Biotechnology, Bharathidasan University, Tiruchirappalli, Tamil Nadu, India SARANYADEVI SUBBURAJ • Department of Biotechnology, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India RAJA SURESH SELVAPURAM SUDALAIMUTHU • Department of Microbiology, Government Arts and Science College, Perambalur, Tamil Nadu, India GHAZALA SULTAN • Department of Computer Science, Faculty of Science, Aligarh Muslim University, Aligarh, Uttar Pradesh, India MENGZE SUN • School of Pharmacy, Lanzhou University, Lanzhou, Gansu, People’s Republic of China K. SUTHINDHIRAN • Marine Biotechnology and Bioproducts Laboratory, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India CAROLINE MERCY ANDREW SWAMIDOSS • Department of Chemistry, Dr. M.G.R. Educational and Research Institute, Chennai, Tamil Nadu, India ˇ eske´ Budeˇjovice, Czech JIHEN THABET • Faculty of Science, University of South Bohemia, C Republic; Laboratory of Algal Biotechnology, Centre Algatech, Institute of Microbiology of the Czech Academy of Sciences, Trˇebonˇ, Czech Republic N. THAJUDDIN • Department of Microbiology, School of Life Science, Bharathidasan University, Tiruchirappalli, Tamil Nadu, India

Contributors

xxv

SHANMUGASUNDARAM THANGAVEL • School of Life Sciences, Defence Research Development Organization, Bharathiar University Campus, Coimbatore, Tamil Nadu, India; DRDO, Bharathiar University Centre for Life Sciences, Coimbatore, Tamil Nadu, India S. THEJASWINI • Government Science College, Bengaluru, Karnataka, India SOMASUNDARAM THIRUGNANASAMBANDHAM • CAS in Marine Biology, Annamalai University, Parangipettai, Tamil Nadu, India MUTHU KUMAR THIRUNAVUKKARASU • Department of Biotechnology, School of Bio Sciences and Technology, Vellore, Tamil Nadu, India HELEN TREICHEL • Laboratory of Microbiology and Bioprocesses, Federal University of FronteiraSul, Erechim, Rio Grande do Sul, Brazil CHARLES SANTHANARAJU VAIRAPPAN • Laboratory of Natural Products Chemistry, Institute for Tropical Biology and Conservation, Universiti Malaysia Sabah, Sabah, Malaysia MOHAN VARADHARAJAN • Division of Forest Protection, Forest Pathology Lab., Institute of Forest Genetics and Tree Breeding, Coimbatore, Tamil Nadu, India S. VEERAMANI • Research and Development Department, Biovedic Nutraceuticals, Bangalore, Karnataka, India M. VEERAPAGU • Department of Microbiology, Thanthai Hans Roever College (Autonomous), Perambalur, Tamil Nadu, India SHANTHI VEERAPPAPILLAI • Department of Biotechnology, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India GOPIKRISHNAN VENUGOPAL • Centre for Drug Discovery and Development, Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu, India ADITI VIJAYAN • Paris Science and Letters University, Paris, France R. T. V. VIMALA • Department of Biotechnology, Bharathidasan University, Tiruchirappalli, Tamil Nadu, India SHUAI WEI • College of Food Science and Technology, Guangdong Provincial Key Laboratory of Aquatic Products Processing and Safety, Guangdong Province Engineering Laboratory for Marine Biological Products, Guangdong Provincial Engineering Technology Research Center of Marine Food, Key Laboratory of Advanced, Guangdong Ocean University, Zhanjiang, China; Collaborative Innovation Center of Seafood Deep Processing, Dalian Polytechnic University, Liaoning, China RENTAO ZHANG • School of Pharmacy, Lanzhou University, Lanzhou, Gansu, People’s Republic of China ZHONGKUN ZHOU • School of Pharmacy, Lanzhou University, Lanzhou, Gansu, People’s Republic of China

Chapter 1 Isolation of Actinobacteria from Soil and Marine Sediment Samples T. Savitha, Ashraf Khalifa, and A. Sankaranarayanan Abstract Actinobacteria (Actinomycetes) are gram-positive, facultative anaerobic fungus-like filamentous bacteria. They are extensively distributed in the natural habitat and entailed in different biological and metabolic processes, such as useful for producing extracellular enzymes. In addition, almost 90% of Actinomycetes genera have been isolated from soil, which are innocuous for different fields: industrial and pharmaceutical sectors. Besides, Actinomycetes produce distinctive pigments on the media which are red, green, yellow, and black in color. Based on the geographical variations in altitude and soil type and their contents, there is a possibility of observing similar microflora, which conjectures to vary the distribution of antimicrobial producing Actinomycetes. Key words Filamentous bacteria, Extracellular enzymes, Pigments, Microflora

1

Introduction Actinomycetes are filamentous bacteria which grow like fungi. They are mainly aerobic and widespread in soil. The main importance of actinomycetes relies on their ability to produce antibiotics. Many of the well known antibiotics are streptomycin, gentamycin, rifamycin and erythromycin. Soil is the important reservoir of most actinobacterial species. Streptomyces is the predominant genera and Actinomadura, Nocardia, Rhodococcus, Arthrobacter and Micromonospora are common genera found in the soil sample. They are ubiquitous in the marine environment, playing an important ecological role in the nutrient cycling and production of novel natural products with pharmaceutical applications. Marine sediments are the richest source for the isolation of various actinobacterial genera and species are isolated from various marine samples like sediments, water, coral, sponges, mangroves, seaweed, and fishes. Among the various strategies for isolation, three different

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_1, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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Isolation methods of Actinobacteria

Membrane filter technique

Serial dilution method

Sprinkler method

Fig. 1 Different isolation methods of Actinobacteria from soil sample

methods can be used to isolate Actinobacteria from the soil sample (Fig. 1).

2

Materials Required

2.1 Isolation of Actinobacteria from Soil Sample

2.2 Isolation of Actinobacteria from Marine Sediment Sample

l

Soil sample.

l

Conical flask—250 ml.

l

Test tubes—15 ml.

l

Micropipettes.

l

Starch casein agar (SCA) plates (starch—10 g, K2HPO4—2 g, KNO3—2 g, casein—0.3 g, MgSO4.7H2O—0.05 g, CaCO3— 0.02 g, FeSO4.7H2O—0.01 g, agar—15 g, distilled water— 1000 ml, pH —7.0).

l

Luria Bertani medium plates (starch—10 g, peptone—2.0 g, yeast extract—4.0 g, Agar—18.0 g, distilled water—1000 ml, pH 7.0).

l

Starch Nitrate agar plates (soluble starch—20.0 g, K2HPO4— 1.0 g, KNO3—2.0 g, MgSO4—0.5 g, CaCO3—3.0 g, NaCl— 100 g, FeSO4—0.1 g, MnCl2—0.1 g, ZnSO4—0.1 g, distilled water—100 ml, pH 7).

l

L-rod.

l

Incubator.

l

Distilled water.

l

Membrane filter.

l

Sterile spatula.

l

Sterile plastic bags/bottles.

l

Sediment sample.

l

Conical flask.

l

Test tubes.

l

Micropipettes.

l

SCA plates (as mentioned above).

Isolation of Actinobacteria from Soil and Marine Sediment Samples

3

3

l

Kuster’s agar plates (glycerol—10 g, casein—0.3 g, KNO3—2 g, K2HPO4—2 g, soluble starch—0.5 g, asparagine—0.1 g, FeSO4.7H2O—0.01 g, CaCO3—0.02 g, MgSO4.7H2O—0.05 g, Agar—15 g, filtered sea water—1000 ml, pH 7).

l

Actinomycetes isolation agar plates (sodium caseinate—2 g, L-asparagine—0.1 g, sodium propionate—4 g, dipotassium phosphate—0.5 g, magnesium sulfate—0.1 g, ferrous sulfate— 0.001 g, agar—15 g, distilled water—1000 ml, pH 8).

l

L-rod.

l

Incubator.

l

Glycerol broth (20%).

Methodology

3.1 Isolation of Actinobacteria from Soil Sample 3.1.1 Pretreatment of Sample

1. Select the sampling area and record the information’s like area of collection, district, state, specific ecosystem and its latitude and longitude. 2. Clean the sample collection place to remove unwanted litters on the surface. 3. Collect the required quantity of soil sample (50–500 g) from 8 to 10 cm depth of the soil by using sterile spatula. 4. Transfer the collected samples to the sterile glass bottles or plastic cover shade dry at room temperature for a week. 5. Then the pretreated sample is subject to further analysis.

3.1.2 Serial Dilution Technique

1. Place 1gram of pretreated soil sample in conical flask having 99 ml sterile distilled water (10 2). 2. Vortex the sample for 10 min to get a stock solution. 3. Then serial dilution is to be carried out by transferring 1 ml of the stock solution to a second test tube with 9 ml distilled water (10 3). 4. The above steps to be followed consequently up to get 10 dilutions [1].

8

5. Then plating can be done using suitable media which is incorporated with suitable antibacterial and antifungal agent. 6. Transfer the respective dilutions (0.1 ml) to the prepared plates by spread plate method. Maintain triplicates. One uninoculated plate will serve as control. 7. Incubate all the plates at 28  C for 5—25 days [2]. 8. Following incubation, colonies are isolated.

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3.1.3 Membrane Filter Technique

1. In this method, prepare a suitable agar medium such as starch casein by autoclaving at 121  C for 15 min. 2. After cooling of the medium to 45  C, it is poured into petri dishes and allowed to settle. Place sterile membrane filters at the centre of plates. 3. Sprinkle the soil sample to be tested on to the membrane filters [3]. 4. Incubate the plates for 4 days; subsequently, the membrane filters are removed. 5. Further incubate the plates until the Actinomycetes become visible after which subculturing can be done. 6. This method is preferred due to its selectivity of Actinomycetes. 7. It is based on the inability of other microbes to produce mycelia that can penetrate the membrane filter [4].

3.1.4 Sprinkler Method

1. In sprinkling method, add the pretreated soil sample directly to the prepared culture medium [5]. 2. The plates are given time to allow contact between the soil particles and the medium. 3. One uninoculated plate will serve as control. 4. Incubate the plates are at 28  C for 5–25 days [6]. 5. Following incubation, observe all the plates for powdery or leathery colonies and can be enumerated.

3.2 Isolation of Actinobacteria from Marine Sediment Sample

1. Select the sampling area such as estuaries, mangroves, or intertidal spots in the marine region. 2. Collect nearly 50–500 g of the sediment samples at 4 cm below the sea water level. 3. Transfer the samples into the sterile plastic bag and transport to the laboratory. 4. Place 10 g of sample into sterile petri plate and dry in a laminar flow chamber for 24 h. 5. Grind the sample gently with mortar and pestle. 6. Prepare SCA plates by using artificial sea water supplemented with suitable antibiotic. 7. Press the sample into a sterile foam plug with 14 mm diameter, and inoculate into SCA plates by stamping. 8. Stamp eight to nine times in a circular fashion to give a serial dilution effect. 9. One uninoculated plate will serve as control. 10. Incubate all the plates at 28  C for 2–6 weeks.

Isolation of Actinobacteria from Soil and Marine Sediment Samples

5

11. Consider the colonies with a tough leathery texture, dry or folded appearance, and branching filaments with or without aerial hyphae.

References 1. Roitch MC, Magiri E, Bii C, Maina N (2017) Bioprospecting for broad spectrum antibiotic producing Actinomycetes isolated from virgin soils in Kericho country, Kenya. Adv Microbiol 7:56–70 2. Kadri SK, Varla NS, Vidavalur S (2014) Screening and isolation of antagonistic Actinobacteria associated with marine sponges from Indian coast. J Microb Biochem Technol S8:003 3. Samer MA (2016) Isolation and identification of Actinomycetes with biosurfactant activity. Al-Muthanna J Pur Sci 3:68–74

4. Jeyaraman T (2015) Isolation, screening and characterization of potent marine Stereptomyces sp.pm105 against antibiotic resistant pathogens. Asian J Pharm Clin Res 8:439–443 5. Aya N, Shams TK, Tomohiko TM, Kazuo S (2011) Streptomyces aomiensis sp.nov, isolated from a soil sample using the membrane filter method. Int J Syst Evol Microbiol 61:947–950 6. Orooba MF, Ali AS, Khansa MY, Gires U, Asmat A (2017) Isolation, screening and antibiotic profiling of marine Actinomycetes extracts from the coastal of Peninsular Malaysia. Int J Chem Tech Res 3:212–224

Chapter 2 Isolation of Actinobacteria from Water Sources Tamalika Chakraborty, Sumana Roy, Dipanjan Mandal, Jeenatara Begum, and Abhijit Sengupta Abstract The Actinobacteria comprise a well-defined clade of bacteria with a high GC content. They are widespread in various ranges of niches. They are present in a diversity of habitats which includes rhizosphere, soil, marine, and freshwater systems. Several Actinobacteria are human and animal pathogens and few of them are pathogenic to plants. Few genera such as Streptomyces and Micromonospora are known for their prolific production of different types of bioactive metabolites, including enzymes, enzyme inhibitors, antibiotics, signaling molecules, and immunomodulators. The present protocol involves collection of Actinobacteria from various freshwater sources like pond and lakes followed by their pretreatment to retard the growth of slime-forming bacteria. The pretreated sample is further diluted and inoculated into a suitable medium followed by enumeration of Actinobacteria. The isolated colonies of actinobacteria are further characterized following Bergey’s Manual of bacteriology. The strains are identified by 16S r-RNA sequencing. The actinobacteria isolated are further tested for production of bioactive metabolites and further antibacterial and antifungal activity of those metabolites is determined. Key words Diversity, Immunomodulators, Pretreatment, Enumeration, 16S r-RNA sequencing

1

Introduction Actinobacteria are a unicellular gram-positive group of bacteria. They content high amount of guanine and cytosine in their DNA [1]. They do not have any distinct cell wall, but they can produce a mycelium which is nonseptated and slender [1, 2]. Actinobacteria obtained from soil, fresh water and of marine origin play a very important role in decomposition of cellulose and chitin, mainly different organic materials. They have the capacity of replenishing the supply of nutrition in the soil and play an important part in humus formation [3]. A wide variety of secondary metabolites with high pharmacological and commercial interest have been obtained from actinobacteria. Actinobacteria are widely used in the development of antibiotics. They act as a promising source of important enzymes on an industrial

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_2, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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scale [4]. Different genera of Actinobacteria can be used for the development of different products such as herbicides, pigments, vitamins, phytohormones, larvicides, and surfactants [5, 6]. However, some rare genera of Actinobacteria are unexplored and might have some biotechnological and industrial potential. The commercial value of Actinobacteria explore the requirement of Actinobacteria from fresh water [7] (Table 1).

2

Materials

2.1 Medium for Isolating Actinobacteria

YIM 14 improved Czapek medium. Sucrose 20 g. NaNO3 2 g. K2HPO4 1 g. MgSO4 7H2O 0.5 g. KCl 0.5 g. FeSO4 7H2O 0.01 g. Vitamin mixture 3.7 mg. Agar 25 g. pH 7.2. YIM 17 glycerol asparagine medium. L-asparagine 1 g. Glycerol 10 g. K2HPO4 1 g. Vitamin mixture 3.7 mg. trace salt 1 ml. Agar 20 g. pH 7.2–7.4. YIM 21 oatmeal medium. Oatmeal 20 g (20 g of Oatmeal is taken and cooked in 1000 ml of distilled water for 20 min, the content is filtered through cheesecloth and volume made up to 1000 ml). Vitamin mixture 3.7 mg. Trace salt 1 ml. Agar 20 g. pH 7.2. Trace elements.

Isolation of Actinobacteria from Water Sources

9

Table 1 Number of Actinobacteria isolated from water sample Total Actinobacteria count in water samples(CFU/ml of water) Water sample number

YIM14

YIM 17

in YIM 21

1

2  10

6

16  10

4  106

2

3  106

5  106

4  105

3

12  107

3  107

4

14  10

7

11  10

2  107

5

16  107

7  107

4  107

6

6  105 7

FeSO4·7H2O 0.1 g. MnCl2 0.1 g. ZnSO4·7H2O 0.1 g. 1 mg penicillin and 50 mg potassium dichromate are added to the isolation medium. 2.2 Chemicals for Biochemical Test

Crystal Violet, Gram’s iodine, alcohol, and Safranin. TMPD (N, N, N0 , N0 -tetramethyl-p-phenylenediamine). DMSO (dimethyl sulfoxide). H2O2 (hydrogen peroxide). Peptonisation Medium. Skimmed milk powder 200 g. CaCO3 0.2 g. Starch Agar.

2.3

Glassware

Petri plates. Screw-capped tubes. Test tubes. Measuring cylinder. Conical flask. Glass rod.

3

Methods

3.1 Collection of Water Sample

Actinobacteria are usually present as saprophytes in different natural habitats, including soil, ocean, lake, plant, and animal. Water is a rich source of Actinobacteria. The type of Actinobacteria is usually influenced by primary ecological factors such as temperature, pH, aeration, nutrient content, salinity, and moisture.

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Test samples are collected from a freshwater source in Barasat, North 24 Parganas in a sterile autoclaved glass bottle. 3.2 Pretreatment of Water Sample

Pretreatment is very important for selective isolation of Actinobacteria because they grow slower than other bacteria and fungi. Pretreatment aims at eliminating unwanted microorganisms, selecting the target microorganism. It will reduce bacterial population from water sample. Treat the water samples with ultrasonic waves at 40  C.

3.2.1 Pre-treatment with Chemicals

Actinobacteria with differential resistance to chemicals can be pretreated with benzethonium chloride, chlorhexidine gluconate, SDS, and phenol. Treating the water samples with these chemicals for 30 min at 30  C can kill various other gram-negative bacteria, bacilli with endospores, and Pseudomonas.

3.3 Basic Principle of Designing Medium

Many factors need to be considered for designing selective isolation media such as the goals for isolation, the taxonomic hierarchy targeted, components of medium and inhibitors. The selective medium must be designed by taking information of Taxonomic and Phenotypic Database.

3.4 Medium for Isolation of Actinobacteria from Fresh Water

YIM 14 improved Czapek medium. YIM 17 glycerol asparagine medium. YIM 21 oatmeal medium. 1. Prepare the 200 ml of YIM 14 improved Czapek YIM 17 glycerol asparagine, YIM 21 oatmeal medium in 500 m conical flask and sterilize in autoclave at 121  C for 15 min, 15 lb./sq. in. 2. Serially dilute the collected water sample in 0.9% saline from 101 to 109 dilution. 3. Take 0.1 ml aliquot from 102 to 103 dilution and inoculated in YIM 14 improved Czapek agar, YIM 17 glycerol asparagine agar, YIM 21 oatmeal agar plates by spread plate technique. 4. Incubate the inoculated plates in moist chamber for 7 days at 55  C. 5. After incubation period, examine and count the total actinobacterial colonies in each plate and calculate the total actinobacterial population in each water sample. 6. Characterize the actinobacterial isolates from water sample by pick the pure isolates and purify by streak plated methods in fresh Czapek agar, YIM 17 glycerol asparagine agar, and YIM 21 oatmeal agar plates and slants.

Isolation of Actinobacteria from Water Sources

3.5 Identification of Actinobacteria by Biochemical Tests

l

1% (wt/vol) solution of TMPD is certified grade DMSO (dimethyl sulfoxide) is prepared.

l

Soak a filter paper in 1% Kovac’s reagent and let it dry; once dry, an isolated colony is collected from the plate and rubbed across the filter paper.

l

The color change is observed. The change of color from pink to scarlet in 15 s proves a positive test.

l

A volume of 0.2 ml of 3–10% H2O2 is taken in a screwcapped tube.

l

Using a platinum wire, a loopful of culture is taken and rubbed onto the walls of the screw-capped tubes.

l

Release of effervescence due to evolution of nascent oxygen reveals a positive result.

l

Starch agar plate is prepared.

l

The isolates are taken and streaked onto the plates.

l

The plates are incubated for 24 h.

l

Iodine is added on to the plates for the observation of starch utilization.

l

Actinobacteria can produce protease and this test determines the ability of Actinobacteria to produce protease.

l

Milk coagulation and peptonization medium is prepared using the following medium, Skimmed milk powder 200 g, CaCO3 0.2 g taken per liter of distilled water.

l

Five milliliters of the medium is further dispensed into narrow tubes, loopful of inoculum is added and incubated for 5, 10, 20, and 30 days, respectively.

l

Milk solidification reveals a positive test for actinobacteria.

3.5.1 Oxidase Test

3.5.2 Catalase Test

3.5.3 Starch Utilization Test

3.5.4 Coagulation and Peptonization of Milk

4

Results

4.1 Isolation of Actinobacteria (Tables 2 and 3)

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Table 2 Colony characteristics of Actinobacteria isolated from water sample Actinobacterial isolates

Colony colours of aerial mycelium

Colony colours of vegetative mycelium

Isolates genus

1

White

Yellow

Streptomyces sp.

2

Cream

White

Micromonospora sp.

3

Yellow

Cream

Intrasporangium sp.

4

Brown

Brown

Saccharopolyspora sp.

5

Gray

Gray

Streptosporangium sp.

6

Bluish

Reddish

Rhodococcus sp.

7

Pinkish

–

Saccharomonospora sp.

Table 3 Biochemical Test for Characterization of Actinobacteria No.

Biochemical tests

Result

1.

Gram staining

Positive

2.

Oxidase test

Positive

3.

Catalase test

Positive

4.

Starch utilization test

Positive

5.

Coagulation and peptonization of milk

Positive

References 1. Makkar NS, Cross T (1982) Actinoplanetes in soil and on plant litter from freshwater habitats. J Appl Bacteriol 52(2):209–218 2. Nithya K, Muthukumar C, Duraipandiyan V, Dhanasekaran D, Thajuddin N (2015) Diversity and antimicrobial potential of culturable Actinobacteria from desert soils of Saudi Arabia. J Pharm Sci Res 7(3):117–122 3. Dhanasekaran D, Panneerselvam A, Thajuddin N, Chandralekha S (2014) Isolation, characterization of antibacterial methyl substituted β-lactam compound from Streptomyces noursei DPTD21 in saltpan soil, India. JBAPN 4(2):71–88 4. Dhanasekaran D, Sakthi V, Thajuddin N, Panneerselvam A (2010) Preliminary evaluation of

Anopheles mosquito larvicidal efficacy of mangrove Actinobacteria. Int J Appl Biol Pharm Technol 1(2):374–381 5. Dhanasekaran D, Ambika K, Thajuddin N, Panneerselvam A (2012) Allelopathic effect of Actinobacterial isolates against selected weeds. Arch Phytopathol Plant Protect 45(5):505–521 6. Oskay AM, Usame T, Cem A (2005) Antibacterial activity of some actinomycetes isolated from farming soils of Turkey. Afr J Biotechnol 3(9):441–446 7. Tan H, Deng Z, Cao L (2009) Isolation and characterization of actinomycetes from healthy goat faeces. Lett Appl Microbiol 49(2):248–253

Chapter 3 Isolation of Actinobacteria from Deep Sea Aparana Kumari and K. V. Bhaskara Rao Abstract Actinobacteria are free living and are found in freshwater, soil, and marine environment. They are grampositive bacteria and having a high GC content (guanine–cytosine) in their genetic material. Actinobacteria are isolated and identified by morphological, physiological, and biochemical properties. Marine actinobacteria are useful for production of novel enzymes and drug discovery. Marine environment can be a useful source of enzymatic diversity with novel primary and secondary metabolites and for exploration of new species of marine actinobacteria. New species of actinobacteria are new possibilities for bioactive compounds and enzymes used in drug discovery. Actinobacteria are also used for discovery of antibiotics. In this chapter, we will discuss several isolation media and the protocol for isolation of actinobacteria from deep sea samples. Key words Marine, Actinobacteria, Species, Isolation, Starch casein agar

1

Introduction The deep sea ecosystem is the biggest aquatic environment and is considered as an important source of biodiversity [1]. Sea ecosystems have a distinctive diversity of microbes including marine actinomycetes [2]. Actinobacteria are present in different natural habitats. The deep sea zone is full of microbes including actinobacteria that has beneficial role in degradation of dead plankton, plants, animals, and pollutants. Some species of actinobacteria may cause disease rarely. Apart from this, these actinobacteria also occupy a great part in the marine zone [3, 4]. Actinobacteria are isolated by culturing, serial dilution, and plating technique. Nutrient agar, tryptic soy agar, Luria–Bertani media, tap water yeast extract media (TWYE), and starch casein agar are used for serial dilution and plating [5]. There are 89 marine actinobacteria isolated from Kanyakumari, Tamil Nadu, India for study of protease inhibition activity against trypsin [6]. Deep sea actinobacteria from marine soil samples are collected from Kothapatnam Beach, Andhra Pradesh for study of biosurfactant production [7]. The present study

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_3, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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Table 1 Marine actinobacteria from different zones of deep sea Actinobacterial isolates No. and species

Deep sea location

Type of sample

1.

A1 (Streptomyces sp.)

Marina Beach, Chennai

Marine sediments [8]

2.

A4 (Streptomyces sp.)

Marina Beach, Chennai

Marine sediments [8]

3.

SDS3 (Streptomyces sp.) Chennai Sea coast, Tamil Nadu, India Marine sediments [9]

4.

A5 (Streptomyces sp.)

Marina Beach, Chennai

Reference

Marine sediments [8]

focuses on the protocol of isolation methods of marine actinobacteria from different zones of deep sea (Table 1) and on their beneficial role.

2

Materials 1. Deep sea sediment is collected through coring devices or surface samplers. 2. Deep sea mud is collected through dredges and benthic grabs.

2.1 Isolation Media for Actinobacteria

1. Starch casein agar (SCA). 2. Yeast malt agar (ISP2). 3. Oatmeal agar. 4. Emerson agar. 5. Zobell marine agar (ZMA). 6. Basal media. 7. Asparagine agar. 8. Trace salts solution (Table 2).

3

Methods

3.1 Collection of Sample from Deep Sea

1. The deep sea samples are collected from Chennai, Tamil Nadu, India. 2. Sediments and mud samples are collected using sterile tubes. 3. The samples are processed by using the following different methods [10]. Method 1

1. Dry the sediment samples overnight in a laminar air flow chamber.

Isolation of Actinobacteria from Deep Sea

15

Table 2 Components of trace salts solution Components

Quantity

Ammonium sulfate

2.64 g

Potassium dihydrogen phosphate (anhydrous)

2.38 g

Dipotassium hydrogen phosphate (3H2O)

5.65 g

Magnesium sulfate (7H2O

1g

Trace salts

1 mL

Distilled water

1L

2. Grind the resulting clumps with mortar and pestle. 3. Place the sediment on the surface of different agar plates. Method 2

1. Dilute dried sediment in sterile seawater. 2. Dilute sample with 3 ml of seawater and mixed samples by vortexing for few minutes and perform serial dilution up to the 109 dilution. 3. Inoculate the diluted samples on the surface of an agar plate by spread plate method with a sterile glass rod. 4. Inoculate the plates at 28  C for 7–10 days. 5. Examine and count the total actinobacterial colonies in the plate. Method 3

1. Mix sediment with 3 ml of sterile seawater. 2. Heat the mixed sediments to 55  C for 6 min. 3. Inoculate 100 μl of the suspension onto different agar plates. Method 4

1. Freeze wet sediment at

20  C for 24 h.

2. Dilute in sterile seawater (1:3, 1:120 depending on particle size). 3. Inoculate 100 μl of the suspension onto different agar plates.

4

Observation 1. Actinobacteria are gram-positive, free-living, saprophytic and form long multinucleate filaments or hyphae to produce mycelium.

16

Aparana Kumari and K. V. Bhaskara Rao

1

2

3

Fig. 1 Diagrammatic representation of isolation of actinobacteria from deep sea. 1. Actinomycete isolates on starch casein agar. 2. Purified isolated colonies on SCA (starch casein agar) medium. 3. Spore chain morphology of isolates using SEM (scanning electron microscope)

2. Actinomycetes account for almost 10% of the microbes found in aquatic organic bulk. 3. They can form spores on hyphae. 4. They are traditionally transitional forms between bacteria and fungi as they are forming mycelium. 5. They are thin, with muramic acid in their cell wall, like bacteria, which is susceptible to the antibacterial antibiotics. 6. Microscopic study is used for morphological characteristics. 7. Detect the chains of spores with open petri dishes under the microscope. 8. Observe spore morphology under SEM (scanning electron microscope) (Fig. 1). References 1. Zhao XQ (2011) Genome-based studies of marine microorganisms to maximize the diversity of natural products discovery for medical treatments. Evid Based Complement Alternat Med 2011:384572. https://doi.org/10. 1155/2011/384572 2. Felczykowska A, Bloch SK, Nejman-FalenczykB, Baranska S (2012) Metagenomic approach in the investigation of new bioactive compounds in the marine environment. Acta Biochim Pol 59:501–505 3. Donadio S, Maffioli S, Monciardini P, Sosio M, Jabes D (2010) Antibiotic discovery in the twentyfirst century: current trends and future perspectives. J Antibiot 63:340–423

4. Meena B, Rajan LA, Vinithkumar NV, Kirubagaran R (2013) Novel marine actinobacteria from emerald Andaman & Nicobar Islands: a prospective source for industrial and pharmaceutical byproducts. BMC Microbiol 13(1):1 5. Vollmers J, Wiegand S, Kaster AK (2017) Comparing and evaluating metagenome assembly tools from a microbiologist’s perspective- not only size matters. PLoS One 12: e016966 6. Sreedharan V, Rao KVB (2017) Efficacy of protease inhibitor from marine Streptomyces sp. VITBVK2 against Leishmania donovanieAn in vitro study. Exp Parasitol 174:45–51. https://doi.org/10.1016/j.exppara.2017.02. 007

Isolation of Actinobacteria from Deep Sea 7. Shubhrasekhar C, Supriya M, Karthik L, Gaurav K, Bhaskara Rao KV (2013) Isolation, characterization and application of biosurfactant produced by marine actinobacteria isolated from saltpan soil from coastal area of Andhra Pradesh, India. Res J Biotechnol 8 (1):18–25 8. Kamarudheen N, George CS, Pathak S, George SL, Bhaskara Rao KV (2015) Antagonistic activity of marine Streptomyces sp. on fish pathogenic Vibrio species isolated from

17

aquatic environment. Res J Pharm Tech 8 (11):1529–1533 9. Nair S, Nandi D, Nandi S, Veena S, Bhaskara Rao KV (2015) Screening and identification of keratinase producing marine actinobacteria from Chennai Sea coast. RJPBCS 6 (4):828–833 10. Karthik L, Kumar G, Bhaskara Rao KV (2010) Diversity of marine actinomycetes from Nicobar marine sediments and its antifungal activity. Int J Pharm Pharm Sci 2(1):199–203

Chapter 4 Isolation of Actinobacteria from Estuaries Ashraf Khalifa and A. Sankaranarayanan Abstract Actinomyces an aerobic, gram-positive, spore-forming bacteria, belonging to the order Actinomycetales with aerial mycelium growth. They are the most abundant organisms in the soil and have been reported in different habitats including aquatic habitats, especially marine, estuarine, and wetland. The Saprophytic behavior and with the special feature of the production of the diversified bioactive materials, need the searching of new Actinobacteria from the estuarine and other habitats in relation with the threatening multidrug -resistant (MDR) pathogenic microbes. Basically estuarine environment which yielded a hostile environment enriched. Key words Estuary, Actinobacteria, Diversity

1

Introduction Being the transition zone between river and marine environments, an estuary is a unique ecosystem. In general, estuaries are productive ecosystems with a rich biodiversity. Besides, estuaries are rich in nutrients, hence supporting a variety of life. The research papers [1–3] revealed the marine and associated environments having various features, as described in Fig. 1 for the reason of rich actinobacterial diversity. Research has revealed Actinobacteria as a potential group of microbes with 78% of G + C contents capable to producing biotechnologically valuable products [4]. Estuary is an ideal environment that harbors various biotic sources. Marine and associate environment considered the large resources for the secondary metabolite production of Actinobacteria [5–8] and still the unusual and unexplored habitats has to be investigated for the promising Actinobacteria isolates [1]. Actinobacteria are an ecologically important and highly underexplored bacterial group. They play a vital role in the degradation of xenobiotic compounds including pollutants such as hydrocarbons

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_4, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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Ashraf Khalifa and A. Sankaranarayanan

Marine / Estuary

Increased diversity

Rich Secondary

Present in sediment /

Production of

metabolites

deep sea environment

novel bioactive compounds

Fig. 1 Marine/Estuary chart

and chlorinated compounds [9], polychlorinated biphenyl polluted soil samples [10].

2

3

Materials l

Estuarine sediment sample.

l

Conical flask, 250 ml.

l

Test tubes, 15 ml.

l

Micropipettes.

l

Starch casein agar (SCA) plates (Starch—10 g, K2HPO4—2 g, KNO3—2 g, Casein—0.3 g, MgSO4.7H2O—0.05 g, CaCO3— 0.02 g, FeSO4.7H2O—0.01 g, Agar—15 g, Distilled water— 1000 ml, pH 7.0).

l

Nystatin.

l

Nalidixic acid.

l

L-rod.

l

Incubator.

l

Distilled water.

l

Sterile spatula.

l

Sterile plastic bags/bottles.

Method

3.1 Collection of Estuary Samples [8, 11]

1. Collect the estuary sediment sample from different locations and transfer into sterile polyurethane bags. 2. Add 1 g of sediment sample in 10 ml of sterile distilled water and stir for 15 min, and allow the suspension to stand for 30 min and separate the supernatant. Then enrich the sample as per the specified method [12]. 3. Then transfer the supernatant into a conical flask containing sterile starch casein broth and incubate it at 28  2  C for 7 days in static condition with intermittent shaking.

Isolation of Actinobacteria from Estuaries

21

4. Spread 0.1 ml of enriched media on SCA medium (supplemented with nystatin 10 μg/ ml and nalidixic acid 25 μg/ml) and keep the plates for incubation at 28  2  C for 7–10 days. 5. Observe the colonies. 6. Segregate the isolated Actinobacteria based on morphology, labeled with number in SCA slants for further studies.

References 1. Yu J, Zhang L, Liu Q, Qi X, Ji Y, Kim BS (2015) Isolation and characterization of Actinobacteria from Yalujiang coastal wetland, North China. Asian Pac J Trop Biomed 5 (7):555–560 2. Ward AC, Bora N (2006) Diversity and biogeography of marine Actinobacteria. Curr Opin Microbiol 9:279–286 3. Wilson ZE, Brimble MA (2009) Molecules derived from the extremes of life. Nat Prod Rep 66:44–71. https://doi.org/10.1039/ b800164m 4. Sirisha B, Haritha R, Jagan Mohan YSYV, Siva Kumar K, Ramana T (2013) Bioactive compound from marine actinomycetes isolated from the sediment of Bay of Bengal. Int J Pharma Chem Bio Sci 2:257e264 5. Jiang Z, Tuo L, Huang D, Osterman IA, Tyurin AP, Liu S, Lukyanov DA, Seglev PV, Dontsova OA, Korshun VA, Li F, C-h S (2018) Diversity, novelty and antimicrobial activity of endophytic actinobacteria from mangrove plants in Beilun Estuary National Nature Reserve of Guangxi, China. Front Microbiol 9:868. https://doi.org/10.3389/fmicb. 2018.00868 6. Li F, Liu S, Lu Q, Zheng H, Osterman IA, Lukyanov DA, Serglev PV, Liu S, Ye J, Huang D, Sun C (2019) Studies on antibacterial activity and diversity of cultivable actinobacteria isolated from mangrove soil in Futian and Maoweihai of China. Evid Based Complement Alternat Med 2019:1–11. https://doi.org/10. 1155/2019/3476567

7. Arumugam T, Senthil Kumar P, Kameshwar R, Prapanchana K (2017) Screening of novel Actinobacteria and characterization of the potential isolates from mangrove sediment of south coastal India. Microb Pathog 107:225–233. https://doi.org/10.1016/j.micpath.2017.03. 035 8. Sivasankar P, Manivasagam P, Vijayanand P, Sivakumar K, Sugesh S, Poongodi S, Maharani V, Vijayalakshmi S, Balasubramanian T (2013) Antibacterial and brine shrimp lethality effect of marine actinobacterium Streptomyces sp. CAS 72 against human pathogenic bacteria. Asian Pac J Trop Dis 3(4):286–293 9. Piza FF, Prado PI, Manfio GP (2004) Investigation of bacterial diversity in Brazilian tropical estuarine sediment reveals high actinobacterial diversity. Antonie Van Leeuwenhoek 86:317–328 10. Nogales B, Moore ERB, Enrique L-B, Ramon R-M, Amann R, Timmis KN (2001) Combined use of 16S ribosomal DNA and 16S rRNA to study the bacterial community of polychlorinated biphenyl-polluted soil. Appl Environ Microbiol 67(4):1874–1884 11. Dhanasekaran D, Selvamani S, Pannerselvam A, Thajuddin N (2009) Isolation and characterization of Actinomycetes in Vellar Estuary, Annagkoil, Tamil Nadu. Afr J Biotechnol 8(17):4159–4162 12. Shirling EB, Gottlieb D (1966) Methods for characterization of Streptomyces species. Int J Syst Bacteriol 16(3):313–340

Chapter 5 Isolation of Actinobacteria from Sponges Neethu Kamarudheen and Kokati Venkata Bhaskara Rao Abstract Amidst plethora of marine microbes, actinobacteria, the prolific antibiotic producers, play a very substantial role. Being active endosymbionts of sponges, actinobacteria are crucial in providing several important secondary metabolites of industrial and pharmacological significance. Sponges, the oldest multicellular sessile feeders, can hold large volumes of actinobacteria and are one of the largest habitats for isolation following marine water. In the chapter, we discuss the isolation technique, several isolation media, and analysis of actinobacteria from sponges. Key words Sponges, Endosymbionts, Actinobacteria, Marine, Isolation

1

Introduction Sponges, one of the oldest known aquatic organisms, serve as an integral part of aquatic ecosystems. The flowing water brings in a lot of nourishment and many floating microbes. Besides absorbing and storing nutrients, sponges nourish and harbor a large number of microbial communities within their mesophyll region [1]. Sponges can accommodate microbial communities up to an extent of around 40 percentage of its volume. In most cases they remain associated until disturbed by environmental factors [2]. High microbial abundance (HMA) sponges are those that have microbial communities of up to 108 to 1010 cells per gram. In contrast, those that contain communities in the range of 105 to 106 are called low microbial abundance (LMA) sponges [3]. The microbial symbionts acquire nutrients from the sponges and provide chemical defense and other benefits to the host. Besides this, they also prove to be rich sources of metabolites of great value [4]. Among the bacterial communities, actinobacteria contribute a multitude of bioactive secondary metabolites with biomedical and industrial applications. They are significant contributors of major molecules against bacteria, fungi, parasites, malaria, and present

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_5, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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Table 1 Few actinobacterial strains isolated from various marine sponges S.No Sponges

Actinobacteria isolated

Sponge collection location Reference

Actinomycetales bacterium

South China Sea

[6]

1

Craniella australiensis

2

Fasciospongia cavernosa Nocardiopsis alba

Southwest coast, India

[7]

3

Dendrilla nigra

Nocardiopsis dassonvillei

Southwest coast, India

[8]

4

Callyspongia sp.

Streptomyces griseoincarnatus Gulf of Mannar, India

[9]

5

Xestospongia sp.

Nocardia xestospongiae

[10]

Andaman Sea

immunomodulation, anti-inflammatory, antioxidant, and antitumor activities. These secondary metabolites can be anything ranging from peptides to polyketides [5]. Although actinomycetes can be observed in different quantities in various marine sources, which includes marine water, marine sediments, and marine invertebrates, sponges have been observed to have the highest population of actinomycetes as endosymbionts (Table 1) [11]. In the present chapter, we discuss isolation techniques and various isolation media for endosymbiotic actinobacteria.

2

Materials

2.1 Isolation Media and Constituents

1. Emerson agar (1 L) (beef extract—4 g, yeast extract—1 g, peptone—4 g, dextrose— 10 g, NaCl—2.5 g, agar—20 g, pH —7.0  0.2). 2. M1 media (1 L) (soluble starch—10 g, yeast extract—4 g, peptone—2 g, agar—18 g, pH 7.0  0.2). 3. Marine Sponge Agar (MSA) (1 L) (raffinose—10 g, CaCO3— 0.5 g, NaCl— 20 g, agar—15 g, L-histidine—1 g, ferrous sulfate—0.01 g, dipotassium hydrogen phosphate—1 g, pH 7.0  0.2). 4. Starch–Casein Nitrate Seawater agar (1 L) (soluble starch— 10 g, sodium caseinate—1 g, potassium dihydrogen phosphate—0.5 g, magnesium sulfate—0.5 g, agar—18 g, seawater—1 L, pH 7.0  0.2). 5. Sterile habitat marine water. 6. Nalidixic acid (25 μg/mL). 7. Cycloheximide (100 μg/mL). 8. Ethanol (70%) [5, 7, 12, 13].

Isolation of Actinobacteria from Sponges

2.2 Laboratory Equipment

3

25

Homogenizer, mortar and pestle, 0.2 μm syringe filter, petri plates, conical flasks.

Methodology

3.1 Collection of Sponges

1. Collect fresh sponges in a sterile polypropylene bag by snorkeling or scuba diving based on the depth and transfer to sterile plastic bags. 2. Bring the samples to laboratory under aseptic condition.

3.2 Processing of Sample

3. Wash sponges thoroughly with sterile distilled water and sterile marine water to remove all the loosely attached microbes and all marine debris. 4. Surface-sterilize sponges in ethanol and finally rinse with sterile water. 5. Identify the sponge’s genus and species using a standard manual [5, 14, 15].

3.3 Isolation of Actinobacterial Isolates

1. Cut the clean sponge material into 1 cm3 sized pieces. 2. Homogenize the samples using a sterile mortar and pestle or in a homogenizer using 10 volumes of sterile marine water (Fig. 1). 3. Transfer the homogenate to serially dilute it to 10 dilutions.

1

to 10

7

4. Plate the 10 5, 10 6, and 10 7 dilutions onto various agar plates, namely, marine sponge agar, M1 media, and Emerson agar. 5. Prepare culture plates for selective isolation of actinobacterial endosymbionts. Therefore, the agar media are all supplemented with an antibacterial agent like nalidixic acid and an antifungal like cycloheximide. 6. Inoculate the serial diluted 1 mL of sponge sample in culture plates by pour plate method.

Slice Wash

Homogenize

Fig. 1 Flowchart representing isolation of actinobacterial sponge endosymbionts

26

Neethu Kamarudheen and Kokati Venkata Bhaskara Rao

7. Incubate the inoculated plates at 28  C for a period of 7–21 days for Streptomyces sp. and longer period of incubation for rare actinobacteria [15–17]. 8. Observe, count, and purify distinctive colonies; characterize and identify the sponge associated actinobacteria by polyphasic taxonomic identification protocols.

References 1. Wehrl M, Steinert M, Hentschel U (2007) Bacterial uptake by the marine sponge Aplysina aerophoba. Microb Ecol 53:355–365 2. Thomas C, Horn M, Wagner W, Hentschel U, Proksch P (2003) Monitoring microbial diversity and natural products profiles of the sponge Aplysina cavernicola following transplantation. J Mar Biol 142:685–692 3. Hentschel U, Usher KM, Taylor MW (2006) Marine sponges as microbial fermenters. FEMS Microb Ecol 55:167–177 4. Faulkner DJ (2000) Marine pharmacology. Antonie Van Leeuwenhoek 77:135–145 5. Abdelmohsen UR, Bayer K, Hentschel U (2014) Diversity, abundance and natural products of marine sponge-associated actinomycetes. Nat Prod Rep 31:381–399 6. Li ZY, Liu Y (2006) Marine sponge Craniella austrialiensis-associated bacterial diversity revelation based on 16S rDNA library and biologically active Actinomycetes screening, phylogenetic analysis. Lett Appl Microbiol 43:410–416 7. Gandhimathi R, Kiran GS, Hema TA, Selvin J, Raviji TR, Shanmughapriya S (2009) Production and characterization of lipopeptide biosurfactant by a sponge-associated marine actinomycetes Nocardiopsis alba MSA10. Bioprocess Biosyst Eng 32(6):825–835 8. Selvin J, Shanmughapriya S, Gandhimathi R, Kiran GS, Ravji TR, Natarajaseenivasan K, Hema TA (2009) Optimization and production of novel antimicrobial agents from sponge associated marine actinomycetes Nocardiopsis dassonvillei MAD08. Appl Microbiol Biotechnol 83(3):435–445 9. Kamarudheen N, Rao KB (2019) Fatty acyl compounds from marine Streptomyces griseoincarnatus strain HK12 against two major bio-film forming nosocomial pathogens; an in vitro and in silico approach. Microb Pathog 27:121–130 10. Thawai C, Rungjindamai N, Klanbut K, Tanasupawat S (2017) Nocardia xestospongiae

sp. nov., isolated from a marine sponge in the Andaman Sea. Int J Syst Evol Microbiol 67:1451–1456 11. Selvin J, Ninawe AS, Kiran GS, Lipton AP (2010) Ecological implications and bioprospecting avenues. Crit Rev Microbiol 36:82–90 12. Mincer TJ, Fenical W, Jensen PR (2005) Culture-dependent and culture-independent diversity within the obligate marine actinomycete genus Salinispora. Appl Environ Microbiol 71:7019–7028 13. Selvin J, Gandhimathi R, Kiran GS, Priya SS, Ravji TR, Hema TA (2009) Culturable heterotrophic bacteria from the marine sponge Dendrilla nigra: isolation and phylogenetic diversity of actinobacteria. Helgol Mar Res 63:239–247 14. Sun W, Dai S, Jiang S, Wang G, Liu G, Wu H, Li X (2010) Culture-dependent and cultureindependent diversity of Actinobacteria associated with the marine sponge Hymeniacidon perleve from the South China Sea. Antonie Van Leeuwenhoek 98:65–75 15. Sun W, Zhang F, He L, Karthik L, Li Z (2015) Actinomycetes from the South China Sea sponges: isolation, diversity, and potential for aromatic polyketides discovery. Front Microbiol 6:1048 16. Shamikh YI, El Shamy AA, Gaber Y, Abdelmohsen UR, Madkour HA, Horn H, Hozzein WN (2020) Actinomycetes from the Red Sea sponge Coscinoderma mathewsi: isolation, diversity, and potential for bioactive compounds discovery. Microorganisms 8:783 17. Gamaleldin NM, Bakeer W, Sayed AM, Shamikh YI, El-Gendy AO, Hassan HM, Hozzein WN (2020) Exploration of chemical diversity and antitrypanosomal activity of some red sea-derived actinomycetes using the OSMAC approach supported by LC-MS-based metabolomics and molecular modelling. Antibiotics 9:629

Chapter 6 Isolation of Actinobacteria from Shrimp A. S. Shijila Rani, S. Babu, A. Anbukumaran, P. Prakash, S. Veeramani, and V. Ambikapathy Abstract Actinobacteria act as a probiotics in aquaculture environments. Actinobacteria have gained special importance as they play a major role in the recycling of organic matter as well as production of pharmaceuticals, enzymes, antimicrobial agents, immune modifiers, and vitamins. The application of new probiotics is a good strategy in the biological control of infectious diseases in aquaculture. Probiotics are used to improve water quality and control of bacterial infections. A predominant number of Actinobacteria are present in the gut region than any other region, because the gut region is a rich source of nutrients and engulfed feed material are stored in this region. Thus, the microbes that colonize the gut, commonly referred to as gut microbiota or gut microbiome, interact with their host and contribute to a number of key host processes, including digestion and immunity. Key words Shrimp, Gut, Starch casein agar

1

Introduction Actinobacteria are widely distributed in aquatic habitats, which may sometimes be washed in from surrounding terrestrial habitats. Actinobacteria are a group of bacteria that share some common characteristics with fungi and can cause diseases like fungi. They are able to form hyphae, usually considered a trait of fungi only. Aquaculture is a strategic and rapidly developing industry. Aquaculture of finfish, crustaceans, and mollusks contributed to 43% of the aquatic animal food produced for human consumption in 2007 and is expected to increase further the demand of the rapidly growing global population [1]. Actinobacteria they can act as a probiotics. A probiotic is defined as “a live microbial feed supplement which beneficially affects the host animal by improving its intestinal microbial balance” [2]. Probiotics which compete with bacterial pathogens for nutrients or inhibit the growth of patho-

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_6, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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Table 1 Description of actinobacteria associated with shrimp S. No

Actinobacteria

Shrimp

1

Streptomyces sp.

Litopenaeus vannamei King Abdulaziz university Saudi Arabia [3]

2

Streptomyces fradiae Penaeus monodon

Location

Country

Reference

King Abdulaziz university Saudi Arabia [4]

gens can be a valid alternative to the prophylactic application of antibiotics and biocides. Gut-inhabiting microbes are recognized as important drivers of several metabolic processes in the host. The characterization and subsequent manipulation of this microscopic community is an attractive proposition for aquaculture research (Table 1). In an aquaculture system, shrimp and microorganisms share the same aquatic medium; the intestinal microbial community interacts directly with planktonic microbiota and probiotics [5, 6]. The Actinobacteria probiotic diets with pre, pro, and symbiotic supplementation which can also improve animal growth and feed efficiency [7]. Therefore, probiotics have shown to be a promising and environmentally friendly alternative to disease prevention, especially in crustacean aquaculture of high commercial value [8].

2 2.1

2.2

Materials and Methods Requirements

Procedure [9]

l

Starch casein agar (Composition: Casein Powder—1.00 g; Starch—10.00 g; Sea Water—37.00 g; Agar—15.00 g; Distilled Water ¼ 1000 ml, pH (at 25  C) 7.0  0.1).

l

L. vannamei, Penaeus monodon.

l

Petri plate.

l

Test tube.

l

Test tube stand.

l

Scissors.

l

Forceps.

l

Pipette.

l

Spirit lamp.

l

Hot air oven.

l

L-rod spreader stand.

l

Healthy L. vannamei and Penaeus monodon shrimps are collected from Lakshmi Aqua Farm, Eripurakarai, Adirampattinam, Tamil Nadu, India.

Isolation of Actinobacteria from Shrimp

29

l

Separate gut from L. vannamei and Penaeus monodon shrimp and wash thoroughly with tap water.

l

One gram of gut sample is weighed and dissolved with 10 ml distilled water in a test tube.

l

To take 9 ml distilled water in seven test tubes and 1 ml sample was transfer in first tube (101) followed by serially dilute in six test tubes (102 to 107 dilution) after 1 ml sample take from 107 dilution test tube is discard.

l

l

l

l

l

Prepare and sterilize starch casein agar medium at 121  C for 30 min in an autoclave. Supplement with rifampin and nystatin (to inhibit the growth of bacteria and fungi) in 45  C molten Starch casein agar medium and pour in sterile petri plate and to stand 15 min. The suitable dilutions of Actinobacteria isolation is 102, 103, and 104 dilution. Take 0.1 ml of 102 dilution and spread over the starch casein agar medium and subsequently to 103 and 104 dilutions as mentioned in Fig. 1. Wait 5 min to complete preincubation, then incubate the plate in inverted position at 30  C for 2–4 weeks.

Fig. 1 Flowchart explaining isolation of Gut actinobacteria from Shrimp

30

A. S. Shijila Rani et al.

Table 2 Isolation of Actinobacteria from shrimp gut S. No

Dilutions

1.

10

2

10

3

10

2 3 4

No. of Actinobacteria (CFU/ml) 17 10 7

l

After incubation period the plates are observed.

l

The results are recorded and tabulated.

2.3

Observation

The Actinobacteria colony morphology is powdery, filamentous growth, aerial mycelium and tough, dusty, and frequently pigmented colonies (Table 2).

2.4

Results

One gram of shrimp gut sample record in 17  102 CFU/ml.

References 1. Bostock J, McAndrew B, Richards R, Jauncey K, Telfer T, Lorenzen K, Little D, Ross L, Handisyde N, Gatward I, Corner R (2010) Aquaculture: global status and trends. Philos Trans R Soc Lond Ser B Biol Sci 365 (1554):2897–2912 2. Fuller R (1989) Probiotics in man and animals, a review. J Appl Bacteriol 66:365–378 3. Garcia-Benal M (2017) Probiotic effect of Streptomyces spp. on shrimp (Litopenaeus vannamei) post larvae challenged with Vibrio parahaemolyticus. Aquac Nutr 24:865–871 4. Aftabuddin S, Kashem MA, Kader MA (2013) Use of Streptomyces fradiae and Bacillus megaterium as probiotics in the experimental culture of tiger shrimp Penaeus monodon (Crustacea, Penaeidae). AACL Bioflux 6:253–267 5. De Schryver P, Defoirdt T, Sorgeloos P (2014) Early mortality syndrome outbreaks: a microbial management issue in shrimp farming? PLoS Pathog 10:e1003919

6. Xiong J, Wang K, Wu J, Qiuqian L, Yang K, Qian Y, Zhang D (2015) Changes in intestinal bacterial communities are closely associated with shrimp disease severity. Appl Microbiol Biotechnol 99(16):6911–6919 7. Ringo E, Olsen RE, Jensen I, Romero J, Lauzon HL (2014) Application of vaccines and dietary supplements in aquaculture: possibilities and challenges. Rev Fish Biol Fish 24(4):1005–1032 8. Lobo C, Moreno Ventas X, Tapia-Paniagua S, Rodriguez C, Morinigo MA, de La Banda IG (2014) Dietary probiotic supplementation (Shewanella putrefaciens Pdp11) modulates gut microbiota and promotes growth and condition in Senegalese sole larviculture. Fish Physiol Biochem 40(1):295–309 9. Subramani R, Aalbersberg W (2013) Culturable rare Actinomycetes: diversity, isolation and marine natural product discovery. Appl Microbiol Biotechnol 97:9291–9321

Chapter 7 Isolation of Actinobacteria from Coral Reef S. Babu, A. S. Shijila Rani, V. Ambikapathy, P. Prakash, and A. Anbukumaran Abstract Coral reefs are the result of a symbiotic relationship between photosynthetic microorganisms called zooxanthellae and tiny sea anemone cousins called polyps. The zooxanthellae, which live in the tissue of the polyps, capture energy from the sun and pass it on their hosts. Meanwhile, the polyps secrete calcium carbonate to create shells around their bodies. Actinobacteria are a ubiquitous major group of coral holobionts. Marine Actinobacteria, particularly coral-associated Actinobacteria, have attracted much attention recently. Key words Coral reef, Humic acid–—vitamin agar medium, Antibiotics

1

Introduction Coral reef ecosystem is one of the most important tropical marine ecosystems, mainly distributed in the Indo-West Pacific, Eastern Pacific, Western Atlantic, and the Eastern Atlantic [1]. Corals provide habitats for numerous bacteria in their mucus layer, tissue, and calcium carbonate skeleton, as well as dinoflagellates, fungi, archaea, and viruses [2]. Coral-associated bacteria not only take part in carbon, nitrogen, and sulfur biogeochemical cycles and provide necessary nutrients for coral but also keep corals from being infected by pathogens [3, 4]. Actinobacteria is generally accepted as a ubiquitous major group in corals [5]. Environmental conditions, coral species, colony physiology, and seasonal variation are factors that considerably influence the coral-associated bacterial community [6]. Moreover, due to various microhabitats provided by corals’ biological structures, spatial heterogeneity in bacterial communities associated with a single coral colony has been observed [7]. As a major coral-associated bacterial group, how actinobacteria are spatially and temporally organized in corals, and the connection between the actinobacteria communities in corals

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_7, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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Table 1 Description of actinobacteria associated with coral reef S. No

Actinobacteria

Country

Reference

1

Nocardiopsis alba

India

[8]

2

Streptomyces sp.

India

[9]

3

Saccharothrix espanaensis

India

[10]

and in seawater remain poorly understood (Table 1). A comprehensive investigation of the distribution of this ubiquitous group at spatial and temporal scales will help understand the variation of coral associated bacteria and the potential function of actinobacteria, and will contribute a lot to bioprospect the actinobacteria resources for utilization as novel sources for bioactive natural products.

2 2.1

2.2

Materials and Methods Requirements

Procedure [11]

l

Humic acid–vitamin agar (Humic acid—1 g/l, Na2HPO4— 0.5 g/l, KCl—1.7 g/l, MgSO4.7H2O—50 mg/l, FeSO4.7H2O—10 mg/l, CaCO3—10 mg/l, agar—18 g/l, seawater—30%/l, pH 7.5).

l

Coral reef (scleractinian coral Montipora venosa).

l

Petri plate.

l

Test tube.

l

Test tube stand.

l

Pipette.

l

Spirit lamp.

l

Hot air oven.

l

L-rod spreader stand.

l

Healthy scleractinian Montipora venosa coral fragments (approximately 10  10 cm) are collected from sea at the depth of 3— 5 m using punch and hammer.

l

Coral mucus, tissues, and skeleton are separated and stored.

l

Approximately 2 g of soft coral is thoroughly washed twice with filtered (0.2 mm size filter paper) seawater, ground with a sterile mortar and pestle, and transferred to a 50 ml centrifuge tube.

l

The soft coral is then vigorously vortexed for 3 min after adding 10 ml filtered seawater. The sample is serially diluted with seawater up to 10 7.

Isolation of Actinobacteria from Coral Reef

33

Fig. 1 Flowchart showing isolation of Actinobacteria associated with coral reef

l

l

l

l

The humic acid–—vitamin agar medium is sterilized at 121  C for 30 min in an autoclave. Supplement 45  C molten humic acid–vitamin agar medium with rifampin (suppress the growth bacteria) and cycloheximide (suppress the growth of fungi) and pour it into sterile petri plate and allow to stand for 15 min. The suitable dilutions of Actinobacteria isolation are 10 10 3, and 10 4.

2

,

Take 0.1 ml of 10 2 dilution and spread over starch casein agar medium and repeat the same for 10 3 and 10 4 dilutions (Fig. 1).

l

Wait 5 min to complete preincubation, then incubate the plate in inverted position at 30  C for 2–4 weeks.

l

After incubation period the plates are observed.

l

The results are recorded and tabulated.

34

S. Babu et al.

Table 2 Isolation of Actinobacteria from coral reef by serial dilution method S. No

Dilutions

No. of Actinobacteria (CFU/ml)

10

2

25

2

10

3

19

3

10

4

11

1.

2.3

Observation

The Actinobacteria colony morphology is powdery, filamentous growth, aerial mycelium, and tough, dusty, and frequently pigmented colonies (Table 2).

2.4

Results

One gram of coral reef sample recorded 25  10

2

CFU/ml.

References 1. Moberg F, Folke C (1999) Ecological goods and services of coral reef ecosystems. Ecol Econ 29:215–233 2. Rosenberg E, Koren O, Reshef L, Efrony R, Ziber-Rosenberg I (2007) The role of microorganisms in coral health, disease and evolution. Nat Rev Microbiol 5:355–362 3. Raina JB, Tapiolas D, Willis BL, Bourne DG (2009) Coral-associated bacteria and their role in the biogeochemical cycling of sulfur. Appl Environ Microbiol 75:3492–3501 4. Bourne DG, Webster NS (2013) Coral reef bacterial communities. In: Rosenberg E, DeLong EF, Lory S, Stackebrandt E, Thompson F (eds) The Prokaryotes. Springer-Verlag, Heidelberg, pp 163–187 5. Carlos C, Torres TT, Ottoboni LM (2013) Bacterial communities and species-specific associations with the mucus of Brazilian coral species. Sci Rep 3:1624 6. Hong MJ, Yu YT, Chen CA, Chiang PW, Tang SL (2009) Influence of species specificity and other factors on bacteria associated with the coral Stylophora pistillata in Taiwan. Appl Environ Microbiol 75:7797–7806 7. Sweet MJ, Croquer A, Bythell JC (2011) Bacterial assemblages differ between

compartments within the coral holobiont. Coral Reefs 30:39–52 8. Lin ZJ, Torres JP, Ammon MA, Marett L, Teichert RW, Reilly CA, Kwan JC, Hughen RW, Flores M, Tianero MD, Peraud O, Cox JE, Light AR, Villaraza AJL, Haygood MG, Concepcion GP, Olivera BM, Schmidt EW (2013) A bacterial source for mollusk pyrone polyketides. Chem Biol 20:73–81 9. Lin Z, Reilly CA, Antemano R, Hughen RW, Marett L, Concepcion GP, Haygood MG, Olivera BM, Light A, Schmidt EW (2011) Nobilamides A-H, long-acting transient receptor potential vanilloid-1 (TRPV1) antagonists from mollusk-associated bacteria. J Med Chem 54:3746–3755 10. Kalinovskaya NI, Kalinovsky AI, Romanenko LA, Pushilin MA, Dmitrenok PS, Kuznetsova TA (2008) New Angucyclinones from the marine mollusk associated Actinomycete Saccharothrix espanaensis an 113. Nat Prod Commun 3:1611–1616 11. Hayakawa M, Nonomura H (1987) Humic acid-vitamin agar, a new medium for the selective isolation of soil actinomycetes. J Ferment Technol 66:501–509

Chapter 8 Isolation of Actinobacteria from Earthworm Cast V. Ambikapathy, A. S. Shijila Rani, A. Anbukumaran, R. Shanmugapriya, and S. Babu Abstract Earthworm casts are known to contribute significantly to surface soil fertility in agroecosystems. Knowledge of their role in maintaining soil fertility is of primary importance in maintaining a healthy soil ecosystem. These physicochemical properties of earthworm casts increase soil fertility, and hence production rate. Many microbes are present in earthworm casts and one-third of it constitutes Actinobacteria. Earthworm castings have rarely been explored for Actinobacteria possessing antimicrobial activity and industrial enzymes. There is immense potential to identify new Actinobacteria in earthworm castings to discover novel bioactive compounds. Key words Earthworm casts, ISP-2 HiMedia, Actinobacteria

1

Introduction Casting by earthworms is an important activity which has been shown by several studies to have a significant impact on soil fertility. A worm casting is a biologically active mound containing several bacteria, enzymes, and remnants of plant materials and animal manure that have not been digested by the earthworm [1]. Earthworms and their casts are useful in land improvement, reclamation, and organic waste management [2, 3]. Earthworm casts significantly affect plant growth through their effects on microorganisms, aggregation of soil, and nutrient supply [4]. Three major cast types are observed to be produced by earthworms, namely, pellet casts (granular casts) produced by Eudrilus eugeniae, Agrotoreutus spp., and Eutoreutus spp. [5, 6]; turret casts (funnel/finger shaped) produced by Hyperiodrilus africanus and Ephyriodrilus afroccidentalis; and the mass (moldy) casts produced by Libyodrilus violaceus [7]. There have been studies which showed that earthworm castings encourage high proliferation of microflora (Table 1). Some

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_8, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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Table 1 Description of actinobacteria from earthworm cast S. No.

Actinobacteria

Earthworm

Type of earth case

Country

Reference

1. 2. 3.

Nocardia sp. Micromonospora sp. Saccharopolyspora sp.

Pheretima posthuma

Forest Grassland Agricultural land

India India India

[8]

researchers reported more microbial count in the gut or casts of earthworms than in the surrounding soil [5, 6]. Actinobacteria are aerobic, spore-forming gram-positive bacteria, belonging to the order Actinomycetales characterized with substrate and aerial mycelium growth. The name “Actinobacteria” was derived from Greek atkis (a ray) and mykes (fungus), having characteristics of both bacteria and fungi, yet possess sufficient distinctive features to delimit them into “Kingdom bacteria.” Actinobacteria are potential producers of antibiotics and of other therapeutically useful compounds. Bioactive secondary metabolites produced by Actinobacteria include antibiotics, antitumor agents, immunosuppressive agents, and enzymes. These metabolites are known to possess antibacterial, antifungal, antioxidant, neuritogenic, anticancer, antialgal, antihelmintic, antimalarial, and antiinflammatory properties and play a major role in the cycling of organic matter in the soil ecosystem. Actinobacteria’s ability to produce a variety of bioactive secondary metabolites has been well established, and for this reason, the discovery of novel antibiotic and nonantibiotic principal components through microbial secondary metabolite screening is becoming increasingly important.

2 2.1

Materials and Methods Requirements

l

ISP-2 (International Streptomyces Project-2 Medium) HiMedia (yeast extract, 4.0 g/L; malt extract, 10.0 g/L; dextrose, 4.0 g/ L; agar, 20 g/L, distilled water—1000 mL, pH 7.2).

l

Pheretima posthuma and Eudrilus eugeniae.

l

Petri plate.

l

Test tube.

l

Test tube stand.

l

0.1% NaCl

l

Pipette.

l

Spirit lamp.

l

Hot air oven.

l

L-rod spreader stand.

Isolation of Actinobacteria from Earthworm Cast

2.2

Procedure [9]

37

l

Earthworm casts are collected from Periyar Maniyammai vermi compost center, Thanjavur.

l

One gram of Pheretima posthuma and Eudrilus eugeniae earthworm cast sample is weighed and dissolved with 10 mL distilled water in a test tube.

l

To take 9 mL distilled water in seven test tubes and transfer 1 mL sample in first test tube then transfer another test tube (10 1) followed by serially dilute in six test tubes (10 2 to 10 7 dilution) after 1 mL sample take from 10 7 dilution test tube is discard.

l

l

l

l

Prepare and sterilize ISP-2 medium at 121  C for 30 min in an autoclave. Supplement the 45  C molten ISP-2 medium with cycloheximide and nystatin to inhibit the growth of bacteria and fungi in and pour into sterile perti plate and let stand for 15 min. The suitable dilutions of Actinobacteria isolation are 10 10 3, and 10 4.

2

,

Take 0.1 mL of 10 2 dilution and spread over the starch casein agar medium, followed by 10 3 and 10 4 dilutions, as shown in Fig. 1.

Fig. 1 Flowchart for isolation of Actinobacteria

38

V. Ambikapathy et al.

Table 2 Isolation of Actinobacteria from leaf and root of mangrove plant S. No

Dilutions

No. of Actinobacteria (CFU/mL)

10

2

25

2

10

3

16

3

10

4

10

1.

l

Wait 5 min to complete pre-incubation, then incubate the plate in inverted position at 30  C for 2–4 weeks.

l

After incubation period the plates are observed.

l

The results are recorded and tabulated.

2.3

Observation

The Actinobacteria colony morphology is powdery, filamentous growth, aerial mycelium, and tough, dusty, and frequently pigmented colonies (Table 2).

2.4

Results

One gram of earthworm cast recorded 25  10

2

CFU/mL.

References 1. Lavelle P, Martin A (1992) Small-scale and large-scale effects of endogeic earthworms on soil organic matter dynamics in soils of the humid tropics. Soil Biol Biochem 24:1491–1498 2. Edwards CA, Bates JE (1992) The use of earthworms in environmental management. Soil Biol Biochem 14(12):1683–1689 3. Johnson DL (1997) Earthworms casts reflect soil conditions. Agric Res 45:19 4. Sabrina DT, Hanafi MM, Nor Azwady AA, Mahmud TMM (2009) Earthworm populations and cast properties in the soils of oil palm plantations. Mal J Soil Sci 13:29–42 5. Sims RW (1971) Eudrilinea from southern Nigeria and a taxonomic appraisal of the family Eudrilidae (Oligochaeta). J Zool Lond 164:529–549

6. Segun AO (1976) Two new genera of Eudrilid earthworms from Nigeria. Proc Biol Soc Wash 88:383–394 7. Beddard F (1981) On the structure of two genera of earthworms belonging to the Eudrilidae and some remarks on Nemertodrilus. Quat J Microsc Sci 32:235–278 8. Kumar V, Bharti A, Negi YK, Gusain O, Pandey P, Bisht GS (2012) Screening of actinomycetes from earthworm castings for their antimicrobial activity and industrial enzymes. Braz J Microbiol 43:205–214 9. Hayakawa M, Sadakata T, Kajiura T, Nonomura H (1991) New methods for the highly selective isolation of Micromonospora and Microbispora from soil. J Ferment Bioeng 72:320–326

Chapter 9 Isolation of Actinobacteria from Compost Samples T. Savitha, Ashraf Khalifa, and A. Sankaranarayanan Abstract Actinomyces are aerobic, spore-forming gram-positive bacteria, belonging to the order Actinomycetales characterized with substrate and aerial mycelium growth. They are the most abundant organisms that form thread-like filaments in the soil and are responsible for the characteristically “earthy” smell of freshly turned healthy soil. They play a major role in the cycling of organic matter, inhibit growth of several plant pathogens in the rhizoplane, and decompose complex mixtures of polymers in the dead plant, animal, and fungal materials, resulting in the production of many extracellular enzymes that are conducive to crop production. Composting has become an increasingly important strategy for the treatment of municipal organic wastes. Key words Organic matter, Decompose, Compost, Crop production

1

Introduction Composting is the controlled conversion of degradable organic products and wastes into stable products with the aid of microorganisms. It is an aerobic process where complex degradable materials are degraded and transformed by microbes into organic and inorganic by-products [1]. These products contain “humic-like” compounds that differentiate them from those found in native soil, coals, and peats. Composting is a means of transforming different degradable wastes into products that can be used safely and beneficially as biofertilizers and soil amendments [2]. Biological buffering of soils, biological control of soil environment by nitrogen fixation, and degradation of high molecular weight organic compounds like hydrocarbons in the polluted soils are remarkable characteristics of Actinomycetes. Besides, they are known to improve the availability of nutrients; minerals enhance the production of metabolites and promote plant growth. In the process of composting, microbes break down organic matter and produce carbon dioxide, water, heat, and humus, the relatively stable organic end product. Under optimal conditions, composting proceeds through three phases:

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_9, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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(1) the mesophilic phase, or moderate-temperature phase, which lasts for a couple of days; (2) the thermophilic, or high-temperature phase, which can last from a few days to several months; and (3) a several-months cooling and maturation phase. Different communities of microbes predominate during various composting phases. According to [3], the major component responsible for the biodegradation and conversion process during composting is the resident microbial community. It could be mediated by the activity of mixed microbial communities. Two different groups of aerobic microbes are involved in composting, namely, mesophilic organisms and thermophilic organisms. These organisms could be bacteria, actinomycetes, molds, and yeasts, and they dominate in different phases of composting. In the mesophilic stage, the representative bacterial flora is Pseudomonas sp., Bacillus sp., Flavobacterium sp., and Clostridium sp. Actinomycetes include Streptomyces sp. and fungal forms include Alternaria sp., Cladosporium sp., Aspergillus sp., Mucor sp., and Penicillium sp. In the thermophilic stage, the microbes include bacteria such as Bacillus sp., Thermus sp.; Actinomycetes such as Streptomyces sp., Micropolyspora sp., Thermoactinomyces sp., Thermomonospora sp.; and fungi such as Aspergillus sp., Mucor sp., Absidia sp., Sporotrichum sp., and Thermoascus sp. The compost microbial population is highly dominated by Actinomycetes, and they are known for their roles in degrading lignocellulosic materials efficiently under neutral conditions. As per [4], the distribution of Thermomonospora sp., Saccharomonospora sp., Streptomyces sp., and Microtetraspora sp., in mushroom, green waste, and sewage compost is abundant, facilitating the degradation of complex molecules under considerably high temperature and low nutrient conditions. Actinomycetes can thrive in the compost environment owing to the versatility of their metabolic pathways. It has been demonstrated that compost is applied to agricultural fields as a long-term fertilizer to improve soil structure, as a substitute for peat in horticulture, as a suppressive agent against plant pathogens, and as a microbial additive to increase enzyme activity. The enzymes also play an important role in the later stages of composting and particularly for the degradation of relatively complex, recalcitrant compounds. Composting of organic residues is a complex, exothermic, and dynamic ecological process. Organic matter decomposition involves a mixed microbial population, comprising bacteria, actinomycetes, fungi, and protozoans, that brings about the hydrolysis of organic residues.

Isolation of Actinobacteria from Compost Samples

2

41

Materials 1. Compost sample. 2. Conical flask, 250 ml. 3. Test tubes, 15 ml. 4. Micropipettes. 5. Starch casein agar plates (starch—10 g, K2HPO4—2 g, KNO3—2 g, casein—0.3 g, MgSO4.7H2O—0.05 g, CaCO3—0.02 g, FeSO4.7H2O—0.01 g, agar—15 g, distilled water—1000 ml, pH 7.0). 6. Amphotericin B. 7. Tetracycline. 8. L-rod. 9. Incubator. 10. Distilled water. 11. Sterile spatula. 12. Sterile plastic bags/bottles.

3

Methodology

3.1 Collections of Compost Samples

1. Collect the samples during thermophilic stage of composting  (50–55 C) in sterile polythene bags [5].

3.1.1 Banana Waste Compost 3.1.2 Manure Sample Preparation

1. Collect the samples from animal farms. 2. Record the temperature of the manure compost sample during its collection/sampling. 3. Sample collection is carried out in the middle part of the compost heap using a sterile spatula and place in a sterile zip-lock bag. 4. Then crush the samples (if the sample is hard/rough) and use them for the isolation of Actinomycetes. 5. Samples should be immediately processed to maintain freshness and to avoid contamination [6], as shown in Fig. 1.

3.2 Serial Dilution Technique

1. Add 1gram of compost sample in a test tube containing 100 ml distilled water (10 2). 2. Vortex the sample for 10 min to get a stock solution.

1:10

1.0mL

1:100

1.0mL

1:103

Fig. 1 Diagram showing collection, serial dilution, and culture of compost sample

Colonies:

Plate 0.1mL

9.0mL broth

Colony-forming units (unknown concentration)

1.0mL

1.0mL

1:104

1.0mL

1:105

1.0mL

1:106

42 T. Savitha et al.

Isolation of Actinobacteria from Compost Samples

43

3. Then, serial dilution is carried out by transferring 1 ml of the stock solution to a second test tube with 9 ml distilled water (10 3). 4. The above step is repeated until you reach 10 3.3 Media Preparation

6

dilution [7].

1. Prepare starch casein agar (SCA) and sterilize at 121  C in 15 lbs./square inch pressure for 15 min. 2. Amphotericin B (50 mg/ml) and tetracycline (20 mg/ml) are added to prevent fungal and bacterial growth. 3. Pour the medium onto sterile petri plate and allow for solidifying. 4. Carry out the spread plate technique by using the diluted compost samples in triplicate. 5. One uninoculated plate will serve as the control. 6. Incubate all the plates at 50–55  C for 10 days. 7. Following incubation, colonies are isolated and subjected to further analysis.

References 1. Toledo M, Siles J, Gutierrez M, Martin M (2018) Monitoring of the composting process of different agroindustrial waste: influence of the operational variables on the odorous impact. Waste Manag 76:266–274 2. Yu H, Xie B, Khan R, Shen G (2019) The changes in carbon, nitrogen components and humic substances during organic-inorganic aerobic co-composting. Bioresour Technol 271:228–235 3. Hafeez M, Gupta P, Gupta YP (2018) Rapid composting of different wastes with Yash activator plus. Int J Life Sci Sci Res 4:1670–1674 4. Lacey J (1997) Actinomycetes in compost. Ann Agric Environ Med 4:113–121

5. Anusuya D, Geetha M (2014) Isolation of thermophillic Actinomycetes from banana waste compost and their biochemical characteristics. Int J Sci Res 3(5):315–317 6. Low ALM, Mohammad SAS, Abdulla MFR (2015) Taxonomic diversity and microbial activities of Actinomycetes from manure compost. Res J Microbiol 10(11):513–522. https://doi. org/10.3923/jm.2015.513.522 7. Roitch MC, Magiri E, Bii C, Maina N (2017) Bioprospecting for broad spectrum antibiotic producing Actinomycetes isolated from virgin soils in Kericho country. Kenya Adv Microbiol 7:56–70

Chapter 10 Isolation of Gut Actinobacteria from Fecal and Tissue Samples Priyanka Sarkar Abstract Actinobacteria are distributed across various natural habitats ranging from soil to animals. Thus, they play an important role in diverse natural processes. Despite their low abundance in the human gut, Actinobacteria play a vital role in aiding gut homeostasis. Besides, these bacteria are also the source of diverse natural drugs and bioactive metabolites. In the last decade, special attention has been given to Actinobacteria owing to their role in gastrointestinal (GI) and other systemic diseases including neurological ones. Intensive studies are being carried out to explore their therapeutic properties, especially that of Bifidobacteria. Therefore, it is crucial that we understand and further develop a suitable method that would aid in isolation and cultivation of the vital species for understanding their mechanistic roles in the host’s health. This chapter will provide a detailed insight into the diverse isolation methods that can be applied in the context of Actinobacteria. Key words Fecal samples, Tissue, Spread-plate technique, PCR, Bifidobacterium

1

Introduction Actinobacteria (actinomycetes) have been under the spotlight of research due to its ability to produce various natural drugs and other bioactive metabolites such as enzyme inhibitors., antibiotics, and enzymes etc. Actinomycetes are found in diverse natural habitats such as soil, ocean, lichens, plants, and animals including humans even in the extreme environments [1]. The human gastrointestinal tract is enriched with the diverse microbial community which would amount to approximately 100 trillion microorganisms [2]. The main constituents can be categorized under four phyla, namely, Firmicutes, Bacteroidetes, Actinobacteria, and Proteobacteria. Out of these four, Actinobacteria is one of the important member of the gut microbiota, although it represents only the smallest segment. Despite its low abundance, it plays a pivotal role in maintenance the gut

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_10, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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Table 1 List of actinobacteria reported in feces and tissue samples S. No Actinobacteria

Host/ sample

References

1

Streptomyces (Streptomyces fungicidicus, Streptomyces albus, and Streptomyces celluloflavus), Oerskovia (mostly O. turbata) and Nocardiopsis (Nocardiopsis lucentensis)

Goat— Feces

2

Bifidobacterium longum, Bifidobacterium pseudocatenulatum, Bifidobacterium adolescentis, Bifidobacterium pseudolongum, Bifidobacterium breve, and Bifidobacterium bifidum

Human— [5] Tissue

3

Bifidobacterium dentium, Bifidobacterium animalis subp. Lactis

Human— Feces

[4]

[5–9]

homeostasis. Accumulating researches have been highlighted the therapeutic role played by Actinobacteria in gastrointestinal and systemic diseases. Moreover, Bifidobacteria, a class of Actinobacteria, have gained special attention due to their role as probiotics in many pathological conditions [3]. In this chapter, isolation protocols for Actinobacteria, particularly Streptomyces sp. and Bifidobacterium sp. are provided (Table 1).

2

Isolation of Actinobacteria from Goat Feces Using the Spread Plate Technique 1. Confine the selected goats and feed them a diet of hay and supplement for about 14 days. 2. Collect fecal samples on 15th day. 3. Homogenize the fecal sample in 4.5 mL of sterilized water and stir for 5 min, followed by supernatant collection. 4. Place an aliquot of 0.1 mL diluted supernatant fluid in a petri dish containing 15–20 mL agar complete minimal (CM) medium with and without inhibitor (Table 2). 5. For the inhibitor, prepare the medium with 1g KNO3, 0.5g K2HPO4, 0.4g MgSO4.7H2O, and 10g glucose in 1000 mL deionized water, and potassium dichromate (25mg L
1). 6. Incubate the inoculated plates at 26 C and monitor it periodically for approximately 20 days for the growth of actinomycetes. 7. Carry out plate counts using a microscope. 8. Recognize the actinomycetes by the presence of filamentous hyphae and/or by the formation of tough and leathery colonies that will adhere to the agar surface.

20

–

2

Glucose (g)

Galactose + raffinose (g)

Dropout mix (g)

–

Agar(g)

20

–

–

Uracil (U) (4 mg/ mL)

–

10

–

15

2

–

20

6.7

Tryptophan 10 (T) (4 mg/ mL)

Histidine (H) (4 mg/ mL)

Leucine (L) 15 (4 mg/ mL)

6.7

YNB

–

5

–

5

15

2

–

20

6.7

20

–

–

–

15

2

–

20

6.7

20

–

–

–

–

2

–

20

6.7

20

–

10

–

15

2

20 + 10

–

6.7

20

–

10

–

–

2

20 + 10

–

6.7

–

–

–

–

15

2

20 + 10

–

6.7

20

–

–

–

15

2

20 + 10

–

6.7

–

–

–

–

2

20 + 10

–

6.7

Glu/ Glu/ Glu/ Glu/ Glu/ Gal/ Gal/Raf/ Gal/Raf/ Gal/Raf/ Gal/Raf/ CM
U
H CM
U
H CM
T CM
U
H
T CM
U
H
T
L Raf
U
H CM
U
H
L CM
U
H
T CM
U
H
T CM
U
H
T
L Ingredients medium agar agar agar agar agar agar medium agar agar

Table 2 Composition of CM medium

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9. Pick the colonies representing actinomycetes and transfer it to starch casein agar slants. 10. Preserve the pure culture in 20% glycerol and store at
80 C (for long term storage) for further identification and characterization. 11. For further confirmation of the identified actinobacterial strain, PCR-based approach can be considered with the aid of various primers (e.g., 27f-GAGTTTGATCMTGGCTCAG and 1492r-ACGGYTACCTTGTTACGACTT).

3

Isolation of Bifidobacteria from Human Gut Bifidobacteria are under limelight in research due to its potential probiotic activity. The isolation process of the microflora from both human mucosal tissue and fecal samples is described below. 1. Collect the samples in sterile containers followed by transportation to the laboratory in anaerobic jars containing Anaerocult A (Oxoid). 2. Clean the biopsy channels with sterile saline after taking out the tissue sample each time. 3. Wash the samples in 900μL saline solution (0.25% cysteine, 10μg L
1 vitamin K1, and 0.02g L
1 hemin). 4. Serial-dilute the supernatants of samples, followed by pour plate approach onto Bifidobacterium selective agar (BSM) medium (Table 3).

Table 3 Composition of Bifidobacterium selective agar medium Sl no.

Ingredients

g/L

1

Peptone special

22.220

2

Corn starch

0.970

3

Sodium chloride

4.830

4

Dextrose (glucose)

2.500

5

Lactulose

2.500

6

L-cysteine hydrochloride monohydrate

0.500

7

Riboflavin (vitamin B2)

0.010

8

Agar

14.490 

Note: The pH of the medium should be 6.3  0.2 (at 25 C)

Isolation of Gut Actinobacteria from Fecal and Tissue Samples

49

To reconfirm the specific genus or species, PCR-based sequencing approach can also be considered apart from the morphological and biochemical studies. 3.1 Reagents for PCR Reactions

3.2

PCR Program

MgCl2 1.5 mM. Tris–HCl 20 mM. KCl 50 mM. dNTPs 200 μM. Primers 15–25 pmol/μl, each. Taq DNA polymerase 1U. Template DNA 50 ng. Total reaction volume 25 μL. Initial denaturation 3 min at 94  C. Denaturation 30 s at 94  C. Annealing 30s at 56.5  C. Extension 1 min at 72  C (for 35 cycles). Elongation step 10 min at 72  C 1. The amplifications can be further cross-checked on 1–2% agarose gels, followed by ethidium bromide staining. 2. Purify PCR fragments further using the PCR purification kit, followed by sequencing. Composition of PCR mastermix Tris–HCl 10 mM KCl 50 mM MgCl2 3 mM Deoxynucleoside triphosphate 200 μM each Primers 1 μM/each Taq DNA polymerase 2.5 U Template DNA 25 ng Total reaction volume 25 μL PCR program 94  C for 3 min (1 cycle) 94  C for 30 s 48  C for 30 s, (35 cycles) 72  C for 4 min 72  C for 6 min (1 cycle)

3. To identify the specific strain, molecular typing with targeting the repetitive intergenic consensus sequences (ERIC) approach

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can be considered using the PCR primers ERIC1 (50 - ATG TAAGCTCCTGGGGATTCAC -30 ) and ERIC-2 (50 AAG TAAGTGACTGGGGTGAGCG-30 ). 4. Further, perform nucleotide sequencing with the primers bifsec (50 -CATGCCCCTACGTCCAG-30 ) and 23S-bif (50 -CA AGGCATCCACCATACGC-30 ). 5. Analyze the sequence data using various software (e.g., DNASTAR, Clustal Omega), followed by sequence assembly using databases such as NCBI (National Center for Biotechnology Information) using BLAST (Basic Local Alignment Search Tool).

Acknowledgments I gratefully acknowledge the guidance of Dr. Mohan Chandra Kalita, Dr. Mojibur R. Khan, and Dr. Rupjyoti Talukdar in my research. Asian Healthcare Foundation and Asian Institute of Gastroenterology are also thankfully acknowledged for providing me the essential research infrastructural facilities. References 1. Jiang Y, Li Q, Chen X, Jiang C (2016) Isolation and cultivation methods of Actinobacteria. Actinobacteria Basics Biotechnolog Appl 11:39–57 2. Rinninella E, Raoul P, Cintoni M, Franceschi F, Miggiano GA, Gasbarrini A, Mele MC (2019) What is the healthy gut microbiota composition? A changing ecosystem across age, environment, diet, and diseases. Microorganisms 7(1):14 3. Binda C, Lopetuso LR, Rizzatti G, Gibiino G, Cennamo V, Gasbarrini A (2018) Actinobacteria: a relevant minority for the maintenance of gut homeostasis. Dig Liver Dis 50 (5):421–428 4. Tan H, Deng Z, Cao L (2009) Isolation and characterization of actinomycetes from healthy goat faeces. Lett Appl Microbiol 49(2):248–253 5. Turroni F, Foroni E, Pizzetti P, Giubellini V, Ribbera A, Merusi P, Cagnasso P, Bizzarri B, de’Angelis GL, Shanahan F, van Sinderen D (2009) Exploring the diversity of the

bifidobacterial population in the human intestinal tract. Appl Environ Microbiol 75 (6):1534–1545 6. Ventura M, Zink R (2002) Rapid identification, differentiation, and proposed new taxonomic classification of Bifidobacterium lactis. Appl Environ Microbiol 68(12):6429–6434 7. Ventura M, Canchaya C, Fitzgerald GF, Gupta RS, van Sinderen D (2007) Genomics as a means to understand bacterial phylogeny and ecological adaptation: the case of bifidobacteria. Antonie Van Leeuwenhoek 91(4):351–372 8. Sambrook J, Russell D (2001) Molecular cloning: a laboratory manual, 3rd edn. Cold Spring Harbor Laboratory Press, Cold Spring Harbor, NY 9. Sch€afer J, J€ackel U, K€ampfer P (2010) Development of a new PCR primer system for selective amplification of Actinobacteria. FEMS Microbiol Lett 311(2):103–112

Chapter 11 Isolation of Gut Actinobacteria from Termites S. Malavika, Sahana Kranthi, H. S. Shishira Rao, Shreyanka S. Moily, and A. Martin Paul Abstract Microorganisms are extremely diverse in their habitat thriving throughout the biosphere. Among them, Actinobacteria constitutes one of the largest bacterial phyla. Actinobacteria are ubiquitous in both terrestrial and aquatic ecosystems. Microorganisms colonizing the gastrointestinal tracts of animals are called as gut microbiota and it is also one of the habitats scarcely explored. Actinobacteria is considered to be the fourth largest phyla among the gut microbiota and found abundantly are the members of Streptomycetaceae, Nocardiopsaceae, and Micromonosporaceae. Actinobacteria are found to be colonizing guts of various organisms including humans, fishes, cattle and insects. The gut microbiota of termites are ought to be beneficial to host by producing secondary antimicrobial metabolites against various microorganisms thus rendering a mutual interaction. The Streptomyces species from termites also exhibit probiotic activities in herbivores and antagonistic activities against pathogens. Apart from their role of symbionts, their significance in antibiosis and drug development has led to the unraveling of actinobacteria for their diverse metabolic capabilities in the spheres of biotechnological industries, agroindustries; and regarded as one of the potent microbes for producing more than 10,000 bioactive metabolites. Since the habitats and host specificity are vast, the present chapter aims to provide an insight into the isolation protocols of gut Actinobacteria from termites. Key words Actinobacteria, Termites, Gut microbiota, Bacteriophage

1

Introduction Actinobacteria are ubiquitous gram-positive bacteria with a wide range of niches including aquatic and terrestrial habitats. Members of actinobacterial group have high guanine and cytosine content in their genomic DNA [1]. They lack a distinct cell wall but are found producing nonseptate, slender mycelium. Colonies of Actinobacteria exhibit a powdery consistency and are found producing hyphae and sporangia-like fungi in the culture media by adhering firmly to the agar surface. Actinobacteria replenish the supply of nutrients in the soil by playing a crucial role in organic matter turnover and the carbon cycle. They constitute a significant part

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_11, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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Fig. 1 Biotic and abiotic factors that influence the gut microbiota of termites in terms of physiological and metabolic activity. These factors are likely to affect the processes such as reproduction, antimicrobial activity, and organic matter turnover, and enzyme activity in addition to digestion

in the degradation of organic substances like cellulose, polysaccharides, fats, and proteins [2]. A large number of antibiotic compounds such as streptomycin, actinomycin, and tetracycline are produced by the actinobacterial members [3]. Actinobacteria is among the four largest phyla of the gut microbiota. Symbiotic interactions are fundamental as they play a vital role in nutrition, in detoxification of certain compounds, in growth and defense against pathogens [2]. Actinobacteria are known to be beneficial to the gut of termites’ by aiding in digestion, termite nutrition and gas emissions such as carbon dioxide, hydrogen, and methane “(Fig. 1 near here)” [4]. One of the environments that have hardly been exploited in actinobacterial isolation is that of the guts of termites [5]. Termites belong to the order Isoptera and are divided into lower and higher termites. Higher termites have a more evolved diet and gut microbiota, few feeding on wood and well-rotted plant matter, few being exclusive soil feeders while others are found growing and feeding

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on cellulolytic fungi, whereas lower termites are mostly wood-feeding insects [6]. Various strains of Actinobacteria such as Micromonospora spp. and Streptomyces spp. were isolated from the hindgut of several termite species, namely, Macrotermes, Odontotermes, Amitermes, and Microcerotermes [7]. Actinobacteria are extensive in both lower and higher termite species [5]. Termites can extensively degrade wood constituents (cellulose and hemicellulose) with the help of symbiotic gut microbiota [8]. These symbionts produce hydrolytic enzymes that aid in the breaking down of lignocellulose ingested by the termites; accordingly the microbes are potential producers of biofuels from agricultural waste products [1, 9]. The Actinobacteria associated with the termite gut are known to produce secondary antimicrobial compounds which are essential for pathogen inhibition in termites [10]. Actinobacteria isolated from termite gut exhibits remarkable antimicrobial activities. For example, few actinobacterial isolates were observed to inhibit both gram-positive and gram-negative pathogens; also the antimicrobial activity was found to be more effective in grampositive than in that of the gram-negative pathogen [11]. Traditionally the gut of the termite species is isolated on different media such as actinomycete isolation agar, starch casein agar, chitin agar, and ISP-2. Considering the diverse mutualistic behavior of actinobacteria with that of the termites, the current chapter provides an insight into different isolation protocols of gut actinobacteria from termites by using various media.

