Micro-algae: Next-generation Feedstock for Biorefineries: Contemporary Technologies and Future Outlook (Clean Energy Production Technologies) 9811906793, 9789811906794

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Clean Energy Production Technologies Series Editors: Neha Srivastava · P. K. Mishra

Pradeep Verma Editor

Micro-algae: Next-generation Feedstock for Biorefineries Contemporary Technologies and Future Outlook

Clean Energy Production Technologies Series Editors Neha Srivastava, Department of Chemical Engineering and Technology, IIT (BHU) Varanasi, Varanasi, Uttar Pradesh, India P. K. Mishra, Department of Chemical Engineering and Technology, IIT (BHU) Varanasi, Varanasi, Uttar Pradesh, India

The consumption of fossil fuels has been continuously increasing around the globe and simultaneously becoming the primary cause of global warming as well as environmental pollution. Due to limited life span of fossil fuels and limited alternate energy options, energy crises is important concern faced by the world. Amidst these complex environmental and economic scenarios, renewable energy alternates such as biodiesel, hydrogen, wind, solar and bioenergy sources, which can produce energy with zero carbon residue are emerging as excellent clean energy source. For maximizing the efficiency and productivity of clean fuels via green & renewable methods, it’s crucial to understand the configuration, sustainability and technoeconomic feasibility of these promising energy alternates. The book series presents a comprehensive coverage combining the domains of exploring clean sources of energy and ensuring its production in an economical as well as ecologically feasible fashion. Series involves renowned experts and academicians as volume-editors and authors, from all the regions of the world. Series brings forth latest research, approaches and perspectives on clean energy production from both developed and developing parts of world under one umbrella. It is curated and developed by authoritative institutions and experts to serves global readership on this theme.

Pradeep Verma Editor

Micro-algae: Next-generation Feedstock for Biorefineries Contemporary Technologies and Future Outlook

Editor Pradeep Verma Bioprocess and Bioenergy Laboratory, Department of Microbiology Central University of Rajasthan Ajmer, Rajasthan, India

ISSN 2662-6861 ISSN 2662-687X (electronic) Clean Energy Production Technologies ISBN 978-981-19-0679-4 ISBN 978-981-19-0680-0 (eBook) https://doi.org/10.1007/978-981-19-0680-0 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 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 Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

Dedicated to My Beloved Mother

Preface

The fossil fuels which fulfil the major need of energy and chemicals have been depleting at a very fast rate. To meet the needs of the industrial and energy sector, biofuels and biochemicals are viable alternatives. Microalgal biomass is rich in protein, lipids and other essential biomolecules that can be potentially converted to biofuel and value-added chemicals to meet the global need. The integrated microalgae-based biorefinery can result in simultaneous generation of biofuel, such as biodiesel, bioethanol and bio-hydrogen, and value-added compounds, such as carotenoids, fatty acids and protein. The potential of microalgae to utilize wastewater as a substrate can help in generation of bioelectricity and in concurrent bioremediation, thus making the overall process self-reliant and economically viable. Therefore, several attempts have been made on a global level to develop an integrated microalgae-based biorefinery. The fast progress in the development of integrated microalgae-based biorefinery requires better understanding for the cultivation, harvesting and downstream processing. Apart from this, the understanding of contemporary technologies developed at laboratory scale to streamline different stages of microalgae-based biorefinery is necessarily required. The advanced interdisciplinary research utilizing advanced bioinformatics and data mining strategies with contemporary molecular/metabolic engineering strategies and synthetic biology-based resources can be useful in making a giant leap of progress in making integrated microalgae biorefinery a reality. Thus, the proposed book is an attempt to provide an account on past, present and future constraints in microalgae-based biorefineries. The book will provide an insight into the recent advancements in the technologies and methods in developing microalgae-based biorefinery for bioenergy and biochemical generation. The biotechnological advances via utilization of modern molecular biology, system biology, synthetic biology or metabolic engineering approach will also be discussed. It will also be focused on the limitations of already existing technologies and providing future prospects of different contemporary technologies. The development of any technologies has a direct effect on the human being and environment; therefore, the socio-economic, techno-economic and environmental impact of the microalgae-based biorefineries will also be included in the book. The new microalgae-based biorefinery approaches will suggest vii

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how these approaches can be consolidated to design an integrated self-sustainable microalgae-based biorefinery. This edited book will be equally beneficial for researchers in the area of a microalgal assisted biorefinery and the bachelor’s, master’s and young budding graduate students as a textbook. Ajmer, Rajasthan, India

Pradeep Verma

Acknowledgements

First of all, I would like to convey my gratitude to the Series editor Dr. Neha Srivastava and Prof. P.K. Mishra for considering the submission of this book entitled “Micro-algae: Next-Generation Feedstock for Biorefineries—Contemporary Technologies and Future Outlook” under the book series “Clean Energy Production Technologies”. I am thankful to Springer Nature for accepting my proposal to act as editor for the current book volume. The current volume of the book series is only possible because of the support from all the researchers and academicians who contributed to the book; therefore, the editor is thankful for their contribution. I would also like to thank my Ph.D. scholar, Dr. Bikash Kumar, currently working as Post doctoral researcher at IIT, Guwahati, for providing me with all the necessary technical support and editorial assistance during the entire stage of book development. I am also thankful to the Central University of Rajasthan (CURAJ), Ajmer, India, for providing infrastructural support and a suitable teaching and research environment. The teaching and research experience at CURAJ has provided the necessary understanding of the needs of academicians, students, and researchers in a book that was greatly helpful during the development of the book. I am also thankful to the Department of Biotechnology for providing me funds through sponsored projects (Grant No. BT/304/ NE/TBP/2012 and BT/PR7333/ PBD/26/373/2012), for setting up my laboratory “Bioprocess and Bioenergy Laboratory”. I am always thankful to God and my parents for their blessings. I also express my deep sense of gratitude to my wife (Savita) and kids (Mohak and Netra) for their support during the development of the book and in life.

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Contents

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Third-Generation Biofuels from Microalgal Bioresource: Potential Strategy and Current Trends . . . . . . . . . . . . . . . . . . . . . . Arun Kumar Rai and Saurav Anand Gurung The Promising Future of Microalgae as Biofuels and Valuable Bioproducts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Satyabrata Dash, Sabyasachy Parida, Bijayananda Sahoo, and Biswajit Rath Overview on Advanced Microalgae-Based Sustainable Biofuel Generation and Its Life Cycle Assessment . . . . . . . . . . . . . . . . . . . . M. Iniyakumar, V. Venkat Ramanan, A. Ramalakshmi, R. Bobita, J. Tharunkumar, K. Jothibasu, and S. Rakesh Microalgae Cell Wall Disruption and Biocomponents Fractionation for Fuel Conversion . . . . . . . . . . . . . . . . . . . . . . . . . . J. Tharunkumar, K. Jothibasu, M. Iniyakumar, and S. Rakesh

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Recent Advances in Hydrothermal Liquefaction of Microalgae . . . . Mahadevan Vaishnavi, Kannappan Panchamoorthy Gopinath, and Praveen Kumar Ghodke

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Carotenoids and Pigment Generation Using the Microalgal Production System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 Pankaj Kumar Jain, Praveen Jain, Brijesh Pandey, Prakash Kumar Sarangi, Anand Prakash, Akhilesh Kumar Singh, and Rajesh K. Srivastava

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Molecular Engineering/Metabolic Engineering-Based Advanced Biotechnological Approach in Microalgal Biorefinery . . . . . . . . . . . 145 D. Vidya and K. Arunkumar

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Algae-Bacteria Interactomics Unveils Their Role in Growth and Production of High-Value Biorenewables . . . . . . . . . . . . . . . . . . . . 165 Abdalah Makaranga and Pannaga P. Jutur

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Microalgae and Cyanobacteria: A Potential Source for Drug Discovery Using Genome Mining Approach . . . . . . . . . . . . . . . . . . 177 David Wiseman Lamare and Neha Chaurasia

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Synthetic Biology-Based Advanced Biotechnological Approach in Microalgal Biorefinery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205 Saeed Uz Zafar, Anju Mehra, and Pannaga P. Jutur

Editor and Contributors

About the Editor Pradeep Verma completed his Ph.D. from Sardar Patel University, Gujarat, India, in 2002. In the same year, he was selected as a UNESCO Fellow and joined the Czech Academy of Sciences, Prague, Czech Republic. He later moved to Charles University, Prague, to work as a Post-Doctoral Fellow. In 2004, he joined as a visiting scientist at the UFZ Centre for Environmental Research, Halle, Germany. He was awarded a DFG fellowship, which provided him another opportunity to work as a Post-Doctoral Fellow at the University of Göttingen, Germany. He moved to India in 2007, where he joined Reliance Life Sciences, Mumbai, and worked extensively on biobutanol production, which attributed a few patents to his name. Later, he was awarded JSPS Post-Doctoral Fellowship program, and he joined the Laboratory of Biomass Conversion, Research Institute of Sustainable Humanosphere (RISH), Kyoto University, Japan. He is also a recipient of various prestigious awards, such as the Ron Cockcroft award by Swedish society and UNESCO Fellow, ASCR, Prague. Recently, for his contribution to the areas of fungal microbiology, industrial biotechnology, and environmental bioremediations, he was awarded the prestigious Fellow award for Mycological Society of India (2020), P.K. Jain Memorial Award (MSI), and Biotech Research Society of India (2021). Prof. Verma began his independent academic career in 2009 as a Reader and Founder Head at the xiii

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Editor and Contributors

Department of Microbiology at Assam University. In 2011, he moved to the Department of Biotechnology at Guru Ghasidas Vishwavidyalaya (A Central University), Bilaspur, and served as an Associate Professor till 2013. He is currently working as a Professor (former Head and Dean, School of Life Sciences) at the Department of Microbiology, CURAJ. He is a member of various national and international societies/academies. He has completed two collaborated projects worth 150 million INR in the area of microbial diversity and bioenergy. Prof. Verma is a group leader of the Bioprocess and Bioenergy Laboratory at the Department of Microbiology, School of Life Sciences, CURAJ. His areas of expertise involve microbial diversity, bioremediation, bioprocess development, lignocellulosic process, and algal biomass-based biorefinery. He holds 12 international patents in the fields of microwave-assisted biomass pretreatment and bio-butanol production. He has more than 73 research and review articles in peer-reviewed international journals and contributed to several book chapters (32 published, 11 in press) in different edited books. Prof. Verma has edited 07 books and is editorial board member, guest editor, and reviewers to prestigious high-impact journals.

Contributors K. Arunkumar Phycoscience Laboratory, Department of Plant Science, Central University of Kerala, Kasaragod, Kerala, India R. Bobita Biofuel Research Laboratory, Department of Microbiology, Central University of Tamil Nadu, Thiruvarur, Tamil Nadu, India Neha Chaurasia Department of Biotechnology and Bioinformatics, North Eastern Hill University, Shillong, Meghalaya, India Satyabrata Dash Department of Biotechnology, Maharaja Sriram Chandra Bhanja Deo University Sriram Chandra Vihar, Takatpur, Baripada, Odisha, India Praveen Kumar Ghodke Department of Chemical Engineering, National Institute of Technology Calicut, Kozhikode, Kerala, India Kannappan Panchamoorthy Gopinath Department of Chemical Engineering, SSN College of Engineering, Kalavakkam, Tamil Nadu, India

Editor and Contributors

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Saurav Anand Gurung Department of Botany, Sikkim University, Gangtok, Sikkim, India M. Iniyakumar Agricultural Microbiology, Amrita School of Agricultural Sciences, Amrita Vishwa Vidyapeetham, Coimbatore, Tamil Nadu, India Pankaj Kumar Jain Department of Botany, Kalyan Post Graduate College, Sector 7, Durg, Chhattisgarh, India Praveen Jain Department of Botany, Government Chandulal Chandrakar Arts and Science PG college Patan, Durg, Chhattisgarh, India K. Jothibasu Department of Microbiology, Karpagam Academy of Higher Education, Coimbatore, Tamil Nadu, India Pannaga P. Jutur Omics of Algae Group, Industrial Biotechnology and DBTICGEB Centre for Advanced Bioenergy Research, International Centre for Genetic Engineering and Biotechnology, Aruna Asaf Ali Marg, New Delhi, India Davidwiseman Lamare Department of Biotechnology and Bioinformatics, North Eastern Hill University, Shillong, Meghalaya, India Abdalah Makaranga Omics of Algae Group, Industrial Biotechnology and DBTICGEB Centre for Advanced Bioenergy Research, International Centre for Genetic Engineering and Biotechnology, Aruna Asaf Ali Marg, New Delhi, India Anju Mehra Omics of Algae Group, Industrial Biotechnology and DBT-ICGEB Centre for Advanced Bioenergy Research, International Centre for Genetic Engineering and Biotechnology, Aruna Asaf Ali Marg, New Delhi, India Brijesh Pandey Department of Biotechnology, School of Life Sciences, Mahatma Gandhi Central University, East Champaran, Bihar, India Sabyasachy Parida Department of Biotechnology, Maharaja Sriram Chandra Bhanja Deo University Sriram Chandra Vihar, Takatpur, Baripada, Odisha, India Anand Prakash Department of Biotechnology, School of Life Sciences, Mahatma Gandhi Central University, East Champaran, Bihar, India Arun Kumar Rai Department of Botany, Sikkim University, Gangtok, Sikkim, India S. Rakesh Biofuel Research Laboratory, Department of Microbiology, Central University of Tamil Nadu, Thiruvarur, Tamil Nadu, India A. Ramalakshmi Department of Agricultural Microbiology, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, India V. Venkat Ramanan Department of Environmental Studies, SOITS, Indira Gandhi National Open University, New Delhi, India Biswajit Rath Department of Biotechnology, Maharaja Sriram Chandra Bhanja Deo University, Sriram Chandra Vihar, Takatpur, Baripada, Odisha, India

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Bijayananda Sahoo Department of Biotechnology, Maharaja Sriram Chandra Bhanja Deo University, Sriram Chandra Vihar, Takatpur, Baripada, Odisha, India Prakash Kumar Sarangi College of Agriculture, Central Agricultural University, Imphal, Manipur, India Akhilesh Kumar Singh Department of Biotechnology, School of Life Sciences, Mahatma Gandhi Central University, East Champaran, Bihar, India Rajesh K. Srivastava Department of Biotechnology, GIT, GITAM, Visakhapatnam, Andhra Pradesh, India J. Tharunkumar Biofuel Research Laboratory, Department of Microbiology, Central University of Tamil Nadu, Thiruvarur, Tamil Nadu, India Mahadevan Vaishnavi Department of Chemical Engineering, SSN College of Engineering, Kalavakkam, Tamil Nadu, India D. Vidya Phycoscience Laboratory, Department of Plant Science, Central University of Kerala, Kasaragod, Kerala, India Saeed Uz Zafar Omics of Algae Group, Industrial Biotechnology and DBTICGEB Centre for Advanced Bioenergy Research, International Centre for Genetic Engineering and Biotechnology, Aruna Asaf Ali Marg, New Delhi, India

Chapter 1

Third-Generation Biofuels from Microalgal Bioresource: Potential Strategy and Current Trends Arun Kumar Rai and Saurav Anand Gurung

Abstract The rising shift from fossil fuels to cleaner energy fuels has attracted the application of microalgae as third-generation biofuels in recent times. The steady progress from “food vs. fuel” to a “food and fuel” alternative utilizes the favorable photosynthetic capacity, efficient resource utilization as well as the cost-competitive property of microalgal bioresource. Highly efficient CO2 capture by microalgal cell factories is one of the primary drivers of the global warming solution. Biofuels (bioethanol, biodiesel, and biogas) derived from microalgae are called thirdgeneration biofuels and represent the next-generation sustainable energy reserve. With different cultivation strategies, conversion techniques, and genetic engineering for strain improvement, there is immense scope for the future prospect of microalgae as a future fuel. Keywords Third-generation biofuels · Raceway ponds · Photobioreactors · Flocculation · Bioconversion · Strain improvement

Abbreviations ATP BOD C/N CFP COD ECF FAFE FAME GFP GM GOI

Adenosine triphosphate Biological Oxygen Demand Carbon/mitrogen Cyan fluorescent protein Chemical Oxygen Demand Electrocoagulation Flocculation Fatty acid ethyl esters Fatty acid methyl ester Green fluorescent protein Genetically modified Gene of interest

A. K. Rai (*) · S. A. Gurung Department of Botany, Sikkim University, Gangtok, Sikkim, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 P. Verma (ed.), Micro-algae: Next-generation Feedstock for Biorefineries, Clean Energy Production Technologies, https://doi.org/10.1007/978-981-19-0680-0_1

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HABR-PBR NIT RNAi SHF SSF TAG

1.1

Hybrid Anaerobic Baffled Reactor and Photobioreactor Nitrate reductase gene RNA Interference Separate hydrolysis and fermentation Simultaneous saccharification and fermentation Triacylglycerols

Introduction

In recent times biofuels have gained immense importance based on the several benefits associated with their efficient energy production system. Unlike fossil fuels generated by petroleum and diesel, biofuels have the advantage of being renewable as well as environment friendly. The greenhouse gas emissions especially carbon dioxide can be reduced to up to 78% by using biodiesel fuels compared to fossil-derived diesel. In addition, compared to 12,360 g of carbon dioxide per gallon produced through petroleum diesel fuel, biodiesel only produces 2661 g of CO2 per gallon (Fleet et al. 1993). Shifting the focus to renewable biofuels meant a large amount of food feedstock such as sugarcane, maize, wheat, and barley would be utilized for fuel production instead of nutritional uses, thus stating the major drawbacks of first-generation fuels (Xue et al. 2021; Kumar and Verma 2021). To solve this major “Food vs. Fuel” debate, second-generation fuels were then introduced to harness the non-nutritional lignocellulosic biomass such as forest residues, sugarcane bagasse, wheat straw, and corn stover (Wu et al. 2019; Bhardwaj et al. 2021;). However, a need for a tremendous amount of water and arable land was a major factor that presented a further need to explore newer resources for biofuel generation. Microalgae with exceptional photosynthetic capacity, prolific lipid, and carbohydrate profile, as well as its adaptability to perform under extreme stress conditions with high yield output, makes them an ideal candidate for biofuel feedstock generation labelled as third-generation biofuels. Microalgae can be grown in non-arable land and can be cultivated all year round with unchanged yield. Unlike plant-based biofuels that require fertilized nutrient supply for growth, microalgae can be grown using nutrient rich wastewater as a medium such as sewage sludge, municipal wastewater, biological swine wastewater, and dairy wastewater. A study generated efficient Chemical Oxygen Demand (COD) and Biological Oxygen Demand (BOD) removal at 80.62% and 85.61%, respectively, using dairy wastewater as a medium. Chlorella vulgaris used in the study produced a biomass yield of 1.23 g/L in 7 days (Choi 2016). Ji et al. (2015) demonstrated efficient lipid productivity, growth rate, and carbohydrate yield of 13 mg L
1 Day L
1, 0.41 g L
1, and 14.7 mg L
1 Day L
1, respectively, using Scenedesmus obliquus cultures. Wastewater has a harmful impact in the ecological perspective such as eutrophication; however, microalgal-based greener technology can allow nutrient removal as well as utilize the nutrient-rich wastewater in the production of biofuels.

1 Third-Generation Biofuels from Microalgal Bioresource: Potential. . .

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Fig. 1.1 Process technology for biofuel production from microalgal biomass

This biorefinery approach can be further enhanced using improved strains via metabolic and genetic engineering, improving cultivation parameters as well as optimizing the bioconversion processing. Considering the aggressive energy demand and need at a rate of 1.4% per year third-generation fuels are the current well-suited biofuel generation source (Peng et al. 2020). In this chapter, we will briefly discuss various potential strategies such as a range of cultivation practices to increase microalgal biomass, harvesting strategies to harness the produced biomass, and bioconversion techniques to convert the obtained biomass into third-generation biofuels (Fig. 1.1). Furthermore, strain improvement and genetic engineering approaches in microalgae will be discussed.

1.2 1.2.1

Range of Cultivation Strategies Open Cultivation System

Open pond cultivation is the most simple, straightforward, and oldest method for cultivating industrially important microalgae. Classical open pond cultivation in the form of shallow lakes and ponds for growing Spirulina sp. cultures have been reported from earlier times (Ciferri 1983; Durand-Chastel 1980). In addition to Spirulina, several other microalgae such as Chlorella, Chaetoceros, Dunaliella,

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Isochrysis, Nannochloris, Nitzschia, Schizochytrium, Skeletonema, and Tetraselmis were commercially cultivated for their nutraceutical role as powders, tablets, and extracts in the mid-1990s in the Asia Pacific rim (Touloupakis et al. 2016; Goswami et al. 2021a). Technically, open pond cultivation of microalgae is an open biomass production system where the microalgal cultures are continuously exposed to the external environment. With that being said, open pond cultivation system is limited due to several factors, viz., climatic fluctuations and contamination issues. The sunlight regime plays an important role in photo-productivity, and also influences the water temperature in open pond cultivation. However, in an uncontrolled environment as in an open pond the benefits of solar irradiance may not be fully utilized. Microalgae, in general, show maximum photosynthetic productivity at 100–500 μE m
2 s
1, still at higher irradiance photoinhibition of microalgal culture occurs (Goswami et al. 2021b; Chowdury et al. 2020). A study investigating the effect of photoinhibition in open ponds of the National Institute of Technology Rourkela (NITRKL) reported that photoinhibition decreased the average annual biomass productivity by 20% which also resulted in lower lipid productivity at 87.5 to 68.65 m3 ha
1 yr.
1 (Aly and Balasubramanian 2016). Water temperature is another factor correlated with the local light conditions that directly influence productivity in open pond cultivation. A study evaluating open pond cultivation of Phaeodactylum tricornutum highlighted that in winter due to lower water temperature and lower sunlight conditions the microalgal productivity is negative. The study concluded that at lower water temperatures the productivity is decreased by 35–55% to their potential productivity values (Slegers et al. 2013). Overcoming contamination during mass cultivation of microalgae becomes the utmost priority for industries as the contaminants significantly decrease microalgae productivity. Several organisms have been identified as contaminants for the microalgal cultures, viz., bacteria, fungi, protozoa, zooplanktons, and other algae. To tackle the contaminants unique approaches such as chemical, biological and environmental control have been practiced (Z. Zhu et al. 2020). Chemical control utilizes specific chemicals to kill the contaminating organism without affecting the microalgal biomass yield. Park et al. (2016) reported sodium hypochlorite (NaOCl) concentration of 0.45–0.6 mg Chlorine/L was required to inhibit the growth of freshwater rotifer Brachionus calyciflorus in Chlorella kessleri cultures. Another study highlighted that copper concentrations of 0.5–5 ppm significantly inhibited the growth of Brachionus calyciflorus without affecting the growth of Chlorella kessleri (Pradeep et al. 2015). As part of biological control, plant-derived pesticides such as azadirachtin, celangulin, matrine, and toosendanin were explored for their role as a biocontrol against rotifer Brachionus plicatilis. Toosendanin treatment at 1.755–2.132 μg/L was found to be optimum for inhibition in Nannochloropsis oculata and Chlorella sp. (Huang et al. 2014). Utilizing the superior adaptability of microalgae, cultivation systems can be exposed to extreme conditions that allow the microalgae to grow while preventing the growth of contaminating organisms. Zhu et al. (2017) demonstrated that ethanol producing Synechocysti-HZ24 could be rescued from bacterial contaminant Pannonibacter phragmitetus by changing the cultivation conditions to a highly alkaline environment. In another study, high alkaline conditions favored the

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Synechocystis PCC 6803 cultures while inhibiting the golden algae contamination (Touloupakis et al. 2016). The open cultivation systems follow several strategies to cultivate microalgae they may be categorized into different types, viz., circular ponds, inclined ponds, unstirred ponds, and raceway ponds. Circular ponds have been utilized to cultivate microalgae from as early as World War II. A central pivot is utilized to maintain a homogenous distribution of microalgal cells with a size configuration of 40–50 m diameter and shallow to 30 cm depth (Lee 2001; Mehariya et al. 2021). An inclined pond utilizes gravitational force to circulate microalgal cultures towards the bottom and a pump system to recycle them back to the top. This process is repeated during the day; however, at night cultures are stored in the tank, thus saving pumping costs (Borowitzka and Moheimani 2013). Unstirred ponds as the name suggest do not utilize the pivot or wheels to mix the culture, it is an inexpensive approach to culture microalgae in open cultivation mode. Natural lakes, ponds, and lagoons are a few examples of the unstirred mode of cultivation (İhsan 2020). Compared to other open systems, raceway ponds are most exploited because of their relatively less cost. Raceway pond utilizes paddle wheels, airlifts, and propellers to enhance the mixing of cultures and light distribution and prevent thermal stratification. Raceway ponds are 15–25 cm in-depth and can be arranged in single channel-based ponds or with multiple channel configurations (Borowitzka and Moheimani 2013). Microalgae are currently explored for microalgae-based biofuels in raceway ponds. Sanchez et al. (2011) established an indoor raceway pond with 115-L capacity and successfully cultured Isochrysis Galbana with 15.3% of microalgal oil content. A comparison of batch and semi-continuous mode of culture in open raceway ponds for lipid production in two microalgae with excellent lipid profiles was studied. Microalgae, Chlorella sp. L1 and Monoraphidium dybowskii Y2 showed significant improvement in areal lipid productivity in semi continuous mode from 4.06 g m
2 d
1 and 3.00 g m
2 d
1 to 5.15 g m
2 d
1 and 5.35 g m
2 d
1, respectively (He et al. 2016). A study investigated an Indian marine microalgae Chlorella variabilis (PTA-ATCC no. 12198) with suitable biodiesel properties in a 400 L raceway pond. Biomass productivity of 8.1 g
2 day
1 and a total lipid of 10–20% per dry algae weight were achieved (De Bhowmick et al. 2014). Koley et al. (2019) demonstrated significant annual biodiesel productivity of 2.186  0.08 and 2.135  0.10 ton hectare
1 year
1 for Scenedesmus accuminatus cultures under polyhouse and ambient conditioned raceway ponds, respectively. An interesting dual culture of yeast (Lipomyces starkeyi) and microalgae (Scenedesmus sp. and Chlorella sp.) in a 1:2 ratio was prepared in a 400 L raceway pond. Using urban wastewater as a medium, a 15% lipid yield per dry weight was measured for microalgae which also demonstrated that this enhancing property of yeast cultures could be used in the coming times to treat wastewater (Iasimone et al. 2017).