2

Materials

2.1 Sample Collection

1. Sterile plastic or metal storage box.

2.2 Sample Processing and Surface Sterilization

1. Laminar air flow (LAF). 2. 50% ethanol 3. 70% ethanol 4. 1% mercuric chloride 5. Standard Iodine solution.

2.3 Aseptic Removal of Gut and Homogenization

1. Microfuge tubes. 2. Vortex shaker. 3. Sterile phosphate buffer. 4. Nutrient broth. 5. Sterile saline solution. 6. Phage solution. 7. Forceps.

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8. Sterile slides. 9. Peptone yeast extract calcium [PYCa] media (composition in g/L: yeast extract, 1.0; peptone, 15; 40% dextrose, 2.5 mL; agar, 15) 4.5 mL of 1 M CaCl2 is added to the autoclaved media. 2.4 Culture Media Preparation

1. Autoclave. 2. pH Meter. 3. Incubator. 4. Chitin agar medium (composition in g/L: Chitin, 5.33; K2HPO4, 0.767; KH2PO4, 0.367; MgSO4, 0.244; FeSO4.7H2O, 0.01; ZnSO4.7H2O, 0.001; MnCl2.4H2O, 0.001; agar, 20; pH, 8.0 after autoclaving) is supplemented with nystatin (0.0427 g/L) and cycloheximide (0.0667 g/L) (see Note 1). 5. Humic acid vitamin agar [HVA] (humic acid, 0.1%; Na2HPO4.12H2O, 0.05%; KCl, 0.17%; FeSO4.7H2O, 0.001%; CaCO3, 0.001%; agar, 15; pH, 7.0) is supplemented with thiamine hydrochloride, riboflavin, nicotinic acid, pyridoxine hydrochloride, inositol, pantothenic acid, calcium salt, p-aminobenzoic acid of 0.005% each and biotin of 0.0025% respectively (see Note 2). 6. Defatted wood powder medium (2% Defatted Japanese beech powder, 1.5% agar in distilled water) (see Note 3). 7. International Streptomyces Project-2 [ISP-2] (composition g/L: yeast extract powder, 4 g; malt extract powder, 10; dextrose, 4; agar, 20; pH 6.2  0.2 at 25  C) (see Note 4). 8. Starch casein agar [SCA] (composition in g/L; dipotassium hydrogen orthophosphate, 2; calcium carbonate, 0.02; ferrous sulfate heptahydrate, 0.01; starch, 10; potassium nitrate, 2; casein, 0.3; magnesium sulfate heptahydrate, 2; agar, 15; pH 7.0  0.1 at 25  C) is used. Media is additionally supplemented with nalidixic acid (25 ppm), nystatin (50 ppm) and cycloheximide (50 ppm) (see Note 5).

2.5 Sub Culturing and Purification

3

1. ISP-2 Medium broth containing 20% glycerol

Methods

3.1 Sample Collection

Termites being social insects, they can be collected from tropical, subtropical, and temperate regions of the world [12]. Based on the saprophytic feeding habit of termites and their symbiotic associations there are many modes of collection procedures (see Note 6)

Isolation of Gut Actinobacteria from Termites

55

1. Collect termites from soil of forest floors, organically rich soils, that is, humus. 2. Collect terrestrial species directly from termite mounds. 3. Collect termites from defecate wood powder, wooden logs, worn-out furniture and from barks of the trees. Collect termites in sterile plastic boxes by wearing sterile gloves and store it in metal storage units (see Note 7) [13]. 3.2 Sample Processing and Surface Sterilization

1. Transfer the collected samples to laboratory, wash thoroughly with tap water to get rid of any adherent dirt and identify the species [12]. 2. All procedures from here onward are carried out under laminar air flow hood. 3. Prior to dissection, termites must be surface sterilized with 1% HgCl2 solution for 3 min followed by a wash in standard iodine solution for 12 s, followed by another wash with 50% ethanol for 12 s and finally rinse it with sterile distilled water [14]. 4. Else, samples can also be surface sterilized by washing thrice with sterile distilled water and by treating with 70% ethyl alcohol for 2 min prior to gut excision [15].

3.3 Aseptic Removal of Termite Gut and Homogenization

Using phosphate buffer/nutrient broth/saline. 1. Dissect the gut of the termite from the terminal abdomen and collect in a microfuge tubes containing 2 mL of phosphate buffer (10 mM Na2HPO4.2H2O, 1.8 mM KH2PO4; pH 7.0). Vortex the content for 5 min. The homogenate thus obtained is serially diluted using sterile phosphate buffer into 10-1, 10-2, and 10-3 and used as inoculum (see Note 8) [1, 15] The above excised gut is also taken into 1 mL of nutrient broth or 10 mL of sterile saline and homogenized using a pestle if phosphate buffer is unavailable. The homogenate is serially diluted in the ratio of 1:10 up to dilution factor 10 3 and used as inoculum [13, 15]. Using Bacteriophage 2. The entire intestinal tract is removed with sterile fine-tipped forceps and is placed on a sterilized slide. 3. Homogenize the guts and transfer into a sterile tube containing 1 mL of stock bacteriophage suspension. (a) Stock bacteriophage suspension is prepared by selecting phages on host ranges of target. (b) Culture the host on PYCa media by placing few drops of selected phages on their host. Incubate the inoculated plates at 27  C for 24 h.

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(c) After incubation, host lawn showing lysis is excised and transferred to PYCa broth at 4  C for 36 h. (d) The broth is filtered using 0.45 μm sterile membrane filter. Stock phage suspension of 1012 pfu phage/mL is prepared and used as stock bacteriophage suspension (see Note 9) [14]. . 4. Incubate the gut mixture for 1 h at 21  C (room temperature) and later use it as inoculum on SCA. 3.4 Isolation and Culturing of Gut Actinobacteria from Termites 3.5

Chitin Agar

A wide variety of culture media is been developed for the growth and enrichment of Actinobacteria from different sources. All media used for isolation is sterilized by autoclaving at 15 psi; 121  C for 20 min. Culture media for Actinobacteria isolated from the gut of termites are listed below. 1. Inoculate 100 μL of serially diluted gut homogenate on the agar plates by spread plate. 2. Incubate the plates aerobically at 28  C up to 4 months and monitor it regularly for microbial growth [16].

3.6

HVA Media

1. Inoculate 100 μL of serially diluted gut homogenate on the agar plates by spread plate. 2. Incubate the plates at 30  C for 4 weeks and monitor regularly for microbial growth [5, 17].

3.7 Defatted Wood Powder Media

1. 100 μL of serially diluted gut homogenate is spread on the agar plates. 2. Incubate the plates at 28–30  C for 4 weeks and monitor it regularly for microbial growth (see Note 10) [5].

3.8

ISP-2

3.9

SCA Media

Hundred microliters of serially diluted gut homogenate is spread on the agar plates. Incubate the plates at 28  C for 1 week and monitor it regularly for microbial growth [5]. 1. The different dilutions of the gut homogenate is spread on agar plates. 2. Incubate it at 28  C for 21 days and monitor it regularly for growth [18].

3.10 Sub-Culturing and Purification of the Isolates

1. Individually pick the isolates obtained on the isolation media showing morphologically distinct colonies. Streak them on fresh agar media to obtain pure isolates. The isolates have to be transferred at least three successive times to ensure maximum purity in the isolates. Pure culture slants thus obtained are frozen at 80  C in International Streptomyces Project

Isolation of Gut Actinobacteria from Termites

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Medium-2 (ISP-2) broth containing 20% glycerol for long term storage [19]. 2. Isolates obtained through phage battery method is purified using oatmeal agar (composition in g/L; oatmeal, 20; agar, 20; pH 7.2) supplemented with 0.1% yeast extract, vitamin mixture 3.7 mg, trace salts 1 mL (see Note 11). The isolates are stored in 20% glycerol at 25  C [17]. 3.11 Identification of the Isolates

4

Identification of the actinobacterial isolates from the pure cultures is done by macroscopic, microscopic and physiological methods as per the Bergey’s Manual of Systematic Biology, second edition and also by 16S rDNA sequencing method [19].

Notes 1. Chitin agar media is beneficial over other media as chitin can be easily broken by actinomycetes than bacteria and some fungal groups. Another reason is that pH 8.0 is known to accelerate the growth of actinomycete in medium [20]. 2. Vitamin mixtures are added to autoclaved media through a filter-sterilized membrane. 3. Defatted wood powder is obtained by extracting Japanese beech powder with ethanol and toluene (2:1) for 24 h by Soxhlet extraction technique. The extract is dried using draft chamber [5]. 4. ISP2 is also known as yeast extract malt extract agar. 5. Termites are grouped into two categories based on the presence and absence of flagellate in their hindgut as lower termites and higher termites, respectively. Lower termites have many types of bacteria in addition to protozoa, while higher termites usually have only the bacteria and a more elaborate anatomy while lacking the protozoa [21, 22]. The major selection criteria were based on the fact that higher termites harbor a predominantly bacterial gut microbiome and that the intestinal pH in each species is slightly acidic or near to neutrality [23]. Direct specimen collection from mounds must be done with utmost safety as they can cause an allergic reaction. 6. Metal boxes must be used instead of wood as storage boxes, as termites can feed on the wood. They also must be placed in a dark room to avoid swarming. 7. The phosphate buffer is an isotonic solution used for maintaining constant pH and it also prevents rupturing of microbial cells due to osmosis [24].

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8. Bacteriophages are used as battery to remove unwanted bacteria during isolation and growth period and to aid in isolation of rare and novel actinomycete members [14]. 9. Each isolating media can be prepared with different pH ranges, namely, 6.0, 6.5, 7.0, and 7.5 as the pH in the guts of the termites are known vary between pH 6.0 and pH 7.5. Nystatin, nalidixic acid and cycloheximide are added to the media in order to reduce the fungal or undesired contaminant during incubation as they are antifungal agents. 10. Defatted wood powder media showed promising results when compared with other media used in the study especially HVA medium. The ratio of the filamentous actinomycete colonies obtained were very high than other isolating media used [5]. 11. Oat meal agar is prepared by cooking or steaming 20 g of oatmeal in 1 L of distilled water for 20 min. The media is filtered through cheese cloth and made up to 1 L using distilled water. Vitamin mixture includes 0.5 mg each of thiamine hydrochloride, riboflavin, niacin, pyridoxine hydrochloride, inositol, calcium pantothenate, 4-aminobenzoic acid and 0.25 mg of biotin. Trace salts solution includes FeSO47H2O, 0.1 g; MnCl2, 0.1 g; ZnSO47H2O, 0.1 g; in 100 mL of distilled water.

5

Conclusion Actinobacteria being ubiquitous in nature have wide range of niches ranging from the volcanic caves to the gut of different organisms. Though their utilities are highly exploited with respect to soil species, the ones found in the gut of termites have not been thoroughly studied [5]. It is very necessary to study interactions at various trophic levels to understand the structural and chemical reciprocity between the guts of the termites and the associated actinobacterial taxa. Though the process is tedious, it important to explore and design improved techniques for isolation and identification of termite gut actinobacteria. Isolation of the microorganisms from the gut of termites can be conducted by various methods. It is necessary to design new techniques for establishing a more efficient and cost-effective method of isolation. Isolation studies should be stepped up further to culture independent techniques like next generation sequencing and metagenomics to unravel the unknown and rare organisms so that the unique intrinsic properties of the microbiota which can be delve into extraction of novel metabolites for a sustainable management system benefitting both termites and mankind.

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References 1. Roes-Hill ML, Rohland J, Burton S (2011) Actinobacteria isolated from termite guts as a source of novel oxidative enzymes. Antoine Van Leeuwenhoek 100:589–605. https://doi. org/10.1007/s10482-011-9614-x 2. Anandan R, Dharumadurai D, Manogaran GP (2016) An introduction to Actinobacteria. In: Dhanasekaran D, Jiang Y (eds) Actinobacteria – basics and biotechnological applications. IntechOpen, Rijeka. https://doi.org/10.5772/ 62329 3. Barrios-Gonzalez J, Ferna´ndez FJ, Tomasini A et al (2005) Secondary metabolites production by solid-state fermentation. Mal J Microbiol 1 (1):1–6 4. Brauman A, Dore J, Eggleton P et al (2000) Molecular phylogenetic profiling of prokaryotic communities in guts of termites with different feeding habits. FEMS Microbiol Ecol 35:27–36. https://doi.org/10.1111/j.15746941.2001.tb00785.x 5. Watanabe Y, Shinzato N, Fukatsu T (2003) Isolation of actinomycetes from termites’ guts. Biosci Biotechnol Biochem 67 (8):1797–1801. https://doi.org/10.1271/ bbb.67.1797 6. Ohkuma M (2003) Termite symbiotic systems: efficient bio-recycling of lignocellulose. Appl Microbial Biotechnol 61:1–9. https://doi. org/10.1007/s00253-002-1189-z 7. Pasti MB, Belli ML (1985) Cellulolytic activity of actinomycetes isolated from termites (Termitidae) gut. FEMS Microbiol Lett 26 (1):107–112. https://doi.org/10.1111/j. 1574-6968.1985.tb01574.x 8. Sch€afer A, Konrad R, Kuhnigk T et al (1995) Hemicellulose-degrading bacteria and yeasts from the termite gut. J Appl Bacteriol 80:471–478 9. Kurtbo¨ke DI, French JRJ (2008) Actinobacterial resources from termite guts for regional bioindustries. Microbiol Aust 29(1):42–44. https://doi.org/10.1071/MA08042 10. Arango RA, Green F, Yang VW (2017) Evaluating the role of Actinobacteria in the gut of wood-feeding termites (Reticulitermes spp.). In: The international research group on wood protection, section 1, biology: paper prepared for the IRG48 scientific conference on wood protection. Ghent, Belgium. pp 4–8 11. Khucharoenphaisan K, Sripairoj N, Sinma K (2012) Isolation and identification of Actinomycetes from termite’s gut against human

pathogen. Asian J Anim Vet Adv 7(1):68–73. https://doi.org/10.3923/ajava.2012.68.73 12. Ali HRK, Hemeda NF, Abdelaliem YF (2019) Symbiotic cellulolytic bacteria from the gut of the subterranean termite Psammotermes hypostoma Desneux and their role in cellulose digestion. AMB Express 9:111. https://doi.org/10. 1186/s13568-019-0830-5 13. Muwawa EM, Budambula NLM, Osiemo ZL et al (2016) Isolation and characterization of some gut microbial symbionts from funguscultivating termites (Macrotermes and Odontotermes spp.). Afr J Microbiol 10 (26):994–1004. https://doi.org/10.5897/ AJMR2016.8060 14. Kurtbo¨ke DI, French JRJ (2007) Use of phage battery to investigate the actinofloral layers of termite gut microflora. J Appl Microbiol 103:722–734. https://doi.org/10.1111/j. 1365-2672.2007.03308.x 15. Rohland J (2010) Investigating the Actinomycete diversity inside the hindgut of an indigenous termite, Microhodotermes viator Dissertation, University of Cape Town 16. Arango RA, Carlson CM, Currie CR et al (2016) Antimicrobial activity of Actinobacteria isolated from the guts of subterranean termites. Environ Entomol 45(6):1415–1423. https:// doi.org/10.1093/ee/nvw126 17. Hayakawa M, Nonomura H (1987) Humic acid vitamin agar, a new medium for the selective isolation of soil actinomycetes. J Ferment Technol 65(5):501–509. https://doi.org/10. 1016/0385-6380(87)90108-7 18. Takizawa M, Colwell RR, Hill RT (1993) Isolation and diversity of Actinomycetes in the Chesapeake Bayt. Appl Environ Microbiol 59 (4):997–1002 19. Jami M, Ghanbari M, Kneifel W et al (2015) Phylogenetic diversity and biological activity of culturable Actinobacteria isolated from freshwater fish gut microbiota. Microbiolog Res 175(2015):6–15. https://doi.org/10.1016/j. micres.2015.01.009 20. Hsu SC, Lockwood JL (1974) Powered chitin agar as a selective medium for enumeration of Actinomycetes in water and soil. Am Soc Microbiol 29(3):422–426 21. Eggleton P (2011) An introduction to termites: biology, taxonomy and functional morphology. In: Bignell DE, Roisin Y, Lo N (eds) Biology of termites: a modern synthesis. Springer, London, p 576

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22. Varma A, Kolli BK, Paul J et al (1994) Lignocellulose degradation by microorganisms from termite hills and termite guts: a survey on the present state of art. Microbiol Rev 15(1):9–28. https://doi.org/10.1111/j.1574-6976.1994. tb00120.x 23. Auer L, Lazuka A, Sillam-Dusse`s D et al (2017) Uncovering the potential of termite gut microbiome for lignocellulose bioconversion in

anaerobic batch bioreactors. Front Microbiol 8:2623. https://doi.org/10.3389/fmicb. 2017.02623 24. Martin NC, Pirie AA, Ford LV et al (2006) The use of phosphate buffered saline for the recovery of cells and spermatozoa from swabs. Sci Justice 46(3):179–184. https://doi.org/10. 1016/S1355-0306(06)71591-X

Chapter 12 Isolation of Gut Actinobacteria from Fishes S. Thejaswini, Sruthy Jojy, Aditi Vijayan, and A. Martin Paul Abstract Actinobacteria are a group of unicellular gram-positive bacteria which are known to contain high guanine and cytosine content in their DNA. Actinobacterial members are widely found, both in land and water habitats. Actinobacteria are known to sediment in water bodies, as a result of water leaching from land. Over the years, gut actinobacteria have gained much attention because of their prime characteristics in animals such as aiding in the hosts’ growth, protection, and nutrition. In addition, the vital contribution to symbiosis is by controlling bacterial diseases in fishes and poultry. Fish gut microbiota has known to play a pivotal role in development of immunity, resistance against pathogens, growth and in providing nutrition to the fish, etc. Actinobacteria are well known for their ability to produce secondary metabolites which are active against pathogenic microorganisms. The measures of gut actinobacteria in fishes are dependent on the sediment composition and fauna residue present in the water body. This is due to the fact that most fishes previously analysed for the composition of gut actinobacteria were detritivore and herbivore feeders. Various methods have been employed over time to isolate the various microbes present in the gut of fishes. Isolation of gut actinobacteria can be done using various methods such as: standard spread plate method using starch casein agar, Kuster’s agar, actinomycete isolation agar. Culture independent, next generation sequencing (NGS) targeting V4 region of the 16S rRNA gene of intestinal DNA has also been discussed as an aiding tool in unravelling mysterious gut microbiota of fishes. The present chapter is principally aimed at providing an insight into techniques of isolation of gut actinobacteria in fishes using different techniques. Key words Gut actinobacteria, Fishes, NGS, Metagenomics

1

Introduction Actinobacteria are a group of unicellular gram-positive bacteria which are present dominantly in the gastrointestinal tract (GIT) of animals. Actinobacterial members are distributed widely in both terrestrial and aquatic habitats, wherein some are free living and others symbiotically associated with plants or animals. Marine sediments are a rich source of bioactive forms of the bacterium. Actinobacteria are known to contain high guanine and cytosine in their DNA [1]. A few strains of Streptomyces species show antifungal and antibacterial activities. They play a significant role in biogeochemical cycling of organic materials in the environment. They are also an

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_12, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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excellent source of antibiotics and novel secondary metabolites. A member of the Actinobacterium group called Bifidobacterium acts as a key regulator of interlukin-10 secretion which plays a significant role during inflammation. Gut endosymbionts like these, act as probiotics and help in improving fish health. Hence, gut endosymbionts are useful in aquaculture to improve fish health. These probiotics reduce stress and enhance the production of immunoglobulin in fish, during adverse conditions. Probiotic bacteria exert many beneficial effects like secreting different types of bacteriocins or antimicrobial proteins, blocking the attachment site for pathogens, producing extracellular enzymes, and enhancing the population of beneficial endosymbiotic bacteria in the gut. They also assist in gut epithelium development. Therefore, bacterial communities influence the physiological characteristics of fishes. Pharmaceutically active antimicrobials and secondary metabolites produced by gut actinobacteria are widely used in the veterinary field, human therapy, and scientific research. Over the years, actinobacteria have gained importance as an aid in agriculture, medicine and in production of food products. With a large diversity of approximately 28,000 species, fishes make up to nearly half of all vertebrate species and exhibit a wide variety of physiologies, ecologies, and natural histories [2]. The gut microbiomes especially in vertebrates are diverse, housing bacteria, fungi, and archaea. The microbes are known to be beneficial to their host in providing enhanced metabolic activity, immunity, protection against pathogens, and so on [3–5]. Thus, fishes represent an important group for understanding the variety and nature of symbioses in vertebrate gut microbial communities [6]. The fish gut microbiota mainly contributes to digestion. It can affect the nutrition, growth, reproduction, population dynamics, and disease vulnerability of the host fish. First attempts in exploring the fish gut microbiome was undertaken decades ago, which accounted for less than 10% of the diversity we know today [7]. The structure and composition of gut microbes is known to vary depending on factors such as host genetics and living environment. For example, gut bacterial diversity research conducted on a group of freshwater fishes showed how microbiomes differed based on diet [8]. Herbivorous fishes showed the presence of gut bacteria that aided in the degradation of cellulose by enzymes like cellulase and amylase. On the other hand, carnivorous fishes showed the presence of bacteria that produced protein degrading enzymes like trypsin. Studies have showed an increase in gut bacterial diversity in fishes that were herbivorous. Trophic levels played an equally important role in deciding the nutrition type of fishes which in turn decided the composition of gut microbiome and the enzymes they produced [9] and the evolutionary history. Other studies carried out also show that the fish gut composition, that is, its richness and diversity vary depending on if the host is adult or

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juvenile. For example, studies have showed that adult zebra fishes had significantly lower gut microbiome richness and diversity when compared to the juveniles [10]. On a broader sense, all known biotic and abiotic factors have their role in gut microbiome of fishes (Fig. 1 near here). Recent studies have, however, showed that the composition of gut microbiome in fishes depend on their physiological and metabolic variations [11]. In the present chapter, emphasis is laid on methodologies of collecting fishes, storage, gut extraction, homogenisation of digesta, isolation and culturing of gut actinobacteria on different isolation media, namely, starch casein agar and Kuster’s agar. Culture independent technique such as NGS for analysing gut microbiota of fishes is also dealt in the chapter as it is most efficient and revolutionised way of understanding and unravelling unknown and rare microbes.

2

Materials

2.1 Sample Collection

2.2

Isolation of Gut

2.3 Homogenization of the Gut

2.4 Culture Media for Isolation of Fish Gut Actinobacteria

l

Fishes from marine, river, freshwater sources.

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Fishing nets.

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Sterile polythene bags.

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Thermal bags.

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Ice cooled box.

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Ice bath.

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Ethanol.

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Laminar air flow hood (LAF).

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Tricaine methanesulfonate.

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Isopropanol.

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Phosphate-buffered saline (PBS).

l

Freezer (
20  C).

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Erlenmeyer flasks (250 mL).

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Saline.

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Rotary shaker with temperature controller.

l

Starch Casein Agar [SCA] (composition in g/L; dipotassium hydrogen orthophosphate 2, calcium carbonate 0.02, ferrous sulfate heptahydrate 0.01, starch 10, potassium nitrate 2, casein 0.3, magnesium sulfate heptahydrate 2, agar 15, pH 7.0  0.1 at 25  C). Media is additionally supplemented with 0.5% (wt/vol) sodium chloride along with nalixidic acid (10 μg/mL), nystatin (25 μg/mL), and cycloheximide (10 μg/mL) (see Note 1).

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Fig. 1 A combination of biotic and abiotic factors which affect the composition, behaviour and metabolic activity of the gut microbiota. These changes affect processes involved in growth, energy storage and health and disease vulnerability in fish apart from digestion

2.5 Subculturing and Purification

l

Kuster’s agar (composition in g/L; glycerol 10, casein 0.3, potassium nitrate 3.0, potassium phosphate 2.0, sodium chloride 2.0, magnesium sulfate 0.05, calcium carbonate 0.02, ferrous sulfate 0.01, agar 16.0; pH 7  0.1 at 25  C). Nalixidic acid (50 mg/L) and cycloheximide (50 mg/L). It can be added to media by filter sterilization (0.2 μm pore size) (see Note 2).

l

Else, the Kuster’s agar can also be supplemented with 50% sea water, nalixidic acid (20 μg/mL), and nystatin (100 μg/mL) for isolation of fish gut actinobacteria [1].

l

Actinomycete isolation agar (composition in g/L; sodium caseinate 2, L-Asparagine 0.1, sodium propionate 4, dipotassium phosphate 0.5, magnesium sulfate 0.1, ferrous sulfate 0.001, glycerol 5, agar 15; pH 8.1  0.2 at 25  C).

l

Streptomyces Project Medium 2 (ISP2) broth.

l

20% glycerol

l

Freezer (
80  C).

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2.6 Sample Preparation for NGS

2.7 DNA Extraction for 16S rRNA Gene Amplification

2.8 Preparation of Illumina Library and Analysis of 16S rRNA Gene Sequence

2.9 Processing and Analysis of 16S rRNA Gene

3

l

Tricaine.

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Membrane filter (0.22 μm).

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Screw-cap tubes.

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Silica beads.

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Tris-EDTA.

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Triton X-100.

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Liquid N2.

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Micropipettes (10–1000 μL).

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Bacterial DNA extraction Kit.

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Vortex.

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Incubator.

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Centrifuge.

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Polymerase chain reaction (PCR).

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PCR primers.

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Illumina adapter sequences.

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DNA template.

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Agarose.

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Electrophoresis unit.

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Illumina sequencer.

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V4 primers.

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Bioinformatic tools and databases.

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Methodology

3.1 Sample Collection

Fishes from marine, river estuaries, freshwater sources is sampled using fishing nets with utmost care, without causing much damage. Fishes are collected in sterile polythene bags or thermal bags, stored in ice cooled box and transported to laboratory within minimum time to avoid growth of microbial contaminants. The samples are processed within 3 h of acquisition and can be refrigerated at 4–8  C.

3.2 Isolation of the Gut

Collected fishes to be anaesthetized in an ice bath for 5–10 min. l

After anaesthetization, surface sterilization is carried out by immersing fishes completely in 70% ethanol for 30 s. All instruments and surfaces is surface sterilized using 70% ethanol and

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instruments are flame sterilized before dissection. The gut is removed separately under aseptic conditions [12, 13]. l

3.3 Homogenization of the Gut

3.4 Culture Media for Isolation of Fish Gut Actinobacteria

Else, the specimens are killed by treating with tricaine methanesulfonate and by disinfecting with 70% isopropanol and gut is excised aseptically for further isolation [14]. The digesta is obtained by squeezing the intestine into a screw cap tube containing phosphate-buffered saline (PBS) and stored at
20  C and thawed prior to homogenization [13].

It can be done in two ways l

After surface sterilization, about 1 g of gut is taken in a 10 mL sterile double strength phosphate-buffered saline (PBS) solution (disodium phosphate, 2–3% (w/v); sodium phosphate, 0–6% (w/v) and sodium chloride, 1–2% (w/v) and is homogenized using tissue homogenizer [12].

l

Else, 1 g of intestinal segments is taken in a 250 mL conical flask containing 100 mL of 0.85% saline and incubated on a rotary shaker for 30 min at 55  C and homogenate obtained is used for microbial isolation (see Note 3).

l

The either way obtained homogenate is serially diluted up to 10
5 dilutions using sterile distilled water. From dilutions of 10
2–10
5, 100 μL of aliquots is spread over the surface of actinobacteria isolating media and incubated [1].

SCA Media l

l

Spread plate the different dilutions of the gut homogenate is on SCA plates. Incubate the plates at 24  C for 28 days and monitor regularly for growth [15]. Kuster’s Agar

l l

Inoculate the different dilutions of homogenate on agar plates. Incubate the plates in dark for 4 weeks at 28  C and monitor regularly for growth [13]. Actinomycete Isolation Agar

l

l

Gut homogenate of 10
2–10
5 dilutions is spread plated on Actinomycete isolation agar plates. Incubate the plates in dark for 4 weeks at 28  C and monitor regularly for growth [13].

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Isolates obtained on the isolation media showing morphologically distinct colonies are individually picked loopful and streaked on fresh agar media to obtain pure isolates. The isolates are transferred at least three successive times to ensure maximum purity in the isolates. Pure culture slants thus obtained to be frozen at
80  C in International Streptomyces Project Medium 2 (ISP2) broth (see Note 4) containing 20% glycerol for long term storage [13].

3.5 Subculturing and Purification

l

3.5.1 Identification of the Isolates

Identification of the actinobacterial isolates from the pure cultures can be done by macroscopic, microscopic, and physiological methods as per the Bergey’s Manual of Systematic Biology, second edition and also by 16S rDNA gene sequencing method [13]. Culture independent techniques. PCR based genetic fingerprinting techniques like temperature gradient gel electrophoresis (TGGE) and denaturing gradient gel electrophoresis (DGGE) are used along with culture dependant techniques of isolation. But these methods have limitations such as, they are time consuming, incompatible with long fragments, some bacterial species show microheterogeneity (variation in chemical structure) which results in multiple bands, they do not have automated analysis facilities and reproducible taxonomy information is not provided by band positions. Hence, to overcome these limitations, metagenomics concept of bacterial community analysis using NGS technique is used. These are accurate, require short period of time, is error-free and large sequencing of data can be done [16] (see Note 5) “(Fig. 2 near here)”.

3.6 Sample Preparation for NGS

Collected fish samples are euthanized by adding tricaine (2.1 mL of 0.4% tricaine per 50 mL fish water) filtered through 0.22 μm before dissection. The aseptically excised intestine are placed in 2 mL screw cap tubes containing 0.1 mm zirconia-silica beads and 200 μL or 400 μL of enzymatic lysis buffer (ELB; Tris-EDTA at pH 8.0 with 0.1% v/v Triton X-100; 0.22 μm filter sterilized) and frozen in liquid N2 [11].

3.7 DNA Extraction for 16S rRNA Gene Amplification

l

l

l

Liquid nitrogen stored digested intestine is thawed at 65  C. DNA is extracted according to Qiagen DNeasy kit method. After thawing, the samples are bead-beaten on high mode on a Mini-Beadbeater-16 instrument (Biospec, Bartlesville, OK) for 1 min with ice chilling. Lysozyme (20 mg/mL) is added to the samples and incubated for 45 min at 30  C. 220 μL or 440 μL buffer AL (Qiagen) is added in addition to 10 μL or 20 μL proteinase K (supplied with Qiagen kit), vortexed well and incubated for 30 min at 56  C.

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Fig. 2 TGGE and DGGE system as a flowchart l

l

After enzymatic digestions, 220 μL or 440 μL of 100% ethanol is added, vortexed, and beads is allowed to settle down to prevent addition to the DNA-binding columns. 700 μL of digestion mix is added to a QIAamp DNA micro or Qiagen DNeasy column and centrifuged for 30 s at 6000  g. Digestion mix is added to columns and centrifuged again if required by discarding the flow-through.

l

For maximum recovery of DNA, the bead is rinsed with a 1:1:1 (v/v/v) mix of ELB, buffer AL, and ethanol and allowed the beads to settle again.

l

The supernatant is carefully collected by avoiding sucking up of beads, and taken in to the column and centrifuged again.

l

After binding of DNA to column as per the manufacturer’s guidelines, followed by washing and DNA is eluted in 34 μL or 100 μL buffer AE [11].

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3.8 Preparation of Illumina Library and Analysis of 16S rRNA Gene Sequence

l

l

l

l

l

l

l

l

3.9 Processing and Analysis of 16S rRNA Gene

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A two-step PCR method is employed to sequence the V4 region of the bacterial 16S rRNA gene by using DNA templates. Firstly, PCR employed primers include (50 to 30 direction) partial Illumina adapter sequences, a 6 nucleotide index, and the V4 targeting forward or reverse primer sequence (see Note 6). PCR is performed in triplicate with approximately equal amounts of DNA template (up to 250 ng per reaction) for each sample. The reactions included a 2 min denature step at 98  C, followed by 22 cycles of denature at 98  C for 20 s, annealing at 50  C for 30 s and extension at 72  C for 20 s, with a final extension at 72  C for 2 min. Triplicate reactions are pooled and cleaned using Zymogen (Irvine, CA) 96-well format spin columns and eluted in 30 μL. 6 μL of the template eluate is used in the second round of PCR cycle with complementary primers of the partial Illumina adapters which have been added in the first PCR round with the rest of the Illumina adapter sequences being same. The second round PCR reactions are similar to the first PCR cycle except for annealing at 66  C is employed with only 12 cycles. Both PCR reactions are made to total reaction volume of 25 μL using Phusion HotStart II polymerase (Thermo Scientific), GC buffer, 200 nM each with HPLC purified primer and Mo Bio (Carlsbad, CA) certified DNA-free water.

l

The product obtained from the second round PCR is subjected to electrophoresis on a agarose gel (1.5%) in 0.5X TBE in order to separate out low molecular weight primer-dimers and smaller expected bands identified as mitochondrial sequences.

l

320–600 base pairs of DNA product are excised from the gel and cleaned up as per the guidelines mentioned in Zymogen’s ZR-96 Zymoclean Gel DNA Recovery Kit. Quantification of the cleaned products is performed using a Qubit (Life Technologies) fluorometer by mixing equal amounts.

l

Above product is submitted in Illumina HiSeq 2000 platform by sequencing on two lanes with paired-end 150 nucleotide reads. Samples showing lesser number of sequences despite good amplification is remixed and again sequenced on a third lane [11].

l

Low quality nucleotides at the ends of the raw reads should be end-trimmed at their first nucleotide below the quality score of 5.

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Read pairs of 100 nucleotides to be obtained on each end by trimming over a 15 nucleotide by cutting an average of 20 quality score using a sliding window quality filtering after trimming the barcodes and primer sequences.

l

The obtained 100 nucleotide reads are aligned to the respective fish genome by using Bowtie and Greengenes core bacterial alignment using mothur to filter reads. The alignment is necessary to pick reads which are not aligned to the primer targeted region of 16S rRNA gene.

l

100 nucleotide sequences pairs those cleared quality and alignment filters are picked and concatenated before demultiplexing by using the combined 12 nucleotide index consisting 6 from each end.

l

For microbial composition analysis, a UCLUST algorithm is used to bin homological sequences of 97% operational taxonomic units (OTUs) against Greengenes. Those reads which failed to cluster against the references has be clustered into OTU by de novo.

l

Abundant sequence from each OTU cluster is picked as the representative sequences. These sequences to be aligned against the trimmed Greengenes core set by filtering with the lane mask and phylogeny can be constructed with FastTree 2 (see Note 7).

l

Taxonomic improvements and taxonomy of representative sequences can be achieved and assigned using Rtax with Greengenes as reference set by trimming accordingly.

l

OTUs which are assigned as chloroplast are removed including those unassigned OTUs. The unassigned OTUs can also be BLAST programmed against NCBI’s nr/nt database to ensure dataset has been purely derived of host sequences.

l

Metagenomic predictions can be inferred by PICRUSt method by obtaining KEGG Orthology (KO) term counts and 16S rRNA gene counts from the bacterial genomes on the Integrated Microbial Genomes (IMG) database version 4.2 and Greengenes respectively [11] “(Fig. 3 near here)”.

Notes 1. Nystatin and cycloheximide are added to starch casein agar in order to reduce the fungal or undesired contaminant during incubation. 2. Nalixidic acid and Nystatin are supplemented with Kuster’s agar to reduce the fungal and gram negative organism during incubation.

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Fig. 3 Steps involved in NGS

3. Incubation during homogenization favors better actinobacteria isolation over other gram-negative and spore-forming bacteria. 4. ISP2 is also known as Yeast Extract Malt Extract Agar. 5. A next-generation sequencing (NGS) technology is used to study the composition and genetic potential of densely populated microbial communities such as gut microbiota. In the past few years, these techniques have been extensively applied to analyze the composition and functional properties of fish microbial communities. Fish microbiota studies have most frequently utilized the 454/Roche pyrosequencing (e.g., the Roche 454 FLX Titanium and FLX+) and Illumina technologies (e.g., the Illumina MiSeq and HiSeq 2000). NGS platforms provide a larger number of reads in a single run, enabling the rapid and cost-effective acquisition of in-depth and accurate sequence data and allowing for the detection of both dominant and low abundance microbial community members [10]. 6. Partial Illumina adapter sequences. 16S_ill_step2_P2: AAGCAGAAGACGGCATACGAGAT CGGTCTCGGCATTCCTGC. 16S_ill_step2_P1: AATGATACGGCGACCACCGAGATCT ACACTCTTTCCCTACACGACG. “V4-reverse” primer is slightly modified to reduce annealing temperature closer to the reverse primer version of the V4 forward primer. V4-reverse primer version of the V4 forward primer is used. V4F_b: CGGTCTCGGCATTCCTGCTGAACCGCTCT TCCGATXXXXXXGTGTGCCAGCMGCCGCGG;

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V4R_b: ACACTCTTTCCCTACACGACGCTCTTCC GATCTXXXXXXTACNVGGGTATCTAATCC). V4F_b and V4R_b used in 16S PCR, in round 1. Bold characters denote the sequences targeting the 16S rRNA gene. Underlined nucleotide sequences indicate overlapping bases in round 1 and round 2 PCR primers. 7. Based on expected error rates of simulations, an OTU cluster size of minimum 4 can be cut and used by chopping off at least 2 sequences per OTU is required to lower the rate of spurious OTUs production. Representative sequence is picked from OTU cluster having abundant sequence.

5

Conclusion The gut of most animals is an abode to a variety of microorganisms which bring forth multiple beneficial effects to the host animal. Actinobacteria are one such group of dominant organisms which are widely being studied along with other gut related microbes. The studies undertaken so far have dealt with finding the composition, beneficial effects to their hosts and in keeping diseases away thus aiding in the growth of fishes. Development of new techniques along with the use of classical methods of isolation has improved aquaculture practices leading to increase in exploration of gut microbiota in fishes. Understanding the fish gut microbiota in further depth will help us devise novel strategies in upholding the health of the fish by altering its gut microbiota. Like in humans, extensive studies have been carried out to understand how microbes behave and how they influence individual’s health. Similar studies when carried out on fishes will certainly shed better knowledge and unravel the secrets as to how each microbe is useful or harmful to the fish. Over the years, it is becoming clear that the gut microbiome highly influences and exerts effects on its host in many ways through secretions, the diversity and function. The gut microbiome in many fishes has been shown to be a probiotic just like lactobacillus is in humans. They are known to be probiotics by reducing stress, secreting different types of bacteriocins or antimicrobial proteins, producing extracellular enzymes, and enhancing the population of beneficial endosymbiotic bacteria in the gut. Thus improved understanding and manipulation of microbial community using rapid cutting edge techniques apart from culture based techniques will definitely increase gut microbiota knowledge exponentially which will be beneficial for both the fishes and humans for developing better health management strategies.

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References 1. Vignesh A, Ayswarya S, Gopikrishnan V, Radhakrishnan M (2019) Bioactive potential of Actinobacteria isolated from the gut of marine fishes. Indian J Mar Sci 48(8):1280–1285 2. Sandi W, Rawls JF (2012) Intestinal microbiota composition in fishes is influenced by host ecology and environment. Mol Ecol 21 (13):3100–3102. https://doi.org/10.1111/j. 1365-294X.2012.05646.x 3. Sophie V, Saccheri F, Mignot G et al (2013) The intestinal microbiota modulates the anticancer immune effects of cyclophosphamide. Science 342(6161):971–976. https://doi. org/10.1126/science.1240537 4. David LA, Materna AC, Friedman J et al (2014) Host lifestyle affects human microbiota on daily timescales. Genome Biol 15(7):1–15. https://doi.org/10.1186/gb-2014-15-7-r89 5. Bird AR, Conlon MA, Christophersen CT et al (2010) Resistant starch, large bowel fermentation and a broader perspective of prebiotics and probiotics. Benef Microbes 1(4):423–431. https://doi.org/10.3920/BM2010.0041 6. Sukanta NK (2010) Role of gastrointestinal microbiota in fish. Aquac Res 41 (11):1553–1573. https://doi.org/10.1111/j. 1365-2109.2010.02546.x 7. Amann RI, Ludwig W, Schleifer KH (1995) Phylogenetic identification and in situ detection of individual microbial cells without cultivation. Microbial Mol Biol Rev 59(1):143–169 8. Ley RE, Hamady M, Lozupone C et al (2008) Evolution and their gut microbes. Science 320 (5883):1647–1652. https://doi.org/10. 1126/science.1155725 9. Liu H, Guo X, Gooneratne R et al (2016) The gut microbiome and degradation enzyme activity of wild freshwater fishes influenced by

their trophic levels. Sci Rep 6:1–12. https:// doi.org/10.1038/srep24340 10. Ghanbari M, Kneifel W, Domig KJ (2015) A new view of the fish gut microbiome: advances from next-generation sequencing. Aquaculture 448:464–475. https://doi.org/10.1016/j. aquaculture.2015.06.033 11. Stephens WZ, Burns AR, Stagaman K (2016) The composition of the zebrafish intestinal microbial community varies across development. ISME J 10(3):644–654. https://doi. org/10.1038/ismej.2015.140 12. Sivasubramanian K, Ravichandran S, Kavitha R (2012) Isolation and characterization of gut micro biota from some estuarine fishes. Mar Sci 2(2):1–6. https://doi.org/10.5923/j.ms. 20120202.01 13. Jami M, Ghanbari M, Kneifel W et al (2015) Phylogenetic diversity and biological activity of culturable Actinobacteria isolated from freshwater fish gut microbiota. Microbiol Res 175 (2015):6–15. https://doi.org/10.1016/j. micres.2015.01.009 14. MacFarlane RD, McLaughlin JJ, Bullock GL (1986) Quantitative and qualitative studies of gut flora in striped bass from estuarine and coastal marine environments. J Wildl Dis 22 (3):344–348. https://doi.org/10.7589/ 0090-3558-22.3.344 15. Takizawa M, Colwell RR, Hill RT (1993) Isolation and diversity of Actinomycetes in the Chesapeake Bayt. Appl Environ Microbiol 59 (4):997–1002 16. Banerjee G, Ray AK (2017) Bacterial symbiosis in the fish gut and its role in health and metabolism. Symbiosis 72(1):1–11. https://doi.org/ 10.1007/s13199-016-0441-8

Chapter 13 Isolation of Actinobacteria from Mangrove Plants V. Ambikapathy, S. Babu, A. Anbukumaran, A. S. Shijila Rani, and P. Prakash Abstract Actinobacteria resemble bacteria and fungi, and are widely distributed in both terrestrial and aquatic ecosystems in soil, where they play an essential role in recycling refractory biomaterials by decomposing complex mixtures of polymers in dead plants, animals, and fungal materials. The filamentous actinobacteria are isolated from surface-sterilized root tissues of healthy wheat plants (Triticum aestivum L.). Actinobacteria are widely distributed in the natural habitats and are used for various methods, namely, pretreatment, enrichment, combinations of antibiotics, and specific isolation media, and some novel methods have been adapted for isolation. Marine Actinobacteria were also isolated using various methods and found to be an important source of novel secondary metabolites. Rare Actinobacteria are isolated using combinations of methods or high-throughput screening methods. Endophytic Actinobacteria can be isolated by mostly chemical treatment for surface sterilization followed by serial dilution. Strategies for a range of isolation methods have been mentioned for the discovery of various genera of Actinobacteria. Key words Mangrove plants, Actinobacteria, Actinobacteria isolation, Agar

1

Introduction Mangrove forests are among the world’s most productive ecosystems that enrich coastal water, yield commercial forest products, protect coastlines, and support coastal fisheries. However, mangroves exist under conditions of high salinity, extreme tides, strong winds, high temperature, and muddy and anaerobic soils. This group of plants has highly developed morphological, biological, ecological, and physiological adaptations to extreme conditions. Mangroves are woody plants that grow at the interface between land and sea in tropical and subtropical latitudes. These plants are associated with microbes, namely, fungi and bacteria, and Actinobacteria constitute the mangrove forest community or mangal [1]. The term “Actinobacteria” was derived from Greek “atkis” (a ray) and “mykes” (fungus) and has features of both bacteria and fungi [2]. Actinomycetes show filamentous bacteria belonging

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_13, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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to the order Actinomycetales, especially Micromonospora and Streptomyces strains, and have a unique and proven capacity to produce novel antibiotics [3]; hence, the continued interest in screening such organisms for new bioactive metabolites [4]. Traditionally, Actinobacteria have been isolated from the terrestrial sources only and the first report of mycelium-forming Actinobacteria being recovered from marine sediments appeared several decades ago [5]. Recently, marine-derived Actinobacteria have been recognized as a source of novel antibiotic and anticancer agents with unusual structures and properties [6]. Actinobacteria represent a ubiquitous group of microbes widely distributed in natural ecosystems around the world and very significant with regard to the recycling of organic matter [7]. Actinobacteria play a major part in the rhizosphere microbial community in the turnover of recalcitrant plant organic matter, and thus the rhizosphere region is considered one of the best habitats for the isolation of these microorganisms (Table 1; Fig. 1).

Table 1 Isolation of Actinobacteria associated with mangrove plants

S. no Actinobacteria

Mangrove plants

Location

Country References

1

Streptomyces xantholiticus

Rhizophora apiculata

Pichavaram

India

[8]

2

Streptomyces coelicolor

Avicennia marina

Parangipettai

India

[8]

3

Streptomyces avicenniae

Avicennia mariana

National mangrove reserve in Fujian Province,

China

[9]

4

Streptomyces nigra Avicennia marina

Zhangzhou, Fujian Province

China

[10]

5

Streptomyces globisporus

Avicennia officinalis

Kakinada

India

[11]

6

Streptomyces sp.

Rhizophora mucronata

Puducherry

India

[12]

Epiphytic / Phylloplane

Surface/ external of plant parts

Endophytic

Colonize internal tissues of plants

Mangrove plants

Fig. 1 Types of Actinobacteria associations from mangrove plants

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2 2.1

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Materials and Methods Requirements

1. Actinobacteria isolation agar (HiMedia): (Composition: sodium caseinate—2.000 g/l; L-asparagine—0.100 g/l; sodium propionate—4.000 g/l; dipotassium phosphate—0.500 g/l; magnesium sulfate—0.100 g/l; ferrous sulfate—0.001 g/l; agar—15.000 g/l, water 1000 ml; final pH [at 25  C] 8.1  0.2). 2. Rhizophora apiculata, Avicennia marina (leaves/ roots/ stem etc.). 3. Petri plates. 4. Ethanol. 5. 0.1% mercuric chloride. 6. Scissors (knife). 7. Pipette. 8. Spirit lamp. 9. Hot air oven. 10. Forceps.

2.2 Isolation Methods 2.2.1 Method 1

1. Collect healthy Rhizophora apiculata and Avicennia marina (leaves/roots/stems etc.) from mangrove environment of Muthupet, Tamil Nadu, India. 2. Prepare and sterilize the Actinobacteria isolation media at 121  C for 30 min in an autoclave. 3. Supplement the molten Actinobacteria isolation media at 45  C with nalidixic acid (suppress the growth of bacteria) and nystatin (suppress the growth of fungi). 4. Pour the medium into a sterile petri plate and allow for solidification. 5. Take the healthy mangrove roots and leaves and wash in running water to remove epiphytes, soil debris, or dust particles on the surface. 6. Follow the three-step surface sterilization procedure: wash the root and leaf sample with 99% ethanol, followed by 6 min immersion in 0.1% mercuric chloride solution, and then wash in 99% ethanol and dry. 7. Aseptically cut the surface-sterilized root and leaf material at a size of 1 cm and inoculate in Actinobacteria isolation media. 8. Incubate the plates at 30  C for 2–4 weeks. 9. Observe the plate after the incubation period. 10. Record and tabulate the results.

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2.2.2 Method 2

1. Collect healthy Rhizophora apiculata and Avicennia marina (leaves/roots/stems, etc.) from the mangrove environment. 2. Prepare and sterilize the Actinobacteria isolation media at 121  C for 30 min in an autoclave. 3. Supplement the molten Actinobacteria isolation media at 45  C with nalidixic acid (suppress the growth of bacteria) and nystatin (suppress the growth of fungi). 4. Pour the medium into a sterile petri plate and allow for solidification. 5. Take the healthy mangrove roots/leaves/stems and wash in running water to remove epiphytes, soil debris, or dust particles on the surface. 6. Follow the three-step surface sterilization procedure: wash the root and leaf sample with 99% ethanol, followed by 6 min immersion in 0.1% mercuric chloride solution, and then wash in 99% ethanol and dry. 7. The surface sterilized plant tissues can be macerated and thoroughly homogenized with phosphate buffer or other suitable liquid medium (Fig. 2).

Fig. 2 Flow chart explaining the isolation of endophytic Actinobacteria

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8. Crush 1 g of surface-sterilized Rhizophora apiculata and Avicennia marina (leaves/roots/stems, etc.) parts in 10 ml of sterilized distilled water with the help of a mortar and pestle (Fig. 2). 9. Take 9 ml of distilled water in seven test tubes and transfer 1-ml sample in first test tube and then transfer to another test tube (10 1) followed by serially diluting in six test tubes (10 2 to 10 7 dilution) after 1-ml sample taken from 10 7 dilution test tube has been discarded. 10. The suitable dilutions for Actinobacteria isolation are 10 10 3, and 10 4.

2

,

11. Take 0.1 ml of the 10 2 dilution and spread over the Actinobacteria isolation agar medium and subsequently the 10 3 and 10 4 dilutions. 12. After inoculation wait 5 min to pre-incubation then the plate was incubated in an inverted position at 30  C for 2–4 weeks. 13. After the incubation period, observe the plates. 14. Record and tabulate the results. 2.3 Isolation of Epiphytic/Phylloplane Actinobacteria from Mangrove Plants: Procedure

1. Collect healthy Rhizophora apiculata and Avicennia marina (leaves/roots/stems, etc.) from the mangrove environment of Muthupet, Tamil Nadu, India. 2. Prepare and sterilize the Actinobacteria isolation media at 121  C for 30 min in an autoclave. 3. Supplement the molten Actinobacteria isolation media at 45  C with nalidixic acid (suppress the growth of bacteria) and nystatin (suppress the growth of fungi). 4. Pour the medium into a sterile petri plate and allow for solidification. 5. Take the healthy mangrove roots/leaves/stems and wash/soak in sterile NaCl 0.9% with shaking for 1 h at 37  C to isolate epiphytic actinobacteria (Fig. 3). 6. Take 9 ml sterile saline in seven test tubes and a 1-ml sample and then transfer to another test tube (10 1) followed by serial dilution in six test tubes (10 2 to 10 7 dilution) after a 1-ml sample taken from 10 7 dilution test tube has been discarded. 7. The suitable dilutions of Actinobacteria isolation are 10 10 3, and 10 4 dilution.

2

,

8. Take 0.1 ml of 10 2 dilution and spread over the Actinobacteria isolation agar medium and subsequently the 10 3 and 10 4 dilutions. 9. after inoculation wait 5 min to pre-incubation then the plate was incubated in an inverted position at 30  C for 2–4 weeks.

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Fig. 3 Flow chart explained by isolation of epiphytic actinobacteria Table 2 Isolation of Actinobacteria from leaf, root, and stem of mangrove plants S. no

Segment

No. of Actinobacteria

1

Leaf

26

2

Root

22

3

Stem

19

10. Observe the plates after the incubation period. 11. Record and tabulate the results, as mentioned in Table 2 [13].

3

Observation The Actinobacteria colony morphologies are powdery, filamentous growths, aerial mycelium, and tough, dusty, and frequently pigmented colonies (Table 3).

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Table 3 Isolation of Actinobacteria from leaf, root, and stem of mangrove plants using the standard plate count method No. of Actinobacteria (CFU/ml) S. no

Dilutions

Leaf

Root

Stem

1

10–2

25

14

19

10

3

19

10

9

10

4

11

9

4

2 3

4

Results The given sample 26 colonies/segment observed. One gram of leaf sample recorded 25  10

2

CFU/ml.

References 1. Kathiresan NK, Bingham BL (2001) Biology of mangroves and mangrove ecosystems. Adv Marine Biol 40:81–251 2. Das S, Lyla PS, Khan SA (2008) Characterization and identification of marine Actinobacteria existing systems, complexities and future directions. Natl Acad Sci Lett 31(5):149–160 3. Bentley SD, Chater KF, Cerdeno-Tarraga AM, Challis GL, Thompson NR, James KD, Harris DE, Quail MA, Kieser H, Harper D (2002) Complete genome sequence of the model actinomycete Streptomyces coelicolor A3(2). Nature 417:141–147 4. Lazzarini A, Cavaletti L, Toppo G, Marinelli F (2000) Rare genera of Actinobacteria as potential producers of new antibiotics. Antonie Van Leeuwenhoek 78:388–405 5. Weyland H (1969) Actinobacteria in North Sea and Atlantic Ocean sediments. Nature 223:858 6. Jensen PR, Gontang E, Mafnas C, Mincer TJ, Fenical W (2005) Culturable marine actinomycete diversity from tropical Pacific Ocean sediments. Environ Microbiol 7:1039–1048 7. Srinivasan MC, Laxman RS, Deshpande MV (1991) Physiology and nutrition aspects of actinomycetes—an overview. World J Microbiol Biotech 7:171–184 8. Gayathri P, Muralikrishnan V (2013) Isolation and characterization of endophytic

Actinomycetes from mangrove plant for antimicrobial activity. Int J Curr Microbiol App Sci 2(11):78–89 9. Xiao J, Wang Y, Luo Y (2009) Streptomyces avicenniae sp. nov., a novel actinomycete isolated from the rhizosphere of the mangrove plant Avicennia mariana. Int J Syst Evol Microbiol 59(10):2624–2628 10. Chen C, Ye Y, Wang R (2018) Streptomyces nigra sp. nov. is a novel actinobacterium isolated from mangrove soil and exerts a potent antitumor activity in vitro. Front Microbiol 9:1587 11. Pooja S, Yandigeri MS, Malviya N, Kumar R, Arora DK (2015) Isolation and characterization of Streptomycetes with plant growth promoting potential from mangrove ecosystem. Polish J Microbiol 64(4):339–349 12. Janaki TB, Nayak K, Ganesan T (2014) Different pre-treatment methods in selective isolation of Actinomycetes from mangrove sediments of Ariyankuppam Back water Estuary, Puducherry. Int J Adv Res Biol Sci 1 (6):154–163 13. Thompson P, Bailey MJ, Ellis RJ, Purdy KJ (1993) Subgrouping of bacterial populations by cellular fatty acid composition. FEMS Microbiol Lett 102:75–84

Chapter 14 Isolation of Actinobacteria from Seaweeds Apsara S. Babu and Kokati Venkata Bhaskara Rao Abstract The marine environment has become a promising source of microorganisms with the ability to produce novel bioactive compounds having pharmaceutical and clinical applications. For the past few years, isolation of bioactive compounds from marine actinomycetes has increased to a greater extent. Marine algae or ocean weeds remain a less explored source in search of actinobacteria producing secondary metabolites. In this chapter, we discuss the isolation techniques of actinobacteria from seaweeds. Key words Actinobacteria, Endosymbionts, Isolation, Marine, Seaweeds

1

Introduction Seaweeds also known as marine algae are multicellular photosynthetic eukaryotes that lack specialized tissues such as root system and vascular structures [1]. In coastal areas, they are found in the subtidal region where photosynthetic light of 0.01% is available. Some of the factors such as light, plant pigments, depth, temperature, and tides determine the dissemination and variation between seaweeds [2]. Based on their pigments, marine algae are classified into red, brown, and green algae. Apart from this, seaweeds turned out to be a prominent source of bioactive compounds with cytotoxic, antitumor, anticancer, and antihypertensive potentialities [3, 4]. Seaweeds produce a massive amount of organic carbon, thereby nourishing a nutrient-rich environment for microorganisms [5]. In addition to that, the microbial symbionts acquire nutrients and shelter from seaweeds and in return provide chemical defense to the host [1]. Actinobacteria are copious producers of novel bioactive compounds with therapeutic and industrial potentials [6]. Many of the secondary metabolites have proven to be antibacterial, antifungal, and antiviral agents. Actinobacteria being widely present in the marine habitat share a symbiotic relation with a wide range of marine organisms. Among rare actinomycetes,

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_14, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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Table 1 Seaweed-associated actinobacteria and their sampling locations S. No Actinobacteria

Seaweeds

Locations

Reference

1.

Streptomyces sp.

Laminaria ochroleuca

Intertidal area of the rocky shore, Mindelo, Northern Portugal

[9]

2.

Actinobacterial strain C1 and C2

Caulerpa scalpelliformis

Intertidal zone of Veraval coastal region, Gujarat, India

[8]

3.

Endophytic actinomycetes strains NMS 1–5

Caulerpa racemosa

Gulf of Mannar region, Rameswaram, Tamil Nadu, India

[5]

4.

Actinomycetes SW A4 Sargassum fluitans

Thirumullavaram Beach, Kollam, Kerala, India

[10]

5.

Streptomyces cyaneofuscatus

Gijon, central Cantabrian Sea, Spain

[4]

6.

Actinomycete DMS 3 Caulerpa taxifolia

[6] Gulf of Mannar region, Mandapam coastal area, Rameswaram, Tamil Nadu, India

7.

Streptomyces sp. YM5-799

Charastunai Beach, Muroran, Japan

Fucus spiralis

Analipus japonicus

[11]

endophytic actinomycetes inhabit the innermost tissues of plants and algae without posing damage to the host [7]. Nevertheless, a few researches have been carried out related to actinobacteria associated with the seaweed [8]. Some of the seaweed-associated actinobacteria and their sampling locations are described in Table 1. This chapter describes the various protocols for isolation of actinobacteria from seaweeds.

2

Materials

2.1 Isolation Media and Components

1. Starch Casein Agar (SCA). 2. Yeast Malt Agar (ISP2). 3. Oatmeal agar (ISP3). 4. Inorganic Salt Starch (ISP4). 5. Glycerol Asparagine Agar Base (ISP5). 6. Tyrosine Agar (ISP7). 7. Actinomycetes Isolation Agar (AIA). 8. Zobell Marine Agar (ZMA). 9. Starch Casein Nitrate Agar (SCN) (Table 2). 10. Raffinose Histidine agar (Table 3).

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Table 2 Media components of Starch Casein Nitrate Agar (SCN) Components

Amount

Soluble starch

10 g

Casein

0.3 g

K2HPO4

2g

KNO3

2g

NaCl

2g

CaCO3

0.02 g

MgSO4.7H2O

0.05 g

FeSO4.7H2O

0.01 g

Agar

17 g

Table 3 Media components of Raffinose Histidine agar Components

Amount

Raffinose

10 g

L-Histidine

1g

K2HPO4

1g

MgSO4.7H2O

0.5 g

FeSO4.7H2O

0.01 g

Agar

17 g

11. Nalidixic acid (50 mg/L). 12. Cycloheximide (50 mg/L). 13. Streptomycin (100 mg/L). 14. 70% Ethanol [6, 8, 9]. 2.2 Laboratory Equipment

1. Mortar and pestle. 2. Erlenmeyer flask. 3. Petri plates. 4. Micropipettes.

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Methodology

3.1 Sample Collection and Preprocessing

1. Collect fresh seaweeds of the genera Macrocystis, Porphyra, Sargassum, and Monostroma (leaves, twigs, and buds) in sterile polyethylene bags filled with seawater and transport to the laboratory. 2. Wash the seaweeds properly with sterile seawater and double distilled water to remove the loosely bound microbes and associated marine debris. 3. Store the samples at 4  C for later use [4, 6–9].

3.2 Isolation of Actinobacteria from Seaweed

1. Aseptically excise the clean seaweed into approximately 2 cm long pieces. 2. Wash the excised samples five times with artificial sterile seawater. 3. Homogenize the samples aseptically using a mortar and pestle. 4. Aliquot 1 ml of seaweed extracts and serially dilute the sample up to 10 8 dilution with seawater. 5. Pipette 1 ml aliquot of 10 4 dilutions on to various agar plates supplemented with an antibacterial agent like nalidixic acid and an antifungal agent like cycloheximide. 6. Incubate the plates at 28  C for 7–14 days for actinobacteria and 7–21 days for Streptomyces sp. (Fig. 1).

Seaweeds

Surface sterilize

1 ml of 10-4 diluon

10-8 10-7 10-6 10-5 10-4 10-3 10-2 10-1

Fig. 1 Schematic representation of isolation of actinobacteria from seaweeds

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7. Identify the isolates based on morphological and microscopical examination [4, 8, 9, 12, 13]. 3.3 Isolation of Endophytic Actinomycetes from Algae

1. Collect the excised algal samples (10 mm length) and surface sterilize with ethanol (70%) for 1 min, thereafter in sodium hypochlorite for 3 min and once again with ethanol (70%) for 30 s. 2. Then surface sterilize with double distilled water for 2 min and remove excess moisture content using sterile cotton. 3. Place the algal samples in starch casein agar media (SCA) supplemented with antibacterial agent streptomycin. 4. Incubate the plates at 28  C for 6–7 days. 5. After incubation, isolate the colonies and subculture onto actinomycetes isolation agar (AIA) [6, 7, 13].

References 1. Egan S, Harder T, Burke C, Steinberg P, Kjelleberg S, Thomas T (2013) The seaweed holobiont: understanding seaweed–bacteria interactions. FEMS Microbiol Rev 37 (3):462–476 2. Dhargalkar VK, Kavlekar DP (2004) In: Verlecar XN, Kavlekar D (eds) Seaweeds—a field manual, 1st edn. National Institute of Oceanography, Dona Paula, 42 pp. http://drs.nio. org/drs/bitstream/2264/96/1/SeaweedsManual.pdf 3. Nathani NM, Mootapally C, Gadhvi IR, Maitreya B, Joshi CG (2020) Marine niche: applications in pharmaceutical sciences, 1st edn. Springer, Singapore. https://doi.org/10. 1007/978-981-15-5017-1 ˜ a AF, Fiedler HP, Nava H, Gonza´lez V, 4. Bran Sarmiento-Vizcaı´no A, Molina A et al (2015) Two Streptomyces species producing antibiotic, antitumor, and anti-inflammatory compounds are widespread among intertidal macroalgae and deep-sea coral reef invertebrates from the central Cantabrian Sea. Microb Ecol 69 (3):512–524 5. Armstrong E, Yan L, Boyd KG, Wright PC, Burgess JG (2001) The symbiotic role of marine microbes on living surfaces. Hydrobiologia 461(1):37–40 6. Rajivgandhi G, Ramachandran G, Maruthupandy M, Saravanakumar S,

Manoharan N, Viji R (2018) Antibacterial effect of endophytic actinomycetes from marine algae against multi drug resistant gram negative bacteria. Exam Mar Biol Oceanogr 1 (4):1–8 7. Ramachandran G, Rajivgandhi G, Maruthupandy M, Manoharan N (2019) Extraction and partial purification of secondary metabolites from endophytic actinomycetes of marine green algae Caulerpa racemosa against multi drug resistant uropathogens. Biocatal Agric Biotechnol 17:750–757 8. Majethiya V, Gohel S (2020) Isolation and screening of extracellular enzymes producing actinobacteria associated with Sea-Weed. Available at SSRN 3560095 9. Gira˜o M, Ribeiro I, Ribeiro T, Azevedo IC, Pereira F, Urbatzka R et al (2019) Actinobacteria isolated from Laminaria ochroleuca: a source of new bioactive compounds. Front Microbiol 10:683 10. Thomas N, Edwin D, Boby T (2020) Identification of an antibacterial potential marine Streptomyces sps from Sargassum fluitans. Int J Res Appl Sci Biotechnol 7(3):53–58 11. Valliappan K, Sun W, Li Z (2014) Marine actinobacteria associated with marine organisms and their potentials in producing pharmaceutical natural products. Appl Microbiol Biotechnol 98(17):7365–7377

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12. Srinivasan R, Sengali Ragunath K, Karuppiah V, Radhesh Krishnan S, Gracy M (2017) Isolation and screening of seaweed associated microbes for development of marine based agri–inputs. Seaweed Res Utiln 39:39–46

13. Wells JM, Raju BC, Hung HY, Weisburg WG, Mandelco-Paul L, Brenner DJ (1987) Xylella fastidiosa gen. nov., sp. nov: gram-negative, xylem-limited, fastidious plant bacteria related to Xanthomonas spp. Int J Syst Evol Microbiol 37(2):136–143

Chapter 15 Isolation of Actinobacteria from Hills M. Veerapagu, K. R. Jeya, and A. Sankaranarayanan Abstract Actinobacteria are a large heterogeneous filamentous group of gram positive to gram variable bacteria containing a high ratio of guanine and cytosine content in their DNA. They are distributed in a wide environment not exempted to terrestrial, marine, and freshwater but mainly soil. They are known for their rich source of the bioactive substance having pharmacological potential. Hill soils are formed by the deposition of organic matter from forest growth, are rich in humus, and act as enriched habitats for the isolation of actinobacteria. Key words Actinobacteria, Hill soil, Isolation, Gram positive, Bioactive substance

1

Introduction The actinobacteria are notably one of the largest phyla actinobacteria that belong to the order Actinomycetales. They are present in huge numbers in a diverse environment. They form preeminent microbes in agricultural, compost, garden soil, and unique environment hill soil. They produce various secondary metabolites such as antibiotics, enzymes, enzyme inhibitors, pesticides, herbicides, immunomodulators, and anticancer agents [1, 2]. Hill soil is a complex environment that affords physical, biological, and nutritional variability. It serves as the source of nutrients for the growth of microbes. Actinobacteria are pivotal in the environment because of their broad range of metabolic processes and biotransformation. They include degradation of insoluble remains of other organisms such as lignocellulose and chitin and are known to secrete humic acid-like substances which improve soil fertility [3]. The isolation of Nocardiopsis flavescens was isolated from soil samples of Valparai hill (latitude 10.37
N and longitude 76.97
E), 11
360 000 N 78
330 000 E) of Tamil Nadu state, India [4]. Streptomyces kurssanovii was isolated from Talakona hill (Lat. 13
480 4200 N;

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_15, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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Long. 79
120 5600 E) soil sample of Andhra Pradesh state of India [5]. Several actinomycetes Micromonospora, Polymorphospora, Streptomyces, Streptacidiphilus, Astrosporangium, Microbispora, Acrocarpospora, Nocardia, Actinomadura, Kocuria, and Shimazuella were isolated from Padawan hill paddy field (N01
13.2480 E 110
18.6800 ) of Malaysia [6]. The soil remains a conducive source of novel actinobacteria. The type of actinobacteria present in the soil is greatly altered by primary ecological factors, such as nutrient, aeration, pH, temperature, salinity, and moisture and organic matter content. Indeed, the success in isolating large numbers of specific actinobacteria can be highly reliant on the choice of environmental samples. It is unrivaled to collect the soil samples from a depth of 5–20 cm in a sterile container. Pretreatment of soil can stimulate the isolation of actinomycetes by either promoting growth of actinomycetes or eliminating most unwanted gram negative bacteria. A simple pretreatment method is drying soil sample in the air because spores of actinobacteria are resistant to desiccation than most bacteria present in soil and hence, heat drying soil sample at 120
C for 1 h favors the growth of Streptomyces and other rare genera Spirilliplanes, Actinomydura, Microbispora etc. on humic acid vitamin (HV) agar [7, 8]. The isolation of Nocardia species from air-dried soil suspension by sucrose gradient centrifugation method [9]. Motile actinomycetes can be isolated by growing motile actinomycetes in the supernatant in a medium containing nalidixic acid and trimethoprim after centrifugation of soil suspension eliminates Streptomycetes and other non-motile actinomycetes [10]. Further to heat treatment of soil sample, different chemicals benzethonium chloride, chlorhexidine gluconate, phenol, SDS, and antibiotics were also used for the isolation of actinobacteria depending upon spore resistance. Physical, chemical, and combination of both methods can be used for selective isolation of actinomycetes species [11]. Isolation of actinobacteria was performed and reported [12] from drying soil sample in the air at room temperature for 3–5 days and heat-treated at 55
C for 10 min. As per the earlier published report, physical treatment and chemical concentration influence the isolation of actinomycetes from soil [13]. It is noted that dry heat treatment at 40
C is an effective pretreatment, centrifugation eliminates the unwanted soil debris, phenol and calcium carbonate are more effective chemical treatments, and the addition of antibiotics in the isolation medium is useful for isolation of actinomycetes by preventing bacterial and fungal growth.

Isolation of Actinobacteria from Hills

2

3

91

Materials Required l

Hill soil sample.

l

Starch casein agar medium: (Starch: 10 g, potassium nitrate: 2 g, sodium chloride: 2 g, dipotassium hydrogen phosphate: 2 g, magnesium sulfate: 0.05 g, ferrous sulfate: 0.01 g, calcium carbonate: 0.02 g, agar: 15 g, double-distilled water: 1000 ml, pH: 7.0).

l

Double-distilled water.

l

Nalidixic acid (Himedia).

l

Nystatin (Himedia).

l

70% v/v ethanol.

l

Conical flask.

l

Test tubes.

l

Petri plate 100  15 mm (Himedia).

l

Micropipettes.

l

L-shaped glass spreader.

l

Bunsen burner.

l

Sterile plastic bags/bottles.

l

Auger/spade.

l

Sieve.

l

Hot air oven.

l

Digital balance.

l

Water bath.

l

Autoclave.

l

Laminar airflow.

l

Plate Master (Himedia).

l

Incubator.

Methodology

3.1 Collections of Hill Soil Sample

1. Remove the surface litter, grass, debris, etc., from the sampling point. 2. With the aid of a soil auger plow a depth of 15 cm and draw the soil sample. 3. If auger is not available use a spade to make a “V” shaped cut to a depth of 15 cm (Fig. 1) [14].

92

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1 inch / 2.5cm 6 inches/ 15 cm

Fig. 1 V-shaped method for soil sample collection

4. Remove a thick slice of soil from top to bottom of exposed face (2.5 cm) of the “V” shaped cut. 5. Transfer the soil sample into an appropriate sterile container. 3.2 Pretreatment of Soil Sample

1. Air dry the soil sample at room temperature for 1 week [15]. 2. Sieve the soil samples through a 250 μm pore size sieve to remove gravel and debris [16]. 3. Heat treat the soil sample at 50
C for 1 h in a hot air oven [17].

3.3 Serial Dilution of Soil

1. Accurately weigh 10 g of the soil sample in a digital balance after pretreatment. 2. Add the sample to 90 ml of sterile double-distilled water in a conical flask. 3. Mix the sample carefully to make soil suspension of 101 dilution. 4. Perform serial dilution by aseptic transfer of 1 ml of soil suspension (101) to 9 ml of double-distilled water in a test tube sterilized previously (102). 5. Perform serial dilution as above up to 106 dilution.

3.4 Preparation of SCAM Plate

1. Weigh the required quantity of starch casein agar medium (SCAM) as per the manufacturer instruction (Himedia). 2. Transfer the medium to a conical flask and add the appropriate amount of double-distilled water. 3. Boil to dissolve the medium completely in a water bath. 4. Sterilize the medium in an autoclave at 15 lbs. pressure (121
C) for 15 min.

Isolation of Actinobacteria from Hills

93

Collection of soil sample from Hills by V-shape sample method Pretreatment of soil sample Air dry soil sample at room temperature for one week Sieve soil sample through 250 μm pore size sieve Heat treat at 50ºC for 1hr Serial dilution of pretreated soil sample upto 10-6 dilution.

Preparation of sterile Starch casein agar medium plate Inoculation of diluted soil suspension to SCAM plate by Spread plate technique Incubation SCAM plate at 28ºC for 7 days

Examine coIony morpholgy on SCAM plate after incubation

Isolate and maintain actinobacteria as pure culture

Fig. 2 Isolation of actinobacteria from Hills

5. Add filter-sterilized nalidixic acid (20 μg/ml) and nystatin (100 μg/ml) to the medium while it is 45–50
C to inhibit bacterial and fungal growth [18]. 6. Mix the medium for uniform distribution of antibiotics. 7. Aseptically pour the medium to sterile petri plate and let it solidify under the Laminar airflow chamber. 3.5 Inoculation of Sample

1. Place the SCAM plate in a Plate Master (Himedia). 2. Transfer an aliquot of 100 μl of soil suspension from the last three dilutions 104, 105, and 106 onto the center of the surface of the sterile SCAM plate separately with the assistance of a micropipette (Fig. 2). 3. Dip the L-shaped glass spreader into alcohol. 4. Flame the glass spreader over a Bunsen burner. 5. Now spread the sample evenly over the entire surface of the agar plate by using a sterile L-shaped glass spreader at an angle of 45
and carefully rotate the petri plate underneath in a Plate Master.

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6. A sterile SCAM plate act as uninoculated control. 7. Incubate all the plates at 28
C for 7 days in an incubator [19]. 8. Examine the morphology of the colony on the SCAM plate after incubation. 9. Isolate the morphologically distinct colony and maintain it as a pure culture.

References 1. Hwang KS, Kim HU, Charusanti P, Palsson BO, Lee SY (2014) Systems biology and biotechnology of Streptomyces species for the production of secondary metabolites. Biotechnol Adv 32(2):255–268 2. Siddharth S, Vittal RR, Wink J, Steinert M (2020) Diversity and bioactive potential of actinobacteria from unexplored regions of Western Ghats, India. Microorganisms 8 (2):225 3. Sharma M, Dangi P, Choudhary M (2014) Actinomycetes: source, identification, and their applications. Int J Curr Microbiol App Sci 3(2):801–832 4. Vineeth M, Ragunathan R (2018) Study on biosystematic and bioactivity of Nocardiopsis flavescens RRMVCBNR obtained from niche habitats of Valparai hill station. J Drug Deliv Therap 8(4):282–290 5. Shekar P, Radhakrishnan M, Gopikrishnan V, Suresh A (2017) Characterization and antimicrobial potential of soil actinobacterium TFA1 isolated from Talakona forest, Andhra Pradesh. J App Pharm Sci 7(3):202–206 6. Basik AA, Juboi H, Shamsul SSG, Sanglie JJ, Yeo TC (2020) Actinomycetes isolated from wetland and hill paddy during the warm and cool seasons in Sarawak, East Malaysia. J Microbiol Biotechnol Food Sci 9(4):774–780 7. Hayakawa M, Sadakata T, Kajiura T, Nonomura H (1991) New methods for the highly selective isolation of Micromonospora and Microbispora from soil. J Ferment Bioeng 72:320–326 8. Tamura T, Hayakawa M, Hatano K (1997) A new genus of the order Actinomycetales, Spirilliplanes gen. nov. with description of Spirilliplanes yamanashiensis sp. nov. Int J Syst Bacteriol 47:97–102

9. Yamamura H, Hayakawa M, Iimura Y (2003) Application of sucrose-gradient centrifugation for selective isolation of Nocardia spp. from soil. J Appl Microbiol 95(4):677–685 10. Hayakawa M (2008) Studies on the isolation and distribution of rare actinomycetes in soil. Actinomycetologica 22(1):12–19 11. Shivabai C, Gutte S (2019) Isolation of actinomycetes from soil sample using different pretreatment methods and its comparative study. Int J Res Anal Rev 6(2):697–702 12. Radhakrishnan M, Vijayalakshmi G, Gopikrishnan V, Jerrine J (2016) Bioactive potential of actinobacteria isolated from certain understudied regions in India. J Appl Pharm Sci 6(8):151–155 13. Chandwad C, Chandwad S, Gutte S (2020) Isolation of actinomycetes from rhizosphere soil: a complete approach. Plant Cell Biotechnol Mol Biol 21(65–66):144–149 14. Acharya SM (2018) Collection and preparation of soil, water and plant samples for analysis. Int J Chem Stud 6(2):3298–3303 15. Kumar PS, Duraipandiyan V, Ignacimuthu S (2014) Isolation, screening and partial purification of antimicrobial antibiotics from soil Streptomyces sp. SCA 7. Kaohsiung J Med Sci 30(9):435–446 16. Njenga WP, Mwaura FB, Wagacha JM, Gathuru EM (2017) Methods of isolating Actinomycetes from the soils of Menengai Crater in Kenya. Arch Clin Microbiol 8(3):45 17. Sunita S, Archana L, Mahananda Z, Snehal J (2015) Isolation and characterization of Actinomycetes from rhizosphere soil of different plants for antiphytopathogenic activity and stress tolerance. Int J Curr Microbiol Appl Sci 4(Special Issue 2):379–387

Isolation of Actinobacteria from Hills 18. Mohanraj D, Bharathi S, Radhakrishnan M, Balagurunathan R (2011) Bioprospecting of actinobacteria from Yelagiri hills with special reference to antibacterial activity. J Chem Pharm Res 3(3):439–446

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19. Kumar N, Singh RK, Mishra SK, Singh AK, Pachouri UC (2010) Isolation and screening of soil Actinomycetes as source of antibiotics active against bacteria. Int J Microbiol Res 2 (2):12–16

Chapter 16 Isolation of Endophytic Actinobacteria from Flowers, Fruits, and Seeds of Higher Plants D. Jayanthi, A. Martin Paul, and Leena Sebastian Abstract Microbial endophytes have coevolved along with plants mutually by colonizing apoplast and symplast regions of the host plant. Among the endophytes, the Actinobacteria are excellent dwellers in plant tissues. Many of actinobacterial interactions with host plants are proven to be beneficial because of their abilities to produce various plant growth–promoting bioactive compounds such as phytohormones, enzymes, enzyme precursors, in nutrient transformations and antagonistic effects ultimately leading to sustainable plant growth and productivity. The ecology of actinobacteria in plants is exceptionally diverse and is swayed by the quantum of host–microbe interactions, soil types including environmental conditions. The field of agriculture has adopted the utilization of endophytic actinobacteria in the form of biofertilizers and biopesticides. The association of endophytic actinobacteria with the host plant has also paved the way for reduction of chemical fertilizers and inducing systemic resistance. Besides their role as plant growth promoters and biocontrol agents, endophytic actinobacteria are considered to be promising entities among microorganisms in producing novel therapeutic compounds which are used in the field of drug development against many human diseases. On an ecological scale, endophytic actinobacteria are also crucially involved in decomposition of toxic pesticides and bioremediation of heavy metals. Applications of novel bioactive compounds especially of microbial origin in the field of agriculture, crop development, and medicine are proven to be promising. Simultaneously the quests for microbial based metabolites are also rising at an alarming rate in order to combat the desires of mankind. To sustain the requirements of scientific communities, advanced and innovative protocols are prerequisite in studying and discovering microorganisms. As isolation techniques of actinobacteria from vegetative parts of plants are well explored,, in the present chapter we provide insights into the technique of isolating actinobacterial populations associated within the reproductive parts of the plant, that is, flowers, fruits, and seeds of plants using culture-dependent methods like isolation on Luria–Bertani agar, humic acid vitamin B (HV) medium, and trehalose–proline agar respectively practical utilization in the field of agriculture, environment, and health. Key words Endophytic actinobacteria, Reproductive parts, Bioactive compounds, Biofertilizers, Biopesticides, Drug development, Bioremediation

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_16, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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Introduction Actinobacteria are prokaryotic, gram-positive generally aerobic bacteria possessing different morphological structure, from unicellular to filamentous organisms. For a very long time these organisms were considered as fungi as they exhibit formation of branching hyphae that produces thick mycelia and spores. However, actinobacteria are prokaryotic organisms with high G + C content in their genome. Actinobacteria possess the potential to produce various bioactive compounds like enzymes, plant growth hormones, antimicrobials, anticancerous substances, antimalarials, antioxidants, immunosuppressive agents, and many more, with potential in various fields like agriculture, industry, and medicine [1–3]. All plants consists endophytic microorganisms, among which actinobacteria takes an important position [4]. Endophytic organisms from rhizosphere or phyllosphere will enter the plants via root hairs, wounds, and by degrading the tissues through production of hydrolytic enzymes like cellulase and pectinase. After entering the plant, they colonize inter and intracellular spaces and vasculatures [5, 6]. Endophytic actinobacteria are capable of establishing associations with plants by colonizing the inner tissues of different plant parts including both vegetative and reproductive parts [7–9]. Endophytic actinobacteria exhibits importance in plant protection by producing bioactive compounds like phytohormones or growth regulators and biological control components. Being in endophytic association these organisms not only help plants but also in turn get nutrition and protection from the associated plant [10–12]. Endophytic actinobacterial colonization are seen in almost all living parts of the plant, rhizoplane (roots), phylloplane (leaves), caulosphere (stem), anthosphere (flowers), carposphere (fruits), and also seeds [13]. Flowers and seeds are considered to be the structures that involve in transmission of the endophytic organism to the next generation [14]. Various studies have reported that endophytic actinobacteria in several plants from primitive thallophytes to advanced spermatophytes harboring have strong interactions with plants when compared to rhizospheric or epiphytic bacteria [15–17]. Both physiological and chemical nature of soil and its moisture content is very important for the endophytic actinobacterial community [18]. The diversity in endophytic actinobacterial colonization and species specificity depends on physicochemical nature of plant tissues and the capacity of the bacterial community to colonize and utilize the substrates in plant tissues [19]. Also, the endophytic actinobacterial richness, diversity and abundances within the host plant is vital and is governed by biotic and abiotic components

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like host plant, microbial community, plant–microbe interactions, and habitat distribution [4]. Importantly, the biogeographic factors and external application of fertilizers and pesticide and genetic modification of plants also influence the diversity and richness of the endophytic actinobacterial community [20]. Hence, numerous factors influence the species diversity of endophytic actinobacterial communities and their localization within the plant tissue [18]. Endophytic actinobacteria exhibits several beneficial effects in plants and is involved in production of biomolecules. Endophytic actinobacteria are the most promising biological resource in promoting plant growth and health, and also to control plant diseases there by leading to sustainable agriculture [21]. Endophytic actinobacteria are involved in production of wide range of bioactive metabolites like immunosuppressive, antitumor, antimicrobial and many pharmaceutical compounds [19]. Among the endophytic actinobacteria, Streptomyces is the most abundant genus that is isolated from plants. Other actinobacteria like Streptosporangium, Actinopolyspora, Nocardia, Micromonospora, Verrucocsispora, Actinocorallia are the some common genera which are isolated from plants [22–25]. A study has reported that endophytic actinobacteria has important gene clusters called PKS and NRPS, these are the genes involved in the synthesis of various secondary metabolites, thus helping in plant growth [26]. Endophytic actinobacteria can be isolated on chemical media such as Luria–Bertani (LB) agar, nutrient agar, Gause’s synthetic agar, HV agar, glycerol–asparagine agar and Chitin medium, potato dextrose agar (PDA), yeast extract malt extract agar, and water agar [27]. There are generally methods available for isolating actinobacteria from vegetative parts of the plants. This chapter discusses culture dependent isolation methodologies of endophytic actinobacteria from reproductive parts of the plant.

2

Materials

2.1 Isolation of Endophytic Actinobacteria from Flowers [13]

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Healthy fresh flowers.

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Wax.

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Tween 20 0.1%.

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Ethanol 70%.

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Sodium hypochlorite (NaOCl) 0.4%.

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Sterile distilled water.

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Sterile scalpel.

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Laminar air flow chamber.

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Cycloheximide.

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Nalidixic acid.

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K2Cr2O7.

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Glycerol.

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BOD incubator.

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Starch casein agar (SCA): dipotassium hydrogen orthophosphate 2 g/L, calcium carbonate 0.02 g/L, ferrous sulfate heptahydrate 0.01 g/L, starch 10 g/L, potassium nitrate 2 g/L, casein 0.3 g/L, magnesium sulfate heptahydrate 2 g/L, agar 15 g/L, pH 7.0. *The media is supplied with nalidixic acid (10 mg/L) and cycloheximide (20 mg/L) (see Note 1).

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Actinomycetes Isolation Agar (AIA): sodium caseinate 2 g/L, L-asparagine 0.1 g/L, sodium propionate 4 g/L, dipotassium phosphate 0.5 g/L, magnesium sulfate 0.1 g/L, ferrous sulfate 0.001 g/L, agar 15 g/L, pH 8.1, glycerol 5 mL. *The media is supplied with nalidixic acid (10 mg/L) and cycloheximide (20 mg/L) (see Note 1).

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Tap Water Yeast Extract Agar (TWYE): Yeast extract 0.25 g/L, potassium hydrogen phosphate (K2HPO4) 0.50 g/L, agar 18 g/L, tap water 1 L, pH 7.0. *The media is supplied with nalidixic acid (10 mg/L) and cycloheximide (20 mg/L) (see Note 1).

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Yeast Malt Extract agar (ISP2): Peptone 5 g/L, yeast extract 3 g/L, malt extract 3 g/L, dextrose 10 g/L, agar 20 g/L, pH 6.2 (see Note 2). *The media is supplied with nalidixic acid (10 mg/L) and cycloheximide (20 mg/L) (see Note 1).

2.2 Isolation of Endophytic Actinobacteria from Fruits [28–30]

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Glycerol Asparagine Agar (ISP5): L-asparagine 1 g/L, dipotassium phosphate 1 g/L, trace salt solution 1 mL (1 mL of trace salt solution contains: ferrous sulfate heptahydrate 0.001 g/L, manganese chloride tetrahydrate 0.001 g/L, zinc sulfate heptahydrate 0.001 g/L), glycerol 10 mL, agar 20 g/L, pH 7.4 (see Note 1). *The media is supplied with nalidixic acid (10 mg/L) and Cycloheximide (20 mg/L) (see Note 1).

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Fruits.

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Sterile distilled water.

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Sterile scalpel.

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Tissue homogenizer.

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NaOCl 1%.

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Alcohol 70%.

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Cycloheximide.

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Nalidixic acid.

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Nystatin.

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Glycerol.

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Humic Acid Vitamin B (HV): Humic acid 1 g/L, calcium carbonate 0.02 g/L, disodium hydrogen orthophosphate 0.5 g/L, potassium chloride 1.7 g/L, magnesium sulfate heptahydrate 0.05 g/L, ferrous sulfate heptahydrate 0.01 g/L, B-Vitamins 5 mL, Agar 18 g/L, pH 7.2. *The media is supplied with nalidixic acid (10 mg/L) and cycloheximide (20 mg/L) (see Note 1).

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Inorganic Salt Starch Agar (ISP 4) Medium: Starch (soluble) 10 g/L, dipotassium phosphate 1 g/L, magnesium sulfate heptahydrate 1 g/L, sodium chloride 1 g/L, ammonium sulfate 2 g/L, calcium carbonate 2 g/L, ferrous sulfate heptahydrate 0.001 g/L, manganous chloride heptahydrate 0.001 g/L, zinc sulfate heptahydrate 0.001 g/L, Agar 20 g/L, pH 7.2. *The media is supplied with nalidixic acid (10 mg/L) and cycloheximide (20 mg/L) (see Note 1).

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R2A solid medium: Tryptone 0.25 g/L, Peptone 0.25 g/L, Acicase 0.5 g/L, yeast extract 0.5 g/L, glucose (Dextose) 0.5 g/L, starch soluble 0.5 g/L, dipotassium hydrogen phosphate 0.03 g/L, magnesium sulfate heptahydrate 0.5 g/L, sodium pyruvate 0.03 g/L, agar 15 g/L, pH -7.2. *The media is supplied with nalidixic acid (10 mg/L) and cycloheximide (20 mg/L) (see Note 1).

2.3 Isolation of Endophytic Actinobacteria from Seeds [31, 32]

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Yeast Malt Extract agar (ISP2): Peptone 5 g/L, Yeast extract 3 g/L, Malt extract 3 g/L, Dextrose 10 g/L, Agar 20 g/L, pH 6.2. *The media is supplied with Nalidixic acid (10 mg/L) and Cycloheximide (20 mg/L) (see Note 1).

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Healthy seed samples.

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Commercial blender.

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Sterile distilled water.

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Incubator.

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LAF.

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20% (v/v) glycerol

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5% NaClO3

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2.5% Na2S2O3

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75% ethanol

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10% NaHCO3

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Sodium propionate agar.

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Yeast extract malt extract (ISP 2):

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Trehalose–proline agar: Trehalose 5 g/L, proline 1 g/L, (NH4)2SO4 1 g/L, NaCl 1 g/L, CaCl2–2 g/L, K2HPO4– 1 g/L, MgSO47H2O 1 g/L, agar 15 g/L, pH 7.0. *The media is supplied with Nalidixic acid (10 mg/L) and Cycloheximide (20 mg/L) (see Note 1).

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Sodium propionate agar: Sodium propionate 1.0 g, L-asparagine 0.2 g, KH2PO4 0.9 g, K2HPO4 0.6 g, MgSO4 7H2O 0.1 g, CaCl2 2H2O 0.2 g, agar 15.0 g, pH 7.0. *The media is supplied with nalidixic acid (10 mg/L) and cycloheximide (20 mg/L) (see Note 1).

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Cellulose–arginine agar: Cellulose 2.5 g/L, arginine 1 g/L, (NH4)2SO4 1 g/L, CaCl2 2 g/L, K2HPO4 1 g/L, MgSO4 7H2O 0.2 g/L, FeSO4 7H2O 10 mg, agar 15 g/L, pH 7.0. *The media is supplied with nalidixic acid (10 mg/L) and cycloheximide (20 mg/L) (see Note 1).

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Glycerol Asparagine Agar (ISP5): L-asparagine 1 g/L, dipotassium phosphate 1 g/L, trace salt solution 1 mL (1 mL of trace salt solution contains ferrous sulfate heptahydrate 0.001 g/L, manganese chloride tetrahydrate 0.001 g/L, zinc sulfate heptahydrate 0.001 g/L), glycerol 10 mL, agar 20 g/L, pH 7.4. *The media is supplied with nalidixic acid (10 mg/L) and cycloheximide (20 mg/L) (see Note 1).

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Starch casein agar (SCA): dipotassium hydrogen orthophosphate 2 g/L, calcium carbonate 0.02 g/L, ferrous sulfate heptahydrate 0.01 g/L, starch 10 g/L, potassium nitrate 2 g/L, casein 0.3 g/L, magnesium sulfate heptahydrate 2 g/L, agar 15 g/L, pH 7.0. *The media is supplied with nalidixic acid (10 mg/L) and cycloheximide (20 mg/L) (see Note 1).

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Tap Water Yeast Extract Agar (TWYE): Yeast extract 0.25 g/L, potassium hydrogen phosphate (K2HPO4) 0.50 g/L, agar 18 g/L, tap water 1 L, pH 7.0. *The media is supplied with nalidixic acid (10 mg/L) and cycloheximide (20 mg/L) (see Note 1).

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Methodology

3.1 Isolation of Endophytic Actinobacteria from Flower

Collect fresh and healthy flowers. Seal the cut ends with wax and bring sample into the laboratory in an icebox and use the sample for isolation within 48 h [13].

3.1.1 Sample Collection 3.1.2 Surface Sterilization

1. Wash the flower samples carefully in tap water for 3–5 min to remove any surface debris. 2. Successively cut in to pieces of 1cm2, rinse with 0.1% Tween 20 for few seconds and transfer to sterile conical flasks. 3. Surface-sterilize the washed flower samples by immersing them sequentially in 70% ethanol for 3 min, followed by 0.4% sodium hypochlorite (NaOCl) for 1 min, 70% ethanol for 2 min, followed by three washes with sterile distilled water for 1 min each. 4. Leave the samples to dry for few minutes in laminar air flow chamber [13] (see Note 3).

3.1.3 Isolation on Culture Media

1. Use a sterile scalpel and cut the flower tissue into 0.5cmsizeplace it on petri plates containing different isolation media (SCA, AIA, TWYE, ISP2, and ISP5). 2. Incubate the inoculated plates at 26  2  C in BOD incubator for 2–4 weeks. 3. Transfer the bacterial colonies grown on the plates from the plated sample tissue segments onto ISP2 media slants and repeatedly subculture until pure cultures are obtained and maintain the isolated pure culture at 4  C [13].

3.2 Isolation of Endophytic Actinobacteria from Fruits

Collect fresh and healthy fruits without defect.

3.2.1 Sample Collection 3.2.2 Surface Sterilization [28]

1. Wash the collected fruits carefully in tap water to remove surface debris and was with sterile distil water. 2. Subsequently, soak the fruit sample in 70% ethanol for 1 min, then soak in NaOCl 1% for 5 min, alcohol 70% for 1 min, finally wash three with sterile distill water (see Notes 3 and 4).

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3.2.3 Isolation on Humic Acid Vitamin B (HV) Culture Medium [28]

1. Make thin slices of sterilized fruit samples. 2. Crush the fruit to make a suspension. 3. Plate 0.1 mL crushed fruit suspension on Humic Acid Vitamin B (HV) medium containing cycloheximide and nalidixic acid. 4. Incubate the inoculated plates for 14–30 days at room temperature (28  C). 5. Actinobacteria colonies that grew on the agar medium will be further purified on ISP 4 medium containing Nystatin at a concentration of 100.0000 IU/mL.

3.2.4 Isolation on R2A Solid Culture Medium [29]

1. Grind the fruit sample using a tissue homogenizer tubes using 10 mL of potassium phosphate buffer (0.05 M, pH 7.0). 2. Filter the homogenized fruit suspension using sterilized gauze. 3. Serially dilute the filtered product in potassium phosphate buffer. 4. Streak aliquots onto R2A solid medium and incubated at 28  C for up to 72 h.

3.2.5 Isolation on Inorganic Salt Starch Agar (ISP 4) Culture Medium [30]

1. Make thin slices of sterilized fruit samples. 2. Crush the fruit to make a suspension. 3. Streak the suspension on Starch inorganic salt agar media plates. 4. Incubate the inoculated plates at 28  C for 3 weeks. 5. Pick the isolated colonies and maintain the pure cultures on ISP2 agar at 4  C and as glycerol suspensions (20%, v/v).

3.3 Isolation of Endophytic Actinobacteria from Seeds

Collect fresh and healthy seed samples without defect.

3.3.1 Sample Collection 3.3.2 Surface Sterilization [31]

1. Air-dry the fresh seed samples and wash thoroughly and transfer to laminar air flow. 2. Aseptically, wash the seeds in 5% NaClO3 for 3 min, followed by wash in 2.5% Na2S2O3 for 10 min, 75% ethanol 3 min, 10% NaHCO3for 10 min and finally rinse in sterile distilled water.

3.3.3 Isolation on Culture Media [31, 32]

1. Use a sterile commercial blender and crumble the sterilized seeds aseptically into small fragments. 2. Inoculate the fragmented seeds onto different selective isolation media (Trehalose–proline agar, sodium propionate agar,

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cellulose–arginine agar, ISP 5 agar, starch–casein, tap water/ yeast extract agar) (see Note 5). 3. Incubate the inoculated plates at 28  C for 2–6 weeks. 4. Subculture the isolated colonies and maintain on yeast extract malt extract agar (ISP 2) slants at 4  C and as glycerol suspensions 20% (v/v) at 28  C.

4

Notes 1. The media is supplied with Nalidixic acid (10mg/l) and Cycloheximide (20mg/l) to preclude bacterial and fungal growth. 2. For preparing selective media acidify the media up to pH 3.0 to 4.0 by aseptically adding 1 vial of 10% Lactic Acid Solution. 3. To check the efficacy of the surface sterilization: Take an aliquot of the sterilized water used in the final cleansing of the samples and inoculate into the culture medium used for the experiment or on to ISP 2 and LB media plates and incubated under the same experimental conditions. The plates were examined for bacterial growth after incubation at 28 and 37o C for 7 days. If no microbial growth occurs on the media surface, the sterilization is considered complete and the samples were used for pure culture isolation study. 4. Pre-wash fruits in running tap water, soak in neutral detergent and rinse in running distilled water. Surface sterilize the fruits aseptically by immersing twice in distilled water and once in 50 mM potassium phosphate buffer, pH 7.0. Followed by immersing the fruits in 70% (v/v) ethanol for 1 min, soak for 5 min under vigorous agitation in 5% (v/v) sodium hypochlorite containing 0.05% (v/v) Tween 80. The fruits are immersed in 70% (v/v) ethanol for 1 min followed by immersion in 50 mM potassium phosphate buffer, pH 7.0, for 15 min. 5. Various other media used for isolation of actinobacteria are ISP 3, Czapek’s solution agar, nutrient agar, potato agar and so on.

References 1. Barka EA, Vatsa P, Sanchez L et al (2016) Taxonomy, physiology, and natural products of Actinobacteria. Microbiol Mol Biol Rev 80:1–43. https://doi.org/10.1128/MMBR. 00019-15 2. Berdy J (2005) Bioactive microbial metabolites. J Antibiot 58:1–26 3. Strobel GA, Daisy B (2003) Bioprospecting for microbial endophytes and their natural products. Microbiol Mol Biol Rev 67:491–502.

https://doi.org/10.1128/MMBR.67.4.491502.2003 4. Golinska P, Wypij M, Agarkar G et al (2015) Endophytic actinobacteria of medicinal plants: diversity and bioactivity. Antonie Van Leeuwenhoek 108:267–289. https://doi.org/10. 1007/s10482-015-0502-7 5. Dudeja SS, Giri R, Saini R et al (2012) Interaction of endophytic microbes with legumes. J

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Basic Microbiol 52:248–260. https://doi.org/ 10.1002/jobm.201100063 6. Suman A, Yadav AN, Verma P (2016) Endophytic microbes in crops: diversity and beneficialimpact for sustainable agriculture. In: Singh DP, Singh HB, Prabha R (eds) Microbialinoculants in sustainable agricultural productivity, 1st edn. Springer, New Delhi, pp 117–143. https://doi.org/10.1007/978-81-3222647-5 7. Qin S, Li J, Chen HH et al (2009) Isolation, diversity and antimicrobial activity of rare actinobacteria from medicinal plants of tropical rain forests in Xishuangbanna, China. Appl Environ Microbiol 75:6176–6186. https:// doi.org/10.1128/AEM.01034-09 8. Schulz B, Boyle C (2006) What are endophytes? In: Schulz B, Boyle C, Sieber TN (eds) Microbial root endophytes, vol 9. Springer, Berlin, pp 1–13 9. Stone JK, Bacon CW, White JF (2000) An overview of endophytic microbes: endophytism defined. In: Bacon CW, White JF (eds) Microbial endophytes. Marcel Dekker Inc, New York, pp 3–29 10. Cao L, Qiu Z, You J et al (2005) Isolation and characterization of endophytic streptomycete antagonists of Fusarium wilt pathogen from surface-sterilized banana roots. FEMS Microbiol Lett 247(2):147–152. https://doi.org/ 10.1016/j.femsle.2005.05.006 11. Goudjal Y, Toumatia O, Sabaou N (2013) Endophytic actinomycetes from spontaneous plants of Algerian Sahara: indole-3-acetic acid production and tomato plants growth promoting activity. World J Microbiol Biotechnol 29 (10):1821–1829. https://doi.org/10.1007/ s11274-013-1344-y 12. Yandigeri MS, Meena KK, Singh D et al (2012) Drought-tolerant endophytic actinobacteria promote growth of wheat (Triticum aestivum) under water stress conditions. Plant Growth Regul 68:411–420. https://doi.org/10. 1007/s10725-012-9730-2 13. Passari AK, Mishra VK, Saikia R et al (2015) Isolation, abundance and phylogenetic affiliation of endophytic actinomycetes associated with medicinal plants and screening for their in vitro antimicrobial biosynthetic potential. Front Microbiol 6:273. https://doi.org/10. 3389/fmicb.2015.00273 14. Tchinda RA, Boudjeko T, Beaunoir SAM et al (2016) Morphological, physiological, and tax-

onomic characterization of actinobacterial isolates living as endophytes of cacao pods and cacao seeds. Microbes Environ 31:56–62. https://doi.org/10.1264/jsme2.ME15146 15. de Oliveira MF, da Silva MG, Van Der Sand ST (2010) Antiphytopathogen potential of endophytic actinobacteria isolated from tomato plants (Lycopersicon esculentum) in southern Brazil, and characterization of Streptomyces sp. R18(6),a potential biocontrol agent. Res Microbiol 161(7):565–572. https://doi.org/ 10.1016/j.resmic.2010.05.008 16. Janso JE, Carter GT (2010) Biosynthetic potential of phylogenetically unique endophytic actinomycetes from tropical plants. Appl Environ Microb 76(13):4377–4386. https://doi.org/10.1128/AEM.02959-09 17. Misk A, Franco C (2011) Biocontrol of chickpea root rot using endophytic actinobacteria. BioControl 56:811–822. https://doi.org/10. 1007/s10526-011-9352-z 18. Zarraonaindia I, Owens SM, Weisenhorn P et al (2015) The soil microbiome influences grapevine-associated microbiota. mBio 6(2): e02527-14. https://doi.org/10.1128/mBio. 02527-14 19. Nimnoi P, Pongsilp N, Lumyong S (2010) Endophytic actinomycetes isolated from Aquilaria crassna Pierre ex Lec and screening of plant growth promoters production. World J Microbiol Biotechnol 26:193–203. https:// doi.org/10.1007/s11274-009-0159-3 20. da Silva DAF, Cotta SR, Vollu RE et al (2014) Endophytic microbial community in two transgenic maize genotypes and in their nearisogenic non-transgenic maize genotype. BMC Microbiol 14:332–340. https://doi. org/10.1186/s12866-014-0332-1 21. Kunoh H (2002) Endophytic Actinomycetes: attractive biocontrol agents. J Gen Plant Pathol 68:249–252. https://doi.org/10.1007/ PL00013084 22. Qin S, Chen HH, Zhao GZ et al (2012) Abundant and diverse endophytic actinobacteria associated with medicinal plant Maytenus austroyunnanensis in Xishuangbanna tropical rainforest revealed by culture-dependent and culture-independent methods. Environ Microbiol Rep 4(5):522–531. https://doi.org/10. 1111/j.1758-2229.2012.00357.x 23. Zhao K, Penttinen P, Xiao T et al (2011) The diversity and antimicrobial activity of endophytic actinobacteria isolated from medicinal

Isolation of Endophytic Actinobacteria from Flowers, Fruits, and Seeds. . . plants in Panxi Plateau, China. Curr Microbiol 62:182–190. https://doi.org/10.1007/ s00284-010-9685-3 24. Verma VC, Gond SK, Kumar A et al (2009) Endophytic actinobacteria from Azadirachta indica a. Juss.: isolation, diversity, and antimicrobial activity. Microb Ecol 57:749–756. https://doi.org/10.1007/s00248-0089450-3 25. Gohain A, Gogoi A, Debnath R et al (2015) Antimicrobial biosynthetic potential and genetic diversity of endophytic actinomycetes associated with medicinal plants. FEMS Microbiol Lett 362(19):fnv158. https://doi.org/10. 1093/femsle/fnv158 26. Luo H, Lin X, Zhang L et al (2013) Isolation, classification and biosynthetic potential of endophytic actinomycetes from Stemona. Acta Microbiol Sin 52(3):389–395 27. Hallmann J, Berg G, Schulz B (2006) Isolation procedures for endophytic microorganisms. In: Schulz BJE, Boyle CJC, Sieber TN (eds) Microbial root endophytes. Springer, New York, pp 299–319 28. Larasati F, Batubara I, Lestari Y (2020) The presence of endophytic actinobacteria in mangosteen peel (Garcinia mangostana) and its

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antioxidant activity. Biodiversitas 21 (4):1488–1497. https://doi.org/10.13057/ biodiv/d210429 29. Miguel PSG, Delvaux JC, de Oliveira MNV, Monteiro LCP et al (2013) Diversity of endophytic bacteria in the fruits of Coffea canephora. Afr J Microbiol Res 7(7):586–594. https:// doi.org/10.5897/AJMR12.2036 30. Du HJ, Zhang YQ, Liu HY et al (2013) Allonocardiopsis opalescens gen. nov., sp. nov., a new member of the suborder Streptosporangineae, from the surface-sterilized fruit of a medicinal plant. Int J Syst Evol Microbiol 63:900–904. https://doi.org/10.1099/ijs.0.041491-0 31. Miao Q, Qin S, Bian GK et al (2011) Amycolatopsis endophytica sp. nov., a novel endophytic actinomycete isolated from oil-seed plant Jatropha curcas L. Antonie Van Leeuwenhoek 100:333–339. https://doi.org/10. 1007/s10482-011-9588-8 32. Qin S, Miao Q, Feng WW et al (2015) Biodiversity and plant growth promoting traits of culturable endophytic actinobacteria associated with Jatropha curcas L. growing in Panxi dry-hot valley soil. Appl Soil Ecol 93:47–55. https://doi.org/10.1016/j.apsoil.2015.04. 004

Chapter 17 Isolation Actinobacteria from Desert Soils Ashraf Khalifa and A. Sankaranarayanan Abstract Actinobacteria constitute a diversified group of microbes living in soil samples. They are aerobic, sporeforming bacteria that result in a positive Gram staining reaction. Their habitat is not restricted only to the soil; they are abundantly present in marine and freshwater environments; however, soil contains a rich diversity of Actinobacteria. The research work focused on the isolation of rare Actinobacteria from the desert, hot springs, and sea mud in search of their potential bioprospecting activities, increasing the chances of finding novel chemo-diversified Actinobacteria from rare environments. Key words Actinobacteria, Desert soil, Isolation, Bioactive substances

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Introduction Novel extremophilic Actinobacteria from unusual environments may yield new, potentially bioactive strains; hence, researchers are moving away from the traditional isolation procedures and are looking for rare niches and ecosystems. The increasing trends of multidrug-resistant pathogens and their serious consequences make the researchers determined to find a novel strain from an unusual environment [1]. In addition, Actinobacteria are considered a reservoir of unlimited bioactive compounds that may be used for various beneficial applications [2]. Members of the Actinobacteria phylum from various extreme environments, such as thermotolerant, halotolerant, alkali-tolerant, halo-alkali-tolerant, and xerophilous, are well documented [3]. Lower availability of water, scarcity of nutrients, high temperature, and high radiation are a few of the special features of the desert ecosystem mentioned here. The potential bioactive components producing Actinobacteria were obtained from different desert soil environments and include Streptomyces spp. (antibacterial and antifungal activities) [4], Streptomyces leeuwenhoekii (against adenocarcinoma and breast carcinoma cells) [5], and Streptomyces asenjonii (broad-spectrum

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_17, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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antimicrobial activities) [6]. Chemical profiling studies using LC-HRMS and NMR revealed the presence of secondary metabolites from Lentzea chajnantorensis from desert soil-isolated Actinobacteria [7, 8]. The research report revealed that the desert soil harbors a rich diversity of Actinobacteria communities [9].

2

Materials and Methods

2.1 Materials Required

1. Soil sample. 2. Conical flask—250 ml. 3. Test tubes—15 ml. 4. Micropipettes (various ranges). 5. Starch casein agar plates (starch—10 g, K2HPO4—2 g, KNO3—2 g, casein—0.3 g, MgSO4.7H2O—0.05 g, CaCO3—0.02 g, FeSO4.7H2O—0.01 g, agar—15 g, distilled water—1000 ml, pH—7.0). 6. Amphotericin B (20 μg/ml). 7. Nalidixic acid (10 μg/ml). 8. Tetracycline. 9. L-rod. 10. Incubator. 11. Distilled water. 12. Sterile spatula. 13. Sterile plastic bags.

2.2

Methodology

2.2.1 Collection of Desert Soil Samples 2.2.2 Media Preparation and Plating Techniques

1. Collection of the soil sample from different locations (ten different locations) in the desert environment [2, 10].

1. Prepare starch casein agar (SCA) and sterilize at 121 C under 15 lb (6.8 kg) of pressure for 15 min. 2. Add it to amphotericin B and nalidixic acid to prevent fungal and bacterial growth respectively. 3. Pour the medium onto a sterile petri plate and allow for solidification. 4. Prepare dilution blank set. Transfer 10 g of soil in 90 ml of sterile distilled water (10 1), mix up the soil sample by shaking, and make tenfold dilutions up to (10 6). 5. Take 0.1-ml aliquots of each soil sample and spread over the agar plates in triplicate. 6. One uninoculated plate will serve as the control.

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7. Incubate all the plates at 28 C for 15 days. 8. Following incubation, the isolates are subjected to further analysis and the data expressed as colony-forming units per gram (CFU/g). 9. Prepare the stock cultures of isolates in cryotubes to contain 1.5 ml 20% (w/v) sterile glycerol solution and preserve at 20  C.

References 1. Berdy J (2015) Microorganisms producing antibiotics. In: Sanchez S, Demain AL (eds) Antibiotics—current innovations and future trends. Academic, Caister, pp 49–64 2. Nithya K, Muthukumar C, Biswas B, Alharbi NS, Shine K, Khaled JM, Dhanasekaran D (2018) Desert Actinobacteria as a source of bio active compounds production with a special emphases on pyridine 2,5 diacetamide, a new pyridine alkaloid produced by Streptomyces sp. DA3-7. Microbiol Res 207:116–133 3. Lubsanova DA, Zenova GM, Kozhevin PA, Manucharova NA, Shvarov AP (2014) Filamentous Actinobacteria of the saline soils of arid territories. Moscow Univ Soil Sci Bull 69:88–92. https://doi.org/10.3103/ S0147687414020057 4. Schulz D, Beese P, Ohlendorf B, Erhard A, Zinecker H, Dorador C, Imhoff JF (2011) Abenquines A–D: aminoquinone derivatives produced by Streptomyces sp. strain DB634. J Antibiot 64:763–768 5. Natchigall J, Kulik A, Helaly S, Bull AT, Goodfellow M, Asenjo JA, Maier A, Wiese J, Imhoff JF, Sussmuth RD, Fiedler H (2011) Atacamycins A–C, 22-membered antitumour macrolactones produced by Streptomyces sp. C38. J Antibiot 64:775–780

6. Abdelkader MSA, Philippon T, Asenjo JA, Bull AT, Goodfellow M, Ebel R, Jaspars M, Rateb ME (2018) Asenjonamides A–C, antibacterial metabolites isolated from Streptomyces asenjonii strain KNN 42, from an extreme-hyper arid Atacama Desert soil. J Antibiot 71:425–431 7. Wichner D, Idris H, Houssen WE, McEwan AR, Bull AT, Asenjo JA, Good Fellow M, Jaspars M, Ebel R, Rateb ME (2017) Isolation and anti-HIV-1 integrase activity of lentzeosides A–F from extremotolerant Lentzea sp. H45, a strain isolated from a high-altitude Atcama Desert soil. J Antibiot 70:448–453 8. Idris H, Imen N, Asenjo JA, Bull AT, Goodfellow M (2017) Lentzea chajnantorensis sp. nov., a very high altitude actinobacterium which produces novel dienes and was isolated from Cerro Chajnantor gravel soil in northern Chile. Anotonie Van Leeuwenhoek 110:795–802 9. Bull AT, Idris H, Sanderson R, Asenjo JA, Andrews B, Goodfellow M (2018) Highaltitude, hyper arid soils of the Central-Andes harbour mega-diverse communities of actinobacteria. Extremophiles 22:47–57 10. Wellington EMH, Williams ST (1978) Preservation of actinomycete inoculums in frozen glycerol. Microbiol Lett 6:151–157

Chapter 18 Methods for Isolation of Epiphytic Actinobacteria from Rhizosphere of Spermatophytes S. Shravya, S. J. Meghana, and D. Jayanthi Abstract Actinobacteria in nature are ubiquitous and are isolated from various environmental conditions like high temperature and salinity and are also present as epiphytes and endophytes. Among epiphytic forms colonizing the rhizosphere and phyllosphere, the rhizospheric actinobacteria are the most dominant group in nature and are considered of great economic importance to human in contributing to a sustainable soil system. The epiphytic actinobacteria present in the phyllosphere and rhizosphere regions play important role in promoting plant growth by producing various growth-promoting compounds like phytohormones and enzymes, aiding in metabolisms such as nitrogen fixation and nutrient-rich mineral absorption from soil and showing antagonistic effects against other harmful organism leading to plant growth and productivity. Actinobacteria have several economic advantages besides promoting plant growth, such as bioremediation of toxic compounds, biomedical use by producing antibiotics leading to drug development, and also biological pest control as they produce important metabolic compounds, hence are also used in industries like food, textile, paper, detergents, pharmaceuticals, and biochemicals. Rhizospheric actinobacteria being the most predominant form in nature among epiphytes are largely explored commercially for their potentials. This chapter mainly aims to provide the methodology for isolation of the epiphytic rhizospheric actinobacteria using culture-dependent methods like isolating on TSA (tryptone soy agar) medium for their utilization in various fields of their potentialities and environmental sustainability. Key words Epiphytic actinobacteria, Rhizosphere, Isolation, Growth promoting, Bioremediation, Antibiotics, Biological pest control

1

Introduction The phylum actinobacteria is the largest and diverse type among bacteria. This phylum consists of bacteria that are Gram-positive with high guanine and cytosine content. Different actinobacteria vary in morphology, physiology, and their metabolic activities. Few examples of actinobacteria are Streptomyces, Mycobacterium, Arthrobacter, Micrococcus, etc. [1]. Plant-associated microbes are classified into rhizospheric microbes, epiphytic microbes, and endophytic microbes

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_18, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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[1]. Epiphytic microbes are non-parasitic, and they colonize on the surface of the plants. These microbes vary in their compositions based on different seasons, physiological conditions, and environmental conditions including the nutritional availability, and their occurrence depends on the specific interactions with abiotic factors [2]. The biological process that occurs within the interface between soil and root has major effects or consequences for the crop growth, soil fertility, and environmental protection. The actinobacteria with different crops produce different plant growth-promoting attributes and promote plant growth directly by producing hormones like indole-3 acetic acid, cytokinin, gibberellins, and abscisic acid. They also help in biological nitrogen fixation and solubilization of phosphorous and potassium [1]. These bacteria have the possibility to protect the roots by producing enzymes that inhibit the growth of fungal pathogens by degrading the cell wall or by producing antifungal compounds [3]. The microbes that are isolated from extreme environmental conditions may exhibit plant growthprompting attributes, and thus, these abiotic stress-tolerant microbes can be applied for plant growth under specific abiotic stress conditions [4, 5]. Most actinomycetes in the soil are Streptomyces species, and 75% of it contributes to the production of different biological compounds [6]. The rhizospheric actinomycetes produce active compounds [7]. Actinobacteria apart from promoting the growth are also used for bioremediation of toxic compounds, help in producing antibiotics, as biological pest control as they produce important metabolic compounds. It is used in industries like food, textiles, detergents, biochemical, and pharmaceuticals. This chapter explicates the different methods of isolating epiphytic actinobacteria on various media from rhizosphere samples of spermatophytes.

2

Materials

2.1 Requirements for Sample Collection

The primary materials required are: 1. Rhizosphere soil sample and root sample. 2. Poly-vinyl bags. 3. Ice cubes. 4. Rotary shaker. 5. Weighing balance. 6. Spatula. 7. Distilled water. 8. Beakers.

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9. Pipettes. 10. Measuring cylinder. 11. Pipettes. 12. Standard flask. 13. Petri dishes. 14. Inoculation loop. 2.2 Chemicals for Pretreatment Process

1. 1% phenol. 2. 2% calcium carbonate. 3. 0.1% SDS. 4. 5% yeast extract for soil sample. 5. Sterile NaCl 0.9% for root sample [8, 9].

2.3 Requirement for Different Isolation Methods 2.3.1 Serial Dilution Method

The four different methods used for isolating epiphytic actinobacteria from rhizosphere require various materials and media for each method as mentioned below: 1. Rhizosphere soil and root sample. 2. Humic acid vitamin agar (HVA): Humic acid 1 g/L, calcium carbonate 0.02 g/L, disodium hydrogen orthophosphate 0.5 g/L, potassium chloride 1.7 g/L, magnesium sulfate heptahydrate 0.05 g/L, ferrous sulfate heptahydrate 0.01 g/ L [10]. Supplement it with nalidixic acid 10 mg/L, cycloheximide 20 mg/L (see Note 1). 3. Tryptone soy agar medium (TSA): Tryptone 17 g/L, soya meal 3 g/L, dextrose 2.5 g/L, sodium chloride 5 g/L, dipotassium hydrogen orthophosphate 2.5 g/L, pH 7.2 [1]. Supplement it with nalidixic acid 10 mg/L, cycloheximide 20 mg/L (see Note 1). 4. Starch casein agar (SCA): Dipotassium hydrogen orthophosphate 2 g/L, calcium carbonate 0.02 g/L, ferrous sulfate heptahydrate 0.01 g/L, starch 10 g/L, potassium nitrate 2 g/L, casein 0.3 g/L, magnesium sulfate heptahydrate 2 g/ L, agar 15 g/L, pH 7.0 [10]. Supplement it with nalidixic acid 10 mg/L, vycloheximide 20 mg/L (see Note 1). 5. 50% glycerol.

2.3.2 Membrane Filter Technique

1. Rhizosphere soil sample. 2. Membrane filters of 0.45-μm pore size. 3. Humic acid vitamin agar (HVA): Humic acid 1 g/L, calcium carbonate 0.02 g/L, disodium hydrogen orthophosphate

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0.5 g/L, potassium chloride 1.7 g/L, magnesium sulfate heptahydrate 0.05 g/L, ferrous sulfate heptahydrate 0.01 g/ L [10]. Supplement it with nalidixic acid 10 mg/L, cycloheximide 20 mg/L (see Note 1). 4. Tryptone soy agar medium (TSA): Tryptone 17 g/L, soya meal 3 g/L, dextrose 2.5 g/L, sodium chloride 5 g/L, dipotassium hydrogen orthophosphate 2.5 g/L, pH 7.2 [1]. Supplement it with nalidixic acid 10 mg/L, cycloheximide 20 mg/L (see Note 1). 5. Starch casein agar (SCA): Dipotassium hydrogen orthophosphate 2 g/L, calcium carbonate 0.02 g/L, ferrous sulfate heptahydrate 0.01 g/L, starch 10 g/L, potassium nitrate 2 g/L, casein 0.3 g/L, magnesium sulfate heptahydrate 2 g/ L, agar 15 g/L, pH 7.0 [10]. Supplement it with nalidixic acid 10 mg/L, cycloheximide 20 mg/L (see Note 1). 6. LB slants. 7. 50% glycerol. 2.3.3 Standard Enrichment Technique

1. Root sample. 2. Mineral salt medium (MSM): Diammonium hydrogen orthophosphate 0.5 g/L, magnesium sulfate 0.2 g/L, ferrous sulfate heptahydrate 0.01 g/L, dipotassium hydrogen orthophosphate 0.1 g/L, calcium nitrate tetrahydrate 0.01 g/L, pH 7.0 [11]. Supplement it with nalidixic acid 10 mg/L, cycloheximide 20 mg/L (see Note 1). 3. Luria Bertani (LB) media: Tryptone 10 g/L, yeast extract 5 g/L, sodium chloride 5 g/L, glucose 1 g/L, pH 7.0 [11]. Supplement it with nalidixic acid 10 mg/L, cycloheximide 20 mg/L (see Note 1).

2.3.4 Direct Inoculation Technique

1. Rhizosphere soil sample. 2. Humic acid vitamin agar (HVA): Humic acid 1 g/L, calcium carbonate 0.02 g/L, disodium hydrogen orthophosphate 0.5 g/L, potassium chloride 1.7 g/L, magnesium sulfate heptahydrate 0.05 g/L, ferrous sulfate heptahydrate 0.01 g/ L [10]. Supplement it with nalidixic acid 10 mg/L, cycloheximide 20 mg/L (see Note 1). 3. Tryptone soy agar medium (TSA): Tryptone 17 g/L, soya meal 3 g/L, dextrose 2.5 g/L, sodium chloride 5 g/L, dipotassium hydrogen orthophosphate 2.5 g/L, pH 7.2 [1].

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Supplement it with nalidixic acid 10 mg/L, cycloheximide 20 mg/L (see Note 1). 4. Starch casein agar (SCA): Dipotassium hydrogen orthophosphate 2 g/L, calcium carbonate 0.02 g/L, ferrous sulfate heptahydrate 0.01 g/L, starch 10 g/L, potassium nitrate 2 g/L, casein 0.3 g/L, magnesium sulfate heptahydrate 2 g/ L, agar 15 g/L, pH 7.0 [10]. Supplement it with nalidixic acid 10 mg/L, cycloheximide 20 mg/L (see Note 1). 5. Yeast Malt extract agar. 6. LB slants. 7. 50% glycerol.

3

Methodology

3.1 Collection of Soil and Root Samples

1. Collect the rhizospheric soil sample in a sterile polyvinyl bag and transport it under ice cold conditions. Then allow the sample for air drying at room temperature for a week [12]. 2. Collect the root sample from the rhizosphere carefully without destroying the plant and place it in a sterile sampling bag. Then transfer it into an ice-filled container (7  C) and store it at 4  C for further use [11].

3.2 Pretreatment/ Enrichment Process

This process eliminates the spore-forming bacteria other than actinobacteria. 1. Take 1 g of soil sample and treat it with dry heat at 120  C for 15 min (see Note 2). 1% phenol, 2% calcium carbonate, 0.1% SDS, 5% yeast extract is treated with the sample separately for 15 min [8]. 2. Wash the root sample in sterile 0.9% NaCl and keep it in a rotary shaker for 1 h (37  C) at 150 rpm [9].

3.3 Serial Dilution Method

1. Prepare a tenfold serial dilution (10 1 to 10 10), by transferring 1 mL each of the soil and root sample respectively from the pretreated sample suspensions into 9 mL of distilled water (10 1). 2. 10 2 solution is prepared by transferring 1 mL of 10 1 suspension into 9 mL of distilled water. Similarly prepare all the successive serial dilutions up to 10 1. 3. Spread 0.1 mL of the serially diluted suspensions using pipette onto the prepared medium like HVA, TSA, and SAC media by spread plate method, using a L-shaped spreader (see Note 3).

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4. Incubate the plates for 1 week at 30  C in the dark and sub-culture on LB slants. 5. Maintain the pure cultures in 50% glycerol at 4  C for future use [8]. 3.4 Membrane Filter Technique

This technique is employed to isolate the epiphytic actinobacteria from rhizospheric soil sample. 1. Place the membrane filters aseptically onto the prepared media like HVA, SAC, and TSA. 2. After air-heat drying process for 15 min, sprinkle 2–3 mg of the soil sample on the membrane filters. 3. Incubate the inoculated plates for 4 days at 28  C and re-incubate it for 3–4 weeks by removing membrane filter. 4. Subculture the colonies formed on LB slants. 5. Preserve the pure isolates in 50% glycerol at 4  C for future use [13].

3.5 Standard Enrichment Technique

To isolate epiphytic actinobacteria from the root sample, following technique is used. 1. After the pretreatment process of root sample, 5 mL of the pretreated suspension is inoculated onto MSM media. 2. Incubate the media for 1 week at 30  C on rotary shaker. 3. Enrichment process is carried out for 5 weeks by preparing fresh MSM media each time. 4. The isolates obtained on MSM media is inoculated on LB media by spread plate or streaking method to obtain the pure culture [11].

3.6 Direct Inoculation Technique

This technique is used to isolate the epiphytic actinobacteria from rhizospheric soil sample. 1. The soil sample of 2–3 mg is directly sprinkled onto SCA medium. Allow some time period for the interactions between soil particles and media to occur. 2. Incubate the media for 2–3 weeks at room temperature. 3. Subculture the actinobacterial colonies on Yeast Malt extract agar (ISP-2, International Streptomyces Project-2: composition g/L: yeast extract powder, 4 g; malt extract powder, 10 g; dextrose, 4 g; agar, 20 g, in 1 L distilled water, pH 6.2  0.2 at 25  C. 4. Preserve the pure isolates in LB slants with 50% glycerol at 4  C (13).

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Notes 1. The media is supplied with nalidixic acid (10 mg/L) and cycloheximide (20 mg/L) to preclude bacterial and fungal growth. Many other media are employed for isolating rhizospheric actinobacteria like, Chitin medium, Czapek agar medium, Soil extract agar medium, Synthetic agar medium, Chemically defined medium, Glucose asparagine agar medium, Gauze’s agar medium, and Arginine glycerol salt medium. 2. The pretreatment process of rhizospheric soil sample differs for different genera of actinobacteria. For Actinomadura, air-dried soil heated at 100  C for 15 min; Streptosporangium, air-dried soil heated at 120  C for 1 h; Streptomyces, soil suspensions heated at 45  C for 10 min; Micromonospora, soil suspensions heated at 60  C for 30 min; Dactylosporangium, air-dried soil heated at 120  C for 1 h, Herbidospora, air-dried soil heated at 28  C for 7 days. 3. For the isolation of actinobacteria of different genera, specific media are used, such as TSA media is used for isolating Arthrobacter genera, Soil extract agar media is used for isolating soilspecific actinobacteria.

References 1. Yadav AN, Verma P, Kumar S et al (2018) Actinobacteria from rhizosphere: molecular diversity, distributions and potential biotechnological applications. In: Singh BP, Passari AK (eds) New and future developments in microbial biotechnology and bioengineering. Elsevier, Amsterdam 2. Selvarajan R, Sibanda T, Venkatachalam S et al (2019) Distribution, interaction and functional profiles of epiphytic bacterial communities from the rocky intertidal seaweeds, South Africa. Sci Rep 9:19835. https://doi. org/10.1038/s41598-019-56269-2 3. Goodfellow M, Williams ST (1983) Ecology of actinomycetes. Annu Rev Microbiol 37:189–216 4. Yadav AN, Sachan SG, Verma P et al (2016) Bioprospecting of plant growth promoting psychrotrophic Bacilli from cold desert of north western Indian Himalayas. Indian J Exp Biol 54:142–150 5. Yadav AN, Verma P, Kour D et al (2017) Plant microbiomes and its beneficial multifunctional plant growth promoting attributes. Int J Environ Sci Nat Resour 3:1–8

6. Goodfellow M, Simpson KE (1987) Ecology of Streptomycetes. Front Appl Microbiol 2:97–125 7. Suzuki S, Yamamoto K, Okuda T et al (2000) Selective isolation and distribution of Actinomadura rugatobispora strains in soil. Actinomycetology 14:27–33 8. Jog R, Pandya M, Nareshkumar G et al (2014) Mechanism of phosphate solubilization and antifungal activity of Streptomyces spp isolated from wheat roots and rhizosphere and their application in improving plant growth. Microbiology 160:778–788. https://doi.org/10. 1099/mic.0.074146-0 9. Castillo I, Ojeda J, Megı´as E et al (2015) Isolation of endophytic, epiphytic and rhizosphere plant growth-promoting bacteria from cultivated rice paddy soils of the Guadalquivir river marshes. Global Adv Res J Agric Sci 4 (2):127–136 10. Wahyudi AT, Priyanto JP, Afrista R et al (2019) Plant growth promoting activity of actinomycetes isolated from soybean rhizosphere. OnLine J Biol Sci 19(1):1.8. https://doi.org/ 10.3844/ojbsci.2019.1.8

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11. Singh T, Singh DK (2018) Isolation and protein characterization of lindane degrading root epiphytic bacterium Arthrobacter sp. T16 from Typha latifolia. Not Sci Biol 10(4):559–566. https://doi.org/10.25835/nsb10410318 12. Khamna S, Yokota A, Lumyong S (2009) Actinomycetes isolated from medicinal plant rhizosphere soils: diversity and screening of antifungal compounds, indole-3-acetic acid

and siderophore production. World J Microbiol Biotechnol 25:649–655. https://doi. org/10.1007/s11274-008-9933-x 13. Njenga WP, Mwaura FB, Wagacha JM et al (2017) Methods of isolating actinomycetes from the soils of Menengai crater in Kenya. Arch Clin Microbiol 8(3):1–7. https://doi. org/10.4172/1989-8436.100045

Chapter 19 Isolation of Epiphytic Actinobacteria from Lichens M. S. Shabeena Banu, T. Nargis Begum, G. Vinothini, D. Dhanasekaran, and N. Thajuddin Abstract The ever-increasing broad spectrum of diseases and the urgent need to combat it has become a challenge, opening an exciting avenue in the field of biotechnology and biomedical research to produce a potent drug. Epiphytic Actinobacteria being a prolific producer of a thousand biologically active secondary metabolites play a significant role in the production of various antimicrobial, antiviral, anticancer, probiotics, and other industrially important compounds. Lichens as a symbiotic structure of alga and fungi known as the ecological niche of various kinds of microbes serve as an alternative source for the isolation of such novel Actinobacteria. The study focuses mainly on the collection, pretreatment, and isolation methods of Epiphytic Actinobacteria isolated from lichens, many of which have been successfully isolated and turned into useful drugs and other organic chemicals. With the increasing advancements in science and technology, there would be greater demand in the future for new bioactive compounds synthesized by Actinobacteria from various lichen sources. Key words Epiphytic, Actinobacteria, Secondary metabolites, Antimicrobial, Antiviral, Anticancer, Probiotics, Lichens, Bioactive compounds

1

Introduction Actinobacteria which are ubiquitous and one of the most diverse groups of bacteria in nature represent the largest taxonomic units among the 18 major lineages currently recognized within the domain bacteria [1]. Actinobacteria represent one of the most primitive lineages among prokaryotes which are believed to have evolved about 2.7 billion years ago [2]. They are found universally, that is, they are widely distributed in natural and all man-made environments. The members are anaerobic; however, some genera range from facultative to obligatory anaerobic, unicellular organisms, filamentous, and spore-forming lineages. “Actinobacteria/ Actinomycetes” derive their name from a Greek word called “atkis” (a ray) and “mykes” (fungus), having the characteristics of both Bacteria and Fungi, but yet possess plenty of distinctive

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features to restrict them into the “Kingdom bacteria” [3, 4]. They are found in diverse ecological niches such as in soils, lichens, rocks, fresh wastes, lake, river bottoms, marine water bodies, manures, composts, and dust as well as on plant residues and food products. Actinobacteria are widespread symbionts of eukaryotes, helping herbivores gain access to plant biomass as nutritional mutualists and producing natural products as defensive mutualists [5–7]. They are correspondingly potential producers of antibacterial and antifungal, antibiotics, anticancer, and other therapeutically useful compounds which have been developed into drugs for the treatment of a wide range of diseases in humans, veterinary, and agriculture sectors [8, 9]. Epiphytic Actinobacteria are more diverse and abundant than endophytic actinobacteria whereas there are only limited studies focusing on its insights and potentials. Epiphytic actinobacteria are found on the surface of all plant bodies and similarly on the outer surface of many lichens which are present on trees and rocks. The lichen-associated epiphytic actinobacteria have abundant biotechnological and pharmaceutical applications which is still an area that is less explored. Lichens serve as an alternative reservoir for the isolation of epiphytic actinobacteria. Lichens are symbiotic mixtures of fungi, green algae, and/or cyanobacteria and whereas these symbiotic components have been extensively described, the microbial community inhabiting this niche has not been well characterized [10]. Lichens are well organized, self-supporting, mutualistic symbiotic mixtures of fungi, green algae, and/or cyanobacteria forming a unique symbiotic structure, the lichen thallus [11, 12]. These symbiotic components have been extensively described and the microbial community inhabiting this niche has not been well characterized [13]. The present study focuses mainly on the collection and isolation of epiphytic actinobacteria from lichens.

2

Materials The materials required for the isolation of epiphytic actinobacteria from lichen samples are as follows.

2.1 Materials Required for the Collection of Lichens

1. Examine the fine structure of the thallus while collecting using a hand lens, preferably of 10 magnification. 2. The lichens from the barks or rock are collected using tools like a sharp, flat-edged chisel (1- to 2-in.-wide edge) and a hammer (1 kg weight). 3. Use a pointed or stout flat-edged chisel to collect lichens growing on rocks. Polythene packets (smaller (6  12 in.) and bigger sized), rubber bands, labeling stickers, a field

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book, notebook, pen, pencil, plant press, knife, secateurs (twig cutter), hand lens, old newspapers or blotters, (nylon) ropes, collection bags, and herbarium packets are the other necessary items required during a lichen collection trip. 4. An altimeter, Global Positioning System (GPS), camera, and few other instruments can be carried as per the objectives of the study [14]. 2.2 Materials and Media Required for the Isolation of Epiphytic Actinobacteria from Lichens

To isolate actinomycetes, three isolation media such as Starch Casein (SC), Luria Bertani (M1), Starch Nitrate (SN), and Kuster’s agar can be used (see Note 1). The materials required and media composition of the isolation media are as follows: 1. L-shaped glass rod (spreader), sterile distilled H2O, mortar and pestle, test tubes, pipettes and tips. 2. Starch Casein Agar (SCA) [15]. Starch

10.0 g

Potassium nitrate

2.0 g

Sodium chloride

2.0 g

Di-potassium hydrogen phosphate

2.0 g

Magnesium sulfate

0.05 g

Calcium carbonate

0.02 g

Ferrous sulfate

0.01 g

Casein

0.30 g

Agar

16.0 g

Distilled water

1000 mL

pH

7  0.2

3. Luria Bertani (M1) [16]. Starch

10 g

Peptone

2.0 g

Yeast extract

4.0 g

Agar

18.0 g

Distilled water

1000 mL

pH

7.0  0.1

4. Starch Nitrate Agar (SNA) [16]. Soluble starch

20.0 g

K2HPO4

1.0 g (continued)

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2.0 g

MgSO4

0.5 g

CaCO3

3.0 g

NaCl

100 g

FeSO4

0.1 g

MnCl2

0.1 g

ZnSO4

40.1 g

Distilled water

1000 mL

pH

7.0  0.1

5. Kuster’s Agar [16]. Glycerol

10.0 g

Casein

3.0 g

Potassium nitrate

2.0 g

Sodium chloride

2.0 g

Di-potassium hydrogen phosphate

2.0 g

Magnesium sulfate

0.05 g

Calcium carbonate

0.02 g

Ferrous sulfate

0.01 g

Agar

16.0 g

Distilled water

1000 mL

pH

7.0  0.2

6. International Streptomyces Project (ISP) 1 (tryptone-yeast extract broth). Tryptone

5.0 g

Malt extract

10.0 g

Agar

16.0 g

Distilled water

1000 mL

pH

7.0  0.2

7. Glucose Asparagine Agar [17]. Glucose

10.0 g

Asparagine

0.5 g

Di-potassium hydrogen phosphate

0.5 g

Agar

16.0 g (continued)

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Distilled water

1000 mL

pH

7.4

8. Kuster’s Agar. Glycerol

10.0 g

Casein

3.0 g

Potassium nitrate

2.0 g

Sodium chloride

2.0 g

Di-potassium hydrogen phosphate

2.0 g

Magnesium sulfate

0.05 g

Calcium carbonate

0.02 g

Ferrous sulfate

0.01 g

Agar

16.0 g

Distilled water

1000 mL

pH

7.0  0.2

All the above-mentioned chemicals purchased were of analytical grade from HiMedia, Sigma-Aldrich, or SRL, India.

3

Methods

3.1 Collection of Lichen Samples

An extensive collection of lichens is done from different sources like tree trunks, rocks, and marine system. Lichens are all visible to the naked eye and easy to collect. They are usually collected along with their substratum irrespectively of their growth form. The lichens that are loosely attached to substratum are scraped out and collected using a sharp scraper or knife; the lichens present on the edges or crevices of rock are collected by breaking the rock. The collected lichens are then stored in polythene packets and closed with the help of rubber bands and used for isolating epiphytic actinobacteria. The locality and the altitude of the area of collection are noted using GPS [14, 18].

3.2 Pretreatment of the Sample

1. Collect the lichen samples and air dry at room temperature for about 2–3 days to remove unwanted Gram-negative bacteria [19]. 2. Each lichen sample (300–500 mg) is washed twice with sterile water to remove solid particles adhering to the surface. 3. The pretreated lichen samples are further used for the isolation of epiphytic actinobacteria.

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3.3 Isolation of Pure Culture of Epiphytic Actinobacteria from Lichens

The isolation of epiphytic actinobacteria from lichens can be carried out by two methods, by serial dilution of the lichen samples without homogenizing it or by treating the cut lichen samples directly with antifungal antibiotics and plated it directly to avoid fugal contamination and enhance specific epiphytic actinobacterial isolation (see Note 1).

3.3.1 Method I

Isolation of Epiphytic Actinobacteria from Lichen Samples by Serial Dilution Method

1. Wash the pretreated lichen samples and rinse it with sterile distilled water. 2. The washed lichen sample is immersed in a conical flask containing distilled water and kept in a shaker for 2 h. 3. After 2 h about 1 mL from the conical flask was taken and serially diluted with distilled water in four dilutions (10 1, 10 2, 10 3, and 10 4). 4. About 0.1 mL of four dilutions 10 2, 10 3, 10 4, and 10 5 are spread over evenly on the surface of the SCA/Luria Bertani (M1), SNA/Kuster’s agar plates (Fig. 1) using L-rod, amended with Cycloheximide (50 mg/L) and Nalidixic acid (20 mg/L) to avoid unnecessary fungal growth (see Note 2) and incubate it at 28  C for 5–7 days until powdery pinpoint actinobacterial colonies are obtained with a clear zone of inhibition. 5. Incubate the plates at 28  C for 5–7 days (see Note 3). 6. After 7 days of incubation, observe the plates for powdery, pinpoint colonies, characteristic of actinobacteria, with a clear zone of inhibition around them being selected. 7. Subsequently, a single actinobacterial colony is picked up and purified with repeated subcultures using SCA or other actinobacterium isolation media to get a pure culture. 8. The purified actinobacterial isolates are then preserved in International Streptomyces Project (ISP)1 (tryptone-yeast extract broth) at 4  C and 25% v/v glycerol stock stored at 40  C for long-time preservation [20, 21] (see Note 4). 9. The selected and identified colonies of actinobacteria are transferred to starch casein agar slant and incubated at 28  C for their growth. After incubation, the slants containing pure epiphytic actinobacterial isolates are stored at 4  C for further studies. 3.3.2 Method II

Isolation of Epiphytic Actinobacteria by Direct Inoculation of Whole Lichen Samples

1. Take the pretreated lichen samples, and rinse with sterile distilled water.

Isolation of Epiphytic Actinobacteria from Lichens

10-1 Diluon

Lichen Sample

10-4 Diluon

10-2 Diluon

Front view of purified Acnobacterial isolate

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10-3 Diluon

Back view of purified Acnobacterial isolate

Fig. 1 Isolation of epiphytic actinobacteria from lichen samples through serial dilution technique (plates of 10 2, 10 3, 10 4, and 10 5 dilutions)

2. Prepare different concentrations of ethanol (0%, 30%, 50%, and 70%) with sterile distilled water (see Note 5). 3. Take the lichen samples and cut into small pieces of about 1 cm each using sterile forceps, wash it with different concentrations of ethanol (0%, 30%, 50%, and 70%) for 2 min in order to minimize the growth of other microbiome adhering to the epiphytic regions of the lichens (Fig. 2). 4. The lichen sample is then washed again with sterile distilled water to remove ethanol. 5. The cut lichen samples is treated with ethanol and placed onto the surface of the SCA plates, using sterile forceps, separately for different concentrations each which is amended with Cycloheximide (50 μg/mL) and Nystatin (50 μg/mL) to avoid unnecessary fungal growth. 6. The plates are then kept for incubation at 28  C for 5–7 days. 7. After 7 days of incubation, observe the plates for powdery, pinpoint colonies, characteristic of actinobacteria. The isolates with a clear zone of inhibition around them were selected from each plate containing cut samples of lichens in varying concentrations of ethanol. 8. Subsequently, single actinobacterial colony is picked up and purified with repeated subcultures using SCA or other actinobacterium isolation media to get a pure culture.

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0% Ethanol

Lichen Sample

50% Ethanol

Front view of purified Acnobacterial isolate

30% Ethanol

70% Ethanol

Back view of purified Acnobacterial isolate

Fig. 2 Isolation of epiphytic actinobacteria by direct inoculation of whole lichen samples treated with varying concentration of ethanol (0%, 30%, 50%, and 70%)

9. Prepare SCA slants containing pure actinobacterial isolates which is stored at 4  C for further studies. 10. The slants can also be stored at

4

20  C for further studies.

Notes 1. Isolation of epiphytic actinobacteria works well and provides visible colonies while performing by method I, whereas when the pretreated lichen samples is treated with ethanol by method II, to minimize the external microbiome growth on plates may at times inhibit the growth of our expected actinobacterial isolates. 2. Actinobacteria share fungal morphology as some actinobacterial species produce mycelium, and at times it becomes difficult to differentiate actinobacterial isolates from fungal growth. The fungi may also grow the actinobacterial colonies inhibiting the isolation process. Thus, adding antifungal antibiotics like Cycloheximide, Nystatin, Nalidixic acid, etc., prevents unnecessary fungal contamination, making actinobacterial isolation an easier process. 3. Actinobacteria can considerable grow well also at normal temperature. A constant check on the agar plates should be done to prevent any overgrowth of fungal contaminants that often

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129

spreads over the actinobacterial colonies which will make isolation difficult. As soon as any individual actinobacterial colonies are observed in the agar plates with a clear zone around, it should be picked carefully and subcultured repeatedly until pure culture is obtained. 4. Storage of actinobacterial isolate is a very important process as in due course of any experimental work there are chances of losing the pure isolate due to any physiological conditions or any fungal contaminations. There are chances of isolates in agar plates becoming slimy and producing liquid droplets along the streaks when kept outside for a long time. Hence the pure culture must be stored by preparing the glycerol stock at 40  C or at 4  C. 5. Treating the lichen samples with 30–50% of ethanol concentrations will minimize the growth of microbiome giving individual colonies that enables easy observation and isolation of required epiphytic actinobacteria. References 1. Ludwig W, Euze´by J, Schumann P, Busse HJ, Trujillo ME, K€ampfer P, Whitman WB (2012) Road map of the phylum Actinobacteria. In: Bergey’s manual® of systematic bacteriology. Springer, New York, NY, pp 1–28 2. Battistuzzi FU, Hedges SB (2009) A major clade of prokaryotes with ancient adaptations to life on land. Mol Biol Evol 26(2):335–343 3. Lewin GR, Carlos C, Chevrette MG, Horn HA, McDonald BR, Stankey RJ, Currie CR (2016) Evolution and ecology of Actinobacteria and their bioenergy applications. Annu Rev Microbiol 70:235–254 4. Das A, Khosla C (2009) Biosynthesis of aromatic polyketides in bacteria. Acc Chem Res 42 (5):631–639 5. Book AJ, Lewin GR, McDonald BR, Takasuka TE, Wendt-Pienkowski E, Doering DT, Currie CR (2016) Evolution of high cellulolytic activity in symbiotic Streptomyces through selection of expanded gene content and coordinated gene expression. PLoS Biol 14 (6):e1002475 6. Coombs JT, Michelsen PP, Franco CM (2004) Evaluation of endophytic actinobacteria as antagonists of Gaeumannomyces graminis var. tritici in wheat. Biol Control 29(3):359–366

7. Currie CR, Scott JA, Summerbell RC, Malloch D (1999) Fungus-growing ants use antibioticproducing bacteria to control garden parasites. Nature 398(6729):701–704 8. Janardhan A, Kumar AP, Viswanath B, Saigopal DVR, Narasimha G (2014) Production of bioactive compounds by actinomycetes and their antioxidant properties. Biotechnol Res Int 2014:217030 9. Castillo UF, Strobel GA, Ford EJ, Hess WM, Porter H, Jensen JB, Stevens D (2002) Munumbicins, wide-spectrum antibiotics produced by Streptomyces NRRL 30562, endophytic on Kennedia nigriscans. The GenBank accession number for the sequence determined in this work is AY127079. Microbiology 148 (9):2675–2685 10. Ahmadjian V (1993) The lichen symbiosis. Wiley, New York, NY 11. Suzuki MT, Parrot D, Berg G, Grube M, Tomasi S (2016) Lichens as natural sources of biotechnologically relevant bacteria. Appl Microbiol Biotechnol 100(2):583–595 12. de la Torre JR, Goebel BM, Friedmann EI, Pace NR (2003) Microbial diversity of cryptoendolithic communities from the McMurdo Dry Valleys, Antarctica. Appl Environ Microbiol 69:3858–3867

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13. Nayaka S (2005) Studying lichens. Sahyadri E-News, Western Ghats Biodiversity Information 14. Ku¨ster E, Williams ST (1964) Production of hydrogen sulfide by streptomycetes and methods for its detection. Appl Microbiol 12 (1):46–52 15. Njenga WP, Mwaura FB, Wagacha JM et al (2017) Methods of isolating Actinomycetes from the soils of Menengai Crater in Kenya. Arch Clin Microbiol 8:3 16. Waksman SA (1961) The role of antibiotics in nature. Perspect Biol Med 4(3):271–287. https://doi.org/10.1353/pbm.1961.0001 17. Jiang Y, Li Q, Chen X, Jiang C (2016) Isolation and cultivation methods of actinobacteria. In: Dhanasekaran D, Jiang Y (eds) Actinobacteria–basics and biotechnological applications. InTech, Rijeka, pp 39–57 18. Gayathri P, Muralikrishnan V (2013) Isolation and characterization of endophytic

actinomycetes from mangrove plant for antimicrobial activity. Int J Curr Microbiol App Sci 2 (11):78–89 19. Chaudhary HS, Yadav J, Shrivastava AR, Singh S, Singh AK, Gopalan N (2013) Antibacterial activity of actinomycetes isolated from different soil samples of Sheopur (a city of Central India). J Adv Pharm Technol Res 4 (2):118 20. Nayaka S (2014) Methods and techniques in collection, preservation and identification of lichens. Plant taxonomy and biosystematics: classical and modern methods. New India Publishing Agency, New Delhi, pp 101–105 21. Sheik GB, Maqbul MS, Gokul Shankar S, Ranjith MS (2017) Isolation and characterization of actinomycetes from soil of Ad-Dawadmi, Saudi Arabia and screening their antibacterial activities. Int J Pharm Pharm Sci 9 (10):276–279

Chapter 20 Isolation of Endophytic Actinobacteria from Lichens M. S. Shabeena Banu, T. Nargis Begum, D. Dhanasekaran, and N. Thajuddin Abstract With the likelihood of discovering new drugs with new chemical structures to combat various lifethreatening diseases, Actinobacteria continue to be the mainstream supplier of various antibiotics in biotechnological industries. In this context, Actinobacteria are receiving much attention in recent years serving as a source of biotechnologically potential compounds. Lichens contribute as an alternative rich reservoir which harbors diverse microorganisms that include Actinobacteria. The study focuses on different methods of isolation of endophytic actinobacteria isolated from lichens. The collection, pretreatment, and isolation methods of lichen-associated actinobacteria are introduced and discussed. There is evidence to suggest that the unique nature of the symbiosis has played a substantial role in shaping many aspects of lichen chemistry. The study of cultivable endophytic actinobacteria isolated from lichens, confers a better explicit of the physiological functions of these microorganisms within the “lichen microbiome.” Key words Endophytic, Actinobacteria, Lichens, Collection, Pretreatment, Microbiome

1

Introduction Actinobacteria (Actinomycetes), gram-positive, aerobic, filamentous bacteria with high G + C content with the GC% of 57%– 75%, serve as a mainstream supplier of a variety of natural drugs and other bioactive metabolites, including antibiotics, inhibitors, and enzymes [1]. The distribution of Actinobacteria in various natural habitats, including soil, ocean, extreme environments, plants, and animals has been reported to date. As there is an alarming scarcity and a need for new antibiotics against many multidrugresistant bacteria and other diseases, microbial natural products remain the most promising source of natural antibiotics. Actinobacteria being a prolific producer of antibiotics and important suppliers to the pharmaceutical and other industries are timehonored for their ability to produce secondary metabolites, many of which are active against pathogenic microorganisms [2]. More than 22,000 bioactive secondary metabolites (including

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_20, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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antibiotics) from microorganisms have been identified and published in many scientific and patent literature, and about half of these compounds are produced by Actinobacteria. So far, approximately 160 antibiotics have been used in human therapy and agriculture, and 100–120 of these compounds, including streptomycin, erythromycin, gentamicin, vancomycin, vermectin, etc., are produced by actinobacteria [3, 4]. In this context, some of these actinobacteria have an endophytic lifestyle which can penetrate the interior of plants or lichens and colonize intracellular spaces and vascular tissues, where they reside showing beneficial, symbiotic, neutral, or pathogenic interactions with the host [5–7]. Lichens have increasingly become a subject of research in microbial biotechnology, as they comprise a wide range of microecosystem within. Recent researches have shown that the lichenized fungi are symbiotic mixtures of fungi, green algae, and/or cyanobacteria with a wide variety of morphologies that have worldwide distribution [8, 9]. As pioneers of terrestrial habitats colonization, they are found from arctic to tropical regions in a large diversity of environments developing among others on stones, arid soils, or as epiphytes on plants [10]. On this background, lichens serve as an alternative rich reservoir for the isolation of endophytic actinobacteria representing a rich untapped source of secondary metabolites. Lichens grow in diverse climatic conditions and on diverse substrates. The lichens that grow on tree trunk and bark are called corticolous lichens, the twig inhabiting ones are ramicolous, the lichens that grow on wood—legnicolous, on rocks and boulders— saxicolous (epilithic), on moss—muscicolous, on soil—terricolous, and on evergreen leaves—foliicolous (epiphyllous). Although there are thousands of species of lichens, there are three main types of lichens based on the appearance of the thallus; they are Crustose, Foliose, and Fruticose. There are few other intermediate categories differentiated based on their growth forms such as Leprose, Placodioid, Squamulose, and Dimorphic lichens (Table 1) (Fig. 1) [11–13]. Thus, these lichens serve as an alternative resource for the isolation of novel endophytic actinobacteria, to explore its diversity, and to study its extremely rich metabolism accompanied by the production of secondary metabolites of extreme chemical diversity serving as a source of biotechnologically potential compounds.

2

Materials The materials required for the isolation of endophytic actinobacteria from lichen samples are as follows.

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Table 1 Types of lichens differentiated based on thallus formation and intermediate growth forms [11–13] Types of lichens based on their thallus formation 1. Crustose lichens

The thallus is closely attached to the substrate, without leaving any free margin giving a thin crust like appearance

2. Foliose lichens

They are called as leafy lichens. The thallus is loosely attached to the substratum. They grow in a more-or-less sheet-like form, but often with a lobed appearance

3. Fruticose lichens

The lichen thallus is attached to the substratum at one point and the remaining major portion either grows erect or hang making it three-dimensional

Types of intermediated growth forms of lichens 4. Leprose lichens The lichen appears powdery or granular and does not form smooth thallus 5. Placodioid lichens

The lichen thallus is closely attached to the substratum at center and lobate or free at the margin, but lack rhizines

6. Squamulose lichens

The lichen thallus is in the form of minute lobes, having a dorsiventral differentiation. This is a form intermediate between crustose and foliose

7. Dimorphic lichens

The lichens single thallus has the characters of both foliose/squamulose and fruticose lichens. The squamules are the primary thallus, which bears an erect body of fruticose lichen, the secondary thallus

a

b

c

d

e

f

g

h

Fig. 1 Different types of lichens: (a) Crustose lichens, (b) Foliose lichens, (c) Fruticose lichens, (d) Leprose lichens, (e) Placodioid lichens, (f) Squamulose lichens, (g) Dimorphic lichens, (h) Saxicolous lichens [11] 2.1 Materials Required for the Collection of Lichens

1. A hand lens, preferably of 10 magnification, is necessary to examine the fine structure of the thallus while collecting. 2. A sharp, flat-edged chisel (1- to 2-in.-wide edge) and a hammer (1 kg weight) are the tools required for collecting lichens from the bark. 3. A pointed or stout flat-edged chisel can be used to collect lichens growing on rocks. Polythene packets (smaller

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(6  12 in.) and bigger sized), rubber bands, labeling stickers, a field book, notebook, pen, pencil, plant press, knife, secateurs (twig cutter), hand lens, old newspapers or blotters, (nylon) ropes, collection bags, and herbarium packets are the other necessary items required during a lichen collection trip. 4. An altimeter, Global Positioning System (GPS), camera, and few other instruments can be carried as per the objectives of the study [11]. 2.2 Materials and Media Required for the Isolation of Endophytic Actinobacteria from Lichens

To isolate actinomycetes, three isolation media such as Starch Casein (SC), Luria Bertani (M1), Starch Nitrate (SN), and Kuster’s agar can be used (see Note 1). The materials required and media composition of the isolation media are as follows: 1. L-shaped glass rod (spreader), sterile distilled H2O, mortar and pestle, test tubes, pipettes and tips. 2. Starch Casein Agar (SCA) [14]. Starch

10.0 g

Potassium nitrate

2.0 g

Sodium chloride

2.0 g

Dipotassium hydrogen phosphate

2.0 g

Magnesium sulfate

0.05 g

Calcium carbonate

0.02 g

Ferrous sulfate

0.01 g

Casein

0.30 g

Agar

16.0 g

Distilled water

1000 mL

pH

7  0.2

3. Luria Bertani (M1) [15]. Starch

10 g

Peptone

2.0 g

Yeast extract

4.0 g

Agar

18.0 g

Distilled water

1000 mL

pH

7.0  0.1

4. Starch Nitrate Agar (SNA) [15]. Soluble starch

20.0 g (continued)

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K2HPO4

1.0 g

KNO3

2.0 g

MgSO4

0.5 g

CaCO3

3.0 g

NaCl

100 g

FeSO4

0.1 g

MnCl2

0.1 g

ZnSO4

40.1 g

Distilled water

1000 mL

pH

7.0  0.1

5. Kuster’s Agar [15]. Glycerol

10.0 g

Casein

3.0 g

Potassium nitrate

2.0 g

Sodium chloride

2.0 g

Di-potassium hydrogen phosphate

2.0 g

Magnesium sulfate

0.05 g

Calcium carbonate

0.02 g

Ferrous sulfate

0.01 g

Agar

16.0 g

Distilled water

1000 mL

pH

7.0  0.2

6. International Streptomyces Project (ISP)1 (tryptone-yeast extract broth). Tryptone

5.0 g

Malt extract

10.0 g

Agar

16.0 g

Distilled water

1000 mL

pH

7.0  0.2

All the above-mentioned chemicals purchased were of analytical grade from HiMedia, Sigma-Aldrich, or SRL, India.

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Methods

3.1 Collection of Lichen Samples

An extensive collection of lichens is done from different sources like tree trunks, rocks, and marine system. Lichens are all visible to the naked eye and easy to collect. They are usually collected along with their substratum irrespectively of their growth form. The lichens that are loosely attached to substratum are scraped out and collected using a sharp scraper or knife; the lichens present on the edges or crevices of rock are collected by breaking the rock. The collected lichens are then stored in polythene packets and closed with the help of rubber bands and used for isolating endophytic actinobacteria. The locality and the altitude of the area of collection are noted using GPS [11, 16].

3.2 Pretreatment of the Sample

1. Several physical and chemical pretreatments have been used for the isolation of endophytic actinobacteria. 2. The collected lichen samples are air dried at room temperature for about 2–3 days to remove unwanted Gram-negative bacteria [17]. 3. Each lichen sample of (300–500 mg) is washed twice with sterile water to remove solid particles adhering to the surface. 4. It is then surface sterilize by sequential immersion in 70% ethanol for 5 mins and a solution of sodium hypochlorite (0.9% available chlorine) for 20 min [18]. 5. Samples are then washed in sterile water thrice to remove the surface sterilization agents (see Note 2). 6. The pretreated lichen samples can be further used for the isolation of endophytic actinobacteria.

3.3 Isolation of Pure Culture of Endophytic Actinobacteria from Lichens

1. About 1–2 g of dried pretreated lichen samples are homogenized using mortar and pestle with 5–10 mL of distilled water in an aseptic condition (see Note 3). 2. 1.0 mL of homogenized sample is then serially diluted from 10 1 to 10 5 dilutions in 10 mL of distilled water each. 3. Then 0.1 mL of four dilutions 10 2, 10 3, 10 4, and 10 5 was spread over evenly on the surface of the SCA/Luria Bertani (M1), SNA/Kuster’s agar plates (Fig. 2), supplemented with Cycloheximide (50 μg/mL) and Nystatin (50 μg/mL) to avoid unnecessary fungal growth (see Note 4). 4. The plates were incubated at 28  C for 5–7 days (see Note 5). 5. After 7 days of incubation, the plates are observed for powdery, pinpoint colonies, characteristic of actinobacteria, with a clear zone of inhibition around them being selected.

Isolation of Endophytic Actinobacteria from Lichens

10-2 Dilution

10-3 Dilution

10-4 Dilution

Front view of purified Actinobacterial isolate

Back view of purified Actinobacterial isolate

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10-5 Dilution

Fig. 2 Isolation of endophytic actinobacterial isolate from lichen samples through serial dilution technique (plates of 10 2, 10 3, 10 4, and 10 5 dilutions)

6. Subsequently, single actinobacterial colony was picked up and purified with repeated subcultures using SCA or other actinobacterium isolation media to get a pure culture. 7. The purified actinobacterial isolates were then preserved in International Streptomyces Project (ISP)1 (tryptone-yeast extract broth) at 4  C and 25% v/v glycerol stock stored at 40  C for long time preservation [17, 19] (see Note 6). 8. The selected and identified colonies of actinobacteria can also be transferred to starch casein agar slant and incubated at 28  C for their growth. After incubation, the slants containing pure actinobacterial isolates can be stored at 4  C for further studies [20].

4

Notes 1. Isolation of lichen-associated endophytic actinobacteria can be preferably done using basic Starch Casein Agar (SCA), as it supports mostly the growth of all actinobacteria by minimizing the bacterial contaminations. 2. The surface sterilization agents that are used to sterilize the surface of lichen samples during pretreatment must be removed thoroughly as it will inhibit the growth of endophytic actinobacteria during isolation.

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3. The whole isolation process should be done in a proper aseptic condition with all sterile equipment and sterile water in order to avoid the growth of actinobacterial contaminants other than the lichen-associated actinobacteria during the process of isolation. It is notable that the isolation of actinobacteria is a much challenging process which needs a considerable amount of patience and a proper handling throughout the process. 4. As the actinobacteria share fungal morphology and produce mycelium, at times it becomes difficult to differentiate actinobacterial isolates from fungal growth. Thus, adding antifungal antibiotics like Cycloheximide and Nystatin prevents unnecessary fungal contamination, making actinobacterial isolation an easier process. 5. Actinobacteria can considerable grow well also at normal temperature. A constant check on the agar plates should be done to prevent any overgrowth of fungal contaminants that often spreads over the actinobacterial colonies which will make isolation difficult. As soon as any individual actinobacterial colonies are observed in the agar plates with a clear zone around, it should be picked carefully and subcultured repeatedly until pure culture is obtained. 6. Storage of actinobacterial isolate is a very important process as in due course of any experimental work there are chances of losing the pure isolate due to any physiological conditions or any fungal contaminations. There are chances of isolates in agar plates becoming slimy and producing liquid droplets along the streaks when kept outside for a long time. Hence the pure culture must be stored by preparing the glycerol stock at 40  C or at 4  C. References 1. Lo CW, Lai NS, Cheah HY, Wong NKI, Ho CC (2002) Actinomycetes isolated from soil samples from the Crocker range Sabah. ASEAN Rev Biodiver Environ Conserv 9:1–7 2. Roshan K, Koushik B, Vikas S, Pankaj K, Avijit T (2014) Actinomycetes: potential bioresource for human welfare: a review. Res J Chem Environ Sci 2(3):05–16 3. Berdy J (2005) Bioactive microbial metabolites. J Antibiot 58(1):1–26 4. Berdy J (2012) Thoughts and facts about antibiotics: where we are now and where we are heading. J Antibiot 65(8):385–395

5. Tervet IW, Hollis JP (1948) Bacteria in the storage organs of healthy plants. Phytopathology 38:960–967 6. Hallmann J, Berg G, Schulz B (2006) Isolation procedures for endophytic microorganisms. In: Microbial root endophytes. Springer, Berlin, pp 299–319 7. Araujo WL, Marcon J, Maccheroni W, van Elsas JD, van Vuurde JW, Azevedo JL (2002) Diversity of endophytic bacterial populations and their interaction with Xylella fastidiosa in citrus plants. Appl Environ Microbiol 68 (10):4906–4914

Isolation of Endophytic Actinobacteria from Lichens 8. Gonzalez I, Ayuso-Sacido A, Anderson A, Genilloud O (2005) Actinomycetes isolated from lichens: evaluation of their diversity and detection of biosynthetic gene sequences. FEMS Microbiol Ecol 54(3):401–415 9. Ahmadjian V (1993) The lichen symbiosis. Wiley, Chichester 10. Crittenden PD, Porter N (1991) Lichenforming fungi: potential sources of novel metabolites. Trends Biotechnol 9(1):409–414 11. Nayaka S (2005) Studying lichens. Sahyadri E-News, Western Ghats Biodiversity Information 12. Coppins BJ (1993) A key to the microlichens of India, Nepal and Sri Lanka. By DD Awasthi. [Bibliotheca Lichenologica, No. 40]. Berlin & Stuttgart: J. Cramer. 1991. Pp. 332+ 2 [Addendum], ISBN 3-443-58019 X. Price DM 130. Lichenologist 25(1):101–101 13. Awasthi DD (1988) A key to the macro lichens of India and Nepal. J Hattoi Bot Lab 65:207–302 14. Ku¨ster E, Williams ST (1964) Production of hydrogen sulfide by streptomycetes and methods for its detection. Appl Microbiol 12 (1):46–52 15. Njenga WP, Mwaura FB, Wagacha JM et al (2017) Methods of isolating Actinomycetes

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from the soils of Menengai Crater in Kenya. Arch Clin Microbiol 8:3 16. Nayaka S (2014) Methods and techniques in collection, preservation and identification of lichens. In: Plant taxonomy and biosystematics: classical and modern methods. New India Publishing Agency, New Delhi, pp 101–105 17. Jiang Y, Li Q, Chen X, Jiang C (2016) Isolation and cultivation methods of Actinobacteria. In: Jiang Y, Dhanasekaran D (eds) Actinobacteria–basics and biotechnological applications. InTech, Rijeka, pp 39–57 18. Gayathri P, Muralikrishnan V (2013) Isolation and characterization of endophytic actinomycetes from mangrove plant for antimicrobial activity. Int J Curr Microbiol Appl Sci 2 (11):78–89 19. Chaudhary HS, Yadav J, Shrivastava AR, Singh S, Singh AK, Gopalan N (2013) Antibacterial activity of actinomycetes isolated from different soil samples of Sheopur (a city of Central India). J Adv Pharm Technol Res 4 (2):118 20. Sheik GB, Maqbul MS, Gokul Shankar S, Ranjith MS (2017) Isolation and characterization of actinomycetes from soil of Ad-Dawadmi, Saudi Arabia and screening their antibacterial activities. Int J Pharm Pharm Sci 9 (10):276–279

Chapter 21 Isolation of Psychrophilic and Psychrotolerant Actinobacteria Manigundan Kaari, Abirami Baskaran, Gopikrishnan Venugopal, Radhakrishnan Manikkam, and Parli V. Bhaskar Abstract Extreme environments with low temperatures constitute peculiar ecosystems that conceal novel biodiversity. These environments are colonized by cold loving organisms named psychrophiles, which have high biomass, diversity, and wide distribution when compared with other organisms thriving in extreme environments. Actinobacteria have the ability to survive in harsh environmental conditions like high salinity, high and low temperature, acidic and alkaline conditions. Actinobacterial diversity in the polar ecosystems has been extensively studied in the recent years using both culture-dependent and culture-independent techniques. Exploring novel actinobacterial strains has laid the foundations for potential industrial and biotechnological applications. This chapter describes the steps involved in sample processing and isolation of psychrophilic and psychrotolerant actinobacteria from water and sediment samples from cold environments. Key words Actinobacteria, Psychrophilic, Psychrotolerant, Filtration

1

Introduction The majority of Earths’ biosphere represented by cold environments have been successfully colonized by psychrophilic (i.e., cold loving) and psychrotolerant microorganisms. They are able to thrive at low temperatures and maintain metabolic activity at subzero temperatures. Numerous investigations have reported the distribution of actinobacteria in cold climatic conditions of Polar Regions including Antarctic, Arctic, Southern Ocean, and Himalayan Glaciers. The relative abundance of actinobacteria was high in permafrost, ice cores, cryoconite, and the forelands of glaciers ˜ aga et al. [2] investigated the actinobacterial [1]. Milla´n-Aguin diversity and evolution in polar environments. Culture-dependent analysis revealed that a total of 78% of isolated strains belonged to the phylum Actinobacteria and all of it corresponding to rare

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_21, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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actinomycete or non-Streptomyces genera. Almost all of the isolates belonged to five genera—Agrococcus, Pseudonocardia, Microbacterium, Salinibacterium, and Rhodococcus. Pyrosequencing data of sediment samples collected from Adelie Basin of Antarctica revealed that the sequence reads comprised nearly 10% actinobacteria [3]. Psychrophilic and psychrotolerant actinobacteria from such polar ecosystems possess the potential to produce novel bioactive compounds such as cold active enzymes, proteins, polysaccharides, lipids, and pigments [4]. Therefore the successful isolation of such cold loving actinobacteria is a prerequisite for exploring its biotechnological applications. There are general and specific approaches described to isolate cold loving actinobacteria from polar environments. Sivasankar et al. [5] collected samples from two sampling sites (Polar Front—1 and 2) during the seventh Indian Scientific Expedition to the Southern Ocean and successfully isolated and identified 9 strains of psychrophilic and psychrotolerant actinobacteria. This chapter highlights the selective procedure for successful isolation of psychrophilic and psychrotolerant actinobacteria.

2

3

Materials l

Samples—seawater, sediment.

l

Filtration Unit.

l

Membrane filter—0.2μm.

l

Isolation media—Actinomycetes Isolation agar (AIA), Starch Casein agar (SCA), Nutrient Agar (NA).

l

Sterile seawater.

l

Nystatin.

l

Nalidixic acid.

l

Incubator—4 and 20  C.

l

Micropipette with tips.

l

Petri plates.

l

Test tubes.

l

15 ml screw cap tubes.

l

Forceps.

Methods

3.1 Sample Collection

1. Collect 1 l of seawater samples at different depths vertically from polar ecosystems like Southern Ocean using Niskin water bottles attached with CTD.

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2. Collect the surface water samples through bucket sampling using sterile container. 3. Collect the surface sediment samples at different depths from selected locations using gravity coring and box coring methods. 3.2 Filtration of Water Sample

1. Filter each 1 l of water sample using 0.2μm filter paper. 2. Transfer the filter paper into a 15 ml screw cap tube containing 10 ml of sterile seawater. 3. Store the samples at 4  C for further studies.

3.3 Serial Dilution and Isolation

1. Take 1 ml of aliquot from 10 ml of water sample (filter paper) and serially dilute up to 106 dilutions in sterile seawater. 2. Similarly, serially dilute 1 g of marine sediment sample in 9 ml of sterile seawater up to 106 dilutions. 3. Prepare AIA, SCA, and NA plates using seawater supplemented with filter-sterilized nystatin (100μg/ml) and nalidixic acid (20μg/ml) to retard the growth of fungi and Gram negative bacterial populations, respectively. 4. Transfer each 100μl aliquot of diluted sample from 104, 105, and 106 dilutions to two of each isolation agar plates. 5. Incubate one set of plates at 4  C for 4–8 weeks to isolate psychrophilic actinobacteria. 6. Incubate another set of plates at 15–20  C for 4–6 weeks to isolate psychrotolerant actinobacteria. 7. Recover and subculture the colonies with suspected actinobacterial morphology (See Notes 1 and 2) in their respective isolation agar medium by incubating them at their respective psychrophilic or psychrotolerant temperatures, until sufficient growth.

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Notes 1. Most of the psychrophilic and psychrotolerant actinobacterial genera belong to nonfilamentous or rare actinobacterial groups which makes them difficult to recover based on their colony morphology. 2. It is advisable to perform Gram staining to select Gram positive bacteria and later perform other characterization studies to identify actinobacterial genera.

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References 1. Zhang B, Wu X, Zhang G, Li S, Zhang W, Chen X, Sun L, Zhang B, Liu G, Chen T (2016) The diversity and biogeography of the communities of Actinobacteria in the forelands of glaciers at a continental scale. Environ Res Lett 11(5):054012 ˜ aga N, Soldatou S, Brozio S, Mun2. Milla´n-Aguin noch JT, Howe J, Hoskisson PA, Duncan KR (2019) Awakening ancient polar Actinobacteria: diversity, evolution and specialized metabolite potential. Microbiology 165(11):1169–1180 3. Carr SA, Orcutt BN, Mandernack KW, Spear JR (2015) Abundant Atribacteria in deep marine

sediment from the Ade´lie Basin. Antarctica Front Microbiol 6:872 4. Yarza´bal LA (2016) Antarctic psychrophilic microorganisms and biotechnology: history, current trends, applications, and challenges. In: Microbial models: from environmental to industrial sustainability. Springer, Singapore, pp 83–118 5. Sivasankar P, Rekadwad B, Poongodi S, Sivakumar K, Parli BV, Kumar NA (2018) Bioinformatics delimitation of the psychrophilic and psychrotolerant actinobacteria isolated from the polar frontal waters of the Southern Ocean. Data Brief 18:576–584

Chapter 22 Isolation of Halophilic Actinobacteria from Different Habitats A. Martin Paul and D. Jayanthi Abstract Prokaryotic microorganisms exhibit very diverse and extreme dwelling habitats. One of such is ought to be the group Actinobacteria with varied habitat requirements including both terrestrial and aquatic environments. Actinobacteria are generally extremophiles and extreme tolerant organisms such as halotolerant, haloalkalitolerant, xerophilic, psychrotolerant, and thermotolerant forms. Halophilic actinobacteria have been usually isolated from alkaline saline habitats (soil), seawater, salt lakes, and brines. The novelty of halophilic actinobacteria has been the economically potent metabolites both at industrial and therapeutic strata. And they have been appraised for secondary metabolites and regarded as an indispensable source of natural bioactive molecules. The intrinsic properties of actinobacteria have disposed the scientific community to be reliant on their metabolites. The surges for actinobacterial novel biomolecules are in demand, and immense innovative methodologies and technologies are obligatory to unravel the treasure of halophilic actinobacterial communities and their associated biomes. With the given pedestal, the present chapter provides insight into elucidating different ways of isolation and identification of halophilic and halotolerant actinobacteria from microenvironment of hypersaline habitats such as associated biospheres of rhizosphere soils, lakes, and marine ecosystems. Key words Actinobacteria, Halophilic, Hypersaline, Rhizosphere, Marine microenvironment

1

Introduction Adaptation is a prerequisite for living organisms to survive, establish, and evolve. Such kind of interaction is evident even from domains of prokaryotic organism from different ecosystems leading to unique environmental niches. Prokaryotic microorganisms exhibit very diverse and extreme dwelling habitats due to their metabolic versatility. For that reason they are known to thrive well in biotic conditions and even at extreme borderlines of abiotic conditions where growth and reproduction are ideal by developing exceptional adaptation mechanisms [1]. Such kind of intrinsic properties are also exhibited by actinobacteria growing in diverse conditions [2]. Actinobacteria luxuriously colonize both terrestrial

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_22, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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and aquatic habitats rendering in creation of unique niche of extremophilic and extreme tolerant organisms including those halophilic, thermophilic, acidophilic, endophytic, symbiotic, endosymbiotic, and gut actinobacteria [3]. Halophiles are salt loving organisms having potentiality in acclimatizing extreme salt saturated environments by balancing the osmotic pressure through synthesis of organic osmolytes such as ectoine, glucosylglycerol, glycine-betaine, and many such [4–7]. As an outcome, halophiles are categorized into three groups based on their physiological growth conditions into extreme halophiles with 2.5–5.2 M NaCl (15–30%), moderate halophiles having 0.5–2.5 M NaCl (3–15%) and slight halophiles with 0.1–0.5 M NaCl (1.0 have positive codon usage bias (abundant codons), while those with RSCU values 1 symbolizes purifying (refining) selection. At neutral evolutionary stage, ¼ 1, that is, the rate of synonymous and nonsynonymous substitutions are equal. The evolutionary rates of the orthologous protein coding genes can be calculated using Codeml program in the PAML software package (ver. 4.5) (http://abacus. gene.ucl.ac.uk/software/paml.html) with runmode ¼ 2 and CodonFreq ¼ 1. A BioPerl script, developed by us, can also be used along with the Codeml package that translates the cDNAs into proteins and aligns them accordingly. The protein alignments are then projected back into cDNA coordinates that should be used by the PAML package to perform the evolutionary rate analysis employing maximum likelihood method (Fig. 5). Pairs of sequences with Ka and Ks values, evocative of saturation, should not be considered for further analysis. Evolutionary selection pressure among the differentially expressed genes can also be estimated to decipher the varying tendencies of evolution

Fig. 5 A representative table for evolutionary analysis based on dN/dS score

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among studied genes. Evolutionary rates of the genes transcribed from the complimentary strands of replication (leading and lagging strands) can also be assessed separately for all the genomes under analysis.