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A. K. Rai and S. A. Gurung

Closed Cultivation System

Although being a costlier method for microalgal cultivation than an open system, a closed cultivation system brings greater control over limiting parameters such as evaporation loss, fluctuating irradiance, and contamination involved in an open cultivation system (Chowdhury and Loganathan 2019; Goswami et al. 2020). A study reported 5.5 times higher volumetric productivity of photobioreactor compared to open raceway pond-based cultivation for Tetraselmis sp. MUR-233 (Raes et al. 2014). The closed cultivation system is a photobioreactor based cultivation strategy. Numerous configurations of photobioreactors have been utilized in microalgal cultivation for several applications such as wastewater treatment, commercial production of high value metabolites, cosmetics, etc. (Balasubramaniam et al. 2021; Goswami et al. 2021b; Das 2015; Talbierz et al. 2012; Ting et al. 2017; Zhu et al. 2019).

1.2.2.1

Tubular Photobioreactors

Tubular photobioreactors are the most widely used closed cultivation system with different technical varieties, viz., airlift and bubble column, horizontal and vertical, helical and polythene bags, and sleeves based tubular photobioreactors. A common feature in tubular photobioreactors includes a circulation pump that enhances the mixing of microalgal cultures, and also the transparent feature of the photobioreactor surface that allows active light penetration. Airlift and bubble column photobioreactors have cylindrical dimensions made up of cheaper materials such as polyethylene, polyvinyl chloride, and polypropylene acrylic (Mehariya et al. 2021). Furthermore, the absence of moving parts such as wheels and propellers thus prevents damage to the microalgal cultures, also since it is made up of transparent material it can be used in indoor and outdoor cultivation. A gas distributor in the bottom part of the photobioreactor column enhances bubble formation which is involved in mixing the cultures. In similar lines airlift photobioreactor gas distributor at the bottom allows the culture to flow in an upward direction in a riser zone, with separate liquid flow in downward direction completing the circulation in the photobioreactor system (Płaczek et al. 2017). Tubular photobioreactors have been widely utilized for the generation of biofuels. A study investigating the application of tubular photobioreactor in bioremediation and oil production from Desmodesmus subspicatus yielded 18% oil content with CO2 supply (Gressler et al. 2014). In another study vertical tubular photobioreactor was utilized to harness Scenedesmus bijugatus for bioethanol and biodiesel production. Significant yield in terms of biomass (0.26 g L
1 d
1 per dry biomass), biodiesel (0.21 g/g dry biomass), and bioethanol (0.158 g/g dry biomass) was obtained (Ashokkumar et al. 2015). Bahadur et al. (2013) investigated a 20-L capacity airlift tubular photobioreactor for Chlorella vulgaris cultures. The photobioreactor produced a significant volumetric production of 0.65 g/L/day which was comparable to the

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theoretical yield of 0.82 g/L/day. Evaluation of a distinctive X-shaped Airlift photobioreactor used for cultivating Chlamydomonas reinhardtii CC125 showed prominent lipid production values of 117.624  3.522 mg/L which was 23.49% higher than the control photobioreactor (Pham et al. 2017). Tao et al. (2017) demonstrated the potential of a unique algal biofilm airlift photobioreactor to treat wastewater using Chlorella vulgaris cultures. Specific carriers in the photobioreactor allowed higher biomass productivity, higher lipid productivity, and improved nutrient removal rates than the conventional photobioreactor system. About 15.93 mg L
1 d
1 and 4.09 mg L
1 d
1 values for the productivity of biomass and lipid were subsequently achieved using this unique photobioreactor system. Furthermore, a study obtained a significant lipid yield of 144 mg/L for Chlorella minutissima in an 18-L capacity batch bubble-column photobioreactor which was quite close to values obtained in previous studies on similar parameters (Pereira et al. 2018). Rasoul-Amini et al. (2011) investigated a naturally isolated strain of Chlorella sp. And demonstrated the favorable biodiesel composition of the microalgae using 2-L capacity bubble-column photobioreactor. CO2 concentrations are a limiting factor in mass microalgal cultivation productivity. Fluctuating the sunlight regime complicates the issue of carbon capture by photosynthetic microalgae. However, with sufficient CO2 concentrations better biomass productivity can be achieved. A study investigated the use of real-time sunlight-based CO2 supply in a 10-L capacity bubble column photobioreactor for Chlorella sp. FC2 IITG. This novel carbon feeding based photobioreactor system gave significant biodiesel yield of 3.3 g L
1 under natural light conditions (Naira et al. 2019). Vertical and horizontal tubular photobioreactors are a series of parallel cylindrical systems adjusted to incline at an angle for efficient sunlight penetration. In outdoor conditions the advantages of being contamination-free and further the feasibility to change angles according to the sun irradiance levels these photobioreactors can be utilized for a longer span of time in outdoor conditions. Installed gas exchange and heat exchange system allows free removal of oxygen produced during the cultivation process and prevents overheating of the cultures, respectively. Helical or annular photobioreactors are highly efficient for small volume operations. The cylindrical tube is helical in shape with transparent material made up of polyethylene with a circulation pump that allows efficient mixing of the microalgal cultures. Lastly, polythene bags and sleeves-based photobioreactors are made up of cheap and sterile polythene-based bags hanging via a supporting rack and equipped with a circulation pump. Since made up of weaker material these types of photobioreactors are at high risk of breakage and mechanical damage (Godbole et al. 2021; Płaczek et al. 2017). Although having several applications tubular photobioreactors have a major drawback of being susceptible to biofilms formation that prevents efficient photosynthetic uptake.

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1.2.2.2

A. K. Rai and S. A. Gurung

Flat Photobioreactors

Flat photobioreactors are another reassuring system for microalgal-based biofuel production. This model comes as a transparent flat-panel configuration made with sheets of glass, plexiglass, and polycarbonates. A flat photobioreactor’s superior surface-to-volume ratio promotes improved and higher biomass productivities (Acién et al. 2017; Yoo et al. 2010). Furthermore, promising innovations in the development of flat photobioreactors have been introduced to improve the costeffectiveness of microalgal cultivation. Yan et al. (2016) developed a novel thin-film flat photobioreactor with a 2000-L capacity that operates in outdoor conditions. Maximum area productivity of 11.0 and 21.9 g/m2/day for Chlorella sp. and Scenedesmus, respectively, was achieved with this novel photobioreactor model. In addition, a study demonstrated the application of a special gas sparging system that allowed better mixing in a flat-panel photobioreactor system. Utilizing Scenedesmus abundans cultures maximum biomass productivity of 6.9 g/L and significant fatty acid methyl ester (FAME) concentration of 1.53 g/L was achieved (Mahesh et al. 2019). Another unique approach to reducing costs and water footprint in microalgal cultivation utilizes cost-effective seawater-based medium in a Green Wall Panel photobioreactor. A potential Chlorella strain CH2 generated 11 t ha
1 y
1 lipids and 41 t ha
1 y
1 biomass via this green approach of mass cultivation (Guccione et al. 2014). Another approach to reduce cost figures in a closed photobioreactor system is employing natural sunlight as a light source. Working on these lines a study established lipid production in Chlorella zofingiensis via a flat plate photobioreactor system in outdoor conditions. The highest lipid content of 54.5% per dry weight under nitrogen starvation was attained (Feng et al. 2011).

1.2.2.3

Hybrid Photobioreactors

As the name suggests Hybrid photobioreactors apply both open and closed cultivation practices to improve productivity and cost-efficiency. It is a two-stage-based model where in the first part microalgae are cultured in a contamination-free closed cultivation system and the subsequent step cultures are shifted at a higher capacity raceway pond. Hybrid photobioreactors can be adapted to meet specific needs. In a study Hybrid photobioreactor comprising of 20-L helical photobioreactor and an open pond under salt stress conditions was evaluated to produce β-carotene in Dunaliella salina. The highest β-carotene yield of 4.85 μg/mg microalgal dry weight was attained (Hashemi et al. 2020). In another study integrated airlift-driven photobioreactor in the first stage to increase biomass yield and in the second stage nutrient-limited raceway ponds to increase lipid yields. Notably, compared to independent photobioreactor systems (raceway ponds or airlift systems) hybrid photobioreactors produced significantly higher growth rates and higher cell density of microalgae Tetraselmis sp. M8 (Narala et al. 2016). In a novel model of pondtubular hybrid photobioreactor flashing light, effects were investigated in Chlorella

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PY – ZU1. The results demonstrated a 31.2% and 54.7% higher biomass yield and areal microalgal biomass compared to conventional raceway ponds (Xu et al. 2020). Moreover, implementation of wastewater for biofuels production via Hybrid Anaerobic Baffled Reactor and Photobioreactor (HABR-PBR) showed promising potential. A synergistic culture in the ratio of 1:2:1 of Chlorella vulgaris, Chlorella sorokiniana, and Scenedesmus simris002 could promote high lipid yield of 44.1% and high FAME percentage of 87.9% (Khalekuzzaman et al. 2019).

1.3

Microalgal Harvesting

Microalgal harvesting is an essential process that covers almost 20–30% of the total cost for microalgal biomass (Singh et al. 2013). Microalgal harvesting is the separation of microalgal cells from the medium present in the cultivation models by several downstream processes. Flocculation is a widely known process that utilizes the unstable microalgal accumulation called flocs to promote harvesting. Chemical flocculants such as ferric chloride, ferric sulphate, aluminum chloride, and aluminum sulphate function by forming charged patches of positively charged hydroxide precipitates on microalgal cells. As a result of this phenomenon, electrostatic bridges bind differentially charged microalgal cells resulting in coagulation (flocs formation) and subsequent harvesting of microalgal cells (Wyatt et al. 2012). A study highlighted the superior separation efficiency (>90%) of Ferric chloridebased flocculation compared to chitosan and alkaline-based flocculation. The study supported ferric chloride-based flocculation with concentration factor (>10) in ten microalgal species, viz., Chlorella vulgaris, Pseudanabaena, Chlamydomonas reinhardtii, Scenedesmus obliquus, Phaeodactylum tricornutum, Diacronema lutheri, Tetraselmis suecica, Nannochloropsis oculata, Dunaliella salina and T-Isocrysis lutea (Lama et al. 2016). In recent years to increase the efficiency combined flocculation techniques have been popular. Wei et al. (2018) reported highly efficient combined coagulants involving ferric chloride with cation-rich starch-based flocculants. Another study showed a novel ferric chloride and polyacrylamide-based hybrid flocculants (Lee et al. 2011). A study investigated the combined flocculation strategy of ferric chloride with cationic polymers such as polyacrylamide and polyethylenoxide in Chlorella vulgaris GKV1. Flocculation efficiency of 60% and 87% was achieved for ferric chloride + polyacrylamide and ferric chloride + polyethylenoxide, respectively. Flocculation efficiency was about 80% when both the cationic polymers were used with ferric chloride (Gorin et al. 2015). The high effectiveness of cationic flocculants is credited to the negatively charged microalgal cell wall that allows the electrostatic binding of flocculants to the microalgae (Enamala et al. 2018; Granados et al. 2012). Despite high efficiency in chemical-based flocculation for microalgal harvesting some issues in the downstream processing limit the flocculation process (Papazi et al. 2010). pH-induced flocculation also shows considerable flocculation efficiency. In a study involving Chlorococcum sp. R-AP13 high flocculation efficiency of 94% was acquired when

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the pH of the medium was increased from 8.5 to 12. The flocculation efficiency was higher compared to aluminum-based and ferric chloride-based flocculation with 87% and 92% efficiency, respectively (Ummalyma et al. 2016). Bases such as magnesium hydroxide, calcium hydroxide, potassium hydroxide, and sodium hydroxide have been utilized to achieve the desired pH for flocculation. Although magnesium ions are reported to have a role in the active formation of hydroxide precipitates that promotes flocs formation due to its high cost a cheaper alternative calcium hydroxide is generally preferred (García-Pérez et al. 2014; Vandamme et al. 2012). Electrolytic processes for harvesting microalgae have been growing popular in the past few years. The development of electro-coagulation–flocculation (ECF) has allowed researchers to fully explore the electrolytic potential for cost-effective harvesting of microalgal biomass. During the process of ECF metal ions such as iron and aluminum from the anode part of the ECF, model reacts with the water in the surrounding media to form metal hydroxides, which neutralizes the negatively charged microalgal cell wall causing the cells to destabilize resulting in flocculation (Vandamme et al. 2011). Fayad et al. (2017) displayed efficient parameter values for harvesting of Chlorella vulgaris via electro-coagulation–flocculation (ECF). A stirring speed of 250 rpm, acidic pH (pH -4), current density (2.9 Ma/cm2), and 1 cm inter-electrode distance are the conditions that generated the maximum cost effectiveness for the model system. In a similar study for evaluating harvesting of Scenedesmus sp. in ECF an optimal condition have been described, i.e., pH-5, inter electrode distance of 2 cm, sedimentation time of 60 min, and current density of 12 mA cm
2, etc. (Pandey et al. 2020). Bioflocculation is another widely explored method of microalgal harvesting that utilizes microorganisms and their polymeric compounds. In comparison to chemical and electrolytic-based flocculation techniques, flocculations are relatively cheaper to use as well as environmentally friendly as they do not utilize harsh chemicals that may negatively affect the environmental structure. Plant-based flocculants have become popular because it is biodegradable, sustainable, and highly cost-effective. Using Moringa-based protein–oil emulsion for harvesting Nannochloropsis sp. a flocculation efficiency of 86.5% was accomplished effectively (Kandasamy and Shaleh 2018). In another study, Moringa oleifera seeds were evaluated for their flocculation capacity in Chlorella vulgaris. A significant flocculation efficiency of 89% was achieved enhanced with an increase in pH, sedimentation time (120 min), and concentration (0.6 g/L) (Teixeira et al. 2012). Abdul Hamid et al. (2016) evaluated the flocculation activity of Moringa oleifera seed powder in Chlorella sp. Evidently, 97% of flocculation efficiency was reached much higher than Alum flocculants whose efficiency was 34%. Working on similar lines Moringa oleifera Lam seeds powder achieved flocculation of 93% via Chlorella sorokiniana (Silva et al. 2021). The significant bioflocculant property of Moringa oleifera seeds is due to the presence of water-soluble cationic polyelectrolytes that destabilizes negatively charged microalgal cell (Jethani and Hebbar 2021). Cationized plant-based polymers represent additional bioflocculants widely utilized in microalgal harvesting. Cationized plant polymers are synthesized via chemical treatment to further enhance

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their flocculation activity. A study investigated 2,3-epoxypropyltrimethylammonium chloride (GTMAC) induced cationic locust bean gum biopolymer (CLBG) for its flocculation capacity. A significant flocculation efficiency of CLBG on three microalgae, viz., Micractinium sp. NCS2, Scenedesmus sp. CBIIT(ISM) and Chlorella sp. NCQ were 96.64%, 97.42%, and 96.68%, respectively (Kumar et al. 2019). Another study showed efficacy at a low dose of cationic starch on Scenedesmus dimorphus being 0.08 g cationic starch/g of microalgal biomass (Hansel et al. 2014). Using nanoparticles-based natural flocculants has gained immense popularity because of its flocculation effectiveness even at higher doses compared to other natural flocculants such as chitosan. While in chitosan at higher doses microalgal restabilization may occur, however, with the higher number of positive charges that are added to microalgal cell nanoparticlesbased flocculation seems a better approach (Blockx et al. 2019). Despite this superior property in flocculation experiments, a study showed lower flocculation efficiency for cationic cellulose nanocrystals (CNCs) bioflocculants compared to chitosan with flocculation efficiency of 90% and > 95%, respectively. However, on application of centrifugation, higher efficiency of more than 95% was achieved for CNCs (Verfaillie et al. 2020). Although mechanisms involving microbial-based bioflocculation is poorly understood in the microalgal harvest process many studies have been conducted on these lines. In a study γ- Poly glutamic acid extracted from Bacillus licheniformis CGMCC 2876 showed significant flocculation efficiency of more than 96% in Desmodesmus sp. F51. The study demonstrated that bacterial extract was effective in neutralizing the microalgal cell much more efficiently than mere pH-based flocculation strategy (Ndikubwimana et al. 2015). Another study on the harvesting capacity of γ- Poly glutamic acid further established the microalgal cell neutralization effect by change in the zeta potential under the influence of the microbial bioflocculants. On incorporation of optimal concentration of γ- Poly glutamic acid extract in Chlorella protothecoides UTEX 255 and Chlorella vulgaris CCTCC M 209256 zeta potential values represented a significant change from 13.62 and 19.08 mV to +0.83 and +21.50 mV (Ndikubwimana et al. 2015). Fungal induced pelletization of microalgae is another area that can boost bioflocculation measures. Filamentous fungi produce a low molecular weight protein called hydrophobins that functions to direct fungal adherence to solid surface. Utilizing this property a co-pelletization model of filamentous fungi and non-filamentous microalgae can thus be proposed (Zhang and Hu 2012). A study highlighted importance of pH in controlling fungal microalgal co-pelletization. Increase in glucose control was used as a control for pH modulation, significantly at 20gm/L glucose concentration 100% co-pelletization of fungal-microalgae was observed at a short retention time (Zhou et al. 2012). Bhattacharya et al. (2017) evaluated a rapid method for fungal induced co precipitation in Chlorella pyrenoidosa. The results demonstrated that a pre-grown fungal culture of Aspergillus fumigatus at 24-h interval can effectively co-precipitate microalgal cell if used in a ratio of 1:5 (fungi: microalgae) and in no longer than 3-h time. Centrifugation is a mechanical technique that separates solid particles from a solution or two immiscible liquids using centrifugal forces and the separation is

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A. K. Rai and S. A. Gurung

dependent significantly on the size, density, and rotor speed of the centrifuge. Although centrifugation is an efficient technique for microalgal harvesting with more than 90% harvesting efficiency, the greater economic cost for its operation makes the industrial application less cost-efficient (Najjar and Abu-Shamleh 2020). Also the large forces applied in the centrifugation process can lead to damage of microalgal cell factory. A study on disc stack centrifuges resulted in significant damage to yeast cells and possible damage to microalgal cells based on observation of micro-eddy sizes (Milledge and Heaven 2011). In a particular study, however, the cost-effectiveness of the centrifugation process was achieved by increasing the flow rate. When only 28.5% of microalgal biomass was processed at an increased flow rate of 18 L/min, 82% energy consumption values were achieved, thus significantly improving the cost-related issues in centrifugal microalgal harvesting (Dassey and Theegala 2013). Sedimentation is more or less a natural phenomenon involving the density-based separation of solids and liquids. It is hypothesized that heavier algal cells sediments and allow harvesting (Enamala et al. 2018). However, in practical microalgal harvesting, sedimentation process is co-enhanced with other separation parameters such as centrifugation, flocculation, and pH-based sedimentation. In a study optimization of sedimentation parameters for Chlorella sorokiniana were determined and harvesting efficiency of more than 97.8% was obtained. Optimal values for this efficiency include velocity gradient (250 s
1), mixing time (10 s) and pH value-12. Further centrifugation would allow an increase in harvested microalgal concentration by 123 times (de Leite and Daniel 2020).

1.4

Conversion Techniques for Biofuels Production

Transesterification is a popular choice in industrial settings for the purpose of biodiesel production. The process involves breaking down stored lipids (Triacylglycerols) via alcohol into fatty acid alkyl esters and glycerol in presence of a catalyst. Although many types of transesterification approaches are reported widely known “in situ transesterification” or direct transesterification have made a significant impact as preferred process technology. In a study comparing direct transesterification and extraction-transesterification process, direct transesterification process gave a higher fatty acid yield and higher lipid recovery in all three microalgae, Chlorella vulgaris, Scenedesmus sp., and Nannochloropsis sp. Also compared to an extraction-transesterification method that involves an extra oil extraction step, a single step direct transesterification reduces the biodiesel cost output by almost 10% (Griffiths et al. 2010). Several factors affect the process of in situ transesterification and influence the yield of biodiesel production. In one study on increasing the volume of alcohol, the increase in lighter FAME (Fatty acid methyl esters) products with lower specific gravity were observed. These lighterweight FAME products are without glycerol, a by-product of transesterification, thus it is more purified FAME compared to the heavier FAME. Further, the influence of temperature on transesterification reaction was established. At room temperature, no

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lower specific gravity FAMEs were produced; however, on increasing the temperature to 90  C highest low specific gravity FAMEs as 70% and 92% were produced in 15 min and 1 h duration, respectively (Ehimen et al. 2010). The choice of acidic or basic catalyst is also a limiting factor in favorable transesterification reactions. Velasquez-Orta et al. (2013) demonstrated that using the acid catalyst for transesterification in Nannochloropsis oculata and Chlorella sp. such as sulphuric acid the FAME yield was 92  2% compared to 79  2% for basic catalysts such as sodium hydroxide. Alkali as a catalyst is sensitive to water and free fatty acids and the subsequent reaction of saponification leads to the formation of soaps and emulsions that inhibit the downstream processes. Despite this alkali catalysed transesterification is a viable approach in biomass with less than 0.5% free fatty acids. In view of rich free fatty acid content in microalgae, acid-based catalysis is preferred as it is insensitive towards free fatty acids and shows a correlative enhancement of FAME with increasing temperature, alcohol volume, and reaction time (Al-Zuhair 2007). Kim et al. (2015) demonstrated that hydrochloric acid can be an effective catalyst with over 90% of FAME yield even when the microalgal biomass used was wet. Despite using highly wet microalgal biomass (80% moisture content) FAME yield was 15% higher compared to that of sulphuric acid. Acid and base-based catalysts are widely utilized but due to the harsh nature of acidic treatment that needs extreme precautions and saponification reaction that decreases the FAME yield, new frontiers of enzyme-catalyzed transesterification reaction have been popularizing in recent times. Nanoparticles such as calcium oxide, aluminum oxide, and magnesium oxide can be utilized as a lipase carrier because of their excellent immobilization capacity and further enhance significant enzyme recovery (Zhang et al. 2013). Thus, instead of using a homogeneous catalyst such as acids or bases, heterogeneous catalysts are now the preferred choice in biodiesel production strategy. In a study heterogeneous catalyst involving potassium hydroxide-Alumina (KOH/Al2O3) gave a significant biodiesel yield of 89.53  1.58% via in situ transesterification in Chlorella vulgaris biomass. Ma et al. (2015) utilized potassium hydroxide is another heterogeneous nanocatalyst magnetic alumina-ferric oxide (Fe2O3–Al2O3) for demonstrating its in situ transesterification performance via co culture of several microalgae, viz., Chlorella vulgaris, Chlamydomonas debaryana, Euglena sp., Oscillatoria quadripunctulata, Microcystis aeruginosa, and Scenedesmus bijuga. The nanocatalyst had a significant transesterification yield of 95.6% and possessed high stability values that can be recovered for at least six runs. Supercritical transesterification is a catalyst-free transesterification strategy under supercritical conditions of temperature and pressure. In one study CO2 was used as co-solvents along with ethanol and methanol for a catalyst-free transesterification reaction involving Spirulina oil. Utilizing CO2 effectively increased the yield from 42% to 65% and 46% to 72% at supercritical conditions of 200  C and 300  C, respectively (Tobar and Núñez 2018). Another study utilized microalgal biochar obtained from Chlorella protothecoides for biodiesel production via supercritical transesterification. At a constant supercritical temperature of 275  C Fatty acid ethyl esters (FAEE) yield of 79% at (5:1 alcohol: fatty acid) and 89% at (20:1, alcohol: fatty acid) were achieved (Levine et al. 2013). Furthermore, a sustainable single step

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strategy involving direct transesterification using wet microalgal biomass in supercritical ethanol conditions produced an efficient conversion rate of 67% at 265  C and a short reaction time of 20 min (Reddy et al. 2014). Biofermentation is another major bioconversion technique involved in biofuels production from microalgae. Although there are three major pathways for bioethanol production including dark fermentation, photo-fermentation, and traditional ethanol fermentation, the traditional fermentation methods are widely utilized in industrial operations. Dark fermentation is a physiological process in which the photosynthetically derived lipids and carbohydrates are hydrolysed to pyruvate for ATP generation in cells. Pyruvate thus produced can be channeled into ethanol, acetate, glycerol, and gases such as hydrogen and carbon dioxide as well. Photofermentation is observed in cyanobacteria such as Synechocystis and Synechococcus sp. where ethanol production occurs directly in the presence of light. Traditional ethanol fermentation involves pre-treatment using physical, chemical, and enzymatic treatment, enzymatic hydrolysis, and fermentation process involving microbial fermenters (Lakatos et al. 2019; Kumar et al. 2020; Agrawal and Verma 2022). A study produced a bioethanol yield of 18.57 g/L based on separate hydrolysis and saccharification process for Microcystis sp. Optimal conditions that were determined through the study include immobilized yeast volume of 15.09% for a time interval of 43.6 h and 98.7 g/L of the microalgal dry weight (El-Mekkawi et al. 2019). There are two methods of saccharification or breakdown of complex carbohydrates into fermentable sugars, viz., separate hydrolysis and fermentation and simultaneous saccharification and fermentation. In the prior hydrolysis of sugars is succeeded by a fermentation process and in the later hydrolysis and fermentation process occurs simultaneously. In a study evaluating the two processes, SSF achieved an ethanol concentration of 57.75 g/L which was 16.26% greater than the SHF process (Suttikul et al. 2016). Out of the several pre-treatment strategies available for bioethanol production from microalgae one study utilized acidic pre-treatment to improve the fermentation process and increase bioethanol yield. Significantly bioethanol yield of 0.28 g/g microalgal dry weight was achieved with 5% sulphuric acid pre-treatment (Phwan et al. 2019). Shokrkar et al. (2017) investigated the efficiency of several pretreatment methods such as chemical (acidic and basic) and enzymatic treatment in bioethanol production. Evidently, results suggested that enzymatic pre-treatment produced the highest bioethanol recovery of 92% (0.46 g bioethanol/g glucose) followed by acidic treatment that yielded 76% bioethanol (0.38 g bioethanol/g glucose). On the contrary, a study produced the highest fermentable monosaccharide yield of 88 mg/g dry biomass obtained through acidic treatment compared to the enzymatic method. Utilizing the combination of both acidic and enzymatic pre-treatment method a significant fermentable monosaccharide yield of 128 g/g and 129 g/g biomass weight for Chlorella sorokiniana and Nannochloropsis gaditana, respectively. Other pretreatment techniques such as autoclave, microwave-assisted, and alkaline hydrolysis produced a significantly lower concentration of fermentable sugars (Hernández et al. 2015). Anaerobic digestion method for biogas production is a cost-effective, environment-friendly strategy to energy production from microalgal biomass. Compared to

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biodiesel and bioethanol production that requires higher concentration and higher prolific values of lipids and carbohydrates, respectively, anaerobic digestion on the other hand is a whole component hydrolysis strategy. The whole conversion of organic biomass can occur via several processes primarily hydrolysis of macromolecules such as protein, carbohydrates, lipids into simpler amino acids and peptides, sugars, and fatty acids, respectively. Furthermore, with the action of acidogenic, acetogenic, and methanogenic microorganism’s volatile fatty acids, carbon dioxide, hydrogen, acetic acid, and methane can be synthesized (Wu et al. 2019). Torres et al. (2021) investigations show a notable biorefinery approach of biogas production using anaerobic digestion in three microalgae, viz., Chlorella sp., Nannochloropsis sp., and Scenedesmus sp. Utilizing by-products from microalgal biodiesel prospects biogas production yield was obtained at par with the dry microalgal biomass based on both its volume as well as its quality. A significant biogas yield of 510.69 NL Kg
1VS was achieved using this microalgal residue in sewage sludge inoculum. An important factor that limits anaerobic digestion of microalgal biomass includes lower carbon and nitrogen (C/N ratio). Microalgae with high protein content complicate the issue of biogas production with a lower C/N ratio leading to the formation of total ammonia nitrogen and volatile fatty acids that interferes with methanogenic activities (Tanimu et al. 2014). A unique strategy involving mixing biomass with a higher C/N ratio can then improve the biogas production efficiency. Macroalgae are thus approached with their higher C/N ratio that can compensate for the lower C/N ratio in microalgae (Wang et al. 2021). In another study a correlation between the C/N ratio and temperature is accomplished as increasing the temperature allowed an increase in C/N ratio by ammonia inhibition. At 35  C C/N ratio were 26.76; however, on increasing the temperature to 55  C C/N ratio of 30.67 was achieved (Wang et al. 2014).