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Conclusion In this chapter, we have discussed some of the popular bioinformatics techniques used for downstream analysis of postgenomic era. All these techniques if, used in appropriate way will lead researchers to statistical results with proper visualization of data. Codon usage, amino acid usage, energy cost analysis along with phylogeny and evolutionary analysis will gather knowledge on culturable strains whose whole genome sequence is available. On contrary, 16 s metagenomics will help us in identifying the unculturable microorganisms present in specific niche. Thus, through combination of all these approaches, a holistic idea about actinobacterial lifestyle can be achieved.

References 1. Sen A, Daubin V, Abrouk D, Gifford I, Berry AM, Normand P (2014) Phylogeny of the class Actinobacteria revisited in the light of complete genomes. The orders ’Frankiales’ and Micrococcales should be split into coherent entities: proposal of Frankiales ord. nov., Geodermatophilales ord. nov., Acidothermales ord. nov.andNakamurellales ord. nov. Int J Syst Evol Microbiol 64:3821–3832 2. Ventura M, Canchaya C, Tauch A, Chandra G, Fitzgerald GF, Chater KF, van Sinderen D (2007) Genomics of Actinobacteria: tracing the evolutionary history of an ancient phylum. Microbiol Mol Biol Rev 71:495–548 3. Ballav S, Dastager SG, Kerkar S (2012) Biotechnological significance of Actinobacterial research in India. Recent Res Sci Technol 4 (4):31–39 4. Aderem A (2005) Systems biology: its practice and challenges. Cell 121:511–513 5. Bork P, Serrano L (2005) Towards cellular systems in 4D. Cell 121:507–509. https://doi. org/10.1016/j.cell.2005.05.001 6. Ikemura T (1985) Codon usage and tRNA content in unicellular and multicellular organisms. Mol Biol Evol 2:13–34 7. Sharp PM, Li WH (1986) Codon usage in regulatory genes in Escherichia coli does not reflect selection for ’rare’ codons. Nucleic Acids Res 14(19):7737–7749

8. Wright F (1990) The ’effective number of codons’ used in a gene. Gene 87(1990):23–29 9. Peden JF (1999) Codon W. PhD Dissertation, University of Nottingham, Nottinghamshire, UK 10. Lithwick G, Margalit H (2005) Relative predicted protein levels of functionally associated proteins are conserved across organisms. Nucleic Acids Res 33:1051–1057. https:// doi.org/10.1093/nar/gki261 11. Futcher B, Latter GI, Monardo P, McLaughlin CS, Garrels JI (1999) A sampling of the yeast proteome. Mol Cell Biol 19(11):7357–7368. https://doi.org/10.1128/mcb.19.11.7357 12. Grosjean H, Fiers W (1982) Preferential codon usage in prokaryotic genes: the optimal codonanticodon interaction energy and the selective codon usage in efficiently expressed genes. Gene 18(3):199–209 13. Ruiz LM, Armengol G, Habeych E, Orduz S (2006) A theoretical analysis of codon adaptation index of the Boophilusmicroplus bm86 gene directed to the optimization of a DNA vaccine. J Theor Biol 239:445–449 14. Bodilis J, Barray S (2006) Molecular evolution of the major outer-membrane protein gene (oprF) of pseudomonas. Microbiology 152:1075–1088

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15. Rice P, Longden I, Bleasby A (2000) EMBOSS: the European molecular biology open software suite. Trends Genet 16:276–277 16. Wu G, Culley DE, Zhang W (2005) Predicted highly expressed genes in the genomes of Streptomyces coelicolor and Streptomyces avermitilis and the implications for their metabolism. Microbiology 151:2175–2187

17. Xia X, Xie Z (2001) DAMBE: software package for data analysis in molecular biology and evolution. J Hered 92:371–373 18. Sarkar I, Gtari M, Tisa LS, Sen A (2019) A novel phylogenetic tree based on the presence of protein domains in selected actinobacteria. Antonie Van Leeuwenhoek 112(1):101–107

Chapter 29 Nanopore-Based Long-Read Sequencing Technology to Obtain Highly Contiguous Whole-Genome Sequence of Actinobacterial Genomes like Streptomyces Sp.: A Complete Guide for Actinobacterial Whole Genome Sequencing Project Using Nanopore Sankaranarayanan Gomathinayagam, Loganathan Karthik, and Kodiveri Muthukaliannan Gothandam Abstract The “postgenomic era” will be dominated by long-read technologies like Oxford Nanopore technology and Pacific Biosystem’s single-molecule real-time sequencing technology. The nanopore technology can produce reads up to 2.3 Mbp length. So technically it can sequence approximately one-third of a Streptomyces genome in a single read unlike other sequencing technologies currently available. But sequencing of actinobacteria comes with some challenges which can be rectified. The current walk-through will be useful for first time actinobacterial biologist right from DNA isolation to computational processing of bacterial genomic data, along with troubleshooting the difficulties in sequencing actinobacteria. Also this chapter will bridge the gap between wet-lab biologist and a computational biologist. Key words Actinomycetes, Whole-genome sequencing, Streptomyces, Bioinformatics assembly, Draft, Complete, Annotation, Nanopore sequencing, FAST5

1

Introduction Genome mining of actinobacteria has revealed that it is a rich source of natural products which play a major role in drug industries [1–3]. Hence, novel genome sequencing technology and assembly techniques needed to maximize the natural products from actinobacteria. To date, nanopore sequence technology has grown rapidly and has been applied in diverse fields.Long read sequencing technologies like Pacific Biosystem’s Single-Molecule Real-Time (SMRT) sequencing technology and Oxford Nanopore Technology (ONT) constitute the revolutionary Third Generation Sequencing (TGS) technologies. If the next generation sequencing

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_29, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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(NGS) technologies revolutionised the “genomic era” with relatively cheap high throughput genomic data, the long-read technologies contribute to the “postgenomic era” significantly in a different way, that is, if genomic sequence were a puzzle, the long-read technologies solve that puzzle with large pieces. In other words, to get human genome data, the human genome must be sequenced 100 fold (~3 Gbp
100 ¼ 300 Gbp) by the shot-gun sequencing method. This is called as 100X coverage. This coverage should comfortably cover the entire human genome to get meaningful insight from it. While in the nanopore sequencing, 30-fold coverage is enough to get the same “meaning” about the human genome. This is possible because of the long-reads it can generate. But there is still a plenty of room for improvements in the nanopore sequencing technology. The nanopore reads often get the adjective as error prone reads. The initial flow cell chemistries in nanopore technology were able to reach only a phred score of Q10-Q16 [4, 5], shot gun sequence reads have a phred score of above Q30. The phred score of Q10 indicates that only 90% of reads are accurate while Q30 means 99.9% of reads are accurate. This seriously affects the “meaning” that come from the genome sequence. If the read length of 2 Mbp has a phred score of Q10, then almost 200 Kbp of reads are incorrect, which when comes from gene of interest it dents the purpose of sequencing. But the constant efforts from Nanopore tech. has improved the read accuracy to Q20 (i.e., 99%). The downstream computational analysis can mask these errors in the sequence reads. This protocol will be helpful for microbiologists who are novices in genome sequencing and data processing in providing a complete guidance from wet lab to computational processing.

2

Materials

2.1

DNA Isolation

Culture: Axenic culture of Streptomyces (15 ml) grown for 48 h at  30 C. Lysozyme (20 mg/ml), Tris-EDTA buffer, liquid nitrogen, 10% sodium dodecyl sulfate, Proteinase K, RNase, phenol, chloroform, molecular biology grade ethanol, ultrapure water.

2.2

Purification

Agencourt AMPure XP magnetic beads and magnetic rack, Beckman Coulter. molecular biology grade water, NanoDrop, Thermo Fisher Scientific.

2.3

Sequencing

Oxford Minion sequencer and flowcell, Oxford Nanopore ligation sequencing kit, Oxford Nanopore flow cell priming kit, NEBnext Oxford Nanopore Ligation sequencing Companion module, MinKNOW software module.

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2.4 Hardware and Software for Data Analysis

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A standard desktop with minimum four-core CPU, minimum 16 GB RAM, 500 GB hard disk/SSD, with latest version of Ubuntu installed/any Unix based environment. Guppy basecaller, (Oxford Nanopore Tech.), FastQC, Filtlong command line tool, Flye assembly tool, Circlator command line tool, Prokka annotation tool/RAST web server, Rebaler assembly tool for polishing, gVolante web server, Quast tool. (Optional: Nanopolish/Racon), AntiSmash web server.

Methods DNA Isolation

1. Culture: Inoculate an axenic culture of Streptomyces in an adequately aerated culture vessel in a standard medium like ISP2 [1] (or a chemically defined medium). 2. Growth conditions: Grow the culture for 48 h at 30  C with adequate shaking, usually at 200 RPM. 3. Culture sanctity: Check the culture for filamentous growth under a microscope. Make sure that it does not have any other bacterial contamination. Because during sequencing this might impact the output. 4. Centrifuge 15 ml of the culture and aspirate the supernatant. Transfer the pellet into a clean porcelain dish and add liquid nitrogen to it [2]. Crush the pellet gently with a sterile pestle. 5. Transfer the content completely into a tube containing 0.5 ml of TE buffer with 10 mg of lysozyme. Incubate the tube at 37  C for 45 min and check for cell breakage with the help of a microscope. 6. Now, to the same tube, add 25μl of 10% SDS and 20μl of Proteinase K and incubate at 45  C for 30 min. 7. Once the incubation is complete, bring the tube to room temperature. Add equal volume of phenol: chloroform (1:1) mixture and mix gently. For phase separation, centrifuge the tube at 5000
g for 5 min. 8. Transfer the aqueous phase carefully into a fresh tube. Use tip-cut pipette tips to avoid fragmentation. Precipitate the DNA with 90% ice-cold ethanol and incubate in a sub-zero temperature for 30 min. 9. Pellet the DNA by centrifuging at 5000
g for 10 min. Wash the pellet twice with 90% ethanol and pellet again. Resuspend the DNA in 100μl of nuclease free water (see Note 1).

3.2 Quality Check of DNA

1. Take 2μl of DNA and check 260/280 and 260/230 ratio along with quantity of DNA using NanoDrop. For the current method expect around 60–80μg of high molecular weight DNA (see Note 2).

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2. Check the size of the DNA fragments by agarose gel electrophoresis. The majority of the fragments could be more than 30 Kbp of size. The fragments may further breakdown during library preparation. Optionally it can be analysed with Bioanalyzer, Agilent Technologies. 3. After fragment check, purify the DNA with Agencourt AMPure XP beads. The beads to DNA ratio should be minimum 0.45
to 1. This purification step apart from selecting larger fragments can also remove inhibitors like pigments from actinobacteria which can block the nanopores during sequencing. 3.3 Library Preparation

The Oxford Nanopore Technology’s protocol page provides all straightforward protocols for all major sequencing project using nanopore. This chapter provides slight modifications at particular steps which can improve the results of the sequencing project (see Notes 3 and 4). 1. Check the hardware of Minion using the configuration flow cell by connecting to the MinKNOW software module. Ensure that the number of pores available is more than 800 for new flow cells. Download the protocol by navigating to protocol page from https://community.nanoporetech.com/protocols. 2. Select appropriate protocol for your project. If only one actinobacterial genome sequence is required, select SQK-LSK109/110 alone. The nanopore technology allows multiplexing of samples of up to 24, in that case select EXP-NBD104/114 too. Also download the protocol for flow cell priming and washing. 3. Get the flowcell ready by bringing it to the room temperature. Take 1–1.5μg of AMPureXP bead purified DNA in 48μl of nuclease free water in 0.2 ml PCR tube. Mix end-repair enzymes and buffers to the DNA by strictly following the steps provided under DNA end-repair section in Oxford Nanopore protocol. 

4. Incubate the PCR tube in a thermal cycler at 20 C for 5 min and stop the end-repair reaction by incubating at 65  C for 5 min. 5. Now purify the DNA with AMPure XP beads. Wash the beads with only freshly prepared 70% ethanol and elute it in 62μl of nuclease-free water by incubating it at room temperature for 5 min (see Note 5). 6. Check the recovery of DNA using NanoDrop quantification by using 2μl of sample from above elute.

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7. Now thaw the adapter mix, ligation buffer, Long fragment buffer/Short fragment buffer, and elution buffer. Place the adapter mix and T4 ligase in ice. 8. To the 60μl of DNA elute from the previous step, add 25μl of Ligation buffer, 10μl of NEBnext quick T4 DNA ligase, and 5μl of adapter mix. Mix gently by inverting the tube several times. Incubate the mixture at room temperature for 10 min. 9. After incubation separate the DNA from the enzyme mix by adding 45μl of AMPure XP beads. Mix gently by flicking the tube. Rest the tube in a magnetic rack. After the beads settle toward the magnet, remove the enzyme mix carefully with pipette. 10. Use 250μl of Long fragment buffer to wash the magnetic pellet instead of ethanol. Mix very carefully by gently flicking the tube. Spin down and discard the supernatant. Elute the DNA from magnetic bead using 16μl of elution buffer. 11. Quantify the amount of DNA using NanoDrop. Expect recovery up to ~400–450 ng at this step from the initial 1.5μg of DNA taken. 12. Attach the flow cell to the Minion device. Perform initial QC checks with the storage buffer. After this, gently slide the priming port and perform flow cell priming with the fuel mix following the protocol provided separately in the protocols page. 13. Take 12μl of the eluted DNAs from the step 10 and to it add 37.5μl of sequencing buffer and 25.5μl of loading beads. Together about 75μl of the library will be available. 14. At step 10, if long fragment buffer was used to recover long fragments, use 75μl of above mixture completely. This should occupy more than 80% pores of the flowcell. 15. Instead, if you wanted both long and short fragments and thus have used short fragment buffer, only 40μl of the above library is enough to achieve approximately the same percentage of pores. 16. With the priming port open, add the necessary volume (according the previous points) into the SpotOn port in a dropwise fashion. 17. Now start the sequencing experiment by providing the path in the MinKNOW software to store FAST5 files. You can optionally enable live base calling, but this is not recommended. 18. Depending on the pore occupancy, the required coverage will be proportionately achieved over some time. Stop the sequencing in the MinKNOW desktop application when the required amount (coverage) of base pairs have been read. Do not detach

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the Minion device until base calling completes, if the live base calling is enabled. 3.4 Computational Analysis of the Raw Sequence Data

Now that the FAST5 files are stored in the set path in the system, we can start base calling using the Guppy command line tool to convert FAST5 files to FASTQ file. The following steps are to get a draft/complete assembly of actinobacterial genome along with annotation done in a UNIX like environment (Ubuntu) as indicates in Note 6. 1. Open the Terminal, which is a command line interface by pressing CTRL+ALT+T together. And type sudo apt update && sudo apt upgrade --assume-yes as shown in Fig. 1. This should take a while depending on the network and computer speed. 2. Now navigate to the folder were FAST5 files are stored in the Terminal. Now install Guppy command line tool following the instructions in the software page in nanoporetech.com. Basecall the FAST5 reads and save them as FASTQ files in a separate folder. This should take a considerable amount of time depending on the computer speed and the file size. 3. Now type cd ~ in the terminal to move to the home directory as shown in Fig. 2. Now type cd followed by the path to the FASTQ files as shown in Fig. 3. 4. Type ls and it should display all the available FASTQ files. All the FASTQ files can be merged into a single file using the following command cat *.fastq > merged.fastq and press enter. 5. Now the raw FASTQ files contains reads of all qualities. To check the quality of reads, use FastQC tool which has GUI.

Fig. 1 Screen grab of installing essential updates in Ubuntu operating system. This may take a while depending the computer and Internet speed

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Fig. 2 Screen grab of the terminal with command to move to home directory. Please use lower case letters and leave a space between cd and tilde

Fig. 3 Screen grab of the terminal with command to move to a specific directory. Please use lower case letters and leave a space between cd and directory name

Fig. 4 Screen grab of the terminal to illustrate the installation of Filtlong tool via command line

Fig. 5 Screen grab of terminal with command to filter reads using filtlong tool

After checking the quality, use filtlong CLI tool to filter out low quality reads. Install the filtlong tool by entering the following commands in a sequential order line by line as shown in Fig. 4. git clone https://github.com/rrwick/Filtlong.git cd Filtlong make -j bin/filtlong –h

After the last command, the common usage instructions for filtlong will be displayed on the screen. Now type cp bin/filtlong usr/local/bin. 6. Type clear in the terminal interface. To filter out the 10% of lower quality reads, enter the following command after moving to the folder where merged.fastq is present. Follow Fig. 5 for reference.

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Sankaranarayanan Gomathinayagam et al. filtlong --min_length 1000 --keep_percent 90 merged.fastq > filtlongoutput.fastq

7. After this step, the Flye assembler can be installed [6]. Flye requires an important dependency named minimap2 [7]. It can be installed by entering the following command sudo apt install minimap To install flye assembler, type the following commands one by one or copy paste it into the terminal and press enter. While installing system wide using sudo python setup.py install, minimap2 automatically gets installed. Please refer to Figs. 6 and 7 for complete pictographical setup guidance for Flye. git clone https://github.com/fenderglass/Flye cd Flye sudo python setup.py install

8. The previous python setup.py install would install Flye system wide. However the following steps would make the bin folder inside Flye folder as working directory for the assembly process. 9. Minimize the terminal and go to Files by clicking the icon in the task bar. Move to the folder where filtlongoutput.fastq is available. Copy the file and paste it into the bin folder inside Flye folder. 10. Now go to the terminal window, make sure that the working directory is /home/XXX/Flye/bin Please see Fig. 8 for

Fig. 6 Screen grab of terminal while installing Flye assembler tool

Fig. 7 Screen grab of Flye assembler tool in command line interface

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Fig. 8 Screen grab of terminal showing files inside binary folder of Flye tool. Copy the filtered files into the binary folder to avoid “input file missing” error

reference. In the terminal window now type cd bin and press enter. Type ls and in that list of files ensure filtlongoutput. fastq is available. 11. Now the filtered FASTQ reads can be assembled into a single FASTA file. After the assembly step, the size of the file typically matches with the genome size of the organism we sequenced. Type or copy-paste the following command in a single line to begin assembly process. flye --nano-raw merged.fastq --out-dir /home/XXX/assembly/ -threads 8

The integer 8 after --threads can be given if the computer has 4 core CPU. 12. After the assembly is complete, navigate to the assembly folder by clicking the Files icon. Ensure assembly.fasta is available in the folder. 13. The assembled genome can now be taken for further downstream process like polishing/circularisation and annotation. 14. After the assembly step, the assembly.fasta can be circularised using the tool circlator [9]. Now type cd ~ to go back to the home directory and install circlator using following command sudo apt install circlator by pressing enter. Circlator requires number of essential dependencies like Bowtie, samtools, prodigal, and MUMmer. Install these by entering the following command sudo apt install bwa samtools prodigal as shown in Fig. 9. 15. To install MUMmer, go to the site https://sourceforge.net/ projects/mummer/files/mummer/3.23/ and download the source code. Apart the above mentioned dependencies, it also requires a tool called canu [10]. Install canu by downloading the latest source code release from github (https://github. com/marbl/canu/releases) and type the following commands in sequential order one by one. tar -xjf canu-2.1.1.tar.xz cd canu-2.1.1/src make -j 8

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Fig. 9 Screen grab of terminal with commands to install dependencies for circulator tool

Fig. 10 Screen grab of terminal with commands to circularise the assembled genome using circulator tool. Since the command involves multiple arguments, refer this figure for clarity

Fig. 11 Screen grab of terminal while cloning Racon scripts from github to the local computer

Fig. 12 Screen grab of terminal while installing the Racon tool from the cloned scripts cd .. cp canu-2.1.1/build/bin/canu/usr/local/bin

16. Copy the polished assembly.fasta file in the home folder using GUI and type the following command followed by enter. A sample screen grab of the same has been given as Fig. 10. circlator all --data_type nanopore-raw --bwa_opts "-x ont2d" --merge_min_id 85 --merge_breaklen 1000 assembly.fasta /home/ XXX/Flye/bin/filtlongoutput.fastq circularised

17. After the previous step look for the file circularised.fixstart. fasta in the home directory. 18. Racon is a tool to polish the produced assembly file with raw reads. This is a consensus based base pair correction which improves the quality of the assembled genome. To install racon, type the following commands one by one. See Figs. 11 and 12 for ref. [8].

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git clone --recursive https://github.com/lbcb-sci/racon.git racon cd racon mkdir build cd build cmake -DCMAKE_BUILD_TYPE=Release .. sudo make install

19. After the installation is complete, install rebaler tool from the github repository by entering the given commands. git clone https://github.com/rrwick/Rebaler.git cd Rebaler python3 setup.py install rebaler –h

20. Rebaler is actually a reference based assembler, it can be used to polish the sequence by taking the circularised.fixstart.fasta from the previous step as a reference with filtlongoutput.fastq as reads. To do that type the following command in the terminal window (see Notes 7–9). rebaler circularised.fixstart.fasta /home/XXX/Flye/bin/filtlongoutput.fastq > finalassembly.fasta

21. Now the final genome assembly can be annotated locally using Prokka or can be uploaded to RAST web server available at rast.theseed.org [11]. 22. 18. During annotation, completeness check can be done at gVolante web server (https://gvolante.riken.jp/) hosting BUSCOv1 for prokaryotes in parallel to annotation step. The completeness assessment would typically look like the one shown in Fig. 13. After affirming the completeness of the genome assembly, report the stats of the assembly and annotation in a table format as shown in Fig. 14.

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Notes 1. For DNA isolation Oxford Nanopore Technologies recommends the use of Qiagen’s Plant genomic DNA extraction kit. While the given protocol would work equally well. The amount of DNA will be more than sufficient for a sequencing project. 2. The quality ratio like 260/280 and 260/230 (1.8 and 2–2.2) is very critical in nanopore sequencing, so it is recommended to use AMPure XP magnetic beads to do an initial clean up before

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Fig. 13 Screen grab of web page of the gVolante web based server for completeness assessment

library preparation. The ratio of AMPure beads to DNA will impact the size of fragments. If short fragments are also necessary, take 1:1 volume of AMPure beads and DNA. 3. The initial input DNA for library preparation can be less than 1μg if the DNA is very much fragmented. But less fragmented DNA gives relatively good contiguous assembly even with low coverage. 4. Always multiplex bacterial/actinobacterial genome while preparing library. This will be economic and also saves lot of time. 5. Always prepare the 70% ethanol fresh. Also preferably use commercial nuclease free water instead of TE buffer during elution steps. 6. This chapter provides basic Linux commands also so that readers can follow this protocol straightaway with basic computer knowledge for computational analysis. There are certain don’ts while working in Linux based systems. UNIX commands are case-sensitive and character sensitive, so type writing errors can cause execution errors.

Nanopore-Based Long-Read Sequencing Technology to Obtain Highly Contiguous. . .

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Fig. 14 Sample table to provide data in MIXs format

7. The Flye and Circlator tools require some dependencies like minimap2, samtools, bwa, MUMmer, and canu which should be installed prior to starting the respective tools.

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8. Always avoid making file names with spaces or uppercase letters in a Linux based environment. Instead of spaces use underscore (“_”) or simply dots like it is given in the protocol (e.g., circularised.fixstart.fasta). 9. If any of these tools fail, look for error messages in the CLI and all of these errors are mostly user rectifiable. References 1. Karthik L, GauravKumar T, Bhattacharyya A, Sarat Chandar S, Bhaskara Rao KV (2014) Protease inhibitors from marine actinobacteria as a potential source for antimalarial compound. PLoS One 9(3):e90972. https://doi. org/10.1371/journal.pone.0090972 2. Karthik L, Kumar G, Bhaskara Rao KV (2013) Antioxidant activity of newly discovered lineage of marine actinobacteria. Asian Pac J Trop Med 6(4):325–332. https://doi.org/10. 1016/S1995-7645(13)60065-6 3. Pavan Kumar JGS, Gomathi A, Vasconcelos V, Gothandam KM (2018) Bioactivity assessment of Indian origin—mangrove Actinobacteria against Candida albicans. Mar Drugs 16(2): 60. https://doi.org/10.3390/md16020060 4. Pooja KK, Gomathinayagam S, Gothandam KM (2021) Draft genome sequence of a highly pigmented bacterium Paracoccusmarcusii KGP capable of producing galacto-oligosaccharides synthesising enzyme. Curr Microbiol 78(2): 634–641. https://doi.org/10.1007/s00284020-02326-3 5. Gomathinayagam S, KodiveriMuthukaliannan G (2020) Metagenomic analysis of the faecal microbiome of rats with 1, 2-dimethylhydrazine induced colon cancer and prophylactic whole-cell carotenoid intervention. Indian J Microbiol 61:38–44. https://doi.org/10.1007/s12088-02000909-z 6. Kolmogorov M, Bickhart DM, Behsaz B, Gurevich A, Rayko M, Shin SB, Kuhn K, Yuan J, Polevikov E, Smith TPL, Pevzner PA

(2020) metaFlye: scalable long-read metagenome assembly using repeat graphs. Nat Methods 17(11):1103–1110. https://doi.org/10. 1038/s41592-020-00971-x 7. Li H (2018) Minimap2: pairwise alignment for nucleotide sequences. Bioinformatics 34(18): 3094–3100. https://doi.org/10.1093/bioin formatics/bty191 8. Ultrafast consensus module for raw de novo genome assembly of long uncorrected reads. http://genome.cshlp.org/content/early/ 2017/01/18/gr.214270.116 (Last accessed: 25/12/2020) 9. Hunt M, Silva ND, Otto TD, Parkhill J, Keane JA, Harris SR (2015) Circlator: automated circularization of genome assemblies using long sequencing reads. Genome Biol 16:294. https://doi.org/10.1186/s13059-0150849-0 10. Koren S, Walenz BP, Berlin K, Miller JR, Phillippy AM (2017) Canu: scalable and accurate long-read assembly via adaptive k-mer weighting and repeat separation. Genome Res 27(5): 722–736. https://doi.org/10.1101/gr. 215087.116 11. Overbeek R, Olson R, Pusch GD, Olsen GJ, Davis JJ, Disz T, Edwards RA, Gerdes S, Parrello B, Shukla M, Vonstein V, Wattam AR, Xia F, Stevens R (2014) The SEED and the rapid annotation of microbial genomes using subsystems technology (RAST). Nucleic Acids Res 42(Database issue):D206–D214. https://doi.org/10.1093/nar/gkt1226

Chapter 30 Mining Genomes of Actinobacteria Sushant Parab, Davide Cora`, and Federico Bussolino Abstract For the last several decades, Actinobacteria have been considered as the major storehouse for the discovery and production of natural products as well as of many valuable secondary metabolites, thus being recognized as one of the most important industrial bacteria. With the advancements in high-throughput genome sequencing methods, there has been a rapid increase in the discovery of novel compounds produced by actinomycetes. Hence, genome mining with various awakening strategies may further enable the identification of new and weakly produced compounds. In this chapter, we discuss the recent advancements in Actinobacteria genome sequencing and the applications of genome mining approaches to identify and characterize biosynthetic gene clusters (BGCs). Furthermore, we discuss several challenges that need to be overcome to accelerate the genome mining process and support the discovery of novel bioactive compounds. Key words Genome sequencing, Genome mining, Biosynthetic gene clusters

1

Introduction For the past several decades Actinomycetes have been the storehouse for numerous bioactive metabolites [1]. Actinomycetes contribute more than 50% to the commercially available antibiotics and their lead compounds [2]. One of the best characterized genera of actinomycetes, Streptomyces, is considered as one of the most important types of industrial bacteria, due to its higher potential of producing secondary metabolites including antibiotics, anticancer drugs, etc. [3–5]. The rapid progress in genome sequencing methods has revolutionized almost every aspect in biological sciences including natural product discovery [6]. With the abundance of genetic data available these days, and the amplitude in which numerous genomes are getting sequenced, there will be no shortage of secondary metabolite gene cluster anymore. The only challenge now is to effectively mine these datasets and to connect the detected Biosynthetic Gene Clusters (BGC) to the already known compounds

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which will eventually guide us to identify the novel or most promising compounds. The current largest collection of mined gene clusters is the “Integrated Microbial Genomes Atlas of Biosynthetic gene Clusters (IMG-ABC)” [7], a database of collected BGCs combined with the experimentally verified BGCs.

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Genome Mining Many researchers have expressed optimism that mining genomes for secondary metabolites will result in improving the research by cushioning the gap, left by the pipelines at low level [8–10]. For every bioinformatic investigation, the term “genome mining” associated is not just for detecting the biosynthetic pathway of bioactive natural product, but also predicting their possible functional and chemical reactions [6]. Genome mining is completely dependent on computing technology and bioinformatics algorithms/tools. Publicly available databases contain a huge amount of data, consisting genome sequences and annotation. Moreover, the major role of genome mining approach is finding new Biosynthetic Gene Cluster (BGCs). The BGCs in fact encode for two subclasses of enzymes, polyketide synthases (PKS) and nonribosomal peptide synthases (NRPS), which are the two most important routes responsible for the formation of natural products [11]. This approach also provides the possibility to compare the novel/unknown gene clusters to the known gene clusters predicting their function and structure through different databases [12]. Even though Genome mining approaches allow us to predict and identify gene clusters that are responsible for the production of natural products, the incorporation of web tools and databases has improved the performance [6]. Among the many available, the three important web tools are as follows: (a) Antibiotics and Secondary Metabolite Analysis SHell (antiSMASH). The first version was issued in 2011 [13], and it is a web server able to associate the gene clusters identification with a series of specific algorithms for natural compound analysis [14]. This approach performs the prediction of gene cluster with a more detailed analysis and provides with a predicted image of amino acid structure [12]. (b) PRediction Informatics for Secondary Metabolomes (PRISM). It is an open-web tool, consisting of a genomic prediction of secondary metabolomes. Using different algorithms that

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compare the new genetic information with 57 virtual enzymatic reactions, this approach provides the possibility of obtaining a correspondence between known natural drugs and possible new ones [12]. (c) Integrated Microbial Genomes Atlas of Biosynthetic gene Clusters (IMG/ABC). It is a comprehensive data mart of Biosynthetic Gene Cluster (BGCs) for secondary metabolite compounds (SMs).

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Additional Tools for Genome Mining

Tools

BAGEL

antiSMASH

Pubmed link

https://pubmed.ncbi. nlm.nih.gov/ 16845009/

https://pubmed.ncbi.nlm. https:// https://pubmed.ncbi. nih.gov/21672958/ pubmed. nlm.nih.gov/ ncbi.nlm.nih. 28244986/ gov/ 25036635/

Short Identifies bacteriocins, introduction and RiPPs using HMM search against the database [15]

Identifies BGCs using HMMer3 to search experimentally characterized proteins [13]

ClusterFinder

Identifies BGCs using a HMM model-based probabilistic algorithm [16]

RODEO

Identifies BGC and RiPP precursor peptide using HMM and machine learning [17]

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GeneBank, EMBL, FASTA Text file

GeneBank

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14 June 2011; 539

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Genome Mining by antiSMASH Materials

1. A complete genome of Streptomyces griseus, GeneBank ID: AP009493.1 [18], is downloaded from National Center for Biotechnology Information (NCBI). 2. The genome is annotated by NCBI Prokaryotic Genome Annotation Pipeline (PGAP), and the annotation method is best-placed reference protein set and GeneMarkS-2+. 3. The complete genome consists of more than 6000 coding genes and CDSs.

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Fig. 1 Query submission 4.2

Procedure

1. Sometimes the server is busy, and the jobs are queued which takes considerable amount of time to process the query. So, an alternative and useful approach is to provide an email address to receive the results. 2. The GeneBank file of the above genome is uploaded on the antiSMASH server with default parameters (Fig. 1). A gene annotated file (GBK/EMBL) obtained from Rapid Annotations using Subsystems Technology (RAST) [19] is recommended, but in case of no gene annotation a simple FASTA file will work. 3. The “Detection Strictness” parameter by default is relaxed. But one can toggle the bar to obtain more stringent results. 4. The “Extra features” panel allows to include additional databases/repositories against which the search will be carried out for identifying clusters. If not, the following options will be run by default as seen in Fig. 1.

4.3

Results

The analysis identified 38 secondary metabolite regions in our query. An overview of all the predicted secondary metabolites is shown in Fig. 2. 1. Each cluster is color coded by predicted metabolite type. 2. Below the species name is an image showing where the clusters are located in the record. 3. A table with a summary of each region/cluster with the rows representing: (a) Region: the cluster/region number. (b) Type: the product type detected by antiSMASH. (c) From, To: the position/location of the region.

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1 2 4

3

4) Clusters from a specific region are observed by selecting it from the

Fig. 2 Overview of the predicted secondary metabolites

(d) Most similar known cluster: the closest relative found from MiBIG database. (e) Similarity: a BLAST hit with the closest compound from MiBIG database. 4. Clusters from a specific region are observed by selecting it from the “Overview panel.” The region displayed in Fig. 3 contains a NRPS protocluster (green) and T3PKS protocluster (yellow). The overlapping region is assigned to candidate cluster. 5. One of the clusters from region 1.4 is “putative NRPS” as shown in Fig. 4; by selecting a particular gene cluster its details can be viewed in the right panel—“Gene details.” 6. A more in-depth information on the selected gene cluster can be seen in the “Detailed Annotation” panel.

5

Discussion In the last decades, there have been great advances made in the field of molecular biology, genome mining together with synthetic biology, pushing firmly the identification of novel BGCs involved in the biosynthesis of natural products. However, these next-generation tools contribute to the unfolding of new natural products; they do have their own advantages and limitations.

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Fig. 3 Clusters of Region 1.4

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Fig. 4 Gene cluster description of region 1.4

Advantages: l

Detection of large compounds [20].

amounts

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The next-generation tools allow to predict the chemical structure and functions [21, 22].

l

The tools are very easy to use and do not require any bioinformatic expertise. Limitations:

l

Only known biosynthetic gene clusters are identified [22].

l

Difficult to predict biotechnological activities of novel natural product [23].

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The approaches still require improvements [22]. References 1. Choi S-S, Kim H-J, Lee H-S, Kim P, Kim E-S (2015) Genome mining of rare actinomycetes and cryptic pathway awakening. Process Biochem 50(8):1184–1193. https://doi.org/10. 1016/j.procbio.2015.04.008 2. Demain AL (2014) Importance of microbial natural products and the need to revitalize their discovery. J Ind Microbiol Biotechnol 41 (2):185–201. https://doi.org/10.1007/ s10295-013-1325-z 3. Hindra Pak P, Elliot MA (2010) Regulation of a novel gene cluster involved in secondary metabolite production in Streptomyces coelicolor. J Bacteriol 192:4973–4982 4. Hranueli D, Cullum J, Basrak B, Goldstein P, Long PF (2005) Plasticity of the Streptomyces genome-evolution and engineering of new antibiotics. Curr Med Chem 12:1697. https://doi.org/10.2174/ 0929867054367176 5. Myles DC (2003) Novel biologically active natural and unnatural products. Curr Opin Biotechnol 14(6):627–633. https://doi.org/10. 1016/j.copbio.2003.10.013 6. Ziemert N, Alanjary M, Weber T (2016) The evolution of genome mining in microbes - a review. Nat Prod Rep 33(8):988–1005. https://doi.org/10.1039/c6np00025h; Epub 2016 Jun 8 7. Palaniappan K, Chen IA, Chu K, Ratner A, Seshadri R, Kyrpides NC, Ivanova NN, Mouncey NJ (2020) IMG-ABC v.5.0: an update to the IMG/Atlas of Biosynthetic Gene Clusters Knowledgebase. Nucleic Acids Res 48(D1): D422–D430. https://doi.org/10.1093/nar/ gkz932 8. Baltz RH (2008) Renaissance in antibacterial discovery from actinomycetes. Curr Opin Pharmacol 8(5):557–563. https://doi.org/ 10.1016/j.coph.2008.04.008; Epub 2008 Jun 3 9. Fischbach MA, Walsh CT (2009) Antibiotics for emerging pathogens. Science 325 (5944):1089–1093. https://doi.org/10. 1126/science.1176667 10. Challis GL (2008) Mining microbial genomes for new natural products and biosynthetic pathways. Microbiology 154

(Pt 6):1555–1569. https://doi.org/10. 1099/mic.0.2008/018523-0 11. Timmermans ML, Paudel YP, Ross AC (2017) Investigating the biosynthesis of natural products from marine proteobacteria: a survey of molecules and strategies. Mar Drugs 15:235 12. Boddy CN (2014) Bioinformatics tools for genome mining of polyketide and non-ribosomal peptides. J Ind Microbiol Biotechnol 41:443–450 13. Medema MH, Blin K, Cimermancic P, de Jager V, Zakrzewski P, Fischbach MA, Weber T, Takano E, Breitling R (2011) antiSMASH: rapid identification, annotation and analysis of secondary metabolite biosynthesis gene clusters in bacterial and fungal genome sequences. Nucleic Acids Res 39(Web Server issue):W339–W346. https://doi.org/10. 1093/nar/gkr466 14. Blin K, Medema MH, Kazempour D, Fischbach MA, Breitling R, Takano E, Weber T (2013) antiSMASH2.0—a versatile platform for genome mining of secondary metabolite producers. Nucleic Acids Res 41:204–212 15. de Jong A, van Hijum SA, Bijlsma JJ, Kok J, Kuipers OP (2006) BAGEL: a web-based bacteriocin genome mining tool. Nucleic Acids Res 34(Web Server issue):W273–W279. https://doi.org/10.1093/nar/gkl237 16. Cimermancic P, Medema MH, Claesen J, Kurita K, Wieland Brown LC, Mavrommatis K, Pati A, Godfrey PA, Koehrsen M, Clardy J, Birren BW, Takano E, Sali A, Linington RG, Fischbach MA (2014) Insights into secondary metabolism from a global analysis of prokaryotic biosynthetic gene clusters. Cell 158(2):412–421. https:// doi.org/10.1016/j.cell.2014.06.034 17. Tietz JI, Schwalen CJ, Patel PS, Maxson T, Blair PM, Tai HC, Zakai UI, Mitchell DA (2017) A new genome-mining tool redefines the lasso peptide biosynthetic landscape. Nat Chem Biol 13(5):470–478. https://doi.org/ 10.1038/nchembio.2319 18. Funabashi M, Funa N, Horinouchi S (2008) Phenolic lipids synthesized by type III polyketide synthase confer penicillin resistance on Streptomyces griseus. J Biol Chem 283 (20):13983–13991. https://doi.org/10.

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1074/jbc.M710461200; Erratum in: J Biol Chem. 2008 Sep 5;283(36):25104 19. Aziz RK, Bartels D, Best AA et al (2008) The RAST server: rapid annotations using subsystems technology. BMC Genomics 9:75. https://doi.org/10.1186/1471-2164-9-75 20. Wohlleben W, Mast Y, Stegmann E, Ziemert N (2016) Antibiotic drug discovery. Microb Biotechnol 9:541–548 21. Scheffler RJ, Colmer S, Tynan H, Demain AL, Gullo VP (2013) Antimicrobials, drug

discovery, and genome mining. Appl Microbiol Biotechnol 97:969–978 22. Zerikly M, Challis GL (2009) Strategies for the discovery of new natural products by genome mining. Chembiochem 10:625–633 23. Olano C, Me´ndez C, Salas JA (2014) Strategies for the design and discovery of novel antibiotics using genetic engineering and genome mining. In: Villa TG, Veiga-Crespo P (eds) Antimicrobial compounds: current strategies and new alternatives. Springer, Berlin, pp 1–25

Chapter 31 Comparative Genomics of Actinobacteria Sushant Parab, Davide Cora`, and Federico Bussolino Abstract The class Actinobacteria contains many bacteria relevant to human health and industry; it includes both the most deadly pathogen and also organisms that are very important for antibiotic production. Hence, Actinomycetes have historically been a leading source for organic products called as secondary metabolites. These secondary metabolites usually originate from regions located nearby in the genome and are referred to as biosynthetic gene clusters (BGC). But there have been no systematic studies to date, on whether a BGC in one species is also likely to be in a second species. Keeping this in mind, classification and comparison of these BGCs may thus systematically catalog the extent of natural product diversity. A comparative genomic approach might be a step forward. So, in this chapter, we try to summarize the work done in comparative genomics with a focus on BGCs and also try to shed some light in answering why this appears to be a difficult bioinformatic task. Key words Actinomycetes, Natural products, Comparative genomics, Biosynthetic gene cluster, Genome visualizations

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Introduction The class Actinobacteria is Gram-positive with a genomic GC content generally over 55% [1]; it is also the largest within the phylum Actinobacteria that contains many bacteria relevant to human health and industry [2]. Historically, Actinomycetes have found to be a leading source for natural product discovery [3], which are also called as secondary metabolites, having a wide range of industrial uses. The genes that are responsible for the production of these secondary metabolites are always located together in the genome and are referred to as biosynthetic gene clusters. These gene clusters are interesting in discovery and characterization of genes responsible for producing secondary metabolites [4, 5]. However, not all the biosynthetic gene clusters present are found to be producing secondary metabolites, and also there is no clear evidence whether such gene cluster remains to be nonfunctional in

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_31, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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other species as well. Hence, systematically comparing biosynthetic gene clusters across genomes is a key step forward. Comparative genomics is the approach by which we can compare such biological information between species/organisms. It is a powerful tool for studying evolutionary relationships, identifying conserved or unique genomic features among organisms [6].

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Comparative Genomics Methods Comparative genomics approach is mainly focused on creating detailed visualizations for the common features between organisms. This is possible by clustering genes in groups called homologs or orthologs from various annotated genomes [7]. Such a comparison can be done in four different ways: (a) A gene comparison based on orthologs: This can be done by creating a gene matrix for a set of genomes with their gene families. (b) A gene comparison based on functions: A protein function comparison, such as subsystems [8] and COGs [9]. (c) Core/Pan genome analysis: This concept of Pan genome analysis was discovered by Tettelin et al. [10]; it is another way of comparing gene families. It is found to be a very important tool for comparative genomics. (d) Whole genome alignment: The genome alignment can be done in two ways by local or global alignment methods. It helps in predicting evolutionary relationships.

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Genome Visualization The rapid advancements in whole genome sequencing have directly increased a need for comparative genomic analysis [11], which has also increased the demand for visualization methods/approaches for data modeling, analysis, and representation [12]. Genome visualization acts as a virtual paradigm for comparative genomics datasets, to view the correlations and display map that shows relationships between genomic intervals [13].

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Comparative Genome Analysis by BPGA Materials

1. Complete genome sequences of three Streptomyces sp., with a GeneBank ID: AP009493.1, CP002047.1, and FN554889.1 [14–16], are downloaded from National Center for Biotechnology Information (NCBI). 2. All the three genomes are annotated by NCBI Prokaryotic Genome Annotation Pipeline (PGAP), and the method used for annotation of these three genomes is also same—Bestplaced reference protein set, GeneMarkS-2+. 3. The three Streptomyces strains selected have a high GC content, with an average of 8000 coding genes and CDSs.

4.2

Procedure

1. There are three ways to start/begin the BPGA pipeline as shown in Fig. 1a; for performing a whole pan-genome analysis with default settings, option 3 (which includes both steps 1 and 2) is preferred. 2. Query submission/Input Preparation: BPGA requires either of the three types of input files (*.gbk, *.faa, *.pep.fsa) for performing a comparative analysis. By selecting the third option (one click analysis), we uploaded three protein FASTA files of the above genomes (Fig. 1b). 3. Once the query has been successfully submitted, BPGA will process the input files for cluster analysis by USEARCH/ OrthoMCL/CD-HIT algorithms and will generate orthologous clusters. 4. These clusters are further passed on for Pan-genome analysis, Functional analysis like COG/KEGG distribution, Species phylogenetic analysis, etc.

4.3

Results

1. BPGA has several functional modules integrated for Pan Genome analysis, from which the first three modules include classification of orthologous clusters into core, accessory, and unique genes (Fig. 2a), and also the identification and distribution of the gene families (Fig. 2b). 2. The analysis on the three genomes identified 2917 core genes, with the accessory genes ranging between 1000 and 1500 for each genome along with some unique genes (2000–5000). 3. Protein sequences of the representative core, accessory, and unique orthologous clusters are extracted and further used for COG function (Fig. 3a) and KEGG pathway analysis (Fig. 3b).

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(b)

(a) Fig. 1 Input Preparation (a) Main page of BPGA. (b) Uploading an input file

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Fig. 2 Identification and classification of the Orthologous clusters (a) and Gene Families (b)

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Conclusion The aim of the comparative genomics study is to find common features/genes between genomes/organisms to study their evolution. However, this study requires tools for comparing and visualizing genomes, which is also a difficult bioinformatic task. In this chapter, we tried to shed some light on the various aspects of

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Fig. 3 COG functional analysis (a) and KEGG pathway mapping (b)

comparative genomics methods, with which we are able to create a systematic framework for natural product discovery by comparative genomics (Fig. 4).

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Fig. 4 A schematic framework for comparative genomics approaches References 1. Doroghazi JR, Metcalf WW (2013) Comparative genomics of actinomycetes with a focus on natural product biosynthetic genes. BMC Genomics 14:611. https://doi.org/10.1186/ 1471-2164-14-611 2. Ludwig W, Euze´by J, Schumann P, Busse H, Trujillo M, K€ampfer P, Whitman W (2012) Road map of the phylum Actinobacteria. In: Whitman WB, Goodfellow M, K€ampfer P, Busse H-J, Trujillo ME, Ludwig W, Suzuki K-I, Parte A (eds) Bergey’s manual® of systematic bacteriology, vol 5. Springer, New York, NY, pp 1–28 3. Be´rdy J (2012) Thoughts and facts about antibiotics: where we are now and where we are heading. J Antibiot 65:385–395. https://doi. org/10.1038/ja.2012.27 4. Osbourn A (2010) Secondary metabolic gene clusters: evolutionary toolkits for chemical innovation. Trends Genet 26(10):449–457. https://doi.org/10.1016/j.tig.2010.07.001 5. Fischbach MA, Walsh CT, Clardy J (2008) The evolution of gene collectives: how natural selection drives chemical innovation. Proc Natl Acad Sci U S A 105(12):4601–4608. https://doi.org/10.1073/pnas.0709132105 6. Jung J, Kim JI, Yi G (2019) geneCo: a visualized comparative genomic method to analyze multiple genome structures. Bioinformatics 35 (24):5303–5305. https://doi.org/10.1093/ bioinformatics/btz596 7. Setubal JC, Almeida NF, Wattam AR (2018) Comparative Genomics for Prokaryotes. In: Setubal J, Stoye J, Stadler P (eds) Comparative

genomics. Methods in molecular biology, vol 1704. Humana Press, New York, NY. https:// doi.org/10.1007/978-1-4939-7463-4_3 8. Overbeek R, Olson R, Pusch GD, Olsen GJ, Davis JJ, Disz T, Edwards RA, Gerdes S, Parrello B, Shukla M, Vonstein V, Wattam AR, Xia F, Stevens R (2014) The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST). Nucleic Acids Res 42(Database issue): D206–D214. https://doi.org/10.1093/nar/ gkt1226; Epub 2013 Nov 29 9. Galperin MY, Makarova KS, Wolf YI, Koonin EV (2015) Expanded microbial genome coverage and improved protein family annotation in the COG database. Nucleic Acids Res 43(Database issue):D261–D269. https://doi.org/10. 1093/nar/gku1223; Epub 2014 Nov 26 10. Tettelin H, Masignani V, Cieslewicz MJ, Donati C, Medini D, Ward NL, Angiuoli SV, Crabtree J, Jones AL, Durkin AS, Deboy RT, Davidsen TM, Mora M, Scarselli M, Margarit y Ros I, Peterson JD, Hauser CR, Sundaram JP, Nelson WC, Madupu R, Brinkac LM, Dodson RJ, Rosovitz MJ, Sullivan SA, Daugherty SC, Haft DH, Selengut J, Gwinn ML, Zhou L, Zafar N, Khouri H, Radune D, Dimitrov G, Watkins K, O’Connor KJ, Smith S, Utterback TR, White O, Rubens CE, Grandi G, Madoff LC, Kasper DL, Telford JL, Wessels MR, Rappuoli R, Fraser CM (2005) Genome analysis of multiple pathogenic isolates of Streptococcus agalactiae: implications for the microbial "pan-genome". Proc Natl Acad Sci

Comparative Genomics of Actinobacteria U S A 102(39):13950–13955. https://doi. org/10.1073/pnas.0506758102; Epub 2005 Sep 19. Erratum in: Proc Natl Acad Sci U S A. 2005 Nov 8;102(45):16530 11. Dark MJ (2013) Whole-genome sequencing in bacteriology: state of the art. Infect Drug Resist 6:115–123. https://doi.org/10.2147/ IDR.S35710 12. Parveen A, Khurana S, Kumar A (2019) Overview of genomic tools for circular visualization in the next-generation genomic sequencing era. Curr Genomics 20(2):90–99. https:// doi.org/10.2174/ 1389202920666190314092044 13. Stothard P, Grant JR, Van Domselaar G (2019) Visualizing and comparing circular genomes using the CGView family of tools. Brief Bioinform 20(4):1576–1582. https://doi.org/10. 1093/bib/bbx081 14. Funabashi M, Funa N, Horinouchi S (2008) Phenolic lipids synthesized by type III

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polyketide synthase confer penicillin resistance on Streptomyces griseus. J Biol Chem 283 (20):13983–13991. https://doi.org/10. 1074/jbc.M710461200; Epub 2008 Mar 24. Erratum in: J Biol Chem. 2008 Sep 15. Wang XJ, Yan YJ, Zhang B, An J, Wang JJ, Tian J, Jiang L, Chen YH, Huang SX, Yin M, Zhang J, Gao AL, Liu CX, Zhu ZX, Xiang WS (2010) Genome sequence of the milbemycinproducing bacterium Streptomyces bingchenggensis. J Bacteriol 192(17):4526–4527. https://doi.org/10.1128/JB.00596-10; Epub 2010 Jun 25 16. Bignell DR, Seipke RF, Huguet-Tapia JC, Chambers AH, Parry RJ, Loria R (2010) Streptomyces scabies 87-22 contains a coronafacic acid-like biosynthetic cluster that contributes to plant-microbe interactions. Mol PlantMicrobe Interact 23(2):161–175. https://doi. org/10.1094/MPMI-23-2-0161

Chapter 32 Biosynthetic Gene Cluster Analysis in Micromonospora Species Using ANTISMASH: Secondary Metabolite Genome Mining Pipeline Mukesh Kumar Manickasamy, Rajagopal Narayanan, and Dhanasekaran Dharmadurai Abstract Micromonospora is a prolific producer of antibiotics. Producing more than about 700 antibiotic compounds, Micromonospora has received much attention in the recent years as a source of broad-spectrum antibiotics for treatment of various infections. Antibiotics are considered as metabolic intermediates or as end products of different species of microorganisms and other living organisms. They are chemical substances that are produced in small concentrations which are capable of killing or inhibiting competing microorganisms. Actinobacteria are promising sources of secondary metabolites of pharmaceutical importance. So studying these secondary metabolites is very essential and important for gaining a better insight on Micromonospora spp. We present a method used for the identification of secondary metabolite coding biosynthetic gene clusters in the whole genome of Micromonospora spp. using antiSMASH pipeline. Key words Micromonospora, Actinobacteria, Secondary metabolites, Antibiotics, antiSMASH

1

Introduction The genus Micromonospora was described by Ørskov in the year 1923 [1], and at the time of writing, the genus comprised only 84 species with validly published names (www.bacterio.net/micro monospora.html). Micromonosporae are frequent inhabitants of aquatic habitats worldwide where they participate in the decomposition of cellulose, chitin, and lignin [2, 3]. Micromonospora strains have been isolated from water samples from streams, rivers and lakes, from lake mud, river sediments, beach sands, littoral sediments, and deep marine sediments [2, 4–6] Micromonosporae have also been found to be the dominant actinobacteria group in a range of aquatic environments, particularly in the deeper mud layers, as well as in deeper sea sediments [7–9].

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_32, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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The genus Micromonospora was characterized as comprising gram-positive, aerobic actinobacteria which produce a single spore directly on the substrate mycelium [10]. A combination of morphological and the chemotaxonomic characteristics is an effective criterion for discriminating this genus from other genera in the family Micromonosporaceae. They are widely distributed in a variety of habitats, notably soils rich in humus [11]. Some Micromonospora spp. are also used as antifungal agents— Gentamicin is a broad-spectrum aminoglycoside antibiotic produced by Micromonospora purpurea bacteria, effective against gram-negative bacterial infections. Major fractions of the gentamicin complex (C1, C1a, C2, C2a) possess weak antifungal activity and one of the minor components (A, A1-A4, B, B1, X), gentamicin B1, was found to be a strong antifungal agent [12]. Microbial secondary metabolites are the sources of nearly all of antibiotics [13], drug intermediates, novel enzymes, and inhibitors. Actinomycetes are promising sources of secondary metabolites of pharmaceutical importance [14, 15]. 1.1 Selection of Genes from GenBank

GenBank, built by NCBI, is a comprehensive open access database of nucleotide sequences and supporting bibliographical and biological annotation. GenBank is primarily built from the submission of sequence data from authors and individual laboratories dealing in large scale sequencing projects for whole genome shotgun (WGS) sequencing as well as environmental sampling [16]. The Micromonospora sp. genomes used in this study are the ones which are chosen and commonly used as antibiotics. An information table about all the genomes available is created. The collected genomes are of many types like complete genomes, chromosome, plasmid, and whole-genome shotgun sequences.

1.2 Scrutiny of Dataset

Sequences with status complete or chromosome in their genome annotation reports and for which information about their isolation source is available are selected. Metadata about the isolation source, location of isolation, genome size, and incidence of plasmids are collected from the GenBank files of the sequences as well as from review of literature [17]. Nucleotide sequences in FASTA format of the whole genomes are collected from GenBank DNA database for all Micromonospora sp. strains justifiably selected.

1.3 Secondary Metabolite Cluster Identification Using antiSMASH

antiSMASH is a software pipeline developed in 2011 for automatic secondary metabolite gene cluster identification, annotation, and analysis. The advantages of antiSMASH are that it is comprehensive, rapid, and user-friendly. Previous in silico methods like ClustScan [18] and SBSPKS toolbox [19] are limited to Type I PKS and NRPS analysis. antiSMASH is more comprehensive and covers more cluster classes like lantipeptides, bacteriocins, and terpenes. Secondary metabolite gene cluster analysis of the selected genomes

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was carried out using antiSMASH 4.0 [20, 21] using the GenBank accession number as input and default parameters and Cluster Finder option off. In the present protocol, we describe the ANTI SMASH : secondary metabolite genome mining pipeline for secondary metabolite gene cluster identification, annotation, and analysis which is comprehensive, rapid, and user-friendly.

2

Materials 1. antiSMASH bacterial version tool, 2. Micromonospora sp. culture. 3. Whole-genome sequences of Micromonospora spp. 4. National Center for Biotechnology Information (NCBI) database.

3

Methods

3.1 Detection of Secondary Metabolites of Micromonospora Species (antiSMASH)

1. Open NCBI with link—https://www.ncbi.nlm.nih.gov/.

2. Set the filter to nucleotide and search for the Micromonospora sp. needed. 3. Download the whole-genome sequence or note down the gene accession number.

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4. Open the antiSMASH tool of bacterial version with the link— https://antismash.secondarymetabolites.org/#!/start.

5. Upload the downloaded whole genome sequence or enter the gene accession number in the data input box.

6. After uploading or entering the gene accession number in the data input box, click on submit and wait for the tool to run and analyze.

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7. After completion, click on the show results hyperlink and note down the observations. 8. Observe, compare, and analyze the type and numbers and chemical structure of biosynthetic gene cluster are present in the whole-genome sequence of Micromonospora sp. including polyketide synthases (PKSs) and nonribosomal peptide synthetases (NRPSs), terpene, lantipeptide, thiopeptide bacteriocin, oligosaccharide, siderophore, beta-lactone, and butyrolactone.

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Conclusions A total of 27 Micromonospora spp. are selected for the study of secondary metabolites and biosynthetic gene cluster analysis. The species selected are as follows: M. chokoriensis, M. citrea, M. costi, M. coxensis, M. eburnea, M. echinaurantiaca, M. echinofusca, M. endophytica, M. globbae, M. humi, M. kangleipakensis, M. lupini, M. mirobrigensis, M. narathiwatensis, M. palomenae, M. pattaloongenesis, M. peucetia, M. profoundi, M. sagamiensis, M. sediminicola, M. taraxaci, M. terminaliae, M. ureilytica, M. viridifaciens, M. wenchangensis, M. yanguenis, M. zamorensis (Table 1). They are characterized and studied on the basis of 34 different parameters of secondary metabolites. Out of these 27 Micromonospora sp., M. wenchangensis shows the maximum number of gene clusters among all having a total number of 52 gene clusters. And M. costi, M. pattaloongenesis shows the minimum number of gene clusters among all, with a total of 11 gene clusters each (Table 2).

Biosynthetic Gene Cluster Analysis in Micromonospora Species Using. . .

Table 1 Biosynthetic gene cluster analysis of Micromonospora sp.—heat map

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Table 2 Total biosynthetic gene clusters in Micromonospora sp. as deduced by antiSMASH analysis

Number of gene clusters in Micromonospora sp. M.zamorensis M.yanguenis M.wenchangensis M.viridifaciens M.ureilytica M.terminaliae M.taraxaci M.sediminicola M.sagamiensis M.profoundi M.peucetia M.pattaloongenesis M.palomenae M.narathiwatensis M.mirobrigensis M.lupini M.kangleipakensis M.humi M.globbae M.endophytica M.echinofusca M.echinaurantiaca M.eburnea M.coxensis M.costi M.citrea M.chokoriensis 0

10

20

30

40

50

Terpene

Lanthipeptide

NRPS

Thiopeptide

LAP

TfuA-related

T2PKS

T1PKS

NAGGN

T3PKS

NRPS-like

Bacteriocin

Oligosaccharide

PKS-like

Siderophore

Thioamide-NRP

Betalactone

Amglyccycl

Indole

hgIE-KS

Butyrolactone

Arylpolyene

Lassopeptide

Head_To_Tail

Phophonate

Phosphoglycolipid

Blactam

Resorcinol

Linaridin

Phenazine

Fused

transAT-PKS

Ladderane

Ectoine

60

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References 1. Kawamoto I (1989) Genus Micromonospora. Bergey’s Man Syst Bacteriol 4:2442–2450 2. Cross T (1989) Growth and examination of actinomycetes-some guidelines. Bergey’s Man syst Bacteriol 4:2340–2343 3. Gullo VP, McAlpine J, Lam KS, Baker D, Petersen F (2006) Drug discovery from natural products. J Ind Microbiol Biotechnol 33 (7):523–531 4. Goodfellow M, Williams ST (1983) Ecology of actinomycetes. Annu Rev Microbiol 37 (1):189–216 5. Williams ST, Goodfellow M, Alderson G, Wellington EMH, Sneath PHA, Sackin MJ (1983) Numerical classification of Streptomyces and related genera. J Gen Microbiol 129:1743–1813 6. Williams ST, Goodfellow M, Alderson G, Wellington EMH, Sneath PHA, Sackin MJ (1983) Numerical classification of Streptomyces and related genera. Microbiology 129 (6):1743–1813 7. Jensen PR, Gontang E, Mafnas C, Mincer TJ, Fenical W (2005) Culturable marine actinomycete diversity from tropical Pacific Ocean sediments. Environ Microbiol 7(7):1039–1048 8. Rusnak K, Troyanovich J, Mierzwa R, Chu M, Patel M, Weinstein M (2001) An antibiotic with activity against gram-positive bacteria from the gentamicin-producing strain of Micromonospora purpurea. Appl Microbiol Biotechnol 56:502–503 9. Mincer TJ, Jensen PR, Kauffman CA, Fenical W (2002) Widespread and persistent populations of a major new marine actinomycete taxon in ocean sediments. Appl Environ Microbiol 68(10):5005–5011 10. Veyisoglu A, Carro L, Cetin D, Igual JM, Klenk HP, Sahin N (2020) Micromonospora orduensis sp. nov., isolated from deep marine sediment. Antonie Van Leeuwenhoek 113 (3):397–405 11. Thawai C, Tanasupawat S, Kudo T (2019) Micromonospora caldifontis sp. nov., isolated from hot spring soil. Int J Syst Evol Microbiol 69(5):1336–1342 12. Qiu D, Ruan J, Huang Y (2008) Selective isolation and rapid identification of members of the genus Micromonospora. Appl Environ Microbiol 74(17):5593–5597

13. Kumar C, Himabindu M, Jetty A (2008) Microbial biosynthesis and applications of gentamicin: a critical appraisal. Crit Rev Biotechnol 28(3):173–212 14. Zhao XQ, Jiao WC, Jiang B, Yuan WJ, Yang TH, Hao S (2009) Screening and identification of actinobacteria from marine sediments: investigation of potential producers for antimicrobial agents and type I polyketides. World J Microbiol Biotechnol 25(5):859–866 15. Praveen Kumar P, Preetam Raj JP, Nimal Christhudas IVS, Sagaya Jansi R, Murugan N, Agastian P, Arunachalam C, Ali Alharbi S (2015) Screening of actinomycetes for enzyme and antimicrobial activities from the soil sediments of Northern Tamil Nadu, South India. J Biol Active Products Nat 5(1):58–70 16. Talukdar M, Bora TC, Jha DK (2016) Micromonospora: a potential source of antibiotic. In: Bioprospecting of indigenous bioresources of North-East India. Springer, Singapore, pp 195–213 17. Benson DA, Karsch-Mizrachi I, Lipman DJ, Ostell J, Wheeler DL (2005) GenBank. Nucleic Acids Res 33(suppl_1):D34–D38 18. Belbahri L, Chenari Bouket A, Rekik I, Alenezi FN, Vallat A, Luptakova L, Petrovova E, Oszako T, Cherrad S, Vacher S, Rateb ME (2017) Comparative genomics of Bacillus amyloliquefaciens strains reveals a core genome with traits for habitat adaptation and a secondary metabolites rich accessory genome. Front Microbiol 8:1438–1453 19. Starcevic A, Zucko J, Simunkovic J, Long PF, Cullum J, Hranueli D (2008) ClustScan: an integrated program package for the semiautomatic annotation of modular biosynthetic gene clusters and in silico prediction of novel chemical structures. Nucleic Acids Res 36 (21):6882–6892 20. Anand S, Prasad MVR, Yadav G, Kumar N, Shehara J, Ansari MZ, Mohanty D (2010) SBSPKS: structure based sequence analysis of polyketide synthases. Nucleic Acids Res 38 (2):487–496 21. Weber T, Nave M, Takano E, Chevrette MG, Medema MH, Schwalen CJ (2017) AntiSMASH 4.0-improvements in chemistry prediction and gene cluster boundary identification. Nucleic Acids Res 45:36–41

Chapter 33 Biosynthetic Gene Cluster Analysis in Actinobacterial Genus Streptomyces Marke´ta Macho, Daniela Ewe, Vishal Ahuja, Jihen Thabet, Avik Banerjee, Kumar Saurav, and Subhasish Saha Abstract Secondary metabolites offer a wide variety of biologically active compounds with great potential in medicine, agriculture, or livestock. With the advance of computational techniques and genome sequencing availability, laborious screening of microbial products can be replaced by more efficient genome mining using extensive genome databases available online. Rapidly developing bioinformatic tools, such as antiSMASH, enable researches to effectively explore the genome of many organisms including plants, fungi, and bacteria and identify biosynthetic gene clusters potentially encoding novel bioactive compounds. In this chapter, we provide a step-by-step guide of using the antiSMASH online tool to identify gene clusters potentially encoding for secondary metabolites in the genome of the model strain Streptomyces griseus NBRC 13350. Key words Genome mining, antiSMASH, Biosynthetic gene clusters, Secondary metabolites, Streptomyces

1

Introduction Microbial secondary metabolites with an immense value for healthcare belong to a wide variety of chemical classes and offer great potential for the development of new medicines including an extensive list of antibiotics, anticancer drugs, and immunosuppressive agents. So far, thousands of compounds with massive variety in structure and bioactivities have been isolated from microbes [1– 3]. However, frequent uses of antibiotics against bacterial pathogens are rapidly diminishing their effect as well as turning normal pathogens into multidrug-resistant bacterial strains [4, 5]. The need for finding novel bioactive compounds is therefore always in high demand. The bacterial genus Streptomyces has been recognized as one of the most prolific producers of natural products among

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_33, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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microorganisms ever since streptomycin was discovered from Streptomyces griseus in the middle of the last century. Since then, this microbe was largely exploited for the production of secondary metabolites [6–8]. In the last two decades, along with the significant development of genomic era including whole-genome sequencing and bioinformatics analysis, it has become apparent that these microorganisms still represent a major source for the discovery of novel secondary metabolites, which is further proven with the complete genome sequencing of Streptomyces coelicolor A3 (2) and Streptomyces avermitilis in 2003 [9]. These studies revealed that classical screening methods have limited reach to explore all possible natural products from these organisms and many remain undetected. On the other hand, the rapid decrease in the cost of genome sequencing over the years also encouraged and attracted the scientific community toward the genomic sequence-guided discovery of new compounds and investigation of their gene clusters’ involvement in the biosynthetic machinery [10]. However, laboratory research, which requires experimental characterization of each gene cluster, is still very laborious and sometimes insufficient to keep pace with the speed of genomic discovery. Therefore, exploring promising secondary metabolites targets without time consuming processes is essential for a successful genome mining and can be achieved by in silico identification. As a result, many bioinformatics tools, including BAGEL, ClustScan, CLUSEAN, NP.searcher, PRISM, and antiSMASH, were developed to annotate and mine these genomes [2, 11]. Functioning of these bioinformatic tools relies on identification of highly conserved sequences within the genome and mapping their location for the detection of secondary metabolite–producing biosynthetic gene clusters (BGCs) [12]. So far, genome of numerous Streptomyces species has been sequenced and according to the RefSeq database, a total of 2102 Streptomyces genomes had been deposited as of the 7 January 2021. Further, the genome mining approaches have revealed that in general, Streptomyces species possess about 30 BGCs for secondary metabolites, including many clusters with undetected compounds. However, most of these bioinformatic tools are only capable to discover specific classes of secondary metabolites, including PKS and NRPS. PRISM and antiSMASH, however, are predicting various types of BGCs by following sequence alignment-based profile in a Hidden Markov Model (HMM) of genes that are specific for certain types of secondary metabolites-producing BGCs [2, 12]. For example, antiSMASH uses highly conserved core biosynthetic enzymes to identify BGCs and further evaluates the results using a set of manually curated BGC cluster rules, finally followed by discarding false positives using negative models (e.g., fatty acid synthases are homologous to PKSs). antiSMASH (antibiotics and secondary metabolites analysis shell) as a bioinformatic tool is a user-friendly web with many

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applications and immensely popular in current genome mining research due to its rapid gene annotation process which only requires bacterial genomes in FASTA format [13, 14]. In the present protocol, we describe the workflow from submitting a genome sequence using a model strain Streptomyces griseus NBRC 13350 (NCBI RefSeq: NC_010572.1; hereafter S. griseus NBRC 13350) in antiSMASH and how to analyze the obtained data step by step.

2

Materials 1. Whole genome sequence of Streptomyces griseus 2. antiSMASH 3. antiSMASH data analysis

3

Methods

3.1 File and Options Input

3.2

Start an Analysis

antiSMASH home page: https://antismash.secondarymetabolites. org for bacterial sequences, https://fungismash. secondarymetabolites.org for fungal, or http://plantismash. secondarymetabolites.org for plant sequences. User-friendly antiSMASH can accept different formats of data including Genbank (recommended), EMBL, or plain FASTA format. Upload FASTA file without any annotation or annotated coding sequences for antiSMASH analysis, used Prodigal for the identification of putative genes (for bacterial sequences) [15] or GlimmerHMM (for fungal sequences) [16] or, if the NCBI accession number is known, antiSMASH can also automatically retrieve the data from NCBI (Fig. 1a). If draft genome sequence is subjected for analysis, it is preferable to use scaffolded sequences containing “N” characters for the gaps, as gene clusters can only be identified if positional information is available. The quality of antiSMASH prediction is highly dependent on the quality of the input data. antiSMASH may not be able to detect gene clusters for poor quality draft genomes with many (thousands) of small contigs. 1. Entering e-mail address is optional, but highly recommended to get an email after results have been processed. 2. Upload Sequence file using the “Upload file” button and selecting the sequence file (Fasta or GenBank format) to upload.

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a)

b)

Fig. 1 Genome sequence submission in antiSMASH, (a) Screenshot of the bacterial antiSMASH job submission page, describing the input options for genome sequence; (b) Screenshot of the notification settings and data input from bacterial antiSMASH job submission page

3. For the present study, S. griseus NBRC 13350 is chosen for analysis. Its genome is available in NCBI database under the RefSeq number NC_010572.1 (Fig. 1b). 4. Retrieve the file directly from NCBI. 5. Select the “Get from NCBI” option for Data Input. 6. Extended parameters (optional) There are total of nine extended features available in the latest version of antiSMASH 6.0 to refine the process of genome mining and annotation. For general analysis of bacterial sequences, the standard antiSMASH parameters work just fine with four default features, KnownClusterBlast, ActiveSiteFinder, SubClusterBlast, and RREFinder (Fig. 2), whereas other five features including MIBiG cluster comparison, Cluster Pfam analysis, ClusterBlast, Pfam-based GO term

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Fig. 2 Screenshot of the selected default parameters and extended features available from bacterial antiSMASH job submission page

annotation, and TIGRFam analysis are available which can enlarge the antiSMASH run (a) KnownClusterBlast analysis (default: on): Enabling this option indicate that the identified clusters are searched against the MIBiG repository [17]. (b) MIBiG cluster comparison (default: off): MIBiG is a hand curated data collection on gene clusters, which have been experimentally characterized. This option makes sure to draw a comparison between genes within the identified cluster against MIBiG repository. (c) Cluster PFAM analysis (default: off): If this option is enabled, each gene product encoded in the detected BGCs is analyzed against the PFAM database [18]. (d) ClusterBlast analysis (default: off): The algorithm used in this feature is similar to MultiGeneBlast and selecting this option increases runtime significantly. In this option, the identified clusters are searched against a comprehensive gene cluster database and similar clusters are identified [19]. (e) Active site finder (default: on): This option deals with the detection of active sites of several highly conserved biosynthetic enzymes and reports the variations among the active sites. (f) Pfam-based GO term annotation (default: off): Pfam is a large collection of protein multiple sequence alignments and profile hidden Markov models. A GO (Gene Ontology) annotation is a statement about the function of a particular gene and is created by associating a gene or gene product with a GO term. If this feature is enabled, each gene or RNA product is analyzed for GO annotation based on the results of Pfam (protein family).

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(g) Subcluster Blast analysis (default: on): This option accounts for identification of the clusters against a database containing operons involved in the biosynthesis of common secondary metabolite building blocks. (h) RREFinder (default: on): This feature enables the identified clusters to be searched against RiPP biosynthetic diversity and delivers a rich dataset of RRE (RiPP recognition element) sequences. (i) TIGRFam analysis (default: off): TIGRFams is a collection of protein families featuring curated multiple sequence alignments, hidden Markov models and associated information designed to support the automated functional identification of proteins by sequence homology. This feature allows the identified clusters to be compared with the functional identification of proteins. After setting the extended features, the task can be run by pressing the “Submit” button at the end of the page. In case the email address is not being provided in the beginning of task submission, the link to this page can be bookmarked—otherwise results cannot be accessible later. For a typical bacterial genome, the computing time is ~0.5–2 h under normal server load, but if long runtime options are selected, a typical analysis will take several days. 3.3 Analysis of antiSMASH Results

Once the job has been submitted successfully on the antiSMASH web page, the analysis and identification of the clusters are carried out on the servers. The results will be sent to the e-mail address which was provided during the job submission once it is finished. 1. Cluster overview table On the top of the screen, a colored circle represents each identified gene cluster. antiSMASH 6 genome mining of S. griseus NBRC 13350 identified 38 gene clusters, out of which 12 were showing 100% similarities with previously identified gene clusters. Here, a detailed list of clusters from S. griseus NBRC 13350 is displayed including coordinates of the identified gene cluster (Fig. 3). 2. Detailed observation view To display and analyze a respective BGC from the identified group, a click at one of the clusters leads from the color circle is required. Here, region 18 a PKS-NRPS hybrid cluster was chosen for analysis (Fig. 4). 3. Gene cluster details: By clicking an individual gene from any annotated biosynthetic gene clusters, retrieve the entire details about that particular gene (Fig. 5). 4. Details on domain architecture: click on domain symbol

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Fig. 3 Screenshot of the cluster overview table obtained from S. griseus NBRC 13350 through bacterial antiSMASH 6 genome mining and annotation analysis

In general, each type of polyketide-synthase module consists of several domains separated by short spacer regions with defined functions. The order of modules and domains of a complete polyketide-synthase is as follows (in the order N-ter minus to C-terminus). Starting or loading module: AT-ACPElongation or extending modules: -KS-AT-[DH-ER-KR]ACPTermination or releasing domain: -TE Domains: AT: Acyltransferase ACP: Acyl carrier protein with an SH group on the cofactor, a serine-attached 40 -phosphopantetheine KS: Keto-synthase with an SH group on a cysteine side-chain KR: Ketoreductase DH: Dehydratase ER: Enoylreductase MT: Methyltransferase O- or C- (α or β) SH: PLP-dependent cysteine lyase TE: Thioesterase

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Fig. 4 Screenshot of the detailed results view of region 18 or 1.18 obtained from S. griseus NBRC 13350 through bacterial antiSMASH 6 genome mining and annotation analysis

The order of modules and domains of a complete nonribosomal peptide synthetase is as follows. Initiation or Starting module: [F/NMT]-A-PCPElongation or Extending modules: -(C/Cy)-[NMT]-A-PCP[E]Termination or Releasing module: -(TE/R) (Order: N-terminus to C-terminus; []: optionally; (): alternatively) Domains F: Formylation (optional) A: Adenylation (required in a module) PCP: Thiolation and peptide carrier protein with attached 40 -phosphopantetheine (required in a module) C: Condensation forming the amide bond (required in a module) Cy: Cyclization into thiazoline or oxazolines (optional) Ox: Oxidation of thiazolines or oxazolines to thiazoles or oxazoles (optional)

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Fig. 5 Clicking on gene arrow reveals the detailed characteristics and features

Red: Reduction of thiazolines or oxazolines to thiazolidines or oxazolidines (optional) E: Epimerization into D-amino acids (optional) NMT: N-methylation (optional) TE: Termination by a thioesterase (only found once in a NRPS) R: Reduction to terminal aldehyde or alcohol (optional) X: Recruits cytochrome P450 enzymes (optional) Here we demonstrate a nonribosomal peptide synthetase modules and domains from region 18 of S. griseus NBRC 13350 below (Fig. 6). 5. Core structure prediction and prediction details At the right side of the window, structure deduced from the biosynthetic enzymes is displayed. Since the chosen cluster 18 is a hybrid cluster of PKS-NRPS, the display links contain NRPS/PKS product, under which the predicted core structure is available. The other cluster is NRPS/PKS monomer where NRPS/PKS monomer predictions are displayed. However, this is just a rough prediction of core scaffold based on assumed PKS/NRPS collinearity and does not take into account any

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Fig. 6 Screenshot of the modules and domains from region 18 of S. griseus NBRC 13350

tailoring modifications or nonstandard reactions. At the bottom of the panel, there is a link which directly links to the NORINE peptide database query form (Fig. 7). 6. Identification of similar gene clusters (cluster BLAST) Similar gene clusters are identified by searching against a comprehensive gene cluster database. The result displayed below depicts the similarity of cluster 18 from S. griseus NBRC 13350 against the other gene clusters obtained from the database (Fig. 8). 7. Identification of known clusters (from MIBiG dataset) The comparison against the known (and studied) biosynthetic gene clusters is displayed. Below is the cluster 18 from S. griseus NBRC 13350 (Fig. 9). 8. Subcluster Blast analysis: Similarities between operons among the biosynthetic gene clusters is identified by this analysis. Below it is displayed cluster 6 from S. griseus NBRC 13350 (Fig. 10). 9. MIBiG Comparison: This is the newest inclusion in version 6 of antiSMASH. The figure below displays a comparison between

Biosynthetic Gene Cluster Analysis in Actinobacterial Genus Streptomyces

Fig. 7 Core structure prediction with detailed features

Fig. 8 Similar gene cluster identification based on cluster BLAST

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Fig. 9 Known cluster BLAST reveals the similarity between biosynthetic gene clusters

Fig. 10 Subcluster BLAST analysis reveals the similarity between operons among the biosynthetic gene clusters

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Fig. 11 MIBiG comparison between genes within two similar biosynthetic gene clusters ranked based on similarity score

Fig. 12 Pfam domains explains the details of protein family corresponding to the identified genes

genes within two similar biosynthetic gene clusters ranked based on similarity score. Below, we displayed the analysis of region 18 from S. griseus NBRC 13350 (Fig. 11). 10. Pfam domains: This displays the details of protein family corresponding to the identified genes. Again the Pfam domain information below is from the region 18 from S. griseus NBRC 13350 (Fig. 12).

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Fig. 13 Display the downloading options of antiSMASH results 3.4 Downloading Results

The results of the antiSMASH analysis are stored on the server for 1 month and are deleted afterward. You can download all or subsets of the results using the download button at the top of the antiSMASH results page (Fig. 13). Download all results: Download a ZIP file containing all results. Take the following steps to open the downloaded results: 1. Extract complete ZIP file to a folder on your disc. 2. Open the “index.html” file with your (we recommend Firefox for local use).

web browser

Download XLS overview file: Download MS Excel file with cluster identification summary Download EMBL summary file/GenBank summary file: Download EMBL/Genbank file containing all the annotation for use in third party sequence analysis Software [14]. (https://docs.anti smash.secondarymetabolites.org/PDFmanual/ antiSMASH5manual.pdf) 3.5 antiSMASH Data Analysis of S. griseus NBRC 13350

The genome of S. griseus NBRC 13350 is 8,545,929 bp long and based on antiSMASH version 6 analysis there are 38 gene clusters predicted from the genome sequence (Fig. 14). Out of the 38 gene clusters, twelve clusters possess 100% similarity with other known BGCs and only one cluster with 94% similarity, whereas the remaining clusters were detected with less than 50% similarity which is a possible indication of producing new or novel natural products by S. griseus NBRC 13350. Among the 38 gene clusters, most of them were in the hybrid category with 8 recovered BGCs, followed by 6 terpene and RiPP gene clusters each. Remaining 18 clusters were distributed between NRPS (4 BGCs), PKS (3 BGCs), siderophore (2 BGCs), melanin (3 BGCs), and others (6 BGCs) (Fig. 15). Below are some of the compounds produced by the BGCs which showed 100% similarity with the gene clusters of S. griseus NBRC 13350 (Fig. 16).

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Fig. 14 Distribution of 38 gene clusters in Streptomyces griseus NBRC 13350 genome

Fig. 15 Distribution of different types of gene clusters in Streptomyces griseus NBRC 13350 genome

Fig. 16 Some of the predicted compounds from Streptomyces griseus NBRC 13350 genome

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Conclusion Among the available widely dispersed genome mining tools, antiSMASH not only provides a unique addition, but also earns a reputation for very high accuracy in its individual cluster

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annotations. antiSMASH is following an exceptional novel analysis such as BLAST-based gene cluster alignments and secondary metabolite COG (Clusters of Orthologous Groups) phylogenetic trees for biosynthetic gene cluster annotation. Day by day, synthetic biology is bringing up new challenges, new ways to study the gene clusters and is leading antiSMASH to come up with modified version and quickly pinpoint those gene clusters most interesting for further study. References 1. Saha S et al (2020) Discovery of unusual cyanobacterial tryptophan-containing anabaenopeptins by MS/MS-based molecular networking. Molecules 25(17):3786 2. Lee N et al (2020) Mini review: genome mining approaches for the identification of secondary metabolite biosynthetic gene clusters in Streptomyces. Comput Struct Biotechnol J 18:1548–1556 3. Lee N et al (2020) Thirty complete Streptomyces genome sequences for mining novel secondary metabolite biosynthetic gene clusters. Sci Data 7(1):55 4. Ventola CL (2015) The antibiotic resistance crisis: part 1: causes and threats. P T 40 (4):277–283 5. Fair RJ, Tor Y (2014) Antibiotics and bacterial resistance in the 21st century. Perspect Medicin Chem 6:25–64 6. Pham JV et al (2019) A review of the microbial production of bioactive natural products and biologics. Front Microbiol 10:1404 7. Belknap KC et al (2020) Genome mining of biosynthetic and chemotherapeutic gene clusters in Streptomyces bacteria. Sci Rep 10 (1):2003 8. Aigle B et al (2014) Genome mining of Streptomyces ambofaciens. J Ind Microbiol Biotechnol 41(2):251–263 9. Ikeda H et al (2003) Complete genome sequence and comparative analysis of the industrial microorganism Streptomyces avermitilis. Nat Biotechnol 21(5):526–531 10. Ishaque NM et al (2020) Isolation, genomic and metabolomic characterization of Streptomyces tendae VITAKN with quorum sensing inhibitory activity from Southern India. Microorganisms 8(1):121

11. Saha S et al (2021) Draft genome sequence of terrestrial Streptomyces sp. strain VITNK9, isolated from Vellore, Tamil Nadu, India, exhibiting antagonistic activity against fish pathogens. Microbiol Resource Announcements 10 (1):e01282–e01220 12. Weber T, Kim HU (2016) The secondary metabolite bioinformatics portal: computational tools to facilitate synthetic biology of secondary metabolite production. Synth Syst Biotechnol 1(2):69–79 13. Blin K et al (2019) Recent development of antiSMASH and other computational approaches to mine secondary metabolite biosynthetic gene clusters. Brief Bioinform 20 (4):1103–1113 14. Blin K et al (2019) antiSMASH 5.0: updates to the secondary metabolite genome mining pipeline. Nucleic Acids Res 47(W1):W81–W87 15. Hyatt D et al (2010) Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics 11:119 16. Majoros WH, Pertea M, Salzberg SL (2004) TigrScan and GlimmerHMM: two open source ab initio eukaryotic gene-finders. Bioinformatics 20(16):2878–2879 17. Medema MH et al (2015) Minimum information about a biosynthetic gene cluster. Nat Chem Biol 11(9):625–631 18. Finn RD et al (2016) The Pfam protein families database: towards a more sustainable future. Nucleic Acids Res 44(D1):D279–D285 19. Medema MH, Takano E, Breitling R (2013) Detecting sequence homology at the gene cluster level with MultiGeneBlast. Mol Biol Evol 30(5):1218–1223

Chapter 34 PCR-Based Determination of Secondary Metabolite Genes in Actinobacterial Cultures Manigundan Kaari, Abirami Baskaran, Gopikrishnan Venugopal, Jerrine Joseph, and Radhakrishnan Manikkam Abstract Actinobacteria are commonly found in nature, and special attention is given to their role in development of different secondary bioactive metabolites. In particular, Streptomyces is a wide and useful resource of bioactive and complex secondary metabolites, many of which have broad spectrum applications. Actinobacteria are natural producers of bioactive substances and hence continue to be an important source of novel secondary metabolites for drug use. In order to amplify genes associated with secondary metabolite biosynthesis, PCR-based methods have been used effectively, and it is therefore possible to predict if secondary metabolite pathways are present inside an organism. The main enzymes for secondary metabolite synthesis are polyketide synthases and nonribosomal peptide synthetases. Ansamycins, tetracyclines, polyenes, and glycopeptides are examples of antibiotic groups developed by this biosynthesis. Key words PCR, Actinobacteria, Secondary metabolites, Genes

1

Introduction Microbial natural products are the primary resource from which new medicinal drugs are produced, while actinobacteria alone account for approximately more than 70% of antibiotics discovered. Renewed interest in the community of actinobacteria that have long been recognized as a prolific source of natural products, including polyketides, nonribosomal peptides, and combinations thereof, is included in the answer to this need (see Notes 1 and 2). The gene-based screening allows the rapid detection of biosynthetic gene clusters in the isolated strains [1]. The organized activities of enzymatic assembly lines performing iterative chemical condensation of monomeric groups, including carboxylic acid and/or amino acid monomers, are synthesized by polyketides, nonribosomal peptides, and polyketide/nonribosomal peptide combinations. More than 20 gene clusters for the development of

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_34, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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secondary metabolites and novel antibiotics were found in Streptomyces coelicolor and Streptomyces avermitilis [2]. There are 25 types of gene clusters for secondary metabolites within the genome of Streptomyces avermitilis. Of the 25 gene clusters, eight are polyketides for type I, two are polyketides for type II, and eight gene clusters are involved in nonribosomal peptide synthetase biosynthesis (NRPS) compounds [3]. PCR amplification of speculated secondary metabolite genes and ascertaining their homology and phylogeny through bioinformatic tools are detailed in this chapter.

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Materials 1. Actinobacterial DNA. 2. Master Mix (Thermo Scientific). 3. Primers (first BASE laboratories). 4. Micro Elute gel extraction kit (Favorgen). 5. Streptomyces DNA isolation kit. 6. Deionized water. 7. PCR thermal cycler. 8. PCR purification kit. 9. Automated sequencer.

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Methods 1. Isolate genomic DNA from the given actinobacterial culture using Streptomyces DNA isolation kit. 2. Perform PCR amplification of the gene of interest in a total of 50 μl reaction volume containing 0.5  Master Mix (25 μl), 10 pmol of each primer (3 μl), 100 ng of DNA template (3 μl), and 19 μl of deionized water. 3. Perform gradient PCR to identify the optimum annealing temperatures for each pair of primers. 4. Accomplish PCR amplification of the KS domains of polyketide synthase type I (PKS I), KS domains of PKS II, the adenylation domains of nonribosomal peptide synthase (NRPS), the enzyme aminodeoxyisochorismate synthase PhzE of the phenazine pathways (phzE), the enzyme dTDP-glucose-4, 6-dehydratase (dTGD) of glycosylation pathway, the enzyme halogenase (Halo) of halogenation pathway, and the enzyme cytochrome P450 hydroxylase (CYP) in polyene polyketide biosynthesis genes using the respective primers.

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5. Purify the PCR product using Micro Elute gel extraction kit (Favorgen) and sequence by dye terminator chemistry using an automated sequencer. 6. Analyze the sequences using the BLASTN search program at The National Center for Biotechnology Information (NCBI): http://www.ncbi.nlm.nih.gov/BLAST/. 7. Perform the BLASTN to estimate the percentage homology with the reported gene clusters, and then submit the sequences to NCBI, GenBank, to get the accession numbers. 8. Analyze the sequences by using various bioinformatics tools, such as EMBOSS transeq (https://www.ebi.ac.uk/Tools/st/ emboss_transeq/) where the nucleotide sequences are translated into their respective peptides sequences. 9. Perform the BLASTP (https://blast.ncbi.nlm.nih.gov/Blast. cgi) of all the resultant translated frames to find the similarity index of the peptides based on the percentage similarity. The functional protein with the highest similarity was selected from all the 6 reading frames. 10. Select the translated sequence of actinobacterial proteins for multiple sequence alignment using the Clustal W alignment tool built-in MEGA 6 (https://www.megasoftware.net/). 11. Compare the partial 16S rRNA sequences of the selected actinobacterial strains using the BLAST tool available on NCBI. 12. Obtain the sequences of closely related species from NCBI and align using the CLUSTAL-W program. 13. The neighbor-joining phylogenetic tree was inferred using Kimura’s 2-parameters in software MEGA 6.0. 14. Evaluate the Tree topologies for branch support using 1000 replications.

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Notes 1. Biosynthesis of secondary metabolites is catalyzed by specific enzymes usually encoded by gene clusters. 2. Polyketide synthases (PKS) and nonribosomal peptide synthetases (NRPS) are the major enzymes of secondary metabolite synthesis.

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References 1. Wood SA, Kirby BM, Goodwin CM, Le Roes M, Meyers PR (2007) PCR screening reveals unexpected antibiotic biosynthetic potential in Amycolatopsis sp. strain UM16. J Appl Microbiol 102(1):245–253 2. Busti E, Monciardini P, Cavaletti L, Bamonte R, Lazzarini A, Sosio M, Donadio S (2006) Antibiotic-producing ability by representatives of a newly discovered lineage of actinomycetes. Microbiology 152(3):675–683

3. Omura S, Ikeda H, Ishikawa J, Hanamoto A, Takahashi C, Shinose M, Takahashi Y, Horikawa H, Nakazawa H, Osonoe T et al (2001) Genome sequence of an industrial microorganism Streptomyces avermitilis: deducing the ability of producing secondary metabolites. Proc Natl Acad Sci U S A 98 (21):12215–12220

Chapter 35 Molecular Mass Determination of Bacteriocin by SDS-PAGE Analysis Santhosh Arul, M. Jayashankar, and Haripriya Dayalan Abstract Actinobacteria are important organisms used mainly for the production of enzymes of commercial importance and secondary metabolites in many industries. The secondary metabolites from Actinobacteria have functions in physiology, communications, medicine etc. Bacteriocin is one such secondary metabolite produced by Actinobacteria, which functions as antimicrobials. Bacteriocins are synthesized in the ribosomes which are proteins or peptides having potential as antimicrobials with low potential to development of resistance. Bacteriocins are generally classified into two major groups based on the presence or absence of lanthionine. Bacteriocins have potential as a bioprotectant and are mostly used in the food preservation sector. The usual process of production of bacteriocin involves selection and isolation of strains from a population. The selected strains are then cultured and identified by their 16S rRNA sequence. One of the standard methods for molecular mass determination is SDS-PAGE analysis. The SDS-PAGE uses a denaturing condition with an anionic detergent sodium-dodecyl sulfate. Polyacrylamide gel is used in the determination of apparent molecular mass based on the separation of proteins on the gel. In this chapter we present a method to determine the molecular mass of bacteriocin by SDS-PAGE. Key words Actinobacteria, Bacteriocin, SDS-PAGE, Molecular mass

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Introduction Actinobacteria are Gram-positive bacteria with high G + C content in their DNA. They form one of the largest phyla of bacteria with terrestrial and aquatic distribution [1–3]. Actinobacteria are important in the biotechnology and pharmaceutical industries for their ability to produce active components; at least 10,000 bioactive components are known to be produced by Actinobacteria [4]. One of such important products is bacteriocin, which are small peptides or proteins that are usually about less than 10 kDa in size; they are synthesized by ribosomes and are cationic with 30–60 amino acids [5–8]. They are classified into 4 major classes based on their size and characteristics [9]. Bacteriocins possess potent broad-spectrum antibacterial activity with low susceptibility

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_35, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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to resistance development and are effective against multidrug resistant strains [9]. With a wide variety of applications, these peptides are potential alternatives to antimicrobial agents currently in use due to the increasing antimicrobial resistance. Additionally bacteriocins possess anti-inflammatory activity [10], anticancer activity [11], and antiallergic activity [12]. These broad applications of bacteriocins make them commercially and clinically important agents and thus determining their molecular weight is essential.

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Materials 1. MRS Broth. Ingredients

Grams/Liter

Proteose peptone

10.000

HM peptone B

10.000

Yeast extract

5.000

Dextrose (glucose)

20.000

Polysorbate 80 (tween 80)

1.000

Ammonium citrate

2.000

Sodium acetate

5.000

Magnesium sulfate

0.100

Manganese sulfate

0.050

Dipotassium hydrogen phosphate

2.000

Final pH (at 25
C)

6.5  0.2

Suspend 55.15 g in 1000 ml distilled water. Heat if necessary to dissolve the medium completely. Distribute in flasks and sterilize by autoclaving at 15 lbs. pressure (121
C) for 15 min. 2. Resolving Gel Buffer. 1.5 M Tris–HCl, pH 8.8. Add about 100 mL water to a 1 L graduated cylinder or a glass beaker (see Note 1). Weigh 181.7 g Tris–HCl and transfer to the cylinder. Add water to a volume of 900 mL. Mix and adjust pH with HCl. Make up to 1 L with water. Store at 4
C. 3. Stacking Gel Buffer. 0.5 M Tris–HCl, pH 6.8. Weigh 60.6 g Tris–HCl and prepare a 1 L solution as in the previous step. Store at 4
C. 4. Thirty Percent Acrylamide/Bis Solution (29.2:0.8) Acrylamide: Bisacrylamide.

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Weigh 29.2 g of acrylamide (see Note 4)monomer and 0.8 g Bis (cross-linker) and transfer to a 100 mL graduated cylinder containing about 40 mL of water. Add a spatula of AG501-X8 (D) mixed-resin beads and mix for about 30 min. Make up to 100 mL with water and filter through a 0.45 μm filter. Store at 4
C, in a bottle wrapped with aluminum foil (see Note 5). 5. Ammonium Persulfate 10% solution in water (see Note 6). 6. N, N, N, N0 -Tetramethyl-ethylenediamine Store at 4
C. 7. SDS-PAGE Running Buffer 0.025 M Tris–HCl, pH 8.3, 0.192 M glycine, 0.1% SDS. SDS lysis buffer (5X): 0.3 M Tris–HCl (pH 6.8), 10% SDS, 25% β-mercaptoethanol, 0.1% bromophenol blue, 45% glycerol. Leave one aliquot at 4
C for current use and store the remaining aliquots at 20
C. 8. Bromophenol Blue (BPB) Solution. Dissolve 0.1 g BPB in 100 mL water. 9. Reducing Sample Buffer. 4.6% SDS, 10% ß-mercaptoethanol, 20% glycerol, 1.5% Tris–HCl pH 6.8, 1% bromophenol blue. 10. Staining Solution. Dissolve 0.4 g of Coomassie blue in 200 ml of 40% methanol, to this add 200 ml of 20% acetic acid. 11. Destaining Solution Add 500 ml of methanol to 300 ml of water. Add 100 ml of acetic acid and adjust the final volume to 1 L.

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Methods 1. Grow isolated strains in MRS broth at 30
C to the early stationary phase with vigorous shaking (120 rpm). 2. Obtain cell-free culture supernatants by centrifugation at 1000  g at 4
C for 10 min. 3. Adjust the pH to 6.5 using 1 N NaOH. 4. Sterile filter using 0.22 μm membrane filter. 5. Transfer the filtered bacteriocin to a flask and precipitate it with ammonium sulfate at 80% saturation. 6. After the preparations stand at 4
C overnight, precipitate the proteins by centrifugation (3000  g, 20 min, 4
C), and

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dissolve in small volumes of 20 mM sodium citrate buffer (pH 5.0). 7. Then dialyze each solution against the same buffer at 4
C for several hours using a cellulose ester membrane (see Note 7). 3.1 Measurement of Protein Concentration and Molecular Weight

1. Measure the protein concentration of partially purified bacteriocin based on the Bradford method [13]. 2. Plot a standard curve of protein using 1 mg/mL of bovine serum albumin (BSA). Use a concentrations range of 0; 2.5; 5; 7.5; 10; 12.5 μg/μL. 3. Add 5 mL of Bradford reagent and incubate for 15 min at room temperature. 4. After the reaction, measure the absorbance at 595 nm. 5. Quantify the unknown protein concentration of the partially purified bacteriocin from the standard curve based on its absorbance.

3.2

SDS-Page

3.2.1 Sodium Dodecyl Sulfate Polyacrylamide Gel Electrophoresis

Estimate the molecular weight (MW) of bacteriocin using the sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) method [14]. 1. Dilute the protein sample to a final concentration of 10 μg/μL with Tris–HCl buffer (pH 6.8). 2. Prepare the protein samples with the addition of reducing sample buffer (1:1 v/v). 3. Heat the samples at 100
C for 5 min. 4. Prepare 16.5% separating gel and 3% stacking gel and allow it to solidify and set it in the apparatus. 5. Load 20 μL of each prepared sample into SDS-PAGE wells. 6. Use a prestained protein marker and load it in a separate well of the same SDS-PAGE to estimate the molecular weight. 7. Run the protein on the gel for 2 h with 100 V constant current. 8. After the electrophoresis stain the gel with Coomassie blue for 15 min. 9. Destain the gel with destaining solution. 10. View the gel under a white light illuminator or use a gel documentation system and capture the image of the gel. 11. Determine the molecular mass by comparing the protein lane to the corresponding marker lane. 12. Measure the distance traveled by protein and the dye front using a ruler and use the relative migration distance formula Rf ¼ migration distance of the protein/migration distance of the dye front.

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13. Plot the log molecular weight vs Rf and generate the equation y ¼ mx + b and solve to determine the molecular weight of unknown protein.

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Notes 1. Prepare all solutions using ultrapure water. 2. Use analytical grade reagents. 3. Prepare and store all reagents at room temperature (unless indicated otherwise). 4. Care should be taken while handling Acrylamide. 5. The percentage of the gel may be modified based on the size of the bacteriocin. 6. Prepare fresh APS. 7. Decide dialysis membrane cut off based on the predicted molecular weight of the bacteriocin.

References 1. Barka EA, Vatsa P, Sanchez L, Gaveau-VaillantN, Jacquard C, Klenk H-P, Cle´ment C, Ouhdouch Y, van Wezel GP (2015) Taxonomy, physiology, and natural products of Actinobacteria. Microbiol Mol Biol Rev 80 (1):1–43. https://doi.org/10.1128/mmbr. 00019-15 2. Embley TM, Stackebrandt E (1994) The molecular phylogeny and systematics of the Actinomycetes. Annu Rev Microbiol 48 (1):257–289. https://doi.org/10.1146/ annurev.mi.48.100194.001353 3. Gao B, Gupta RS (2012) Phylogenetic framework and molecular signatures for the main clades of the phylum actinobacteria. Microbiol Mol Biol Rev 76(1):66–112. https://doi.org/ 10.1128/mmbr.05011-11 4. Be´rdy J (2005) Bioactive microbial metabolites. J Antibiot 58(1):1–26. https://doi.org/ 10.1038/ja.2005.1 5. vanBelkum MJ, Martin-Visscher LA, Vederas JC (2011) Structure and genetics of circular bacteriocins. Trends Microbiol 19 (8):411–418. https://doi.org/10.1016/j. tim.2011.04.004

6. Bierbaum G, Sahl H-G (2009) Lantibiotics: mode of action, biosynthesis and bioengineering. Curr Pharm Biotechnol 10(1):2–18. https://doi.org/10.2174/ 138920109787048616 7. Riley MA, Chavan MA (2006) Bacteriocins: ecology and evolution, 2007th edn. Springer, Berlin 8. Nissen-Meyer J, Rogne P, Oppegard C, Haugen H, Kristiansen P (2009) Structurefunction relationships of the non-lanthioninecontaining peptide (class II) bacteriocins produced by gram-positive bacteria. Curr Pharm Biotechnol 10(1):19–37. https://doi.org/10. 2174/138920109787048661 9. Meade S, Garvey (2020) Bacteriocins, potent antimicrobial peptides and the fight against multi drug resistant species: resistance is futile? Antibiotics 9(1):32. https://doi.org/10. 3390/antibiotics9010032 10. Cotter P, Hill C, Ross R (2005) Bacterial Lantibiotics: strategies to improve therapeutic potential. Curr Protein Pept Sci 6(1):61–75. https://doi.org/10.2174/ 1389203053027584

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11. Bhat UG, Halasi M, Gartel AL (2009) Thiazole antibiotics target FoxM1 and induce apoptosis in human cancer cells. PLoS One 4(5): e5592. https://doi.org/10.1371/journal. pone.0005592 12. Fredenhagen A, Fendrich G, M€arki F, M€arki WA, Gruner J, Raschdorf F, Peter H, H. (1990) Duramycins B and C, two new lanthionine containing antibiotics as inhibitors of phospholipase A2. Structural revision of duramycin and cinnamycin. J Antibiot 43 (11):1403–1412. https://doi.org/10.7164/ antibiotics.43.1403

13. Ernst O, Zor T (2010) Linearization of the Bradford protein assay. J Vis Exp (38):1918. https://doi.org/10.3791/1918 14. Mulyawati AI, Ardyati T, Jatmiko YD (2019) Partial purification and characterization of bacteriocins from Lactobacillus plantarum SB7 and Bacillus amyloliquefaciens BC9 isolated from fermented Sumbawa mare’s milk as food preservative candidates. In: International conference on biology and applied science. https://doi.org/10.1063/1.5115747

Chapter 36 MALDI-TOF Analysis of Actinobacterial Peptides with Respect to MASCOT Database Shanmugaraj Gowrishankar, Arumugam Kamaladevi, and Shunmugiah Karutha Pandian Abstract The role of Actinobacteria, being an imperative resource of structurally distinct classes of short peptides, in new antibiotic development and discovery has been inevitable. Globally, mass spectrometry (MS) is one of the most widely deployed remarkable molecular techniques for the identification of bacteria and their associated peptides. The advances obtained in the field of MS over the past decades have enabled faster, precise, and more reliable data acquisition in protein/peptide identification. The other biomolecules viz. lipids, fatty acid, and carbohydrate in a given sample can also be identified. The technique basically involves the ionization of sample using soft ionization source and measures their mass to charge (m/z) ratio. Specifically, matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) profiling has been a powerful technique used for the rapid and accurate identification of the Actinobacterial peptides. The m/z spectrum obtained for the different protein samples will be matched with the public database like MASCOT, based on the query coverage and peptide match. Key words Actinobacteria, peptide, Mass spectrometry, MALDI-TOF, MASCOT

1

Introduction Coupling of mass spectrometry (MS) with extensive protein/peptide sequence databases and software packages for data mining has been a rapid as well as sensitive tool for protein identification. Matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) and electron spray ionization-mass spectrometry (ESI-MS) are the two commonly used basic types of MS. Notably because of non-requirement of any special training and ease of use, MALDI-TOF has become a very approachable technique. In contrast, the instrumentation of ESI coupled with capillary/nano liquid chromatography made the system quite complicated and

Shanmugaraj Gowrishankar and Arumugam Kamaladevi contributed equally to this work. Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_36, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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requires experienced/experts to operate. The principle of MALDITOF-based protein identification involves digestion of proteins with a specific protease called trypsin. The digested protein creates a mixture of peptides of unique sequence length. By measuring the molecular mass of these peptides in the mixture attribute a dataset known as peptide mass fingerprint (PMF) [1]. The PMF deciphers theoretical molecular mass of digested peptides and helps to identify a best matched protein in MASCOT database. However, PMF dataset should be in sufficient quality and the best matched peptides with a decent significant score could be considered as the desired protein or protein of interest. In order to validate the result, critical analysis of the score generated upon peptide match determines the accuracy of protein identification. Therefore, the present chapter focuses on protein spot excision from gels, sample processing (destaining, reduction, alkylation, tryptic digestion) for identification, and MALDI-TOF analysis followed by MASCOT search.

2

Materials

2.1 Culturing and Harvesting Actinobacteria

1. Petri plates, spatula, centrifuge, microcentrifuge, incubator, and vortexer. 2. ATCC 172 medium—10 g/L glucose, 20 g/L starch, 5 g/L peptone, 2 g/L casein hydrolysate, 1.2 g/L sodium pyruvate, 0.1 g/L MgSO4, 1.2 g/L K2HPO4. 3. Mineral base medium enriched with 10 mM sodium succinate and 0.05% casamino acids. 4. GYM medium—4 g/L glucose, 4 g/L yeast extract, 10 g/L malt extract, 2 g/L CaCO3, 12 g/L agar. 5. Lysis buffer—50 mM Tris–Cl pH 7, 150 mM NaCl, 10 mM MgCl2, 1 mM EDTA, 7 mM β-mercaptoethanol, and 0.5 mM phenylmethylsulfonyl fluoride.

2.2 Preparation of Actinobacteria Proteome

1. Water bath, centrifuge, vortexer, glass bead (0.1 mm), sonicator, biophotometer. 2. Bradford reagent. 3. Lysis buffer—50 mM Tris–Cl pH 7, 150 mM NaCl, 10 mM MgCl2, 1 mM EDTA, 7 mM β-mercaptoethanol, and 0.5 mM phenylmethylsulfonyl fluoride.

2.3 TwoDimensional Gel Electrophoresis (2D-GE)

1. Protein (500 μg to 1 mg), trichloroacetic acid, ammonium bicarbonate, sterile distilled water. 2. Sample loading buffer—7 M urea, 2 M thiourea, 40 mM dithiothreitol (DTT), 4% (w/v) -[(3-cholamidopropyl)dimethylammonio]-1-propanesulfonate (CHAPS), 2% (v/v)

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carrier ampholytes bromophenol blue.

(add

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3. Rehydration buffer—7 M urea, 2 M thiourea, 0.28% (w/v) DTT (add prior to use), 2% (w/v) CHAPS, 2% (v/v) carrier ampholytes (add prior to use), and 0.001% bromophenol blue. 2.4

Equilibration

1. SDS-equilibration buffer—6 M urea, 30% (v/v) glycerol, 75 mM tris pH 8.8, 2% (w/v) SDS, 0.002 (w/v) bromophenol blue, distilled water. 2. Add 1% DTT and 2.5% iodoacetamide prior to use in the equilibration steps.

2.5 Gel Electrophoresis

1. 10
SDS electrophoresis buffer (Laemmli buffer)—250 mM tris base, 1.92 M glycine, 1% (w/v) SDS, distilled water. 2. 4
Tris buffer (pH 8.8) (1000 mL)—1.5 M tris base, 750 mL distilled water, adjust the pH to 8.8 using HCl and make up the final volume to 1000 mL with water. 3. 12.5% denaturant polyacrylamide gel (500 mL)—209 mL 30% acrylamide bisacrylamide solution, 125 mL 4
tris buffer pH 8.8, 5 mL 10% SDS, 5 mL 10% ammonium persulfate, 250 μL TEMED, 150.75 mL distilled water. 4. Fixing solution—40% methanol, 10% glacial acetic acid, 50% distilled water. 5. Coomassie brilliant blue (CBB) stain—500 mL sterile distilled water, 10% orthophosphoric acid, 10% ammonium sulfate, 0.24 g CBB G-250, make up the final volume to 800 mL, 20% methanol (add the reagents in the given order for a proper preparation).

2.6 Excision of Protein Spot, Destaining, In-Gel Trypsinization, and Sample Processing for MALDI-TOF

1. Detaining solution—25 mM ammonium bicarbonate, 50% acetonitrile, MS grade water. 2. Reduction solution—25 mM ammonium bicarbonate, 10 mM DTT, MS grade water. 3. Alkylation solution—25 mM ammonium bicarbonate, 55 mM iodoacetamide, MS grade water. 4. Washing solution—100 mM ammonium bicarbonate, 10% acetonitrile, MS grade water. 5. Peptide resuspension solution—50% acetonitrile, 5% trifluoroacetic acid, MS grade water.

2.7 MALDI Analysis and Protein Identification by MASCOT System

1. α-Cyano-4-hydroxycinnamic acid matrix (CHCA) (5 mg/ mL)—5 mg CHCA, 1 mL of diluent (50% acetonitrile, 0.1% trifluoroacetic acid, 50% MS grade water).

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Methods

3.1 Culturing and Harvesting Actinobacteria [2–4]

1. Inoculate a single colony of Actinobacteria in ATCC 172 medium or mineral base medium enriched with 10 mM sodium succinate and 0.05% casamino acids. 2. Incubate the cells at 30  C in an orbital shaker at 200 rpm. 3. Centrifuge the liquid culture at 2500
g for 10 min at 4  C. 4. For solid culture, inoculate spore suspension (100 μL) in a petri plate containing GYM medium and incubate the petri plates at 30  C. 5. Allow the Actinobacterial culture to grow on a cellophane disk. 6. Scrap the mycelium culture from the cellophane disk using a sterile plain spatula (Harvesting). 7. Dissolve the harvested Actinobacterial mycelium in lysis buffer (volume as required). 8. Disaggregate the mycelium by vortexing the pellet vigorously for a minute in an ice cold condition. 9. Centrifuge the mixture at 2500
g for 10 min at 4  C. 10. Wash the pellet containing Actinobacterial mycelium thrice with sterile distilled water. 11. Repeat the disaggregation step for five times to improve the yield.

3.2 Preparation of Actinobacteria Proteome [5, 6]

1. For soluble protein, boil the disaggregated Actinobacterial cells at 60  C for an hour. 2. Shake the sample vigorously with a glass bead of 0.1 mm size. 3. Add lysis buffer (volume as required) to the mixture. 4. Homogenize the content by employing sonication for 5 cycles (5 s pulse for every 5 s) on ice. 5. Centrifuge the cell lysate at 135000
g for 10 min at 4  C to remove the unbroken cells. 6. Collect the supernatant containing protein in different microcentrifuge tube(s). 7. Again, resuspend the pellet containing unbroken cells in lysis buffer and sonicate the mixture. 8. Centrifuge the cell lysate at 135000
g for 10 min at 4  C. 9. Pool the isolated proteome together and add protease inhibitor (PMSF). 10. Quantify the protein by Bradford method.

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1. Take 500 μg to 1 mg of protein in a final volume of 50–75 μL. 2. Add trichloroacetic acid (10% w/v) to the protein mixture. 3. Incubate the tube at 4  C for 1 h. 4. Centrifuge the tube at 12,000 rpm for 15 min at 4  C. 5. The resultant pellet contains the protein (devoid of other molecular contaminants). 6. Wash the pellet thrice with ice cold acetone to remove the traces of contaminants. 7. Wash the pellet with 50 mM ammonium bicarbonate followed by sterile distilled water to neutralize the pellet. 8. Resuspend the neutralized pellet with sample loading buffer. 9. Load the sample loading buffer containing total protein on immobilized pH gradient (IPG) strips of desired length placed in rehydration tray. 10. Allow to rehydrate the strip with protein samples for 12 h at ambient temperature. 11. Perform isoelectric focusing (IEF) for rehydrated IPG strips by employing IEF system. 12. Follow the four-step program for 7 cm IPG strips: (1) 0–250 V for 1 h, (2) 250 V for 1.5 h, (c) 250–3000 V for 4 h, (4) 3000 V constant until it reaches 15 kVh. Note: Limit the current at 50 μA/strip.

3.4

Equilibration

1. Place the focused strips in rehydration tray containing reduction solution (1% DTT and bromophenol blue). 2. Incubate the tray at room temperature for 20 min with periodic gentle shaking. 3. Transfer the strip to SDS-equilibration buffer containing 2.5% iodoacetamide and trace of bromophenol blue. 4. Incubate the tray at room temperature for 20 min with gentle shaking at regular intervals.

3.5 Gel Electrophoresis [7]

1. Prepare denaturant polyacrylamide gel mix for a required volume. 2. Pour the polyacrylamide gel mix into the gel plate set up and keep at room temperature until complete polymerization occurs. 3. Place the equilibrated strips on polymerized SDS gel and overlay it with soft agar. 4. Fill the buffer tank with 1
electrophoresis buffer and apply the current to perform electrophoresis. 5. After electrophoretic run, remove the gel from the gel plates and transfer it to the fixating solution.

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6. Incubate the gel in fixating solution for 4–12 h. 7. Stain the gel with CBB (at least for 4 h) to visualize the protein spots. 3.6 Excision of Protein Spot, Destaining, In-Gel Trypsinization, and Sample Processing for MALDI-TOF Analysis

1. Excise the protein spots from the gel manually (use end removed micro-tips to accommodate the various diameters of spots). 2. Transfer the gel pieces to a microcentrifuge tube. 3. Destain and dehydrate the gel pieces repeatedly with 30% acetonitrile (ACN) and ammonium bicarbonate (100 mM) in 1:1 ratio. 4. Vacuum dry the gel pieces by employing lyophilizer to remove the excess water. 5. Wash the gel pieces with 50 μL of ACN and 50 μL of ammonium bicarbonate (100 mM) repeatedly for each 10 min to dehydrate and rehydrate the gel pieces. 6. Repeat the steps until getting the transparent gel pieces. 7. Add 50 μL of DTT (10 mM) to alkylate the cysteine residues in the protein spots. 8. Incubate the tubes in the dark for 30 min. 9. Add 50 μL of iodoacetamide (50 mM) and incubate the tubes in the dark for 30 min. 10. Wash the gel pieces thrice with 150 μL of ACN. 11. Vacuum dry the samples. 12. Add 5 μL of 10 mM ammonium bicarbonate in 10% ACN containing 400–600 ng of trypsin. 13. Incubate the tube in ice for 30 min. 14. Then, add 50 μL of ammonium bicarbonate in 10% ACN (care must be taken that the gel pieces should be completely immersed in the solution). 15. Incubate the set up at 37  C for 16–18 h. 16. Spin the tubes for 50 s and collect the supernatant containing peptides in a separate low binding microcentrifuge tube. 17. Add 25 μL of 60% ACN containing 0.1% trifluoroacetic acid and sonicate (2200 MHz) the content for 3 min, to extract the peptide trapped in the gel pieces. 18. Spin the tubes at 10,000 rpm for 10 min. 19. Collect and pool the supernatant. 20. Vacuum dry the extracted peptides for 1 h. 21. Dissolve the dried peptide in a peptide resuspension buffer.

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3.7 MALDI Analysis and Protein Identification by MASCOT System [7]

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1. For MALDI analysis, spot 0.5 μL of CHCA on a stainless steel target plate. 2. Add 0.5 μL of peptide samples on the dried matrix spot and let it dry at room temperature for 30 min. 3. Analyze the peptide by MALDI analyzer coupled with laser source (377 nm) in reflectron ion mode. 4. Use optimum laser power for precise signal. 5. Note: If the laser power is increased manually in order to obtain strong signal, it interferes with the resolution and burns off the sample(s). Therefore, laser signal should be set optimally for obtaining excellent signal. 6. Use positive–ion reflectron mode with 20 kV acceleration voltage to obtain spectra.

3.8 Creating Peptide Mass Fingerprint Data

1. Apply similar power to obtain good MALDI spectrum of trypsin-digested protein (Fig. 1). 2. Extract the PMF data from the MALDI spectrum by employing appropriate software associated with the instrument.

Fig. 1 MALDI-TOF spectrum of trypsin-digested peptide with ion mass

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3. Adjust the baseline threshold prior to the experiment to avoid noise signal in the MALDI spectrum. 4. Note: When the spectrum is generated with the high resolution (reflectron), then the signal raised from the digested peptides will have peaks separated by 1 Da. 3.9 Parameters to Be Filled in MASCOT Search Engine

The MASCOT search engine works on the probability-bases MOWSE algorithm to retrieve a significant protein of match. This algorithm helps in judging the significant score of match protein. In addition, the score of both MS/MS and MALDI-TOF is analyzed in the same protocol. The scores for searches from different databases can be easily compared in MASCOT. Thus, this algorithm has various advantages than the simple cut-off method. 1. Begin the search by opening the MASCOT search engine (http://www.matrixscience.com/cgi/search_form.pl? FORMVER¼2&SEARCH¼PMF). 2. Click the Peptide Mass fingerprint search forum (Fig. 2). 3. Use this forum to identify the protein sequence. 4. The forum needs the details as follows.

Fig. 2 MASCOT search engine system showing the peptide mass fingerprint forum

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5. Name: Type your name/nickname. 6. Email: Provide original email address. This helps the MASCOT host to send the search result link to your email inbox (if the search gets disconnected). 7. Search title: Provide some description for your search, e.g., Actinobacteria. 8. Database: Click the database specific to search against your query, e.g., Choose NCBInr, Swiss Prot, etc. 9. Taxonomy: Click the taxonomical options provided in the list. This helps to restrict your search against a particular species. For instance: All entries or eubacteria or Actinobacteria class, etc. 10. Enzyme: Select the enzyme used to digest the protein into peptides, e.g., trypsin. 11. Missed cleavage: Generally, the sample is partially digested. Thus increasing the number of missed cleavage enhances the probability of identifying missed cleavage in sample. Select the missed cleavage allowed up to 1 or 2. 12. Fixed and variable modifications: This allows the user to provide the details of chemical modifications present in the N- and C-terminal of amino acids. Select carbamidomethyl (C) for fixed modification and oxidation (M) for variable modification. 13. Protein mass: When the user characterizes an unknown protein/peptide then the box can be left empty. In case of known protein, the exact mass should be provided in the box, e.g., 90 kDa. 14. Peptide tolerance: This provides information about the ability of instruments accuracy on the samples’ peptide mass. Use 0.1 to 1.2 Da. 15. Mass values: This aids the user to choose whether the mass is reported for the charged proton (MH+) or not (Mr). Click MH+. 16. Monoisotopic/average: The recent mass spectrometer instruments have the potential to resolve the different isotope peaks of peptides. Hence click monoisotopic. 17. Data input: This contains the options such as data file and query. The data file option aids the user to upload the ion mass peak file saved elsewhere in the system (D:/MALDITOF/Actinobacteria/spot21) corresponding to the peptide. In case of query, the extracted ion masses from the MALDITOF spectra should manually be provided in the given box. 18. Report top: This helps to provide a command on the number of hits to be retrieved/displayed, e.g., 5, 10, 20, etc.

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Fig. 3 Mascot result showing the best matched proteins 3.10 MASCOT Result for PMF Against Actinobacteria Class

1. The mascot report shows a top score of 39 for ribosomal protein (Fig. 3). 2. However the significance of the protein match depends on the query coverage of the result. Here the query coverage for ribosomal protein is 23% (Fig. 4). 3. Thus the identified protein is considered. 4. Note: If the molecular weight and pI of the significantly matched protein match with the gel, then the result can be considered. 5. Note: In General, if the bar falls in the shaded area of MASCOT score graph, it would be considered as an insignificant hit. However, one should not ignore in cases if it satisfies the abovementioned protein identification criteria.

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Fig. 4 Mascot result showing the mascot score, query coverage, and protein sequence of the matched protein References 1. Webster J, Oxley D (2009) Protein identification by peptide mass fingerprinting using MALDI-TOF mass spectrometry. In: Walker JM (ed) The protein protocols handbook. Humana Press, Totowa, NJ, pp 1117–1129 2. Stanier RY, Palleroni NJ, Doudoroff M (1966) The aerobic pseudomonads: a taxonomic study. J Gen Microbiol 43:159–271 3. Manteca A, Jung HR, Schw€ammle V, Jensen ON, Sanchez J (2010) Quantitative proteome analysis of streptomyces coelicolor nonsporulating liquid cultures demonstrates a complex differentiation process comparable to that occurring in sporulating solid cultures. J Proteome Res 9:4801–4811 4. Manteca A, Fernandez M, Sanchez J (2006) Cytological and biochemical evidence for an early cell dismantling event in solid cultures of Streptomyces antibioticus. Res Microbiol 157:143–152

5. Chen Y, Ntai I, Kou-San J, Unger M, Zamdborg L, Robinson SJ, Doroghazi JR, Labeda DP, Metcalf WW, Kelleher NL (2012) A proteomic survey of nonribosomal peptide and polyketide biosynthesis in Actinobacteria. J Proteome Res 11:85–94 6. Mali S, Mitchell M, Havis S, Bodunrin A, Rangel J, Olson G, Widger WR, Bark SJ (2017) A proteomic signature of dormancy in the actinobacterium Micrococcus luteus. J Bacteriol 14:e00206–e00217 7. Mare´chal PL, Decottignies P, Marchand CH, Degrouard J, Jaillard D, Dulermo T, Marine Froissard M, Smirnov A, Chapuis V, Virolle M (2013) Comparative proteomic analysis of streptomyces lividans wild-type and ppk mutant strains reveals the importance of storage lipids for antibiotic biosynthesis. Appl Environ Microbiol 79:5907–5917

Chapter 37 Protocols for Preclinical Evaluation and Molecular Docking of Antimicrobial Compounds from Streptomyces sp., Drug Likeliness Evaluation, ADME-Toxicity Investigation, Docking Modes Between the Ligand and the Target Enzyme, and Active Site Prediction B. K. Anirudh Sreenivas, B. Akshaya, Lokesh Ravi, and Kannabiran Krishnan Abstract Streptomyces is the largest genus of actinobacteria which are gram positive and resemble fungi because of their colonies. These organisms are known for their complex metabolism and their secondary metabolites. These secondary metabolites are currently in the limelight with respect to industrial and commercial applications as antimicrobials. They produce many novel secondary metabolites and new chemical entities which are very effective against bacteria and drug-resistant pathogens as well. Characterizations and studies on these metabolites have gained momentum in recent years. In silico approaches are used quite often to study the efficacy of these compounds against microbial protein targets. In this chapter protocols to be used for various in silico studies such as binding site prediction, pharmacokinetics and molecular docking through CASTp web server, SwissADME tool, and Autodock 4.2 analysis are given. Key words Secondary metabolites, In silico, Binding site, Pharmacokinetics, Molecular docking, SwissADME tool

1

Introduction Streptomyces is the largest genus of actinobacteria and are known to be the most dominant source for bioactive metabolites. They produce almost half of the naturally occurring antimicrobials and continue to be the source for new bioactive compounds [1]. These novel antimicrobials are essential for the diagnosis and treatment of microbial diseases and to effectively manage the threat of antimicrobial resistance. It is the need of the hour to identify new bioactive compounds and new chemical entities to meet the

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_37, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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increasing demand for industrial and pharmaceutical applications [2, 3]. In silico approaches using easily accessible databases and tools have gained pace in recent years owing to their efficiency and lower time requirements. Drug discovery and target optimization are the main components of early pharmaceutical research [4]. Preclinical evaluation of chemical candidates is one such component in drug discovery where the formulations, physicochemical and pharmacokinetic properties are studied [5]. Drug-likeliness is also studied based on the bioavailability of the molecules. Lipinski’s rules are the main points of consideration with respect to drug discovery [6]. In silico studies using protein molecules are also carried out to study their characteristics. The process called target identification is done through various processes including similarity search, homology modeling, and molecular docking to predict specific targets for small molecule ligands [7]. This chapter deals with protocols used for the preclinical evaluation of chemical compounds isolated from Streptomyces sp., active site predictions, and molecular docking to identify best interacting molecules. The online tools and servers required for the prediction of binding sites and preclinical evaluation of lead molecules are discussed.

2

Materials 1. Protein structure in .pdb format. 2. Protein sequence in .fasta format. 3. Ligand structure in .pdb format. 4. Ligand structure in SMILES format. 5. Autodock 4.2 software. 6. UCSF Chimera molecular visualization software.

3

Methods

3.1 SwissADME Analysis

1. SwissADME is an online server which predicts the Adsorption, Distribution, Metabolism, Excretion, and the Toxicity (ADMET) of a drug molecule. 2. This tool also predicts the drug-likeness property, physicochemical property, lipophilicity, and water solubility for the molecule of interest, and these properties are important to classify the molecule as a drug. 3. This server predicts the simple molecular and physicochemical properties of the molecule including the molecular weight, molecular refractivity count of specific atom types, and polar surface area (PSA) with the OpenBabel9, version 2.3.0.

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4. The polar surface area is calculated through a technique called topological polar surface area (TPSA) that considers sulfur and phosphorous as polar atoms [8]. 5. Lipophilicity of the molecule is predicted via the partition coefficient between n-octanol and water (log Po/w). 6. This tool uses many models including XLOGP3, WLOGP, MLOGP, SILICOS-IT, and iLOGP values to predict the lipophilicity with better efficiency. 7. Water solubility is also predicted by the tool through three well-known models, and the predicted values are the decimal logarithm of the molar solubility in water (log S). 8. The pharmacokinetics–ADMET analysis of the molecule is achieved by subjecting the molecule to various predictions. The tool predicts the gastrointestinal adsorption as well as the Blood Brain Barrier permeation capability of the molecule through the Brain Or IntestinaL EstimateD permeation method (BOILED-Egg) predictive model that works by computing the polarity and lipophilicity of the molecule [9]. 9. SwissADME also predicts if molecules are substrates of P-gp or inhibitors of the most important CYP isoenzymes which may lead to unfavorable pharmacokinetic drug-drug interactions leading to some toxic effects. 10. Additionally, this tool predicts the skin permeability coefficient (Kp) which is also based on the molecular size and the lipophilicity of the molecule. A greater negative value of Kp correlates to a lower skin permeability. 11. The “Drug-likeliness” prediction allows assessing the molecules probability to qualify as an oral drug based on the bioavailability of a molecule. 12. The Lipinski’s rule of five is a major consideration for the prediction of drug-likeness [6]. The Ghose (Amgen), Veber (GSK), Egan (Pharmacia), and Muegge (Bayer) methods are also considered for effective prediction. 13. The Abbott bioavailability score is also predicted based on the oral bioavailability score in rats and also on the Caco2 permeability. 14. This tool also supports medicinal chemistry predictions, the chemical descriptions of problematic fragments in a molecule for prediction of drug-likeliness. 15. It also predicts the lead likeliness of a molecule based on which re-design or scaffolding can be done to improve the molecules efficiency [10]. 16. To predict the drug-likeness and the ADMET pharmacokinetic properties of a molecule, draw the structure of the ligand in the

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Fig. 1 Flowchart representing the procedure to perform the pharmacokinetic and drug-likeness study through SwissADME

area provided and click on the central button to convert it into the SMILES format. 17. The SMILES format of the molecule if known can also be pasted directly. Click on the search button to start the predictions. 18. Results, once ready, will be displayed in the same page. To retrieve the results as a CSV file, click on the option provided on top of the results. 19. To copy-paste into an excel sheet use the option next to the download as CSV file. 20. A step-by-step flowchart for pharmacokinetic and druglikeliness analysis through SwissADME is shown in Fig. 1. 3.2

CASTp Analysis

1. CASTp is a web server which provides users with accurate information on the topography of proteins. 2. This server is one of the best servers to predict the pockets of the protein which is a basic step in active site prediction. 3. The server uses the alpha shape method developed in computational geometry to identify the topographic features, to measure the area and volume, and to compute the imprint for a protein of choice. 4. This server identifies all the surface pockets, interior cavities, and cross channels in a protein structure and provides detailed description of all the atoms participating in the same. It also measures all the exact volumes and areas as well as mouth opening if any.

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5. These predictions are calculated based on the solvent accessible surface model (also called Richard’s surface) and molecular surface model (also called Connolly’s surface). 6. The results can be downloaded directly and viewed through the UCSF Chimera [11] or through the PyMOL plugin downloadable from the server [12]. 7. Based on the predictions of the web server, a suitable pocket can be chosen as an active site for the protein either based on literature or based on the co-crystallized ligand data available on the PDB. 8. To predict the binding pockets of the protein, open the calculations on the web server. Click on the browse option and select the protein of interest in .pdb format. The radius probe is always set to default but it can be changed accordingly. Add the E-mail address if required and click on the submit button. A link is displayed which leads to the results page. 9. Once the predictions are done the results are displayed. These results must be downloaded as a compressed file. Open the .poc file in UCSF Chimera molecular viewer to view the results of the prediction. 10. Figures 2 and 3 represent the procedure to be followed to predict the binding pockets through the CASTP web server and view the results through Chimera respectively.

Fig. 2 Procedure to predict the binding pockets of a protein through the CASTp web server

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Fig. 3 Procedure to open and view the results through the Chimera Molecular Viewer 3.3

AutoDock 4

1. Molecular Docking is a computational method used to predict the binding capabilities of a ligand on the target protein. 2. The interaction between the target protein and the ligand is measured through the prediction of binding energy, and this is used for the classification of ligands. 3. Autodock 4.2 is the software that is used for molecular docking, i.e., docking of the ligand with the target protein [13]. 4. AutoDock combines an empirical free energy force field with a Lamarckian Genetic Algorithm for fast prediction of bound conformations with predicted free energies of association [14]. 5. AutoDock 4.2 tool is currently being distributed free of charge as open source under a GPL license at the site: http:// autodock.scripps.edu. 6. ADT is also being distributed free of charge as part of the MGL tools package at the site: http://mgltools.scripps.edu/ downloads. 7. The results of the Autodock 4 software is obtained by following the 5 major steps: (a) Preparation of the protein and the ligand file. (b) Initializing the protein and ligand. (c) Running Autogrid. (d) Running Autodock. (e) Analyzing the results. 8. The first step of the procedure is to prepare the protein and the ligand file for docking. Open the protein structure file (in .pdb format) using a text editor. All the lines starting with “HETATM” and “CONNECT” are need to be deleted and the last line of the file should have “ter” followed by alphanumeric codes. Once the pdb file is edited, save it in the workfolder. Retrieve the ligand of choice in any Autodock recognizable file formats.

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9. Initializing the molecule is the second step of the protocol and starts by opening Autodock and loading the protein molecule. Set the molecule view to ribbon or surface view. To add hydrogens to the protein molecule, go to the edit tab and click on add hydrogens. Select the polar only option from the window. Merge the nonpolar hydrogens in the next step. To perform this step, select the edit tab and go to hydrogens from the dropdown list and select the merge nonpolar option. This is followed by initializing the protein molecule to add the Kollman charges. To add these charges, go to the edit tab again and select the charges option and add the Kollman charges. To save the changes made, select the file option and go to save and click on the write PDB option. Check the tick box next to short nodes in the pop-up window and save the molecule to overwrite the old one. 10. Similarly, open the ligand molecule by choosing the ligand tab and select the input option. To save as Autodock ligand, select the ligand option again and click on output, and save the ligand in the pdbqt file format. 11. The third step of the protocol is to set the gridbox and run Autogrid. To do this, go to the grid option and then macromolecule option—select and save the protein as macromolecule. Similarly, go to the grid option again and select the ligand molecule. Next, go to the grid option again and select gridbox. Set the dimensions of the box accordingly and click on files. Select the option close saving current. Finally, go to the grid option again and click on save and save the file as grid.gpf. 12. The next step is to run Autogrid. To do this step, go to the run option and select Autogrid. Select the parameter file as grid.gpf and select the program pathname as Autogrid4.exe. The log file name fills automatically. Click on the launch option and wait for successful completion. 13. The fourth and the most important step is Running the Autodock where the interaction energy predictions are made by the software. For this go to the docking option and choose the macromolecule. Click on set rigid filename and save the protein in pdbqt format. In the same way select and choose the ligand for docking. Go to the docking option again and click on search parameter to select the genetic algorithm. Perform the similar steps to set the docking output to Lamarckian GA and finally save the file as dock.dpf. To continue and run Autodock, go to the run option and select Autodock. 14. In the new window select the pathway parameter as Autodock4.exe. Select the parameter filename as dock.dpf and wait for the log filename to autofill. Click on the launch option and wait for completion.

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15. The final step of the protocol is to analyze the docking results. For this go to the analyze option and open the dock.dlg file. Set a new name to the ligand and click on ok. Go to the analyze option again and select conformations. Select the play, ranked by energy option. Then click on the option and to set the play option, check the build H-bonds and show info options. Finally, click on the build current and write complex option and save the results as result.pdb.

References 1. Be´rdy J (2005) Bioactive Microbial Metabolites. J Antibiot (Tokyo) 58:1–26 2. Demain AL, Sanchez S (2009) Microbial drug discovery: 80 years of progress. J Antibiot (Tokyo) 62:5–16 3. Roca I, Akova M, Baquero F et al (2015) The global threat of antimicrobial resistance: science for intervention. New Microbes New Infect 6:22–29 4. Terstappen GC, Reggiani A (2001) In silico research in drug discovery. Trends Pharmacol Sci 22:23–26 5. Khurshid Ahmad MH (2014) Drug discovery and in silico techniques: a mini-review. Enzym Eng 04:1–3 6. Lipinski CA, Lombardo F, Dominy BW et al (2001) Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliv Rev 46:3–26 7. Katsila T, Spyroulias GA, Patrinos GP et al (2016) Computational approaches in target identification and drug discovery. Comput Struct Biotechnol J 14:177–184 8. Ertl P, Rohde B, Selzer P (2000) Fast calculation of molecular polar surface area as a sum of fragment-based contributions and its

application to the prediction of drug transport properties. J Med Chem 43:3714–3717 9. Daina A, Zoete V (2016) A BOILED-egg to predict gastrointestinal absorption and brain penetration of small molecules. ChemMedChem 11:1117–1121 10. Daina A, Michielin O, Zoete V (2017) SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Sci Rep 7:42717 11. Pettersen EF, Goddard TD, Huang CC et al (2004) UCSF chimera--a visualization system for exploratory research and analysis. J Comput Chem 25:1605–1612 12. Tian W, Chen C, Lei X et al (2018) CASTp 3.0: computed atlas of surface topography of proteins. Nucleic Acids Res 46:W363–W367 13. Morris GM, Ruth H, Lindstrom W et al (2009) Software news and updates AutoDock4 and AutoDockTools4: automated docking with selective receptor flexibility. J Comput Chem 30:2785–2791 14. Docking AJA, Autodock AJ, Morris GM et al (1998) Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function. J Comput Chem 19:1639–1662

Chapter 38 Energy-Based Pharmacophore Hypothesis Combined with Molecular Simulation Protocol for the Screening of Bioactive Compounds from the Class of Actinobacteria Muthu Kumar Thirunavukkarasu and Ramanathan Karuppasamy Abstract Bioactives derived from the actinobacteria family is the better resource for developing pharmaceutical drugs. In particular, Streptomyces are the major source for the antibacterial, antitumor, and immune suppressive agents. Importantly, the bacterial species reason for the development of about two-thirds of all recognized natural inhibitors including cancer treatment. Despite the attempts to produce new antibiotics, antibacterial resistance tends to develop too rapidly. To keep pace with drug discovery and to facilitate nature inspired drug discovery paradigm, we aimed to provide high precision computational protocol with the aid of 2000 secondary metabolites of various Streptomyces species from KNApSAcK repository. Note that energy-based pharmacophore screening protocol was highlighted to extract the potential active molecules against target of therapeutic importance. Further, glide docking and molecular simulation processing steps were also detailed and their application in searching of ligand molecules is highlighted. Hopefully these high-standard virtual screening protocols can aid in screening of nature inspired bioactive compounds to combat emerging drug-resistance scenario. Key words Actinobacteria, Secondary metabolites, Virtual screening, Molecular docking, Molecular dynamics

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Introduction The actinobacterial strains are greatly studied due to its capacity of extensive secondary metabolites production. In particular, Streptomyces genus is responsible for nearly 45% of currently marketed drugs [1]. Streptomyces are the Gram-positive bacteria and have high amount of G and C contents in their DNA. The strains isolated from the traditional source have been central to the development of essential bioactive metabolites such as antimicrobial and anticancer drugs [2]. The scientific evidences indicate that around 500 distinct Streptomyces species and millions of isolated strains are accountable for an

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_38, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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extraordinarily diverse selection of secondary metabolites derived from multiple synthesis routes. For instance, one of the well-known metabolite Amrubicin which is a derivative of doxorubicin extracted from Streptomyces peucetius var. caesius potentially acts against lung cancer cells [3]. Elsamitrucin is another notable drug isolated from Streptomyces chartreusis and produces an antitumor effect by inhibiting topoisomerase II in some of the cancer types [4]. Numerous literature evidence highlights that the bioactive compounds extracted from actinomycetes displayed a wide range of antimicrobial activity toward Gram-positive and Gram-negative bacteria [5, 6]. Nevertheless, the production of multi-drug resistant pathogens has raised the rates of infection in humans. In particular, the highest risk of death is associated with ESKAPE infections, contributing to the higher health care costs [7]. Moreover, severe toxic effects and lower selectivity of the existing drugs limit the medical practices in many disease types, which necessitates the development of nature inspired compounds [8]. Also, the undiscovered properties of actinobacterial metabolites remain concern for the next generation drug development process [9]. Therefore, we documented energy-based virtual screening strategies to explore the outstanding potential of bioactive compounds extracted from different actinobacterial species to overcome the drug-resistance patterns. A technique of e-pharmacophore incorporates the strengths of both structural and ligand-based drug design and can be used to scan ligands using similar pharmacophore properties [10]. Moreover, molecular docking and molecular dynamic (MD) simulation steps were demonstrated to discriminating the lead compounds from the group of active molecules. We are hoping that these virtual screening protocols might be helpful in the selective drug discovery for the treatment of many disease types.

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Materials The following are the list of instruments and packages necessary to carry out the given protocol with high precision. 1. Ubuntu 14.0 or higher version. 2. Schrodinger packages (PHASE & Glide). 3. Gromacs packages version 5.1.2. 4. High end workstation with minimum of 4 core processor. 5. High-speed internet connection.

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Methods In this section, a comprehensive protocol is provided that specifically directs the researcher to carry out energy-based virtual screening process for the identification of potential lead compound against specific target. Each programs carried out in this study will be based on the protocols provided by the respective developers. The necessary steps to be carried out for the virtual screening and MD simulation studies were also highlighted here. Among the various available algorithms, Schro¨dinger and Gromacs packages were used here to process virtual screening and dynamic simulation studies, respectively.

3.1 Retrieval of Dataset

Structural information on protein recovery is the preliminary step of drug discovery process. The main source is the direct retrieval of structural details which are from the protein data bank (PDB) (http://www.rcsb.org/). In the absence of structural availability, the researcher could utilize the power of modeling techniques to predict the required protein structure. The detailed explanation of structure prediction is explained in this research article [11]. Here, three-dimensional structure of human mitogen-activated protein kinase (MEK) was downloaded by searching the four letter pdb id (PDB ID: 3W8Q) into the search box of protein databank website and used in our analysis. Eventually, the structural information of ligands were download from the vast number of sources. For instance, PubChem, DrugBank, and other publically available websites. Although nature inspired compounds are distributed across the web, few repositories such as NPACT, KNApSACK, StreptomeDB, and Super Natural II are dedicated for immediate retrieval of the bioactive compounds. In all these cases, the ligand structures are usually downloaded in 3D SDF (Structured file format) file format. Open Babel an open source application may be utilized to translate the compound structure into the program required file format.

3.2

Data cleaning is the first and foremost steps to be performed in all the computational analysis to overcome the structural defects. The necessary steps for processing the dataset by using Schro¨dinger packages were detailed here.

Dataset Cleaning

1. Retrieved protein structure was imported into the maestro workspace by using “import structure” option available under the file tab. 2. Then click “preprocess” without changing any parameters in the “protein preparation wizard” of Schro¨dinger suite. 3. Review and modify tab in the wizard used to remove the additional chains and cofactors of small molecules present in

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the protein by simply clicking and deleting the name of the atoms/chain. 4. Finally, refine tab in the preparation wizard optimize and minimize the protein structure with the default constrains. 5. Similarly, the 3D configuration of the ligand molecules was transmitted to the maestro workspace, and the ligand preparation module such as “LigPrep” was implemented with default criteria [12]. 3.3 Receptor Grid Generation

Receptor grid used to specify the active site residues for the effective binding of ligand molecules to the target receptor. Prior to grid generation, the best active site was identified through sitemap module. 1. The minimized protein structure will be included into maestro workspace for executing the site map process. 2. Then find the sitemap function in the task section. And click run. The sitemap algorithm visualizes the binding pocket using the following scheme. Red color surfaces represent the hydrogen bond acceptor, blue color represents the hydrogen bond donor, and the yellow color represents the hydrophobic residues. The example binding site was represented in Fig. 1. 3. The parameters such as pocket volume, size, phobic, philic, balance, hydrogen bond donor, and acceptor ratio will be

Fig. 1 Active site present in the target receptor

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available for the user to select the best binding pocket in the given structure. 4. In majority of the cases, the survival score provided by the sitemap module can be utilized in selecting the appropriate binding site. 5. Further, the grid box was generated using the “Receptor Grid Generation” panel available in the maestro tasks. 6. During the grid generation process, the grid was framed around the best active site by clicking the atoms present in the site. 7. Together with default scaling factors and site parameters the grid generation process can be accomplished. 3.4 e-Pharmacophore Model Generation

Energy-based pharmacophore modeling produces energetically configured pharmacophores that can be used for screening large library. Here, PHASE module was used to generate the e-pharmacophore model hypothesis. PHASE module established the pharmacophore moieties using optimum energy terms produced during the interaction of protein-ligand complexes [13]. In order to generate the interactions between receptor and ligand molecule, Glide XP docking was performed. The detailed procedure to perform the e-pharmacophore model generation was explained here. 1. Initially, the prepared protein and ligand molecules were incorporated into the maestro project table. 2. The docking process can be initiated by clicking on the “ligand docking” panel which is available in the maestro tasks. 3. Choose the compressed form of grid file from the “Receptor grid” menu using browse option followed by selecting the ligands present in the project table. 4. Then XP (extra precision) docking could be picked up by clicking the precision dropdown available in the setting tab. 5. It is important to check the “Write XP descriptor information” box to create energy descriptors for model generation. 6. Finally, the pose viewer file included with receptor molecule will be retrieved as a result of XP docking by clicking the pose viewer file option in the output tab. 7. The example result of XP docked molecules with the target receptor were shown in Fig. 2. 8. The receptor and ligand molecules were included into the maestro workspace from pose viewer file generated during the XP docking studies.

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Fig. 2 Docking pose of reference inhibitors with target protein

9. “Develop pharmacophore model generation” tool (Fig. 3) available under the PHASE module used to develop the e-pharmacophore hypothesis. 10. For the e-pharmacophore model generation choose the “receptor–ligand complex (Workspace)” option from the dropdown menu present in the model generation tool. 11. The automatic e-pharmacophore model generation will be carried out to minimize the handling error during the analysis. 12. Then, select the all reference inhibitors for the model generation using “choose ligand option” in the aforementioned tool. 13. On a completion of e-pharmacophore model generation, the pharmacophoric features (Fig. 4) will be incorporated into the maestro workspace. 14. Altogether, the hypothesis generated by PHASE module contains six pharmacophoric features such as (A) hydrogen bond acceptor, (D) hydrogen bond donor, (H) hydrophobic group, (N) negatively ionizable region, (P) positively ionizable region, and (R) aromatic ring [14]. 3.5 Validation by Enrichment Analysis

It is essential to carry out an enrichment analysis during the e-pharmacophore model generation as it highlights the accuracy of the virtual screening process. This can be accomplished by the following steps. 1. Import the Schro¨dinger decoy set containing 1000 in-active molecules into maestro project table using “import structure” option. Followed by import the 3D structure of known MEK inhibitors in order to define the active molecules.

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Fig. 3 Develop pharmacophore model generation panel

2. Further, the compound screening will be achieved by right clicking the “H” icon followed by “Add to the database screen” option available on the right side of hypothesis entry (Fig. 5). 3. Select both the active (known inhibitors) and in-active (decoy set) molecules for the screening analysis. 4. On a completion of the screening, the resultant compounds will be incorporated in the project table based on the rank order given by PHASE module. 5. Later, initiate the validation process by clicking the “Enrichment calculator” panel (Fig. 6) available in the task section. 6. The compounds from screening results will be used as an input source for the enrichment analysis and a total of known inhibitors could be given in the place of “active file” section. 7. The successful completion of enrichment analysis, the enrichment factors (EH), ROC (Receiver operating characteristic) plot, and other parameters will be visualized in the enrichment

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Fig. 4 e-pharmacophore model hypothesis generated by PHASE module

calculator panel and the associated log file will be generated in the working directory. 8. The accuracy of model could then be visualized in terms of ROC plot as shown in Fig. 7. 3.6 PHASE Database Screening

PHASE screening provides a set of active molecules which shares the similar energy terms to that of generated e-pharmacophore hypothesis. Here, we use the compounds from KNApSAcK core system for the screening of potential actinobacterial metabolites against the target receptor. KNApSAcK Core system is an important source for the recovery of the secondary metabolites data

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Fig. 5 Database screening option from the generated hypothesis. Red circle highlighted the “H” icon used for screening the database

Fig. 6 Enrichment calculator panel

corresponding to the organism of interest (http://www. knapsackfamily.com/) [15]. A complete set of protocols for phase database screening were described here. 1. The SMILES information of actinobacterial secondary metabolites will be retrieved from the KNApSAcK core system.

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Fig. 7 Receiver operating characteristic curve corresponds to the generated e-pharmacophore model

2. Online SMILES Translator and Structure File Generator tool (https://cactus.nci.nih.gov/translate/) used to convert the SMILES information of compounds into 3D SDF (structured file) format. 3. Later, import the downloaded compounds into the maestro project table. 4. Subsequently, the database screening could be implemented for the set of 2000 compounds by using the generated e-pharmacophore model (Highlighted in Subheading 3.4). PHASE screening also adopts the similar protocols as mentioned in Subheading 3.5. 5. Note that prior to phase database screening the compounds should be prepared using the “LigPrep” module. 6. This process will provide a set of active compounds from the library of molecules. The resultant molecules automatically incorporated into a maestro project table for further analysis. 3.7 Lead Optimization

Although PHASE screening provides the list of active compounds, molecular docking and MD simulation studies is a way to benchmark the compounds activity against the target of interest. The researchers may also utilize MM/GBSA calculations or simulation studies to enrich the resultant compounds activity. Here we provide brief description about molecular docking and dynamic studies to support the research community.

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Molecular docking is one of the finest method to eliminating the non-binding ligand molecule from the larger data set. Here we proposed Glide docking protocols to score the ligand molecules based on the binding affinity values. 1. In order to perform the molecular docking analysis, find the “ligand docking panel” available under glide module in the maestro tasks. 2. After that select the “project table (selected entries)” option from the dropdown menu available in the ligands tab in the ligand docking panel. 3. Then define the ligand molecules by selecting entry of screened hit molecules from the project table. 4. Followed by click the settings tab for choosing the precision of docking procedure. Three-tier docking available in the glide module is shown in Fig. 7. For instance, HTVS (high throughput virtual screening), SP (standard precision), and XP (extra precision) order is preferred choice for screening large libraries. Note: If the library consists of few hundreds, researcher can select XP precision in the initial stage itself. 5. In the output tab, choose the pose viewer file type as an output format and click run to initiate the molecular docking analysis. 6. The results can be examined either by glide energy or by glide XPg score.

3.7.2 MD Simulation Studies

The binding affinity analysis through molecular docking provides the superficial outcome of the ligand activity. The deeper insights of ligand behavior can be identified through MD simulation studies. Although high computing power limits it usage, MD study is more important in prediction of the actual circumstance of the ligand molecules against the target receptor. The necessary steps for carrying out MD simulation process using Gromacs packages were highlighted here. 1. The MD simulation of protein-ligand complex needed topologies of both protein and ligand molecules. 2. Gromacs does not produce the topology for the unknown ligand molecules. Hence, we advise the reader to generate the ligand topologies using any external web servers. Here we provide the protocols for the generation of ligand topologies from PRODRG server [16]. 3. Paste the ligand sdf file under the “submit a molecule” window and click “Run PRODRG” to generate the ligand topologies. 4. Once the process completed, the compressed zip file will be downloaded.

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5. Find the “DRGAPH.GRO” and “DRGGMX.ITP” from the compressed output file and transfer into a working directory. The other files are not needed for the MD simulation process. 6. Eventually, the generation of protein topologies could be carried out using “pdb2gmx” tool in the Gromacs packages. 7. After the generation of protein and ligand topologies, combine the coordinates of ligand with the protein coordinates and add “DRG” in the topology file. These steps could be done by using simply paste the coordinates of ligands at the end of the protein coordinates and add the number of ligand atoms with the protein atoms. 8. After creating a topology file for the protein-ligand complex, set up the simulation box to execute the MD simulation. The simulation box can be solvated using number of water models. Here we provide SPC (simple point charge) water model to solvate the system. 9. Further, the charge of the system will be neutralized by adding counterions such as Na+ or Cl into the solvation box. 10. Process the energy minimization step to remove steric clashes raised inside the system. 11. Subsequently, generate the index file of protein-ligand complex to carry out the equilibration steps. 12. The system will be balanced at 1 bar pressure and 300 K temperature using NVT and NPT ensembles process, respectively. 13. Finally, MD simulation will be processed for the required time scale using the “.tpr” file. 14. The trajectory file will be used for the analysis such as RMSD, RMSF, hydrogen bond analysis, PCA and FEL, etc. The commands required for running the MD simulation using Gromacs were depicted in Fig. 8. Also, the detailed explanation of the step-by-step process for the MD simulation of protein-ligand complex was available in the following website (http://www. mdtutorials.com/gmx/complex/index.html). Overall, these high throughput screening protocols give the path to identify the potential lead compound against the target receptor. We assured that these protocols will help the experimental biologist to classify the possible bioactive molecule from the compounds library of any size.

Acknowledgments The authors thank VIT for providing “VIT SEED GRANT” for carrying out this research work.

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Generation of protein topology

Generation of ligand topology

gmx pdb2gmx -f 3w8q.pdb -o conf.gro -water spc

gmx pdb2gmx -f 3w8q.pdb -o conf.gro -water spc

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Generation of solvation box gmx editconf -f conf.gro -o newbox.gro -bt dodecahedron -d Adding counter ions (If the protein energy is positive) gmx genion -s ions.tpr -o solv_ions.gro -p topol.top -nname CL -nn 4

Adding counter ions (If the protein energy is negative) gmx genion -s ions.tpr -o solv_ions.gro -p topol.top -pname NA -np 4 Adding solvation ions gmx solvate -cp newbox.gro -cs spc216.gro -p topol.top -o solv.gro

Energy minimization gmx grompp -f em_real.mdp -c solv_ions.gro -p topol.top -o em.tpr gmx mdrun -v -deffnm em

Index file generation gmx genrestr -f drg.gro -o posre_drg.itp -fc 1000 1000 1000 gmx make_ndx -f em.gro -o index.ndx

Equilibration of the system gmx grompp -f nvt.mdp -c em.gro -p topol.top -n index.ndx -o nvt.tpr gmx mdrun -deffnm nvt gmx grompp -f npt.mdp -c nvt.gro -t nvt.cpt -p topol.top -n index.ndx -o npt.tpr gmx mdrun -deffnm npt

MD simulation gmx grompp -f md.mdp -c npt.gro -t npt.cpt -p topol.top -n index.ndx -o md_0_1.tpr gmx mdrun -deffnm md_0_1

Fig. 8 Flowchart for molecular dynamic simulation studies

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References 1. Law JW, Ser HL, Duangjai A, Saokaew S, Bukhari SI, Khan TM, Ab Mutalib NS, Chan KG, Goh BH, Lee LH (2017) Streptomyces colonosanans sp. nov., a novel actinobacterium isolated from Malaysia mangrove soil exhibiting antioxidative activity and cytotoxic potential against human colon cancer cell lines. Front Microbiol 8:877 2. Sivalingam P, Hong K, Pote J, Prabakar K (2019) Extreme environment Streptomyces: potential sources for new antibacterial and anticancer drug leads? Int J Microbiol 2019:1–20 3. Raja A, Prabakarana P (2011) Actinomycetes and drug-an overview. Am J Drug Discov Dev 1:75–84 4. Portugal J (2003) Chartreusin, elsamicin a and related anti-cancer antibiotics. Curr Med Chem Anticancer Agents 3:411–420 5. FSolanki R, Khanna M, Lal R (2008) Bioactive compounds from marine actinomycetes. Indian J Microbiol 48:410–431 6. DsMatsumoto A, Takahashi Y (2017) Endophytic actinomycetes: promising source of novel bioactive compounds. J Antibiot 70:514–519 7. GMulani MS, Kamble EE, Kumkar SN, Tawre MS, Pardesi KR (2017) Emerging strategies to combat ESKAPE pathogens in the era of antimicrobial resistance: a review. Front Microbiol 10:539 8. Mario Villela-Martinez L, Karen Velez-Ayala A, del Carmen L-SR et al (2017) Advantages of drug selective distribution in cancer treatment: Brentuximabvedotin. Int J Pharmacol 13:785–807 9. Dezfully NK, Hanumanthu N, Heidari A (2018) Streptomyces chartreusis strain ACTM-8 from the soil of Kodagu, Karnataka

state (India): isolation, identification and antimicrobial activity. Int J Pharm Chem Biol Sci 8:187–194 10. Veeramachaneni GK, Raj KK, Chalasani LM et al (2015) High-throughput virtual screening with e-pharmacophore and molecular simulations study in the designing of pancreatic lipase inhibitors. Drug Des Devel Ther 9:4397–4412 11. Mishra S (2013) Fundamentals of homology modeling steps and comparison among important bioinformatics tools: an overview AkanshaSaxenaHalberg hospital and research center, civil lines, Moradabad 244 001, UP, India Rajender Singh Sangwan central Institute of Medicinal and Aromatic Plants, near Kukrail picnic spot, PO CIMAP, Lucknow 226 015, UP, India. Sci Int 1:237–252 12. Schro¨dinger Release 2017-4 (2017) LigPrep, Schro¨dinger, LLC, New York, NY, 2017 13. Preethi B, Shanthi V, Ramanathan K (2016) Identification of potential therapeutics to conquer drug resistance in salmonella typhimurium: drug repurposing strategy. BioDrugs 30:593–605 14. Anju CP, Subhramanian S, Sizochenko N et al (2019) Multiple e-pharmacophore modeling to identify a single molecule that could target both streptomycin and paromomycin binding sites for 30S ribosomal subunit inhibition. J Biomol Struct Dyn 37:1582–1596 15. Afendi FM, Okada T, Yamazaki M et al (2012) KNApSAcK family databases: integrated metabolite–plant species databases for multifaceted plant research. Plant Cell Physiol 53:e1 16. Schu¨ttelkopf AW, Van Aalten DM (2004) PRODRG: a tool for high-throughput crystallography of protein–ligand complexes. Acta Crystallogr D Biol Crystallogr 60:1355–1363

Chapter 39 Receptor Cavity-Based Approach Combined with Autodock Protocol for the Screening of Antiviral Compounds from Streptomyces sp. Rohini K and Shanthi V Abstract Streptomyces sp., one of the vital member of Actinobacteria, is known for producing prolific bioactive metabolites. These diverse set of secondary metabolites possess a wide range of biological activities. Of note, numerous metabolites from different soil and marine sources have been reported to exhibit antiviral properties. Keeping this in mind, in the present chapter we have tried to explore the antiviral activity of Streptomyces derived metabolites especially against the neuraminidase protein of influenza virus. This is achieved by a robust technique of drug repurposing, which has been widely utilized to discover new indications for pre-existing drug molecules. Specifically, the computational strategies have turned out to be more effective as they proficiently determine most promising drug candidate for any indication. Therefore, in this chapter an integrated strategy of receptor cavity-based screening alongside docking analysis using Glide module and AutoDock tool have been employed to analyze the antiviral activity of the metabolites. Note that we have presented a brief protocol for performing this molecular simulation studies. Key words Streptomyces sp., Secondary metabolites, Antiviral, PHASE module, Receptor cavity-based pharmacophore model, Glide module, AutoDock tool

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Introduction The Actinobacteria constitute a discrete clade of Gram-positive bacteria, consisting of large variety of genera. This biological group encompasses many vital soil bacteria for decomposition, important antibiotic producers, and other buoyant species capable of growing in any harsh environments. Of all the members of this class, the best studied genus is Streptomyces. The members of this genus are extensively employed for producing prolific antibiotics [1]. The antibiotics produced have a broad spectrum of biological activities such as antibacterial, antiviral, antifungal, antiparasitic, anticancer, immunosuppressive, enzyme inhibitory and

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_39, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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diabetogenic [2]. Notably, antimycin, a novel actinomycete isolated from Streptomyces kaviengensis, displayed potent antiviral activity against a wide range of RNA viruses involving the Togaviridae, Bunyaviridae, Flaviviridae, Paramyxoviridae, and Picornaviridae families [3]. In light of this, the present chapter provides an overview of a computer-based drug repurposing strategy to explore the antiviral activity of compounds derived from Streptomyces species. The method of drug repurposing has gained limelight in the recent era, as it is cost efficient, labour saving and possesses lower risk of adverse outcomes [4]. The success stories of various repurposed drugs are reported in literature. Several virtual screening strategies have been employed to discover bioactive drugs molecules for the treatment of diseases. One such technique is pharmacophore-based screening strategy [5]. This strategy has the ability to efficiently screen potent drug molecules from large databases by reducing the computational load and time. In particular, the receptor cavitybased pharmacophore modeling employs better prediction accuracy to identify inhibitors specifically for orphan receptors [6]. Therefore, in this chapter, we will explore the protocol of receptor cavity-based virtual screening using the secondary metabolites derived from KNApSaCK database. Moreover, the hit molecules from the previous analysis are further validated using another docking tool, namely AutoDock.

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Materials Receptor cavity-based drug repurposing technique involves operating systems (OS) like Windows and Linux for the proficient use of software. Docking studies are performed using the Glide module and the AutoDock software to compute the binding free energies of the protein–ligand complexes. In particular, good internet connection and web browsers are prerequisite for utilizing different open source servers. Moreover, the required 3D structure of target protein and ligands are also retrieved from Protein Data Bank and PubChem database, respectively.

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3.1 Protein Preparation

The receptor cavity-based pharmacophore modeling requires a protein in PDB format. Therefore, the 3D structure of the target protein, neuraminidase (PDB ID: 3TI6, with a resolution of 1.69 Å), is retrieved from Protein Data Bank [7]. For this purpose, use “Get PDB” option available in Maestro package to download the protein. In order to remove any structural defects in the pre-existing 3D structure, protein preparation step is carried out.

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Fig. 1 Image of protein preparation wizard panel highlighting different sections available

1. Click the “Task” option available on the right side of the Maestro interface to access “Protein Preparation Wizard” panel of Schro¨dinger Suite. The protein preparation panel is shown in Fig. 1. Now to preprocess the protein structure click on the “Preprocess” option available in “Import and Process” section. 2. In the “Review and Modify” section, choose the heteroatoms which do not affect the protein function or conformation and click on the “Delete” button to eliminate them. 3. Another section available in the wizard is “Refine.” This section is employed to optimize and minimize protein using the OPLS (Optimized Potential for Liquid Simulation)-2005 force field. At first, click on the “Optimize” button for protein optimization. Further, to remove the water molecules less than 3 H-bonds to non-waters click the “Remove waters” button. Now keeping the default RMSD value of 0.30 Å, select the “Minimize” option. This step ultimately carries out restrained minimization ensuring that the heavy atoms converge to a RMSD value of 0.30 Å after the minimization process [8]. 3.2 Receptor Grid Generation

A receptor grid is generated for the prepared protein which specifically encloses the binding site of the protein structure. It is typically generated from the position of known ligand present in the crystallized structure of the protein. Here in the case of 3TI6 protein, the location of bound oseltamivir is considered for creating the grid. 1. This process is carried out using the “Receptor Grid Generation” tool present in the task bar. There are various advanced options available in the tool to create the grid. The panel is illustrated in Fig. 2.

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Fig. 2 Receptor grid generation panel

Fig. 3 Generated receptor grid enclosing the binding site

2. Select the “Run” option to generate a grid around the binding site of the protein by keeping all the options as default (see Note 1). 3. A zip file is finally generated in the working directory, containing all the relevant information about the receptor. The image of the generated grid is depicted in Fig. 3.

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Fig. 4 Panel for Phase database creation 3.3 Phase Database Creation

1. Prior to the screening process, a “Phase database” is created using the molecules retrieved from KNApSAcK database. This database comprises of list of metabolites that are associated with different taxonomic class [9]. Here for the present analysis, download the SDF file of 500 secondary metabolites selectively derived from Streptomyces sp. 2. Following the retrieval of molecules, a Phase database is created using the “Create Database” tool available in the task bar (Fig. 4). 3. Import the downloaded molecules in the Maestro interface. Next, to set up the “Database path,” click on “Browse” option. 4. In the “Create Phase Database” tool, select the “Prepare Ligand Structure” option at first. Other treatment involves conformer generation, stereoisomer generation, generating possible ionization state at neutral pH and removing highenergy ionization or tautomer states. Finally, in the “Ligand Filtering” section tick the “Generate QikProp properties” option to generate the ADME properties of the molecules. Additionally, to pre-filter the prepared ligands select the “Prefilter by Lipinski’s Rule” option. 5. Assign a job name and click on the “Run” option to create the Phase database. The created database can now be accessed from the assigned location.

3.4 Developing Pharmacophore Hypothesis

A receptor cavity-based screening approach is a powerful and flexible strategy to determine potential inhibitors for orphan receptors. It includes consideration of the essential chemical features present in the active site of the protein [6]. The following protocol is implemented to spawn a receptor cavity-based pharmacophore model.

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Fig. 5 “Develop pharmacophore model” panel for generating receptor cavitybased model

1. Select the “Develop Pharmacophore Model” panel from the task bar for running the process. 2. Initially, the dropdown box is set to “Receptor cavity (Workspace)” mode (Fig. 5). Subsequently, define the receptor binding site using the X, Y, and Z coordinates of the bound ligand present in the binding site of the target protein. Alternatively, the receptor can also be defined by specifying the centroid of the binding site residues.

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Fig. 6 Hypothesis settings dialog box

3. Now click on the “Hypothesis Settings” option to set the maximum number of features to be generated. Also, the minimum distance between two different features or same feature type can be changed according to the requirement. In the present analysis, hypothesis settings are kept as default and to save the settings click the “Save” button. The “Hypothesis Settings” panel is shown in Fig. 6. 4. Finally, assign a “Hypothesis Name” and click on the “Run” button to develop a pharmacophore model. This generated model is now used for screening process. Click on the “Add to database screen” option to screen the created database. The “Phase ligand screening” panel enables the user to select number of features to be obtained as matches from the total number of features generated. Also it allows to limit the number of matches as hits by changing the number in the output tab of the settings. The scrutinized hits are then available in the entry list. These hits are further carried for the virtual screening process using Glide module. 3.5 Virtual Screening Using Glide Module

Virtual screening is performed using the Glide (Grid-based LIgand Docking with Energetics) module of Schr€ odinger suite. It involves a three-step docking process, namely high throughput virtual screening (HTVS), standard precision (SP) and extra precision (XP) docking [10]. These scoring functions are in the increasing order of accuracy and complexity. The docking process utilizes the

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Fig. 7 Options available in “Ligand Docking” dialog box

molecules from phase screening along with the prepared receptor grid. The “Ligand Docking” option (Fig. 7) available in the task bar is used. Once again, various advanced choices can be stated, like the option of different scoring functions (HTVS, SP, XP, and SP-Peptide mode), constraints for protein-ligand, torsional constraints, etc. In addition to various scoring functions, the time consumed for docking each molecule is dependent on the flexibility and size of the ligand. 1. Initially, browse the receptor grid file from its location and select the hit molecules from the project table. 2. Under the “Settings” section, the precision for screening can be chosen. Here for the virtual screening process, a sequential docking process is performed, beginning with HTVS mode followed by SP and XP docking. All the other parameters in the tool are set as default. Finally, click the “Run” button to initiate the docking process. 3. The molecules possessing a docking score higher than the reference compound are carried forward to the consequent docking modes. Hence, by the end of XP docking process a set of molecules with better binding score than reference compound are obtained as hit molecules. 3.6 Docking Using AutoDock

The docking results generated from the Glide module is further validated using a docking freeware, namely AutoDock. This docking tool provides virtuous and precise prediction of small molecule interaction as well as gives higher association between experimental and predicted inhibitory activity [11]. Moreover, it employs Lamarckian genetic algorithm for conformational searching and uses a semi-empirical free energy force field to predict binding free energy. Its graphical user interface, AutoDock tools, assists in

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formatting target protein and small molecules. Additionally, it also facilitates in stipulating parameters, calculating miscellaneous charges, launching protein–ligand docking and analysis of docking results. The docking protocol is concisely described below. 1. The first step involved in docking is protein preparation. It is performed by retrieval of the target protein (3TI6: neuraminidase) from PDB database. Prior to protein preparation, the energy minimizes the protein using Swiss-PdbViewer (see Note 2) [12]. The preparation step mainly involves elimination of water molecules, securing the atom conformation by incorporating the nonpolar hydrogens and addition of AD4 atom types (see Note 3) and Gasteiger charges. Finally, save the prepared protein in “pdbqt” file format, where “q” represents partial charge and “t” represents AD4 atom types. 2. Second step is ligand preparation. For this process, download the ligands to be docked in its SDF file format. Now convert the existing file format to PDB file using OpenBabel (see Note 4) [13]. Subsequently, the PRODRG server is utilized to optimize the ligands (see Note 5) [14]. Once the ligand molecules are optimized, eventually prepare them using the same procedure as that of protein preparation. In addition, the torsional flexibility of the ligand is also set up. Finally, save the prepared ligand as “pdbqt” format. 3. The next step involves receptor grid generation. The active site residues information is obtained from the literature and is allocated in the protein molecule. The dimensions of x, y, and z axes are changed to generate a grid around the binding site residues (Fig. 8). Figure 9 shows the generated grid box enclosing the binding site residues. Subsequently, save the grid file in “.gpf” format. This file is now used as an input to run “AutoGrid.” AutoGrid efficiently pre-computes the grid maps of interaction energies for different atom types of ligand with the protein. These maps then help “AutoDock” to calculate the total interaction energy of a small molecule with protein. Consequently, write the output file in “.glg” format. 4. For running the AutoDock step, appropriate parameter should be chosen. The AutoDock tool comprises of four diverse search algorithms, namely genetic algorithm (GA), simulated annealing (SA), local search (LS), and Lamarckian genetic algorithm (LGA). Users can select appropriate algorithm as the docking parameter and save it in “.dpf” file format. This file is now used as an input for AutoDock run. Subsequently, save the output file in “.dlg” format. 5. The AutoDock generates coordinates for each conformation of the ligand and saves the information in the output file (.dlg) (Fig. 10). Other information on binding energies and

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Fig. 8 Grid options to generate grid box around the binding site residues

Fig. 9 Image illustrating the grid box generated enclosing the binding site residues

clustering are also generated in the output file. Preferably, the first docking pose with higher binding energy is considered as the best pose of protein-ligand complex. 6. The abovementioned docking process is repeated for all the screened hit molecules. The molecules with better binding affinity are then carried forward for further analysis.

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Fig. 10 Binding energy information of various conformation obtained from .dlg file

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Notes 1. The time taken for creating a receptor grid is highly dependent on the size of the protein. Thereby, for a regular sized protein with 5000–6000 atoms, this step typically requires 2–3 min. 2. Swiss-PdbViewer is used for the energy minimization of the target protein. It uses GROMOS 43B1 force field to fix the inaccurate geometrics of the downloaded protein and computes the energy of the structure. The target protein in PDB format is considered as the input file. Subsequently, the “Energy Minimization” option available in the visualization tool is employed to minimize the protein. The minimized protein is then saved in “.pdb” file format for further analysis. In addition, the energy of both the retrieved protein and minimized protein can be evaluated using the “Compute Energy” option. 3. The AutoDock tool comprises of AD4 atom types. These includes OA, SA, and NA for hydrogen bond accepting atoms, i.e., O, S, and N, respectively; HD for hydrogen bond donors, i.e., H atom; N for non-hydrogen bonding N atoms and finally A representing the C atom in planar cycle. For any other atom, its AD4 atom type is its same element. 4. OpenBabel is one of the downloadable Babel programs which has the ability to convert over 110 various chemical file formats. This chemical toolbox selectively screens and explores for

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molecular file utilizing SMARTS language along with other methods. 5. PRODRG server generates different topologies for the ligand of interest. It aids in the ligand structure amendment and energy minimization. The server accepts the input file in either SYBYL Mol2, MDL Mol, or PDB file formats. The optimized molecule can then be downloaded in various file formats. References 1. Barka EA, Vatsa P, Sanchez L, Gaveau-VaillantN, Jacquard C, Klenk HP, Cle´ment C, Ouhdouch Y, van Wezel GP (2016) Taxonomy, physiology, and natural products of Actinobacteria. Microbiol Mol Biol Rev 80:1–43 2. Berdy J (2005) Bioactive microbial metabolites. J Antibiot 58:1–26 3. Raveh A, Delekta PC, Dobry CJ, Peng W, Schultz PJ, Blakely PK, Tai AW, Matainaho T, Irani DN, Sherman DH, Miller DJ (2013) Discovery of potent broad spectrum antivirals derived from marine actinobacteria. PLoS One 8:e82318 4. Shaughnessy AF (2011) Old drugs, new tricks. BMJ 342:d741 5. Sun H (2008) Pharmacophore-based virtual screening. Curr Med Chem 15:1018–1024 6. Karthick V, Ramanathan K (2014) Computational investigation of drug-resistant mutant of M2 proton channel (S31N) against rimantadine. Cell Biochem Biophys 70:975–982 7. Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, Shindyalov IN, Bourne PE (2000) The protein data bank. Nucleic Acids Res 28(1):235–242 ˝ GM 8. Vass M, Schmidt E´, Horti F, Keseru (2014) Virtual fragment screening on GPCRs: a case study on dopamine D3 and histamine H4 receptors. Eur J Med Chem 77:38–46

9. Afendi FM, Okada T, Yamazaki M, HiraiMorita A, Nakamura Y, Nakamura K, Ikeda S, Takahashi H, Altaf-Ul-Amin M, Darusman LK, Saito K (2012) KNApSAcK family databases: integrated metabolite–plant species databases for multifaceted plant research. Plant Cell Physiol 53:e1 10. Friesner RA, Banks JL, Murphy RB, Halgren TA, Klicic JJ, Mainz DT, Repasky MP, Knoll EH, Shelley M, Perry JK, Shaw DE (2004) Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. J Med Chem 47:1739–1749 11. Forli S, Huey R, Pique ME, Sanner M, Goodsell DS, Olson AJ (2016) Computational protein-ligand docking and virtual drug screening with the AutoDock suite. Nat Protoc 11:905–919 12. Guex N, Peitsch MC (1997) SWISS-MODEL and the Swiss-Pdb viewer: an environment for comparative protein modeling. Electrophoresis 18:2714–2723 13. O’Boyle NM, Banck M, James CA, Morley C, Vandermeersch T, Hutchison GR (2011) Open babel: an open chemical toolbox. J Cheminformatics 3:33 14. Schttelkopf AW, van Aalten DM (2004) PRODRG: a tool for high-throughput crystallography of protein-ligand complexes. Acta Crystallogr D Biol Crystallogr 60:1355–1363

Chapter 40 Pharmacophore-Based Hypothesis Combined with Molecular Docking Protocol for the Screening of Anticancer Compounds from Streptomyces sp. Saranyadevi Subburaj, Priyanka Ramesh, and Shanthi Veerappapillai Abstract Actinobacteria is one of the prolific sources of bioactive metabolites with diverse structural complexity. In specific, streptomyces remains a concern for its unrivaled capacity to produce sustainable metabolites with a wide range of biological activities, including antitumor agents, antibiotics, and anti-infection agents. Recently, the need for the development of new drugs has been increased due to the emergence of new infectious diseases and drug resistance. Hence, computational strategy had gained attention in the field of drug discovery due to its ability to provide lead molecules with minimum cost and time. In particular, ligand-based pharmacophore approach revealed promising results in sorting huge libraries of biologically active compounds. Thus, we intend to provide pharmacophore-based screening protocol to facilitate the drug discovery pipeline. Moreover, this study provides novel insights in molecular docking and pharmacokinetic analysis of ligand molecules. Indeed, the highlighted work plan can be successfully employed for searching the bioactives from KNApSACK database, a comprehensive repository of streptomyces-based bioactives. Eventually, this protocol is of useful to speed up the drug discovery process and to tackle drug resistance. Key words Streptomyces sp., Anticancer, Pharmacophore, Molecular docking, ADME/T

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Introduction Actinobacteria, a Gram positive bacteria, is known for its extraordinary metabolic diversity and for their potential to produce a broad range of novel and impulsive bioactive metabolites. Moreover, these metabolites have higher therapeutic efficacy against an array of health disorders [1]. In specific, streptomyces is the prevalent and highly investigated genus of this phylum, which has made an excellent mark on history of pharmaceutical research [2]. These strains have the ability to generate many clinically significant bioactive molecules with diverse biological activities including anti-fungal, anticancer, anti-inflammatory, antibacterial, anti-parasitic, and

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_40, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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antioxidant activity [3]. It is reported that nearly 7600 bioactive compounds produced by over 500 streptomyces species are distributed across the world wide web [4]. For instance, the FDA approved drugs, daunorubicin and doxorubicin derived from Streptomyces species have been used for the treatment of cancer [5]. Other clinically validated antitumor drugs including aclarubicin, bleomycin, pentostatin, mithramycin, carzinostatin, etc. were also derived from the metabolites produced by the members of streptomyces species [6, 7]. However, multiple drug resistance (MDR), which is largely due to different defense mechanisms in patients, is the greatest threat to cancer care. Most of the developed MDR reversal drugs have failed in clinical trials because of their adverse side effects. On the other hand, studies in natural products have been reported its potential to overcome MDR in cancer patients. These investigations raised the quest for the natural compounds to dampen the drug resistance and adverse effects caused by the available therapeutics [8]. Despite the availability of numerous streptomyces derivatives in the literature, its potential against cancerous targets is not completely explored. Hence, we propose the ligand based virtual screening protocol for identifying novel compounds from KNApSaCK database comprising of nearly 2000 metabolites of Streptomyces species [9]. We are certain that the proposed protocol can be implemented for screening other repositories to identify novel drug-like molecules with high precision, thereby encouraging the drug discovery process from natural sources.

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Materials The protocol for the development of pharmacophore model combined with molecular docking entails operating systems (OS) including Windows, Mac OS X, or Linux platform for an effective usage of software. A basic prerequisite for molecular docking studies comprise the structural information of the target protein, ligand along with computational support. The docking analysis may be executed by employing GLIDE module of Schro¨dinger suite or other equivalent package for enumerating the binding free energy analysis of the small molecules. Here we have highlighted the Schro¨dinger suite based protocol for the virtual applications. Moreover, high-speed internet connection are necessary to employ myriad freely available software and servers during the course of the etiquette.

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Methods The major step in any repurposing method is the preparation of working dataset containing both protein and ligand molecules. The methodology followed for the dataset preparation is given below:

3.1 Protein Preparation

The protocol requires a protein structure in a PDB format. Here, the three-dimensional X-ray coordinates of β-catenin protein (PDB ID: 4DJS; Resolution: 3 Å) was acquired from the Protein Data Bank (http://www.pdb.org), in our analysis. The four letter PDB code or the name of the protein may be used as the query to retrieve the structural information. By selecting the “Download files” option and you will be prompted to open and download or save the file in various formats like FASTA, PDB, PDB (gz), PDBx/ mmCIF and PDBx/mmCIF (gz) formats, etc. It is suggested to download PDB structures with Rfree value of less than 0.3 as it depicts the high quality structure [10]. Additionally, the following steps are required to clean and optimize the structure before it is considered for the analysis. 1. The raw protein structure is processed utilizing Protein Preparation Wizard of Schro¨dinger. The reclaimed PDB structure is imported into the Maestro project by selecting the File Import structures. 2. Then go to “Task” option in the right side of the Maestro home page, select “Protein Preparation Wizard.” After opening the Protein Preparation Wizard panel, you can start preparing the protein by clicking the “Preprocess” option. 3. Then, select “Refine” option to optimize the protein structure. 4. After the optimization process, locate any waters you want to keep and then delete the remaining. Usually, we can remove waters with less than 2 followed by selecting the “Minimize” option. 5. Eventually, the protein was energy minimized by employing the default parameters and it can be utilized for various applications. The processing tab of the Protein Preparation Wizard panel is displayed in Fig. 1.