1.5

Strain Improvement and Genetic Engineering of Microalgae

In view of the faster cellular division and continuous biomass accumulation in microalgal species, the production potential of various bioactive compounds and fuel can be stated. Advancements made in the recent past in metabolic engineering, genome editing, and synthetic biology have demonstrated improvements in transformation efficiencies (Jagadevan et al. 2018; Chaturvedi et al. 2020; Goswami et al. 2021c). These advancements have clustered our understanding of the microalgal metabolic pathway that has now been explored for the production of recombinant proteins such as immunotoxins and antibodies (Poliner et al. 2018a). For delivering transgenes into microalgae, engineering vectors serve as an important method. The glass bead method is a convenient and cost-effective process for gene delivery in microalgae and has been successfully used in Chlamydomonas reinhardti, Dunciella salina, and Platymonas subcordiformis (Cui et al. 2010; Feng et al. 2009; Kindle

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1990). Agrobacterium-mediated transformation is another efficient method that holds a great promise to transform large DNA segments (>100 kb) into cells and has been used successfully in Chlamydomonas reinhardti, Isochrysis sp. and several other microalgal species (Kumar et al. 2004; Prasad et al. 2014). In similar lines Electroporation is a simple, easily applicable and efficient way of gene delivery and has been used successfully in Chlamydomonas reinhardti, Chlorella pyrenoidosa, and Scenedesmus obliquus (Brown et al. 1991; Guo et al. 2013; Run et al. 2016). Nanoparticle-mediated DNA delivery also holds great promise but has not been used in microalgae to date, only its application in monocots and dicots has so far been reported (Demirer et al. 2019). Various attempts have been done in the genetic engineering of microalgae for exploiting their wide potencies in the production of biofuels and economically viable bioactive compounds. The first report on stable nuclear transformation in microalgae, Chlamydomonas reinhardtii by glass-bead mediated transformation was done on the endogenous promoter of NIT (nitrate reductase gene) for the NIT target gene to recover an NIT-deficient strain with a wild type NIT1 gene (Kindle 1990). Furthermore, Agrobacterium-mediated nuclear gene transformation in microalgae was carried in Chlamydomonas reinhardti with CaMV 35S promoter for beta-glucuronidase (UIDA), green fluorescent protein (GFP), and hygromycin phosphotransferase (HPT) genes (Kumar et al. 2004). Promoters work in concert with genetic elements (silencers, enhancers, transcription factors, and boundary elements/ insulators) and plays an essential role to direct the transcription of marker genes and sequences. Electroporation mediated transformation was done in Chlorella pyrenoidosa with transformation efficiency of 1.67  104  0.083 cfu μg
1 using two reporter genes, viz., green fluorescent protein (GFP) and cyan fluorescent protein (CFP) (Kumar et al. 2018). MiyagawaYamaguchi et al. (2011) investigated biolistic transformation of Chaetoceros sp. with Thalassiosira pseudonana (fucoxanthin chlorophyll a/c binding protein) FCP or (nitrate reductase) NR gene promoters for the Nourseothecin resistance (NAT) gene. Significant transformation efficiency of 1.5–6 transformants per 108 cells was achieved for this study. In addition to vectors and promoters incorporation of regulatory elements such as introns and featured transcript sequences are also used for the improvement of transformation efficiency and also to increase the exogenous gene expression (Weiner et al. 2018). Efforts are been done to improve transgene expression by inserting different introns into vectors or including a Kozak consensus sequence in the 50 UTRs (Salama et al. 2019). This can help identify the speciesspecific biological components and regulatory mechanisms which help in the customized designing of synthetic promoters, biological bricks, and circuits (Jia et al. 2016). Overexpressing of genes of interest (GOIs) is of distinct advantage considering the expression of vital genes and is also required for trait optimization. A recently developed technique for multigene expression involves designing expression vectors with bidirectional promoters, isocaudamers, or self-cleaving peptide F2A (Poliner et al. 2018b). This approach has been successfully utilized in microalgal species such as C. reinhardtii and Neochloris oleoabundans (Dent et al. 2015; Muñoz et al. 2019; Poliner et al. 2018b). Random mutagenesis with insertional mutagenesis, RNAi mediated gene knockdown, genome editing, and

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T-DNA techniques have been used in multigene expression. By random insertion of transforming cassettes, whole-genome mutagenesis libraries have been generated only in microalga Chlamydomonas reinhardtii (Mackinder et al. 2017). The mutant population was found to be highly effective to dissect the function of key genes in photosynthesis and TAG biosynthesis (Cerutti et al. 2011; Freeman Rosenzweig et al. 2017). A large number of microalgal species have been engineered using CRISPR/Cas9 systems, such as C. reinhardtii and P. tricornutum for a look into the reconstruction of cellular behavior (Jeon et al. 2017; Sodeinde and Kindle 1993). Nuclear and organelle genomes can be manipulated for the desired output in microalgal bioprocessing. The microalgal chloroplast genome of Nannochloropsis sp. (~120 genes) involved in photosynthesis and gene expression can be precisely manipulated to meet certain needs in microalgal bioprocessing. For the regulated expression of several genes with their gene products involved in photosynthesis, oil metabolism or phytohormone synthesis will be targeted to the plastids (Scotti et al. 2012). To date, more than 100 foreign or native proteins have been produced in microalgal chloroplasts, including 40 proteins with therapeutic values produced in C reinhardtii chloroplasts (Qaim 2009). Chloroplast transformation is generally done by particle bombardment of gold nanoparticles of around 10-micrometer diameter or polyethylene glycol (PEG) mediated protoplast transformation. A recently developed electroporation-based technique was successfully employed for transforming Nannochloropsis chloroplasts (Li et al. 2014; Xie et al. 2014). De novo synthesis of the microalgal chloroplast genome is now possible with synthetic biology principles that have been applied in plastome engineering, allowing the ex vivo assembly, modification, and duplication of the entire Clamydomonas chloroplast genome (Chen and Melis 2013). Genetic modification plays an important role in the development of transgenic microalgal species with varied potentials. Genetically modified (GM) microalgae are created by the insertion of DNA containing marker genes and GOIs into the genome of the host. C. reinhardtii chloroplast was successfully transformed and the strain selection with zero false positives was obtained upon reconstitution of a functional Rubisco large subunit gene (rbcl) gene recovery of Rubisco catalytic activity, coupled with the heterologous expression of the Saccharomyces cerevisiae ADH1 gene (Poliner et al. 2018b). Non–GM breeding in microalgae is done using extrachromosomal vectors or episomes in Nannochloropsis oceania, thus highlights the potential to create non-GM microalgal strains by tools derived from episomes with specific universal microalgal host (Han et al. 2020; Loera-Quezada et al. 2016). Transcriptional engineering also aims at trait improvement of microalgae by expressing plant transcription factors resulting in enhanced production of desired chemicals (Kemmer et al. 2010). Among all the microalgal taxa C. reinhardtii is the only species in which the transcriptional regulation and cellular metabolism are best understood. Microalgal species are largely employed in the production of biofuels. Microalgae produce fatty acid molecules and other energy rich combustible molecules that can be utilized as biofuel. Overexpression of DGAT2 gene in microalgae Phaeodactylum tricomutum increased the lipid production by 35% (Niu et al. 2013). Similarly in Chlamydomonas reinhardtii disruption of ADP-glucose phosphorylase or

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isoamylase genes resulted in tenfold increase in TAG accumulation (Work et al. 2010).

1.6

Conclusions

Third-generation biofuels from microalgae require the collaboration of several strategical models of efficient cultivation, harvesting, and bioconversions. While photobioreactors may be highly controlled and productive high-end cost associated with them limits the industrial application. Instead, hybrid photobioreactor-based cultivation system presents a better approach to negate the limitations pushed by open and closed cultivation models. Harvesting process estimate up to 20–30% cost as an industrial bioresource with technological advancements such as centrifugation, freeze dryer, and refrigeration costs. However, exploration into sustainable biofuels production strategy has allowed researchers to develop greener technology with minimum footprints. The utilization of bioflocculants emphasizes one such strategy instead of using harsh acidic and alkaline chemicals. Finally, prospects of genetically modified microalgae with favorable characteristics put forward another opportunity to develop industrial interests and find superior outcomes in the production of thirdgeneration fuels. Competing Interest All the author declares there is no competing interest.

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Chapter 2

The Promising Future of Microalgae as Biofuels and Valuable Bioproducts Satyabrata Dash, Sabyasachy Parida, Bijayananda Sahoo, and Biswajit Rath

Abstract Microalgae are autotrophs with simple growth requirements such as light, sugars, and CO2 that can produce more amount of lipids, proteins, and carbohydrates at a short interval. Their biomass can be processed into biofuels and other high-value bioproducts efficiently by increasing their commercial viability for use in nutraceuticals, cosmeceuticals, pharmaceuticals, and the food industry. Currently, focus has been shifted to microalgae due to their higher food and fuel production ability. Renewable energy sources especially biofuel is the major thrust of research of this century. In the fuel industry sector, algal biofuels have been emerged as a clean, green, nature-friendly, cost-effective solution than other fuels. Economically and environmentally friendly production of such energies using microalgae with more oil content is a good oil-producing alternative than fossil fuels and oil-based crops. Additionally, microalgae offer rich biodiversity with an enormous potential to produce structurally diverse high-value novel compounds which are either impossible or difficult to produce via synthetic routes. This review aims to provide the current status of a microalgal application for biofuel production, as well as their cultivation, harvesting, extraction, and processing to produce novel microalgaebased bio products and also to provide some information about different commercially available algae products and their utility. Keywords Biofuel · Compounds · Lipid · Microalgae · Renewable energy

Abbreviations BGA EDX EF EPA

Blue-green algae Energy dispersive X-ray Electrolytic flotation Eicosapentaenoic acid

S. Dash · S. Parida · B. Sahoo · B. Rath (*) Department of Biotechnology, Maharaja Sriram Chandra Bhanja Deo University, Sriram Chandra Vihar, Takatpur, Baripada, Odisha, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 P. Verma (ed.), Micro-algae: Next-generation Feedstock for Biorefineries, Clean Energy Production Technologies, https://doi.org/10.1007/978-981-19-0680-0_2

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DHA GHG PBRs PUFAs

2.1

docosahexaenoic acid Greenhouse Gases Photobioreactors Polyunsaturated fatty acids

Introduction

Currently, the world depends mainly on petroleum as a source of fuel. The increasing energy demand has led to a price spike of petroleum oil coupled with the increasing emission of greenhouse gases (GHG). A recent study indicates that by 2020 there will be an alarming risk of fossil fuel crisis (Leggett and Ball 2012; Kumar et al. 2020) which thus compels to increase global interest for biofuel production to reduce GHG emissions and will reduce dependence on fossil fuels. Use of wheat, corn, sugarcane, sugar beets or molasses as feedstock for biofuel production has many limitations because of limited land area and nutrient content (Chisti 2008; Hoekman 2009; Duer and Ovre 2010; Subhadra 2010; Goswami et al. 2020a). The use of some non-food crops such as Bouteloua dactyloides and Jatropha curcas (Sujatha et al. 2008; Robins 2010) for biofuel production has also been examined, but these may still have some constraints. Recent advancements in biofuel feedstock have been focusing on fast-growing microalgae (Subhadra 2010; Chandra et al. 2012; Bhardwaj et al. 2020). Microalgae have been advocated since long time as an efficient renewable biofuel source (Benemann et al. 1977). They constitute an inbuilt system that utilizes solar energy to synthesize value added products such as lipids and starch (Lie et al. 2008; Khan et al. 2009; Mehariya et al. 2021). Microalgae include prokaryotic cyanobacteria and eukaryotic algae and are a diverse group of unicellular, photosynthetic microorganisms. Due to their simple cell structure they are efficient converters of solar energy; grow photo autotrophically and produce significant global atmospheric oxygen by fixing carbon dioxide. They are of great commercial interest as they are capable to produce several useful products including biofuel, bioactive molecules, nutraceuticals, food, and feed supplements. They produce biomass with a vast array of biochemicals using sunlight, CO2, and various other naturally occurring nutrients. Microalgae possess superior properties as compared to plants for biodiesel production as they are non-food sources of biofuel and have simple cell structures and contains a high amount of lipid (up to 80% in dry weight). They can produce approximately 6
1010 tons of biomass per year which equals to 40% of total photosynthesis biomass in the world (Cheng et al. 2013a, 2013b). Many microalgae include a high amount of macromolecules such as triacylglycerol and starch which can be used for bioethanol, biodiesel, and biohydrogen production (Radakovits et al. 2010; Agrawal et al. 2020; Agrawal and Verma 2022). Microalgal species produces not only lipids but also proteins, enzymes, sugar, vitamins, and secondary metabolites such as

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β-carotene which attracts their commercial utility in fuel, food, cosmetics, and pharmaceuticals industries (Koller et al. 2014).

2.2

Biofuel Production Process

2.2.1

Cultivation

Microalgal cultivation is a vital stage in the production of biofuel. Several culture conditions, such as light, temperature, pH, nutrition, medium composition, and agitation, influence microalgal cultivation, rate of photosynthesis, growth pattern, cellular metabolism, and cell composition. The culture system has an impact on growth of microalgae. Microalgae may grow in a variety of metabolic systems, including autotrophic, heterotrophic, and mixotrophic metabolisms (Klein et al. 2018; Goswami et al. 2021a). Microalgae’s autotrophic metabolism is based on photosynthesis, which allows carbon to be assimilated from CO2 using chlorophyll and light energy. Microalgae grow heterotrophically by absorbing low-molecular organic molecules dissolved in culture medium, such as acetic acid, glycerol, carbohydrates (pentoses and hexoses), acetate, and other organic agents. When exposed to light, mixotrophic development occurs in microalgae under dark circumstances instead of absorbing CO2, they shift to the uptake of organic compounds. Cultivation of microalgae is classified as open pond, closed pond and Photobioreactors (PBRs) system.

2.2.1.1

Open Pond System

The oldest and cheapest method of industrial microalgal production is open pond because the required amount of energy and carbon supplements is available from atmosphere (Rawat et al. 2016a, b). However, only a few microalgal strains may be successfully grown because they must maintain a high growth rate under uncontrolled ambient circumstances to avoid microbial contamination that might damage the cultured organism (Cuello et al. 2016). The circular pond is one of the open pond systems in which the culture is mixed and moved by a central pivot circulating agitator (Papazi et al. 2010; Goswami et al. 2021b) and the pond size is designed according to limitation of mixing and by the rotating arm not beyond 10,000 m2 (Faried et al. 2017). The cost factor involved in the construction and operation of circular ponds is significant; therefore, it is not recommendable for commercial scale (Faried et al. 2017). The raceway pond is another type of open pond system that is commonly used for outdoor microalgal production (Fig. 2.1). The raceway is used to build the pond shape, which is rotated by paddle wheels for optimal nutrient availability and aeration (Jorquera et al. 2010). The building materials might be made of concrete or mud composition with a plastic or PVC lining, but this cultivation system is susceptible to climate change and has little

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Fig. 2.1 Raceway and circular pond system of microalgal cultivation

control over culture parameters such as temperature and lighting, resulting in substantial seasonal variation in production (Sandbank et al. 1974). During summer, the rate of water evaporation increases, yet the intensity of daylight stays enough as a result high evaporation rates lower the temperature, maintaining the microalgal growth rate. Despite the fact water delivery to the pond is frequently required in the summer, it is regarded an engineering challenge for balance water levels (Mehmood et al. 2014).

2.2.1.2

Close Pond System

Closed ponds are more efficient in growing microalgae because they have greater control over the production environment than open ponds (Lundquist et al. 2010). Close ponds (intense ponds) are shallow circuits with water depths ranging from 15 cm to 35 cm, and microalgal output in these ponds is nearly ten times that of extensive ponds. Closed pond systems are more expensive than an open pond, but less expensive than photobioreactors (Singh and Gu 2010; Lundquist et al. 2010; Darzins et al. 2010).

2.2.1.3

Photobioreactors

Photobioreactors (PBRs) are superior to conventional microalgal cultivation techniques, i.e., tubular and Flat-plate PBRs, which are a unique form of the high-tech microalgal culturing reactor (Hossain and Mahlia 2019; Prakash et al. 2021). The most common type of photobioreactors is the vertical tubular reactors having high surface to-volume ratios, moderate shear forces and low cost, the ability to use maximum sunlight as a result of high efficiency of CO2 consumption (Sukenik et al. 1988). When compared to tubular PBRs, flat-plate PBRs required less energy for mass transfer which is sufficient to avoid the excess concentration of dissolved oxygen (Sierra et al. 2008). All the photobioreactors designs are based on the idea

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Fig. 2.2 Tubular and flat-plate PBRs of microalgal cultivation

of reducing the light path and therefore increasing the amount of light exposed to each cell (Fig. 2.2).

2.2.2

Harvesting

Harvesting is an important step for the high biomass production of microalgae. Small cell size and colloidal structures of microalgae makes harvesting difficult (Misra et al. 2014; Goswami et al. 2020b). The best harvesting method is determined by the morphological and anatomical features of the microalgal species. Harvesting usually involves filtration, flocculation, flotation, gravity sedimentation, and centrifugation techniques (Shah et al. 2014).

2.2.2.1

Filtration

Filtration is a mechanical process that separates solids from liquids or gases and is carried out by filtrating microalgae under pressure in micro strainers of pore size 2–30 μm. This approach is commonly used to filter small-scale microalgal samples.

2.2.2.2

Flocculation

The most efficient harvesting method is flocculation which needs lower energy and capital cost. In the growth medium, microalgal cell surfaces are negatively charged and repel each other due to electrostatic repulsion. This facilitates microalgal cells in creating a stable system (Brady et al. 2014). The surface charge of the cells is inhibited when flocculants are added to the microalgae growth medium, allowing them to stick to one other and form flocs. Flocculants are typically inorganic salts

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containing metal ions such as Al+3 and Fe+3 (Catie 2009). Generally, microalgal cells can be flocculated at pH 9 or above (Kumar et al. 2013).

2.2.2.3

Flotation

Flotation is a gravity separation process in which air or gas bubbles are attached to solid particles, which are subsequently transported to the liquid surface and aggregate as a float that may be skimmed off. The stability of the suspended particles determines flotation success (Shelef et al. 1984). When it comes to extracting microalgae, flotation is more crucial and informative than sedimentation. Flotation can collect particles with a diameter greater than 500 μm by colliding and adhering to them (Surendhiran and Vijay 2012). Flotation techniques are classified as dissolved air flotation, electrolytic flotation, or dispersed air flotation based on the mechanism of bubble formation (Shelef et al. 1984). Dissolved air flotation (DAF) is also known as the froth flotation technique and creates small droplets of size 10–100 μm (Milledge and Heaven 2013). The higher solubility of air in water as pressure increase causes the formation of fine air bubbles in the DAF. Electrolytic flotation (EF) is another type of flotation procedure that uses electrolysis to create gas bubbles and is successful on a laboratory size for a wide range of microalgae.

2.2.2.4

Centrifugation

The most popular method in harvesting microalgae is centrifugation. Centrifugation is a mechanical separation process that separates solid–liquid combinations using centrifugal force. Although this process does not involve any extra chemicals it requires more electrical energy than flocculation. Various studies have found that centrifugation is the most successful microalgal harvesting technique in terms of recovery (Chen et al. 2015). As centrifugation is energy-dependent and requires a lot of maintenance, it is applicable for a high-value product than for a low-value product (Dassey and Theegala 2013). There are a variety of centrifugation equipment available on the market, including hydro cyclones, tubular centrifuges, solid-bowl decanter centrifuges, nozzle-type centrifuges, and solids-ejecting disc centrifuges of varied sizes and capacities. However, these were used for microalgae separation from the dilute culture medium (Show et al. 2013). Table 2.1 present the benefits and drawbacks of microalgae harvesting techniques (Barros et al. 2015).

2.2.3

Extraction

One of the most significant steps in the generation of biofuel from microalgae is lipid extraction.

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Table 2.1 The benefits and drawbacks of microalgae harvesting techniques (Barros et al. 2015) Methods of harvesting Filtration

Description Separation through membrane filtration or porous mesh Separation is enabled by flocculating algal cells at the bottom Rising gas bubbles move cells upward

Flocculation

Flotation

Centrifugation

Concentrating biomassbased using centrifugal force

Benefits High efficiency of recovery Method is simple and quick, with minimal energy needs Low-cost approach that is applicable to large-scale applications Rapid and high recovery efficiency

Drawbacks The membrane should be cleaned on a regular basis It can be costly and hazardous to microalgae biomass Chemical flocculation is required Expensive and high energy needs

There are several strategies in extracting microalgae to synthesize microalgal lipids. In general, microalgae extraction is separated into two key steps, such as the Chemical process and the Mechanical process (Enamala et al. 2018).

2.2.3.1 2.2.3.1.1

Chemical Method Folch Method

It is the most frequently utilized extraction method, in which cells are homogenized using solvents (Axelsson and Gentili 2014). The mixtures of various organic solvents have been recommended for the selective extraction of lipids from microalgae, for the extraction of lipids from endogenous cells, the most commonly employed combination is chloroform & methanol (2:1 ratio). The homogenized cells were first equilibrated with a 25% volume saline solution, then mixed properly. The resultant mixture was allowed to stand until biphasic separation occurred and the lipids accumulated on the top layer (Bensalem et al. 2018; Folch et al. 1957).

2.2.3.1.2

Bligh and Dyer Method

This approach entails extracting lipids and partitioning with protein precipitation at the interface of two liquid phases at the same time (Bligh and Dyer 1959). It is extremely similar to the Folch technique but differs primarily in the solvent-to-tissue ratio. In this process, the homogenized microalgal cells are extracted with chloroform-methanol (1:2). This method is also used in large-scale and pilot-scale extraction processes with some modification as done by Hajra (1974).

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Mechanical Method Bead Beating

Bead beating is a simple method to break down microalgal cells that involves shaking a closed container packed with beads (Ranjith Kumar et al. 2015). This process contains two categories: vessel shaking (vibrating or shaking containers) and agitation. In the vessel shaking method, the cells are damaged by shaking in the complete container whereas the entire culture gets agitated in the agitation bead method (Onumaegbu et al. 2018). The instrument is covered by cooling jackets throughout this process to decrease heat and preserve the sensitive biomolecules. The main advantage of this approach is the simplicity of its equipment and rapidity, but it is difficult to scale up since considerable cooling is required to minimize heat deterioration of target products (Muhammad et al. 2021).

2.2.3.2.2

Expeller Press

The expeller press is said to be the earliest method of extracting oil from microalgae. The basic concept behind this method is that the oil content of dry or wet biomass is extracted by breaking the cells under high pressure. If too much pressure is applied, both the quality and quantity of lipids will decrease (Radin 1978). A screw-type of apparatus was utilized to crush the dried biomass in this procedure. The microalgal dried biomass was compressed using continuous pressure and friction which compels the oil to flow through the small openings (Radin 1978).

2.2.3.2.3

Microwave Extraction

This method of extraction was first demonstrated by Ganzler et al. (1986). They created an advanced technique in extracting lipids from microalgae. This technique’s application procedure is simpler than those of previous approaches. In this method, a polar material is put in an electric field that oscillates quickly, producing microwaves that generate heat as a result of frictional forces caused by inter and intra molecule movements (Amarni and Kadi 2010). During the heating process, vapour is created within the vessel and disrupting the cell to produce superior extracts, this technique employs extreme heat and high pressure within the vessel.