3.2 Ligand Preparation

Ligand structure used in the computational analysis also needs to be optimized as like the protein preparation. For instance, ligand cleaning can be accomplished using LigPrep module in Schro¨dinger. The processed steps are outlined below. 1. To perform LigPrep, the input files can be in Structure Data File (SDF) format. For instance, we have taken an available 10 known inhibitors with dissimilar scaffold to impede β-catenin and it can be downloaded as SDF format from the

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Fig. 1 The processing tab of the Protein Preparation Wizard panel

PubChem database by their Chemical Abstracts Service (CAS) numbers. PubChem is an open access database which comprises both 2D and 3D conformations of the ligand molecules in numerous file formats, such as Structure Data File (SDF), JavaScript Object Notation (JSON), Abstract Syntax Notation One (ASNT), and eXtended Markup Language (XML). 2. The 10 existing inhibitors corresponding to the target target protein was retrieved from the prior knowledge in the field. Here, the compounds, namely PNU-74654, PKF118-744, ZTM000990, PKF115-584, iCRT3, PKF222-815, iCRT5, iCRT14, PKF118-310, and CGP049090 specific to β-catenin were reclaimed from the literature [11, 12].

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Fig. 2 The LigPrep panel for ligand preparation

3. The downloaded SDF files were imported into the Maestro panel by choosing the File Import structures option. After importing the structures, Go to Task and select the LigPrep panel (Fig. 2). 4. In the LigPrep section, choose the “Project Table” entries option. Then select “Do not change” option, deselect “Desalt” and “Generate tautomers” option. Subsequently, for the tautomer generation, change 1 instead of 32 per ligand in the “Generate at most” option. Type the name of the job and then click “Run” button to initiate the project. Once the run is completed, the prepared ligand structures will be incorporated and enlisted in the project table entries. The LigPrep performs 2D to 3D structure conversion, addition of hydrogen atoms, removal of removal of water molecules, neutralization of the charged groups, generation of tautomers and

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ionization states, lower energy conformations, and optimization of the geometries of the small molecule [13]. 3.3 PHASE Database Creation

PHASE database creation is recognized as the integral modules of drug development and optimization [14]. The database should be developed using the set of prepared ligand molecules library which may be screened during the analysis. Steps involved in database creation are given below: 1. Here, the SDF file of around 2000 molecules can be downloaded by visiting the KNApSAcK database. High throughput virtual screening is always executed with thousands of compounds. Phase database can be created, prepared and filtered just by clicking the “Create Database” option in the task tool bar. It results in opening up a new tool box as shown in Fig. 3. 2. The process is initiated by choosing “Create a new database” option in the opened toolbox. One has to set the path for creating database by browsing the destination location in the “database path.” Moreover, the molecules are imported by choosing the downloaded SDF files. 3. The imported compounds are prepared by clicking the “Prepare Ligand Structures” option using Epik module of Schro¨dinger suite. This process generates possible states at pH 7.0  2.0. The specified chiralities of the stereoisomers are retained throughout the process by enabling “Retain specified chiralities” (vary other chiral centers) option. At most 4 low energy stereoisomers per ligand are retained. Moreover, minimum of 1 low energy 5/6 membered ring conformations are generated during this process. Removal of higher ionization or tautomer states are enabled to prevent generation of high energy tautomer. 4. The above prepared ligands are filtered by generating QikProp properties and can be pre-filtered based on Lipinski’s rule. Later the database creation job is submitted by clicking the “Run” option in the toolbar. Finally, the generated database can be accessed from the path given during the process.

3.4 Pharmacophore Model Generation

The simplest method for identifying potential lead molecules against the target is achieved by screening the molecules based on the pharmacophore model [15]. Hence, the prepared 10 reference compounds were chosen for pharmacophore model generation. The IC50 values of the reference compounds needs to be retrieved from literature evidences. Then, it was converted into pIC50 value using the tool available at https://www.sanjeevslab.org/tools.html [16]. Based on the pIC50 values, the reference molecules should be classified into actives and inactives during model generation. So that the generated model will discriminate the active compounds

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Fig. 3 Phase database creation using Schro¨dinger suite

from the inactives with high precision. The protocol for the same is described below. 1. Select the prepared reference molecules and click “Develop Pharmacophore Hypothesis” in the task toolbar. 2. Set the dropdown box to “Multiple ligands (selected entries)” option to develop pharmacophore hypothesis. Later, define the molecules into actives and inactive based on their pIC50 value as shown in Fig. 4. 3. Keep other setting in default and click “Run” to develop pharmacophore hypothesis. This process usually generates ligand conformers based on the user input and identifies the common pharmacophore in the complete set. 4. The list of generated pharmacophore model will be displayed on your workspace navigator. The appropriate model can be chosen based on the survival score and fitness score available in the project table.

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Fig. 4 Defining of reference compounds into actives and inactive

5. Further the chosen hypothesis can be selected for “Add to database screen” by click the H icon available near the selected hypothesis. The phase ligand screening process was initiated by adding created phase database to the process and by matching minimum 4 features out of 5 as shown in Fig. 5. If the number of molecules is higher, we can limit them by changing to 1000 in the output tab of the screening settings toolbar. The list of phase screened molecules will then be available in the workspace navigator for further analysis. A complete set of scrutinized molecules along with their score can be accessed in the project table. 3.5 Receptor Grid Generation and Molecular Docking

Molecular docking plays a vital role in drug discovery by identifying potential molecules against the targets [15]. This process includes screening of molecules through three docking processions, namely high throughput virtual screening (HTVS), standard precision (SP), and extra precision (XP), respectively. In this study, GLIDE (Grid-based LIgand Docking with Energetics) module of Schro¨dinger is implemented to perform the docking processes [17]. 1. Prior to docking, a grid was created by employing GLIDE inside the cubic box focused on the inhibitor (if the complex structure is available). Else, sitemap of the Schro¨dinger may be used to fix the grid. In order to generate a grid, go to “Task” option, select “Receptor Grid Generation” option as exemplified in Fig. 6. 2. Keep all the settings in default with appropriate job name, click “Run” to generate receptor grid. Eventually, the generated

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Fig. 5 Feature selection for performing phase screening of molecules based on the generated pharmacophore hypothesis

grid can be accessed from the project folder which is created initially. Consequently, the prepared protein and molecules from phase database (KNApSAcK database molecules) should be considered for screening based on the generated pharmacophore hypothesis. Step-by-step protocol for performing multi-stage docking is given below.

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Fig. 6 The dialog box for receptor grid generation

1. The minimized protein and the compounds obtained after phase screening are selected for docking process. On selection, click the “Ligand Docking” option available in the task toolbar. 2. Select the generated grid file and the ligands to be screened from the project table to perform docking process. Docking process is limited for the compounds with more than 500 atoms and 100 rotatable bonds. In order to soften the potential for non-polar portions of the small molecule, set the scaling factor and partial charge cut-off as 0.80 and 0.15, respectively. Illustration of this step is given in Fig. 7. 3. The precision of screening can be changed in the setting as HTVS, SP, or XP. Note that the sequence of performing docking is HTVS, followed by SP and XP. It should be noted that only the precision process changes during screening while other parameters are set as default (Fig. 8). Hence the molecules obtained after HTVS screening process are carried further for SP. Later, the screened molecules in SP is considered for XP docking process. Finally, to identify the potential molecule, the XP GScore of the screened molecules after XP docking may be mapped with the reference compound. The compounds with minimal binding energy usually considered for pharmacokinetic evaluation.

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Fig. 7 Parameters to be fixed during docking process 3.6 Pharmacokinetic Analysis of Screened Compounds

The screened molecules are further considered for ADME (Absorption, Distribution, Metabolism, and Excretion) study. The ADME analysis of the molecules can be performed by QikProp module of Schro¨dinger package. QikProp is a fast, precise and easy to use module for ADME prediction [18]. It can calculate substantially important descriptors and pharmacologically related features of ligand molecules, either by individual or groups. Additionally, it can also be used for comparing a properties of molecules with 95% of existing known drugs. The steps to perform QikProp are as follows. 1. Go to “Task” and Select “QikProp” section, pick “Project Table (selected entries)” from the “Use structures from” selection menu. Enter the job name, then click “Run” option as exemplified in Fig. 9. The job begins to run and when it finishes, the results are incorporated in the project table. We can view the outcomes from the table menu.

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Fig. 8 Setting of docking precision level during the process

2. A set of 16 ADME properties, namely QPlogPoct, QPlogPw, QPlogPo/w, QPlogS, QPlogBB, QPlogKp, QPPCaco, QPPMDCK, Molecular weight, Solvent Accessible Surface Area (SASA), Hydrophobic SASA (FOSA), Hydrogen bond acceptor (accptHB), Hydrogen bond donor (donorHB) Central Nervous System (CNS) activity, Human Oral Absorption (HOA), and #stars values can be considered from the QikProp output of more than 40 descriptors for screening the lead compounds. Notably, the value for CNS lies in the range of 2 (inactive) and +2 (active). The compounds with a lesser value of #stars (0) and higher value of HOA (3) imply the better drug-like molecules. Hence, the molecules which obeys abovementioned criteria may be the right choice for further in vitro analysis.

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Fig. 9 QikProp analysis panel 3.7 Protein–Ligand Interaction Analysis

The binding interactions of the protein and ligand entail particular intermolecular contacts. The interaction form of the complexes can be examined by employing the ligand interaction diagram (LID) of the Schro¨dinger package. 1. The LID panel permits the user to generate and show a two-dimensional diagram of the binding interactions between the protein residues and ligand molecules. To open the Ligand Interaction Diagram panel, choose directly by clicking the “Ligand Interaction Diagram” on the project toolbar. 2. The diagram is produced spontaneously from the selected structures in the workspace. Figure 10 exemplifies the Ligand Interaction Diagram panel of the Schro¨dinger software. In the LID image, the protein–ligand interactions were marked using lines amid the protein residues and ligand atoms are as follows: (a) Dotted and solid pink—Hydrogen bond interactions to the side chains and backbone of protein. (b) Orange—Pi-cation interaction. (c) Green—Pi-Pi stacking interaction. (d) Blue with pink—Salt bridge interaction. Moreover, the residues are denoted as color coded, labeled by residue number and name. The residue which is represented based on color is given below: 1. Red—Aspartic acid and Glutamic acid residue (Acidic). 2. Green—Alanine, Valine, Isoleucine, Leucine, Tyrosine, Phenylalanine, Tryptophan, Methionine, Cysteine, Proline (Hydrophobic residue). 3. Purple—Lysine, Arginine (Basic). 4. Blue—Serine, Threonine, Glutamine, Asparagine, Histidine (Polar). 5. Light gray—Glycine and water (Other). 6. Dark gray—Metal atoms.

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Fig. 10 The Ligand Interaction Diagram panel

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Acknowledgments The authors thank VIT for providing “VIT SEED GRANT” for carrying out this research work. References 1. Silva LJ, Crevelin EJ, Souza DT et al (2020) Actinobacteria from Antarctica as a source for anticancer discovery. Sci Rep 10:1–15 2. Sivalingam P, Hong K, Pote J, Prabakar K (2019) Extreme environment streptomyces: potential sources for new antibacterial and anticancer drug leads? Int J Microbiol 2019:1–20 3. Rani R, Arora S, Kaur J, Manhas RK (2018) Phenolic compounds as antioxidants and chemopreventive drugs from Streptomyces cellulosae strain TES17 isolated from rhizosphere of Camellia sinensis. BMC Complement Altern Med 18:82 4. Abd-Elnaby H, Abo-Elala G, Abdel-Raouf U, Abd-elwahab A, Hamed M (2016) Antibacterial and anticancer activity of marine Streptomyces parvus: optimization and application. Biotechnol Biotechnol Equip 30:180–191 5. Park SR, Yoon YJ, Pham JV (2019) A review of the microbial production of bioactive natural products and biologics. Front Microbiol 10:1404 6. Newman DJ, Cragg GM (2007) Natural products as sources of new drugs over the last 25 years. J Nat Prod 70:461–477 7. Olano C, Mendez C, Salas A (2009) Antitumor compounds from marine actinomycetes: from gene clusters to new derivatives by combinatorial biosynthesis. Nat Prod Rep 26:628–660 8. Deng S, Shanmugam MK, Kumar AP, Yap CT, Sethi G, Bishayee A (2019) Targeting autophagy using natural compounds for cancer prevention and therapy. Cancer 125:1228–1246 9. Afendi FM, Okada T, Yamazaki M et al (2012) KNApSAcK family databases: integrated metabolite–plant species databases for multifaceted plant research. Plant Cell Physiol 53:e1

10. Wlodawer A, Minor W, Dauter Z, Jaskolski M (2008) Protein crystallography for non-crystallographers, or how to get the best (but not more) from published macromolecular structures. FEBS J 275:1–21 11. Zhang X, Hao J (2015) Development of anticancer agents targeting the Wnt/β-catenin signaling. Am J Cancer Res 5:2344 12. Lepourcelet M, Chen YN, France DS (2004) Small-molecule antagonists of the oncogenic Tcf/β-catenin protein complex. Cancer Cell 5:91–102 13. Sastry GM, Adzhigirey M, Day T, Annabhimoju R, Sherman W (2013) Protein and ligand preparation: parameters, protocols, and influence on virtual screening enrichments. J Comput Aided Mol Des 27:221–234 14. Dixon SL, Smondyrev AM, Rao SN (2006) PHASE: a novel approach to pharmacophore modeling and 3D database searching. Chemical Biol Drug Des 67:370–372 15. Sharma T, Harioudh MK, Kuldeep J (2020) Identification of potential inhibitors of Cathepsin-B using Shape & Pharmacophorebased Virtual Screening, molecular docking and explicit water thermodynamics. Mol Inform 39:1900023 16. Selvaraj C, Tripathi SK, Reddy KK, Singh SK (2011) Tool development for prediction of pIC50 values from the IC50 values-a pIC50 value calculator. Curr Trends Biotechnol Pharm 5:1104–1109 17. Hall DC Jr, Ji HF (2020) A search for medications to treat COVID-19 via in silico molecular docking models of the SARS-CoV-2 spike glycoprotein and 3CL protease. Travel Med Infect Dis 35:101646 18. Schro¨dinger (2017) QikProp, LLC, New York

Chapter 41 Methods of Identification and Validation of Drug Target Jerrine Joseph, Radhakrishnan Manikkam, Manigundan Kaari, Gopikrishnan Venugopal, Mary Shamya, and Wilson Aruni Abstract Drug target identification is the first stride in the drug discovery progression. However, traditional drug discovery methods are laborious, lavish, and often produce few drug targets. In contrast, advances in complete genome sequencing, bioinformatics, and cheminformatics epitomize a striking substitute approach to identify drug targets commendable of experimental sequel. Ever since of the availability of both pathogen and host–genome sequences, it has become difficult to identify drug targets at the genomic level for any given pathogen. Key words Drug, Target, Database, Bioinformatics, Pathway

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Introduction In recent years, computational methods have been used widely for the identification of potential drug and vaccine targets in different pathogenic microorganisms [1]. Subtractive and comparative genomics approach combined with metabolic pathway analysis was found to be an efficient way to identify the protein-set essential for the pathogen’s survival but absent in the host [2]. Subtraction of the host genome from essential genes of pathogens helps in searching for non-human homologous targets which ensures no interaction of drugs with human targets. On the other hand, comparative genomics method emphasizes the selection of conserved proteins amongst several species as most favorable targets. The use of advanced bioinformatics tools with integrated genomics, proteomics, and metabolomics [3] may ensure the discovery of potential drug targets for most of the infectious diseases. Once the target (s) have been identified, the in silico virtual screening of different chemical databases could provide unprecedented opportunity to select and design the best possible inhibitor(s) [4].

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_41, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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Materials/Databases/Software KEGG, DEG PSORTb, BioEdit, Swiss-Prot database. Protein Data Bank and ModBase, ESyPred3D server and Refseq database.

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Methods

3.1 Pathway Analysis and Protein Retrieval

1. The Kyoto Encyclopedia of Genes and Genomes (KEGG) database [5] will be searched for metabolic pathways. The identification numbers of all pathways from both organisms will be listed. 2. A manual comparison is usually made, and pathways that do not appear in the human genomes but are present in the pathogen are obtained using amino acid sequences of proteins from KEGG database annotations and from uniprotKB [6, 7].

3.2 Identification of Essential Proteins and Non-homologous Proteins in Humans

1. Database of Essential Genes (DEG) [8] is used to identify the essential proteins involved in host-pathogen pathways. 2. The DEG 6.8 database is retrieved from http://www.tubic.tju. edu.cn/deg/. The BioEdit Sequence Alignment Editor (version 7.1.3) will be used for Protein Basic Local Alignment Search Tool (BLASTP) search to screen for and eliminate the probable essential proteins of the organism setting e-value cutoff 10 4, sequence identity >35%, bit score >100, and others as default. 3. All human protein sequences retrieved from Refseq database ftp site (ftp://ftp.ncbi.nlm.nih.gov/genomes/H_sapiens/pro tein/) and essential proteins will be subjected to BLASTP search against the human proteins with BioEdit. Only the non-hit proteins at e-value cutoff 10 10 are to be selected as non-homologous proteins to avoid any functional similarity with host proteome.

3.3 Subcellular Localization Prediction and Targets’ Prioritization

Subcellular localization prediction of the essential non-human proteins was done by PSORTb version 3.0.2 [12] which predicts three types of localization such as cytoplasmic, membrane, and extracellular proteins for Gram-negative bacteria. 1. The potential drug targets will be evaluated by several molecular and structural criteria [9] for prioritizing suitable drug targets. Drug targets’ prioritization involved calculation of molecular weight (MW) using computational tools and drug targets associated literature available at Swiss-Prot database. Protein Data Bank and ModBase (http://www.salilab.org/ modbase) databases will be searched for identifying experimentally and computationally solved 3D structures, respectively [10].

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2. The selected protein will be searched for any structural identity with the 3D ligand binding site of any human protein structure on the web server SMAP-WS at a cutoff value of 30% sequence identity [11]. Moreover, druggability is another important prioritization criterion for therapeutic targets; that is defined as the likelihood of being able to modulate the activity of the therapeutic target protein with a small-molecule drug [12]. The druggability of identified drug targets will be measured by mining DrugBank contents. 3.4 Identification of Novel Targets and Searching for Common Proteins

1. To identify novel targets among the potential targets, databases DrugBank, SuperTarget, and Therapeutic Target Database will be searched for similarity with the cytoplasmic proteins. Parameters were set as e-value 35%, and bit score >100. 2. The non-hit proteins at the threshold value will be selected as novel drug targets. 3. The novel targets will be subjected to BLASTP if no exact protein data bank (PDB) structure available in PDB, it will be subjected to BLAST search against PDB structures using 0.001 e-value cutoff. 4. The template for homology modeling is chosen considering X-ray diffraction resolution and highest sequence similarity. Homology modeling will be done on ESyPred3D server [13].

3.5 Structure Validation and Active Site Prediction

1. The modeled structure will be assessed through SWISSMODEL structure assessment tool and ANOLEA (atomic non-local environment assessment) assessing the packing quality of the models. PROCHECK suite of program will check the stereochemical quality of protein structures. 2. Energy minimization will be carried out by GROMOS96 with default parameters implemented in Swiss PDB Viewer (version 4.0.4). Active site of the modeled structure will be as determined by CASTp server.

3.6 Virtual Screening, Drug Likeliness, and Toxicity Analysis

1. For visual analysis and comparison of the active site interaction with the ligands, extracted from BindingDB databases and docked with the subject receptor. 2. Virtual screening will be done with molecules, experimental and approved molecules deposited in DrugBank, based on selected active sites. 3. Virtual screening will be performed on Linux (Ubuntu 10.04) based cluster with 32 core systems. The top 100 molecules will be selected based on lowest binding energy after being docked several times. The selected molecules were analyzed by Lipinski’s rule of five.

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4. The ligand interaction analysis and visualization will be with the help of Pymol and Discovery Studio (Accelrys, San Diego, CA, USA). 5. Absorption, distribution, metabolism, excretion, and toxicity (ADMET) prediction will be carried out with PreADMET server.

References 1. Stumm G, Russ A, Nehls M (2002) Deductive genomics: a functional approach to identify innovative drug targets in the post-genome era. Am J Pharmacogenomics 2(4):263–271 2. Kanehisa M, Goto S, Furumichi M, Tanabe M, Hirakawa M (2010) KEGG for representation and analysis of molecular networks involving diseases and drugs. Nucleic Acids Res 38(Database issue):D355–D360 3. Lacchia A, Di Giovanni C (2013) Virtual screening strategies in drug discovery: a critical review. Curr Med Chem 20(23):2839–2860 4. Keller TH, Pichota A, Yin Z (2006) A practical view of ‘druggability’. Curr Opin Chem Biol 10(4):357–361 5. Kanehisa M, Goto S, Hattori M et al (2006) From genomics to chemical genomics: new developments in KEGG. Nucleic Acids Res 34 (Database issue):D354–D357 6. Hecker N, Ahmed J, von Eichborn J et al (2012) Super Target goes quantitative: update on drug-target interactions. Nucleic Acids Res 40(Database issue):D1113–D1117 7. Lambert C, Leonard N, De Bolle X, Depiereux E (2002) ESyPred3D: prediction of proteins 3D structures. Bioinformatics 18 (9):1250–1256

8. Laskowski RA, MacArthur MW, Moss DS, Thornton JM (1993) PROCHECK: a program to check the stereochemical quality of protein structures. J Appl Cryst 26:283–291 9. Guex N, Peitsch MC (1997) SWISS-MODEL and the Swiss-PdbViewer: an environment for comparative protein modeling. Electrophoresis 18(15):2714–2727 10. Aguero F, Al-Lazikani B, Aslett M et al (2008) Genomic-scale prioritization of drug targets: the TDR Targets database. Nat Rev Drug Discov 7(11):900–907 11. Cheng AC, Coleman RG, Smyth KT et al (2007) Structure-based maximal affinity model predicts small-molecule druggability. Nat Biotechnol 25(1):71–75 12. Holman AG, Davis PJ, Foster JM, Carlow CK, Kumar S (2009) Computational prediction of essential genes in an unculturable endosymbiotic bacterium, Wolbachia of Brugiamalayi. BMC Microbiol 9:243 13. Ren J, Xie L, Li WW, Bourne PE (2010) SMAP-WS: a parallel web service for structural proteome-wide ligand-binding site comparison. Nucleic Acids Res 38(Web Server issue): W441–W444

Chapter 42 Transcriptome Profiles of Streptomyces sp. Sushant Parab, Davide Cora`, and Federico Bussolino Abstract Actinobacteria are potential producers of various secondary metabolites with diverse bioactivities. Streptomyces are one of the largest and valuable resource of bioactive and complex secondary metabolites, many of which have important clinical applications. Recent advancements in high-throughput sequencing technologies have made possible the mapping of Streptomyces genome which helps to elucidate the dynamic changes in gene expression in response to cellular status at both transcriptional and translation levels. In this chapter, we will provide a background on the approaches of the transcriptomic assembly along with the development of tools and algorithms that can be used for building prokaryotic transcriptomes. Key words Streptomyces sp., RNA-Seq, Transcriptome assembly and annotation, Secondary metabolites

1

Introduction Streptomyces comprise the largest genus of actinobacteria with over 800 described species [1–3]. They are huge natural reservoir of secondary metabolites including antibiotics, antiparasitics, immunosuppressants, and other value-added biochemical compounds [4–10]. Recent advancements in genome mining approaches have indicated that each Streptomyces genome encode for over more than 30 biosynthetic gene clusters (BGCs) [11], which has potential to produce various unexplored secondary metabolites whose functions are still found to be “silent” under laboratory conditions [12]. Hence, it is essential in determining the transcriptional regulatory elements that govern the expression of secondary metabolite BGC.

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Approaches for Analyzing Transcriptomic Data Transcriptomic assembly (RNA-seq) is a powerful tool for detecting variations in gene expression matrices between conditions,

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species/strains, organisms [13, 14]. The performance of such an analysis, however, is completely dependent on the quality of the assembly [15]. A mis-assembly can alter the gene and transcript quantification, isoform detection, etc. leading up to the increase in false positives rates [16]. These problems sometimes aggravate more to errors in non-model organisms [17]. There are two types of approaches for transcriptome assembly:

3

De Novo Assembly Most of the de novo assemblers use the de Bruijn graph concept for aligning reads of the RNA-seq data [18], hence the generated contigs totally depend on the quality of the sequenced data [19– 25]. These de Bruijn graphs are generated by k-mer decompositions, where the reads are broken down into shorter sequences of length k (the k-mers) and the assembly is constructed by overlapping these short segments. One major limitation of the de Bruijn graph concept is the need for a k-mer [25], shorter k-mers are more likely to cover the original sequence, while there is always a chance of them corresponding to multiple reads from multiple transcripts. While, on the other hand longer k-mers can avoid such uncertainty but may not cover entire original sequence leading to fragmented assembly. As a result, even though using the same de novo algorithms for performing two assemblies with different k-mer length will generate two different set of contigs [26]. De novo assemblers: idba-Tran [21], SOAPdenovo-Trans [20], maSPAdes [24], and Trinity [19].

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Reference-Based/Genome-Guided Assembly The uncertainty/obscurity of k-mer decompositions is avoided in genome-guided assembly (Table 1) by mapping the reads directly to the reference genome. In this type of mapping the reads are split, where first part of the reads maps to one exon and the latter one to another exon [26]. Split-read mappers such as TopHat [27], STAR [28], HISAT [29], and HPG-aligner [30] are used for referencebased mapping (Table 2). Other examples of genome-guided assemblers are Bayesembler [31], Cufflinks [32], and StringTie [33].

1 July 2013; 62

Publication date and citation counts

15 June 2014; 282

http://sourceforge.net/projects/ soapdenovotrans/

http://www.cs.hku.hk/~alse/idba_tran

Web Address/ source code

7 May 2012; 6100

http://cab.spbu.ru/software/ spades/

15 May 2011; 5692

http://trinityrnaseq. github.io

Linux

Linux

Unix-like system

User interface

Unix-like system

Trinity fully reconstructs a large fraction of the transcripts present in the data, also reporting alternative splice isoforms and transcripts from recently duplicated genes SPAdes, a new assembler for both single-cell and standard (multicell) assembly

It is a de novo transcriptome assembler inherited from the SOAPdenovo2 framework, designed for assembling transcriptome with alternative splicing and different expression level

Short It is an iterative De Bruijn Graph short read introduction assembler, uses local assembly for reconstructing missing k-mers

Trinity https://pubmed. ncbi.nlm.nih. gov/21572440/

maSPAdes https://pubmed.ncbi.nlm.nih. gov/22506599/

https://pubmed.ncbi.nlm.nih.gov/ 23813001/

Pubmed link

SOAPdenovo-Trans https://pubmed.ncbi.nlm.nih.gov/ 24532719/

Idba-Trans

Tools

Table 1 De novo assemblers

http://tophat.cbcb.umd.edu

Web Address/ source code

Publication date 1 May 2009; 5967 and citation counts

Linux

9 March 2015; 3198

http://www.ccb.jhu.edu/software/ hisat/

Linux

Linux

1 January 2013; 8102

18 February 2015; 1317

http://code.google.com/p/rna-star/ http://ccb.jhu.edu/software/ stringtie

Linux

https://pubmed.ncbi.nlm.nih.gov/ 25690850/

User interface

https://pubmed.ncbi.nlm.nih.gov/ 23104886/

It is to align large (>80 billion reads) A computational method that applies It is a fast splice junction mapper for It is a fast and sensitive spliced alignment program for mapping transcriptome RNA-seq dataset. It a network flow algorithm RNA-Seq reads. It aligns reads to RNA-seq reads. It uses a large set of uses sequential maximum mappable originally developed in mammalian-sized genomes using FM indexes that collectively cover seed search in uncompressed suffix optimization theory, together the ultrahigh-throughput short the whole genome arrays followed by seed clustering with optional de novo assembly, to read aligners, and then analyzes the and stitching procedure assemble these complex data sets mapping results to identity splice into transcripts junctions between exons

https://pubmed.ncbi.nlm.nih.gov/ 25751142/

Short introduction

StringTie

https://pubmed.ncbi.nlm.nih.gov/ 19289445/

STAR

Pubmed link

HISAT

TOPHAT

Tools

Table 2 Reference-based assemblers

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Transcriptome Profiles of Streptomyces sp.

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Transcriptomic Analysis by TOPHAT Materials

1. Raw RNA-seq reads of Kineococcus radiotolerans [34] are downloaded from NCBI’s Gene Expression Omnibus (GEO), having a GEO accession: GSM1238698, GSM1238699. It is a paired-end data sequenced by Illumina Hiseq2000. 2. K. radiotolerans [35] (NC_009664, NCBI) is used as a reference for mapping the raw reads by a genome-guided approach.

5.2

Procedure

bowtie2-build

1. Indexing the reference genome: ### bowtie2-build = creates an index -f \ ### input is a FASTA file Kineococcus_radiotolerans.fasta\### reference FASTA file actinobacteria_reference ### output

2. Mapping the raw reads to the reference genome: tophat -p 8 -G ref_K_radiotoerans.gtf -o tophat_out1 \ actinobacteria_reference \ SRR999644_1.fastq.gz, \ SRR999644_2.fastq.gz

### using TopHat ### genome annotation file ### output directory ### reference_genome ### paired read sample A*_1 ### paired read sample A*_2

The above commands will create an output directory: tophat_out1, which includes the BAM files for the mapped (accepted_hits.bam) and unmapped reads (unmapped.bam), along with some *.bed files and *.txt files which includes the alignment summary. 3. SAMtools can be used for viewing the BAM files: samtools view accepted_hits.bam

### view the bam file

samtools sort -o out.bamaccepted_hits.bam

### sort alignments by leftmost coordinates ### convert BAM to SAM

samtools view -h -o out.samaccepted_hits.bam

4. Once the alignment from Tophat is completed, the bam files can be processed by cufflinks/feature counts for extracting the transcript/gene counts. If there are samples coming from more than one condition, then the differential expression study can

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Fig. 1 Overview of transcriptomics data analysis

be carried out by differential expression algorithms such as cuffdiff/edgeR/DESeq2. A general overview of the pipeline is shown in Fig. 1. References 1. Kim JN, Kim Y, Jeong Y, Roe JH, Kim BG, Cho BK (2015) Comparative genomics reveals the Core and accessory genomes of Streptomyces species. J Microbiol Biotechnol 25 (10):1599–1605. https://doi.org/10.4014/ jmb.1504.04008 2. Jones SE, Elliot MA (2017) Streptomyces exploration: competition, volatile communication and new bacterial Behaviours. Trends Microbiol 25(7):522–531. https://doi.org/ 10.1016/j.tim.2017.02.001. Epub 2017 Feb 27 3. Hwang S, Lee N, Jeong Y, Lee Y, Kim W, Cho S, Palsson BO, Cho B-K (2019) Primary transcriptome and translatome analysis determines transcriptional and translational regulatory elements encoded in the Streptomyces clavuligerus genome. Nucleic Acids Res 47 (12):6114–6129. https://doi.org/10.1093/ nar/gkz471 4. Fl€ardh K, Buttner M (2009) Streptomyces morphogenetics: dissecting differentiation in a filamentous bacterium. Nat Rev Microbiol 7:36–49. https://doi.org/10.1038/ nrmicro1968 5. Hwang K-S, Kim HUK, Charusanti P, Palsson BØ, Lee SY (2014) Systems biology and biotechnology of Streptomyces species for the production of secondary metabolites. Biotechnol Adv 32(2):255–268., , ISSN 0734-9750.

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Quintana-Ortı´ ES, Dopazo J (2016) Highly sensitive and ultrafast read mapping for RNA-seq analysis. DNA Res 23(2):93–100. https://doi.org/10.1093/dnares/dsv039. Epub 2016 Jan 5 31. Maretty L, Sibbesen JA, Krogh A (2014) Bayesian transcriptome assembly. Genome Biol 15(10):501. https://doi.org/10.1186/ s13059-014-0501-4 32. Trapnell C, Williams BA, Pertea G, Mortazavi A, Kwan G, van Baren MJ, Salzberg SL, Wold BJ, Pachter L (2010) Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol 28(5):511–515. https://doi.org/10. 1038/nbt.1621. Epub 2010 May 2 33. Pertea M, Pertea GM, Antonescu CM, Chang TC, Mendell JT, Salzberg SL (2015) StringTie

enables improved reconstruction of a transcriptome from RNA-seq reads. Nat Biotechnol 33 (3):290–295. https://doi.org/10.1038/nbt. 3122. Epub 2015 Feb 18 34. Li L, Chen Z, Ding X, Shan Z, Liu L, Guo J (2015) Deep sequencing analysis of the Kineococcus radiotolerans transcriptome in response to ionizing radiation. Microbiol Res 170:248–254. https://doi.org/10.1016/j. micres.2014.10.003. Epub 2014 Nov 6 35. Tatusova T, Ciufo S, Fedorov B, O’Neill K, Tolstoy I (2014) RefSeq microbial genomes database: new representation and annotation strategy. Nucleic Acids Res 42(Database issue):D553–D559. https://doi.org/10. 1093/nar/gkt1274. Epub 2013 Dec 6. Erratum in: Nucleic Acids Res. 2015 Apr 20;43 (7):3872

Chapter 43 Culture of Actinobacteria, Isolation and Characterization of their Bioactive Compounds Charles Santhanaraju Vairappan Abstract Actinobacteria are prolific producers of secondary metabolites with a wide array of structural diversity and potent activities. These bioactive compounds account for approximately 70% of the naturally occurring compound in various stages of clinical trials. Many of these secondary metabolites are useful antitumor drugs, such as anthracyclines, peptides, aureolic acids, enediynes, carzinophilin, and mitomycins. This chapter will describe the culture of actinobacteria from soils, plants, lichens, termite mounts, and marine sponges. Sample handling technique, media preparation, and culture techniques will be described in detail. Subsequently, actinobacteria cultured broth media will be extracted for its secondary metabolites using liquid-liquid extraction with organic solvents of various polarity. Further separation of the bioactive compounds will be done using a series of RP-18 Gravity Flush column chromatography techniques and High-Performance Liquid Chromatography (HPLC), coupled with “Bioassay Guided Separation” approach. Isolated biologically active pure compounds were subjected to spectroscopic analysis using 1 H-Nuclear Magnetic Resonance (NMR), 13C-NMR, COSY (Correlation-Spectroscopy), HSQC (Heteronuclear Single Quantum Correlation), HMBC (Heteronuclear Multiple Bond Correlation), and NOESY (Nuclear Overhauser Effect Spectroscopy) measurements. Additional spectroscopic measurement will be taken using polarimeter, FTIR, and High resolution LCMS IT-TOF. Spectroscopic data obtained from these measurements will be used to elucidate the structure of the bioactive compounds. Key words Actinobacteria, Culture, Bioactive Compounds, Bioassay Guided Separation, Compound Isolation, Characterization of Bioactive Compound

1

Introduction Symbiotic partnerships between plants, animals, and microbes are widespread in nature as organisms interact during ecological processes that facilitates ecosystem functions and produces ecosystem services in the form of nutrition, metabolic and defense compounds. Defensive microbial symbionts that benefit the host by protecting it against pathogens have been investigated to better understand the presence and role of ecological chemicals produced by these symbiotic organisms in association with their hosts.

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_43, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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Analysis of symbiont derived ecological chemicals coupled with the latest trends in omics-based dereplication have revolutionized natural product chemistry and has presented a wide range of structurally interesting new chemical entities identified as bioactive natural products. Metabolomic investigation of symbiotic microorganisms in soil, plants, lichens, termite mounts, and marine invertebrates has revealed their ability to produce defense chemicals, that are capable of preventing detrimental infestations of pathogens on their host. The chemical diversity, their biological activity, and biosynthetic potential of cultivable symbiotic microorganisms associated with their host organisms have been reported by natural products chemist for the last two decades [1–3]. Actinobacteria have been repeatedly shown to be the most prolific symbiont and have been proven to produce a wide diversity of secondary metabolites. Actinobacteria are a phylum of Grampositive bacteria, and found in a very diverse ecosystems let it be terrestrial, aquatic, or marine. They are known to aerobic, anaerobic, filamentous, spore-forming bacteria, found in terrestrial as well as aquatic (freshwater and marine) habitats, also known to have a characteristic earthy odor due to their ability to produce geosmin [4]. Although they are commonly found in soil, they are often found in very diverse ecosystems as symbiont in plants, insects, and invertebrates. Actinobacteria are known to be engaged in defensive symbioses and are the producers of defensive chemicals. They are well reported to be exceptionally potent producers of secondary metabolites, the rediscovery rates of known compounds are high in intensively studied genera such as Streptomyces species. Today, researchers have moved to study the less common host such as lichens, termite mounts, stingless-bee hives, and marine sponges, with the hope to discovering unprecedented new strains that produce novel chemical scaffolds. Secondary metabolites produced by these unique symbionts could be grouped into cyclic peptides, isoflavones, pyrones, polyketides, glycopeptides, echinosporin, and many other chemical scaffolds (Fig. 1). Their inherent ability to produce plethora of secondary metabolites and enzymes for pharmaceutical, agricultural, and biotechnological applications make actinobacteria one of the most explored microbes among prokaryotes. Bioactive compounds reported from actinobacteria are known for their importance in various physiological, cellular, and biological processes not limited to medicine but also includes environmental sensing, mineral acquisition and recycling, and establishing social communication. Recent discoveries have revealed that members Actinobacteria belonging to the genus Glycomyces and Streptomyces are capable of inhibiting the growth of penicillin resistant Staphylococcus aureus [5]. Thus, it is obvious that members of actinobacteria are prolific producers of secondary metabolites with not only ecological importance, but of functional potential in medicine, environment,

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Fig. 1 Biologically active secondary metabolites isolated from NocardiopsisHB383 (Nocapyrone A), Amycolatopsis hippodrome (Amycolasporin A), Sphaerimonospora mesophile (Linfuranone A), Actinomadura sp-RB99 (Maduraktermol A), and Streptomyces sp. (Hexadepsipeptide A)

agriculture, and ecosystem health. Primary aim of this chapter is to describe the basic methods involved in the handling of actinobacteria isolated from various host, their broth culture, extraction/ concentration of the bioactive constituents, chromatographic separation, bioassay-guided isolation, spectroscopic data collection, and characterization of the isolated compounds.

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Materials

2.1 Microbial Broth Culture

2.1.1 Agar Medium

Actinobacteria strains utilized for the broth culture were isolated from many different sources such as soil, plants, lichen, stinglessbees, termite mount, and marine sponges. Details of their isolation and techniques from soil are described in the Note 1. Isolated actinobacteria are kept as individual isolates in slant agar tubes in 20  C freezer. Culturable strains of isolated actinobacteria were activated by several subculture steps using the agar mediums described below before they were ready for broth culture. 1. Humic acid-vitamin agar was prepared as described previously. It is a minimal medium containing Na2HPO4 0.05%; KCl 0.17%, MgSO4·7H2O 0.005%, FeSO4·7H2O 0.001%, CaCO3

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0.002% at pH 7.2, supplemented with 0.1% (w/v) of humic acid as carbon source. 2. Czapek medium: Sucrose 20 g, NaNO3 2 g, K2HPO4 1 g, MgSO4·7H2O 0.5 g, MgSO4·7H2O 0.5 g, KCl 0.5 g, FeSO4·7H2O 0.01 g, vitamin mixtures 3.7 mg, agar 25 g, pH 7.2. 3. Glycerol asparagine medium: L-asparagine 1 g, glycerol 10 g, K2HPO4 1 g, vitamin mixtures 3.7 mg, trace salt* 1 mL, agar 20 g, pH 7.2–7.4. 4. Oatmeal medium: Oatmeal 20 g (cook or steam 20 g oatmeal in 1000 mL distilled water for 20 min, filter through cheese cloth, and add distilled water to restore volume of filtrate to 1000 mL), vitamin mixture 3.7 mg, trace salts 1 mL, agar 20 g, pH 7.2. 2.1.2 Broth Medium

1. Seed medium composed of 4 g L 1 yeast extract, 4 g L 1 glucose, 5 g L 1 malt extract, 3.75 mg L 1 multiple vitamin solution (thiamine 0.5 mg, riboflavin 0.5 mg, niacin 0.5 mg, pyridoxine 0.5 mg, inositol 0.5 mg, calcium pentothenate 0.5 mg, p-aminobenzoic acid 0.5 mg, biotin 0.25 mg), and 1 mL L 1 trace element solution (2 g L 1 FeSO·7H2O, 1 g L 1 MnCl·4H2O, 1 g L 1 ZnSO·7H2O). 2. Bn-2 agar medium consisting of 0.5% soluble starch, 0.5% glucose, 0.1% meat extract, 0.1% yeast extract, 0.2% NZ-case, 0.2% NaCl, 0.1% CaCO3, and 1.5% agar was inoculated into 500 mL K 1 flasks each containing 100 mL of seed medium (pH 7.0) consisting of 1% soluble starch, 0.5% glucose, 0.3% NZ-case, 0.2% yeast extract, 0.5% Tryptone (Difco Laboratories), 0.1% K2HPO4, 0.05% MgSO4·7H2O, and 0.3% CaCO3. 3. *Trace salts solution: FeSO4·7H2O 0.1 g, MnCl2 0.1 g, ZnSO4·7H2O 0.1 g, distilled water 100 mL. 50 mg potassium dichromate and 1 mg of penicillin are added in the isolation media. 4. All chemicals and salts used in the above preparations were from Sigma-Aldrich (Germany), and Fisher Chemicals (USA), Wako Pure Chemical industries, Ltd. (Japan) or Nacalai (Japan).

2.2 Extraction and Crude Extract

Since the actinobacteria strains are isolated from various biological and natural resources, evidently their choice of growth media and their growth profile will differ from species to species. It is important to study their preferred medium of growth and a change in the growth medium could result in the expression of different secondary metabolites or growth profile. Therefore, it is important to establish the growth profile or growth curve for the intended actinobacteria species and some preliminary assay should have

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been done to gauge their biological potential before embarking on the search for a particular strain’s secondary metabolites. Actinobacteria growth profile could be done following the basic microbiological protocol and McFarland Turbidity indices could be correlated with this profile to facilitate large volume culture of the desired strains [6]. The organic solvents, chemicals and instruments needed for the extraction and yield of crude extract are as below: Methanol (Fisher Chemical, USA). 1-butanol (Fisher Chemical, USA). Ethyl Acetate (Fisher Chemical, USA). Diaion HP20 resin (Sigma-Aldrich, USA). Ultra Turrax T25 Basic Disperser (IKA, Germany). Beckman Ultra High-Speed Centrifuge (Beckman, USA). 1 L Pear Shape Separation Flask (4 units). 2.3 Crude Extract Profiling

Crude extract chemical profiling is usually carried out to see the rough distribution of compounds in any given extracts, and to obtain solvent mixtures suitable for the separation of this crude extract. Since crude extract of actinobacteria was obtained from culture broth, it is expected to be medium polar to polar. Therefore, basic chemical profiling was carried out using a reverse phase thin layer chromatography system (RP-Si gel). Details of the TLC, glassware, solvents, and visualization techniques are given below: 1. SiO2 Gel, Aluminum Sheet Thin Layer Chromatography (TLC) F254nm—cut into 20  100 mm (Crude Extract Profiling), 75  100 mm (Fraction Profiling). 2. RP-Si Gel, Aluminum Sheet Thin Layer Chromatography (TLC) F254nm—cut into 20  100 mm (Crude Extract Profiling), 75  100 mm (Fraction Profiling). 3. Visualization Reagents: (1) 5% Molybdo Phosphoric Acid Spray, (2) 10% Sulfuric Acid in MeOH, (3) UV-Vis light observation at 254 nm and 356 nm. 4. TLC Development Chamber Solvent Systems: (1) CHCl3: MeOH (1:3), (2) CHCl3:MeOH (3:4), (3) Hex:EtOAc (1:3), (4) CHCl3:MeOH:H2O (64:25:4). 5. Duran TLC Development Chamber (Duran, USA).

2.4 RP-18 Column Chromatography

Crude extract was separated into fractions of various polarity by subjecting the crude extract to flush gravity RP-18 Silica Gel Column Chromatography. Glassware, accessories, and solvents utilized during this investigation are given below:

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1. Gravity Flush Glass Column (200  46  53 mm, L  I. D.  O.D.), with fritted disk, without PTFE stopcock (Yazawa, Japan). 2. LiChroprep RP-18 (40–63 mm) (Merck, Germany). 3. 250 mL Erlenmeyer Flask (2 Units) (Duran, USA). 4. 200 mL Elution solvent at 100% H2O (F-1), 25% MeOH (F-2), 50% MeOH (F-3), 75% MeOH (F-4), 100% MeOH (F-5), CHCl3:MeOH:H2O ((64:25:4)(F-6). 5. Diaphragm Vacuum Pump (Scilogex, China). 6. Vacuum filtering ring adapter with PP hose connector (Merck, Germany). 7. N2 Gas (Chromatography Grade) (MOX, Malaysia). 8. Whitton 20 mL Borosilicate Vials (Fisher, USA). 9. Sanyo

20  C Deep Freezer (Sanyo, Japan).

10. Eyela Rotary Evaporator (Eyela, Japan). 2.5

HPLC Separation

Crude, fraction, and partially separated compounds were subjected to High-Performance Liquid Chromatography (HPLC) (Fig. 2) separation using a semi-preparative column. But, prior to the separation, it is important to determine the most suitable semipreparative column type and solvent gradient for the crude extract that is going to be purified. The instruments and solvent systems needed for this solvent and column selection are given below:

Fig. 2 Gravity flush RP-18 column chromatography; (a) Yazawa Glass Column with fret, (b) Complete column system with adapter and vacuum pump

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Fig. 3 High-Performance Liquid Chromatography consisting of: (1) Solvent Pumps—LC-20AT and LC-6AD, (2) Oven—CTO-20A, (3) UV-Vis Detector— SPD-20A, (4) RID Detector—RID-10A, and System Controller—SCL-10A VP

1. Luna 5 m C18(2) 100 Å (250  20 mm) (Phenomenex, USA). 2. Luna 5 m C18 100 Å (250  20 mm) (Phenomenex, USA). 3. Luna 5 m Phenyl-Hexyl (250  20 mm) (Phenomenex, USA). 4. Shimadzu HPLC with UV Detector. 5. HPLC Solvents: (1) Solvent A—10% MeCN, (2) Solvent B— 100% MeCN. 6. HPLC Setting: (1) Flow rate: 2.0 mL min 1, (2) Solvent: 50% B Solvent, (3) UV Detector Setting: 210 nm, (4) Gradient Solvent System: 0–5 min: 50% B Solvent, 5–40 min: 100% B Solvent, 45 min: STOP (Fig. 3). 2.6 1D and 2D NMR Data Acquisition

NMR data is acquired only for compounds that are pure after repeated HPLC purification. Sample in the range of 1–8 mg is dissolved in 0.75 mL of deuterated chloroform or methanol solvent using accessories shown in Fig. 4a. Then, the NMR tube is inserted into Oxford magnet to be analyzed.

2.7 LCMS-IT-TOF-MS Data Acquisition

High resolution mass data was acquired using Liquid Chromatography Mass Spectroscopy Ion Trap Time Of Flight (Shimadzu, Japan) as shown in Fig. 5. Sample introduction was done in one of these two ways: 1. Sample is injected into the Rheodyne injector attached to the oven, sample will go through LCMS column, separated and resulting peak is then channeled to the mass analyzer to be

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Fig. 4 Nuclear Magnetic Resonance measurement accessories and spectrometer; (a) Glass Pasteur Pipet (230 mm) with rubber spout, 5 mm Sigma-Aldrich NMR sample tube with cover, and Deuterated Chloroform (Merck, Germany), (b) JEOL ECA 600 MHz Spectrometer with Oxford Magnet

ionized and data is processed using software to calculate its chemical formula and millimass unit. 2. Pure compound is injected into Rheodyne port that is attached to the LCMS Mass analyzer (Fig. 5b–d). Compound is ionized and data is processed using software to calculate its chemical formula and millimass unit. 2.8 FTIR and Optical Rotation Data Acquisition

3

FTIR Spectrums for the pure compounds were taken using one of the three accessories shown below depending on the physical state of the compound, solid, liquid, semi-solid/gum. Optical Rotation readings were taken using an AutoPol V automatic polarimeter (Rudolph, USA) (Fig. 6).

Methods

3.1 Actinobacteria Culture

A slant/petri dish cultured actinobacteria strain is inoculated into 500 mL Erlenmeyer flasks containing 100 mL of seed medium. The pH is set at 7.2 with adjustment, and flasks are incubated for 2 days at 28  C on a rotary shaker at 180 rpm. A 20 mL amount of the seed culture (0.5 McFarland Index turbidity) was used to inoculate the fermentation medium. The large-scale fermentation was carried out in a 1000 mL Erlenmeyer flask with 200 mL of fermentation medium composed of soybean meal 10 g L 1and mannitol 10 g L 1, with a pH of 7.2 with no adjustment, and the flasks were incubated for 7 days at 28  C on a rotary shaker at 180 rpm. A 20 mL amount of the seed culture was used to inoculate the fermentation medium. The large-scale fermentation was carried

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Fig. 5 LCMS-IT-TOF system complete with: (a) (1) Four-line solvent delivery system with DGU-20AR 3R Degasser, (2) LC-20AD binary solvent pump (2 Unit), (3) CBM-20A Communication Bus Module, (4) SIL-20AC XR Autosampler, (5) SPD-M20A Diode Array Detector, (6) CTO-20 AC Column Oven, (7) LCMS IT TOF, (b) LCMS-IT-TOF, (c) Direct Injection Rheodyne Port, (d) Direct Injection Internal Chamber

Fig. 6 Rudolph Research Analytical Autopol IV Polarimeter with short path 50 mm cell

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out in a 1000 mL Erlenmeyer flask with 200 mL of fermentation medium composed of soybean meal 10 g L 1and mannitol 10 g L 1, with a pH of 7.2 with no adjustment, and the flasks were incubated for 7 days at 28  C on a rotary shaker at 180 rpm. Culture duration could be more than 7 days subjected to the growth rate that could be visually observed based on broth turbidity and cell suspension in the broth and culture flask wall. The completed fermentation broth was clarified with a centrifuge to obtain 100 L of culture supernatant. 3.2 Extraction and Crude Extract

The methods used in the termination of actinobacteria fermentation, separation of biomass from supernatant, and extraction vary from one laboratory to the other. It depends on the research philosophy of the Principal Investigator, standard methods used in that particular laboratory, complexity of the culture organisms, sensitivity of the secondary compounds or just the availability of chemicals and instruments. Therefore, four different extraction protocols are given so as to facilitate one’s research approach and the availability of the chemicals and instruments: Protocol-1: When the culture turbidity reaches maximum and the growth curve approaches stationary phase, it is ideal to stop the fermentation process. A total of 50 mL of 1-butanol is added to each flask, and the flasks are allowed to shake for 1 h. The mixture is then centrifuged at 6000 rpm for 10 min, and the organic layer separated from the aqueous layer containing the actinobacteria cells. Evaporation of the solvent would give quantifiable amount of crude extract from cultured volume of actinobacteria [7]. Protocol-2: When the culture turbidity reaches maximum and the growth curve approaches stationary phase, it is ideal to stop the fermentation process. Resulting fermentation broth is clarified with a centrifuge to obtain 100 L of culture supernatant. The supernatant is then extracted with EtOAc four times, using a pear-shaped separation flask. The combined EtOAc extracts are concentrated under reduced pressure to yield a quantifiable amount of dried extract [8]. Protocol-3: When the culture turbidity reaches maximum and the growth curve approaches stationary phase, it is ideal to stop the fermentation process. The culture broth (12 L) is homogenized with an Ultra Turrax T25 basic (IKA-Werke GmbH and Co., Staufen, Germany) at 16,000 rpm for 30 s and extracted with 6 L of EtOAc. The solution is dried to yield a quantifiable organic extract [3]. Protocol-4: When the culture turbidity reaches maximum and the growth curve approaches stationary phase, it is ideal to stop the fermentation process. Bacterial cells are harvested by centrifugation at 4000  g for 10 min, and the cell pellet separated from the supernatant. The obtained supernatant is then mixed with activated HP20 resin (40 g/L) and stirred at 4  C overnight. The HP20 resin

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is then separated by filtration, washed with double distilled H2O (2 L), and eluted using 50% MeOH (2 L) and 100% MeOH (2 L). The resulting MeOH-containing fractions were combined and concentrated in vacuo [2]. 3.3 Chemical Profiling

Preparation of Developing Container: Developing chamber for TLC is a specially designed chamber consisting of a jar or rectangle container. Prepare desired solvent mixture into the chamber to a depth of just less than 0.5 cm. Saturation of the container with the developing solvent vapor could be achieved by lining one side of the chamber with a filter paper or TLC Saturation Pad (Merck, Germany). Cover the container air tight and allow it to stand while you prepare the TLC plate. Preparation of TLC Plate: TLC plates used in natural products chemical profiling are SiO2 gel absorbent type, either on glass plates or aluminum sheets. Aluminum TLC plates should be cut using a sharp cutter and ruler into sizes of 20  100 mm (crude extract), or 75  100 mm (Column Chromatography fractions). Measure 0.5 cm from the bottom of the plate. Using a pencil, draw a line across the plate at the 0.5 cm mark. This is the origin: the line on which you will spot the plate. Take care not to press so hard with the pencil that you disturb the adsorbent. Under the line, mark lightly the name of the samples you will spot on the plate, or mark numbers for time points. Leave enough space between the samples so that they do not run together; about 4 samples on a 5 cm wide plate is advised. Dissolve about 1 mg in 1 mL of a volatile solvent such as hexanes, ethyl acetate, or methylene chloride. Generally, a concentration of 1% usually works well for TLC analysis. If the sample is too concentrated, it will run as a smear or streak (see troubleshooting section below); if it is not concentrated enough, you will see nothing on the plate. Sometimes you will need to use trial and error to get well-sized, easy to read spots. Use a glass microcapillary or fine sized hematological glass capillary to spot the extract, fractions or compounds onto the prepared TLC plates. Dip the capillary into the solution and then gently touch the end of it onto the proper location on the TLC plate. Don’t allow the spot to become too large, touch it to the plate, lift it off, and blow on the spot gently to assist the solvent evaporation. If you repeat these steps, the wet area on the plate will stay small. If you are unsure of how much sample to spot, you can always spot multiple quantities and see which looks best. TLC Plate Development: Place the prepared TLC plate in the developing beaker, cover the beaker with the watch glass, and leave it undisturbed on your bench top. The solvent will rise up the TLC plate by capillary action. Make sure the solvent does not cover the spot. Allow the plate to develop until the solvent is about half a cm below the top of the plate. Remove the plate from the beaker and immediately mark the solvent front with a pencil. Allow the plate to dry.

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Visualization of TLC: If there are any colored spots, circle them lightly with a pencil. Most samples are not colored and need to be visualized with a UV lamp. Hold a UV lamp over the plate and circle any spots you see. Beware! UV light is damaging both your eyes and your skin! Make sure you are wearing your goggles and do not look directly into the lamp. Protect your skin by wearing gloves. If the TLC plate runs samples which are too concentrated, the spots will be streaked and/or run together. If this happens, you will have to start over with a more dilute sample to spot and run on a TLC plate. 3.4 RP-18 Column Chromatography

Place 100 g of RP-18 in a 200 mL beaker, pour distilled water to completely submerge the gel and sonicate it to saturate the gel with water. Stir the gel with a glass rod and make sure all air bubbles are released from the gel and no floating gel on the surface. Pour the aqueous slurry slowly using a rod for assistance and pour more distilled water to make sure that water is about 1 cm above the gel level. Take 20 g of RP-18 SiO2 gel, and mix it evenly with 1 g of crude actinobacteria crude extract in 90% MeOH. It is important that the crude extract dissolves well in 90% MeOH before RP-18 gel is mixed into it. Then, rotary evaporate the mixture under vacuo until the RP-18-crude extract mixture becomes dry and powdery. Transfer that to the top of the column that has been prepared with 100 g of RP-18 gel in water. Saturate the column with 1 volume of the gel. Make sure all bubbles are released from the gel in the column. Next, eluate the prepared column with 200 mL of each solvent systems that has been prepared; F-1:100%H2O, F-2: 25%MeOH, F-3: 50%MeOH, F-4: 75%MeOH, F-5: 100%MeOH, F-6: CHCl3:MeOH:H2O (64:25:4). Column elution could be enhanced by placing a vacuum filtering ring adapter between the bottom outlet of the column and collection flask. Then the adapter is fixed to a diaphragm vacuum pump. This will enhance column elution with the respective fractions without having a negative impact of the solvent gradient separation of the crude extract. Concentrate the collected fractions using rotary evaporator, transfer the respective fractions into a 20 mL borosilicate vial, label the vials, desiccate for 2 h, flush it with inert N2 gas, and store them in a 20  C freezer.

3.5 HPLC Optimization and Compound Separation

High-Performance Liquid Chromatography is an important tool in obtaining the crude extract profile and isolation of pure compounds from actinobacteria crude extracts and column chromatography column. First, a basic well-functioning HPLC with a well available selection of analytical and semi-preparative column is important. It is suggested that there should be a range of columns such as C18, C18(2), ODS-3, and phenyl-hexyl column types.

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There are basically three levels of HPLC analysis involved in the isolation of pure compounds from a crude extract from actinobacteria and the details are as stated below: Solvent Selection: Solvent selection is of primary importance, it involves basically double distilled H2O, methanol (MeOH), and acetonitrile (MeCN). Typical HPLC solvent reservoir is represented by A Solvent and B Solvent, although there are always a four-lane option. A solvent could be set as aqueous (30% MeOH or 30% MeCN) and B Solvent could be represented by 100% MeOH or 100%MeCN. It is vital that one uses the same analytical column to test the separation profile of the crude extract using both these solvents at a 0.5 mL/min at 210 nm. Based on the retention time of the peaks and separation profile, one could differ the time program used during the gradient run of the separation. A typical gradient run is; 0 min—30%B, 0–5 min—50% B, 5–40 min—100%B, 45 min—Stop, the flow rate for an analytical column (s50  4.6 mm) is basically set at 0.5 mL/min and 2.0 mL/min for a semi-preparative column (250  20 mm). If the separation is still not good after trying various solvent gradient program, then it is suitable that one changes the solvent from MeOH to MeCN. Crude sample concentration used in this process is in the range of 5 mg/mL, and a total volume of 5 μL is injected into the column. Column Selection: Column selection is also a very important procedure in establishing the suitable column needed for chemical profiling of crude extract, fractions, and/or pure compounds. Set a particular solvent system as the solvent choice, solvent gradient, then try this with several columns such as C-18, C-18(2), ODS-3, and Phenyl-Hexyl. One could use either analytical column types or semi-preparative columns during this process. Crude sample concentration used in this process is in the range of 5 mg/mL, and a total volume of 5 μL is injected into the column. Fraction Profiling: Once the solvent gradient and column type has been determined, it is important that one records the following HPLC Chromatographs: (1) Crude extract HPLC profile and (2) Fractions 1–6 profile. This has to be established to avoid any confusions of mistakes in the compound separation during the “Bioassay Guided Separation” process. Based on the Bioassay Guided Separation (See Note 2), fractions that exhibited positive bioassay results will be further separated using the same solvent gradient and column, to isolate sub-fractions based on their separation of the peaks. These sub-fractions are subjected to bioassay and the positive sub-fractions are again subjected to further purifications and removal of impurities to obtain a pure bioactive compound [9]. The bioactive HPLC purified compound could be tested for its purity using a simple TLC with molybdophosphoric acid or by measuring its 1H-NMR for 16 scans under the experimental conditions described below. The compound is considered pure if there are no other spots or blotches on the TLC or when there are no

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additional smaller peaks or impurities in the 1H-NMR spectrum. Once the compound is confirmed to be pure, then it will be subjected to 1D and 2D NMR, HR LCMS-IT-TOF, FTIR and Optical Rotation measurements. All these spectroscopic data will be used to elucidate the planar and stereochemistry of the isolated compounds. 3.6 1D and 2D NMR Data Acquisition

NMR spectroscopy data is important and needed to elucidate the basic and stereo structure of any isolated compounds. There are a minimum of six data sets needed to accomplish chemical structure 1 13 1 elucidation: (1) H-NMR, C-NMR, H-1H-COSY, 1 13 1 13 H- C-HSQC, H- C-HMBC, and NOESY. Due to the complex nature of the chemical entity, its functional moiety and electronegative atom, one needs to make some meticulous adjustment to the data points to be taken, relaxation delay and pulse sequence and flip angle. Below are some details of the minor adjustment that were utilized in the data acquisition for compounds isolated from actinobacteria. 1D-1H-NMR Measurement Parameters—Experiment: single_pulse.ex2. Acquisition: (1) x_domain: Proton, (2) x_offset: 5 ppm (center of the observation range), (3) x_points: 16384, (4) Scans: 8 or 16 (set according to your sample concentration), (5) x_prescans: 4 (number of dummy scans). Pulse Width: (1) x_angle: 45 [deg] (Flip angle. Set according to T1 and relaxation delay), (2) x_90_width: x90 (90 pulse width. Default value is automatically set), (3) Relaxation delay: 5 s (Delay between scans, set according to T1 and flip angle). 1D-13C-NMR Measurement Parameters—Experiment: single_pulse_dec.ex2. Acquisition: (1) x_domain: Carbon13, (2) x_offset: 100 ppm (center of the observation range), (3) x_sweep: 250 ppm, (4) x_points: 32768 (Number of data points determines the resolution), (5) Scans: 32 or 64 (Set according to your sample concentration), (5) x_prescans: 4 (Number of dummy scans). Pulse Width: (1) x_pulse: 7.9 ms, (2) iir_domain:Proton (Decoupled nucleus), (3) irr_offset: 5 ppm (Decoupler offset. Set the center of proton chemical shifts), (4) irr_pulse: 9.55 ms, (5) Selection_angle: 45 [Deg] (Set 45 for DEPT-45 , 90 for DEPT-90 , or 135 for DEPT-135 ), (6) j_constant: 140 Hz (1JCH coupling constant value. Set average or expected value), (7) Relaxation delay: 2 s (Delay between scans, set according to T1 values), (8) Decoupling: ON (Proton decoupling, increases the sensitivity), (9) irr_pwidth: 70 ms (Pulse width of 1H composite pulse decoupling), (10) irr_noise: WALTZ (1H decoupling sequence). 2D-1H-1H COSY Measurement—Experiment: dqf_cosy_phase.ex2.

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Acquisition: (1) x_domain: Proton, (2) x_offset: 4.58512 ppm (Center of the observation range, default value is 5 ppm), (3) x_sweep: 8.03360 ppm (Enter observation range, default value is 15 ppm), (4) x_points: 1024xn (Sample spectrum consists of 1024 points), (5) Scans: 16xn (Sample spectrum is obtained by 16 scans), (5) x_prescans: 4 (Number of dummy scans), y_points: 256xn (Sample spectrum consists of 256 points). Pulse: (1) x_pulse: 12.5 ms [90 ], (2) relaxation_delay: 1.5 s (Enter waiting time for repetition pulse sequence, default value is 1.5 s. Usually this is 1.3 times the estimated T1 value). 2D-1H-13C pfg Phase Sensitive HSQC Measurement—Experiment: hsqc_dec_phase_pfgzz.ex2. Acquisition: (1) x_domain: Proton, (2) x_offset: 4.69713 ppm (Enter a central position of the observation range in the f2 axis, default is 5 ppm), (3) x_sweep: 8.83364 ppm (Enter the observation range in the f2 axis, default value is 15 ppm), (4) x_points: 1024xn (Sample spectrum consists of 1024 points), (5) scans: 2xn scans (Sample data is obtained by 2 scans), (6) y_domain: Set the observation nucleus for the f2 axis, default is Carbon13, (7) y_offset: 98.13889 (Enter a center position for the observation range in the f1 axis, default value is 85 ppm), (8) y_sweep: 180.20039 (Enter the observation range in the f1 axis, default is 170 ppm), (9) y_points: 256xn (Sample spectrum consists 256 points), (10) x_prescans: 4. Pulse: (1) x-pulse: 12.5 ms (Enter a 90 pulse width for the observation channel (1H) in the f2 axis, default value is x90, stored in probe_file), (2) y_pulse: 11.2 ms (Enter a 90 pulse width for the observation channel (13C) in the f1 axis, default value is y90, stored in probe_file), (3) j_constant:140 Hz (Enter the 1JCH value, default value is 1 ms), (4) purge: 1 ms (Spin_lock_purge_pulse, default value is 1 ms), (5) relaxation_delay: 1.5 s (Enter 1.3 times the estimated T1 value), (6) grad_1_amp: 35% (Pulse output for the first FG pulse (PFG1), default is 35%), (7) grad_2_amp: 10% (Pulse output for the second FG pulse (PFG2), default value is 10%, (8) decoupling: ON (verify the check mark is 13C_decoupling). 2D-1H-13C pfg HMBC Measurement—Experiment: hmbc_pfg.ex2. Acquisition: (1) x_domain: Proton, (2) x_offset: 4.69713 ppm (Center point of the observation range in the f2 axis, default is 5 ppm), (3) x_sweep: 8.83364 ppm (Observation range in the f2 axis, default value is 15 ppm), (4) x_points: 2048xn (Sample spectrum consists of 2048 points), (5) x_prescans: 4, (6) scans: 4xn (sample data is obtained by 4 scans), (7) y_domain: Carbon13, (8) y_offset: 98.13889 (Enter a center position for the observation range in the f1 axis, default value is 100 ppm), (9) y_sweep: 180.20039 (Enter the observation range in the f1 axis, default is 250 ppm), (10) y_points: 256xn (Sample spectrum consists 256 points).

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Pulse: (1) x-pulse: 12.5 ms (Enter a 90 pulse width for the observation channel (1H) in the f2 axis, default value is x90, stored in probe_file), (2) y_pulse: 11.2 ms (Enter a 90 pulse width for the observation channel (13C) in the f1 axis, default value is y90, stored in probe_file), (3) j_constant:140 Hz (Enter the 1JCH value, default value is 140 Hz), (4) long_range_j: 8 Hz (Enter the 1JCH value, default value is 8 Hz), (5) relaxation_delay: 1.5 s (Set waiting time for pulse repetition, default value is 1.5 s, enter 1.3 times the T1 value), (6) grad_selection: PFG ratio to be applied to y_domain is displayed, (7) grad_1_amp: 60% (Pulse output for the first FG pulse (PFG1), default is 60%), (7) grad_2_amp: 60% (Pulse output for the second FG pulse (PFG2), default value is 60%), (8) grad_3_amp: 30.18% (Pulse output for the third FG pulse (PFG3), default value is calculated from the PFG ratio to be applied to y_domain and grad_1), (9) grad_recover: 0.1 ms (Circuit recovery time after FG pulse, default value is 0.1 ms). 2D-1H-1H Phase Sensitive NOESY Measurement—Experiment: noesy_phase.ex2. Acquisition: (1) x_domain: Proton, (2) x_offset: 4.58512 ppm (Enter a center position of the observation range, default value is 5 ppm), (3) 8.03360 ppm (Enter the observation range, default range is 15 ppm), (4) x_points: 1024xn, (5) scans: 4xn scans (sample spectrum is obtained by 4 scans), (5) x_prescans: 4, (6) y_points: 256xn (Sample spectrum consists of 256 points). Pulse: (1) x_pulse: 12.5 ms, (2) mix_time: set mixing time, default value is 500 ms, (3) relaxation_delay: 1.5 s (Enter a waiting time for repeating a pulse sequence, default is 1.5 s. Usually this value is set to 1.3 times the estimated T1 value. 3.7 HRIT-TOF-MS Data Acquisition

High resolution mass data is obtained using a LCMS IT TOF instrument as shown in Fig. 5. Compounds subjected to this analysis could be pure compounds or partially pure compound with 10% of impurities in them. There are two basic intentions of doing this analysis: (1) In the case of pure compounds, the NMR 1D and 2D data would have been obtained, analysis is done to confirm the chemical formula, millimass unit, and unsaturation index, (2) In the case of impure compound, this is usually done before the 1D and 2D NMR data is obtained, the mass data will be used to search the novelty of this compound in databases such as Marinlit or Science Finder, in an effort to verify the compound’s novelty. Compounds are usually dissolved in appropriate organic solvent to ensure it dissolves completely and 1 mL is injected via Rheodyne Injection Port either directly to the mass analyzer (in the case of pure compounds) or via Rheodyne Injection Port at the mass analyzer. Resulting data is processed using LabSolution Software that has Formula Predictor functions [10].

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Fourier Transform Infrared (FTIR) is used to obtain the functional groups such as hydroxyl, ketone, aldehydes, carbonyl, ether bridge, and benzene functionality in a given organic compound. It identifies chemical bonds in a molecule by producing an infrared absorption spectrum. The spectra produce a profile of the sample, a distinctive molecular fingerprint that could be used to identify functional groups in the analyzed compound. Sample preparation could be done using three basic accessories: 1. KBr Pellet: This technique is ideal for solid compounds, where the pure compound is mixed with a small amount of KBr and ground using a quartz mortar and pistil as shown in Fig. 7a. Resulting powder is filled into a mold and subjected to high pressure, pellet that is approximately 10–12 mm in diameter is mounted onto the Spectrum Two FTIR (Perkin Elmer, USA) and data taken.

Fig. 7 Fourier Transform Infrared complete with (a) Compound-KBr pelleting accessories, (b) Liquid and Gum type compound mounting accessories, (c) Diamond ATR-Perkin Elmer FTIR

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2. KBR Window: This technique is suitable for compounds that are in the form of liquid or semi-solid/gum. It consists of two KBr or NaCl circular windows. A small quantity of the compound is introduced onto one side of the window and sandwiched with the other pair. The pair of KBr/NaCl window is then mounted between its holder as shown in Fig. 7b and inserted into the analysis path of the Spectrum Two FTIR (Perkin Elmer, USA) and data taken. 3. Diamond ATR: This technique is ideal for a very small amount of compound regardless of its physical form, although it is best for solids and thin film. Small piece of this compound is placed on the tiny spot of ATR and pressure it with the upper pressor as shown in Fig. 7c. Data could then be taken, cleaning for the next sample is also simple and easy. Optical rotation, also known as polarization rotation or circular birefringence, is the rotation of the orientation of the plane of polarization about the optical axis of linearly polarized light as it travels through certain compounds. Solutions of chiral compounds have the property of rotating plane-polarized light passed through them. That is, the angle of the light plane is tilted to the right or to the left after emerging from the sample. Compound exists in nature as enantiomer, each enantiomer of a stereoisomeric pair is optically active and has an equal but opposite-in-sign specific rotation. In chemical structure elucidation process, optical rotation value is needed to determine its chiral orientation. 1. Autopol IV Polarimeter is used for this measurement, it comes with sample cell length of 50 mm, 100 mm, or 200 mm. Set the temperature of the measurement chamber and let it to reach constant equilibrium. First, organic solvent that will be used to dissolve the compound gas to be filled into the cell and its reference blank data taken. Once data is taken, empty the cell and use the same cell for compound measurement. 2. Then, a specific amount of precisely measured compound (2–10 mg) is dissolved in a 2 mL AR Grade chloroform or methanol and introduced into the sample cell, data taken with a push of a button on the instrument. Present model AutoPol IV has multiple wavelength function and is capable of measuring optical rotation value and specific rotation value.

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Notes 1. The soil samples or other specimens (1.0 g) were diluted in sterile water to prepare a 10 3 g/mL suspension. The suspension (300 μL) was inoculated onto humic acid-vitamin (HV) agar and incubated at 28  C for 14 days. HV agar was prepared as previously described in the purification of the bacterial

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strains. Isolation of differentiated bacterial colonies was performed by replating different colonies on coconut mannitol (CM) agar plates containing 20 g L 1 coconut powder (Green Organic), 20 g L 1 mannitol (Sigma-Aldrich), and 20 g L 1 agar (Difco). Plate dilution method was used to isolate actinobacteria from the sample suspension. Approximately 0.1–0.2 mL of each sample (10 2 and 10 3 dilutions) was used to coat the plates and cultivated for 7 days in a moist chamber at 55  C. Single actinomycete colony is picked to inoculate an agar slant containing the same isolation medium. Other agar plates such as Czapek medium, Glycerol Asparagine medium, and Oatmeal medium could also be used for subculture depending on the affinity of the isolate to grow. 2. Bioassay guided separation is a set of protocol that is used to systematically screen the crude extract, fractions and sub-fraction and HPLC peaks against the desired bioassay in order to identify the bioactive fractions and ultimately compounds. References 1. Menegatti C, Lourenzon VB, RodriguezHernandez D, Paixao-Melo WG, Ferreira LLG, Andricopulo AD, Nascimento FS, Pupo MT (2020) Meliponamycins: antimicrobials from stingless bee-associated Streptomyces sp. J Nat Prod 83:610–616 2. Lee SR, Schalk F, Schwitalla JW, Benndorf R, Vollmers J, Kaster AK, de Beer ZW, Park M, Ahn MJ, Jung WH, Beemelmanns C, Kim KH (2020) Polyhalogenation of isoflavonoids by the termite-associated Actinomadura sp. RB99. J Nat Prod 83:3102–3110 3. Schneemann I, Ohlendorf B, Zinecker H, Nagel K, Wiese J, Imhoff JF (2010) Nocapyrones A-D, g-Pyrones from a Nocardiopsis strain isolated from the marine sponge Halichondria panicea. J Nat Prod 73:1444–1447 4. Salwan R, Sharma V (2020) Molecular and biotechnological aspects of secondary metabolites in actinobacteria. Microbiol Res 231:126374 5. Golinska P, Wypij M, Agarkar G, Rathod D, Dahm H, Rai M (2015) Endophytic actinobacteria of medicinal plants: diversity and bioactivity. Antonie van Leeuwenhoek 108 (2):267–289 6. Cockerill FR et al (2012) Methods for dilution antimicrobial susceptibility tests for bacteria

that grow aerobically; approved standard, 9th edn. CLSI, Wayne, p 12. ISBN1-56238-784-7 7. Akiyama H, Indananda C, Thamchaipenet A, Motojima A, Oikawa T, Komaki H, Hosoyama A, Kimura A, Oku N, Igarashi Y (2018) Linfuranones B and C, Furanonecontaining polyketides from a plant-associated Sphaerimonospora mesophile. J Nat Prod 81:1561–1569 8. Jin Y, Aobulikasimu N, Zhang Z, Liu C, Cao B, Lin B, Guan P, Mu Y, Jiang Y, Han L, Huang X (2020) Amycolasporins and Dibenzoyls from lichen-associated Amycolatopsis hippodrome and their antibacterial and anti-inflammatory activities. J Nat Prod 83:3545–3553 9. Balde MA, Tuenter E, Mateeussen A, Traore S, Cos P, Maes L, Camara A, Diallo MST, Balde ES, Balde AM, Pieters L, Foubert K (2021) Bioassay-guided isolation of antiplasmodial and antimicrobial constituents from the roots of Terminalia albida. J Ethnopharmacology 267:113624 10. Vairappan CS, Zanil II, Kamada T (2014) Structural diversity and geographical distribution of halogenated secondary metabolites in red algae, Laurencia nangii Masuda (Rhodomelaceae, Ceramiales) in the coastal waters of North Borneo Island. J Appl Phycol 26:1189–1198

Chapter 44 Miniaturized Production of Bioactive Extracts from Actinobacteria Abirami Baskaran, Radhakrishnan Manikkam, Manigundan Kaari, Jerrine Joseph, Gopikrishnan Venugopal, and Balagurunathan Ramasamy Abstract Antibiotic resistance occurs when the bacteria gain resistance across a whole class of drugs with similar mechanism of action. This could be wide and rapid, which alleviates the need for the discovery and development of novel antibiotics. Reports have shown that of all the microbial bioactive metabolites nearly 45% were produced by actinobacteria, with 80% of such secondary metabolites being produced by the genus Streptomyces. The metabolic and physiological properties of Actinobacteria range from production of extracellular enzymes to secondary metabolites. The discovery of useful bioactive compounds can be significantly increased with the persistent progress in science and technology from novel actinobacterial species. The existing agar methods for production of metabolites are rather time consuming with less scope. A novel, economic and complementary approach to screening bioactive molecules is by reproducing the cultures in small scale. This is achieved by growing the strains on agar medium inside 2 ml microcentrifuge tubes, evaluating their growth and production of secondary metabolites which subjected to extraction using solvents, finally tested for antimicrobial activity against pathogens. This procedure can avoid metabolite losses which are usually observed in normal extraction procedures. Key words Actinobacteria, Secondary metabolites, Microcentrifuge tubes, Antimicrobial activity, Antibiotics

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Introduction Infections from multidrug-resistant bacteria stand in the top three threats affecting public health globally and this is a consequence from misusing and overusing antibiotics, more importantly lack of novel antibiotics with upgraded mechanisms of action [1]. Bioactive metabolites produced by actinobacteria have proven to be resilient sources of novel antibiotics with antibacterial, antifungal, anticancer properties, to name a few. Actinobacteria represent one of the most diverse phyla within the bacterial domain, with phenotypically

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_44, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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diverse organisms widely distributed in aquatic and terrestrial ecosystems. In addition, actinobacteria exhibit bioactivity producing compounds such as phytotoxins, immunosuppressors, enzyme inhibitors, biosurfactants, nanoparticles, and biopesticides. This makes them significant resource in biotechnological, medical, and pharmaceutical applications [2]. Despite being rich sources of secondary metabolites, screening of actinobacteria in large numbers in search of antibiotics and other significant products has its own limitations with the agar methods in use which is highly errorprone. It could be really beneficial to cultivate organisms with favorable resources in small scale [3]. There’s a desperate need for a screening approach that will be both time- and cost-efficient that can improve the process of production of bioactive extracts substantially. Large-scale analysis of bacterial screening could be done by pharm giants using highly specialized instruments which are inaccessible for institutions and organizations with limited facilities and resources. Since this should not restrict anyone to the contribution towards research, an innovative strategy was followed wherein the actinobacterial cultures to be screened for production of bioactive extracts were grown on solid agar media inside 2 ml microcentrifuge tubes, incubated and the extracts were tested for antimicrobial activity using diffusion disks. It is challenging to grow Streptomyces and other mycelial organisms in small scale since their secondary metabolite production must be evaluated for their reproducibility. This process was validated by Radhakrishnan et al. 2012 [4] and reported to be highly efficient and time saving.

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Materials 1. Microcentrifuge tubes (2 ml). 2. ISP2 agar. 3. Nutrient agar. 4. Incubator. 5. Centrifuge. 6. Bacterial pathogens—S. aureus; E. coli. 7. Methanol. 8. Sterile glass rod. 9. 4  C incubator. 10. Inoculation loop. 11. Sterile filter paper disk. 12. Dimethyl sulfoxide (10%). 13. Forceps. 14. Micropipette.

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Methods

3.1 Miniaturized Production of Bioactive Compounds

1. Add 0.5 ml of ISP2 agar medium in 2 ml microcentrifuge (eppendorf) tubes and sterilize by autoclaving at 121  C for 15 min. 2. Prepare agar slants by maintaining the tubes in a tilted posture until solidification. 3. Inoculate actinobacterial spores onto the agar slants using inoculation loop and incubate for 7–14 days at 28  C.

3.2 Extraction of Bioactive Compounds

1. Post incubation, extract the bioactive compounds using solidliquid extraction method. 2. Add 1 ml of methanol onto the inoculated tubes and blend using sterile glass rod. 3. Allow the tubes for extraction at 4  C for 18–24 h. 4. Centrifuge the tubes at 11200  g for 10 min to separate the solvent extract portion from the agar medium. 5. Concentrate the solvent portion by evaporation under fume hood or using eppendorf concentrator at 30–45  C for 10–30 min to get the crude extract.

3.3 Antimicrobial Activity

1. Test the antimicrobial activity of obtained extract using disk diffusion method. 2. Dissolve the crude extract by adding 100 μl methanol or 10% DMSO (sterile). 3. Add 10 μl of crude extract on to sterile filter paper disk with 5 mm diameter and let dry. 4. Inoculate the test bacterial pathogens like S. aureus and E. coli on nutrient agar plates using sterile cotton swab. 5. Place the extract infused disks onto nutrient agar plates inoculated with bacterial and fungal pathogens. 6. Incubate the plates at 37  C for 24 h and observe for zone of inhibition (see Note 1). Note the results in Table 1.

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Notes 1. Appearance of inhibition zone around the extract impregnated disk indicates the presence of bioactive compounds in the crude extract, whereas the absence of inhibition zone around the

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Table 1 Antimicrobial activity of bioactive extracts Extract No

Test pathogens (Zone of inhibition expressed in mm) S. aureus

E. coli

extract impregnated disk indicates the absence of bioactive compounds in the crude extract. References 1. Murray EM, Allen CF, Handy TE, Huffine CA, Craig WR, Seaton SC, Wolfe AL (2019) Development of a robust and quantitative highthroughput screening method for antibiotic production in bacterial libraries. ACS Omega 4 (13):15414–15420 2. Azman AS, Othman I, Velu SS, Chan KG, Lee LH (2015) Mangrove rare actinobacteria: taxonomy, natural compound, and discovery of bioactivity. Front Microbiol 6:856

3. Minas W, Bailey JE, Duetz W (2000) Streptomycetes in micro-cultures: growth, production of secondary metabolites, and storage and retrieval in the 96–well format. Antonie Van Leeuwenhoek 78(3–4):297–305 4. Radhakrishnan M, Priya J, Balagurunathan R et al (2012) Miniaturized fermentation in eppendorf tubes for the detection of antagonistic actinomycetes. Int J Bioassays 1(9):30–35

Chapter 45 Screening, Characterization, and Identification of Antibacterial Compounds from Actinobacteria T. Savitha, Ashraf Khalifa, and A. Sankaranarayanan Abstract The presence of active ingredients (secondary metabolites) present in the natural products is always in lesser quantities. The lab-intensive and time-consuming extraction and isolation process has been the difficult task in exploring natural products for drug development. Extraction is the first step to separate the desired natural products from the plants, marine organisms, or microbial fermentation medium. Liquid-liquid extraction method is very commonly used for the extraction of bioactive compounds from Actinobacteria. The components present in the natural extract are complex and contain a variety of natural products that require further separation and purification to obtain the active compounds. The separation depends on the physical or chemical difference of the individual compounds present in the crude extract. Chromatographic techniques are the commonly used methods used to obtain pure natural products from a complex mixture. Key words Secondary metabolites, Bioactive compounds, Extraction, Chromatographic analysis

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Introduction The phylum Actinobacteria contains several hundred bacterial species that are found in soil, fresh water, and marine environments. They well knew for their production of various antibiotics and similar metabolites. Nearly 70–80% of the commercially available secondary metabolites are isolated and characterized from different species of Actinomycetes [1]. Natural compounds from microbes, especially from Actinomycetes, gain much attention and become a novel source of pharmacologically active biomolecules having immense chemical and biological activity. Hence, they may be explored from various ecological habitats are being continuously investigated for search of novel antimicrobial compounds [2]. Actinobacteria have the capacity to synthesize different biologically active secondary metabolites such as cosmetics, vitamins, nutritional materials, herbicides, antibiotics, pesticides, anti-parasitic compounds and enzymes like cellulose and xylanase, used in water

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treatment [3]. In the present scenario, nearly 80% of the antibiotics are produced from Streptomyces sp., widely distributed in soil, and their ability to produce novel antibiotics and non-antibiotics lead molecules caused these bacteria to be targeted in drug screening program. Discovery of novel antibiotics from Actinobacteria is important in helping to cope with the growing proportion of antibiotic-resistant bacterial infections that become untreatable. Hence, the procedure framed for the successful screening, characterization, and identification of antibacterial compounds from Actinobacteria.

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Screening of Actinobacteria for Antimicrobial Activity

2.1 Primary Screening 2.1.1 Materials Required

1. Pure actinobacterial culture. 2. Test bacterial standard cultures (Staphylococcus aureus (ATCC 25923), Escherichia coli (ATCC 25922)). 3. Nutrient agar medium. 4. Inoculation loop, etc.

2.2

Procedure

Primary screening for evaluating the antibacterial potential of the axenic culture is performed by perpendicular streak method of [4]. 1. Actinobacterial isolates which are screened for antagonist study is inoculated as single streak in the middle of nutrient agar medium. 2. Incubate the inoculated plates for 4 days at 28
C. 3. Following incubation, subsequently, seed the plate with the test bacterial culture (Staphylococcus aureus (ATCC 25923), Escherichia coli (ATCC 25922) by single streak at a 90
angle to the streak of the producer strain. 4. Again incubate the inoculated plates for 1–2 days at 28
C. 5. Following incubation, analyze the distance of incubation as measure as mm. Microbial stains showing moderate to good inhibition activity are selected for secondary screening.

2.3 Secondary Screening

1. Pure actinobacterial culture.

2.3.1 Materials Required

3. Saline.

2. Nutrient broth. 4. Starch Casein Broth (SCB) {10.0 g soluble starch, 0.3 g casein, 2.0 g KNO3, 2.0 g NaCl, 2.0 g K2HPO4, traces of MgSO4.7H2O, CaCO3, FeSO4.7H2O, Distilled water—1 L, pH 6.8}. 5. Orbital shaker, etc.

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Procedure

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Subject the selected Actinobacteria with antibacterial activity to secondary screening by well-diffusion method. 1. Inoculate the test bacterial culture into 10 mL nutrient broth. 2. Incubate at 37
C for 2–4 h. 3. Standardize the turbidity to 0.5 McFarland standards using sterile physiological saline, corresponding to the absorbance 0.0–0.13 at 625 nm. 4. Inoculate active actinobacterial cultures into 50 mL of SCB medium. 5. Incubate it in an orbital shaker of 200 rpm at 30
C for 6 days. 6. Following incubation, centrifuge the broth cultures at 112  g for 10 m. 7. Collect the supernatant aseptically and test their antibacterial activity against test cultures. 8. In well-diffusion assay, aseptically made wells (6 mm in diameter and 5 mm in depth) on nutrient agar plate containing fresh test bacterial lawn cultures using cork-borer and each well are loaded with 100 μL of actinobacterial extract. 9. Incubate the plates at 37
C for 24 h. 10. Following incubation, measure zone of inhibition as mm. 11. Use Ampicillin (23 μg/mL) and empty well without any antibiotic or extract as positive and negative control, respectively [5].

2.5 Extraction of Antibacterial Compounds from Actinobacteria

1. Pure actinobacterial culture.

2.5.1 Materials Required

5. Orbital shaker.

2. Nutrient broth. 3. Saline. 4. SCB. 6. Whatman filter paper. 7. Solvents (Acetone, Chloroform, Ethanol, Ethyl acetate, Methanol, Petroleum ether, Xylene), etc.

2.6

Procedure

1. Inoculate the active actinobacterial cultures on to 100 mL of SCB. 2. Incubate at 30
C in a shaker at 200 rpm for 6 days. 3. Filter the broth culture by using Whatman No 2 filter paper (11 μm). 4. Use Millipore filters (0.45 μm) for organic solvent extraction (Acetone, Chloroform, Ethanol, Ethyl acetate, Methanol, Petroleum ether, Xylene) to the culture filtrate in the ratio of 1:1 (v/v).

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5. Shake the mixture vigorously for 5 min. 6. Collect the supernatant and preserved at 4
C. 7. Determine the antibacterial activities of the solvent extracts by well-diffusion assay as described previously. 2.7 Physicochemical Characterization of Bioactive Metabolites from Actinobacteria

2.7.1 Materials Required

Characterization of bioactive secondary metabolites has direct influence on the physical, chemical, and biological properties of the specific compound of a selected strain. Early detection of the specific chemical compounds present in the crude extract is of great interest for the selection of purification methods, in which desirable product can be obtained. There are various preliminary screening methods commonly available for the detection of chemical group of a particular compound [6, 7]. 1. Pure actinobacterial culture. 2. Methanol. 3. Solvents (acetone, chloroform, dichloromethane, diethyl ether, ethyl acetate, n-hexane, dimethyl sulfoxide). 4. Sodium hydroxide. 5. Hydrochloric acid. 6. Sodium bicarbonate. 7. Copper acetate. 8. Dragendorff’s reagent. 9. Wagner’s reagent. 10. Lead acetate solution. 11. Ammonia. 12. Ferric chloride. 13. Benedict’s reagent. 14. Fehling’s A and B solution. 15. Potassium hydroxide, etc.

2.8

Procedure

1. Color and consistency. Determine the color and consistency of the sample by direct observation. 2. Solubility test. Dissolve 1 mg of purified compound in 10 mL of solvents such as water, methanol, acetone, chloroform, dichloromethane, diethyl ether, ethyl acetate, n-hexane, and dimethyl sulfoxide.

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Screening of Chemical Compounds

3.1 Test for Terpenoids

To 100 μg of sample, add 2 mL of chloroform and 3 mL of concentrated H2SO4 to form a layer. Formation of reddish-brown coloration of the precipitate at the interface indicates the presence of terpenoids.

3.2 Test for Diterpenes

To 100 μg of sample, add three to four drops of copper acetate solution. Formation of emerald green color indicates the presence of diterpenes.

3.3

Dragendorff’s test: To 100 μg of sample, add 1 mL of Dragendorff’s reagent (solution of potassium bismuth iodide). Formation of red precipitate indicates the presence of alkaloids. Wagner’s test: To 100 μL of sample, add 1 mL of Wagner’s reagent (Iodine in potassium iodide). Formation of brown/reddish precipitate indicates the presence of alkaloids.

Test for Alkaloids

3.4 Test for Carotenoids

To 100 μg of sample, add 1 mL of chloroform and shake vigorously. The resulting mixture mixed with 85% H2SO4. A blue color at the interface shows the presence of carotenoids.

3.5 Test for Flavanoids

Alkaline reagent test: To 100 μg of sample, add 3–4 drops of 20 % NaOH solution. A change to yellow colour which on the addition of acid changed to colorless solution depicted the presence of flavonoids. Lead Acetate test: Treat the test sample with few drops of lead acetate solution. Formation of yellow color precipitate indicates the presence of flavonoids.

3.6 Test for Anthraquinones

To 100 μg of sample, add 2 mL of 10% HCL for 5 min. Then partition the solution against equal volume of chloroform and transfer the chloroform layer to a clean, dry test tube. Add equal volume of 10% ammonia solution to the chloroform layer; shake well and allow them to separate. Observe the separated aqueous layer for any color change; delicate rose pink color shows the presence of anthraquinones.

3.7 Test for Glycosides

Treat 100 μg of sample with ferric chloride solution and immerse in boiling water for about 5 min. Cool the mixture and extract with equal volume of benzene. Separate the benzene layer and treat with ammonia solution. Formation of rose-pink color in the ammoniacal layer indicates the presence of anthranol glycosides.

3.8 Test for Reducing Sugars

Benedict’s test: Treat 1 mL of sample with Benedict’s reagent and heat gently. Orange red precipitate indicates the presence of reducing sugars.

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Fehling’s test: Treat 1 mL of sample with diluted HCL, neutralize with alkali and heated with Fehling’s A and B solutions. Formation of red precipitate indicates the presence of reducing sugars. 3.9

Test for Tannins

To 100 μg of sample, add about 1 mL of distilled water and two to three drops of ferric chloride. Appearance of bluish-black or brownish green precipitate indicates the presence of tannins.

4 Purification of Antibiotic Compounds from Actinobacteria by Thin-Layer Chromatography Thin-Layer Chromatography (TLC) is an extremely valuable analytical technique in the detection of compounds in the crude mixture. It is normally done on a small glass or plastic plate coated with a thin layer of a solid support—silica gel, which acts as a stationary phase. The mobile phase is an organic solvent or solvent mixture. The test sample is applied near the bottom of the plate as a small spot, and then placed in a jar containing few mL of solvent. The solvent travels up the plate by capillary action, carrying the sample mixture along with it. Each compound in the mixture moves at a different rate, depending on its solubility in the mobile phase and the strength of its absorption to the stationary phase. When the solvent gets near the top of the plate, it is allowed to evaporate, leaving behind the components of the mixture at various distances from the stationary phase. 4.1 Materials Required

1. Actinobacterial extract. 2. TLC sheet/plate. 3. Capillary tube. 4. Solvents used: acetone, methanol, n-hexane, ethyl-acetate, chloroform, dichloromethane, water. 5. TLC chamber. 6. UV torch. 7. Visualizing reagents: Iodine crystals, ninhydrin, vanillin, and H2SO4.

4.2

Procedure

1. Dissolve the given actinobacterial extract in respective solvent, and collect the solvent extract by allowing the debris to settle down. 2. Take the silica gel-coated TLC sheet and cut using scissors with the required size (e.g., 1.5 cm  5 cm). 3. Take the extract in capillary tube and spot at the bottom of the TLC sheet, and allow to air dry.

Screening, Characterization, and Identification of Antibacterial Compounds. . .

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4. First run the extract in 100% of each solvent individually to know the separation of solvent with different polarity. 5. Then prepare the solvent system using different solvents at different ratio. 6. Run the chromatogram in different solvent systems. 7. Mark the solvent front after the solvent reaches the maximum. 8. Allow the chromatogram to air dry. 9. Prepare the different visualizing reagents. 10. Observe the TLC chromatogram under the naked eye, under UV light, by exposing iodine crystals and/or spraying ninhydrin and/or vanillin-H2SO4 solution. 11. Then mark the separated spots and measure the distance moved by them. 12. Calculate the Rf value by applying the formula: Rf value ¼ Distance moved by the solute/distance moved by the solvent.

References 1. Khanna M, Solanki R, Lal R (2011) Selective isolation of rare Actinomycetes producing novel antimicrobial compounds. Int J Adv Biotechnol Res 2:357–375 2. Valliappan K, Sun W, Li Z (2014) Marine Actinobacteria associated with marine organisms and their potentials pharmaceutical natural products. Appl Microbiol Biotechnol 98(7):7365–7377 3. Ogunmwonyi IH, Mazomba N, Mabinya L, Ngwenya E, Green E, Akinpelu DA (2010) Studies on the culturable marine Actinomycetes isolated from the Nahoon beach in the Eastern Cape Province of South Africa. Afr J Microbiol Res 4(21):2223–2230 4. Madigan MT, Martiko JM, Parker J (1997) Antibiotics: isolation and characterization. In: Madigan MT (ed) Brock biology of microorganisms, 8th edn. Pearson, New York, pp 440–442

5. Cholarajan A, Vijayakumar R (2013) Isolation, identification, characterization and screening of antibiotic producing Actinobacteria from the crop fields of Thanjavur district, Tamilnadu, India. Int J Rec Sci Res 4(1):55–60 6. Rao RKV, Mani P, Satyanarayana B et al (2017) Purification and structural elucidation of three bioactive compounds isolated from Streptomyces coelicoflavus BC 01 and their biological activity. 3 Biotech 7(1):24 7. Uzair B, Menaa F, Khan BA et al (2018) Isolation, purification, structural elucidation and antimicrobial activities of kocumarin, a novel antibiotic isolated from actinobacterium Kocuria marina CMG S2 associated with the brown seaweed Pelvetia canaliculata. Microbiol Res 206:186–197

Chapter 46 Isolation, Identification, and Screening of Polyene Antifungal Compound Producing Streptomyces sampsonii MDCE7 from Agroforestry Soil Srinivasan Radhakrishnan and Mohan Varadharajan Abstract Actinomycetes presently known as Actinobacteria are widely found in diverse environment. Actinomycetes population were found maximum between the depths of 10–20 cm upper layer of the soil. They are morphologically distinct including white, gray, pink, brown, grayish white, green, and red color colonies. Most of the isolates were morphologically white. A number of Actinomycetes were reported as well known for biocontrol agents, which has the capability to suppress numerous fungal pathogens. Streptomyces species was dominant among the soil actinomycetes and producing 80% of secondary metabolites include antifungal agents that degrade cell walls and inhibit the synthesis of mannan and β-glucan enzymes. Calcium carbonate (CaCO3) pre-treatment method is commonly used to isolate actinomycetes from soils. Streptomyces spp. are identified based on the colony morphology, staining methods, spore shape and arrangement, biochemical tests, and physiological tests; its antifungal traits were characterized by in vitro screening methods such as agar streak, agar disk, and dual culture method; its polyene antifungal compound was characterized by UV visual spectrophotometric method in 95% methanolic extract. Key words Actinomycetes, Streptomyces, Calcium carbonate, Secondary metabolites, Fungal pathogens, Starch casein agar medium

1

Introduction Actinomycetes are Gram-positive, belong to the phylum Actinobacteria and order Actinomycetales and their DNA are rich in G + C content with the GC% of about 50–70% and they are widely distributed in aquatic and terrestrial habitats [1, 2]. They are aerobes, facultative anaerobes or anaerobes, which have a rigid cell wall that contains muramic acid and some contains teichoic acids. Actinomycetes have well-developed radial mycelium, which can be divided into substrate mycelium and aerial mycelium according to morphology and function. Some Actinobacteria can form complicated structure, such as spore, spore chain, sporangia, and

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_46, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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sporangiospore. Actinobacteria have different cultural characteristics in various kinds of cultural media, which are important in the classification identification, general with spores, aerial hyphae, with or without color and the soluble pigment. Actinomycetes have provided many important and an unprecedented amount of novel microbial products. They produce approximately about two-thirds of naturally occurring known antibiotics produced by all microorganisms [3]. The Actinomycetes produces an enormous amount of antibiotics, bioactive metabolites, enzymes, growth hormones, as well as plant growth promoting substances and many are excellent biocontrol agents used in protecting plants against phyto-pathogens [4–7].

2

Materials

2.1 Isolation of Actinomycetes from Agroforestry Soil Samples

1. Soil samples. 2. Sterile polythene bag. 3. Distilled water. 4. Calcium carbonate (CaCO3). 5. Starch Casein agar medium (SCA) (Soluble starch—10 g/l, K2HPO4—2 g/l, KNO3—2 g/l, Casein—0.3 g/l, MgSO4.7H2O—0.05 g/l, CaCO3—0.02 g/l, FeSO4.7H2O—0.01 g/l). 6. Petri plates, conical flasks, micropipettes. 7. Orbital shaker (25
C) and incubator (30
C).

2.2 Screening of Actinomycetes Isolates for its Antifungal Activity against Fungal Phyto-Pathogens

1. Pure cultures of Actinomycete isolates.

2.3 Characterization of Streptomyces sampsonii MDCE7

1. For morphological, cultural, and biochemical characteristics, refer the methods as described in the International Streptomyces Project (ISP) [2, 8].

2. Fungal pathogens (Fusarium oxysporum, Rhizoctonia solani, and Sclerotium rolfsii). 3. Potato Dextrose Agar (PDA) (infusion from potatoes—200 g/ l, dextrose—20 g/l, agar—15 g/l, pH —5.6  0.2). 4. SCA.

2. Physiological characterization—Growth on different concentrations of NaCl, pH and temperature in SCB; growth in the presence of 0.01% sodium azide and 0.001% potassium tellurite in SCB.

Isolation, Identification, and Screening of Polyene Antifungal Compound. . .

2.4 CharacterizationofPolyenes Antifungal Compound Produced by Streptomyces sampsonii MDCE7 Using UV Visual Spectrophotometric Method

3

381

1. ISP-2 (Yeast extract—4 g/l, Malt extract—10 g/l, Dextrose— 4 g/l). 2. 95% methanol. 3. Separating funnel. 4. UV visual double beam PC based spectrophotometer.

Methods

3.1 Isolation of Actinomycetes from Agroforestry Soil Samples [9, 10]

1. 10 g of air dried soil is mixed with 1% of calcium carbonate (CaCO3) and incubated at 50
C for 30 min. 2. After incubation, add the pre-treated 10 g soil into 90 ml of sterile distilled water. 3. The soil suspension is shaken vigorously under room temperature (25  2
C) on an orbital shaker at 200 rpm for 30 min and serially diluted up to 105 dilution. 4. Add 200 μl samples from the serially diluted soil suspension onto starch casein agar (SCA) plates and perform spread plate technique. 5. All the plates are incubated at 28  2
C for 1–2 weeks. 6. After incubation, emerging Actinomycetes are picked and streaked onto fresh SCA plates and incubated at 28  2
C for 1 week. 7. Pure cultures are maintained at SCA slants. 8. Colony forming units (CFU) of Actinomycetes per one gram of soil is determined by using the formula. CFU/g ¼ Total no. of colonies counted/sample volume taken from dilution  dilution factor. 1. One loopful of each isolates is streaked as a straight line on Starch Casein Agar (SCA) medium and incubated at 28  2
C for 6 days.

3.2 Screening of Actinomycetes Isolates for Its Antifungal Activity Against Fungal Phyto-Pathogens

2. After the sixth day, the test fungal pathogens (F. oxysporum, R. solani, S. rolfsii) are streaked at right angle, but not touching each other, and then incubated at 28  2
C for 48 h.

3.2.1 Agar Streak Method

3. Measure the zone of inhibition against each test fungal pathogen and the values are expressed in millimeter (mm) (Fig. 1).

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F. oxysporum (control)

S. rolfsii (control)

R. solani (control)

Test

Test

Test

Fig. 1 Determination of antagonistic activity of Actinomycetes isolates against F. oxysporum, S. rolfsii, and R. solani by agar streak method 3.2.2 Agar Disk Method

1. Actinomycetes isolates are inoculated on SCA medium and incubated at 28
C for 5–7 days. 2. After incubation, from well-grown Actinomycetes isolates, 6 mm agar disks are prepared by using sterile cork borers. 3. Disks are then aseptically transferred to PDA plates having fresh lawn cultures of F. oxysporum, R. solani, and S. rolfsii. 4. Controls included using plain disks from SCA medium. 5. Plates are incubated at 24
C for 4–6 days and fungicidal activity is evaluated by measuring the diameter of inhibition zones (mm) (Fig. 2).

3.3 Dual Culture Method

1. Mycelial disks (5 mm diameter) of the selected fungal pathogens (F. oxysporum, R. solani, and S. rolfsii) are placed at one end of the Petri plate.

Isolation, Identification, and Screening of Polyene Antifungal Compound. . .

F. oxysporum

R. solani

383

S. rolfsii

Fig. 2 Determination of antifungal activity of Actinomycetes isolates against F. oxysporum, S. rolfsii, and R. solani by agar disk method

2. The Actinomycetes antagonists are streaked 1 cm away from the periphery of the Petri plate just opposite to the mycelial disk of the pathogen. 3. Simultaneously inoculate with fungal pathogen at one end of the Petri plate and this serve as control. 4. Visual observation on the inhibition of pathogenic fungal growth is recorded after 96 hours of incubation at 28 
C (Fig. 3). 5. Measure the radial growth of mycelium in mm and percent inhibition (PI) is calculated by using the below mentioned formula: Percent Inhibition ¼

C T  100 C

where C is the growth of test pathogen (mm) in the absence of the antagonistic isolate; T is the growth of test pathogen (mm) in the presence of the antagonistic isolate. 3.4 Characterization of Streptomyces sampsonii MDCE7

1. Perform the staining technique and other biochemical test as per methods as described in the International Streptomyces Project (ISP) [2, 8]. 2. Infer the results with already available results of Streptomyces sampsonii (Table 1: Plate 1). 3. Prepare the SCB medium supplemented with different concentration of NaCl (i.e., 2, 5, 7, 9, and 12%), effect of seven different pH (4.0–10.0) and temperatures (i.e., 4
, 15
, 25
, 37
, 42
, and 55
C), sodium azide (0.01%) and potassium tellurite (0.001%). 4. Inoculate one loop full of Streptomyces sampsonii MDCE7 into sterilized SCB broth medium with above conditions and incubate for 7–12 days at 28
C  2
C. 5. After incubation, to confirm the growth of S. sampsonii MDCE7, one loop full of sample is streaked on SCA plates and incubate for 7–12 days at 28
C  2
C.

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F. oxysporum (control)

Test

R. solani (control)

Test

S. rolfsii (control)

Test

Fig. 3 Determination of antifungal activity of Actinomycetes isolates against F. oxysporum, S. rolfsii, and R. solani by dual culture method

6. Observe the plates. Observe the SCA plates, if the growth of S. sampsonii MDCE7 is present, which indicates positive results and infer the results with already available results of S. sampsonii in Table 1. 7. Microscopic examination: Formation of aerial mycelium, substrate mycelium, and spores are studied by light microscopy and the spore surface and spore structure by scanning electron microscopy. 8. Cover slip Culture Technique: SCA plates are prepared and S. sampsonii MDCE7 is streaked and insert sterile square cover slips at an angle 45
and incubate at 28  2
C for 8–10 days. After incubation, remove the cover slip and perform wet mount technique and observe under light microscope and record the results (Plate 1).

Isolation, Identification, and Screening of Polyene Antifungal Compound. . .

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Table 1 Biochemical and physiological characterization of S. sampsonii MDCE7 S. No. Parameters

S. sampsonii MDCE7

1

Colony morphology

Colonies are opaque, convex and mycelial growth with irregular margins. Color of the aerial mycelium was cream to pale yellow and the substrate mycelium was cream to brown color with no diffusible pigment production

2

Gram staining

+

3

Indole test



4

MR



5

VP



6

Citrate test



7

Production of H2S



8

Starch test

+

9

Glucose

+

10

Sucrose



11

Maltose

+

12

Arabinose

+

13

Sorbitol



14

Fructose



15

Inositol



16

Lactose

+

17

Mannitol

+

18

Raffinose

+

19

Rhamnose



20

Xylose

+

21

Salicin

+

22

Galactose

+

23

Casein hydrolysis

+

24

Nitrate reduction test

W+

25

Gelatin hydrolysis

+

26

Growth in presence of NaCl

27

2%, 5%, 7%, 9%

+

12%

W+

Growth in presence of Sodium azide (0.01%)

+ (continued)

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Table 1 (continued) S. No. Parameters Potassium tellurite (0.001%) 28

29

S. sampsonii MDCE7 +

Growth at temperatures (
C) 25, 37, 42

+

4, 15 and 55



Growth at different pH 4 and 5



6 to 10

+

Note: + ¼ positive;  ¼ negative, W+ ¼ weak positive;  ¼ doubtful

9. Scanning electron microscopic study: Perform field emission scanning electron microscopy (FE-SEM) analysis using a FEI Quanta 200F microscope. A slide of 1  1 cm is used for specimen preparation of S. sampsonii MDCE7 culture. Put the glass slide on the growing culture plate like cover slip culture technique. These slides are observed directly under FE-SEM at 15–20 kV after gold coating using BAL-TECSCD-005 Sputter Coater, BAL-TEC AG, Balzers, Liechtenstein; Germany, under argon atmosphere to make the sample conducting, without using any fixative and dehydration procedures. The FE-SEM micrographs were analyzed by xT Microscope Server software (Plate 1). 3.5 Characterization of Polyenes Antifungal Compound Produced by Streptomyces sampsonii MDCE7 Using UV Visual Spectrophotometric Method

1. Inoculate one loop full of potential Actinomycetes into sterilized ISP-2 broth medium and incubate for 7–12 days at 28
C  2
C under shaking at 120 rpm [11]. 2. After incubation, the broth culture medium is centrifuged at 5488  g for 10 min and discard the supernatant and the collect mycelial pellet. 3. Add 25 ml of 95% methanol to extract the polyenes antifungal compound by mixing for 10–15 min at room temperature. 4. The methanolic extractant of the obtained mycelium is used to determine the presence of polyenes antifungal compound by UV visual double beam PC based spectrophotometer (ECIL model—UV 1800 series) at 200–1000 nm of absorption spectrum. 5. The presence of polyene and its type are determined on the basis of characteristic three peak spectra of using standards as reported by Riviere et al. [12] (Fig. 4).

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A). Colony morphology:

Aerial veiw

Substrate view

B). Spore morphology under light microscope

Hyphae and spore arrangement

Spore chain as spirales

C). Spore morphology under scanning electron microscope (SEM)

Note: Yellow colour arrow indicates the

Note: Pink colour arrow indicates the

hyphae and brown colour shows spore

smooth surface of spores

arrangement in chains.

Plate 1 Colony and spore morphological characteristics of Streptomyces sampsonii MDCE7. (a). Colony morphology. (b). Spore morphology under light microscope. (c). Spore morphology under scanning electron microscope (SEM). Note: Yellow color arrow indicates the hyphae and brown color shows spore arrangement in chains. Note: Pink color arrow indicates the smooth surface of spores

6. Infer the results with already available results of Streptomyces sampsonii (Fig. 5).

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ABSORBANCE

2.25 379.50 402.00

1.50

360.00 0.75

0.00

0.75 200.0

260.0

320.0

380.0

440.0

500.0

WAVELENGTH nm Fig. 4 Ultraviolet absorption spectrum of antifungal compound produced by Streptomyces sampsonii GS 1322 in methanol (95%) (Riviere et al. 1977) 1.697 1.500 380.68

361.42

Abs.

1.000

404.22

0.500

0.000

-0.322 297.45

350.00

400.00

450.00

500.00

536.35

nm.

Fig. 5 Ultraviolet absorption spectrum of antifungal compound produced by Streptomyces sampsonii MDCE7 (Ac 160) in methanol (95%)

Isolation, Identification, and Screening of Polyene Antifungal Compound. . .

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References 1. Good Fellow M, Williams ST (1983) Ecology of actinomycetes. Annu Rev Microbiol 37:189–216 2. Holt JG, Krieg NR, Sneath PHA, Staley JT, Williams ST (eds) (1994) Bergey’s manual of determinative bacteriology. Lippincott Williams and Wilkins, Baltimore, MD, 816p 3. Dhanasekaran D, Thajuddin N, Panneerselvam A (2012) Applications of actinobacterial fungicides in agriculture and medicine. In: Dhanasekaran D (ed) Fungicides for plant and animal diseases. In Tech, pp 29–56 4. Tahvonen R (1982) Preliminary experiments into the use of Streptomyces spp. isolated from peat in the biological control of soil and seedborne disease in peat culture. J Agric Sci Fini 54:357–369 5. Tahvonen R, Hannukkala A, Avikainen H (1994) Effect of seed dressing treatment of Streptomyces griseoviridis on barley and spring wheat in field experiments. Agric Sci Fini 4:419–427 6. Tahvonen R, Avikainen H (1987) The biological control of seedborne Alternaria brassicicola of cruciferous plants with a

powdery preparation of Streptomyces sp. J Agric Sci Fini 59:199–208 7. Tahvonen R, Lahdenpera ML (1988) Biological control of Botrytis cinerea and Rhizoctonia solani in lettuce by Streptomyces sp. Ann Agric Fenn 27:107–116 8. Shirling EB, Gottlieb D (1966) Methods for characterization of Streptomyces species. Int J Syst Bacteriol 16:313–340 9. El-Nakeeb AM, Lechevalier HA (1963) Selective isolation of aerobic Actinomycetes. Appl Microbiol 11(2):75–77 10. Oskay M, Tamer AU, Azeri C (2004) Antibacterial activity of some Actinomycetes isolated from farming soils of Turkey. Afr J Biotechnol 3(9):441–446 11. Jain PK, Jain PC (2007) Isolation, characterization and antifungal activity of Streptomyces sampsonii GS 1322. Indian J Exp Biol 45:203–206 12. Riviere J, Moss MO, Smith JE (1977) Antibiotics, in industrial applications of microbiology. Wiley, New York

Chapter 47 Screening of Actinobacterial Cultures for Antimycobacterial Activity Using Mycobacterium smegmatis Ramachandran Chelliah and Deog-Hwan Oh Abstract Tuberculosis (TB) is a significant threat to public health and infectious disease caused by mycobacterium (MTB). In addition, some non-tuberculous mycobacterial (NTM) organisms often lead to infection in humans with immune deficiency and even immunocompetence. In this regard, the research investigated the antimycobacterial effects of endophytic actinobacteria as a substitute framework, using Mycobacterium smegmatis. Key words Tuberculosis, Actinobacteria, Infectious disease, Mycobacterium smegmatis

1

Introduction To illustrate the antagonism between microorganisms, the technique of Agar plug diffusion is sometimes applied, and the technique is analogous to those applied in the model of disk diffusion [1]. It includes having an agar culture on its suitable culture medium of the strain of significance. Bacteria contain molecules which disperse into the agar medium during their development [2]. An agar plug or cylinder is sterile sliced with a sterile cork borer after incubation and coated on the agar surface of another plate previously inoculated by the strain of bacteria studied [1]. From the plug, the compounds disperse to the agar medium. Then, by the appearance of the inhibition zone around the agar plug, the antibacterial property of bacterial secreted molecules is observed. Due to its highly infective nature, tuberculosis can be a sterile intensive procedure and requires a biological protection level 3 (BSL3) cabinet. M. tuberculosis, with an incubation period of 16–24 h, also takes longer time. The development of new anti-TB agents has delayed tuberculosis. In previous study, Vinita et al. [1] applied the fast-growing existence and fundamental similarities with M. tuberculosis, the non-infective M. smegmatis [3]. These findings

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_47, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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illustrate the usefulness of M. smegmatis as a key monitor surrogate host to select chemical compounds for rapid monitoring for MDR M. tuberculosis [1].

2

Materials 1. Actinobacterial cultures. 2. ISP2 agar plates. 3. G7H9 broth. 4. G7H11 agar. 5. Albumin dextrose catalase. 6. 0.5% Glycerol.

3

Methods 1. Inoculate on ISP2 agar plates the specified actinobacterial strains. 2. The ISP2 agar plates are incubated at 28  C for 7–14 days. 3. Inoculate a loop of M. smegmatis bacteria in a sterile flask with glass pebbles attached to 0.3 ml of Middlebrook 7H9 broth. 4. The suspension of M. smegmatis mixed for 30 s using vortex and hold it uninterrupted for 5 min and then use Middlebrook 7H9 broth to make up the suspension up to 5 ml. 5. Then add 200 μl of M. smegmatis suspended to 5 ml of 7H11 molten agar and pour instantly into the 7H9 agar plate of Middlebrook. 6. Use disposable cork borer to cut 5 mm plug of actinobacterial strain from ISP2 agar. 7. Place the actinobacterial agar plug over the layer of previously inoculated 7H11 agar plates with M. smegmatis culture. 8. Plates were incubated at 28  C for 48–72 h. 9. The plates were observed for zone of inhibition round the actinobacterial agar plug (see Note 1).

4

Note 1. The occurrence for the zone of inhibition clearence around the actinobacterial agar plug towards inhibitory activity against M. smegmatis, whereas the absence towards zone of inhibition revels the absence of inhibitory activity.

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References 1. Vinita C, Namrata C, Rama Pati T, Sudhir S (2007) Evaluation of Mycobacterium smegmatis as a possible surrogate screen for selecting molecules active against multi-drug resistant Mycobacterium tuberculosis. J Gen Appl Microbiol 53:333–337 2. Ashok A, Nandhini U, Sreenivasan A, Kaari M, Kalyanasundaram R, Manikkam R (2020)

AntiMycobacterial activity of endophytic actinobacteria from selected medicinal plants. Biomed Biotechnol Res J 4(3):193 3. Manigundan K, Revathy S, Sivarajan A, Anbarasu S, Jerrine J, Radhakrishnan M, Balagurunathan R (2019) Bioactive potential of selected actinobacterial strains against Mycobacterium tuberculosis and other clinical pathogens

Chapter 48 Screening of Actinobacterial Extracts/Compounds for Antimycobacterial Activity by Luciferase Reporter Phage (LRP) Assay Shuai Wei, Shucheng Liu, Ramachandran Chelliah, and Deog-Hwan Oh Abstract Actinomycetes were tested for antimicrobial and antimycobacterial activity with less known habitats. Crude extracts have been evaluated against normal Mycobacterium tuberculosis strain and drug-sensitive and drugresistant clinical isolates were tested with crude extract of Actinobacteria by luciferase reporter phage (LRP) assay. Significant change in antimycobacterial activity throughout filtrates of actinomycete culture and solvent extracts was noted. The secondary metabolite of unusual ecosystem actinomycetes are intended to antagonize species in their respective environments. These are likely to be new antimycobacterial agents, since infectious agents are unknown. Key words Actinomycetes, Luciferase reporter phage (LRP), Antimycobacterial, Mycobacterium tuberculosis

1

Introduction Tuberculosis (TB) is one of the worldwide plagues as well as a challenging health disease. As reported by WHO in 2013, 11 million people were affected by TB and 1.5 million deaths was directly related with active TB cases [1]. Since the overuse and rampant use of the antibiotic drugs, an increasing emergence of resistance to previous effective drugs appeared, which resulted in multi-drug resistant (MDR) strains and extensively resistant drug strains [2]. However, several susceptibility assays for evaluating the mycobacterial drugs and screening natural products take longer time and lower efficiency, including disk diffusion method, agar dilution methods, and broth dilution assay, radiometric (BACTEC), dye-based, and fluorescent/luminescent reporter assays. Thus, rapid, low cost, and effective assays for screening new actinobacterial extracts or compounds as drug candidates are required [3]. Luciferase reporter phage (LRP) assay is an efficient method

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_48, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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for detecting, identifying, and testing the antibiotic susceptibility of M. tuberculosis [4], which is able to screen a large number of actinobacterial extracts within a short time [5].

2

Materials Required 1. Actinobacterial Extracts. 2. Test strain-Mycobacterium tuberculosis H37Rv (reference strain). 3. G7H9 broth. 4. Albumin dextrose. 5. 0.5% Glycerol. 6. DMSO. 7. D-luciferin. 8. Phage: phAE129 with high titer. 9. Luminometer. 10. Selective cultivation and isolation medium—Lowenstein–Jensen (LJ) medium.

3

Methods

3.1 Actinomycete Extract Preparation

1. Transfer the actinobacterial culture into the YEME agar plates (15–20 ml per plate) and put inside the incubator for 7–14 days at 28
C. 2. Collect the agar medium and cut into small pieces. 3. Extract the cut medium using methanol (50 ml). 4. After extraction for 24 h, collect the methanol part and concentrate the sample using a concentrator plus from Eppendorf at 45
C. 5. Weigh the extract with pre-weighed prepared Eppendorf tubes.

3.2 Phage Propagation and Titer Calculation

1. Make tenfold dilutions of the phage phAE129 by transferring 50 μl of the phage lysate in 450 μl of MP buffer. 2. Incubate M. smegmatis mc2 155 in Middlebrook 7H9 complete medium and obtain a turbidity of 0.8 OD at 600 nm (equivalent to 5  108 cfu/ml). 3. Add 500 μl of the cell suspension to 4.5 ml of the phage with tenfold dilutions, vortex and incubate for 30 min at 37
C.

Screening of Actinobacterial Extracts/Compounds for Antimycobacterial. . .

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4. Withdraw 200 μl of the mixture and mix with 5 ml of 7H9 top agar at 45–50
C, then pour on 7H9 base agar plates and incubate at 37
C for 12–14 h. 5. Take plaques from the plates using 5 ml of MP buffer and keep at room temperature for 4 h. 6. Remove the host bacteria using 0.45 μm filters. 7. Determine the concentration of the filtered phage based on the actual mean number of plaque on the plates using the following equation: 8. Plaque forming units/ml (PFU/ml) ¼ Mean value of plaque  10  dilution factor. 3.3 Actinobacterial Extract and Cell Suspension Preparation

1. Dry the collected plant materials under room temperature and make into power using a blender. 2. Do the extraction with hexane and methanol (1:5) or other solvents and filter using filter paper (0.45 μm, Whatman). Stock solution of 10 mg/ml was prepared with 10% DMSO and stored at 20
C before use. 3. Transfer 0.1 ml of stock solution in 0.9 ml of distilled water or DMSO to make a working concentration of 1 mg/ml. 4. Prepare a uniform cell suspension of M. tuberculosis that equivalents to # 2 McFarland standards in G7H7 broth with glass beads. 5. Stock solution. 6. Prepare the stock solution of crude extracts (10 mg/ml) using 10% dimethyl sulfoxide (DMSO), and filter using 0.45 μm filters. 7. Dilute about 100 μl of stock extract solution in 900 μl of sterile distilled water to get 1 mg/ml concentration of working solution. 8. Prepare the cell suspension equivalent to #2 MacFarland units by inoculating the log phase culture of M. tuberculosis from LJ slope into G7H9 broth in Bijou bottles with few glass beads and vortex.

3.4

LRP Procedure

1. Prepare 350 μl of G7H9 broth with 10% albumin dextrose and 0.5% glycerol in 2 ml tube. 2. Add 100 μl of M. tuberculosis H37Rv to each tube. 3. Add 50 μl of crude extract (1 mg/ml) to make a final concentration of 100 μg/ml.

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Table 1 Antimycobacterial activity of the extracts

Extract sample

RLU reduction (%) MB H37Rv

Drug-sensitive MB

Multi-drug MB

resistant

4. Take the same procedure for the drug-sensitive and multi-drug resistant M. tuberculosis isolates. Using DMSO (1%) as negative control. 5. Put in the incubator for 72 h at 37
C. 6. Inoculate 50 μl of phAE129 and 40 μl of CaCl2 (0.1 M) solution to each tube and incubate at 37
C for 4 h. 7. Take 100 μl from the mixture from each tube and put into the luminometer cuvette. 8. Add 100 μl of D-Luciferin and measure the relative light unit (RLU) using luminometer (Table 1). 9. Calculate the inhibition ability according to the following equation: 10. RLU reduction (%) ¼ 100  (RLU of the control  Sample RLU)/RLU of the control. (higher or equal to 50%, it meens the extract have antimycobacterial activity) (See Note 1).

4

Note 1. When the RLU reduction percentage of the extracts is higher than or equal to 50%, it means the extracts have antimycobacterial activity.

References 1. World Health Organisation 2014. Global report, 2014. WHO/HTM/TB/2014.08 2. Shah NS, Wright A, Bai GH, Barrera L, Boulahbal F, Martin-Casabona N, Drobniewski F, Gilpin C, Havelkova M,

Lepe R, Lumb R, Metchock B, Portaels F, Rodrigues MF, Rusch-Gerdes S, Van Deun A, Vincent V, Laserson K, Wells C, Cegielski JP (2007) Worldwide emergence of extensively

Screening of Actinobacterial Extracts/Compounds for Antimycobacterial. . . drug-resistant tuberculosis. Emerg Infect Dis 13:380–387 3. Prabu A, Hassan S, Prabuseenivasan et al (2015) Andrographolide: a potent antituberculosis compound that targets aminoglycoside 20 -Nacetyltransferase in Mycobacterium tuberculosis. J Mol Graph Model 61:133–140 4. Pawde DM et al (2020) Mannose receptor targeted bioadhesive chitosan nanoparticles of

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clofazimine for effective therapy of tuberculosis. Saudi Pharm J 28(12):1616–1625 5. Shawar RM et al (1997) Rapid screening of natural products for antimycobacterial activity by using luciferase-expressing strains of Mycobacterium boris BCG and Mycobacterium intracellulare. Antimicrob Agents Chemother 41 (3):570–574

tdpref

Chapter 49 Screening of Actinobacteria for Anti-TB Activity by Microplate Alamar Blue Assay (MABA) Shuai Wei, Shucheng Liu, Ramachandran Chelliah, and Deog-Hwan Oh Abstract The gradually growing resistant strains to existing drugs and latent TB in tuberculosis (TB) considered being a significant concern. In order to extend the antimicrobial potential, prevent the development of drug resistant mutants, and reduce toxicity, a combination of traditional drugs and medicinal plants therapies can serve. The research was performed in order to test antimycobacterial ability (Microplate Alamar Blue Assay (MABA) against Mycobacterium tuberculosis (under aerobic or anaerobic conditions). Key words Tuberculosis, Actinobacterial, Microplate Alamar Blue Assay (MABA), Mycobacterium tuberculosis

1

Introduction Dilution methods are commonly applied to study the minimum inhibition concentration (MIC) of extracts or compounds. Twofold dilution of known concentration was normally applied [1]. However, sometimes the test sample from novel extracts or compounds may not be fully dissolved and the turbid appeared with uncertain reasons, such as the bacteria growth [2]. But the alamar blue is one kind reagent based on oxidation/reduction, which could help visually read the results and avoid false results [3].

2

Materials Required 1. Actinobacterial Extracts. 2. Test strain-Mycobacterium tuberculosis H37Rv (reference strain). 3. Middlebrook 7H9 broth and supplements. 4. Oleic acid, albumin, dextrose, and catalase (OADC) medium.

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_49, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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tdpref

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5. Albumin dextrose. 6. 0.2% Glycerol. 7. DMSO. 8. Alamar Blue reagent.

3

Methods

3.1 Preparation of M. tuberculosis Culture

1. Thaw the M. tuberculosis H37Rv at room temperature from stock culture. 2. Dispense 10 ml of Middlebrook 7H9 broth in a 15 ml conical tube and add 10% OADC and 0.2% of glycerol. 3. Inoculate 0.1 ml of thawed M. tuberculosis H37Rv in Middlebrook 7H9 broth. 4. Put the inoculated broth in the incubator at 37
C, until the OD600 value ranges from 0.4 to 0.8. 5. Use 7H9 broth to dilute the culture to OD600 value of 0.001, which means a concentration of approximately 105 CFU/ml. 6. Withdraw 0.1 ml of the diluted culture (105 CFU/ml) and inoculate in the following assay plate.

3.2

MABA Procedure

1. Dilute the test extract solution using Middlebrook 7H9 broth supplemented with OADC to a final concentration from 250 μg/ml to less than 1 μg/ml. 2. Thaw and weigh isoniazid. Use DMSO to dissolve isoniazid and use it as a positive control with a starting concentration of 1.28 μg/ml, while only DMSO added in the medium was used as negative control. 3. Dispense 0.1 ml of 7H9 broth into each assay well of the 96-well plate. 4. Add 0.1 ml of the test extracts or compounds to the wells in the first row A and mix up and down 6–8 times. 5. Withdraw 0.1 ml from the first row A and add to the second row B to make a twofold dilution, mix up and down 6–8 times. Transfer 0.1 ml from row B to row C and repeat the procedure down to row G only. 6. Discard 0.1 ml from row G rather than putting it in row H. 7. Pipette 0.1 ml of the M. tuberculosis H37Rv culture into each assay well. The final volume in each well is 0.2 ml. Do the experiment in duplicate. 8. Seal the 96-well plate and incubate the plate at 37
C for 7 days. 9. Then, inoculate 32.5 μl of alamar blue in each assay well.

tdpref

Screening of Actinobacteria for Anti-TB Activity by Microplate Alamar Blue. . .

403

Table 1 MIC of extracts or compounds on the activity of M. tuberculosis with MABA Extract sample

MB H37Rv

10. Put back the plate and incubate at 37
C at dark for another 16–18 h (Table 1). 11. Check the color [see Note1–3].

4

Notes 1. Here, the minimal inhibitory concentration (MIC) was defined as the lowest concentration that caused 90% inhibition which showed a pink color. 2. The blue color means “no mycobacterial growth,” and the pink color means “growth occurrence.” 3. The MIC value will be presented as mean value. The lowest concentration that resulted to 90% inhibition will be the MIC. The MIC values determined by this method will be crosschecked using the broth dilution methods. A blue color in the well will be scored as “no mycobacterial growth,” and a pink color will be scored as “growth occurrence.”

References 1. Shah NS, Wright A, Bai GH, Barrera L, Boulahbal F, Martin-Casabona N, Drobniewski F, Gilpin C, Havelkova M, Lepe R, Lumb R, Metchock B, Portaels F, Rodrigues MF, Rusch-Gerdes S, Van Deun A, Vincent V, Laserson K, Wells C, Cegielski JP (2007) Worldwide emergence of extensively drug-resistant tuberculosis. Emerg Infect Dis 13:380–387 2. Prabu A, Hassan S, Prabuseenivasan et al (2015) Andrographolide: a potent antituberculosis

compound that targets Aminoglycoside 20 -Nacetyltransferase in Mycobacterium tuberculosis. J Mol Graph Model 61:133–140 3. Shawar RM et al (1997) Rapid screening of natural products for antimycobacterial activity by using luciferase-expressing strains of Mycobacterium boris BCG and Mycobacterium intracellulare. Antimicrob Agents Chemother 41 (3):570–574

Chapter 50 Screening of Actinobacteria for Anti-TB Activity by Agar Dilution Assay Ramachandran Chelliah and Deog-Hwan Oh Abstract Actinomycetes were tested for antibacterial and anti-mycobacterial activity from less studied environments. By cultivating these strains via shake flask fermentation using soybean meal medium, crude bio-active molecules were developed. Cell free supernatant and mycelia were removed, respectively, with ethyl acetate and methanol. The antibacterial activity of crude extracts was tested against enteric pathogens by a disk diffusion process. Key words Actinomycetes, Anti-mycobacterial, Bio-active, Disk diffusion

1

Introduction In the 1950s, Canetti et al. identified first ever form of diagnostics and therapeutics (DST) for M. tuberculosis, which involved the formulation of a concentration sequence of drugs in the Lowenstein–Jensen medium matrix against M. tuberculosis. The tests for agar dilution cause the MIC to be calculated. The downside is the strong need for methods of analysis quantities (20 mg/plate to test 1000 mg/ml), which limit its application [1]. In the vapor phase of a petri plate, volatilization of the test sample and activity can also occur and play a role in evaluating MIC by this process, influencing the actual therapeutic efficacy. A dosage array of anti-tuberculosis drugs, in 7H10 form, moderately dispersed in 25-well plates with diluted samples. The key drawback of such test is the time period taken to visibly identify colonial development [2].

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_50, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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Materials Required 1. Actinobacterial ethyl acetate extracts. 2. 7H9 agar. 3. M. tuberculosis H37 Rv. 4. Dimethyl sulfoxide (DMSO). 5. Ethyl acetate. 6. Rifampicin.

3

Methods 1. Extraction of ethyl acetate based actinobacterial extract using ISP2 agar. 2. Prepare the stock solution by dissolving 10 mg of crude extract in 1 ml of DMSO. 3. Use 7H9 sterile broth to systematically dilute the extract and rifampicin. 4. The diluted solution was autoclaved (121  C) medium cooled to 50  C. 5. Take a medium concentration of 10 μg per ml. 6. Total 5 ml of the medium at each of the concentrations into quadrants corresponding to the concentrations in the petri dishes. 7. The medium without any drug as growth control includes one region in each petri plate. 8. Inoculate the sections with an inoculum of M. tuberculosis H37Rv equivalent to the McFarland standard No.1. 9. Evaluate the operation for each quadrant from the number of colonies. 10. After 21 days of incubation at 37  C, determine the numbers of colonies on the drug containing quadrants, and express as percentages of those on the drug-free quadrant.

References 1. Ahmad S, Mokaddas E (2012) Tuberculosis: risk factors, drug resistance, rapid detection and treatment. In: Martin DF, Walker SE (eds) Tuberculosis: risk factors, drug resistance and treatment. Nova Science Publishers Incorporated

2. Manikkam R, Venugopal G, Subramaniam B et al (2014) Bioactive potential of actinomycetes from less explored ecosystems against mycobacterium tuberculosis and other nonmycobacterial pathogens. Int Sch Res Notices 2014:812974

Chapter 51 Antiplasmodial Activity of Halophilic Actinobacteria Dharumadurai Dhanasekaran and Saravanan Karthikeyan Abstract Malaria is one of the major public health problems globally. The WHO, World malaria Report gives the estimate of 247 million malaria cases among 3.3 billion cases at risk in 2006. The report gives estimates for India as 10,649,554 malaria cases in 2006, with 15,008 deaths. 109 countries were found endemic for malaria in 2008. Malaria continues to be a devastating parasitic disease that causes the death of two million individuals annually. The increase in multi-drug resistance together with the absence of an efficient vaccine hastens the need for speedy and comprehensive antimalarial drug discovery and development. Today, the microorganisms residing in deep ocean sediments remain an untapped resource for natural compound discovery. Among the microorganisms actinobacteria, a group of bacteria that accounts for more than 50% of the antibiotics identified to date. Actinobacteria are one of the most efficient groups of secondary metabolite producers and are very important from an industrial point of view. Among its various genera, Streptomyces, Saccharopolyspora, Amycolatopsis, Micromonospora, and Actinoplanes are the major producers of commercially important biomolecules. Several species have been isolated and screened from the soil in the past decades. Consequently, the chance of isolating a novel actinobacterial strain from a terrestrial habitat, which would produce new biologically active metabolites, has reduced. However, in the previous report, none of these compounds have been tested against parasitic diseases. The present investigation is planned to isolate the actinobacteria from saltpan soil of South Indian coastal region and evaluate their antimalarial activity using the human malaria parasite P. falciparum for the antimalarial compouds of potent actinobacteria. Key words Plasmodium, Giemsa stain, Antimalarial assay, Hypersaline actinobacteria

1

Introduction Malaria has been recorded as far north as 64
N latitude and as far south as 32
S. It has occurred in Dead Sea at 400 m above sea level and at 2800 m in Cochabamba (Bolivia) [1]. Eighty six percent of the world malarial cases have been reported in the African region mainly Nigeria, Democratic Republic of Congo, Ethiopia, United Republic of Tanzania and Kenya (WHO 2008). Among the non-African countries, 80% of the cases were in India, Sudan, Myanmar, Bangladesh, Indonesia, Papua New Guinea, and Pakistan (WHO 2008). In India, the major contributors of malaria

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_51, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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incidence are Andhra Pradesh, Bihar, Gujarat, Madhya Pradesh, Maharashtra, Rajasthan, and Orissa which contribute to above 65% of the total cases [2]. The World health Organization has set various goals for control of malaria at a global level. The WHO World Report has stated the following goals: “Since the inception of accelerated malaria control with the founding of the Roll Back Malaria Partnership in 1998, the principal goal has been to reduce mortality by 50% by 2010”. In 2005, the World Health Assembly determined to “ensure a reduction in the burden of malaria of at least 50% by 2010 and by 75% by 2015.” Also, research needs to be done to discover newer and better drugs from microbes. Actinobacteria being abundant and omnipotent in the environment, there must be many more bioactive compounds that are yet to be discovered. The marine sediment-derived actinomycetes include obligate marine taxa, and an impressive array of readily cultivable diversity that has not been previously reported from land. In the past few years, chemical studies on marine actinobacteria have yielded numerous novel secondary metabolites that display a wide range of activity against human tumors and other disease targets. However, in the previous report, none of these compounds have been tested against parasitic diseases. In the present investigation, it is planned to test the activity of extracts from marine actinobacteria to inhibit the human malaria parasite P. falciparum.

2

Materials

2.1 Sample Collection

1. Sterile polythene bags.

2.2 Isolation of Hypersaline Actinobacteria

1. Media M1–M12. 2. Starch Casein agar. 3. Marine agar. 4. Natural seawater. 5. Petri Plates. 6. Incubator.

2.3 Antimalarial Assay

1. 5 L cultures flask.

2.3.1 Preparation of the Actinobacteria Extracts

3. DMSO.

2. Ethyle Acetate. 4. 96-well microtiter plates.

Antiplasmodial Activity of Halophilic Actinobacteria 2.3.2 Cultivation of P. falciparum

409

1. P. falciparum strains D10, 3D7, HB3, and Dd2. 2. 50 mL of human O-positive serum. 3. 2.5 g of AlbuMAXII. 4. 0.5 mL of gentamicin. 5. 5.94 g of HEPES. 6. 2.01 g of sodium bicarbonate. 7. 0.050 g of hypoxanthine. 8. 10.44 g of RPMI 1640 medium.

2.3.3 Screening of Antimalarial Agent Producing Actinobacteria

1. 96-well assay plates. 2. A Complete media. 3. 3D7 infected erythrocytes 2.5% hematocrit and 0.5% parasitemia. 4. Petri Plates. 5. Modular incubation chamber. 6. Freezer. 7. Lysis buffer. 8. Molecular Devices spectrum.

2.3.4 Microscopic Analysis

1. Giemsa stain.

2.3.5 Antiplasmodial Activity of Pure Antimalarial Compound against P. falciparum

1. Complete culture medium at a hematocrit of 1.5%.

2. Nikon Eclipse E200 microscope.

2. 96-well microtiter plates. 3. 20 mg/mL of lithium L-lactate (Sigma). 4. 5.5 mg/mL of TRIS (Sigma). 5. 3.7 mg/mL of 3-acetylpyridine adenine dinucleotide (APAD; Sigma). 6. NBT (1.6 mg/mL; Sigma). 7. PES (0.1 mg/mL; Sigma). 8. 25% acetic acid. 9. Incubator.

3

Methods

3.1 Sample Collection

1. Collect the saltpan soil and sediments samples from saltpan area of Marakanam and Tutucorin, Tamilnadu, India. 2. Bring the samples in sterile polythene bags to the laboratory for further use.

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3.2 Isolation of Hypersaline Actinobacteria

1. Different medium is employed for the isolation of marine actinobacteria, including media M1–M12 [3], Starch Casein agar [4] as well as Marine agar [5]. 2. Prepare all media will be with natural seawater. 3. Serially dilute the sample and spread it in the plate containing the appropriate selection media. 4. Incubate the plates at 28
C for 4–6 weeks.

3.3 Antimalarial Assay

1. Grow marine actinobacteria in 5 L culture flask.

3.3.1 Preparation of the Actinobacteria Extracts

3. Bring the crude extract to a standard concentration of 25 mg/ mL in DMSO by drying.

2. Extract the marine actinobacteria with ethyl acetate.

4. Dispense 10 mL into 96-well microtiter plates. 3.3.2 Cultivation of P. falciparum

1. Get P. falciparum strains D10, 3D7, HB3, and Dd2 from the ATCC. 2. Maintain the parasite strains in in-vitro method according toTrager and Jensen [6]. 3. Maintain cultures in a complete medium containing 50 mL of human O-positive serum, 2.5 g of AlbuMAXII, 0.5 mL of gentamicin, 5.94 g of HEPES, 2.01 g of sodium bicarbonate, 0.050 g of hypoxanthine, and 10.44 g of RPMI 1640 medium per liter at a pH of 6.75. 4. Incubate the parasite infected erythrocytes at temperature of 37
C in gas environment of 5% CO2, 1%O2, and 94% N2 [7].

3.3.3 Screening of Antimalarial Agent Producing Actinobacteria

SYBR Green assay in microplate method to screen a set of crude extracts from marine actinobacteria for their ability to inhibit parasite growth in culture. 1. Dilute the antimalarial agent in complete medium, dilute 40 mL sample and transfer to a 96-well assay plate. 2. To this solution dispense 80 mL of complete media with 3D7 infected erythrocytes 2.5% hematocrit and 0.5% parasitemia in the assay. 3. Dispense uninfected erythrocytes in the background wells at the same final hematocrit. 4. Incubate the plates 72 h in a low oxygen environment (96% N2, 3% CO2, 1% O2) in a modular incubation chamber. 5. Seal the plates and place it in a 80
C freezer overnight, then thaw and add 120 mL of lysis buffer. 6. Dispense the sample into wells and incubate at 37
C in the dark for 6 h to achieve an optimum signal to noise ratio. 7. Read the plates with a Molecular Devices spectrum [8].

Antiplasmodial Activity of Halophilic Actinobacteria 3.3.4 Microscopic Analysis

3.4 Antiplasmodial Activity of Pure Antimalarial Compound against P. falciparum

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1. Stain a thin smears of malaria culture with giemsa stain. 2. Observe with a Nikon Eclipse E200 microscope. The antiplasmodial activity is studied in vitro against the Plasmodium falciparum strain by a micromethod using the lactate deshydrogenase (LDH) assay [9]. 1. Parasites will be cultivated using the method of Trager and Jensen [6]. 2. Infect the erythrocytes with P. falciparum (ring stage, 1% of parasitaemia) and re-suspend it in complete culture medium at a hematocrit of 1.5%. 3. Distribute the suspension in 96-well microtiter plates (200 μL per well). Perform drug testing in triplicate. 4. For each assay, incubate a parasite culture with the antimalarial compound for 48 h in 5% CO2 at 95% relative humidity, and freeze until the biochemical assay could be run. 5. Defrost the sub-sample and take 20 μL of the contents of each well and mix well with 100 μL of a substrate solution containing 20 mg/mL of lithium L-lactate (Sigma), 5.5 mg/mL of TRIS (Sigma), and 3.7 mg/mL of 3-acetylpyridine adenine dinucleotide (APAD; Sigma), in the well of another microtiter plate. 6. Incubate for 30 mins, add 25 μL of mixture of NBT (1.6 mg/ mL; Sigma) and PES (0.1 mg/mL; Sigma) to each well. 7. Again incubate for 35 mins and stop the reaction by adding 25% acetic acid (25 μL per well). Note: Accumulation of the reduced form of APAD will be measured at λ ¼ 650 nm, using a spectrophotometer (microplate reader, Metertech). IC50 values will be determined graphically in a concentration versus percent inhibition curve.

References 1. Gilles HM, Warrel DA (1993) Bruce-Chwatt’s essential malariology. Edward Arnold, London 2. Lal S, Dhillon GPS, Aggarwal CS (1999) Epidemiology and control of malaria. Indian J Pediatr 66:547–554 3. Zhang H, Lee YK, Zhang W et al (2006) Culturable actinobacteria from the marine sponge Hymeniacidon perleve: isolation and phylogenetic diversity by 16S rRNA gene-RFLP analysis. Antonie Van Leeuwenhoek 90:159–169

4. Kuster E, Williams ST (1964) Selection of media for isolation of streptomycetes. Nature 202:928–929 5. Pathom-Aree W, Stach JE, Ward AC et al (2006) Diversity of actinobacteria isolated from challenger deep sediment (10, 898 m) from the Mariana trench. Extremophiles 10:181–189 6. Trager W, Jensen JB (1976) Human malaria parasites in continuous culture. Science 193:673–675 7. Patel V, Booker M, Kramer M, Ross L, Celatka CA, Kennedy LM, Dvorin JD, Duraisingh MT,

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Sliz P, Wirth DF, Clardy J (2008) Identification and characterization of small molecule inhibitors of Plasmodium falciparum dihydroorotate dehydrogenase. J Biol Chem 283(50):35078–35085 8. Jacques P, Eric M, Ponts N, Ste’phane B, William F, Le Roch K (2008) Marine

Actinomycetes: a new source of compounds against the human malaria parasite. PLoS One 3(6):2335 9. Makler MT, Hinrichs D (1993) Measurement of the lactate dehydrogenase activity of Plasmodium falciparum as an assessment of parasitemia. Am J Trop Med Hyg 48:205–210

Chapter 52 An In Vitro Antiamoebic Activity of Actinobacteria Karthiyayini Balakrishnan, Dhanasekaran Dharumadurai, Thirumurugan Ramasamy, and Muthuselvam Manickam Abstract Amoebiasis is a ubiquitous disease caused by the protozoan parasite Entamoeba histolytica. It infects 50 million people per year and leading cause of death about 100,000 people due to parasitic disease worldwide. Metronidazole is the primary treatment for amoebiasis. The feature of this disease is the occurrence of morbidity affecting the quality of life and the pace of developmental activities. The adequate therapy for amoebic colitis is necessary to reduce illness, prevent development of complicated disease and extraintestinal spread, and decrease transmission. There are number of agents which possess potent amoebicidal action against trophozoites of E. histolytica available for therapeutic use. So, the prompt possessing symptomatic relief of suffering is from intestinal dysentery. Metronidazole is one of the most effective antiamoebic medications. However, we are in need of new drugs to inhibit the growth of Entamoeba histolytica. Hence, the present protocol is used to screen the antiamoebic activity of actinobacteria isolates. Key words Amoebiasis, Entamoeba histolytica, Antiamoebic activity, Metronidazole, Actinobacteria, Secondary metabolites

1

Introduction Amoebiasis is an infection caused by the protozoan parasite Entamoeba histolytica. Amoebae occasionally penetrate the intestinal mucosa, resident in the large bowl and may disseminate to other organs. The parasite secretes proteinases which dissolve in the host tissues, killing host cells and engulfing red blood cells. The trophozoites of E. histolytica invade the intestinal mucosa, causing amoebic colitis. Entamoeba histolytica, the causative agent of amoebic dysentery, is a parasitic contaminant of food, water, and soil. It can cause invasive intestinal and extraintestinal disease. Amoebas breach the mucosal barrier and travel through the portal circulation to the liver, where they cause abscesses consisting of a few E. histolytica trophozoites surrounding dead and dying hepatocytes and

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_52, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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Table 1 Compounds derived from actinomycetes showing antiamoebic activity S.No

Actinomycetes

Compounds

References

1.

Actinomycete metabolites

Echinomycin A; Tirandamycin A

[3]

2.

Micromonosporarhodorangea

Gentamicin

[4]

3.

Streptomyces sanyensis

Indolocarbazole

[5]

liquefied cellular debris. The major clinical manifestations of Entamoeba histolytica infection are amoebic colitis and amoebic liver abscesses [1]. Infection with the protozoan Entamoeba histolytica is common in low- and middle-income countries, and up to 100,000 people with severe disease die every year. Adequate therapy for amoebic colitis is necessary to reduce illness, prevent development of complicated disease and extraintestinal spread, and decrease transmission. Metronidazole[1-(2-hydroxyethyl)-2-methyl-5-nitroimidazole] is the reference drug of choice for the treatment of anaerobic protozoan and bacterial infections. It shows a more pronounced activity than that of all other compounds [2]. However, it has mutagenic effect in bacteria, is carcinogenic to rodents and is associated with transient myopia, neuropathy, and immunosuppression. Actinomycetes are fibrous, branching Gram-positive bacteria. The morphology of actinomycetes seems fungal type. It has unique metabolic and physiological capabilities. Some of the actinomycetes produce bioactive compounds such as amino glycosides, anamycins, b-lactam, and macrolides. The actinomycetes producing bioactive and chemical compounds are responsible for antimicrobial and toxic activities (Table 1). This protocol infers the in vitro antiamoebic activity of actinobacterial secondary metabolites.

2

Materials l

96-well plate microplate.

l

Neubauer’s cell.

l

Diamond TYIS-33 growth medium. Composition: 1.0 g Potassium phosphate, dibasic. 0.6 g Potassium phosphate, monobasic. 2.0 g Sodium chloride. 20.0 g Casein digest peptone.

An In Vitro Antiamoebic Activity of Actinobacteria

415

10.0 g Yeast extract. 10.0 g Glucose. 1.0 g L-cysteine Hydrochloride. 0.2 g Ascorbic acid. 1.0 mL Ferric Ammonium citrate, brown form (22.8 mg/mL) (pH 6.8)

3

l

DMSO.

l

Metronidazole.

l

MeOH.

l

0.9% Sodium chloride solution.

l

Methanol.

l

Distilled water.

l

0.5% aqueous eosin.

l

0.1 N Sodium hydroxide solution.

Methods

3.1 In Vitro Antiamoebic Activity by the Method of Bharti et al. (2000) [6]

1. Take 96-well plate microplate. 2. Add 100 μL Diamond TYIS-33 growth medium to all the wells. 3. First column is considered as blank which contains only medium. 4. From the second column, culture amoeba from E. histolytica HK-9 strain in Diamond TYIS-33 growth medium under axenic conditions. 5. Dilute the suspension to 105 organism/mL. 6. Incubate the microplate for 72 h. 7. Dissolve the actinobacteria test compounds in DMSO, it is a stable solvent complex which does not inhibit the amoeba. 8. Prepare fresh stock solution before use at the concentration of 1 mg/mL. Metronidazole can be considered as a standard reference drug. 9. Dissolve 10 mg of metronidazole in 2 mL MeOH (10 mg/ 2 mL). 10. Add the actinobacteria-derived test compounds from the second well in the concentration of 0–100, 0–500, or 0–1000 μg/ mL. 11. After incubation, add the test compound and leave for 72 h. 12. In between count the number of E. Histolytica cells with hemocytometer (Neubauer’s cell count).

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Table 2 IC50 analysis of antiamoebic compounds S. No.

Name of the test compound

1.

Metronidazole

2.

Actinobacterial compound A

3.

Actinobacterial compound B

IC50 mg/mL

S.D.  10

13. After 72 h of incubation, remove all the medium from the plate. 14. Wash the plate with sodium chloride solution (0.9%). 15. Complete this procedure quickly and the plate is not allowed to cool in order to prevent the detachment of amoebae. 16. Allow the plate to dry at room temperature for few mins. 17. Add chilled methanol to fix the amoebae for 15 min, then remove methanol, dry the plate. 18. Stain the amoebae with 0.5% aqueous eosin for 15 min. 19. Wash the stain with tap water for one time. 20. Again, wash the plate with distilled water twice. 21. Air dry for few mins. 22. Add 200 mL of 0.1 N sodium hydroxide solution to dissolve the protein and release the dye. 23. Measure the optical density of the resulting solution in each well with a microplate reader at 490 nm. 24. Calculate the percentage inhibition of amoebal growth from the optical densities of the control and test wells and plotted against the logarithm of the dose of the drug tested. 25. Determine the IC50 value for the best fitting line by linear regression analysis as indicated in Table 2. 26. Report the IC50 values in μM. 27. All the experiments were carried out in triplicate at each concentration level and repeated thrice.

4

Observation The results are predicted by the percentage of growth inhibition compared with the untreated controls and plotted as probit values as a function of the drug concentration [7]. The IC50 and 95% confidence limits were interpolated in the corresponding dose–response curve [8].

An In Vitro Antiamoebic Activity of Actinobacteria

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The activities of the compound indicate the incorporation of metal fragments. It generally produces an enhancement of the activity. References 1. Stanley SL (2001) Pathophysiology of amoebiasis. Trends Parasitol 17(6):208–285 2. Tona L, Kambu K, Ngimbi N, Cimanga K, Vlietinck AJ (1998) Antiamoebic and phytochemical screening of some Congolese medicinal plants. J Ethnopharmacol 61:57–65 3. Espinosa A, Socha AM, Ryke E, Rowley DC (2012) Antiamoebic properties of the actinomycete metabolites echinomycin A and tirandamycin A. Parasitol Res 111:2473–2477 4. Ganesh Kumar C, Himabindu M, Jetty A (2008) Microbial biosynthesis and applications of gentamicin: -a critical appraisal. Crit Rev Biotechnol 28(3):173–212 5. Cartuche L, Reyes-Batlle M, Sifaoui I, Arberas˜ er JE, Ferna´ndez JJ, LorenzoJime´nez I, Pin Morales J, Dı´az-Marrero AR (2019) Antiamoebic activities of indolocarbazole metabolites

isolated from Streptomyces sanyensis cultures. Mar Drugs 17(10):588 6. Bharti N, Maurya MR, Naqvia, F. &Azama. A. (2000) Synthesis and antiamoebic activity of new cyclooctadiene ruthenium (II) complexes with 2-acetylpyridine and benzimidazole derivatives. Bioorg Med Chem Lett 10:2243–2245 7. Abid M, Azam A (2006) Synthesis, characterization and antiamoebic activity of1-(thiazolo [4,5-b]quinoxaline-2-yl)-3-phenyl-2-pyrazoline derivatives. Bioorg Med Chem Lett 16:2812–2816 8. Hayat F, Salahuddin A, Umar S, Azam A (2010) Synthesis, characterization, antiamoebic activity and cytotoxicity of novel series of pyrazoline derivatives bearing quinoline tail. Eur J Med Chem 45:4669–4675

Chapter 53 Screening for Antiviral Activity: MTT Assay Ramachandran Chelliah, Fazle Elahi, and Deog-Hwan Oh Abstract To evaluate the efficiency of the actinobacterial extract, a precise and reliable method was developed against dengue virus, based on the dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) protocol. Dextran sulfate applied as a positive control to determination of cell viability, based on the spectrophotometer optical density of formazan was applied. The values of dextran sulfate IC50 and the values of dextran sulfate and the actinobacterial extracts were calculated by the process of plaque reduction. Key words Actinobacterial extract, Dengue virus, Formazan, IC50, Dextran sulfate

1

Introduction A spectrophotometer that tests cell metabolic activity is the MTT assay. The mitochondrial activity of viable cells is determined by NAD(P)H-dependent cellular oxidoreductase enzymes, especially mitochondrial succinate dehydrogenase, in human cells [1, 2]. These enzymes are able to reduce the MTT 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide yellow-colored tetrazolium stain to its purple-colored insoluble formazan [3]. The cells are then dissolved and discharged with an organic solvent (e.g., isopropanol), and spectrophotometrically measured by the solubilized formazan reactant. Cytotoxicity (loss of viable cells) or cytostatic activity (shift from proliferation to quiescence) of possible medically significant and hazardous substances may also be calculated using tetrazolium dye assays [4, 5].

2

Materials Required 1. Crude metabolite actinobacterial extract. 2. MTT solution (5 mg/mL in PBS) (light sensitive and store in 20
C).

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_53, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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3. Virus treated Vero cell line (e.g., dengue virus). 4. 96-Well microtiter plate (flat bottom). 5. Dimethyl sulfoxide (DMSO). 6. UV-visible spectrophotometer (Microtiter plate reader).

3

Methods

3.1 Preparation of MTT Solution

1. 5 mg/mL of MTT was added with phosphate buffer saline (PBS) and mixed by vortexing or homogenization [Note— MTT is soluble in polar soluble (distilled water—10 mg/ mL), ethanol (20 mg/mL), and buffered salt solutions and culture media (5 mg/mL)]. 2. Sterilize the MTT solution using 0.20 mm microsyringe filter. 3. Short-term storage (1–4 days) of MTT solution at 4
C but long-term storage (3–6 months) at 20
C.

3.2

Antiviral Assay

1. The Vero cell line (2  106 cells/well) was prepared in 96-well plates. 2. The base medium for this cell line is ATCC-formulated Eagle’s Minimum Essential Medium (EMEM) with 10% of fetal bovine serum incubated at 28
C for 24 h, and then treated with different concentration of actinobacterial metabolites (1:1 to 1:64), along with duplicates and 100 μL culture medium per well along with the untreated medium as control. 3. Incubation of cells in CO2 for 72 h. After the incubation remove the growth medium and add 100 μL of MTT solution (5 mg/mL). 4. Incubate the titer plate for 4 h and discard the MTTT solution, further supplement with 100 μL of DMSO, add 100 μL of the solubilization solution (0.04 N HCl in isopropanol and/or DMSO) into each well for dissolving of formazan crystals and shake the plate gently to dissolve the crystal’s completely. 5. The absorbance on the titer plate was read at 595 nm. Determine the CC50 and IC50 by using MTT assay. The 50% cytotoxic concentration (CC50) cell viability (The extract concentration that reduced the cell viabelityby 50%, when compared with untreated control), likewise the 50% inhibitory concentration (IC50) was distinct as 50% of viral replication compared with dengue viral control. 6. The selectivity index (SI) was determined from the CC50/IC50 ratio (It is an important factor for assessing antiviral activity). Determine the cell viability and antiviral activity according to the following formulas:

Screening for Antiviral Activity: MTT Assay

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Table 1 Antiviral activity S. no

Sample code no.

Concentration

Cell viability

Optical density (OD at 590 nm)

1 2 3 4

Cell viability (%) ¼ OD value of experimental control. (Untreated cell)  OD value of experimental sample. (Treated cell)/OD value of experimental control. (Untreated cells)  100 7. Antiviral activity ¼ (ODt) DENV  (ODc) DENV  100/ (ODc) cells  (ODc) DENV, where (ODt) DENV absorption were measured at various concentrations of 1000–3.096 μg/ mL and DENV—infected cells (ODc) DENV is untreated control absorbance, DENV—infected cells and (ODc) is the absorption of untreated control Vero cells (see Table 1).

References 1. Aleshin VA, Artiukhov AV, Oppermann H, Kazantsev AV, Lukashev NV, Bunik VI (2015) Mitochondrial impairment may increase cellular NAD (P) H: resazurin oxidoreductase activity, perturbing the NAD (P) H-based viability assays. Cell 4(3):427–451 2. Bunik VI, Mkrtchyan G, Grabarska A, Oppermann H, Daloso D, Araujo WL, Gaunitz F (2016) Inhibition of mitochondrial 2-oxoglutarate dehydrogenase impairs viability of cancer cells in a cell-specific metabolismdependent manner. Oncotarget 7(18):26400 3. Athukorala Y, Ahn GN, Jee YH, Kim GY, Kim SH, Ha JH, Kang JS, Lee KW, Jeon YJ (2009) Antiproliferative activity of sulfated

polysaccharide isolated from an enzymatic digest of Ecklonia cava on the U-937 cell line. J Appl Phycol 21(3):307–314 4. Balagurunathan R, Radhakrishnan M, Shanmugasundaram T, Gopikrishnan V, Jerrine J (2020) Determination of cytotoxicity of actinobacterial extracts and metabolites. In: Protocols in actinobacterial research. Springer, New York, NY, pp 197–203 5. Deshmukh Sameer B (2012) Invitro cytotoxic and Cytoprotective activity of Silibinin and Genistein on breast and Colon cell lines. Doctoral dissertation, JKK Nattraja College of Pharmacy, Komarapalayam

Chapter 54 Screening for Anticancer Activity: 3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium (MTT) Assay Ramachandran Chelliah and Deog-Hwan Oh Abstract A potential barrier to clinical treatment is the discovery of anticancer drugs that destroy or disable tumor cells in the presence of normal cells without unnecessary toxicity. The possible consequences of marine products such as seaweed that demonstrate anticancer activity have been illustrated in several literature articles. Crude bacterial condensed extract dissolved in DMSO using the Soxhlet apparatus. The antitumor activity were tested in Human hepatocellular carcinoma cell lines (HepG2) (Liver Cancer). MTT assay (3-(4, 5-dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide, yellow tetrazole) the cytotoxic activity of extract at different concentrations (100 μg/ml-300 μg/ml) were screened for an antitumor impact toward selected cell lines. Key words Anticancer drugs, DMSO, In vitro, Cell lines

1

Introduction A colorimetric assay that analyzes cell metabolic rate is the MTT assay. The NAD(P)H-dependent cellular oxido-reductase reaction in living cells, in particular mitochondrial succinate dehydrogenase, regulates the mitochondrial function of viable components in living cells. The yellow-colored tetrazolium dye MTT 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide can be reduced to its insoluble formazan, which has a purple color, by these enzymes [1]. The cells are then solubilized and discharged with an organic solvent (e.g., isopropanol); the spectrophotometer were applied to determine the absorbence of the solubilized formazan reagent. Cytotoxicity (loss of viable cells) or cytostatic activity (shift from development to quiescence) were calculated with tetrazolium dye biomarkers. As the MTT reagent is sensitive to heat, MTT tests are typically performed in the dark [2].

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_54, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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Materials 1. HepG2 cell line. 2. MTT (5 mg/ml in PBS). 3. MTT solvent—Acidic isopropanol (0.1 N HCl in absolute isopropanol) or Dimethyl sulfoxide (DMSO). 4. Culture medium—(RPMI 1640) 96-Well plate (flat bottom). Actinobacterial extract.

3

Methods

3.1 Preparation of MTT Solution

1. [Note: MTT is also hydrophilic (10 mg/ml), ethanol (20 mg/ ml)]. Add 5 mg/ml of MTT with PBS and blend by magnetic stirring or sonication. 2. After the addition of MTT, sterilize the solution based on 0.04 μm syringe filter. 3. And store the MTT solution at
20  C. 4. For short-term of storage use 4  C and for long-term storage use
20  C.

3.2

Assay Protocol

1. Inoculate the HepG2 cells in 96-well microtiter plates and (1  105) cells allow attaching on to the plates for 24 h at 37  C in anaerobic (5% CO2) condition. 2. Substitute the medium of culture with a new medium (RPMI1640). 3. Add 20 μl (at different concentrations from 100 to 543

>543

>1086

2174  0.01

>543

n-Bu2Sn(HOr)

>388

>388

>776

>388

>776

Cis-platin

8.97  0.1

6.72  0.13

5.99  0.05

3.71  0.05

5.97  0.01

5-fluorouracil

>0.65

1.61  0.05

1.41  0.05

7.17  0.13

2.27

36.17  0.40

13.59  0.05

55%) and the ability to degrade variety of dyes. 2. Inoculate the cultures of actinobacterial consortium into effluent basal medium with various concentrations of effluent and synthetic dyes. 3. Incubate the experimental set up for 8 days 30  2  C, and analyze the decolorization of the effluent samples as described earlier.

References 1. Chung KT, Cerniglia CR (1992) Mutagenicity of azo dyes structure activity relationship. Mutat Res 277(3):201–220 2. Nigam P, McMillan G, Banat IM, Merchant R (1996) Decolourization of effluent from the textile industry by a microbial consortium. Biotechnol Lett 18:17–20 3. Shaul GM, Holdsworth TJ, Dempsey CR, Dostal KA (1991) Fate of water soluble azo dyes in the activated sludge process. Chemosphere 22:107–119 4. Reife A (1993) Dyes: environmental chemistry. In: Kroschwit JI (ed) Encyclopedia of chemical tech. Wiley, New York, p 775 5. Robinson T, Mcmillon G, Merchant R, Nigam P (2001) Remediation of dyes in textile effluent: a critical review on current treatment technique with a proposed alternative. Bioresour Technol 77:247–255 6. Salah Uddin M, Zhou J, Qu Y, Guo J, Wang P, Zhao LH (2007) Biodecolourization of Azo-dye acid red B under high salinity condition. Bull Environ Contam Toxicol 79 (4):440–444 7. Ayed L, Chaieb K, Cheref A, Bakhrouf A (2009) Biodegradation of triphenylmethane dye malachite green by Sphingomonas paucimobilis. World J Microbiol Biotechnol 25:705–711 8. Kannan N (1996) Laboratory manual in general microbiology. Palani Paramount Publications, Palani, India, p 316

9. Williams ST, Cross T (1971) Isolation, purification cultivation and preservation of actinomycetes. Methods Microbiol 4:295–334 10. Pridham TG, Tresner HD (1974) Streptomycetaceae. In: Buchanan RE, Gibbons NE (eds) Bergey’s manual of determinative bacteriology, 8th edn. Williams and Wilkins, Baltimore, pp 748–829 11. Shirling EB, Gottlieb D (1966) Methods for characterization of Streptomyces species. Int J Syst Bacteriol 16:312–340 12. Hernandez JA, Corpas FJ, Gomez M, Del Rio LA, Sevilla F (1994) Salt stress-induced changes in superoxide dismutase isozymes in leaves and mesophyll protoplasts from Vigna unguiculata L. New Phytol 126:37–44 13. Xiao X, Li TT, Lu XR, Feng XL, Han X, Li WW, Li Q, Yu HQ (2018) A simple method for assaying anaerobic biodegradation of dyes. Bioresour Technol 251:204–209 14. Lade, H., Govindwar, S. and Paul, D., 2015. Low-cost biodegradation and detoxification of textile azo dye C.I. reactive blue 172 by Providencia rettgeri strain HSL1. J Chem, 2015 894109, 10 pages. doi:https://doi.org/10. 1155/2015/894109. 15. Nehra K, Anju M, Malik K (2008) Isolation and optimization of conditions for maximum decolourization by textile—dye decolourization bacteria. Pollut Res 27:257–264

Chapter 102 Bioleaching of Heavy Metals from e-Waste Using Actinobacteria Gopikrishnan Venugopal, Manigundan Kaari, Meganathan P. Ramakodi, and Radhakrishnan Manikkam Abstract End-of-Life Electrical and Electronic Equipments, commonly known as e-waste, is an emerging problem with developed as well as developing nations. Our obsession on electrical and electronic equipments, the unquenchable desire for latest devices and rapid advances in technology has resulted in the world wide generation of huge amount of e-waste. The application of microbial biotechnology is extensively exploited for metal extraction and emerged as one of the sustainable and eco-friendly tools. The bio-metallurgical process is usually referred as bioleaching which utilizes microorganisms to recover metals from low-grade ores and e-waste (Hong and Valix, J Clean Prod 65:465–472, 2014). Benefiting from lower operational cost and energy requirements in metal recovery, bioleaching has drawn more and more attention. Actinobacteria are metabolically multitalented bacteria that are widely distributed in nature including the metalcontaminated soils (Abdelmohsen et al., Nat Prod Rep 31:381–399, 2014). Members of the phylum actinobacteria are well explored for many environmental cleanups, but not much for remediation of e-waste. Key words e-Waste, Metal contamination, Bioleaching, Bio-metallurgical and Actinobacteria

1

Introduction Electronic waste or waste electrical and electronic equipment (WEEEs) is an up-and-coming and fast-growing waste stream with difficult characteristics. According to United Nations “Global E-waste Monitor report, 2015,” the global capacity of entire e-waste generated in 2014 was about 41.8 million metric tonnes (MT). The existence of metals like copper, aluminum, iron, and various valuable metals like gold, silver, palladium, platinum, etc., in high concentrations, made e-waste an “urban mine.” Bioleaching is one of the successful bio-hydrometallurgical method, which can be employed for metal recovery from different WEEEs. Recovery of precious metals like copper, gold and silver is possible at high

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_102, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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concentrations from WEEEs using microbes [3]. Urban mining of these metals has expected most important interest every part of the world. In the mining industry, naturally-occurring microorganisms have been exploited for extraction of metals from mining waste and lean ores. Microorganisms act as biocatalysts in extracting metals from metal-laden sources. Biomining is an oxidation process, and includes both biooxidation and bioleaching. Most bioleaching studies focus on two types of microorganisms, namely mesophilic bacteria and thermophilic archaea [4, 5]. The function of microbial biotechnology is extensively exploited for metal extraction and emerged as one of the sustainable and eco-friendly tools. However, a limited field-scale study is prevailing in the realm of resource recovery from e-waste using bioleaching method. Hence, the application of bioleaching requires more attention and technical knowhow in developing countries to curtail crude practices. A glance of e-waste management in India and the menace of 95% crude e-waste recycling are also elaborated. The incentives toward profit, socioeconomic, and environmentally sustainable approaches have been delineated based on critical analysis of the available literature [4]. The applications of bioleaching in e-waste using actinobacteria, including its available methods have been discussed in this chapter.

2

Materials 1. Actinobacterial strain. 2. Printed circuit boards (PCBs). 3. Conical flask. 4. ISP2 broth. 5. UV visible spectrophotometer. 6. ICP-MS.

3

Methods

3.1 Collection and Processing of e-Waste

1. Collect the Printed circuit boards (PCBs) from the e-waste dumping area. 2. Transfer the PCBs in 10-M NaOH solution for 48 h without disturbance. 3. Then, take the PCBs and wash under running tap water to remove the solder. 4. Dry the treated PCBs in tray dryer for 40 min. 5. Finally sieve for fine powder with 120-μm pore size for analysis and bioleaching [6, 7].

Bioleaching of Heavy Metals from e-Waste Using Actinobacteria

3.2 Determination of Metal Content of PCB

707

1. Add 5 g of PCB powder in 250-ml Erlenmeyer flask and mix with 40-ml aqua-regia [a mixture of concentrated acid (69% m/v) and hydrochloric acid (37% m/v) at 1:3 ratios], allow it for 24 h. 2. Centrifuge the mixture at 2800
g for 15 min. 3. Filter the digested PCB solution through a 0.45-μm membrane filter. 4. Use ICP-MS to analyze the metal concentration of PCB powder [8].

3.3 Bioleaching of Heavy Metals from the Printed Circuit Board (PCB)

1. Prepare 200 ml of yeast extract malt extract broth in 500-ml conical flask and inoculate actinobacterial culture. 2. Incubate at 28  C in 120 rpm in shaking incubator for 24–48 h. 3. After incubation, centrifuge the culture broth at 10,000 rpm for 10 min. 4. Wash the pellet two times with sterile distilled water. 5. Add 1 g of crude PCB powder into each 150 ml of ISP 2 broth medium in three 500-ml conical flasks. 6. Adjust the pH of the medium to 5, 6 and 7, respectively. 7. Inoculate the 48-h fresh culture of actinobacterial strain into PCB containing solution. 8. Then incubate the flasks in a rotary shaker at 110 rpm for 120 h. 9. Aseptically draw the sample every 24 h. 10. Centrifuge the cells at 10,000 rpm for 20 min. 11. Collect the cell-free supernatant in clean tubes and use for analysis. 12. Analyze the heavy metals from the crude PCB using ICP-MS with following formula [6, 7]. %heavy metal extraction ¼ Initial metal content  metal content after leaching= initial metal content
100:

3.4 Characterization of PCB and Bioleaching Residue SEM Analysis

1. Analyze the dried PCB powder and its bioleaching residue using SEM [7]. 2. Wash the bioleaching residue for five times and dry at 80  C. 3. Mount the PCB and bioleached residue with 2.5% glutaraldehyde for 60 min and wash with 0.1-M sodium acetate buffer (pH 7.3).

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4. Dehydrate and examine the sample with a QUANTA 200. 5. Analyze the sample using XRD and FTIR

References 1. Hong Y, Valix M (2014) Bioleaching of electronic waste using acidophilic sulfur oxidising bacteria. J Clean Prod 65:465–472 2. Abdelmohsen UR, Bayer K, Hentschel U (2014) Diversity abundance and natural products of marine sponge-associated actinomycetes. Nat Prod Rep 31:381–399 3. Annamalai M, Gurumurthy K (2019) Microbiological leaching of metals and its recovery from waste electrical and electronic equipment: a review. World Rev Sci Technol Sustain Dev 15 (1):1–16 4. Shashi A, Sunil K (2020) Bioleaching: urban mining option to curb the menace of E-waste challenge. Bioengineered 11(1):640–660 5. Subhabrata D, Gayathri N, Yen-Peng T (2016) Bio-extraction of precious metals from urban solid waste. In: Proceedings of the first international process metallurgy conference (IPMC

2016). AIP Conf. Proc., vol 1805, pp 0200041–020004-8 6. Jadhav U, Sua C, Hocheng H (2016) Leaching of metals from printed circuit board powder by an Aspergillus niger culture supernatant and hydrogen peroxide. RSC Adv 6:43442–43452 7. Dhanalashmi K, Menaka R, Vignesh A, Annam Renita A, Manigundan K, Shanmugasundaram T, Gopikrishnan V, Jerrine J, Radhakrishnan M (2019) Bioleaching of heavy metals from printed circuit board (PCB) by Streptomyces albidoflavus TN10 isolated from insect nest. Bioresour Bioprocess 6:47 8. Yamane HL, Moraes VT, Espinosa DCR, Tenor Rio JAS (2011) Recycling of WEEE: characterization of spent printed circuit boards from mobile phones and computers. J Waste Manag 31:2553–2558

Chapter 103 Biosynthesis and Characterization of Silver Nanoparticles from Actinobacteria R. T. V. Vimala, G. Rajivgandhi, S. Sridharan, M. Jayapriya, G. Ramachandran, C. Chenthis Kanisha, N. Manoharan, and Wen-Jun Li Abstract An efficient biosynthetic process for the rapid production of nanoparticles would enable the development of “microbial nanotechnology” for mass-scale production. The present protocol focuses on the methodology to synthesize and characterize the silver nanoparticle (AgNPs) using actinobacterial strains. UV-Vis spectroscopy and High Resolution Transmission electron microscopy (HR-TEM) are proposed to be used to characterize the synthesized AgNPs. X-ray diffraction (XRD) of the nanoparticles dispersion will confirm the presence or absence of elemental silver signal peaks. Key words Silver nanoparticles, Surface plasmon, UV-Vis absorption spectrum, XRD

1

Introduction Silver nanoparticles are in high demand due to their attractive physicochemical properties. Therefore, AgNPs are considered as receiving attention due to their attractive physicochemical properties. Biological resources such as fungi, plants, actinomycetes, yeast, and bacteria can be employed for the synthesis of nanoparticles (NPs), including silver which exhibits different biological activity. Moreover, the biosynthesis method has emerged as a simple, nontoxic, and environmental friendly method. The NPs synthesis by living organisms leads to several advantages such an understanding of their size, shape, and reduction in time synthesis. In addition, microorganisms especially, actinomycetes can be used as ecofriendly nano factories for the synthesis of different compounds of nanoparticle in size. Actinomycetes are capable of accumulating the metal due to their interactive effect. These kinds of biologically synthesized nanomaterials have gained significant interest due to the use of experimental conditions such as tempera-

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_103, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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ture, pH, and pressure. Biological synthesis exerts extra advantages over chemical methods such as higher productivity and lower cost. Moreover, the extracellular biological synthesis of AgNPs is an attractive and ecologically friendly alternative approach for the production at the large scale. In addition, it deals with the advantage of easy downstream processing. Moreover, handling and manipulation are easy to the bacteria. Considering these advantages, microbial biosynthesis is considered as an excellent alternative approach for the extracellular synthesis of AgNPs.

2

Materials 1. Soil samples. 2. Starch-nitrate medium. 3. Silver nitrate.

3

Methods

3.1 Isolation of Actinomycetes

1. Isolate actinomycetes strains from the soil samples according to the methods of [1]. 2. Maintain the isolated strains on starch-nitrate medium composed of the following components (g/L): 20 g starch, 0.5 g K2HPO4, 1 g KNO3, 0.5 g MgSO4∙7H2O, 0.01 g FeSO4, 15 agar (for solid medium), and pH 7. 3. Inoculate the isolated actinomycetes strains in a starch-nitrate agar medium. 4. Incubate at 30–32  C for 7 days.

3.2 Preparation of Cell Free Extract

1. Inoculate the isolated actinomycetes strains in a starch-nitrate medium (50 ml). 2. Keep it for incubation in a rotary shaker at 200 rpm and 30–32  C for 7 days. 3. Centrifuge at 19,297  g for 10 min. Then, collect the supernatant for further experiments.

3.3 Biosynthesis of AgNPs

1. Add 1 mM silver nitrate (50 ml) solution equally with the actinomycete supernatants (50 ml) as described by the protocol of [2] with little modifications. 2. Incubate the samples in a shaker at 37  C and 200 rpm for 5 days. 3. Perform control experiments with an uninoculated media for nanoparticle synthesis. 4. Observe colour change into a yellowish brown.

Biosynthesis and Characterization of Silver Nanoparticles from Actinobacteria

3.4 Characterization of AgNPs Analyses

711

1. Examine the reduced silver ions by sampling about 2 ml of the solution at time intervals. 2. Monitor UV-Vis spectra by UV-Vis spectroscopy analysis using a spectrophotometer (UV-Vis spectroscopy; Thermo Spectronic, USA) at the wavelength range of 200–700 nm. 3. Characterize High Resolution Transmission Electron Microscopy (HR-TEM) studies of AgNPs using TEM microscope (HR-TEM; HT7800, RuliTEM) and then XRD (DMAX-RB; Rigaku, Japan).

4

Observation and Results Preliminary screening for the AgNPs can be observed from pale yellow to a brown color indicating that formation of AgNPs which can be observed by UV-Vis spectroscopy at 420 nm as shown in the figure due to the reduction of Ag+ ions and formation of surface plasmon resonance in the reaction mixture, while no color change appeared in culture filtrates without silver nitrate (Fig. 1a). HR-TEM is carried out to observe the shape and size of the produced nanoparticles. Figure 1b shows that 2 theta values clearly prove that the NPs formed are crystalline in nature. In addition, HR-TEM shows that actinomycetes have the tremendous capability to synthesize AgNPs which are well defined separated as much as possible, spherical in shape (Fig. 2).

5

Conclusion It can be concluded that green biosynthesis of AgNPs from actinomycetes is considered an excellent alternative route.