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Biofuel Products

The algal biomass biofuel conversion process may be divided into three types such as chemical, biochemical, and thermochemical. Chemical conversion is demonstrated by the transesterification of the lipid component to biodiesel. The biochemical conversion entails fermentation the carbohydrate fraction to create bioethanol and anaerobic digestion of the whole biomass to produce biogas. Thermochemical conversion, which includes hydrothermal liquefaction, pyrolysis, and gasification, is the thermal degradation of algal organic components into liquid or gaseous fuels (Amin 2009; Brennan and Owende 2010; Chaturvedi et al. 2020). Although microalgae biofuels have the potential to overcome many of the sustainability difficulties that other biofuels but producing their biomass with available technology is not cost-effective, and existing algal species cannot be cultivated adequately.

2.3.1

Solid Product

2.3.1.1

Charcoal

Microalgal biochar is a biofuel that may be kept underground to act as a carbon sink for future generations (Fig. 2.3). These biofuels were co-combusted with fossil coals during commercialization to create heat for the power generation industries (Hossain et al. 2019; Chaiwong et al. 2013; Ahmed et al. 2018; Goswami et al. 2021c). An investigation demonstrated that biochar derived from Chlamydomonas reinhardtii could generate 24.63–30.11 MJ/kg1 heat (Heilmann et al. 2011). Microalgae were

Fig. 2.3 Production of biochar from microalgae

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co-pyrolyzed and co-combusted with other types of biomass to form biochar. The equation for biochar yield is presented by (Feng et al. 2018): Biochar yield ¼ ¼ Mbiochar/Mbiomass
100. Elements from microalgae biochar were evaluated using a CHNO analyzer and energy dispersive X-ray (EDX). Earlier studies suggest that biochar from microalgal species such as Stigonematales sp., Spirulina sp., and Chlamydomonas reinhardtii grew in wastewater with a low oxygen and carbon content (30–46%) and other inorganic elements (Mg, K, Ca, Al, Si, and N) (Hossain et al. 2019; Torri et al. 2011; Ferreira et al. 2014; Yu et al. 2017).

2.3.2

Liquid Products

2.3.2.1

Ethanol

Bioethanol may be produced by fermenting microalgal polysaccharides at 30–400  C for 24–96 h (Harun et al. 2010; Kumar and Verma 2021). Fermentation is anticipated to create more transesterification since algal cells grown under normal circumstances contain more carbohydrate than lipid. The fermentation process consists of several steps: first, microalgal carbohydrates must be released from the cell by disrupting the cell wall, which is not easily fermentable; second, polysaccharides must be hydrolyzed to fermentable sugars by microorganisms such as Saccharomyces cerevisiae; and finally, a suitable yeast is added to begin fermentation to ethanol (31.1 MJ/kg). The bioethanol must be refined by distillation (an energy-intensive procedure), leaving a solid residue of all other cell components, including lipids and proteins that can be utilized as cow feed or to produce methane (Brennan and Owende 2010). Bioethanol yield might be increased by increasing reaction time, temperature, pre-treatment of algal biomass, and yeast concentration (Amin 2009; Harun et al. 2010). Despite the fact, the majority of microalgae have a low carbohydrate content, their biomass composition can be manipulated by using different cultivational stress conditions (nutrient starvation or high light intensity), and some have increased carbohydrate accumulation to a content of up to 65% of their biomass (Markou et al. 2012). As a result, several microalgal species have been promoted for bioethanol production, either because of their favorable body composition (i.e., high starch content) or by genetic modification.

2.3.2.2

Diesel

Biodiesel is a combination of mono-alkyl esters of long-chain fatty acids generated from a renewable lipid feedstock such as algal lipid, with a heating value of 39–41 kJ/g (Brennan and Owende 2010; Amin 2009). The transesterification reaction converts lipids to biodiesel by exchanging the carbonyl group R1 of esters with the organic group R2 of alcohol. This reaction is catalysed by either a strong acid donating a proton to the carbonyl group (electrophilic), a strong base removing a

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proton from the alcohol (nucleophilic), an enzyme, or a heterogeneous catalyst (Amin 2009). Although the enzymatic method is still more expensive than other catalysts, it does not require neutralization, requires less alcohol, and may convert feedstocks with a high free fatty acid concentration (Brennan and Owende 2010). The reaction temperature, reaction period, alcohol/lipid ratio, catalyst type and dose, mixing intensity, and lipid profile are all factors that influence the total yield of biodiesel (Amin 2009; Cheng et al. 2014). The low lipid content of algal biomass, dewatering and drying of algal biomass, which generally includes more than 99% water, subsequent solvent recovery, following lipid extraction and biodiesel production all are challenges to the practical production of biodiesel from microalgae. As previously stated, cultivating microalgae under stress circumstances might enhance lipid content; yet overall lipid production may even decrease due to a decrease in biomass productivity (Rodolfi et al. 2009). On the other hand, the quality of algal lipids generated under stress circumstances, may be enhanced. Furthermore, dewatering, drying, lipid extraction, and solvent recovery are all time-consuming processes (Brown et al. 2010). Many microalgal species may modify their metabolism in response to small changes in the chemical composition of their growth medium, resulting in high lipid productivity. Mandal and Mallick (2009) revealed that optimizing nitrate, phosphate, and thiosulphate levels in culture might promote lipid accumulation in Scenedesmus obliquus. As a result, the lipid content increased to 43% of its dry weight in N-deficient culture, compared to only 12.7% in the control (Mandal and Mallick 2009).

2.3.3

Gaseous Products

2.3.3.1

Methane

Anaerobic digestion is the anaerobic bacterial conversion of organic material directly into biogas at temperatures ranging from room temperature to 55  C (Zamalloa et al. 2012). It has been commercialized and can be used to treat biomass with a high moisture content (90–99%) (Brennan and Owende 2010). Anaerobic digestion takes place in three stages, hydrolysis, fermentation, and methanogenesis (Brennan and Owende 2010). In theory, the yield of methane from the various components of algal biomass is greatest for lipid, followed by protein, and finally carbohydrate (Sialve et al. 2009). Several parameters influence algal biomass digestion, including biomass biochemical composition, HRT, loading rate, pH, temperature, substrate to inoculums ratio, and co-digestion (Yen and Brune 2007).

2.3.3.2

Hydrogen

Bio-hydrogen has the potential to become a source of energy. Many investigators have explored that microalgae were the commonly available and inexpensive source

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for the production of bio-hydrogen (Chandrasekhar et al. 2015). Hans Graffon and his co-researcher have noticed that the species Chlamydomonas reinhardtii had frequently switched from producing oxygen to hydrogen (Melis and Happe 2001). Further work revealed that the enzyme hydrogenase is responsible for bio-hydrogen production, and when microalgal species are deprived of sulphur, they switch to producing H2 from O2 (Ghirardi et al. 2000). There are just a few organisms known to produce bio-hydrogen (Jung et al. 2011). Figure 2.4 depicts the mechanism of bio-hydrogen generation from microalgae through dark and photo fermentation.

2.4 2.4.1

Valuable Bioproducts Human Healthy Food and Animal Feed

Microalgae and cyanobacteria have been cultivated for food applications for a long time (Chacón-Lee and González-Mariño 2010; Goswami et al. 2021d). The United Nations’ Food and Agriculture Organization has identified a global trend toward increased demand for algal products as food supplements or additives (FAO 2016). Algal research has led to the development of novel food products and dietary supplements due to other nutritional concerns (Borowitzka 2013). Protein with essential amino acids and lipids with fatty acids are abundant in microalgal species (Ward and Singh 2005; Guil-Guerrero et al. 2004). Microalgae can improve human and animal health owing to its unique bioactive components. Microalgae are an essential source of practically all the vitamins required by humans, recognizing the importance of their nutritional potential. Vitamin A, B1, B2, B6, B12, C, E, K, nicotinic acid, biotin, folic acid, and pantothenic acid are among the many vitamins available (Becker 2004). Microalgae-based products are readily available in the form of capsules, tablets, or as nutritional or coloring ingredients to beverages, pasta,

Microalgae

Hydrolysis

C6H12O6+2H2 O

Glycolysis Pyruvate+NADP

2CH3COOH+2CO2+4H2 (Dark Fermentation) 4H2O 8H2+4CO2 (Photo Fermentation)

Fig. 2.4 A biohydrogen production overview from microalgae

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sweets, and gums (Liang et al. 2004). Spirulina and Chlorella species are already accessible as nutritional supplements on the market, with no processing other than drying. They are a good supply of proteins and amino acids that mammals cannot make themselves and should obtain from diet (Wells et al. 2017). Furthermore, numerous antioxidant compounds obtained from microalgae, such as astaxanthin, MAAs, β -carotene, lutein, and other carotenoids have the ability to defend against oxidative stress, which has been linked to a variety of diseases and ageing. Microalgal fatty acids are intriguing not only because of their nutritional value, but also because of their medicinal potential. Polyunsaturated fatty acids (PUFAs) derived from microalgae, such as Omega-3 and Omega-6 fatty acids, are thought to be beneficial in the treatment of asthma, arthritis, and heart disease (Adarme-Vega et al. 2012; Kapoor et al. 2021). Commercially important fatty acids include eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), linoleic acid, gamma-linolenic acid, and arachidonic acid, which are known to lower cholesterol, prevent cardiovascular disease, and cure inflammatory disorders (Bannenberg et al. 2017). To give vitamins, essential fatty acids, and minerals, as well as strengthen the immune and reproductive systems, control weight, and improve appearance, an estimated 30% of annual microalgae production is dedicated to mammals and aquaculture (Forján et al. 2015). In animals such as horses, cows, sheep, lambs, poultry, pigs, and other pets, including microalgae in their feed enhances their immune systems, lipid metabolism, gastrointestinal function, and stress tolerance, as well as enhancing hunger, weight, egg production, and reproductive performance (Kovacs et al. 2013). It can be used to replace up to 10% of the standard proteins in chicken feed. It has been proven that adding microalgal biomass to diet enhances meat and egg quality (Bruneel et al. 2013).

2.4.2

Fertilizers

Chemical fertilizer manufacturing costs are rising these days, necessitating the development of a suitable alternative. Biofertilizers are low-cost products that contain natural substances created by microorganisms such as algae, bacteria, and fungi, which are compatible with soil texture and aid in soil fertility and plant growth. Microalgae contain a variety of substances that aid in germination, leaf or stem growth, flowering, and can even be utilized as a biological pesticide (Bhattacharjee 2016). Many nutrients remain in discarded biomass after oil and carbohydrates have been recovered from microalgae. One possible use for this unused biomass is biofertilizer, which will boost the economic potential of algae for re-use in cultivation following nutrient extraction. Most microalgae and cyanobacteria can fix nitrogen from the atmosphere and can be utilized as biofertilizers (Table. 2.2). As a natural biofertilizer, they play vital function in preserving and enhancing soil fertility for increased rice growth and output (Song et al. 2005). After water, nitrogen is the second most crucial component for plant growth in fields, and fertilizers are used to meet this need (Malik et al. 2001).

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Table 2.2 Various microalgal species used as biofertilizers Microalgal species Chlorella sp. Nostoc sp., Nostoc muscorum Spirulina sp., Spirulina platensis, Chlorella sp., Scenedesmus sp. Chlorella vulgaris Dunaliella salina Haematococcus pluvialis Chroococcidiopsi ssp. and Anabaena sp. Dunaliella salina Calothrix elenkinii

Mode of action Enhanced germination rate of wheat, maize, barley Improved stability and mineral content of saline soil, enhanced seed germination Promoted seed germination in cereals, wheat; increased pepper and beet yields Improved growth in leafy vegetables, wheat, potato, pea, wheat, and tomato Biocidal effect and promoted lettuce yield Promoted seed germination in wheat Increased root growth and secondary metabolite in Beta vulgaris Support shoot length, spike length, lateral root, grain weight in the wheat plant Trigger germination and seed growth in wheat plants Amplify microbial community in roots of rice plants

References Odgerel and Tserendulam (2017), Uysal et al. (2015) Issa et al. (2007), Maqubela et al. (2009), Weiss et al. (2012) Michalak et al. (2016), Dias et al. (2016) Das et al. (2018), Renuka et al. (2017), Wuang et al. (2016), Ronga et al. (2019) Faheed and Fattah (2008) El Arroussi et al. (2016) Rao et al. (2001) Hussain and Hasnain (2011)

El Arroussi et al. (2016) Natarajan et al. (2012)

Various chemical and physical qualities of soil are improved with the help of bluegreen algae (BGA), along with higher yield. Nostoc, Anabaena, and Tolypothrix are blue-green algae that can fix atmospheric nitrogen and are employed as inoculants for growing paddy crops in both upland and lowland environments (Priyadarshani and Rath 2012).

2.4.3

Cosmetics

Microalgae and cyanobacteria include useful components for cosmetic applications, which are rich in antioxidants, pigments, fatty acids, and other bioactive substances, and are regarded an emerging and promising area (Fig. 2.5). Cosmetics are compounds that provide cleansing, healing, anti-sunscreen, and antibacterial properties, as well as anti-aging, anti-cellulite, moisturizing, and beautifying properties (Saraf 2012). Microalgae has been characterized as a sustainable source of bioproducts due to the ability to generate safe products using environmentally acceptable bioprocesses (Michalak and Chojnacka 2014). The secondary metabolites produced by microalgal species during culture make them a great natural source of these

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Fig. 2.5 Microalgal extracts in the cosmetic industry (Rodrigues et al. 2018)

compounds, with significant cosmetologically action (Table. 2.3) (Ariede et al. 2017). Natural polysaccharides, such as ulvans from green algae, fucoidans from brown algae, and carrageenans from red algae, as well as hydrating and moisturizing minerals, antimicrobial substances, carotenoids, antioxidants, and anti-inflammatory compounds are abundant in microalgal species and have been studied as a potent and beneficial biotechnological application in the production of cosmetics (Wang et al. 2015).

2.4.4

Bioplastics

The fight to become fossil-fuel independent emphasises the need to limit the use of petrochemically generated plastics. While global demand for plastic is increasing, exerting pressure on present market conditions, the accumulation of plastic in landfills and marine environments raises serious environmental issues (Rahman and Miller 2017). These issues spark international, national, and local activities, particularly in the packaging business. Bio-based plastics with biodegradable capabilities have been proposed as an alternative to petrochemicals. Bioplastics can be characterized as renewable, meaning they come from natural and renewable sources, petroleum-based yet biodegradable, or a combination of both (Reddy et al. 2013). Using microalgae to make bioplastic would be a vehicle for directly capturing CO2 from the atmosphere and converting it into a polymer. Direct use of the biomass as a bioplastic, blending of the biomass with petroleum plastics, transitional processing in biorefineries, and genetic engineering procedures to create strains that produce

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Table 2.3 Microalgae and cyanobacterial applications in cosmetics (Ariede et al. 2017) Microalgae and cyanobacteria Arthrospira and Chlorella Ascophyllum nodosum, Chlorella vulgaris, Alaria esculenta, Chondrus crispus, Mastocarpus stellatus, Spirulina platensis, Dunaliella salina Chlorogloeopsis sp., Isochrisis, Nannochloropsis, Fucus vesiculosus, Nostoc sp. Porphyra, Spirulina sp. and Chlorella sp. Thraustochytrium, Aurantiochytrium and Schizochytrium Monodus sp., Thalassiosira sp., Chaeloceros sp., and Chlorococcum sp. Coccoid and Filamentous Phaeodactylum tricornutum Chlamydocapsa sp. Nannochloropsis oculata Monodus sp., Thalassiosira sp., Chaeloceros sp. and Chlorococcum sp.

Commercial applications Skin and, hair care products and sunscreen lotions Anti-aging factors

Prevent aging, wrinkles formation and skin sagging Moisturizers for skin, face and body Skin perfection with non-toxic, non-irritating, and non-sensitizing compounds Anti-aging products that intensify collagen stimulus Skin photo-aging Skin elasticity and firmness Products for skin and hair protection Skin whitening Hair loss

bioplastics are some of the methods for converting microalgae to bioplastics (Rahman and Miller 2017). Spirulina platensis, Chlorella vulgaris, Nannochloropsis spp., Botryococcus braunii, and other microalgae and cyanobacteria have all been used to make bioplastics (Zeller et al. 2013; Shi et al. 2012; Torres et al. 2015). Bioplastics are not yet cost-competitive with petroleumbased alternatives. Biorefineries or the simultaneous manufacturing of many product lines are offered as other production models that could cut costs and improve economic feasibility (Anthony et al. 2013; Trivedi et al. 2015).

2.4.5

Fine Chemicals

Over the last decade, the amount of microalgal biomass used to make fine compounds has increased dramatically. Microalgae have been studied to produce vitamins and vitamin precursors, including as L-ascorbic acid (vitamin C), riboflavin, and α-tocopherol, for use in food and cosmetic applications, as well as mariculture (Brown and Farmer 1994; Brown and Miller 1992). Running et al. reported commercially effective heterotrophic ascorbic acid synthesis by Chlorella (Running et al. 1994). Carotenoids, euglenoids, and red microalgae, such as β-carotene from halophilic Dunaliella and astaxanthin from Haematococcus and other chlorophytes, are also targets for commercialization (Saini et al. 2021). β-carotene (pro-vitamin A) is extracted on a commercial scale from mass-cultured Dunaliella for incorporation

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into human dietary supplements (Borowitzka and Borowitzka 1988). The pink color of cultured salmonid fishes and other seafood is due to astaxanthin; however, it is not yet financially competitive with synthetic goods in the aquaculture business. Diatoms and golden-brown microalgae have been studied as possible commercial sources of the desired fatty acids. Microalgae-derived eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) are commercially available. Microalgae have been studied as sources of polysaccharides, lipids, oils, and hydrocarbons, and they have been used to make high-value research biochemicals such as phycobilin’s for fluorescent cell labelling (Glazer 1994), stable isotopically labelled fatty acids, proteins, and other molecules, and deuterated lubricants (Kyle et al. 1989). Spirulina’s phycocyanin, a blue phycobilin, is used to color food and cosmetics. Lutein, a carotenoid and phycocyanin derivative found primarily in microalgae, is gaining popularity as a rich natural source of antioxidants and a food colorant with potential applications in human food and feed. Pharmaceutical (antioxidant, antiinflammatory, anticancer, neuroprotective, and hepatoprotective agents), cosmetic (natural dyes and fluorescent agents), and pharmaceutical (antioxidant, antiinflammatory, anticancer, neuroprotective, and hepatoprotective agents) industries all use phycobiliproteins.

2.5

Conclusion

In the time scale of civilization, it was observed that microalgae and cyanobacteria are cultivated and exploited to obtain biologically active metabolites. Several species of microalgae display a large variety of bioactive compounds such as fatty acids, lipids, carbohydrates, antioxidants, antifreeze proteins, and even antibiotics. They are potent source of biofuels, food ingredients, and bioactive products. Microalgae adapted to extreme environments which intends to produce a secondary metabolite having bioprospecting applications. There is a huge potential for setting up nutraceutical and pharmaceutical industries using microalgae biomass by large scale cultivation and subsequent exploitation in the production of bioactive substances. Despite a series of works on the use of microalgae as feedstocks, chemicals and natural products, the extraction and purification processes being applied, needs thorough investigation. Microalgae are promising sources of biofuels, high-value molecules, and various bioactive metabolites for digging out new drugs and several other potential applications. This review has highlighted on microalgae as a promising source of structurally diverse and biologically active compounds reflecting their multivalent utilities in various industries. Nevertheless, further investigations are needed on elucidating the structural complexity of secondary metabolites of microalgae to focus their specific utility and to extend future research in this area which is a very promising prospective for human welfare. Conflict of Interest The authors have no conflict of interest to declare.

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Chapter 3

Overview on Advanced Microalgae-Based Sustainable Biofuel Generation and Its Life Cycle Assessment M. Iniyakumar, V. Venkat Ramanan, A. Ramalakshmi, R. Bobita, J. Tharunkumar, K. Jothibasu, and S. Rakesh

Abstract Microalgae are increasingly considered as preferential candidates for bioethanol and biodiesel production owing to their multifaceted benefits such as simpler growth requirements, ability to produce bioethanol and biodiesel in higher titers and potential in scale up. In this chapter, different bioethanol and biodiesel production routes of microalgae are discussed in each fuel, their cultivation conditions are discussed in detail. Biochemistry of bioethanol and biodiesel production by microalgae is also discussed. One of the major constraints in biofuel technology is the cost of production, which can be reduced by production of multiple allied products (food, fuels, chemicals) through bio-refinery approach. In this chapter, products such as vitamins, amino acids, carotenoids, polyunsaturated fatty acids producing microalgae and their mechanism are discussed. Finally, this chapter also deals with life cycle assessment of biofuel production by microalgae. Keywords Microalgae · Biodiesel · Bioethanol · Biorefinery

M. Iniyakumar Agricultural Microbiology, Amrita School of Agricultural Sciences, Amrita Vishwa Vidyapeetham, Coimbatore, Tamil Nadu, India V. V. Ramanan Department of Environmental Studies, SOITS, Indira Gandhi National Open University, New Delhi, India A. Ramalakshmi Department of Agricultural Microbiology, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, India R. Bobita · J. Tharunkumar · S. Rakesh (*) Biofuel Research Laboratory, Department of Microbiology, Central University of Tamil Nadu, Thiruvarur, Tamil Nadu, India e-mail: [email protected] K. Jothibasu Department of Microbiology, Karpagam Academy of Higher Education, Coimbatore, Tamil Nadu, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 P. Verma (ed.), Micro-algae: Next-generation Feedstock for Biorefineries, Clean Energy Production Technologies, https://doi.org/10.1007/978-981-19-0680-0_3

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Abbreviations ACC BOD COD DLUC GHGs LCA LCB MLDP RuBisCo SCW

3.1

Acetyl-CoA-carboxylase Biological oxygen demand Chemical oxygen demand Direct land-use change impacts Greenhouse gas Life Cycle Assessment Lignocellulosic biomass Major lipid droplet protein Ribulose-1,5-bisphosphate carboxylase/oxygenase Subcritical water

Introduction

The ever-increasing global population and continuous dependence on fossil fuels increased urbanization, and industrialization poses a major threat to energy security and environmental concerns to both developed and developing nations. It has been estimated that 39.4 billion tons of CO2 would be emitted at the end of this year due to fossil fuels (https://www.globalcarbonproject.org/carbonbudget). More than 190 countries have agreed to reduce their greenhouse gas (GHGs) emissions to keep the global mean temperature below 2  C. To achieve this ambitious goal, the countries CO2 emissions on average should be declined by 1.4 billion tons each year. This indicates that the Nations should adopt renewable technologies to mitigate greenhouse gas emissions. One of the major contributors to increased GHGs in the transportation sector, although their contribution has declined in 2019 owing to the pandemic, their emission was the largest contributor to GHGs with an estimate of 7.3 billion metric tons in 2020. To abide by reduced emission promises, reduced dependence on unsustainable and non-renewable fossil fuels which are very close to the point of exhaustion at the current consumption rate, to reduce dependence on environmental concerns, developed countries have already started producing two biofuels, namely, bioethanol and biodiesel which are most promising in meeting all the issues aforementioned and keep the global warming below 2  C. Bioethanol is a liquid fuel initially produced from food resources such as maize, sugarcane, and sweet potato, as a first-generation biofuel, owing to “food vs. fuel” debate the focus on first-generation biofuels especially bioethanol has been shifted to second-generation where biomass from agricultural and forestry residues such as Lignocellulosic biomass (LCB) was extensively used for fuel production. Technologies on LCB to bioethanol have reached the commercial-scale wherein advanced pretreatment technologies have been developed to break down the carbon (cellulose and xylose) efficient catalysis have been commercialized to convert the complex polysaccharides into simple glucose for the yeast to consume and produce

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bioethanol via fermentation. Many advanced fermentations are in place to produce bioethanol commercially (Neto et al. 2018; Kumar et al. 2020). Problems of biomass storage, continuous availability of biomass resources for conversion, an account of GHGs in transportation has opened up ways for third and fourth generation biofuels. Major candidates of these third and fourth-generation biofuels are algae (Demirbas 2010). Algae are photosynthetic microorganisms capable of growing in aquatic ecosystems including wastewaters. There are different types of algae-based on their pigment production they are red algae, brown algae, and green algae (Romera et al. 2007; Bhardwaj et al. 2020; Agrawal et al. 2020). Based on the size they are classified as micro and macroalgae as the name suggests microalgae are microscopic in nature can grow in presence of sunlight with water and CO2. Macroalgae are visible to naked eyes such as seaweed with similar growth conditions of microalgae. Among the two types of algae, microalgae are considered as potential candidates for biofuel production owing to their fastest growth rates and accumulation of carbon, lipids, pigment, food additives in their biomass. It has been estimated that microalgae can transform 10% of solar energy into the biomass of 77 g/m2/day (Khan et al. 2018). Not only these microalgae can have multiple benefits in consideration for biofuel production as they do not require additional land and freshwater to cultivate them, but they are also not edible and do not enter I to the human food chain, they can be grown in higher intensity without depending on season and climate (Brennan and Owende 2010; Goswami et al. 2020). In this chapter, biodiesel and bioethanol production capabilities of algae are discussed. In the past two decades, developed nations have adopted a circular bioeconomy in contrast to the existing linear economy. In the circular economy, many value-added products can be extracted from biomass and the wastes are sustainably used without dumping them into the environment (Muscat et al. 2021). As part of the circular economy of biofuels production by microalgae meets all the aspects. They are sustainable in that too many value-added products can be generated from the biomass of microalgae besides biofuel production. This chapter addresses bioethanol and biodiesel production by microalgae with emphasis on the bio-refinery and circular economy.

3.2

Bioethanol-Based Microalgal Biorefinery

Bioethanol is one of the most commercially produced vehicular fuels produced worldwide. USA and Brazil are the two major bioethanol-producing countries. Global biofuel production has gradually increased from 187 thousand barrels of oil equivalent per day in 2000 to 1.8 million barrels of oil equivalent per day in 2019 (IEA 2019). Such an increase in bioethanol production is due to well-established industrial facilities created by nations around the globe. The microalgae bioethanol production process can be divided into four steps: (1) Nutrient limited cultivation of microalgae with an excess of carbon source for the accumulation of carbohydrates such as glycogen, starch, agar, and cellulose; (2) Lysis of cells for carbohydrate

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extraction, this can be achieved by acidic, solvent, enzymatic extraction; (3) Hydrolysis of extracted carbohydrates by enzymatic methods; (4) Microbial fermentation of hydrolyzed sugars into bioethanol (Khan et al. 2018; Goswami et al. 2021a). To have enhanced algal bioethanol production, several parameters must be considered. The products generated from microalgae-based biorefinery are mentioned in Fig. 3.1.