Fig. 1 (a) UV-Vis spectra and (b) XRD analysis of microbially synthesized AgNPs derived from actinobacterial strain, Streptomyces coeruleorubidus strain GRG4 (KY457708)

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(a)

(b)

Fig. 2 (a) Synthesized AgNPs nanoparticles; (b) TEM micrograph of synthesized AgNPs derived from actinobacterial strain, Streptomyces coeruleorubidus strain GRG4 (KY457708) References 1. Składanowski M, Wypij M, Laskowski D, Golinska P, Dahm H, Rai M (2017) Silver and gold nanoparticles synthesized from Streptomyces sp. isolated from acid forest soil with special reference to its antibacterial activity against pathogens. J Clust Sci 28(1):59–79

2. Vimala R, Sathishkumar G, Sivaramakrishnan S (2015) Optimization of reaction conditions to fabricate nano-silver using Couroupita guianensis Aubl. (leaf & fruit) and its enhanced larvicidal effect. Spectrochim Acta A Mol Biomol Spectrosc 135:110–115

Chapter 104 Biosynthesis and Characterization of Gold Nanoparticles from Actinobacteria R. T. V. Vimala, G. Rajivgandhi, S. Sridharan, M. Jayapriya, G. Ramachandran, C. Chenthis Kanisha, N. Manoharan, and Wen-Jun Li Abstract Biosynthesis method has emerged as simple, nontoxic, and environmental friendly and has been developed to produce Gold nanoparticles (AuNPs). In the present protocol, the extracellular synthesis of AuNPs is carried out using a culture supernatant of isolated actinomycetes. Bioreduction of AuNPs is confirmed by a UV-visible spectrophotometer that shows the peak between 520 and 550 nm. The size and distribution of the biosynthesized AuNPs are analyzed by HR-TEM that shows the formation of AuNPs. The crystalline nature and mean size of the AuNPs can be confirmed using XRD. The study shows the rapid and eco-friendly synthesis of AuNPs from actinomycetes. Key words AuNPs, Biosynthesis, HR-TEM, XRD, UV-visible spectrophotometer

1

Introduction Several physical and chemical based methods have been developed to produce AuNPs. The nanotechnology field are tremendously developed due to an eco-friendly and cost-effective process which is an easy to scale up nanoparticle production. Moreover, nanoparticles synthesis shows functional properties, improved stability and reproducibility are other advantages associated with the use of biological synthesis. Actinomycetes produce four specific proteins of molecular masses between 10 and 80 kDa. Different proteins and their interactions exhibit different nanocrystals that lead to the formation of complex morphology and size. Moreover, cysteine residues and free amine groups of the actinomycete proteins attach with AuNPs and stabilize synthesized nanoparticles. Different proteins may act as a capping and stabilizing agent on the surface of metal nanoparticles. Enzymes released out from cells might be the protein involved in the reduction of chloroauric ions and cap the

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_104, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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metal nanoparticles. Many microorganisms produce metal nanoparticles either intra or extracellularly. In the case of actinomycetes, metal ion reduction takes place on the mycelia surface of actinomycetes along with cytoplasmic membrane that results in nanoparticles formation. Ion transportation of the microbial cell involves the intracellular synthesis of nanoparticles. Considering all these advantages, microbial biosynthesis is considered as an excellent alternative approach for the extracellular synthesis of AuNPs.

2

Materials 1. Soil samples. 2. Starch-nitrate medium (20 g starch, 0.5 g K2HPO4, 1 g KNO3, 0.5 g MgSO4∙7H2O, 0.01 g FeSO4, 15 agar). 3. Gold chloride.

3

Methods

3.1 Isolation of Actinomycetes

1. Isolate actinomycetes strain from the soil samples according to the methods of [1]. 2. Maintain the isolated strains on starch-nitrate medium composed of the following components (g/L): 20 g starch, 0.5 g K2HPO4, 1 g KNO3, 0.5 g MgSO4∙7H2O, 0.01 g FeSO4, 15 agar (for solid medium), and pH 7. 3. Inoculate the isolated actinomycetes strains in a starch-nitrate agar medium. 4. Incubate at 30–32  C for 7 days.

3.2 Preparation of Cell-Free Extract

1. Inoculate the isolated actinomycetes strains in a starch-nitrate medium (50 ml). 2. Keep it for incubation in a rotary shaker at 200 rpm and 30–32  C for 7 days. 3. Centrifuge at 112,00  g for 10 min. Then, collect the supernatant for further experiments.

3.3 Biosynthesis of AuNPs

1. Add 1 mM Gold chloride (50 ml) solution equally with the actinomycete supernatants (50 ml) as described by the protocol of [2] with little modifications. 2. Incubate the samples in a shaker at 37  C and 200 rpm for 5 days. 3. Perform control experiments with an uninoculated media for nanoparticle synthesis. 4. Observe color change into yellowish violet.

Biosynthesis and Characterization of Gold Nanoparticles from Actinobacteria

3.4 Characterization of AgNPs Analyses

715

1. Examine the reduced gold ions by sampling about 2 ml of the solution at time intervals [1]. 2. Monitor UV-Vis spectra by UV-Vis spectroscopy analysis using spectrophotometer (UV-Vis spectroscopy; Thermo Spectronic, USA) at the wavelength range of 200–700 nm. 3. Characterize High Resolution Transmission Electron Microscopy (HR-TEM) studies of Gold nanoparticles using TEM microscope (HR-TEM; HT7800, RuliTEM) and then XRD (DMAX-RB; Rigaku, Japan).

4

Observation and Results Preliminary screening for the gold nano synthesis can be observed from pale yellow to purple color by mixing gold salts with the cellfree supernatant due to the reduction of Au+ ions and formation of surface plasmon resonance in the reaction mixture, while no color change appeared in culture filtrates without hydrogen tetrachloroaurate (III). It can be confirmed by a UV-Vis spectrophotometer that shows the range between 520 and 550 nm. Figure 1a shows the formation of AuNPs. HR-TEM is carried out to observe the shape and size of the produced nanoparticles. HR-TEM shows that actinomycetes have the tremendous capability to synthesize AuNPs which are well defined separated as much as possible, spherical in shape (Fig. 2a, b). In addition, XRD reveals the crystallinity of the synthesized nanoparticles which are formed owing due to the electrostatic repulsion between particles in the solution (Fig. 1b).

Fig. 1 (a) UV-Vis spectra and (b) XRD analysis of microbially synthesized AuNPs derived from actinobacterial strain, Streptomyces coeruleorubidus strain GRG4 (KY457708)

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(a)

(b)

Fig. 2 (a) Synthesized AuNPs gold nanoparticles; (b) HR-TEM images of the synthesized AuNPs derived from actinobacterial strain, Streptomyces coeruleorubidus strain GRG4 (KY457708)

5

Conclusion The present protocol reveals the simple and eco-friendly method for synthesis of AuNPs from actinomycetes which are considered as an excellent alternative approach.

References 1. Hulkoti NI, Taranath T (2014) Biosynthesis of nanoparticles using microbes-a review. Colloids Surf B: Biointerfaces 121:474–483 2. Ranjitha V, Rai VR (2017) Actinomycetes mediated synthesis of gold nanoparticles from

the culture supernatant of Streptomyces griseoruber with special reference to catalytic activity. 3 Biotech 7(5):299

Chapter 105 Antimicrobial Activity of Extracellular Green-Synthesized Nanoparticles by Actinobacteria R. T. V. Vimala, G. Rajivgandhi, S. Sridharan, M. Jayapriya, G. Ramachandran, C. Chenthis Kanisha, N. Manoharan, and Wen-Jun Li Abstract Biological systems such as bacteria, fungi, or plants for the synthesis of noble nanoparticles are easy, inexpensive, and eco-friendly. The synthesized nanoparticles using actinomycetes are the most important one which is highly toxic to bacteria and smaller nanoparticles synthesized by microbial route have a greater antibacterial activity when compared to their chemical moieties. Therefore, the study focuses mainly to evaluate in vitro antibacterial activity against Gram-positive and Gram-negative bacteria using synthesized silver nanoparticles (AgNPs) and gold nanoparticles (AuNPs) from actinobacterial strains. Key words Antibacterial activity, Biogenic synthesis, Silver nanoparticles, Gold nanoparticles

1

Introduction Silver is toxic to most bacterial cells and can be exploited as a potent bactericidal agent. Silver resistant bacterial strains store silver nanoparticles in their periplasmic space. Moreover, the antibacterial activity of the silver containing materials is widely used in medicine to reduce infections and also to prevent bacterial colonization on vascular grafts, dental materials, stainless steel materials, catheters, and human skin and also it has the potential advantages of small size, surface structure, coatings reactive groups and provide the maximum contact with the environment due to their welldeveloped surface. The antimicrobial activity of AgNPs is involved by interacting with microbes and then releases silver ions and finally, involves in cellular internalization process. Initially, AgNPs bind with the cell wall peptidoglycan and react with the cytoplasmic membrane and then targeted to ribosomal DNA particularly, at the sites of phosphorus and sulfur present in proteins. It preferably infects the cell division, respiratory chain, and finally causing cell death.

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_105, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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Gold nanoparticles are preferred over other inorganic nanoparticles for biomedical applications due to their excellent biocompatibility, nontoxic, stability of oxidation resistance. Gold nanoparticles found wide application in chemical testing, electronics, catalysis, drug delivery, imaging, and biological labeling. The improvement efficacy of antibacterial antibiotics conjugated with AuNPs could be achieved against various bacterial strains. In addition, the antibacterial properties of AgNPs and AuNPs are related to their slow oxidation and liberation of Ag+ and Au3+ ions to the environment, making them ideal biocidal agents. In the present study, we report the remarkable antimicrobial activity of AgNPs and AuNPs synthesized from actinobacterial strains.

2

Materials 1. Soil samples. 2. Starch-nitrate medium (20 g starch, 0.5 g K2HPO4, 1 g KNO3, 0.5 g MgSO4∙7H2O, 0.01 g FeSO4, 15 agar). 3. Muller Hinton agar. 4. AgNPs. 5. AuNPs.

3

Methods

3.1 Isolation of Actinomycetes

1. Isolate actinomycetes strains from the soil samples according to the methods of [1]. 2. Maintain the isolated strains on starch-nitrate medium composed of the following components (g/L): 20 g starch, 0.5 g K2HPO4, 1 g KNO3, 0.5 g MgSO4∙7H2O, 0.01 g FeSO4, 15 agar (for solid medium), and pH 7. 3. Inoculate the isolated actinomycetes strains in a starch-nitrate agar medium. 4. Incubate at 30–32  C for 7 days.

3.2 Preparation of Cell Free Extract

1. Inoculate the isolated actinomycetes strains in a starch-nitrate medium (50 ml). 2. Keep it for incubation in a rotary shaker at 200 rpm and 30–32  C for 7 days. 3. Centrifuge at 112,00  g for 10 min. Then, collect the supernatant for further experiments. 1. Perform bactericidal activity of synthesized AgNPs and AuNPs [2].

Antimicrobial Activity of Extracellular Green-Synthesized Nanoparticles. . .

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2. Spread the freshly prepared cultures over the petri plates containing Muller Hinton agar.

3.3 Antibacterial Activity of AgNPs and AuNPs

3. Make the gel puncture with a well size of 6 mm diameter over the petri plates. 4. Add the varying concentration of AgNPs (20, 40, 60, 80 μl) and AuNPs (20, 40, 60, 80 μl) in their respective wells. 5. Incubate the plates for 24 h at 37  C in the incubator. 6. Observe the zone of inhibition around the well after the incubation. 7. Maintain negative control (distilled water) and positive control (chloramphenicol).

4

Observation and Results AgNPs and AuNPs exert a detrimental effect on different human pathogens. The antimicrobial activity of the produced AgNPs and AuNPs can be measured using agar well diffusion method. Commonly, AgNPs and AuNPs biosynthesized by the bacterial supernatant shows greater antibacterial activity when compare with control (Negative control). Herein, Table 1 shows the antibacterial effect of AgNPs and AuNPs against bacterial pathogen.

Table 1 Antibacterial activity of AgNPs and AuNPs produced by actinobacterial strain, Streptomyces coeruleorubidus strain GRG4 (KY457708) against bacterial species Antibacterial activity AgNPs

AuNPs

Positive control 20 μl 40 μl 60 μl 80 μl 20 μl 40 μl 60 μl 80 μl 60 μl Zone of inhibition(mm)

Zone of inhibition(mm)

E. coli BDUMS-3 (KY617770)

8

12

18

18

6

9

16

16

23

B. cereus RMN1 (MK521259)

6

10

12

12

4

8

14

14

19

Proteus mirabilis strain BDUMS2 (KY617769)

5

8

10

10

4.5

8

12

12

16

K. pneumonia BDUMS 25 (MN396685)

4

9

14

14

5

7

12

12

18

Clinical isolates of human pathogen

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Conclusion It concludes that AgNPs and AuNPs can be synthesized from actinobacterial strains and have the potential ability to act as an antimicrobial agents.

References 1. Składanowski M, Wypij M, Laskowski D, Golinska P, Dahm H, Rai M (2017) Silver and gold nanoparticles synthesized from Streptomyces sp. isolated from acid forest soil with special reference to its antibacterial activity against pathogens. J Clust Sci 28(1):59–79

2. Hamed M, Abdelftah L (2019) Biosynthesis of gold nanoparticles using marine Streptomyces griseus isolate (M8) and evaluating its antimicrobial and anticancer activity. Egypt J Aquat Biol Fish 23(1):173–184

Chapter 106 Antibiofilm Activity of Extracellular Green-Synthesized Nanoparticles by Actinobacteria R. T. V. Vimala, G. Rajivgandhi, S. Sridharan, M. Jayapriya, G. Ramachandran, C. Chenthis Kanisha, N. Manoharan, and Wen-Jun Li Abstract Scientists have recently focused the nanoparticle due to their potent antimicrobial activity. The increasing resistance to antibiotics related to microbial biofilms creates an urgent need to find out an alternative and active antibiofilm agent. Moreover, the antibiofilm property of the AgNPs and AuNPs can be exploited in medical devices to avert microbial colonization. Therefore, the present protocol focuses to assess the significant antibiofilm activity toward pathogenic microbes using the synthesized silver nanoparticles (AgNPs) and gold nanoparticles (AuNPs), since it reflects its possibility to use in the biomedical field. Key words Biofilms, Silver nanoparticles, Gold nanoparticles, Multidrug resistance

1

Introduction Nanoparticles are recently exploited in many fields such as medicine, food, electronics, and agriculture. Nanoparticles can be synthesized either chemically or biologically. Due to the continuous increase in microbial multidrug resistance and antibiotic therapy limitations, there is an urgent need to develop an efficient antimicrobial agent with new mechanisms of action. The chemical synthesis of metal nanoparticles involves the use of hazardous chemicals to change the metal ions into metal nanoparticles. Biologically synthesized metal nanoparticles derived from actinomycetes have many advantages compared to chemical synthesis due to the use of ecofriendly agents as reducing and stabilizing agents. AgNPs and AuNPs have been proven as efficient metallic nanoparticles due to their promising bioactivities that can include antioxidant, antibacterial, and antibiofilm properties. The potential antibiofilm property of the AgNPs and AuNPs can be utilized in medical devices to decrease the infections of microbes and to avert colonization of bacteria on medical equipment such as catheters,

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_106, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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dental materials, stainless steel materials, vascular grafts, and human skin. Therefore, AgNPs and AuNPs can be exploited to reduce the formation of biofilm, thereby reducing the transmission of infectious diseases. Recently, bacterial biofilms have been considered as one of the public health concerns. The present protocol aims to focus on the antibiofilm activities of biosynthesized AgNPs and AuNPs against bacterial pathogens.

2

Materials 1. Soil samples. 2. Starch-nitrate agar medium (20 g starch, 0.5 g K2HPO4, 1 g KNO3, 0.5 g MgSO4∙7H2O, 0.01 g FeSO4, 15 agar). 3. AgNPs. 4. AuNPs.

3

Methods

3.1 Isolation of Actinomycetes

1. Isolate actinomycetes strains from the soil samples according to the methods of [1]. 2. Maintain the isolated strains on starch-nitrate medium composed of the following components (g/L): 20 g starch, 0.5 g K2HPO4, 1 g KNO3, 0.5 g MgSO4∙7H2O, 0.01 g FeSO4, 15 agar (for solid medium), and pH 7. 3. Inoculate isolated actinomycetes strains in a starch-nitrate agar medium. 4. Incubate at 30–32  C for 7 days.

3.2 Preparation of Cell Free Extract

1. Inoculate the isolated actinomycetes strains in a starch-nitrate medium (50 mL). 2. Keep it for incubation in a rotary shaker at 200 rpm and 30–32  C for 7 days. 3. Centrifuge at 112,00  g for 10 min. 4. Collect the supernatant for further experiments.

3.3 In Vitro Antibiofilm Activity of AgNPs and AuNPs

1. Analyze the biofilm inhibitory activity of the synthesized AgNPs and AuNPs against clinical microbes using microtiter plate assay [2]. 2. Add 180 mL of lysogeny broth (Tryptone, 10.0; yeast extract, 5.0; NaCl, 10.0. At pH 7.2) and 10 mL of overnight actinobacterial broth with synthesized AgNPs and AuNPs at a

Antibiofilm Activity of Extracellular Green-Synthesized Nanoparticles by. . .

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Fig. 1 Antibiofilm inhibitory activity derived from actinobacterial strain, Streptomyces coeruleorubidus strain GRG4 (KY457708) against pathogenic bacteria

minimal inhibitory concentration of 20 mg/mL (confirmed with varying concentration of 10–40 mg). 3. Maintain the negative control. Incubate it for 24 h at 37  C. After the incubation, wash with phosphate buffer saline pH 7.2. 4. Add crystal violet for staining and incubate it for 1 h. Then, wash with distilled water and dry. Further, measure the optical density at 570 nm using an absorbance plate reader.

4

Observation and Results

4.1 Antibiofilm Activity of AgNPs and AuNPs

5

The ability of the AgNPs and AuNPs to eradicate bacterial biofilm formation of pathogenic bacteria (Pseudomonas aeruginosa and Staphylococcus aureus) can be measured using microtiter plate assay. Commonly, AgNPs and AuNPs samples exhibit greater biofilm inhibition activity against pathogenic bacteria when compared with control. Herein, Fig. 1 shows the maximum antibiofilm effect of AgNPs and AuNPs against bacterial pathogens.

Conclusion It can be concluded that AgNPs and AuNPs synthesized from actinobacterial strains have the potential to be used as an antibiofilm agent that can be exploited in nanomedicine.

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References 1. Składanowski M, Wypij M, Laskowski D, Golinska P, Dahm H, Rai M (2017) Silver and gold nanoparticles synthesized from Streptomyces sp. isolated from acid forest soil with special reference to its antibacterial activity against pathogens. J Clust Sci 28(1):59–79

2. Deepika MS, Thangam R, Vijayakumar TS, Sasirekha R, Vimala R, Sivasubramanian S, Arun S, Babu MD, Thirumurugan R (2019) Antibacterial synergy between rutin and florfenicol enhances therapeutic spectrum against drug resistant Aeromonas hydrophila. Microb Pathog 135:103612

Chapter 107 Cytotoxic Activity of Extracellular Green Synthesized Nanoparticles by Actinobacteria R. T. V. Vimala, G. Rajivgandhi, S. Sridharan, M. Jayapriya, G. Ramachandran, C. Chenthis Kanisha, N. Manoharan, and Wen-Jun Li Abstract Nanoparticles biosynthesis is the cost effective eco-friendly methods which is an alternative to chemical and physical methods. Owing due to the research interest in nanotechnology, biomedical applications and microbial biotechnology, nanoparticles synthesis using microbes are being exploited widely. Cytotoxicity of biosynthesized silver nanoparticles (AgNPs) and gold nanoparticles (AuNPs) against in vitro human cancerous cell line shows an anticancer activity in terms of IC50 values. Further studies are required to elucidate the toxicity and the mechanism involved with anticancer activity of the synthesized AgNPs and AuNPs. Key words Anticancer activity, Silver nanoparticles, Gold nanoparticles, Cancerous cell line

1

Introduction Nanotechnology can be used as an excellent platform by modifying and developing the properties of the metals properties by changing them into nanoparticles which have wide applications in numerous fields like drug delivery, antimicrobial agents, diagnostic, and treatment of various diseases. Biological resources such as actinomycetes, plants, yeast, fungi, and bacteria can be employed for nanoparticle synthesis including AgNPs and AuNPs, which exhibits different biological activity. The biological synthesis of metal nanoparticles has been achieved by different microorganisms. Among these, actinomycetes are considered an important resource for new products of medical and industrial interest. They are being used as eco-friendly nanofactories. The synthesis of nanoparticles by actinomycetes represents good stability and polydispersity. In addition, nanoparticle produced by actinomycetes exhibits important biocidal activity against different pathogens. Moreover, it can be manipulated

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_107, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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genetically to provide better control oversize. The present protocol is used to assess the anticytotoxic activity of AgNPs and AuNPs synthesized from actinobacterial strains.

2

Materials 1. Soil samples. 2. Starch-nitrate agar medium (20 g starch, 0.5 g K2HPO4, 1 g KNO3, 0.5 g MgSO4∙7H2O, 0.01 g FeSO4, 15 agar). 3. AgNPs. 4. AuNPs. 5. DMSO. 6. MTT.

3

Methods

3.1 Isolation of Actinomycetes

1. Isolate actinomycetes strains from the soil samples according to the methods of Składanowski et al. [3]. 2. Maintain the isolated strains on starch-nitrate medium composed of the following components (g/L): 20 g starch, 0.5 g K2HPO4, 1 g KNO3, 0.5 g MgSO4∙7H2O, 0.01 g FeSO4, 15 agar (for solid medium), and pH 7. 3. Inoculate the isolated actinomycetes strains in a starch-nitrate agar medium. 4. Incubate at 30–32  C for 7 days.

3.2 Preparation of Cell Free Extract

1. Inoculate the isolated actinomycetes strains in a starch-nitrate medium (50 mL). 2. Keep it for incubation in a rotary shaker at 200 rpm and 30–32  C for 7 days. 3. Centrifuge at 112,00  g for 10 min. 4. Collect the supernatant for further experiments.

3.3 Cytotoxic Activity of AgNPs and AuNPs on Human Tumor Cell Lines

MTT [3-(4, 5-dimethylthiazol 2-yl)-2, 5-diphenyltetrazolium bromide] assay is explored to find out IC50 concentration of the nanoparticles [1, 2]. 1. Dissolve AgNPs and AuNPs in 0.1% DMSO (Sigma, St. Louis, USA) buffer. 2. Add A549 cell lines with the varying concentrations of the AgNPs and AuNPs (10, 25, 50, and 100 μg/mL) for 24, 48, and 72 h. 0.1% of DMSO is used as the solvent control.

Cytotoxic Activity of Extracellular Green Synthesized Nanoparticles. . .

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Fig. 1 Anticancer activity of (a) AgNPs and (b) AuNPs derived from actinobacterial strain, Streptomyces coeruleorubidus strain GRG4 (KY457708)

3. Aspirate and remove the liquids carefully after the treatment, followed by the addition of 20 μL of MTT solution (5 mg/mL in phosphate buffered saline) to each well and incubates for 4 h. 4. Add 100 μL of DMSO to dissolve the formed formazan crystals. Measure the amount of formazan at 560 nm using a microplate reader (Bio-Rad, California, USA). Repeat the experiments thrice. Finally, calculate the inhibition percentage.

4

Observations and Results

4.1 Anticancer Activity

5

Anticancer effect of the synthesized AgNPs and AuNPs can be measured using MTT. Mitochondrial dehydrogenase reduces MTT that leads to the formation of a purple formazan product. To evaluate the anticancer activity of AgNPs and AuNPs produced by actinomycetes, several steps are carried out: lyophilization, cytotoxicity test, and effect of the median inhibitory dose (IC50) on different tumor cell lines. AgNPs and AuNPs derived from actinomycetes show a reasonable degree of anticancer activity after the incubation with cancerous cell lines. From the data, a line graph was plotted between concentrations versus % inhibition by varying concentrations of 10, 25, 50, and 100 μg/mL. As clearly shown in Fig. 1, effect of AgNPs and AuNPs on a tumor cell line shows a dose-dependent decrease in viability percentage of cell lines.

Conclusion It can be concluded that AgNPs and AuNPs synthesized from actinobacterial strains can serve as an effective cytotoxic agent.

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References 1. Deepika MS, Thangam R, Sheena TS, Vimala R, Sivasubramanian S, Jeganathan K, Thirumurugan R (2019) Dual drug loaded PLGA nanospheres for synergistic efficacy in breast cancer therapy. Mater Sci Eng C 103:109716 2. Abd-Elnaby HM, Abo-Elala GM, Abdel-Raouf UM, Hamed MM (2016) Antibacterial and anticancer activity of extracellular synthesized silver

nanoparticles from marine Streptomyces rochei MHM13. Egypt J Aquat Res 42(3):301–312 3. Składanowski M, Wypij M, Laskowski D, Golinska P, Dahm H, Rai M (2017) Silver and gold nanoparticles synthesized from Streptomyces sp. isolated from acid forest soil with special reference to its antibacterial activity against pathogens. Journal of Cluster Science 28 (1):59–79

Chapter 108 Sporicidal Activity of Extracellular Green-Synthesized Nanoparticles by Actinobacteria R. T. V. Vimala, G. Rajivgandhi, S. Sridharan, M. Jayapriya, G. Ramachandran, C. Chenthis Kanisha, N. Manoharan, and Wen-Jun Li Abstract Actinobacteria are considered as a potential source of bioactive compounds as targets in screening programs due to their diversity and their proven ability to produce novel metabolites and other molecules of pharmaceutical importance. Therefore, silver nanoparticles (AgNPs) and gold nanoparticles (AuNPs) synthesized from Actinobacterial sp. cell filtrate has become a promising alternative to the conventional chemical synthesis approach. Further, biosynthesized and characterized AgNPs and AuNPs can be applied for significant sporicidal activity. Therefore, this protocol exhibits the distinctive potential of biogenic AgNPs and AuNPs for their efficient use in developing novel sporicidal agents synthesized from Actinobacterial sp. cell filtrate. Key words Sporicidal activity, Biogenic synthesis, Silver nanoparticles, Gold nanoparticles

1

Introduction Nanotechnology is an emerging technology that includes scientific fields such as physics, chemistry, biology, material science, and medicine. Generally, nanoparticles are synthesized by breaking down bulk materials into nanosized materials. Actinobacterial extract remains an outstanding source when compare with other microorganisms and plant materials because of its increased extracellular reductive metabolites production and easy handling to develop a clean, nontoxic, biocompatible, and eco-friendly procedure for the synthesis of nanoparticles. The adherence of AgNPs and AuNPs to the surface of spore coat, pit formation, and its complete structural loss can be detected under field emission scanning electron microscopy. It strongly recommends that the application of AgNPs and AuNPs as a sporicidal agent could be a new approach in reliably removing the hazardous Bacillus spores. Moreover, the synthesis of NPs with

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1_108, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

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improved stability, functional properties, and reproducibility are other advantages associated with the use of biological synthesis. To address this thrust area of research, the study is focused to find out the determination of sporicidal properties of biosynthesized and characterized AgNPs and AuNPs against vegetative cells and spores of Bacillus subtilis, a model spore forming bacteria.

2

Materials 1. Soil samples. 2. AgNPs. 3. AuNPs. 4. Potassium phosphate buffer.

3

Methods

3.1 Sporulation Procedure

1. Allow the fresh culture of B. cereus to inoculate in the propagation medium and incubate at 37
C for 24 h. 2. Transfer the inoculum into the sporulation medium and incubate at 37
C for 2 days. 3. Wash the spores with 10 mM potassium phosphate buffer (pH– 6.8) and visualize the spore image under phase contrast microscopy and store by refrigeration at 2–8
C. 4. Determine the spore count and its viability.

3.2

Sporicidal Assay

The assay has been performed according to the methodology of [1, 2]. 1. Spread B. cereus spore suspension on nutrient agar plates (supplemented with 0.06 g of MgSO4 and 0.25 g of KH2PO4 per liter) and incubate at 37
C for 10 days to develop spore formation. 2. Perform Schaeffer Fulton differential staining to observe the spores and vegetative cells after the incubation. 3. Purify it by centrifugation for 10 min at 112,00  g twice. 4. Suspend the precipitated spores in sterile deionized water and then, vortex to create a homogenous suspension. 5. Add the varying concentrations of 100–200 μg/mL of AgNPs and AuNPs with spore suspension for different periods of exposure i.e., 0–8 h. 6. After the treatment, perform serial 10X dilutions and plate onto nutrient agar plates and incubate at 37
C for 24 h.

Sporicidal Activity of Extracellular Green-Synthesized Nanoparticles by. . .

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7. Calculate the colony forming unit value after the incubation. Similarly, calculate the sporicidal activity % and log10 reduction values based on the formulae. Maintain control without untreated spores. Sporicidal% ¼ No:of CFU from untreated sporesNo:of CFU from treated spores ∗100 No:of CFU from untreated spores

Log reduction ¼ log 10 ðA=B Þ

4

Observations and Results When evaluating the sporicidal activity of biosynthesized AgNPs and AuNPs, the assay shows maximum susceptibility toward nanoparticles against B. cereus spores by applying varying concentrations (100–200 mg/mL) of AgNPs and AuNPs for different exposure time i.e., 0–8.0 h (Fig. 1). The result of sporicidal activity of B. cereus spores upon treatment with AgNPs and AuNPs shows higher reduction. Moreover, the higher concentrations of AgNPs and AuNPs are required to act against spores due to the structural complexity when compared with vegetative cells.

Fig. 1 Log10 reduction of sporicidal activity of AgNPs and AuNPs derived from actinomycetes (100 μg/mL). Mean are represented as standard deviation (n)

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Conclusion It is concluded that the protocol demonstrates the potential of biosynthesized AgNPs and AuNPs as a sporicidal agent.

References 1. Gopinath PM, Dhanasekaran D, Ranjani A, Thajuddin N, Akbarsha MA, Velmurugan M, Panneerselvam A (2015) Optimization of sporicidal activity and environmental Bacillus endospores decontamination by biogenic silver nanoparticle. Future Microbiol 10(5):725–741

2. Narayanan KB, Sakthivel N (2010) Biological synthesis of metal nanoparticles by microbes. Adv Colloid Interf Sci 156(1–2):1–13

INDEX A Acarbose ........................................................................ 475 Acetylene .............................................................. 596, 597 Acid protease ................................................................. 533 Actinobacteria.............................................. 193, 276, 463 actinomycetes .......................................................... 616 antibacterial compounds, screening, characterization, and identification................................ 371, 372 extraction .................................................. 373, 374 physicochemical characterization .............374–376 screening ................................................... 372, 373 thin-layer chromatography ...................... 376, 377 associations from mangrove plants .......................... 76 bioactive components ............................................. 109 bioactive compounds .............................................. 611 bioactive molecules ................................................. 595 biochemical characteristics...................................... 698 biochemical identification....................................... 586 biological functions................................................. 611 biological management........................................... 615 characterization of biochemical methods ........................................ 697 colony morphology........................................... 696 microscopic morphology .................................. 696 chemical profiling........................................... 357, 358 cold loving ............................................................... 142 colonies of ................................................................. 51 colony morphologies ................................................ 80 crude extract chemical profiling ............................. 351 cultivation techniques of......................................... 170 Actinomadura isolation ........................... 177, 178 Actinoplanes isolation .............................. 176, 178 Actinopolyspora isolation ................................... 175 Frankia isolation ...................................... 175, 176 heat treatments and culture media................... 177 materials.....................................................170–172 Micromonospora isolation.................................. 178 Nocardia isolation.....................................173–174 Nocardiopsis isolation ............................... 172, 173 Pseudonocardia isolation ................................... 174 Saccharomonospora isolation ............................. 175 Saccharopolyspora isolation....................... 174, 175 culture ...................................................................... 354 decolorization ability of .......................................... 698

degradation of dye ............................................ 700 textile dyes ................................................ 699, 700 decolorization process carbon sources ................................................... 702 consortium effect of.......................................... 703 incubation period .............................................. 701 NaCl effect ........................................................ 701 nitrogen sources ................................................ 702 pH effect............................................................ 701 temperature effect ............................................. 701 description ................................................................. 75 drug repurposing strategy, bioactive metabolites of ..................................... 293, 294 dataset cleaning ........................................ 295, 296 enrichment analysis, validation by.................... 297 e-Pharmacophore Model generation296, 298–300 materials............................................................. 294 MD simulation studies............................. 303, 305 molecular docking............................................. 303 PHASE database screening..............297, 301, 302 receptor grid generation ................................... 296 retrieval of dataset ............................................. 295 dye decolorization ability anaerobic degradation....................................... 697 broth assay ......................................................... 697 enzyme mediated decolorization/degradation ....................... 697 plate assay .......................................................... 697 dye polluted soil ...................................................... 698 E-waste (see E-waste) extraction and crude extract .......................... 350, 356 fecal and tissue samples............................................. 46 spread plate technique ..................................46, 48 from compost samples banana waste compost ........................................ 41 manure sample preparation ................................ 41 media preparation ............................................... 43 serial dilution technique ..................................... 41 from coral reef bioactive natural products .................................. 32 biological structures ............................................ 31 flowchart .............................................................. 33 serial dilution method......................................... 34 spatial heterogeneity ........................................... 31

Dhanasekaran Dharumadurai (ed.), Methods in Actinobacteriology, Springer Protocols Handbooks, https://doi.org/10.1007/978-1-0716-1728-1, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

733

METHODS IN ACTINOBACTERIOLOGY

734 Index

Actinobacteria (cont.) from dye polluted soil ............................................. 696 from earthworm casts flowchart of ......................................................... 37 proliferation of microflora .................................. 35 soil fertility........................................................... 35 FTIR and optical rotation data acquisition.................................. 354, 363, 364 gastrointestinal and systemic diseases ...................... 46 gold nanoparticle synthesis (see Gold nanoparticle synthesis) growth ..................................................................... 595 HPLC optimization and compound separation ..................................................... 358 HPLC separation ........................................... 352, 353 HRIT-TOF-MS data acquisition ........................... 361 isolation from desert soils collection of the soil sample ............................. 110 materials required.............................................. 110 media preparation and plating techniques........................................... 110, 111 isolation from mangrove plants epiphytic/phylloplane actinobacteria........... 79–80 isolation methods .......................................... 77–79 requirements........................................................ 77 LCMS-IT-TOF-MS data acquisition ............ 353, 355 leaf and root of mangrove plant ............................... 38 marine-derived .......................................................... 76 materials................................ 595, 596, 611, 616–618 metabolic capabilities .............................................. 595 methods .........................................596, 597, 612, 613 microbial antagonists .............................................. 616 microbial broth culture.................................. 349, 350 microorganisms .............................................. 615, 616 microscopic examination ........................................ 586 miniaturized production, bioactive extracts ................................................ 367, 368 antimicrobial activity ................................ 369, 370 compounds ........................................................ 369 extraction of ...................................................... 369 materials............................................................. 368 protocol ............................................................. 369 molecular identification ................................. 586, 587 morphological characteristics ................................. 698 plant roots ............................................................... 615 protocol ................................................................... 616 RP-18 column chromatography .......... 351, 352, 358 secondary metabolites................................... 348, 611, (see also Silvernanoparticle synthesis) soil health................................................................. 611 soil, isolation from ...................................................... 2 strains ................................................................ 53, 611 symbiotic interactions ............................................... 52 taste and odor description ...................................... 631

uses............................................................................... 8 whole-genome analysis, methods for bioinformatics and evolutionary studies .......... 196 bioinformatics and genome-wide association studies .......................................................... 195 bioinformatics and identification of mutations ................................................ 195 biological research............................................. 194 Blast Matrix ....................................................... 201 Codon Adaptation Index.................................. 198 codon usage......................................196–198, 200 genomic research, bioinformatics in ....... 194, 195 materials............................................................. 196 Pan–Core genome plot............................ 201, 202 phylogeny and evolutionary analysis ........203–205 protein energetic cost ....................................... 200 Relative Synonymous Codon Usage....... 197, 199 statistical analysis ............................................... 200 tRNA Adaptation Index ................................... 200 uncultivable microbes, metagenomics for ....... 202 Actinobacteria cultures ................................................. 565 Actinobacteria extracts.................................................. 408 Actinobacteria isolation from fishes ........................................................... 61–63 culture independent techniques ......................... 67 culture media....................................................... 66 DNA extraction.............................................67, 68 homogenization .................................................. 66 isolation of gut .................................................... 65 materials......................................................... 63–65 NGS, sample preparation for.............................. 67 preparation .......................................................... 69 protocol ......................................................... 70–72 sample collection ................................................. 65 16S rRNA gene, processing and analysis of..........................................69, 70 subculturing and purification ............................. 67 from termites ............................................................. 51 aseptic removal and homogenization ..........55, 56 biotic and abiotic factors .................................... 52 chitin agar ............................................................ 56 defatted wood powder media............................. 56 HVA media .......................................................... 56 identification........................................................ 57 isolation and culturing ........................................ 56 ISP-2 .................................................................... 56 materials.........................................................53, 54 protocol .........................................................57, 58 sample collection ...........................................54, 55 sample processing and surface sterilization .................................................... 55 SCA media ........................................................... 56 sub-culturing and purification......................56, 57 Actinobacteria isolation agar ....................................77, 79

METHODS Actinobacterial bioherbicides, screening and analysis of growth and vigor index seedlings .......................... 542 moist chamber technique .............................. 539–541 rolled paper towel assay ................................. 539, 540 Actinobacterial metabolites .......................................... 454 Actinobacterial peptides culturing and harvesting ......................................... 274 equilibration ............................................................ 275 MALDI-TOF ................................................. 273, 274 MASCOT search ..................................................... 274 materials aTCC 172 medium........................................... 276 equilibration ...................................................... 275 preparation ........................................................ 274 Actinobacterial strain .................................. 710, 716, 719 Actinomadura isolation ....................................... 177, 178 Actinomycetes ............................193, 379, 414, 415, 672 antagonistic activity of agar streak method............................................ 382 determination agar disk method............................................... 383 dual culture method.......................................... 384 identification............................................................ 194 isolation of ...................................................... 380, 381 natural product........................................................ 229 screening of ............................................................. 380 agar disk method............................................... 382 agar streak method............................................ 381 dual culture method................................. 382, 383 Actinomycetes isolation agar (AIA) ..............87, 142, 672 Actinomycins ................................................................. 618 Actinoplanes isolation .......................................... 176, 178 Actinopolyspora isolation ............................................... 175 Actinorhizal plants ........................................................ 603 Active site finder............................................................ 251 Adaptation ..................................................................... 145 Aerobic microbes ............................................................ 40 Agar dilution assay ............................................... 405, 406 Agar disk method.......................................................... 383 actinomycetes .......................................................... 382 Agar plug diffusion ....................................................... 391 Agar streak method....................................................... 382 actinomycetes .......................................................... 381 Agar well diffusion assay............................................... 575 Agar well diffusion method................................. 584, 612 Agarose gel electrophoresis .......................................... 439 Alkaliphilic actinobacteria ............................................. 146 Alpha-amylase....................................................... 475, 476 Alpha-Amylase Inhibition Assay................................... 477 Alpha-glycosidase .......................................................... 475 Amoebiasis..................................................................... 413 Amoebic colitis .............................................................. 414 Amylase .......................................................................... 495 experimental protocol ............................................. 498

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ACTINOBACTERIOLOGY Index 735

solid state fermentation .......................................... 497 Amylase activity .................................................... 476, 499 Amylolytic activity ......................................................... 495 Anaerobic degradation.................................................. 697 Analipus japonicus .......................................................... 84 Animal biofilm-associated infections............................ 484 Annotation ........................................................... 212, 219 Antagonistic activity actinomycetes agar streak method............................................ 382 Antiamoebic activity IC50 analysis ............................................................ 416 in vitro ............................................................ 415, 416 observation .............................................................. 416 Anti-biofilm Assay ................................................ 484, 485 Antibiotic susceptibility test ....................... 550, 551, 583 Antibiotics ............................................................ 1, 7, 238 Antibiotics and Secondary Metabolite Analysis SHell (antiSMASH) ............................................... 222 Anticancer activity ......................................................... 425 diphenylpicrylhydrazine (DPPH) assay ........ 453, 454 DNA fragmentation assay (see DNA fragmentation assay) dual staining method materials............................................................. 428 methods ............................................................. 428 hydrogen peroxide scavenging assay ............. 461, 462 lactic acid dehydrogenase assay ..................... 435, 436 metal chelating assay ...................................... 457, 458 neutral red uptake assay ................................. 431, 432 nitric oxide scavenging assay ......................... 455, 456 total antioxidant assay .................................... 459, 460 trypan blue exclusion assay (see Trypan blue exclusion assay) Antifreeze proteins (AFPs) ........................................... 467 production/purification ......................................... 468 Antimalarial agent ......................................................... 410 Antimalarial assay ................................................. 408–411 Antimicrobial activity screening, of actinobacteria extraction .................................................. 373, 374 physicochemical characterization .............374–376 screening ................................................... 372, 373 thin-layer chromatography ...................... 376, 377 Antimycobacterial activity actinobacterial extracts/compounds, screening of......................................... 395, 396 actinobacterial extract and cell suspension preparation................................................... 397 actinomycete extract preparation ..................... 396 LRP procedure ......................................... 397, 398 materials............................................................. 396 phage propagation and titer calculation ........................................... 396, 397

METHODS IN ACTINOBACTERIOLOGY

736 Index

protocol ............................................................. 398 Mycobacterium smegmatis .............................. 391, 392 materials............................................................. 392 methods ............................................................. 392 protocol ............................................................. 392 Antiplasmodial activity.................................................. 411 AntiSMASH ........................................238, 239, 244, 248 detection .................................................239–241, 243 Streptomyces..................................................... 250, 254 Anti-TB activity by agar dilution assay ..................................... 405, 406 by microplate alamar blue assay (MABA) .............................................. 401–403 Antiviral Assay ...................................................... 420, 421 Aquaculture ...............................................................27, 28 Ascorbic acid method ................................................... 590 Aspergillus niger ............................................................ 527 Atherosclerosis .............................................................. 457 Autodock .............................................289, 291, 314–316 AutoDock 4.2 tool........................................................ 289 Autodock4 software ...................................................... 289 Autogrid ........................................................................ 291

B Bacillus genus ................................................................ 533 Bacterial biofilms ........................................................... 483 Bacterial plant pathogens.............................................. 612 Bacteriocins ................................................................... 267 acrylamide/bisacrylamide....................................... 269 BPB ................................................................. 269, 270 MRS broth............................................................... 268 protein concentration ............................................. 270 resolving gel buffer ................................................. 268 SDS-PAGE .............................................................. 270 stacking gel buffer ................................................... 268 Bacteriophage ............................................................55, 56 Bifidobacteria composition of .......................................................... 48 PCR program ......................................................49, 50 PCR reactions............................................................ 49 Bifidobacterium ............................................................... 62 Bile salt deconjugation......................................... 576, 585 Bile salt tolerance test ................................................... 582 Bioactive compound production.................................. 626 Bioactive compounds...................................................... 98 Bioactive metabolites actinobacteria drug repurposing strategy ................................ 294 Bioactive secondary metabolites ........................... 36, 163 Biochemical test ................................................................ 9 Biocontrol activity ......................................................... 612 Biofilm ........................................................................... 479 Biofilm bacteria ............................................................. 483 Biogenic amines production................................ 576, 584

Bioinformatics ............................................................... 335 and evolutionary studies ......................................... 196 and genome-wide association studies .................... 195 and identification of mutations .............................. 195 Biological nitrogen fixation .......................................... 114 Biological pest control .................................................. 114 Biological process.......................................................... 114 Biomineralization .......................................................... 487 Biomining ...................................................................... 706 Bioremediation.............................................................. 114 Biosurfactant production drop folding test...................................................... 643 emulsification index measurement ......................... 643 hemolytic assay ........................................................ 643 lipase activity............................................................ 643 materials................................................................... 642 oil-spreading method.............................................. 643 Biosurfactants characterization of.......................................... 648, 649 chemical composition .................................... 655, 656 critical micelle concentration (CMC) and surface tension.......................................................... 654 emulsification index and emulsification activity (EA)..................................................... 654, 655 hydrophobic component ........................................ 648 natural sources-derived biosurfactants................... 648 OVAT/OFAT approach growth/production parameters........................................... 649, 650 purification of ........................................ 648, 651, 653 stability and tolerance ............................................. 655 statistical optimization approach................... 650–652 Biosynthetic Gene Cluster (BGCs) .............221–223, 229 Blast Matrix (BM) ......................................................... 201 Boswellic acid ................................................................ 446 Bovine serum albumin (BSA)....................................... 270 Brevibacterium ammoniagenes ..................................... 488 Broth assay............................................................ 697, 699 BUSCOv1 ..................................................................... 218

C Caatinga biome ............................................................. 497 Calcium carbonate induced biomineralization............ 488 Calcium chloride method .................................... 492, 493 Carbohydrate hydrolyzing enzymes............................. 475 Carbon source ............................................................... 692 Carboxylesterases .......................................................... 156 Carboxymethylcellulose (CMC) .................................. 521 Caspase-Activated DNase (CAD) ................................ 440 CASTp analysis .............................................................. 287 Casuarina sp. abiotic and biotic stresses ....................................... 604 actinorhizal host ...................................................... 603 actinorhizal plants ................................................... 603 ecosystem and habitat types ................................... 604

METHODS materials.......................................................... 605, 606 methods .......................................................... 606–608 nitrogen ................................................................... 604 nitrogen-fixing microsymbionts ............................. 603 physical and microbiological quality ...................... 604 soil fertility............................................................... 604 Caulerpa racemosa .......................................................... 84 Caulerpa scalpelliformis .................................................. 84 Caulerpa taxifolia ........................................................... 84 Cell proliferation ........................................................... 429 Cellulase enzyme production ................................................. 523 materials................................................................... 522 pretreatment of soil................................................. 522 sample collection ..................................................... 522 screening of isolates ................................................ 522 Cellulolytic activity........................................................ 524 Cellulose degradation of ........................................................... 62 Chemical composition ......................................... 655, 656 Chemotaxonomy........................................................... 181 cell wall amino acids....................................... 183, 184 fatty acids ........................................................ 183, 184 whole cell sugars ............................................ 182, 183 Chromobacterium violaceum......................................... 480 Chromosomal aberrations ............................................ 451 Cladograms.................................................................... 188 Cluster BLAST ..................................................... 256, 257 Cluster PFAM analysis .................................................. 251 ClusterBlast analysis ...................................................... 251 Coagulation ..................................................................... 11 Codeml package ............................................................ 204 Codon Adaptation Index (CAI) .................................. 198 Codon usage bias (CUB) .................................... 198, 200 CodonW software ................................................ 196, 199 Colorimetric assay ......................................................... 423 Colorimetric method .................................................... 622 Column chromatography ............................................. 686 Column selection .......................................................... 359 Communicable diseases ................................................ 484 Comparative genomics ................................................. 230 BPGA ....................................................................... 231 Composting banana waste compost .............................................. 41 biofertilizers and soil amendments .......................... 39 degradable organic products and wastes ................. 39 manure sample preparation ...................................... 41 media preparation ..................................................... 43 mesophilic stage ........................................................ 40 organic residues......................................................... 40 serial dilution technique ........................................... 41 thermophilic stage..................................................... 40 Composting process...................................................... 156

IN

ACTINOBACTERIOLOGY Index 737

Compound Annual Growth Rate (CAGR) ................. 647 Critical micelle concentration (CMC) ......................... 654 Crude e-waste recycling................................................ 706 Crude extract chemical profiling .................................. 351 Crustose lichens ............................................................ 133 Cryoprotective agents ................................................... 468 Cryotubes ...................................................................... 498 Cycloheximide................................................70, 127, 138 Cyclomarin A................................................................. 463 Cytochrome P450 hydroxylase (CYP)......................... 264 Cytotoxicity .......................................................... 419, 423

D Dataset cleaning drug repurposing strategy ............................. 295, 296 Deep sea ecosystem......................................................... 13 Delayed apoptotic cells ................................................. 429 Desert soils ecosystem................................................................. 109 environments ........................................................... 109 isolation of actinobacteria.............................. 110–111 soil sample ............................................................... 110 Diabetes mellitus ........................................................... 475 Diaminopimelic acid (DAP) ......................................... 182 Dilution methods................................................. 401, 554 Diphenylpicrylhydrazine (DPPH) assay ............. 453, 454 Direct inoculation technique........................................ 118 Disk diffusion assay ....................................................... 481 Distribution, of actinobacteria ..................................... 131 DNA fragmentation ...................................................... 429 agarose gel electrophoresis ..................................... 439 DNA separation method ............................... 441, 442 materials................................................................... 440 mechanisms of fragmentation ................................ 439 DNase test ............................................................ 550, 551 Docking Streptomyces, receptor cavity-based approach.............................................. 314–316 Domain architecture ............................................ 253–256 Drop folding test........................................................... 643 Drug discovery .............................................................. 286 Drug repurposing strategy actinobacteria .......................................................... 294 dataset cleaning ........................................ 295, 296 enrichment analysis, validation by.................... 297 e-Pharmacophore Model generation ...................................296, 298–300 materials............................................................. 294 MD simulation studies............................. 303, 305 molecular docking............................................. 303 PHASE database screening..............297, 301, 302 receptor grid generation ................................... 296 retrieval of dataset ............................................. 295

METHODS IN ACTINOBACTERIOLOGY

738 Index

Drug target methods of identification and validation of........... 335 essential proteins and non-homologous proteins, identification of ........................................... 336 materials/databases/software .......................... 336 pathway analysis and protein retrieval.............. 336 structure validation and active site prediction . 337 subcellular localization prediction and targets’ prioritization....................................... 336, 337 virtual screening, drug likeliness and toxicity analysis ................................................ 337, 338 Drug-drug interactions................................................. 287 Druglikeliness ....................................................... 286, 287 dTDP-glucose-4, 6-dehydratase (dTGD) ................... 264 Dual culture method .................................................... 384 actinomycetes ................................................. 382, 383

E Eagle’s Minimum Essential Medium (EMEM) .......... 420 Ecological chemicals ..................................................... 347 Electrophoretic mobility shift assay (EMSA) ...................................... 554, 556, 557 Emulsification activity (EA)................................. 654, 655 Emulsification index.................................... 643, 654, 655 Endophytic actinobacteria from lichens collection of lichen samples .................................... 135 isolation of pure culture of ............................ 136, 137 materials required for the collection of lichens ...................................................... 132 pretreatment of the sample..................................... 136 starch casein agar..................................................... 133 Endophytic actinobacteria isolation from flowers, fruits and seeds of higher plants........ 98 beneficial effects .................................................. 99 chemical media .................................................... 99 colonization ......................................................... 98 from flower, methodology................................ 103 from fruits, methodology ........................ 103, 104 from seeds, methodology ........................ 104, 105 materials.......................................................99–102 protocol ............................................................. 105 soil and moisture content, physiological and chemical nature of ......................................... 98 Endophytic actinomycetes .............................................. 87 Energy-based pharmacophore hypothesis ................... 294 Energy-based virtual screening strategies .................... 294 Enrichment analysis validation by ............................................................ 297 Entamoeba histolytica .................................................... 413 e-pharmacophore .......................................................... 294 e-Pharmacophore Model generation ..........296, 298–300 Epiphytic actinobacteria ...................................... 115, 118 actinomycetes .......................................................... 114 materials................................................................... 114

Epiphytic actinobacteria from lichens collection of lichen samples .................................... 125 direct inoculation of whole lichen samples ................................................ 126, 128 glucose asparagine agar........................................... 124 International Streptomyces Project (ISP) 1 .......... 124 Kuster’s agar ................................................... 124, 125 luria bertani ............................................................. 123 materials required for collection of lichens............ 122 pretreatment of the sample..................................... 125 serial dilution method.................................... 126, 127 starch casein agar..................................................... 123 starch nitrate agar.................................................... 123 Epiphytic actinobacteria from rhizosphere collection of soil and root samples......................... 117 direct inoculation technique................................... 118 pretreatment/enrichment process ......................... 117 serial dilution method.................................... 117, 118 standard enrichment technique.............................. 118 Equilibration ................................................................. 277 Esterification index........................................................ 642 Estuaries........................................................................... 19 sample collection ....................................................... 20 Ethidium bromide (EtBr)............................................. 427 Ethylene gas .................................................................. 596 Evolutionary analysis phylogeny and ................................................ 203–205 Evolutionary studies bioinformatics and .................................................. 196 E-waste, bioleaching application collection and processing........................................ 706 metal content of PCB ............................................. 707 SEM analysis............................................................ 707

F FAST5 files .................................................................... 212 Fecal samples .............................................................46, 48 Fermentation broth ...................................................... 673 Filamentous bacteria ......................................................... 1 Filter paper method ............................................. 621, 622 Fishes actinobacteria isolation from ..............................62, 63 culture independent techniques ......................... 67 culture media....................................................... 66 DNA extraction.............................................67, 68 homogenization .................................................. 66 isolation of gut .................................................... 65 materials......................................................... 63–65 NGS, sample preparation for.............................. 67 preparation .......................................................... 69 protocol ......................................................... 70–72 sample collection ................................................. 65 16S rRNA gene, processing and analysis of..........................................69, 70

METHODS subculturing and purification ............................. 67 actinobacteria Isolation from..............................61, 62 Foliicolous lichens......................................................... 132 Foliose lichens ............................................................... 133 Food and Agricultural Organization (FAO) ............... 538 Formazan ....................................................................... 435 Fourier Transform Infrared Spectroscopy (FT-IR) Analysis................................................ 686, 689 Fraction Profiling .......................................................... 359 Frankia isolation .................................................. 175, 176 MLSA based phylogeny of ..................................... 203 Free radical DPPH ........................................................ 453 Fruticose lichens............................................................ 133 Functional group analysis ............................................. 658 Fungal plant pathogens ....................................... 612, 613

G Gas chromatography–mass spectrometry (GC–MS) odor compounds ..................................................... 632 Gel electrophoresis............................................... 275, 277 Gelatinase production.......................................... 576, 585 GenBank ........................................................................ 238 Genetic engineering ...................................................... 684 Genome mining ................................................... 222, 248 additional tools........................................................ 223 advantages................................................................ 226 antiSMASH .................................................... 223–225 limitations ................................................................ 226 Genome mining of actinobacteria................................ 207 Genome sequencing ................................... 194, 207, 221 Genome visualization.................................................... 230 Genome-wide association studies (GWAS) ................. 195 Genomic database mining ............................................ 194 Genomic DNA .............................................................. 554 Genomic research, bioinformatics in .................. 194, 195 geoA gene......................................................633, 638–640 Geosmin...............................................630, 631, 636, 638 Giemsa stain ......................................................... 409, 411 Glide module........................................................ 312, 314 Glucose Asparagine Agar .............................................. 124 Glycolipids ..................................................................... 641 Gold nanoparticle synthesis antibacterial properties of cell free extract .................................................. 718 isolation of actinomycetes................................. 718 observation studies............................................ 719 antibiofilm activity cell free extract .................................................. 722 in vitro antibiofilm activity ............................... 722 isolation of actinomycetes................................. 722 materials............................................................. 722 observation studies............................................ 723 biosynthesis of ......................................................... 714 characterization of................................................... 715

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ACTINOBACTERIOLOGY Index 739

cytotoxic activity of ........................................ 726, 727 isolation of actinomycetes....................................... 714 materials................................................................... 714 observation studies.................................................. 715 preparation of cell-free extract ............................... 714 sporicidal activity of ....................................... 730, 731 Gram negative bacteria ................................................... 90 Gram-positive bacteria .................................................. 113 Gram-positive filamentous bacteria.............................. 533 Granulometry ................................................................ 499 Gravimetry..................................................................... 498 Griess reagent ....................................................... 455, 456 Gross Domestic Product (GDP).................................. 537 Gryllotalpa africana...................................................... 496 Gut actinobacteria........................................................... 29 Gut microbes structure and composition of ................................... 62 Gut microbiomes ............................................................ 62 Gut microbiota................................................................ 52 gVolante web based server................................... 215, 218

H Halophilic actinobacteria .............................................. 146 Brine lake soil ................................................. 148, 150 halophytes....................................................... 149, 151 hypersaline soil ............................................... 148, 149 marine sediment ............................................. 147, 149 metabolites .............................................................. 146 rhizopheric soils ............................................. 148, 150 Hank’s balanced salt solution (HBSS)......................... 472 Hemocytometer ............................................................ 445 Hemolytic activity ....................................... 551, 576, 584 Hemolytic assay.................................................... 642, 643 Herbicides...................................................................... 538 Herbivorous fishes .......................................................... 62 Hidden Markov Model (HMM).................................. 248 High microbial abundance (HMA) ............................... 23 Higher plants, flowers, fruits and seed endophytic actinobacteria isolation from ................ 98 beneficial effects .................................................. 99 chemical media .................................................... 99 colonization ......................................................... 98 from flower, methodology................................ 103 from fruits, methodology ........................ 103, 104 from seeds, methodology ........................ 104, 105 materials.......................................................99–102 protocol ............................................................. 105 soil and moisture content, physiological and chemical nature of ......................................... 98 Hill soil ......................................................................89, 91 HPLC method .............................................................. 622 HRBC membrane stabilization ........................... 463–465 Human gastrointestinal tract.......................................... 45 Humic acid vitamin agar (HVA)115, 117, 118, 148, 150

METHODS IN ACTINOBACTERIOLOGY

740 Index

Humus formation ............................................................. 7 Hydrogen peroxide scavenging assay.................. 461, 462 Hyperglycemia............................................................... 475 Hypersaline actinobacteria................................... 408, 410

I IC50 analysis .................................................................. 416 Ice Recrystallization Inhibition (IRI) .......................... 469 Immobilized cells ................................................. 492, 493 Immunomodulating agents .......................................... 472 Immunomodulators...................................................... 471 Immunomodulatory regimens ..................................... 472 In silico approaches....................................................... 286 In silico studies.............................................................. 286 In vitro cell based assays ............................................... 447 Indole 3-acetic acid (IAA) detection filter paper method .................................. 621, 622 thin layer chromatography method .........622–624 estimation colorimetric method ......................................... 622 HPLC method .................................................. 622 identification by HPLC method ............................ 624 Innovative technologies ................................................ 471 Inorganic Starch-Salt agar ............................................ 673 Integrated Microbial Genomes Atlas of Biosynthetic gene Clusters (IMG/ABC) ........................ 222, 223 International Streptomyces Project (ISP). 124, 126, 135, 136, 158, 509 Intestinal microbiota..................................................... 563 Iodonitrotetrazolium chloride (INT) .......................... 435 Isolates .................................................................. 523, 524 Isolation of actinobacteria from hills collection of hill soil sample ..................................... 91 inoculation of sample..........................................93, 94 materials required...................................................... 91 preparation of SCAM plate....................................... 92 pretreatment of soil sample ...................................... 92 serial dilution of soil.................................................. 92 Isolation of actinobacteria from seaweeds ..................... 86 laboratory equipment ............................................... 85 raffinose histidine agar .............................................. 85 sample collection and preprocessing ........................ 86 starch casein nitrate agar........................................... 85 Isolation of endophytic actinomycetes from algae........ 87 Isolation of epiphytic actinobacteria from lichens, see Epiphytic actinobacteria from lichens Isolation of epiphytic actinobacteria from rhizosphere, see Epiphytic actinobacteria from rhizosphere ISP-2 ................................................................................ 56

J Jensen’s medium .................................................. 595, 596

K Keratinase production amycolatopsis sp strain............................................ 515 biodegradation of.................................................... 514 experimental protocol .................................... 515–518 hydrogen bonds and hydrophobic interactions .................................................. 513 microbial origin ....................................................... 513 thermostable keratinolytic protease ....................... 515 Kimura two parameter (K2P) model ........................... 203 KnownClusterBlast analysis .......................................... 251 Kuster’s Agar ............................................... 124, 125, 135

L Lactate deshydrogenase (LDH .................................... 411 Lactic acid dehydrogenase assay.......................... 435, 436 Lactobacillus metabolites ..................................... 556, 558 Laminaria ochroleuca ..................................................... 84 Larvicidal activity ................................................. 626, 627 LCMS-IT-TOF-MS data acquisition .................. 353, 355 Legnicolous lichens....................................................... 132 Leprose lichens .............................................................. 133 Lichens collection of lichen samples .................................... 125 collection of samples ............................................... 135 different types.......................................................... 133 intermediated growth forms................................... 133 isolation of epiphytic actinobacteria from lichens (see Epiphytic actinobacteria from lichens) materials required for collection of ........................ 122 materials required for the collection of ................. 132 pretreatment of the sample..................................... 125 symbiotic components ............................................ 122 Licuri.............................................................................. 498 Licuri cake (LC) ............................................................ 498 Licuri shells (LS) ........................................................... 498 Ligand preparation Streptomyces, pharmacophore-based hypothesis ........................................... 321, 323 LigPrep panel ................................................................ 323 Lipase activity ....................................................... 642, 643 Lipase production experimental protocol isolation and cultivation of ............................... 507 material .............................................................. 506 screening and determination ............................ 508 Lipid peroxidation......................................................... 457 Lipophilicity .................................................................. 287 Liquid chromatography–tandem mass spectrometry (LC-MS) ............................................. 687, 689 Low microbial abundance (LMA) ................................. 23 Luciferase reporter phage (LRP) assay ...... 395, 397, 398

METHODS Luria Bertani (M1) .............................................. 123, 133 Luria-Bertani culture (LB) ........................................... 554 Lymphocyte Proliferation Assay.......................... 472, 473

M Malaria ........................................................................... 407 Malt Yeast Extract Agar ................................................ 672 Mangrove forests............................................................. 75 Mangrove plants actinobacteria associations ........................................ 76 isolation of actinobacteria......................................... 76 endophytic actinobacteria................................... 78 epiphytic/phylloplane actinobacteria........... 79–80 isolation methods .......................................... 77–79 materials, requirements....................................... 77 standard plate count method ............................. 81 woody plants ............................................................. 75 Mangrove wet soil......................................................... 496 Marine actinobacteria ..................................................... 13 isolation from deep sea ............................................. 16 isolation methods ...................................................... 14 media isolation .......................................................... 14 salts trace.................................................................... 15 sample collection .................................................14, 16 Marine algae, see Seaweeds Marine environment ......................................................... 1 Marine sediment, isolation from ..............................2, 4, 5 Marine sediment-derived actinomycetes ..................... 408 Marine/Estuary chart ..................................................... 20 MASCOT search engine system................................... 280 Mass spectrometry (MS)............................................... 273 Material Safety Data Sheet (MSDS) ............................ 446 Matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) ............................. 273 MD simulation studies......................................... 303–305 Melanin pigment alternative method for extraction.................. 677–678 composition of media .................................... 672, 673 pigment-producing actinobacteria ................ 673–675 preparation of inoculum ......................................... 675 purification of crude pigment................................. 680 solid-state fermentation ................................. 676–677 spraying reagent ...................................................... 680 submerged fermentation ........................................ 677 tyrosinase activity ........................................... 675–676 Melanin synthesis .......................................................... 671 Meloidogyne incognita ................................................... 617 Membrane filter technique .......................................4, 115 Metagenomics ...........................................................67, 70 for uncultivable microbes .............................. 202, 203 Metal chelating assay............................................ 457, 458 Methanol ....................................................................... 388 Metronidazole ............................................................... 414

IN

ACTINOBACTERIOLOGY Index 741

MIBiG Streptomyces..................................................... 256, 259 MIBiG cluster comparison ........................................... 251 Microbes screening, for melanin development materials................................................................... 668 methods ................................................................... 668 Microbes screening, simulated gastrointestinal transit cell-free extract preparation .................................... 546 materials................................................................... 546 observation skills ............................................ 547, 548 survival of actinobacteria ........................................ 547 Microbial broth culture ................................................ 350 Microbial community ................................................... 564 Microbial decolorization processes .............................. 696 Microbial dyes ............................................................... 667 Microbial immobilization ............................................. 491 Microbial induced calcium precipitation (MICP) materials................................................................... 488 methods .......................................................... 488, 489 Microbial production.................................................... 533 Microbial secondary metabolite screening .................... 36 Microbial secondary metabolites.................................. 247 Microbial symbionts..................................................23, 83 Microenvironments....................................................... 146 Micromonospora ........................................... 237, 238, 242 Micromonospora isolation.............................................. 178 Micromonospora species biosynthetic gene cluster analysis in antiSMASH ............................. 239–241, 243, 244 GenBank ............................................................ 238 materials............................................................. 239 scrutiny of dataset ............................................. 238 secondary metabolite cluster identification using antiSMASH ........................................ 238, 239 secondary metabolites and................................ 242 Microorganisms............................................................. 615 Microplate alamar blue assay (MABA) M. tuberculosis culture, preparation of ................... 402 materials................................................................... 401 procedure........................................................ 402, 403 Microtiter plate (MTP)................................................. 484 Miniaturized production actinobacteria ................................................. 367, 368 antimicrobial activity ................................ 369, 370 compounds ........................................................ 369 extraction of ...................................................... 369 protocol ............................................................. 369 materials............................................................. 368 Minion ........................................................................... 210 Minitab .......................................................................... 650 Mitochondrial activity................................................... 419 Mitogen-activated protein kinase (MEK).................... 295 MLSA based phylogeny of Frankia ............................. 203

METHODS IN ACTINOBACTERIOLOGY

742 Index

Moderately thermophilic actinobacteria ...................... 155 Moist chamber technique............................................. 539 Molecular docking ...................................... 289, 294, 303 Streptomyces, pharmacophore-based hypothesis ... 325, 327, 328 Molecular dynamic (MD) simulation .......................... 294 Molecular identification................................................ 576 Molecular phylogenetics ............................................... 187 Mosquitocidal activity bioactive compound production ............................ 626 larvicidal activity ............................................. 626, 627 materials................................................................... 626 MTT assay ..................................................................... 419 preparation of solution ........................................... 420 MTT method ....................................................... 555–557 Mucin degradation............................................... 576, 585 Mud and soil sample ..................................................... 507 Multi-drug resistant (MDR) ............................... 320, 395 MUMmer ...................................................................... 217 Muscicolous lichens ...................................................... 132 Mycobacterium smegmatis antimycobacterial activity, screening of......... 391, 392 materials............................................................. 392 methods ............................................................. 392 protocol ............................................................. 392

N NaCl Tolerance Assay ................................................... 583 Nalidixic acid ........................................................ 126, 127 Nanopore technology initial flow cell chemistries in.................................. 208 Nanotechnology............................................................ 725 National Center for Biotechnology Information (NCBI).................................................. 50, 265 Natural compounds ...................................................... 371 Natural pigments........................................................... 671 Nematicidal .......................................................... 616–618 Nematode ...................................................................... 617 Neutral red uptake assay ...................................... 431, 432 Next generation sequencing (NGS) ............................ 207 Nitric oxide scavenging assay .............................. 455, 456 Nitrogen sources ........................................................... 692 Nocardia isolation................................................ 173–174 Nocardia species.............................................................. 90 Nocardiopsis flavescens ..................................................... 89 Nocardiopsis isolation ........................................... 172, 173 Nodulation kinetics.............................................. 605–607 Nonribosomal peptide synthase (NRPS)....................................... 222, 264, 265 Non-steroidal anti-inflammatory drugs (NSAIDs) ..................................................... 464 Nonstreptomycete actinobacteria ................................ 169 Nonviable cells .............................................................. 431

Nutrient agar (NA) ....................................................... 673 Nystatin .................................................................. 70, 138

O Odor compounds.......................................................... 629 GC–MS analysis ............................................. 632, 637 gene identification in Streptomyces spp..................... 633, 637, 639 production and extraction ............................. 632, 636 screening of actinobacteria ............................ 632, 634 Odor metabolites actinobacterial isolates ............................................ 638 compound 2-methylisoborneol.............................. 640 drinking water ......................................................... 630 geosmin and 2-MIB................................................ 630 O-glycosyl bond ............................................................ 527 Oil-spreading method.......................................... 642, 643 Olfactory analysis .......................................................... 640 Onion root tip assay materials................................................................... 450 methods exposure to text samples.......................... 450, 451 microscopic studies ........................................... 451 mitotic index ..................................................... 451 Online tools................................................................... 286 OpenBabel ..................................................................... 317 Orange waste powder ................................................... 497 Organic farming ............................................................ 538 Organic matter decomposition ...................................... 40 Organic stimulation films ............................................. 642 Oxford Nanopore Technology (ONT)............... 207, 210

P Pan–Core genome plot........................................ 201, 202 Paraffin baiting technique............................................. 174 Paraffin coated slide techniques ................................... 174 Pathogenicity test.......................................................... 551 PCR amplification ......................................................... 264 materials................................................................... 264 methods .......................................................... 264–265 PCR-based sequencing approach................................... 49 Pectinase applications .............................................................. 527 determination of ..................................................... 529 enzyme production ................................................. 529 materials................................................................... 528 sample collection ..................................................... 528 screening of isolates ................................................ 528 secondary screening of............................................ 530 Peptide mass fingerprint (PMF).......................... 274, 279 Peptone Yeast Iron Agar (PYIA).................................. 673 Peptonisation Medium ..................................................... 9

METHODS Peptonization .................................................................. 11 Peripheral blood mononuclear cells (PBMC) ............. 473 Pfam domains Streptomyces.............................................................. 259 Pfam-based GO term annotation................................. 251 pH adjustment method ................................................ 653 pH effect............................................................... 691, 702 Phage propagation antimycobacterial activity, actinobacterial extracts/ compounds, screening of ................... 396, 397 Phagocytosis enhancement assay......................... 472, 473 Pharmacophore-based hypothesis Streptomyces..................................................... 319, 320 ligand preparation ............................321, 323, 324 materials............................................................. 320 pharmacophore model generation ...................................322, 325, 326 PHASE database creation ................................. 322 protein preparation ........................................... 321 protein-ligand interaction analysis .......... 331, 332 receptor grid generation and molecular docking .......................................325, 328, 330 screened compounds, pharmacokinetic analysis of ......................................................... 329, 330 Phase database Streptomyces pharmacophore-based hypothesis .................... 322 receptor cavity-based approach ........................ 310 Phase separation method .............................................. 653 Phenol tolerance test .................................................... 582 Phosphate buffer saline (PBS)...................................... 420 Phosphate-solubilizing actinobacteria NBRIP medium ............................................. 591, 592 screening of .................................................... 590, 591 by ascorbic acid method .......................... 590, 591 vanadomolybdophosphoric acid colorimetric method................................................ 590, 592 Phosphorous and potassium solubilization ................. 114 Phylogenetic analysis..................................................... 188 align a dataset .......................................................... 189 phylogenetic trees ................................................... 190 statistical test ........................................................... 190 Phylogeny and evolutionary analysis ............................... 203–205 Phylum actinobacteria .................................................. 113 Pigment inhibition assay............................................... 481 Placodioid lichens ......................................................... 133 Plant-associated microbes............................................. 113 Plant-based therapeutics ............................................... 471 Plasmodium falciparum antiplasmodial activity............................................. 411 cultivation ................................................................ 410 Plate assay ............................................................. 697, 698 Plate counting method ................................................. 555

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ACTINOBACTERIOLOGY Index 743

Polar surface area (PSA) ............................................... 286 Polyketide synthase type I (PKS I)............................... 264 Polyketide synthases (PKS).................................. 222, 265 Postprandial hyperglycemia .......................................... 475 Potato dextrose agar (PDA) ......................................... 612 Poultry breeds ............................................................... 571 PRediction Informatics for Secondary Metabolomes (PRISM)....................................................... 222 Pretreatment.................................................................... 10 chemicals.................................................................... 10 Probiotics......................................................................... 27 antibiotic susceptibility test .................................... 550 anti-pathogenic activity test electrophoretic mobility shift assay ......... 556, 557 medium, buffer, and MTT ............................... 554 metabolites of Lactobacillus ............................. 555 MTT method ........................................... 555, 556 plate counting method ..................................... 555 DNase test ............................................................... 550 for poultry production antagonistic activity.................................. 575, 584 antibiotic susceptibility test .............................. 575 assessment of probiotic properties of...... 582, 583 bile salt deconjugation ...................................... 585 bile salt tolerance test........................................ 575 biogenic amines production ............................. 584 biosynthesis of vitamin B12......................579–581 estimation of vitamin B12 ................................ 575 extraction of vitamin B12 ................................. 574 fermentation process ......................................... 574 gelatinase production........................................ 585 in vitro biosafety aspects of...................... 576, 584 in vivo biosafety aspects ........................... 585, 586 inoculum preparation........................................ 574 isolation and screening ....................572, 576, 577 mucin degradation ............................................ 585 phenol tolerance test......................................... 575 phenotypic characterization of Actinobacteria strains ........................................................... 573 simulated gastric juice survivability test ........... 575 temperature and NaCl tolerance assay............. 575 in poultry farming in vitro of actinobacteria isolates..............565–567 microbial community........................................ 564 microbial supplements ...................................... 563 poultry samples ........................................ 567, 568 short-chain fatty acids (SCFA) ......................... 564 materials................................................................... 550 observations studies ................................................ 552 pathogenicity test .................................................... 551 Prodigiosin pigments immuno-suppresser and anticancer agents ............ 684 microbial prodiginines, production of ................... 688 prodigiosin and undecylprodigiosin....................... 684

METHODS IN ACTINOBACTERIOLOGY

744 Index

Prodigiosin pigments (cont.) purification .............................................................. 688 soil samples .............................................................. 685 therapeutic benefits ................................................. 684 water samples........................................................... 685 PRODRG ...................................................................... 318 Propionibacterium freudenreichii ................................. 577 Protease determination of ..................................................... 535 materials................................................................... 534 methods ................................................................... 534 Protein data bank (PDB) .............................................. 295 Protein denaturation............................................ 463–465 Protein energetic cost ................................................... 200 Protein modification ..................................................... 457 Protein Preparation Wizard panel ................................ 322 Pseudonocardia isolation............................................... 174 Psychrophilic microorganisms .....................141–143, 467 Psychrotolerant microorganisms ......................... 141–143

Q QikProp analysis............................................................ 331 Qualitative determination............................................. 554 Quorum sensing inhibitory (QSI) ............................... 480 anti-virulence approach........................................... 479 materials................................................................... 480 methods .......................................................... 480, 481

R Raffinose Histidine agar.................................................. 85 Ramicolous lichens........................................................ 132 Rapid Annotations using Subsystems Technology (RAST) ......................................................... 224 Rare actinobacterial species .......................................... 169 RAST web server........................................................... 218 Reactive oxygen species (ROS) .................................... 457 Rebaler ........................................................................... 218 Receptor cavity-based approach Streptomyces..................................................... 307, 308 developing pharmacophore hypothesis ........................................... 310, 313 docking using AutoDock..........................314–316 materials............................................................. 308 phase database creation..................................... 310 protein preparation .................................. 308, 309 protocol .................................................... 317, 318 receptor grid ............................................. 309, 310 virtual screening using Glide module ................................................ 312, 314 Receptor grid generation.............................................. 296 Streptomyces, pharmacophore-based hypothesis .................................. 325, 327, 328

Streptomyces, receptor cavity-based approach.............................................. 309, 310 Reciprocal Best Blast Hit approach.............................. 204 Relative Synonymous Codon Usage (RSCU).... 197, 199 Reproductive parts .......................................................... 98 Resident microbial community ...................................... 40 Reverse side pigments ................................................... 691 Rhizosphere.........................................114, 115, 117, 496 Rhodococcus opacus ........................................................ 496 Rolled paper towel assay ............................................... 539 Root incubation methodology..................................... 617 Root nodules ........................................................ 604–607 Root sample................................................................... 117 RREFinder..................................................................... 252

S Saccharomonospora isolation ......................................... 175 Saccharopolyspora isolation................................... 174, 175 Salimanides A ................................................................ 463 Salimanides B ................................................................ 463 Saline environments ...................................................... 496 Salt concentration ......................................................... 692 Sample pretreatment ......................................................... 3 Saxicolous lichens................................................. 132, 133 Sea ecosystems................................................................. 13 Seaweeds actinobacteria and sampling locations ..................... 84 bioactive compounds ................................................ 83 isolation of actinobacteria from seaweed ................. 86 isolation of endophytic actinomycetes from algae .. 87 laboratory equipment ............................................... 85 raffinose histidine agar .............................................. 85 sample collection and preprocessing ........................ 86 starch casein nitrate agar........................................... 85 Secondary metabolite cluster identification........ 238, 239 Secondary metabolite compounds (SMs).................... 223 Secondary metabolites ................. 24, 348, 506, 684, 685 Selectivity index (SI) ..................................................... 420 Self-aggregation ............................................................ 566 Serial dilution method .............................. 3, 34, 126, 127 Short-chain fatty acids (SCFA) .................. 564, 565, 568 Shrimp ............................................................................. 28 gut actinobacteria...................................................... 29 isolation from gut ..................................................... 30 Sideromycins ................................................................. 599 Siderophore production antimicrobial unit .................................................... 599 applications .............................................................. 599 ferric ion .................................................................. 599 materials................................................................... 600 methods ................................................................... 600 microorganisms’ discharge ..................................... 599

METHODS Silver nanoparticle synthesis antibacterial properties of cell free extract .................................................. 718 isolation of actinomycetes................................. 718 observation studies............................................ 719 antibiofilm activity cell free extract .................................................. 722 in vitro antibiofilm activity ............................... 722 isolation of actinomycetes................................. 722 materials............................................................. 722 observation studies............................................ 723 biosynthesis of ......................................................... 709 cell free extract preparation .................................... 709 characterization of................................................... 710 cytotoxic activity of ........................................ 726, 727 isolation of actinomycetes....................................... 709 materials................................................................... 709 observation studies.................................................. 710 sporicidal activity of ....................................... 730, 731 Simulated gastric juice survivability test ...................... 582 Single gene-based phylogeny ....................................... 188 Single-Molecule Real-Time (SMRT) sequencing technology ................................................... 207 Single-nucleotide polymorphisms (SNPs)................... 195 Slip-buried method ....................................................... 173 SMILES format ............................................................. 288 Sodium alginate method ..................................... 492, 493 Soil fertility ...................................................................... 35 Soil sample..................................................................... 117 Solid state fermentation (SSF) ..................................... 665 Solvent selection............................................................ 359 Spectrophotometer ....................................................... 419 Sponges............................................................................ 23 endosymbionts .......................................................... 25 isolation media .......................................................... 24 lab equipment............................................................ 25 marine ........................................................................ 24 processing of sample ................................................. 25 Spore-forming bacteria ................................................. 117 Spread plate technique..............................................46, 48 Sprinkling method ............................................................ 4 SPSS (IBM) ................................................................... 650 Squamulose lichens ....................................................... 133 Standard enrichment technique ................................... 118 Starch Agar (SA) media ................................................ 673 Starch casein agar (SCA)........................84, 87, 110, 118, 123, 133, 137, 142, 380, 496, 611, 672 Starch casein agar medium (SCAM) .............................. 92 Starch Casein Nitrate Agar (SCN) ................................. 85 Starch Nitrate Agar (SNA) .................................. 123, 133 Statistical optimization approach ........................ 650–652 Sterilization methods .................................................... 665 Stone-dwelling actinomycetes ...................................... 163 behavior ................................................................... 164

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ACTINOBACTERIOLOGY Index 745

characterization .............................................. 165, 166 culture medium .............................................. 164, 166 habitat ...................................................................... 164 isolation ................................................................... 165 media compositions ................................................ 167 specimen collection ................................................. 164 specimen preparation .............................................. 164 Streptomyces.....................................................90, 285, 293 antimicrobials .......................................................... 285 Autodock 4.2 .......................................................... 289 biosynthetic gene cluster analysis in.............. 247–249 analysis procedure .................................... 249, 250 antiSMASH .............................................. 250, 254 core structure prediction and prediction details .................................................. 255, 257 domain architecture ..................................253–256 downloading...................................................... 260 extended parameters .................................250–252 file and options input ........................................ 249 known clusters, identification of ............. 256, 258 materials............................................................. 249 MIBiG comparison .................................. 256, 259 Pfam domains .................................................... 259 S. griseus NBRC 13350, antiSMASH data analysis of ......................................................... 260, 261 similar gene clusters, identification of .................................. 256, 257 subcluster Blast analysis ........................... 256, 258 CASTp ..................................................................... 287 pharmacophore-based hypothesis with molecular docking protocol ................................ 319, 320 ligand preparation ............................321, 323, 324 materials............................................................. 320 pharmacophore model generation ...................................322, 325, 326 PHASE database creation ................................. 322 protein-ligand interaction analysis .......... 331, 332 receptor grid generation and molecular docking .......................................325, 328, 330 screened compounds, pharmacokinetic analysis of ......................................................... 329, 330 PyMOL plugin ........................................................ 289 receptor cavity-based approach combined with Autodock protocol ............................. 307, 308 developing pharmacophore hypothesis... 310, 313 docking using AutoDock..........................314–316 materials............................................................. 308 phase database creation..................................... 310 protein preparation .................................. 308, 309 protocol .................................................... 317, 318 receptor grid ............................................. 309, 310 virtual screening using Glide module ................................................ 312, 314 SwissADME.................................................... 286–288

METHODS IN ACTINOBACTERIOLOGY

746 Index

Streptomyces (cont.) transcriptome profiles of ......................................... 339 approaches for ................................................... 339 de novo assembly .............................................. 340 reference-based/genome-guided assembly ...............................................340–342 TOPHAT........................................................... 343 Streptomyces antibioticus ...................................... 617, 618 Streptomyces avermitilis ................................................. 248 Streptomyces griseus ........................................................ 248 Streptomyces kurssanovii .................................................. 89 Streptomyces olivaceous................................................... 578 Streptomyces parvulus .................................................... 496 Streptomyces peucetius var. caesius ................................. 294 Streptomyces sampsonii GS 1322 ultraviolet absorption spectrum of antifungal compound.................................................... 388 Streptomyces sampsonii MDCE7 .......................... 379, 380 characterization of................................. 380, 383, 384 colony and spore morphological characteristics of .......................................... 387 cover slip culture technique.................................... 384 microscopic examination ........................................ 384 polyenes antifungal compound, characterization of .................................................................. 384 scanning electron microscopic study ..................... 386 Ultraviolet absorption spectrum of antifungal by............................................ 388 Streptomyces sp. ................................................................ 86 contiguous whole-genome sequence of DNA isolation ................................................... 209 DNA, quality check of ............................. 209, 210 library preparation...........210–212, 215, 217–219 materials.................................................... 208, 209 protocol ............................................................. 213 geosmin and 2-MIB................................................ 630 odor compounds, gene identification .............................. 633, 637, 639 PCR amplification, geoA gene ................................ 638 soil ............................................................................ 630 taste and odor description ...................................... 631 Streptomycete actinobacteria ....................................... 169 Streptomycetes ................................................................... 90 Strictly thermophilic actinobacteria ............................. 155 Subcluster Blast analysis................................................ 252 Streptomyces..................................................... 256, 258 Submerged fermentation ..................................... 517, 665 Substrate concentration, effects of............................... 493 Surface tension .............................................................. 654 SwissADME.......................................................... 286, 287 Synthetic dyes....................................................... 695, 700

T Tap water yeast extract media (TWYE) ......................... 13 Temperature effect ........................................................ 692

Termites .....................................................................52, 53 actinobacteria isolation from .................................... 51 aseptic removal and homogenization ..........55, 56 biotic and abiotic factors .................................... 52 chitin agar ............................................................ 56 defatted wood powder media............................. 56 HVA media .......................................................... 56 identification........................................................ 57 isolation and culturing ........................................ 56 ISP-2 .................................................................... 56 materials.........................................................53, 54 protocol .........................................................57, 58 sample collection ...........................................54, 55 sample processing and surface sterilization .................................................... 55 SCA media ........................................................... 56 sub-culturing and purification......................56, 57 Terricolous lichens ........................................................ 132 Tetrazolium dye assays.................................................. 419 Textile dye effluent........................................................ 699 Thermal hysteresis activity ............................................ 469 Thermophilic actinobacteria......................................... 155 biological stability ................................................... 156 carboxylesterases ..................................................... 156 composting process................................................. 156 culture media........................................................... 157 enzymatic activity .................................................... 156 isolation, soil sample ............................................... 156 liquid/soild samples....................................... 157, 158 sources ..................................................................... 156 thermotolerant ........................................................ 159 types ......................................................................... 158 Thin layer chromatography (TLC) .................... 622–624, 686, 689 actinobacteria, antibiotic compounds purification.......................................... 376, 377 Third Generation Sequencing (TGS) technologies ................................................. 207 TIGRFam analysis ......................................................... 252 Topological polar surface area (TPSA) ........................ 287 Total antioxidant assay......................................... 459, 460 Total lipid content ........................................................ 657 Transcriptome profiles Streptomyces.............................................................. 339 approaches for ................................................... 339 de novo assembly .............................................. 340 reference-based/genome-guided assembly ...............................................340–342 TOPHAT........................................................... 343 tRNA Adaptation Index ............................................... 200 Trypan blue exclusion assay assay procedure........................................................ 444 equipment................................................................ 444 methods ................................................................... 444 preclinical investigations ......................................... 443

METHODS Tryptone soy agar medium (TSA) ............. 115, 118, 119 Tuberculosis (TB) ................................................ 391, 395 Two-dimensional gel electrophoresis (2D-GE) .......... 274 Tyrosinase activity ................................................ 675–676

U Uncultivable microbes metagenomics for........................................... 202, 203 UV-visible spectrophotometry ............................ 686, 689

V Validation by enrichment analysis ............................................ 297 Valienamine ................................................................... 476 Valiolamine .................................................................... 476 Viable cells ............................................................ 431, 447 Virtual screening .................................294, 295, 312, 314 Vitamin B12 daily requirement of................................................ 661 estimation of............................................................ 666 extraction of ............................................................ 665 production of inoculum preparation and fermentation.......... 665 isolation of Streptomyces.................................. 664 materials.................................................... 662, 664 sample collection and serial dilution ................ 664 solid state fermentation (SSF) .......................... 665 sterilization methods......................................... 665 submerged fermentation .................................. 665 Vitamins......................................................................... 571 Voglibose ....................................................................... 476 Volatile organic compounds (VOCs).................. 629, 630 V-shaped method for soil sample collection.................. 92

W Wastewater treatment ................................................... 491 Water sample biochemical test......................................................... 12 catalase test .......................................................... 11 coagulation .......................................................... 11

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ACTINOBACTERIOLOGY Index 747

oxidase test .......................................................... 11 peptonization ...................................................... 11 starch utilization test........................................... 11 collection of ................................................................. 9 colony characteristics ................................................ 12 designing medium..................................................... 10 fresh water ................................................................. 10 pretreatment .............................................................. 10 Weeds organic farming ....................................................... 538 Whole cell sugar pattern (WCSP) ................................ 182 Whole exome sequencing ............................................. 195 Whole-genome analysis actinobacteria Blast Matrix ....................................................... 201 Codon Adaptation Index.................................. 198 codon usage......................................196–198, 200 Pan–Core genome plot............................ 201, 202 phylogeny and evolutionary analysis ........203–205 protein energetic cost ....................................... 200 Relative Synonymous Codon Usage....... 197, 199 statistical analysis ............................................... 200 tRNA Adaptation Index ................................... 200 uncultivable microbes, metagenomics for202, 203 Whole-genome sequence Streptomyces sp. DNA isolation ................................................... 209 DNA, quality check of ............................. 209, 210 library preparation...........210–212, 215, 217–219 materials.................................................... 208, 209 protocol ............................................................. 213

X Xenobiotic compounds................................................... 19

Y Yeast Malt (YM) ................................................... 497, 499 YIM 14 improved Czapek medium ................................. 8 YIM 17 glycerol asparagine medium ............................... 8 YIM 21 oatmeal medium ................................................. 8