3.3

Cultivation Conditions of Microalgae for Bioethanol and Biodiesel

Cultivation of microalgae on large scale is the prime factor to achieve higher biomass. Such high biomass intensity can not only generate more bioethanol but also different value-added products. Although microalgae can be grown effectively on large scales, at a commercial scale it needs to undergo many conditions (Zhu 2015; Agrawal and Verma 2022). Any new cultivation technology should increase biomass content for sustainable production of bioethanol. Microalgae require sunlight as an energy source and water, CO2 is converted into carbohydrate-rich biomass. Nitrogen and phosphorous are major nutrients required to produce biomass. Other macro and micronutrients are also needed for the growth of microalgae. To satisfy all the nutrient demands wastewater from municipal, agricultural, and industrial sources serves as a good source for microalgae cultivation (Reyimu and Özçimen 2017; Goswami et al. 2021b). To achieve a higher biomass content cultivation of microalgae under bioreactor is essential. Large-scale cultivation is done in open ponds or high-rate ponds. They offer less input cost but contamination with other microorganisms is the major problem in this type of cultivation. Continuous and batch-type culturing of microalgae also yields higher biomass, heterotrophic and mixotrophic cultivation of microalgae can also be considered effective in biomass production (Narala et al. 2016; Mehariya et al. 2021). In recent years introduction of microalgae in wastewater treatment plants as a tertiary treatment method has had many advantages such as removal of Chemical oxygen Demand (COD), Biological oxygen demand (BOD), N, P, K, and other pollutants and contaminants from wastewater besides producing bioethanol (Abdel-Raouf et al. 2012; Li et al. 2019; Goswami et al. 2021c; Prakash et al. 2021). The intensity of light is another important parameter in deciding biomass production. Each species needs to be optimized for their light intensities it should be noted that higher light intensity would increase the photosynthetic rate to a certain extent but up to a particular saturation point. Beyond that increase in light intensity would damage the cells due to photoinhibition. Not only is this shading effect due to higher light intensity is also a problem to biomass production. Light and dark periods are also important to microalgae production it has been estimated that the 16 h light and 8 h dark periods are considered as suitable for algal growth. Temperature also affects the growth of algae, temperature beyond the optimum would inhibit or stop the activity

3 Overview on Advanced Microalgae-Based Sustainable Biofuel Generation. . .

Fig. 3.1 Products generated from microalgae-based biorefinery

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Table 3.1 Higher titers of bioethanol, biodiesel, and functional biorefinery products from microalgae

Microalgal strain Chlorella sp.

Chlorella vulgaris FSP-E A. platensis NIES-39

Pre-treatment and fermentation conditions/ biorefinery compound producing microalgae Acid hydrolysis and hydrothermal pre-treated slurry with glucoamylase Acid hydrolysis followed by separate hydrolysis and fermentation Enzymatic and calcium chloride addition with shaking

Bioethanol/biodiesel yield/ uses of biorefinery products Bioethanol seven times higher than control (48 g L) Bioethanol yield of 11.7 g L 1 with a theoretical yield of 87.6% Bioethanol yield of 16 g/L and a theoretical yield of 93%

Botryococcus braunii UTEX 572 Nannochloropsis oculata Chlorella protothecoides CCAP 211/8D Stichococcus sp

Lipid production combined with flu gas of 10% showed enhanced lipid productivity In presence of 2% aerated CO2 From the extracts of Jerusalem artichoke higher tiers were achieved Mycosporine-like amino acids (MAA)

B. braunii

Butylated hydroxytoluene (BHT Astaxanthin

Decreased the quantum effaces of UV. The algae can be used for the synthesis of MAA Antioxidant and antiviral activity Antioxidant property

Glutathione

Lowering the heart attack

Dunaliella sp.

Glycerol

Skin Moistening agent

Pavlova sp.

DHA, APA, and EPA-omega 3 fatty acids

Brain and eye development in infants

Hematococcus pluvialis Dunaliella sp.

Lipid productivity 20.65 mg/ L/day Lipid productivity 0.142 g L 1 d 1 Lipid productivity 1881.3–1840.0

References Marika et al. (2019) Ho et al. (2013) Aikawa et al. (2018) Yoo et al. (2010) Chiu et al. (2009) Cheng et al. (2009) Karsten et al. (2007) Babu and Wu (2008) Ping et al. (2007) Li et al. (2004) Hadi et al. (2008) Chu (2012)

of microalgae biomass. Most microalgal species could grow well between 20-30  C. Mixing and aeration of microalgae would significantly increase the biomass concentration, proper mixing enables nutrient exchange, proper light intensities, mixing of nutrients, and avoid settlement of biomass at the bottom. The most preferred pH range of 6–8.7 increase in pH increases the salinity of medium would affect the growth of biomass significantly (Okoro et al. 2019; Goswami et al. 2021d). Table 3.1 showed the products obtained from microalgal biorefinery.

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Disruption of Algal Biomass and Fermentation of Sugars

Disruption of algal biomass to get out the lipids, carbohydrates and other valueadded products comes under pretreatment conditions. The pretreatment step is the most expensive among the bioethanol production steps in microalgae (Mishra et al. 2017). Acid treatment or alkali treatment are the most common methods to disrupt the algal cell. However, physical, chemical, biological, and combinations have been used. Another important parameter in pretreatment is the presence of lignocellulosic components in biomass which may hinder the process. Several key factors are to be addressed if the algal ethanol production needs to be sustainable and profitable. First, the appropriate pretreatment technologies must be standardized to get maximum profit. Microalgae with more cellulose content need to be pretreated more efficiently that needs to be addressed. The cost of pretreatment should be reduced at the same time emission of gases due to the pretreatment process also to be standardized (Stirk et al. 2020). Enzymatic or acid hydrolysis of carbohydrates yields fermentable sugars. The fermenting yeast requires mono sugars to convert into ethanol. Most acids are used to break down complex sugar molecules under higher temperatures. Strong acids such as nitric, sulfuric, hydrochloric acids can rupture the algal cell wall and release the sugars than weak acids. However, severe acid treatment of sugar also releases fermentation inhibitor hydroxymethyl furfural which reduces the yield of monomeric sugar production in saccharification. A combination of mechanical and chemical methods produces considerable yield, enzymatic methods such as amylase, invertase, cellulase are greener to the environment and yield more carbohydrates. Combinational utilization of xylose and glucose, or five and six carbon utilizing fermentable microorganisms needs to develop for efficient conversion of carbohydrates into bioethanol (Arun et al. 2021).

3.5

Biorefinery Biodiesel from Microalgae

In nature, several microalgae are known to accumulate lipids in their biomass up to 75% under stress conditions. High C: N ratio would switch on the oil accumulating pathways in microalgae. In fungi and yeast, the mechanisms of Tri Acyl Glycerol are well established, and the malic enzyme seems to be rate-limiting enzyme to generate NADH and proceed for TAG accumulation (Konur 2021; Chaturvedi et al. 2020). However, in microalgae Chlamydomonas reinhardtii a major lipid droplet protein (MLDP) is associated with droplet formation. Similarly, the TAG yield had a significant shift when starch synthesis was blocked by inactivating ADP glucose phosphorylase activity (Atikij et al. 2019). For biodiesel to be produced it needs to be produced in larger quantities, open ponds and photo-bioreactors are employed to cultivate and produce more biomass. Harvesting of microalgae biomass for extraction of lipid to be converted into biodiesel is an important process and accounts for

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20–30% of total production cost. The small size of 2–20 micrometer and high-water content makes the harvesting process difficult. Finally, the oil is trans esterified using methanol and KOH and used for engine applications without any modifications (Khan et al. 2018).

3.5.1

Oleaginous Microalgae for Biodiesel Production

Microalgae accumulate lipid in carbon-rich and N deficit conditions and environmental conditions such as increased temperature can also accumulate to enhance the lipid content. The process of lipid accumulation varies among microalgae. In general N starvation reduces the enzyme Ribulose-1,5- bisphosphate carboxylase/oxygenase (RuBisCo) activity, this reduction, in turn, diminishes the protein development but excess carbon is channeled into lipid synthesis. N starvation also triggers the enzyme acetyl acetyl-CoA-carboxylase (ACC) then fatty acid production and elongation are initiated which is further converted into Tri acyl glycerol’s in the cytoplasm. Starvation of N is the most widely seen mechanism apart from this P, Iron, Silicon, even salinity stress can induce the lipid accumulation in microalgae. Besides these, the lipid accumulation stage depends on the growth of the microalgae, in many microalgae the stationary phase of the growth seems to be lipid accumulating. Among the auto and heterotrophic growth of microalgae external supply of nutrients (heterotrophic) growth favors more lipids than autotrophic cultures (Li-Beisson et al. 2019).

3.5.2

Biomass Production for Biodiesel

Fuels produced by algae have 10–45% of oxygen and very low levels of Sulphur and other pollutants. Therefore, the fuels produced by microalgae are clean burning and release no emission of pollutants. In addition, 1 kg of algal biomass can fix 1.83 kg of CO2, therefore algae can not only produce biomass but also sequester atmospheric carbon which is an alternative way to mitigate the greenhouse conditions. To produce maximum biomass there are several types of bioreactors available to increase the content. The following are the reactor types to discuss the biomass production capacity of microalgae (Khan et al. 2018).

3.5.2.1

Open Cultivation Reactors

Natural, circular, and inclined ponds are the open pond type reactors where microalgae can be grown in the open system. They can be constructed easily with simple designs and high production can be achieved. Although it has many benefits proper environmental conditions, contamination, mass transfer rate, and mixing are

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difficult to maintain. Mixing of microalgae can be achieved using a rotating arm in the circular reactor. The capacity of the circular ponds cannot exceed 10,000 m2 and commercialization is hindered due to higher arm length and higher energy strength. Raceway ponds have paddle wheel which continuously works to prevent sedimentations. The disadvantages of contamination, single culture inoculation for more days can be achieved in closed photobioreactors. Tubular bioreactors, on the other hand, are made of plastic and ensure good mixing of algae through spargers placed at the bottom of the reactor. Tubular photobioreactors can also be used in horizontal, vertical, and near-horizontal modes (Wang et al. 2018).

3.5.2.2

Harvesting the Biomass

Coagulation and flocculation are the two most widely used processes for harvesting biomass. Ferric chloride addition to biomass with agitation for 20 mins results in better harvesting of the biomass. Poly D glucosamine-based flocculation is also followed for harvesting which involves mixing the chemicals and agitation of biomass for 30 min helps in better results. The combination of the two steps also increases the efficiency of harvesting. Harvested biomass is taken in polybags and sun-dried to remove the moisture later the biomass is oven-dried for further processing. Flotation is another process where the biomass gets attached to small size bubbles enable them for easy harvesting. Dissolved air bubble system, dispersed air flotation electro flotation are the three major methods involved in the flotation of biomass. Flotation requires less energy easy way of harvesting the biomass (Junior et al. 2020).

3.5.2.3

Extraction of Lipid from Microalgae

Once the biomass is harvested many high-value products accumulated in the biomass must be unlocked utilizing cell disruption and the products must be purified. Mechanical extraction is the conventional way to disrupt the cell wall utilizing heat, electric pulse, waves, shear forces, etc. Chemicals are the next major ways to extract the cell wall lipid using polar and non-polar, organic solvents and recently ionic liquids are used to disintegrate the cell wall. Microwave and ultrasonication are physical methods followed for the extraction of compounds from biomass. Trypsinbased enzymatic methods are a green process where harsh chemicals can be avoided and effectively used for disruption of the cell wall. Extracted lipids are transesterified using methanol and KOH for biodiesel production (Menegazzo and Fonseca 2019).

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Bio-Refinery Products from Microalgae

Apart from the production of fuels, several other value-added products can be produced from the algal biomass through biorefinery means. During World War II times protein supplement to all people was a question, just when microalgae were grown in open ponds as protein food supplements. The energy crisis during the 1970s helped the microalgae to proceed for fuel purposes and over the last few decades algae is considered as a potential biomass for biorefinery products. Vitamins and medicinally important polysaccharides are produced by microalgae. Pigments, namely, astaxanthin, zeaxanthin, carotene, etc. can be produced in therapies for tumorigenesis, neuronal disorders, and optical diseases. Essential amino acids content produced by microalgae makes them a suitable candidate for protein production. Sterols produced by Microalgae have a beneficial effect on anti-cancer, anti-inflammatory, and neurological treatments. Polyunsaturated fatty acids such as DHA are produced in enhanced quantities by microalgae which act as food and feed supplements. A rich source of vitamin E can be produced by Haslea ostrearia. High quantities of vitamin E and C can be accumulated by P. cruentum. Antibiotic resistance by pathogens is another problem associated with a communicable disease. Several extracts of Microalgae show a wide range of bioactive natural products that are effective, either in crude or purified form. Green microalga Chlorella inhibited the growth of gram-positive and gram-negative bacteria. Fungistatic and fungicidal compounds have been produced by some microalgae. Okadaic acid and ciguatoxin are effective antifungal agents produced by microalgae (Menegazzo et al. 2020).

3.7

Life Cycle Assessment of Biofuel Generation from Microalgae

Life Cycle Assessment (LCA) is a comprehensive tool to assess the environmental impacts of the production process or products or activity by quantifying the energy and material usage and waste generation (Prasad et al. 2020). LCA enables optimization of the production process, efficient use of feedstocks, identification of challenges and opportunities to upscale the production process (Venkatramanan et al. 2021). The LCA study involves four steps, namely, goal setting, inventory analysis, impact assessment, and interpretation. The goal of the study defines the system boundaries, functional unit, and scope of the study. The second step is inventory analysis in which the input and output data are used to model the product life cycle. The third step is life cycle impact assessment. Life cycle impact analysis specifies the system boundary. The system boundary states the raw material cultivation, conversion processes, and waste management. The LCA approach adopted in bioenergy studies is the cradle-to-grave life cycle approach (Prasad et al. 2020). The fourth step is interpretation. The results of the LCA study are interpreted to conclude the measures that exhibit minimum environmental impact.

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Key Issues in LCA of Biofuel Generation from Microalgae

LCA study of biofuel production from microalgae is complex and challenging. The challenges concerning LCA studies on microalgae arise from the cultivation stage of microalgae and downstream processing steps. Further, the issues concerning functional units, delineating system boundaries, choosing impact categories should be considered appropriate to increase the quality and applicability of LCA results. Studies have shown that biofuel production from microalgae causes environmental impacts. So, there is a need for comprehensive LCA which includes all the stages/ sub-stages in the life cycle of biofuel. The stages include microalgae cultivation, dewatering, transportation of algal biomass, lipid extraction, transportation of biofuel, and final consumption. The sustainability of algae-based biofuel production is dependent on the cultivation system, species of algae, source of nutrients, and location of cultivation (Chia et al. 2018). Collotta et al. (2016) in a comparative LCA study reported that co-location of algae cultivation with other industrial facilities or a wastewater treatment plant results in the reduction of atmospheric emissions and improvement of wastewater effluent discharges. Integrating wastewater treatment and biofuel production is a cost-effective approach for lowering the environmental impact of microalgal fuel production (Xin et al. 2016). For a functional unit of 1 MJ biofuel, the total energy demands are 4.44 MJ with 13% from biomass production, 85% from lipid extraction, and 2% from biodiesel production (Khoo et al. 2011). Therefore, the adoption of the right processes is essential for the sustainable production of biofuel from microalgae.

3.7.1.1

Selection of Microalgal Species and Cultivation Method

The selection of microalgal species to produce biofuel and other value-added products is based on biomass productivity, lipid content, and lipid productivity. The selection of species is important for downstream processing as well (Zhu et al. 2017). Lu et al. (2021) in an LCA study of microalgal oil production from heterotrophic fermentation reported that oil produced by heterotrophic Schizochytrium sp. had lower impacts than autotrophic Chlorella sp. However, oil produced from heterotrophic Chlorella sp. had lower impacts only in eutrophication, acidification, and ecotoxicity. Heterotrophic microalgae due to their high biomass density and lipid content are harvested and processed with fewer environmental impacts. Microalgae are cultivated generally in open ponds, closed photobioreactors, fermenters, or hybrid systems. The open pond/raceway pond cultivation requires less capital, less energy, and less regular maintenance but is vulnerable to contamination (Dickinson et al. 2017). Microalgae cultivation in photobioreactors yields high cell densities and high value bioproducts. Ubando et al. (2019) reported that maximum economic performance and minimum environmental impacts are observed in the case of a flat plate reactor. In comparison, the cultivation of

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microalgae in open ponds is less expensive than photobioreactors (Davis et al. 2011). The net energy ratio (NER) for raceway pond and flat plate photobioreactor was reported to be more than 1 (Jorquera et al. 2010). Photobioreactors are preferred for large-scale biofuel production as they produce a high amount of biomass (Chen et al. 2021). However, an LCA study on a hybrid system that coupled airlift tubular photobioreactors with raceway ponds in a two-stage process reported high biomass growth and lipid accumulation and lower environmental impact (Adesanya et al. 2014). A two-stage cultivation strategy involving the open raceway ponds and photobioreactors for a simultaneous increase in growth rate and lipid content of microalgae is reviewed by Aziz et al. (2020). To ensure the sustained production of microalgae, the cultivation parameters and requirements are optimized. They require carbon, nitrogen, phosphorus for their growth. The quantity and cost of fertilizer nutrients used in microalgal cultivation are prohibitive. Studies have been reported on alternative sources of nutrients such as wastewater and flue gases for microbial growth. The nutritional needs and cultivation parameters are optimized to ensure the sustained productivity of microalgae. Sibi et al. (2016) reviewed enhanced lipid productivity approaches in microalgae and suggested nutrient limitation as to the most often adopted approach for increasing lipid productivity. The life cycle fossil energy ratio of Chlorella vulgaris based biodiesel is improved by growing microalgae under nitrogen-deprived conditions. On the other hand, the life cycle fossil energy ratio of Phaedactylum tricornutum grown under nitrogen-deprived conditions decreases (Jian et al. 2015). Harvesting and subsequent downstream processing account for 20–30% of the total production cost (Uduman et al. 2010). Dewatering and concentration of algal biomass are performed through methods such as flotation, filtration, centrifugation, and flocculation (Ma et al. 2018). The concentration efficiency is high for centrifugation and filtration methods. The transportation of microalgae to the lipid extraction unit and transportation of biofuel to final consumption are inventoried in the LCA study. The dehydration and lipid extraction contribute 21–30% and 39–57% of the total energy requirement, respectively (Dasan et al. 2019). Direct lipid extraction from wet biomass is preferred because it avoids the cost-intensive dehydration step (Yellapu et al. 2018). In the lipid extraction stage, the pre-treatment increases extraction efficiency. There are many cell disruption methods such as high-pressure homogenization, bead milling, enzymatic lysis, and electroporation method (Dickinson et al. 2017). Lipid extraction is a significant step in downstream processing. Passive cell disruption lipid extraction methods such as in-situ transesterification, direct saponification, supercritical fluid extraction, organic solvent extraction, etc. are used to extract lipid from microalgae (Nagappan et al. 2019). The popular lipid extraction methods are organic solvent extraction and supercritical carbon dioxide. The organic solvent extraction method is inexpensive but hazardous and time-consuming. Supercritical carbon dioxide is faster and environmentally friendly but requires high initial capital cost and energy. Emerging technologies such as ultrasound-assisted extraction and microwave-assisted extraction methods aim to increase the extraction of lipid. The lipid is converted to biofuel either through transesterification, microemulsion, or

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pyrolysis. However, transesterification is the most common technique adopted to convert lipid into biodiesel. Direct transesterification that combines lipid extraction and transesterification in one step, produces biodiesel with much lesser organic solvent (Ma et al. 2018). The transesterification process in the presence of Fe2O3 nanocatalyst yielded 86% biodiesel yield (Banerjee et al. 2019). Ponnusamy et al. (2014) in an LCA study on the lipid extraction method reported that subcritical water (SCW) extraction with thermal energy recovery reduces energy consumption by three to five folds when compared to the organic solvent extraction method. Brentner et al. (2011) through a combinatorial LCA study reported a best-case scenario involving flat-panel enclosed photobioreactor and direct transesterification of algal cells with supercritical methanol that yields a cumulative energy demand savings of more than 65 GJ, reduces water consumption by 585 m3, and decrease greenhouse gases emissions by 86% as compared to a base case scenario.

3.7.1.2

Life Cycle Impact Assessment

Life cycle impact assessment involves the selection of impact categories, classification, characterization, normalization, grouping, weighting, and data quality analysis (Venkatramanan et al. 2021). It is essential to choose an appropriate and comprehensive set of impact categories to measure the impacts on the ecosystem, human health, and resources (Prasad et al. 2020). Life cycle impact assessment should sufficiently cover the impact categories and they must agree with the goal and scope of the study. Cherubini and Strømman (2011) classified impact categories into three types of namely energy input-output analysis, global warming, and other life cycle impact categories. The midpoint environmental impact categories such as “global warming,” “resource depletion,” “acidification,” “eutrophication,” “photochemical oxidation,” and “human toxicity” are included in the LCA studies of biodiesel (Collet et al. 2014). However, the common indices used in the LCA study of biodiesel include global warming potential, acidification, eutrophication, and water footprint. Fortier et al. (2017) reported the inclusion of direct land-use change impacts (DLUC) in the algal biofuel LCAs to determine the life cycle climate change impacts of algal biofuels.

3.7.1.3

Uncertainties in LCA Study

Microalgae on account of their rapid growth rate, high productivity, and valuable composition are preferred as a feedstock for the production of biofuels and valueadded products (Chia et al. 2018). In this regard, LCA studies focus on the commercialization of microalgal biofuel production. However, there is a certain degree of uncertainties in the LCA study on account of the complexity of the biofuel system, LCA methods/approach, data insufficiency, impact categories, and reference system (Liska 2015; Prasad et al. 2020). Although uncertainties exist at all steps of biofuel production processes, uncertainty analysis is crucial for microalgal fuel technology

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(Sills et al. 2013). The type of oleaginous microbes, diverse growing conditions and nutritional requirements, different harvesting, lipid extraction, and conversion technologies make the LCA study of biofuels from microalgae complicated (Mittelbach 2015). The uncertainties can be minimized by adhering to the ISO framework, increasing the transparency (Muench and Guenther 2013), accounting for heterogeneity among biomass systems, avoiding assumptions from other bioenergy systems (Muench 2015), and inclusion of different impact categories (Prasad et al. 2020). LCA is a reliable and potential tool for sustainability assessments and provides decision support to policymakers.

3.8

Challenges for Microalgae-Based Biorefinery

Although microalgae are considered a valuable feedstock for biofuel production, there are certain challenges. The foremost challenge for large-scale production is high initial and operation costs (Zhu et al. 2017). The cost of biofuel production from microalgae can be reduced by efficient use of resources, water recycling, and adopting a biorefinery approach. The biorefinery approach enables the production of biofuels and other value-added products which will reduce the cost of biofuels (Zhu 2015; Koyande et al. 2019). The competitiveness of microalgal oil can be increased using renewable technologies as photovoltaics and biogas production (Jez et al. 2017). The second challenge for large-scale microalgal biodiesel production is the huge demand for water and nutrients for microalgae cultivation. The consumption of water is maximum during the cultivation and harvesting stages. Reuse of water after harvesting reduces the water footprint. While the water footprint of a process involving water recycling was 600 kg water/kg-biodiesel, the water footprint of a process without water recycling was 3700 kg water/kg-biodiesel (Yang et al. 2011; Dickinson et al. 2017). The use of wastewater from microalgae cultivation reduces water footprint and nutrient use, as the wastewater is rich in nutrients such as phosphorus and nitrogen. However, the problems associated with the use of wastewater such as microbial contamination, toxic contaminants are a cause of concern. Minimizing the greenhouse gases emissions and climate change impacts through improving the energy balance of the microalgae production system is another challenge. The use of locally available renewable sources to meet the electricity demand of microalgae production, harvesting, and transformation will reduce greenhouse gases emissions (Collet et al. 2014). Therefore, there is a need for concerted research effort towards improving biomass productivity and lipid productivity through metabolic and genetic engineering, increasing the efficiency of cultivation methods, optimizing culture conditions, and developing technologies for lipid extraction and conversion into biofuels. Conflicts of Interest The authors have no conflicts of interest to declare.

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Chapter 4

Microalgae Cell Wall Disruption and Biocomponents Fractionation for Fuel Conversion J. Tharunkumar, K. Jothibasu, M. Iniyakumar, and S. Rakesh

Abstract Major environmental issues of current decades focus on lowering the carbon footprints and global temperature rise. Conversion of microalgae biomass to fuel is a promising platform for carbon-neutral biofuels which would decrease the dependency on petrochemicals. The current review describes a general characteristic of freshwater microalgae cell walls. The conventional techniques used to disrupt cell walls and extraction of intra as well as extracellular bio components consume energy. The conventional cell disruption techniques do not result in uniform disruption efficiency in all algal species due to differences in cell wall thickness. Further, the conventional cell disruption methodology applies energy in water rather than the algal cell. For example, microwaves, sonication, and other physio-chemical methods spend significant energy to heat water. The current chapter focuses on solvent-free green technologies such as enzymatic, cell lysis by bacteria, ultraviolet light, highpressure gases, hot water pretreatment, osmotic shock, milking, and in situ extraction to disrupt cell walls. Further, it also highlights the extraction and fractionation bio components for fuel conversion. Keywords Disruption · Solvent-free · Pretreatment · Biofuels · Bio components

J. Tharunkumar · S. Rakesh (*) Biofuel Research Laboratory, Department of Microbiology, Central University of Tamil Nadu, Thiruvarur, Tamil Nadu, India e-mail: [email protected] K. Jothibasu Department of Microbiology, Karpagam Academy of Higher Education, Coimbatore, Tamil Nadu, India M. Iniyakumar Agricultural Microbiology, Amrita School of Agricultural Sciences, Amrita Vishwa Vidyapeetham, Coimbatore, Tamil Nadu, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 P. Verma (ed.), Micro-algae: Next-generation Feedstock for Biorefineries, Clean Energy Production Technologies, https://doi.org/10.1007/978-981-19-0680-0_4

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Abbreviations (U)HPH ATPS FFAs HC HPH HTL HVED PEF PLE SCF SFE SWE

4.1

Ultra-high-pressure homogenization Aqueous two-phase systems Free fatty acids Hydrodynamic cavitation High-pressure homogenization Hydrothermal liquefaction High-voltage electrical discharges Pulsed electric field Pressurized liquid extraction Supercritical fluid Supercritical fluid extraction Sub-critical water extraction

Introduction

Microalgae are microscopic photosynthetic autotrophs that produce a wide range of high-value metabolites, which has aroused researchers’ interest in building microalgal-based biorefineries. Lipids, carbohydrates, proteins, vitamins, pigments, and phytosterols are naturally accumulated in high concentrations in some microalgal strains, which can be harvested, purified and employed in a variety of feed, chemical and pharmaceutical industries (Wang et al. 2017; Mehariya et al. 2021). The microalgal biomass can be produced in higher quantities with less landmass, and it does not compete with arable land, without compromising food crops. Among the microalgal cell components, lipid has garnered attention in the production of biofuel and is a feasible alternative to plant-based lipid sources such as soybean, jatropha, and rapeseed. Microalgae can be selected to generate an increased amount of lipid for biofuel production depending on the species and optimal growth conditions (Jacob-Lopes et al. 2015; Agrawal and Verma 2022). Microalgal lipids are classified as polar lipids, which make up the microalgal cell membrane, and non-polar lipids, which include free fatty acids (FFAs) and acylglycerols (mono, di, and tri) that serve as the cell’s energy source and are the primary components of biofuel generation (Enamala et al. 2018; Chaturvedi et al. 2020). Microalgal biofuel production has been proposed as a way to achieve sustainable development while also addressing current challenges such as fossil fuel depletion and global level rise in CO2 emissions. Microalgal cells mitigate CO2 emissions in the atmosphere through photosynthetic processes and biofix inorganic carbon, transforming it into high-value organic bioproducts (Bhardwaj et al. 2020; Prakash et al. 2021). Cultivation, harvesting, cell disruption, lipid extraction, strain improvement and transesterification are all processes in the biofuel production process (Jothibasu et al. 2021; Rakesh et al. 2014, 2015). Harvesting and lipid extraction is the most

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time-consuming and energy-intensive of them. Because of the microscopic algae cells, thick cell walls, low biomass growth in the medium for harvesting, and limited contact between the solvent and the intracellular components for lipid extraction, these downstream processing processes are challenging (Uduman et al. 2010; Goswami et al. 2021a). As a result, providing a path for an economically feasible technique concentrating on producing high-value microalgae bioproducts to raise biomass value and improve the microalgae biorefinery’s economy is an uphill task (Laurens et al. 2017; Goswami et al. 2021c). Microalgae are unicellular organisms with a complex cell wall made up of several different molecular components, intra- and intermolecular lipid, cellulose, protein, glycoprotein, and polysaccharide linkages (Yap et al. 2016; Agrawal et al. 2020). The cell wall of certain microalgae has a rigid structure made up of silica frustules or calcium carbonate (Bolton et al. 2016). Mechanical, physiochemical, and biological methods are used to rupture the cell wall structure of microalgae to extract lipids. Although lipids are widely extracted from microalgal biomass using solvent-based techniques, the robust, multi-layered cell walls of microalgal species prevent conventional organic solvents from entering the cell, reducing lipid extraction efficiency (Kim et al. 2016). Downstream procedures such as cell disruption and lipid extraction, which require a lot of energy and cost, are still the prime techno-economic constraints for commercializing microalgal biodiesel production (Günerken et al. 2015). Microalgae are eukaryotic cells with thick cell walls which are, unlike prokaryotic cells, resistant to mechanical and chemical stresses through cell disruption methods. Several attempts have been made to design an efficient and effective way for disrupting cell walls to extract lipids and other vital components. There are two sorts of cell disruption methods: mechanical and non-mechanical. Cell disruption methods have been used on both dry and wet biomass, however, the focus has recently times shifted to the use of wet biomass for lipid extraction, as dry biomass for lipid extraction is not cost-effective (Lee et al. 2017). The current advances in cell wall disruption and biocomponent separation from microalgae for fuel conversion, including their merits and demerits are discussed in this book chapter (Fig. 4.1).

4.2

Mechanical Cell Disruption

A mechanical method of cellular disintegration is often performed by applying mechanical forces that includes bead milling, high-pressure homogenization, hydrodynamic cavitation, or by transferring energy via conventional heat, waves, and electric currents such as steam explosion, hydrothermal liquefaction, freeze-drying, ultrasonication, microwave treatment, pulsed electric field technique (D’hondt et al. 2017; Rakesh et al. 2015). Operational parameters such as intensity, processing duration, reactor design, chemical type and dose, biomass characteristics (dry state/ wet state and concentration), and size have a considerable impact on efficiency (Kim

Fig. 4.1 Various cell wall disruption and biocomponent separation techniques for fuel conversion

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et al. 2016). The following is a summary of recent improvements in the mechanical approach of cell disruption for extracting microalgal intracellular components for biofuel generation (Table 4.1).

4.2.1

Shear-Force Disruption

4.2.1.1

Bead Milling

Bead milling has a long history, dating back to when it was originally used in the cosmetics industry to decrease the particle size of paint or lacquer and grind minerals. Bead milling was effectively applied for the disruption of microbial cells for the downstream processing of intracellular metabolites following its efficiency in the chemical industry (Postma et al. 2015). Bead milling is a complicated operation with a number of variables to consider, including bead diameter, density, filling, agitator speed, and feed rate. In addition, the design of the grinding chamber and the agitator might differ (Phong et al. 2018b). The disintegration of microalgal cells is also influenced by the type and size of beads. Because of their greater specific density, zirconium oxide (ZrO2) beads are considered to be more effective than glass beads at disintegrating cells (Doucha and Lívanskỳ 2008). The study carried out by Montalescot et al. designed the optimal parameters for the bead milling process of cell disruption in two microalgal species Nannochloropsis oculate and Porphyridium cruentum. The results showed that milling with 45% loaded 1.3 mm zirconia beads at an agitator speed of 8 m/s resulted in 90% cell disruption in Porphyridium cruentum, and the specific energy required was 21,010 J/kg, whereas Nannochloropsis oculate required filling ratios of 80 to 85% with 0.6 mm zirconia beads at an agitator speed of 8–10 m/s, and the specific energy required was 81,011 J/kg, which was 40 times higher (Montalescot et al. 2015). The release of biochemicals and biomass from Neochloris oleoabundans cells disrupted by bead milling was studied under nitrogen-repleted and nitrogen-depleted circumstances. The zirconia bead size of 0.4–0.6 mm with mill rotation of 2000 rpm was applied and the results showed that bead milling of nitrogen repleted cells resulted in a 34% (w/w) release of biochemicals on average, while nitrogen depleted cells showed 57%, 59%, 68%, and 56% (w/w) of biomass, proteins, carbohydrates, and lipids respectively with 92%, 57%, and 46% (w/w) of phospholipids, glycolipids, and neutral lipids, respectively (Günerken et al. 2016). Another research of the microalgae Chlorella sorokiniana bead milling disruption kinetics found that glass beads of 0.4 mm size and a 14 m/s impeller velocity were the best conditions for effective cell disruption (Zinkoné et al. 2018).

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Table 4.1 Microalgae cell wall disruption techniques with advantages and disadvantages Pretreatment methods Mechanical Bead milling

Mechanism of action Shear stress and mechanical constriction

Advantages – Solvent-free – Effective for samples with high moisture content – Can be used on algal slurry on a large scale

High pressure homogenization

Cavitation and shear stress

– High efficiency – Does not require dry biomass – Solvent free – Easy and simple

Hydrodynamic cavitation

Cavitation and shock waves

– Low energy requirement – Lower operating cost – Shorter processing time

Ultrasonication

Cavitation, acoustic streaming and liquid shear stress

Microwave

Increase in temperature and molecular energy

– Lower extraction time – Less solvent requirement – Higher penetration of solvents into the cellular compartment – Higher amount of lipid is released – Eco-friendly – Easy to scaleup process – Low operating cost – Dewatering of algal biomass is not required – Shorter extraction time – Less solvent usage – Higher extraction yield

Disadvantages – Low efficiency with rigid cell wall – Vulnerable to lipid degradation – Undesirable products as well as beads removal will necessitate further processes – Energy consumption is high – High cost of maintenance – Rise in temperature leads to degradation of thermolabile compounds – Low efficiency with rigid cell wall – Large amount of fine cell fragments – Requires extra energy and process for solid-liquid separation – Suitable only for cell suspension with low viscosity – High power consumption – Difficulties in scaling up process – Production of reactive hydroxyl radicals – Not applicable to large scale

– Centrifugation or filtration is required to remove solid residue – Protein denaturation, lipid degradation – Not suitable for volatile and non-polar compounds – High energy consumption Formation of free radicals (continued)

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Table 4.1 (continued) Pretreatment methods Pulse electric field

Mechanism of action Electroporation – cell membrane permeabilization and pore formation by electric field induced tension

Steam explosion

High pressure drops and rapidly expanding steam causes explosion and disruption of cell wall

Hydrothermal liquefaction (HTL)

Hydrolysis by high temperature and pressure

Freeze drying

Intracellular water expands and freeze thaw method disrupts cell wall

Solvent-based cell disruption

Disrupt the hydrogen bonding and electrostatic forces

Advantages – Higher extraction of compounds – Less time consumption – No cell debris formation – High energetic efficiency – Easy accessibility for lipid recovery – Low operating cost – Can be applied in algal slurry – Easy to scale up methods – Wet biomass is used – Economically feasible operational process – Highly efficient – Large scale industrial application

– Do not damage intra cellular components – Easy and gentle extraction of fragile compounds like proteins and enzymes – Classic and most reliable for lipid extraction – Easy penetration into the cells – Complete extraction of lipids

Disadvantages – Sensitive to medium conductivity – High maintenance cost – Decomposition of fragile compounds

– Less selectivity – Efficiency depends on species – High energy consumption

– Undesirable compounds such as high N content are observed in microalgae derived biocrude oil – There is a scarcity of research on the impacts of heating rate, starting pressure, and particle size on microalgae HTL – High energy and time consuming – Degradation of lipids Dehydration may occur

– Not applied in industrial scale – Pretreatment methods are needed for effective extraction – Expensive solvents – Highly toxicity – Highly flammable – Chemically reactive (continued)

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Table 4.1 (continued) Pretreatment methods Supercritical fluid extraction (Green technology)

4.2.1.2

Mechanism of action When a fluid’s pressure and temperature exceed their critical values, the fluid enters the supercritical zone

Advantages – Increased lipid yields due to supercritical fluids’ higher penetration power – Reduced extraction time due to the fluids’ liquid–gas properties – Production of solvent-free crude lipids – Inherent safety of an industrial-scale SFE system – Process suitability for a continuous-flow, industrial-scale SFE unit

Disadvantages – Intensive energy needs

High-Pressure Homogenization

The homogenization method is widely used for the microbial cell disruption of microalgae, bacteria, and yeast. In high-pressure homogenizer the homogenizer’s valve seat designs influence cell disruption efficiency (Coccaro et al. 2018; Ekpeni et al. 2015). Shear forces of highly pressured fluids on the fixed valve surface and hydrodynamic cavitation caused by shear stress created by pressure drop are commonly used to achieve high disruption efficiency (Shene et al. 2016). The processing fluid of wet biomass is pressured in intensifiers and fed through a homogenization chamber in high-pressure homogenization, which causes energy accumulation in the fluid by the pressure and released into the channel through an orifice valve, where the fluid’s velocity rises to 200–400 m/s, causing mechanical stress such as shear and elongational forces, turbulence, and cavitation, that causes microbial cell wall disruption (Donsì et al. 2013; Halim et al. 2013). The study was conducted to examine the release of ionic components, carbohydrates, proteins, and pigments, the biomass of the microalgae Parachlorella kessleri was treated to high-voltage electrical discharges (HVED) and high-pressure homogenization (HPH). The results revealed that HVED at 40 kV/cm for 4 ms is effective for extracting ionic cell components and carbohydrates, whereas HPH at 1500 bar, 1–10 passes is effective for releasing total intracellular components, including significant amounts of proteins, whose release was 6.8 times higher than HVED (Zhang et al. 2019). The effects of high-pressure homogenization (HPH) at 300, 600, and 900 bar on the microstructural and rheological features of four microalgal suspensions, namely, Arthospira platensis, Isochrysis sp., Nannochloropsis sp., and Tetraselmis sp., were

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examined. The disintegration of microalgal cells caused by HPH treatment changed the cell shape, particle size, and rheological characteristics. The most prominent effect of HPH treatment was shown in A. platensis, whereas Nannochloropsis sp. showed a minimal effect due to its robust cell walls (Magpusao et al. 2021). The effect of ultra-high-pressure homogenization (U)HPH on microalgae Nannochloropsis sp. cells was examined in research. The findings revealed that applying an ultra-high pressure of 250 MPa reduced the number of homogenizations passes necessary to achieve a certain degree of cell rupture. However, the process generates heat, which causes heat-labile components to degrade, thus it is also regarded as a high-energy consuming disruption technique (Bernaerts et al. 2019).

4.2.1.3

Hydrodynamic Cavitation

The formation of cavities inside homogenous liquid media by the development of microbubbles is known as hydrodynamic cavitation (HC). When the pressure falls below the vapor pressure, microbubbles occur, which collapse as the pressure rises over the vapor pressure. The collapse of the microbubbles causes shock waves, which temporarily raise pressure (100–5000 atm) and temperature (500–15,000 K), disrupting the microalgal cells mechanically (Lee and Han 2015). A reactor for hydrodynamic cavitation is called a hydrocavitator. According to a study, the Fenton reaction-mediated cell destruction when accompanied by hydrodynamic cavitation (HC) is highly effective for direct lipid extraction from wet microalgal biomass. Lipid and chlorophyll extraction efficiency increased from 43.1% to 77.4% and 22.4% to 97.2%, respectively (Lee and Han 2021). The effects of Hydrodynamic cavitation-assisted NaOH pretreatment on methane generation from the cyanobacterium Desertifilum tharense were examined. Process parameters such as cavitation number (Cυ: 0.3–0.7), NaOH concentration (0–4%), solid content (1.5%), reaction duration (4 h), and reaction temperature (30  C) were integrated in the experimental design to show the parameter-specific impact of HC pretreatment. Pretreatment raised soluble COD by 2–35.3%, whereas methane production increased from 241.5 to 290.6 mLCH4 gVS1. When compared to the raw D. tharense, application of HC with a low Cυ of 0.3 increased methane generation by 20.3% (Fardinpoor et al. 2021).

4.3 4.3.1

Electric and Wave Energy-Based Cell Disruption Ultrasonication

The most applicable and efficient method for lipid extraction from oleaginous microbial biomass was found to be ultrasonication. Cavitation and shock-wave propagation are two phenomena that occur when ultrasound is applied to cells. Cavitation applies pressure to cells in the form of microbubbles, causing cell walls

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and membranes to be disrupted (Gerde et al. 2012). Ultrasonication has been used to disrupt microalgal cells in a variety of solvents like chloroform-methanol, n-hexane, diethyl ether (Araujo et al. 2013). A study on the cell disruption effectiveness of ultrasonication and ultra-homogenization on the microalgae Chlorella sp. found that applying high-frequency vibrations (sonication) for 60 min resulted in a maximum cell disruption efficiency of 52.6%. However, ultra-homogenization was less effective in disrupting of algal cells, but efficiency improved as rotation speed increased. Within 60 min, disruption efficiency reached 48.5% at a rotation speed of 24,000 rpm (Skorupskaite et al. 2019). Another study found that employing an alkaline and ultrasonication combined approach enhanced cell disruption efficiency. The ultrasonication-assisted alkaline treatment at 37 kHz for 1200 s had the combined advantage of cell disruption provided by ultrasonic cavitation as well as solvent solubility power, and this combination treatment produced the highest protein yield from microalgae Chlorella sorokiniana and Chlorella vulgaris (Phong et al. 2018a). The impact of ultrasonication on the cell rupture of Nannochloropsis sp., a marine microalga, was investigated. Ultrasonication (20 kHz) at 3.8 W/mL for up to 5 min was used on the concentrated viscous wet-biomass (12–25% solids content), resulting in a considerable increase in lipid yield from 11% to almost 70% in just 5 min when compared to extraction without cell rupture (Yao et al. 2018).

4.3.2

Microwave

Microwave treatment, in which electromagnetic waves are applied to a suspension of cells in an organic solvent, is another widely used approach for lipid extraction from oleaginous microbes. It is a non-contact approach that heats all of the target reactants at the same time, with a short processing time, high disruption efficiency, and low energy usage as compared to conventional heating (Budarin et al. 2015). The study examined the extraction of lipids from Botryococcus braunii and Chlorella vulgaris microalgae cells following ultrasonic and microwave treatments. Microwave pretreatment was shown to be more effective than ultrasonic pretreatment. The greatest lipid output from B. braunii was 56.42% using microwave radiation and 39.61% using ultrasonication, while it was 41.31% and 35.28% for C. vulgaris, respectively. For C. vulgaris, the methane yield from residual extracted biomass processed with microwaves ranged from 148 to 185 NmL CH4/g VS, whereas for B. braunii, the yield ranged from 128 to 142 NmL CH4/g VS (Rokicka et al. 2021). The extraction of lipids from high-moisture Scenedesmus quadricauda microalgae biomass disrupted by microwave was investigated. Microwave pre-treatment improves the disruption of microalgae cells, resulting in high lipid yields of up to 49% at a power of 600 W, an 8-min heating period, and a 3.5-h extraction time. Scenedesmus quadricauda sp. total lipid was extracted using an organic solvent combination of methanol and sulphuric acid (Onumaegbu et al. 2019). Another study demonstrated that microwave radiation pre-treat effectively disrupts wet

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microalgal biomass Chlorella pyrenoidosa for lipid extraction. The results revealed that when using the optimal conditions of 5 min of microwave irradiation duration, 700 W output power, and 2 g/L microalgal biomass concentration, the lipid extraction was enhanced by 55.32% as compared to the untreated condition (Rana and Prajapati 2021).

4.3.3

Pulse Electric Field (PEF) Cell Disruption

PEF (pulsed electric field) is a technique that employs an external electric field to produce a critical electrical potential across the cell wall, resulting in cell disruption. The intensity of the applied electric field and pulses affects membrane porosity (Günerken et al. 2015). The study investigated the effect of primary pulsed electric field (PEF) on Arhtrospira platensis microalgae cell damage and the extractability of important substances such water-soluble proteins (WSP), C-phycocyanin (C-PC), and carbohydrates (CH). In contrast to untreated samples, the use of PEF treatment monopolar pulses, 20 kV/cm and 100 kJ/kgsusp at room temperature considerably increased the extraction yield of WSP 17.4%, CH 10.1%, and C-PC 2.1%. Furthermore, irrespective of pulse polarity, the synergistic effect of combined PEF at temperature 35  C treatment resulted in the extraction of up to 37.4% (w/w) total WSP, 73.8% total CH, and 73.7% total C-PC. Surprisingly, the PEF treatment allowed for a greater purity C-phycocyanin extract than the high-pressure homogenization procedure (Carullo et al. 2020). Although PEF treatment is relatively simple, has high energy efficiency, and relatively fast, it showed a low impact on the disruption of Chlorella sorokiniana cells, mainly due to the rigid cell wall (Leonhardt et al. 2020). Microalgae were treated with a high-voltage pulsed electric field (PEF) to breach the cell membrane of Chlorella prior to lipid extraction. The lipid extraction yield was discovered to be dependent on the electric field intensity and specific energy input, and the Chlorella cell disintegration rate. The extraction yield of lipids was enhanced by up to 167% after PEF treatment. However, if the voltage is too high, the quality of the extracted biodiesel will decrease (Zhang et al. 2021).

4.4 4.4.1

Heat-Based Disruption Steam Explosion

Pretreating lignocellulosic materials for bioenergy production sometimes involves using a high-pressure steam-explosion method. In most cases, raw material is exposed to steam at 180–240  C (1.03–3.45 MPa) for many minutes before being depressurized to ambient pressure, resulting in an explosion and significant cell-wall disruption (Nurra et al. 2014). The microalga Nannochloropsis gaditana was

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subjected to acid catalyzed steam explosion treatment in a study. The n-hexane extraction capacity of untreated microalgae was very low, yielding just 2.1% lipid. The quantity of lipid extracted using n-hexane, on the other hand, was considerably increased to 17.6% of lipid yield as a result of using the 5% sulphuric acid in the steam explosion method. The steam explosion is a revolutionary cell disruption and pre-fractionation technique that results in complete cell disruption (Lorente et al. 2017). The steam explosion has the potential to be used as a pre-fractionation treatment as well as a broad-spectrum microalgae cell disruption. Acid-catalyzed steam explosion enabled effective cell disintegration as well as carbohydrate hydrolysis and partial protein hydrolysis, and it was especially efficient when microalgal strains had recalcitrant cell walls. In a microalgae biorefinery, the sequence of steam explosion, dynamic membrane filtration, and solvent extraction as downstream unit operations cost reduction (Lorente et al. 2018).

4.4.2

Hydrothermal Liquefaction

Under increased temperatures and pressures of 280–370  C and 10–25 MPa, hydrothermal liquefaction (HTL) allows wet biomass to be converted directly to bio-crude. Water facilitates the hydrolysis of macromolecules and the polymerization of small molecules into the bigger molecules that make up biocrude oil under these harsh conditions (Chiaramonti et al. 2017; Goswami et al. 2021b). Recent research used the flash heating hydrothermal liquefaction process to extract bio crude from the microalgae Nannochloropsis sp. The greatest bio-crude yield was 31.4%, with a low nitrogen level of 3.3%, according to the findings. Lipids in microalgae may be successfully transformed into bio-crude at a low reaction temperature of 200  C, while heteroatom compounds playing a significant role in improving bio-crude production at a higher temperature of 275  C (Tang et al. 2020). Phaeodactylum tricornutum is a promising biomass source for producing biocrude by hydrothermal liquefaction (HTL). The ideal conditions for the development of this species at the lab scale include adjusting the photoperiod (18:6 h light:dark), providing specific CO2 injection, and varying the initial nitrate content (11.8 mM). Because of the reduced lipid and high ash concentrations in this biomass, the biocrudes from a 90 L cultivated microalga yielded lower yields than those produced from biomass of 1 L cultivated at the lab scale by HTL at 320  C. The heteroatom concentrations in the biocrudes, on the other hand, were unaffected by the culture scaling-up. After a posthydrotreatment stage, a larger-scale culture is proposed to produce a biocrude that may be utilized as biofuel (Megía-Hervás et al. 2020). HTL’s generation of biocrude with low nitrogen concentration was the subject of another investigation. At a laboratory scale, the microalgae Scenedesmus obliquus was studied to see how variations in nitrogen levels affected the culture medium, cell development, and nitrogen concentration in the final biomass. Cell development is harmed by the stress caused by limiting the nitrogen supply and increasing its availability. The amount of nitrogen in the final biomass and the biocrude generated from this biomass reduces

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as the nitrogen concentration in the culture medium reduces, lowering the costs of refining procedures to create diesel-type fuel and necessitating lower catalyst ratios and less extreme conditions. To balance the decreased nitrogen content in microalgae and the greater biocrude production yields, the relevance of creating the combined culture and HTL conditions was established (Miranda et al. 2021).

4.4.3

Freeze Drying

Various dehydration technologies, such as freeze-drying, spray drying, solar drying, air drying, and flash drying, have been commercialized for the preservation of microalgal biomass, particularly in the food and feed sectors. The freeze-drying approach can harm cells because intracellular water expands while freezing, and the freeze-thaw cycle is commonly employed to recover protein from cells (Show et al. 2015). The extraction of antioxidant and plant bio stimulating chemicals from Chlorella sp., Chlorella vulgaris, and Scenedesmus acutus was studied using freeze-drying combination with sonication or ball milling. When compared to freeze-dried biomass using 50% methanol as a solvent, both cell disruption procedures yielded larger extract yields from the biomass. Chlorella extracts have stronger antioxidant activity than freeze-dried extracts. In Chlorella sp. extracts, the freeze-drying coupled sonication method produced the highest antioxidant activity. For C. vulgaris extracts, freeze-drying combined with ball milling produced the highest results. In S. acutus extracts, both cell disruption techniques lowered antioxidant activity. The active chemicals were released using water extracts after the membrane was damaged by freeze-drying (Stirk et al. 2020). Scenedesmus obliquus, a microalga, was dried using several methods in another study (freezing, freeze-drying, oven drying). Due to the presence of reactive water in the biomass, the biomass that was just frozen had the lowest FAME content. Frozen biomass, on the other hand, had a larger percentage of saturated and monounsaturated fatty acids, whereas freeze-drying or oven drying increased the proportion of polyunsaturated fatty acids. If the biomass is to be used to make biodiesel, the ideal approach would be to simply freeze it (de Oliveira et al. 2020).

4.5

Solvent-Based Cell Disruption

Extracting lipids and carotenoids from microalgal biomass that has been concentrated by harvesting and dewatering is generally performed using solvent-based procedures. The two most prevalent biomass types for lipid extraction methods are dry (using dried biomass) and wet (using wet biomass) (Xu et al. 2011). The time and cost of producing biodiesel by transesterification are significantly increased when the biomass is subjected to a dry process. As a result, wet biomass has been chosen to reduce production costs and process constraints. However, if microalgal

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biomass includes a high-water content, lipid extraction efficiency will be reduced. In these situations, higher alcohol to total lipid concentration is necessary, which may not be eco-friendly. As a result, solvent extraction of lipids from wet microalgal biomass is challenging without proper pretreatment (Ehimen et al. 2010; Yousuf et al. 2017). The solvents used in lipid extraction should have high specificity for intracellular lipids, be insoluble in water, have a high penetration potential through the cell matrix, have a low boiling point, be volatile, inexpensive, and safe. The solvent extraction approach is based on the breakdown of the hydrogen bond between polar lipids and the hydrophobic interaction between non-polar or neutral lipids (Pragya et al. 2013; Sati et al. 2019). For complete recovery of intracellular lipids, a combination of polar and nonpolar solvents with a specific mixing ratio has been utilized in the solvent extraction process. Non-polar solvent molecules penetrate cell walls, enter the cytoplasm, and form complex structures with neutral lipids found in the cytoplasm as globules. However, a small percentage of neutral lipids stay inside the cell binding with polar lipids that are hydrogen-bonded to the cell membrane protein. As a result, the polar solvent is used to disperse these lipid fractions from the cell membrane. Finally, the lipids are extracted using solvent distillation or evaporation (Dong et al. 2016). Isopropanol, dichloromethane, acetone, chloroform, methanol, n-hexane, and other organic solvents are employed for lipid extraction. The solvents used and the amounts in which they are utilized impact the effectiveness of solvent extraction. Although many organic solvents and mixes have been employed in the past, the 1:2 v/v (Bligh – Dyer technique) and 2:1 v/v (Folch method) chloroform: methanol ratio has been reported as a quick, effective, and quantifiable combination for microalgal lipid extraction (Bligh and Dyer 1959; Folch et al. 1957; Zhu et al. 2017). Hexane or a combination of hexane and alcohol has been reported as a less hazardous alternative to the chloroform: methanol mixture and has been used in various analyses of the Soxhlet extraction procedure. The practical applicability of traditional solvent extraction is limited due to the large volume of solvents required, as well as the fact that it is time-consuming, environmentally unfriendly, and inefficient (Arathi et al. 2020; Dong et al. 2016). Soxhlet extraction is a traditional technique for extracting lipids and carotenoids on a scientific scale. By refilling the biomass with a new solvent, it employs a continuous organic solvent to prevent solvent evaporation and condensation cycles in lipid extraction. Soxhlet extraction requires a large volume of organic solvents such as n-hexane, ether, chloroform, and methanol and takes a long time to complete, but it yields a greater yield and has no effect on the bioactivity of the molecules extracted (Imbimbo et al. 2020). Green solvents, such as bio-based solvents, ionic liquids, and supercritical fluids, are being explored for use in microalgal lipid extraction to overcome the issues posed by organic solvents (Kumar et al. 2017). Compressed fluid extraction technologies such as sub-critical water extraction (SWE), pressurized liquid extraction (PLE), and supercritical fluid extraction (SFE) are alternatives to the traditional method of lipid extraction. The solvents used in PLE and SWE are kept at high enough temperatures and pressures to keep the fluids in a liquid condition. The boiling point and pressure of the SFE solvents are kept above critical levels to

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considerably increase solvent penetration into the cell matrix (Herrero et al. 2013). Supercritical fluid (SCF) extraction might be a viable technology for improving molecule recovery, with potential applications in a variety of industries. As compared to standard extraction procedures, SCF extraction allows for a higher extraction rate in less time. Several solvents, such as ethanol, hexane, methanol, pentane, butane, nitrous oxide, sulphur hexafluoride, and fluorinated hydrocarbons, can be utilized in supercritical fluid extraction due to their crucial properties (Uddin et al. 2015). However, CO2 is a desirable solvent for SCF-based extraction methods due to its thermodynamics and heat transport capabilities. Because of its lower extraction temperature and pressure, CO2 is a superior solvent for extracting thermolabile molecules without degradation or change in chemical composition. CO2 is also non-flammable, non-toxic, and cost-effective, and it can be recycled, unlike organic solvents. The solvent in SCF-CO2 extraction remains in the gas phase under atmospheric conditions, a significant amount of CO2 is removed from extracts, resulting in a solvent-free extract (Goto et al. 2015; Herrero et al. 2006). The chemical nature of CO2 under supercritical conditions, which is comparable to that of lipophilic solvents, is the prime constraint of SCF extraction. The use of a suitable polar co-solvent to alter SCF-CO2 polarity and increase the solubility of bioactive molecules is an excellent technique for improving extraction efficiency (Molino et al. 2020). In a recent study subcritical dimethyl ether, a green solvent was used to extract lipids from microalgae Tomopterus obliquus (Wang et al. 2021).

4.6

Merits and Demerits of Different Cell Disruption Techniques

Various cell-wall disruption procedures, such as mechanical – bead milling, highpressure homogenization, hydrodynamic cavitation, ultrasonication, microwave treatment, pulse electronic field treatment, and chemical-based techniques like organic solvents, ionic liquid, osmotic shock, surfactant, as well as a biological method like using hydrolytic enzymes and algicidal treatment have been tested with different microalgae to improve microalgal biocomponent extraction efficiency for fuel generation (Park et al. 2015; Rakesh et al. 2020, 2015). Mechanical methods of cell disruption have the merits of high product recovery rates with strong controllability and scalability while being energy intensive. The demerits of these disruptive techniques are high cost of operation, high energy consumption, low-efficiency rate, and also, they are not ideal for extraction of volatile intracellular metabolites like proteins, pigments, etc., Because such compounds are damaged by high pressure, shear stress, or heat, they can only be employed in the lipid extraction process. To minimize energy consumption and enhance disruption efficiency, they are sometimes coupled with non-mechanical disruption techniques or pretreatments (Bharte and Desai 2021; Show et al. 2015). Shear force methods of cell disruption (bead milling, high pressure homogenization) have the advantages of being solvent-free,

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simple, effective with short contact times, and suitable for high moisture content microalgal biomass, while the disadvantages include low efficiency with rigid microalgal cell membranes and high maintenance costs. The advantages of wave and electric energy-based methods include low solvent consumption, greater solvent penetration into cellular compartments, shorter processing times, and nontoxicity; however, the disadvantages include high power consumption, the need for filtration or centrifugation to remove solid residue, incompatibility for non-polar or volatile compounds, and degradation of fragile intracellular compounds (proteins) (Patel et al. 2018). The advantages of a solvent-based extraction process include the use of inexpensive solvents, the ability to recycle solvents, the easiness of the extraction process, fast separation, highly purified extracts, low toxicity, and the lack of a separation process. However, the disadvantages include high residual water content in microalgal biomass, which lowers the quality of the extract, the use of large amounts of solvents, and high equipment and operational costs (Karim et al. 2020). Furthermore, the biology and cell wall feature of each microalgal species influence the choice of optimal cell disruption and lipid extraction procedures. Research on cost- and energy-efficient extraction of important algal components must be based on a better knowledge of cell physiology and cell wall structure (Zuorro et al. 2019). So far, there has been relatively limited significant research on particular cell-wall structures and extraction techniques.

4.7

Fractionation of Carbohydrates and Lipids

Microalgae carbohydrates are a potential biocomponent that is widely utilized in the food industry as thickeners, emulsifiers, gelling agents, and stabilizers, as well as in the biorefinery sector to generate a range of value-added products (Gifuni et al. 2017). Using the phenol-sulphuric acid technique and the Lowry method, the carbohydrate and protein content of microalgae is measured (Dubois et al. 1956; Lowry et al. 1951). Pectin, agar, and alginate in the outer layer of the cell wall, cellulose (with no lignin) and hemicellulose in the inner layer of the cell wall, and starch granules inside the cell are the significant amount of carbohydrate in microalgal biomass (Velazquez-Lucio et al. 2018). Microalgae have different types of carbohydrates depending on the species; for example, rhodophytes (red algae) contain Floridian starch, whereas chlorophytes (green algae) contain amylopectinlike polysaccharides. In the cell walls of microalgae, lignin is absent, and certain species lack cellulose and hemicellulose (Markou et al. 2012). Traditional carbohydrate extraction techniques from microalgal biomass include alkali extraction, alcohol extraction, potassium chloride (KCl) extraction, and drum drying (Hernandez-Carmona et al. 2013). To transform polysaccharides isolated from microalgae into fermentable sugars, researchers utilized a hydrolysis procedure using strong acidic (H2SO4 and H3PO4) or alkaline conditions (NaOH and ammonium) or an enzymatic technique. Organic solvents are often used to extract hydrophilic components such as carbohydrates/protein and hydrophobic components such

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as lipids/pigments from disrupted microalgal cells. This method, however, has the drawback of generating protein denaturation (Hernández et al. 2015). As a result, it is preferable to identify unique alternatives to traditional methods. Aqueous two-phase systems (ATPS) have been created as a more biocompatible and effective liquid-liquid extraction strategy for fractionation and purification of bio components without harming biomolecules from microalgal biomass (Ruiz et al. 2020). Algal biomass fractionation of microalgae Scenedesmus acutus was carried out as part of an algal biorefinery. By decarboxylation/decarbonylation with an affordable Ni-Cu catalyst, the purified lipids were effectively converted to diesel fuel range hydrocarbons. The aqueous stream produced by biomass fractionation was found to be primarily made up of simple sugars (Pace et al. 2020). Marine macroalgae have the potential to be a long-term source of food, minerals, chemicals, and energy. The fractionation of the biomass to co-produce different products is vital in the successful valorization of the marine biomass in seaweed biorefinery (Blue economy). A total of 90.31% of the initial biomass was recovered using the green extraction method, with the fractions from the initial dry weight biomass being 45.42% salts, 3.67% starch, 3.81% lipids, 13.88% ulvan, 14.83% proteins, and 8.70% cellulose (Prabhu et al. 2020). For the fractionation of microalgal components (proteins, pigments, lipids, and carbohydrates) of Neochloris oleoabundans, the team devised a liquidliquid extraction procedure. The partitioning behavior of microalgal pigments and proteins in aqueous two-phase systems (ATPS) made up of the polymer polypropylene glycol 400 (PPG 400) and cholinium dihydrogen phosphate (Ch DHp) reveal that selective pigment fractionation in the PPG 400-rich phase and protein fractionation in the Ch DHp-rich phase. A multiproduct strategy was shown to be able to fractionate free glucose and proteins in the ionic liquid-rich phase, pigments in the polymer-rich phase, and starch and lipids at the interface (Suarez Ruiz et al. 2020).

4.8

Conclusion

Microalgae is recognized as one of the most promising feedstocks for the production of biofuels and other high-value goods. The extraction of intracellular lipids, on the other hand, is the most important stage in algae-based biodiesel manufacturing, since it can alter product quality, quantity, and cost efficiency. However, to build an inexpensive and sustainable extraction process, the pretreatment technique must be energy efficient, environmentally safe, and scalable for industrial use. As a result, research efforts should focus on gaining a better knowledge of the interaction between pretreatment processes and lipid extraction problems to design a feasible and scalable approach for extracting lipids from wet biomass. More study and review are needed to develop an efficient, practical, and scalable microalgal lipid extraction technology for biodiesel production. To successfully pursue sustainable development and address the challenging difficulties of how to fulfil present requirements without jeopardizing future generations’ ability to meet their needs, it is vital to

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encourage efficient bio-manufacturing and make a shift towards a bio-sustainable society. Conflicts of Interest The authors have no conflicts of interest to declare.

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Chapter 5

Recent Advances in Hydrothermal Liquefaction of Microalgae Mahadevan Vaishnavi, Kannappan Panchamoorthy Gopinath, and Praveen Kumar Ghodke

Abstract Hydrothermal liquefaction (HTL) of biomass is evolving as an effective technology for competent valorization and efficient energy densification of diverse biomass feedstocks, extending from lignocelluloses to algae and organic wastes. Microalgae have been identified as a promising alternative resource for biofuel production as it accumulates various bio-components such as lipids, carbohydrates, and proteins. Substantial research into HTL has led to a fundamental understanding of the different process conditions, reaction patterns, behavior, and response of the algal biomass. This chapter summarizes the basic principles of HTL, products, and their properties. The current developments in catalytic HTL and up-gradation techniques of bio-oil are discussed. To facilitate a more holistic view, a comparison of various thermochemical techniques and the merits and demerits of all HTL associated processes are also outlined. Keywords Hydrothermal liquefaction · Microalgae · Thermochemical · Bio-oil

Abbreviations AE CH4 CNT CO CV FCC

Antagonistic effect Methane Carbon nanotube Carbon monoxide Calorific value Fluid Catalytic Cracking

M. Vaishnavi · K. P. Gopinath Department of Chemical Engineering, SSN College of Engineering, Kalavakkam, Tamil Nadu, India P. K. Ghodke (*) Department of Chemical Engineering, National Institute of Technology Calicut, Kozhikode, Kerala, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 P. Verma (ed.), Micro-algae: Next-generation Feedstock for Biorefineries, Clean Energy Production Technologies, https://doi.org/10.1007/978-981-19-0680-0_5

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HHV HLB HTC HTL HTW HV Kg KW MJ NOx OHE PAC Ref. SCWG SCWU SE Sox TCC Wt% ZSM

5.1

Higher Heating Value Hydrophilic and lipophilic balance Hydrothermal Carbonization Hydrothermal liquefaction Hydrothermal Water Heating Value; Oxygen Kilogram Kilo watt Mega Joules Nitrogen oxide One step Hydrogenation Esterification Polycyclic Aromatic Hydrocarbons Reference Super Critical Water Gasification Super Critical Water Upgradation Synergetic effect Sulphur oxide Thermo Chemical Conversion Weight percentage Zeolite Socony Mobil

Introduction

The continuing use of fossil fuels, environmental pollution, and global warming in recent years are the driving forces of the accelerated energy crisis and its subsequent rapid global energy demand. This imposes the need for new energy sources, raising the interest in renewable energy production technologies. In the worldwide search for a new alternative energy source, in conjunction with the sustainable development of our society, biomass is considered to be one of the most promising candidates not only because of its renewability but also of its carbon neutral and high productivity characteristics (Dimitriadis and Bezergianni 2017; Kumar and Verma 2021). In the contemporary renewable energy source paradigms such as solar, wind, and hydro, biomass plays an exceptional role because, as the only carbon-based renewable energy source, it is uniquely suited and more amenable for the direct production of liquid fuels and chemicals (Williams et al. 2018; Bhardwaj et al. 2020). This fact positively impacts the economic feasibility and sustainability of biomass-based processes. Furthermore, a liquid thus obtained from biomass could undergo further processing to be converted into drop-in fuels or valuable chemicals. Depending on the biomass used for the conversion process, the biofuel thus generated can be distinguished as first, second, and third-generation biofuels. Firstgeneration biofuels are obtained from edible biomass such as food crops, sugarcane, and vegetable oils, thus leading to several economical and ethical issues. To

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overcome the above issues, Lignocellulosic-based biomass – wood waste, agricultural waste, forestry, sorted domestic waste, etc., were employed to obtain the second-generation biofuels. Further, to avoid the competition of food and soil use, third-generation biofuels, obtained from aquatic life such as macroalgae and microalgae, are being extensively investigated. The exploitation of these organisms for biofuel production has various advantages—they have a high ability of CO2 fixation, depending upon their growth conditions; ability to grow throughout the year on non-arable land, utilizing less water than land plants or even sewage; their biochemical composition can be made to desire by altering the conditions of their growth environment (Shahi et al. 2020; Agrawal et al. 2020; Goswami et al. 2020a). These organisms contain higher lipid concentrations that are very much desirable for biofuel production, although the roadmap for biomass conversion to platform chemicals, which can be substituted for petroleum precursors, is strenuous and complex (Matayeva et al. 2019).

5.2

Background

Biomass can be converted to various useful forms of energy and chemicals by several different processes – biochemical and thermochemical. Various factors such as the type and quantity of biomass feedstock available, the end product requirements, environmental issues, and process economics, influence the selection of the conversion process (Balagurumurthy et al. 2015). The most common biochemical processes include fermentation and anaerobic digestion, which occur at low temperatures in a diluted water phase, resulting in bioethanol and biogas, respectively. In comparison with biochemical processes, Thermochemical Conversion (TCC) technologies – controlled heating or oxidation of biomass, are new fuel production pathways that possess a distinctive time advantage over the former, as TCCs occur in a matter of few hours, minutes, or seconds even (Singh et al. 2016). TCC technologies are categorized based on their associated oxidation environment, particle size, and heating rate, ranging from heating biomass in an oxygen-free environment (endothermic) to full exothermic oxidation of biomass (Tanger et al. 2013). A range of technologies including Gasification, Hydrothermal Liquefaction, Pyrolysis, Direct combustion, and Supercritical fluid extraction falls under the classification of TCC technology (Biller and Ross 2011; Heidenreich and Foscolo 2015; Goswami et al. 2021a). Direct combustion of biomass, the dominant bioenergy pathway, is widely applied to produce electricity by complete combustion and oxidation of carbon and hydrogen-rich biomass to carbon-di-oxide and water. However, the detailed complex kinetics and the incomplete reaction of biomass combustion resulted in the release of intermediates such as CH4, CO, particulate matter, NOx, SOx, etc. (Tanger et al. 2013). Supercritical fluid extraction employs a supercritical fluid at higher pressures for the separation of two components and has chief applications in petroleum recovery, de-waxing, coal processing, selective extraction of oils, fragrances, and many others (Sapkale et al. 2010).

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Gasification, an exothermic partial oxidation process, is considered to be a relatively flexible process, in regard to the type of biomass that can be converted, and it renders a valuable gaseous product, syngas or producer gas consisting majorly of carbon monoxide, hydrogen, and methane (Dimitriadis and Bezergianni 2017). The gas is further upgraded to liquid fuels or chemical feedstock utilizing an auxiliary process such as biological fermentation or catalytic Fischer-Tropsch process (Wang et al. 2015). The gasification process also results in high molecular volatiles such as polycyclic aromatic hydrocarbons (PACs) that condense into tars posing both a fouling challenge as well as a potential persistent environmental threat (Milne et al. 1998; Tanger et al. 2013). Pyrolysis and Hydro-Thermal Liquefaction (HTL) are two comparable technologies that involve the thermal decomposition of biomass in the absence of oxygen into highly heterogeneous bio-based solid, liquid and gaseous intermediates. The liquid product obtained is called bio-oil or bio-crude (pyrolysis oil—in case of pyrolysis) is characterized by high oxygen content and alkalinity and is further upgraded into fuels. The solid product, known as biochar, is rich in carbon and can be used as fuel, solid amendment (Tanger et al. 2013), or catalyst (SundarRajan et al. 2020). The complex reaction pathways, optimization of the operational parameters, and product up-gradation via catalytic and thermal processes to produce infrastructure compatible liquid transportation fuels are current research areas in the engineering front (Demirbas 2007). There are significant differences in the operating conditions and the characteristics of the product obtained by the two technologies for biomass conversion. Table 5.1 compares both the technologies on operating conditions and the characteristics of bio-oil obtained. Certain advantages such as lower operating temperature, ability to use feedstock with high moisture content as such without pretreatment, capacity to produce bio-oils with higher HHV, lower oxygen content, higher throughputs, and high energy and separation efficiency (Elliott et al. 2013), put HTL on the pedestal as a more viable and beneficial biomass conversion process.

5.2.1

Fundamentals of HTL

Hydrothermal Liquefaction (HTL), also known as hydrous pyrolysis (Jazrawi 2014; Goswami et al. 2020b), is thermochemical conversion of biomass in a hightemperature pressurized environment (Yang and Yang 2019), in the presence of hot compressed water at subcritical conditions, mainly into a liquid product known as bio-crude or bio-oil (Dimitriadis and Bezergianni 2017). HTL operates effectively in the 250–450
C temperature range and pressures approximately 100–350 bar (Castello et al. 2018). In Hydrothermal Water (HTW) practices, water remains in a liquid or relatively dense state, and this near and supercritical water has been successfully employed for liquefaction, gasification, and further up-gradation processes. HTL occurs in a confined range just above the vapor-liquid coexistence curve and at pressures,

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Table 5.1 Comparison of HTL and pyrolysis for biomass conversion (Dimitriadis and Bezergianni 2017; Matayeva et al. 2019) Parameter Treatment conditions Moisture content Pressure (MPa) Temperature (
C) Catalyst Bio-oil characteristics Heating value (HHV) Insoluble solids (%) Water content (%) C (%) H (%) O (%) N (%) S (%) Density (g/ml) Viscosity (mPa s) Upgrade

Pyrolysis

Liquefaction

40% 5–20 200–400 Sometimes

Low (~17–22 MJ/kg) 0.5–0.75 High 15–23 39–56 7.5–8 12–51 cellulose > hemicellulose > lignin and solid residue yield follows the trend lignin > cellulose > hemicellulose > protein > lipid (Yang et al. 2018).

5.2.4

Elemental Composition of Biomass

The microalgal biomass as any others consists of elemental carbon (C), nitrogen (N), sulphur (S), and oxygen (O). Carbon (C) being the important constituent of the biomass, contributes majorly to the overall heating value (HV) of the fuel. Table 5.2 gives the elemental composition of a few algal species. The amount of lignin, cellulose, and hemicellulose contribute to the carbon content of the biomass (Gollakota et al. 2018). Hydrogen (H) content of the biomass, constituted from the chemical structures of carbohydrates and phenolic polymers also contribute significantly to the overall HV of the fuel (Goswami and Kreith 2007). Nitrogen (N) and Sulphur (S) are important nutrients for biomass growth and are seen in the structures of amino acids, proteins, and enzymes. The presence of these elements significantly hinders the energy extraction process and the overall HV of the fuel (Karampinis et al. 2012; Hirel et al. 2011). Oxygen (O) is a vital element after C, both in terms of the chemical composition of biomass and its impact on the overall HV of the biofuel obtained by any processing technique (Elliott 2011).

5.2.5

Microalgae As Hydrothermal Liquefaction Feedstock

Algae, being considered as one of the most promising and attractive energy sources, has many advantages when compared to other biomass feedstock – their ability to survive in various strenuous environments, low agricultural land competition, rapid growth rates, high yield per acre, and high versatility of value-added by-products (Dimitriadis and Bezergianni 2017). On the other side, a high amount of thermal energy is required for the drying of algae as they are wet biomass feedstock, making them inappropriate and unsuitable for refinery processes. However, drying is an

Scenedesmus sp.

Nannochloropsis sp.

Botryococcos braunii

Chlorella vulgaris

Species Spirulina

Biomass Bio-oil Biomass Bio-oil Biomass Bio-oil Biomass Bio-oil Biomass Bio-oil

C (%) 48.1 68.9 52.6 70.7 77.04 80.49 47.6 76.1 52.1 72.6

H (%) 6.97 8.9 7.1 8.6 12.4 13.42 7.5 10.3 7.4 9.0

N (%) 10.14 6.5 8.2 5.9 1.23 0 6.9 4.5 8.8 6.5

O (%) 34.13 14.9 32.2 14.8 9.86 6.01 25.1 8.8 31.1 10.5

S (%) 0.66 0.86 0.5 – 0.18 0.07 0.5 0.5 0.46 1.35

Ash (%) 12.66 – 7.0 – 0.7 – 12.4 – 6.0 –

Moisture (%) 5.2 – 5.9 – 1.64 0.30 – – – –

Table 5.2 Elemental composition of algal biomass and bio-oil obtained from HTL of the species HHV – 33.2 23.2 35.1 35.58 39.04 23.1 38 22.6 35.5

Yield (%) – 32.6 – 54.2 – – – – – –

Vardon et al. (2012)

Barreiro et al. (2015)

Liu et al. (2012)

Biller and Ross (2011)

References Vardon et al. (2011)

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obsolete pretreatment for HTL, as these systems can effectively handle wet biomasses, and the production of liquid fuel precursors such as bio-oil gives HTL the competitive advantage as an algae conversion pathway with low energy consumption when compared to other processes (Biller and Ross 2011; Shuping et al. 2010; Toor et al. 2011). In addition to the above-mentioned benefits, the process water of HTL is rich in nutrients (N and P), elements (Fe, Ca, Mg, K), minerals, and polar organic compounds (Biller et al. 2012; Ross et al. 2010). Concurrently, the residual solid algal biomass is a carbon deposit preserved of its nutritional value and can be further used as a catalyst for further gasification processes and animal feed additives, respectively (Arun et al. 2020).

5.2.6

HTL Process Flow

The HTL route conversion of biomass to bio-liquid is carried out in subcritical water at moderate temperatures and high pressures. The phase separation of the product streams occurs spontaneously under operating conditions resulting in liquid bio-crude as the primary product along with a gaseous stream of CO2, and small traces of aqueous and solid-phase byproducts (Biller and Ross 2016; Rowbotham et al. 2012). These products have the unique feature of high energy content and thus enhanced energy recovery options and opportunities in comparison to other conversion processes. Table 5.3 lists a few liquid phase products obtained from HTL of microalgae. The water used for the HTL process can be recirculated into the system, thus reducing the water requirement for the process and also enhancing the bio-oil yield. The aqueous phase generated during the process can be used for anaerobic treatment or the Catalytic Hydrothermal Gasification process for the production of syngas (Rajagopal et al. 2021). The solid phase obtained has direct applications as fertilizer/biochar and as the catalyst for the gasification process (Arun et al. 2018, 2020; SundarRajan et al. 2020). As aforementioned, in addition to exclusion of the pretreatment step (drying) and using the wet algal biomass per se, the nutrients (in the aqueous phase) used for algal growth can be recycled back into cultivation by means of hydrotreatment, and the CO2 released from the HTL process can also be utilised in the photosynthesis process for the growth of next batch of algae, making HTL the forerunner among other algal-bioenergy production processes (Gollakota et al. 2018). It also has to be noted that, the size of microalgal biomass is essentially quite small, increasing complexities in the pumping of slurries into the reactor systems.

5.2.7

Yield Calculations

Apart from the HTL operation by itself, the separation of the desired bio-oil from various other products obtained holds great significance. Among the three types of

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Table 5.3 Liquid phase products of HTL from different species of microalgae Biomass feedstock Nannochloropsis sp. Chlorella vulgaris & Spirulina

Products Monoaromatics Phenols

Nannochloropsis sp.

Benzene/Toluene/ Styrene Cholesterol/ Cholestene Vitamin E Fatty acids Myristic acid

Dunaliella tertiolecta

Palmitic acid

Nannochloropsis sp.

Steric acid/oleic acid Tetradecanoic acid Octanoic acid Alkane/Alkene Hexadecane Heptadecane

S. platensis Dunaliella tertiolecta

Chlorella vulgaris, Spirulina, Nannochloropsis sp., Porphyridium cruentum Microcystis viridis Chlorella vulgaris, Spirulina, Nannochloropsis sp., Porphyridium cruentum Dunaliella tertiolecta

Phytane/Phytene

Laminaria sp.

Cycloalkane

Nannochloropsis sp.,

Polyaromatic compounds Naphthalene Quinoline Anthracene Phenanthrene Pyrene and Carboloze Nitrogen compounds Pyrrols/ Pyrrolidines Pyridines

Nannochloropsis sp.,

Amides

Dunaliella tertiolecta

Amines and Nitriles Oxygenated compounds Esters

Microcystis viridis S. platensis Microcystis viridis Enteromorpha prolifera

Chlorella sp., Nannochloropsis sp., Porphyridium sp.

Spirulina

References Duan and Savage (2011a, b) Ross et al. (2010) Jena and Das (2011) Zou et al. (2010) Brown et al. (2010) Shuping et al. (2010) Valdez et al. (2011) Biller and Ross (2011) Yang et al. (2004) Biller and Ross (2011) Shuping et al. (2010) Anastasakis and Ross (2015)

Yang et al. (2004) Jena et al. (2012) Yang et al. (2004) Zhou et al. (2010)

Biller and Ross (2011) Valdez et al. (2011) Valdez et al. (2011) Zou et al. (2010)

Jena et al. (2011) (continued)

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Table 5.3 (continued) Biomass feedstock Laminaria sp.

Products Aldehydes

Chlorella vulgaris Dunaliella salina S. platensis

Ketones Alcohols Acetic acid

S. platensis

Furans

References Anastasakis and Ross (2015) Ross et al. (2010) Yang et al. (2011) Jena and Das (2011) Jena et al. (2012)

products (solid, liquid, and gas) obtained by the HTL process, the gaseous mixture commonly consisting of nitrogen, hydrogen, methane, carbon monoxide, and carbon dioxide, is easily separated during the depressurization of the reactor by a gas product system collector (Fang et al. 2008). The solid and liquid products when filtered result in a filtrate consisting of water and water-soluble organics and inorganics. The characteristics of the filtrate depend mainly on the biomass feedstock, catalyst, solvent used for the HTL process, and the leftover solids. The residual deposits from the reactor walls are obtained by washing with a solvent (commonly acetone) and are mixed with the previously obtained filtrate. This mixture on filtration yields an organic fraction containing excess acetone, which is further removed utilizing evaporation. The physical parameters such as lignin content of feedstock, catalysts, and solvents used, and operational parameters such as residence time, temperature, and solvent to feed ratio, have a major influence on the efficiency of the HTL method (Sanghi and Singh 2012) and thus the calculation of yield is pertinent to sufficiently characterize, evaluate and in further stages optimize the whole process. There exist various ways to present the yield of the HTL process – (i) HTL yield is defined only in terms of the desired product fraction (Minowa et al. 1998) HTL yield ðwt%Þ ¼

organic mass in each product  100 organic mass in feedstock

ð5:1Þ

(ii) Yield percentage is defined in terms of the weight of all HTL products (solid, liquid, gas) (Zhang et al. 2008) gas mass  100 feedstock mass residue mass Residue yield% ¼  100 feedstock mass Gas yield% ¼

ð5:2Þ ð5:3Þ

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Liquid yield% ¼ 1 

 gas mass residue mass   100 feedstock mass feedstock mass

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ð5:4Þ

(iii) Yield percentage is defined taking into consideration all liquefied products, i.e., the aqueous fraction (AQ), the acetone soluble fraction (AS), and the residue fraction (RS) (Ye et al. 2014) residue mass Overall HTL yield% ¼ 100   100 feedstock mass
 AQ mass  100 AQ% ¼ AQ mass þ AS mass

  AQ mass AS% ¼ 100   100 AQ mass þ AS mass

ð5:5Þ ð5:6Þ ð5:7Þ

(iv) Yield percentage defined in terms of weight of bio-oil (SundarRajan et al. 2020; Arun et al. 2019), i.e., the organic phase obtained after filtration and vacuum evaporation of the solvent Bio oil yield ðwt%Þ ¼

mass of bio  oil ðgÞ  100 mass of raw algae ðgÞ

ð5:8Þ

Typically, the oil yields from various biomass (wood, waste, and algae) liquefaction can range from 10 to 60 wt. % and the yield from algae is also dispersed throughout this range. On the other hand, the yields obtained from algae, although dispersed throughout the range, 40% of them render a minimum of 45% yield (Dimitriadis and Bezergianni 2017).

5.3

Catalytic HTL

To commercialize and make the manufacture of biofuels competitive, it is necessary to reduce the costs associated with their production by addressing several challenges linked to the low energy density of biomass feedstock, low efficiency of conversion processes, subsequent low energy-intensive up-gradation method, and a reliable distribution system to reach user interface (Balan 2014). Therefore, the development and usage of catalysts to improve bio-oil yields, quality, and in-situ up-gradation become imperative. Also, an increase in operational parameters such as pressure, temperature, and residence time improves the production of bio-oil and its quality by enhancing its Higher Heating Value (HHV), impacts physicochemically by boosting its flow properties and reducing the undesirable hetero- atomic contents such as O, S, and N, but has a major negative impact on the process economy (Ou et al. 2015; Yu et al. 2011; Peterson et al. 2008). Usage of catalysts in biomass liquefaction reduces

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Table 5.4 Effect of catalyst on bio-oil yield and its properties Biomass feedstock Nannocloropsis sp.

Dunaliella tertiolecta Spirulina platensis

Chlorella sp.

Microcystis viridis

Catalyst Pd/C CoMo/γ-Al2O3 Ru/C Ni/TiO2 Na2CO3

Effect of catalyst Increase in yield by 20% Increase in yield by 15% Increase in yield by 13% Increased acids and hydrocarbons in bio-oil Increased oil yields and HHV Increase in yield by 3.8%

5% Na2CO3 Co/CNTs, Ni/CNTs, Pt/CNTs Na2CO3 NiO, Ca3(PO4)2 Pd/HZSM5@meso-SiO2

Increase in yield by 5.8% Increase in yield by 9%

NaOH Ce/HZSM-5 5% Na2CO3 Na2CO3

Increase in yield by 11.7% and increased gas yields Increased oil yields Increased oil yields and reduced coke yields Increase in yield by 10% Increase in yield by 33% Increase in yield by 5% Increase in yield by 33%

References Duan and Savage (2011a, b) Duan and Savage (2011a, b) Duan and Savage (2011a, b) Wang et al. (2018) Shakya et al. (2015) Saber et al. (2016) Shuping et al. (2010) Chen et al. (2017) Jena et al. (2012) Jena et al. (2012) Liu et al. (2018)

Yu et al. (2014) Xu et al. (2014) Yu et al. (2014) Yang et al. (2004)

the activation energy of the reaction, thus reducing the required reaction temperature, enhancing the reaction kinetics, and improving process efficiency by reducing the formation of tar and char (Matayeva et al. 2019). Table 5.4 lists out the effect of catalysts on the product properties of HTL of certain microalgae. Catalytic routes in HTL are categorized as homogeneous catalysis (water-soluble) including organic acids and alkali catalysts and heterogeneous catalysis (non-water soluble) including transition metal oxides, supported metals, insoluble organic salts molecular sieves, and others (Nagappan et al. 2021). The type of catalyst used plays a crucial role in the yield and quality of bio-oil produced.

5.3.1

Homogeneous Catalysts

A broad spectrum of homogenous catalysts has been extensively used for HTL which includes – alkaline compounds such as K, Na, Ca forms of hydroxides and carbonates, organic acids such as acetic acid and formic acid, and inorganic acids such as sulphuric acid (Nagappan et al. 2021). Alkali (KOH, K2CO3) as a catalyst is very efficient in the conversion of carbohydrates rich and lignin-rich biomass, by ensuring a higher degree of liquefaction and promoting the hydrolytic

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depolymerization of lignocellulosic polymers, thus leading to low solid residue formation (undesirable product of HTL) (Biller and Ross 2011; Singh et al. 2013). When alkali is used as catalyst, it improves the primary depolymerization reaction which in turn improves the biomass conversion capability and increases the carbon and H2 content in bio-oil (Bi et al. 2017; Zhu et al. 2015). Also, utilizing deoxygenation, denitrification, and desulphurization reactions, alkali reduces the hetero atom contents in the bio-oil (Xu et al. 2018). Alkali carbonates (especially potassium K2CO3) are preferred over hydroxides, which are known to cause corrosion of walls of HTL reactor (Duan and Savage 2011a, b; Murakami et al. 1990), because carbonates react with water to form bicarbonates which act as a secondary catalyst promoting bio-oil yield by escalating the repolymerization of bio-oil products and rising its non-polarity thus facilitating rapid separation of oil and water phases (Zhu et al. 2015; Huang et al. 2013; Meier et al. 1985). The order of reactivity of biomass degradation, selectivity of alkali solutions, and bio-oil yield follows the trend of K2CO3 > KOH > Na2CO3 > NaOH (Jindal and Jha 2016; Karagöz et al. 2005). Organic acid catalysts, although improve the flow properties of bio-oil by reducing the fraction of high boiling compounds, when used in HTL are converted into gases thus increasing the yield of gaseous products (Miao and Wu 2006). Also, when compared to alkali catalysts, they are comparatively less effective in reducing the hetero-atom content of biomass and further promoting biomass degradation (Xu et al. 2018; Meng et al. 2008).

5.3.2

Heterogeneous Catalysts

Although homogeneous catalysts are inexpensive, effective, and have positive effects on bio-oil yield and quality, their recovery and recycling are high energyconsuming separation steps adding to the already high cost associated with biocrude manufacturing chain (Perego and Bianchi 2010; Chen et al. 2017). Thus, recently several heterogeneous catalysts are being reportedly studied due to their high recyclability, stability, and hydrogen selectivity characteristics (Guo et al. 2010; Liu et al. 2018; Guo et al. 2010). Their high activity and easy recovery from liquid products make them more suited for re-use facilitating a decrease in the overall cost of the biofuel production process, thus aiding and opening up more scale-up opportunities. On the other hand, when compared with homogeneous catalysts, heterogeneous ones have limited internal/external diffusion capabilities associated with solid-liquid and solid-gas reactions (Lee et al. 2000). Heterogeneous catalysts include alkaline earth metals and their oxides such as CaO, MgO, colemanite, and hydrotalcite (Yim et al. 2017; Tekin et al. 2012; Ortigueira et al. 2015; Vickers 2017), transition metals such as Pt, Pd, Mo, Ni, Ru, and others supported on active carbon such as Pd/C, Pt/C, Ni/SiO2-Al2O3, metal oxides such as SiO2, Al2O3, molecular sieves and zeolites (Xie et al. 2019; Ong et al. 2019). Alkaline earth metal-based catalysts have similar properties and characteristics to alkaline homogenous ones, acting mainly on the promotion of the

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decomposition reaction of carbohydrates (Zhu et al. 2015). Although the addition of these types of catalysts increases the bio-oil yield, it also increases the concentration of oxygenated compounds in it, thus lowering its HHV (Yim et al. 2017; Tekin et al. 2012; Ortigueira et al. 2015; Vickers 2017). Transition metal and its oxides, characterized by their low cost and high activity for up-gradation of bio-oil (Arun et al. 2015), affect the flow properties of bio-oil by significantly decreasing its viscosity and having a high concentration of hydrocarbons (Wang et al. 2018). It also increases the bio-oil yield and promotes better deoxygenation of lipids to form alkene (Biller and Ross 2011), and simultaneously removes part of O2 via gasification (Toor et al. 2011). Usage of transition metal nanocatalysts promotes dehydrogenation activity resulting in high H2 generation (De Vlieger et al. 2012) and shows improved desulphurization and denitrogenation activity increasing its HHV and decreasing oxygen and nitrogen content (Saber et al. 2016). Zeolites, microporous, alumino-silicate minerals, commonly used as adsorbent catalysts, are used to improve the bio-oil yield and its quality (Duan et al. 2016). Usage of zeolites in combination with metals increases the yield of bio-oil (Liu et al. 2018) with high hydrocarbon content (Cheng et al. 2017) and decreased oxygen content. Also, zeolites catalyzed the HTL process, decreases the yield of oxygenated compounds such as ketones, acids, alcohols, and phenols resulting in acid-free bio-oil (Liu et al. 2018; Cheng et al. 2018) and furfurals and increased yield of esters. Having said that, as the amount of zeolites used increases, the amount of solid residue formed also increases resulting in obstruction of active pore sites and deactivation of catalyst. The most crucial property to evaluate the quality of bio-oil produced by any thermochemical process is HHV, as it is considered as a measure of the oxygen content in it, and thereby determining its final use. Transition metals and their oxides, act on biomass depolymerization, promote hydrodeoxygenation reactions and the formation of alkylbenzenes, thereby achieving high HHV values of bio-oil (in the range of 2835 MJ/kg), and also simultaneously increasing the quality of bio-oil and stability of value-added byproducts such as aldehydes and ketones.

5.4

Co-Liquefaction

Typically, any type of biomass is characterized as bulky, with low energy density, and having inconsistent properties or compositions throughout the year. Moreover, it is highly improbable to obtain a sufficient quantity of one type of biomass from a single region, unless otherwise cultivated, thus making the overall economy of the process non-viable (Overend 1982; Li et al. 2016). Co-liquefaction is an upcoming technological option to produce economical and environment-friendly alternate fuels as the logistics cost associated with the collection and transportation of feedstock can be considerably reduced (De Jong et al. 2017). More importantly, the process of co-liquefaction utilizes all types of biomass and produces positive synergetic effects

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Table 5.5 Effect of co-liquefaction on HTL process and products Biomass sample Scenedesmus sp. with sewage sludge

Prosopis juliflora with paint sludge Chlorella sp. with sawdust

Chlorella vulgaris with kitchen waste (dried and ground) Spirulina platensis with Enteromorpha prolifera

Effects of co-liquefaction Increased bio-oil yield of 38.27% and the Solid residue (Biochar + Catalyst) from the HTL process was treated and used as catalyst for the consecutive cycle Increased bio-oil yield 49.26% and HTL aqueous phase contained organic acids was recycled in consecutive cycles Increased bio-oil yield 57.8% oil yield and Recycling of aqueous phase and using as liquefaction medium more effective than the ethanol water system This combination of KW and CV in ratio 1:1 resulted in a higher yield with CaO as a catalyst Synergetic effect of 3.2 wt% due to SP intermediates promoting Enteromorpha prolifera decomposition

Author & year Arun et al. (2020)

Jayakishan et al. (2019) Hu et al. (2018)

Jin et al. (2013)

such as increased quality and the net quantity of bio-oil obtained (Jayakishan et al. 2019). Bio-oil with increased H/C ratios and desirable physicochemical properties for ease of downstream applications can be obtained by altering the biochemical composition of feedstock at moderate temperatures and low residence times (Yang et al. 2017; Zhang et al. 2015). Co-liquefaction aims to increase the bio-oil yield and its effect (CE) is defined as the difference between the actual yield of mixed feedstock (Yactual) and a mass fraction (xi) averaged yield calculated by individual feedstock (Yi) (Yang and Yang 2019). Thus, Co  liquefaction effect ðCEÞ ¼ Y actual 

X

Y i xi

ð5:9Þ

When the above difference is positive, it is termed as synergetic effect (SE), indicating yield enhancement and when negative it is called antagonistic effect (AE) indicating a diminishing yield. Typically, SE originates from positive interactions between breakdown fractions and intermediates of co-liquefied biomass and is dependent upon the mixing ratio of various biomasses and operating parameters of the HTL process (Yang et al. 2017; Wu et al. 2017). Microalgae are hydrothermally liquefied with a variety of feedstock such as macroalgae, plastics, kitchen waste, sawdust, rice husk, swine manure, and others. This system of co-liquefaction possesses many advantages and Table 5.5 lists some examples of co-liquefaction of various microalgal species and its effect on HTL products. The liquefaction intermediates of one biomass feedstock enhance or promote the originally suppressed decomposition (due to various factors) of the other (Jin et al. 2013) supporting high energy recovery. The bio-oils obtained from

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co-liquefaction portrayed high quality, enhanced nutrient recovery and distribution (Chen et al. 2014) suggesting co-liquefaction is an energetically and economically competitive bio-oil production route. The yield of bio-oil can be increased, and solid residue decreased by tailoring the mass ratio of biomass feedstock as the physicochemical properties such as lignin and ash content of the feed significantly affect the yield of solid residue (Gai et al. 2015). Although co-liquefaction of microalgae with other types of biomass has a positive synergetic effect on the bio-oil yield, the quality of bio-oil obtained is not without inconsistencies, especially when protein-rich microalgae are used in co-liquefaction (increases N content and N containing compounds in bio-oil) (Yang and Yang 2019). The synergetic effect (SE) strongly depends upon the operational parameters of the co-liquefaction process such as the biomass feedstock ratio, solvent to feedstock ratio, and also on the solvent/extraction method used for bio-oil separation. The major challenges in the study of co-liquefaction and its effect include statistical significance and evaluation under definite conditions and molecular-level understanding of the process. More insights on the kinetics and liquefaction mechanism are necessary to design/optimize co-liquefaction of certain combinations of feedstock under specific liquefaction and separation conditions to facilitate more efficient biomass conversion.

5.5

Bio-Oil Upgradation Techniques

Bio-oil has an intricate composition comprising of many non-identical components majorly acids, aldehydes, and phenols acquired from depolymerization and fragmentation of biological macromolecules (Ahamed et al. 2021; Lyu et al. 2015). Typically, bio-oil is a thick, black, viscous organic liquid having a characteristic smoky scent with pH in the range of 3.5 to 4.2 and 70–95% equivalent energy value of that of petro-crude (Costanzo et al. 2016; Saber et al. 2016; Zhang et al. 2019). However, bio-oil differs significantly from petro-crude due to its variable composition, chemical constituents, and physical properties that confer: • • • •

thermal and oxidative instability, acidic, viscous, and corrosive nature, increased O content and thus low heating value, elevated N hetero-atom content and water.

These characteristics render the bio-oil unsuitable and undesirable to be used directly in petroleum refineries for transport fuel application and therefore, enhancing and upgrading the bio-oil with prerequisite properties is imperative. Several bio-oil up-gradation techniques are available – Emulsification, Steam reforming, Catalytic cracking, hydrotreatment and supercritical fluid treatment, and others (Mathimani et al. 2019; Zhang et al. 2019), and Table 5.6 lists the merits and demerits of various upgradation processes.

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Table 5.6 Merits and demerits of up-gradation processes Upgradation technique Emulsification

Hydrotreating

Catalytic cracking

Steam reforming

5.5.1

Merits Improves ignition (Ahamed et al. 2021) Improved cetane and calorific value (Chong et al. 2017) Improves stability (Lian et al. 2017) Reduces viscosity of bio-oil (Garcia-Perez et al. 2010) Reduces N, S, O content (Gandarias and Arias 2013) Improves fuel stability and quality (Elliott 2011) No alteration in boiling range (Ahamed et al. 2021)

Increases yield and better quality (Lian et al. 2017) Reduces acidity (Chong et al. 2019) Reduction of undesirable organics (Ahamed et al. 2021) H2 production (Zhang et al. 2019) Can be utilized in already in-place equipment (Huber et al. 2006)

Demerits Increases corrosiveness (Chiaramonti et al. 2003; Huber et al. 2006) High cost of emulsifiers (Lian et al. 2017) Emulsification is energy intensive process (Saber et al. 2016) Decreases HHV and octane number (Zhang et al. 2013) H2 usage (Ahamed et al. 2021) Large amount of catalyst (Tang et al. 2008) Decreased bio-oil yield (Xiu and Shahbazi 2012) Catalyst cost (Wang et al. 2011) Increased production of solid residue leading to catalyst deactivation and reactor clogging (Xiu and Shahbazi 2012) Coking of catalyst (Chen et al. 2015) Catalyst regeneration (Chen et al. 2015) Inferior quality of upgraded oil when zeolites are used (Mortensen et al. 2011)

Catalyst deactivation due to coking (Saber et al. 2016) Deposited carbon reduces hydrogen yield (Wu et al. 2008) Choice of catalyst (Ahamed et al. 2021)

Emulsification

A stable emulsification system requires low compatibility of selected liquids, where complete dispersal of them is achieved by mixing them with the help of an emulsifying agent. Bio-oil is most commonly dispersed in a two-phase emulsification system with a continuous phase of fossil oil (diesel) in conjunction with a cheap and suitable emulsifying agent. Key factors such as the amount of emulsifier used, bio-oil to diesel volume ratio, temperature and intensity of stirring play a major role in achieving the desired emulsification effect (Ahamed et al. 2021). Due to the high concentration of oxygen and water, diesel and bio-oil are totally immiscible with each other. Thus, when compared with other mechanical mixing methods (e.g., agitation), ultrasonic-assisted emulsification achieves narrower distribution of fine tiny-sized liquid droplets producing well stable emulsions (Lian et al. 2017). Commercial emulsifiers such as Altox 4914, Tween 80, Span 80, among others, are used for bio-oil and diesel emulsifications. The hydrophilic and lipophilic balance (HLB) value of the emulsifier is one of the crucial parameters, and its correlation with HHV of the fuel is used in the practical application of emulsification

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to lower operation costs (Lin et al. 2016). The stability and efficiency of an emulsified system is characterized by key system characteristics such as acid value, viscosity, average molecular weight, water content, density, and presence of desired functional groups. Also, to make the emulsification system more eco and environment friendly, bio-oils can be emulsified with biodiesel as it contains fattyacid esters which help in decreasing viscosity as the solubility of furans, sugars, and oligomers in a bio-oil increase in the biodiesel phase (Garcia-Perez et al. 2010).

5.5.2

Steam Reforming

In the steam reforming process, the liquid fuel in the presence of steam at 700–100
C and a catalyst, is converted into synthesis gas, consisting mainly of hydrogen and carbon-monoxide. One of the major advantages of this technology is the simultaneous production of renewable gaseous clear hydrogen during bio-oil up-gradation. Various catalysts such as Ni, Al2O3, MgO, La2O3 are being used for steam reforming to produce H2 and other model compounds such as furfurals, acetic acid, cyclopentanone, m-cresol, and others (Lan et al. 2010, 2014). At higher temperatures of 950
C, there is less coke deposition, as the carbon nanofibers on the surface of the catalyst are removed by absorptive steam (Lan et al. 2014). As steam reforming of fossil fuels is a well-established technology, a renewable fuel such as bio-oil can also be used in fluidized and fixed bed reactors to be converted into syngas or producer gas consisting mainly of H2, CO, CO2, CH4 along with a range of products such as hydrogen, alkanes, aldehydes, and others by various reactions such as water-gas shift reaction, Fischer-Tropsch synthesis, fermentation or by homogeneous catalysts, oxo synthesis, respectively (Ahamed et al. 2021). The overall steam reforming reaction of any oxygenated compound can be represented as (Gollakota et al. 2018) C n H m Ok þ ð2n  k ÞH2 O ¼ nCO2 þ

  2n þ m H2 2k

ð5:10Þ

The maximum yield of hydrogen can be obtained by the equation 2 + m/2n  k/n. The choice of catalyst, operating temperature, and steam to carbon ratio play an important role in eliminating catalyst deactivation and coke formation.

5.5.3

Catalytic Cracking

Catalytic cracking is one of the bio-oil up-gradation techniques where heavier hydrocarbons are transformed into lighter ones and oxygen is removed in the form of water, CO, and CO2 in the presence of a catalyst, and the remaining fraction of hydrocarbons is converted into liquid hydrocarbon products. Simultaneously, the

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acidity and viscosity of bio-oil are reduced by the esterification of acidic and alcoholic components (Lian et al. 2017). Catalysts such as CaO, MgO, and ZnO with higher deoxygenation capabilities, yielded bio-oil with improved properties and desired physical effects such as acidity reduction without elevating the water content of bio-oil and lesser coke formation (Bertero and Sedran 2015; Chong et al. 2019). Fluid Catalytic Cracking (FCC) by means of petrochemical precursors are generated from conventional hydrocarbons, is one of the best technological options for bio-oil up-gradation, where catalytic cracking of bio-oil into liquid hydrocarbons, coke, and gas takes place in the presence of a catalytic bed (most commonly alumina-silica) (Bertero and Sedran 2015). Catalysts such as Fe/γ-Al2O3 and zeolites (HZM-5, HZSM-5) support the successful conversion of bio-oils into gaseous products and the production of phenols and aromatic hydrocarbons (Xu et al. 2013; Ahamed et al. 2021). During the zeolite catalytic cracking process, undesirable model organics without aromatic rings such as acids, aldehydes, ketones, furfurals, and others, undergo cyclo dehydration in catalytic reaction pathways resulting in products such as naphthalene, phenols, benzene, indene, and other derivatives of polyaromatic hydrocarbons (Dan et al. 2012). The choice of a zeolite catalyst, its varying acidities, and bio-oil to catalyst ratio plays an important role in bio-oil deoxygenation, increasing primary hydrocarbon content and production of non-condensable (Ibarra et al. 2019; Imran et al. 2016). Although zeolites offer high surface area and adsorption capacities that facilitate better bio-oil up-gradation, deposition of graphite and fibrous coke inside the pores ad surface of the catalyst due to carbon accumulation, decreased the specific area, pore-volume, and crystallinity of catalyst, thereby leading to its subsequent deactivation (Yin et al. 2014).

5.5.4

Hydrogenation

Bio-oils can be upgraded by hydrogenation technology under high pressure (10–20 MPa) and temperature with gaseous hydrogen, in the presence of a catalyst. The degree of oxygenation is one of the important aspects in determining its applications and typically ii is required to range below 5 wt% of O2. The stability and quality of bio-oils can be enhanced by hydrogenation as it decreases the organic acid, alcohol, and aldehyde contents by esterification, thus impacting its degree of oxygenation and viscosity. Also, these undesirable organic compounds lead to increased acidity and corrosiveness, restricting their applicability. Therefore, better quality of fuel precursors with no major alterations in boiling range is obtained by the hydrogenation process at temperatures beyond 500
C, where saturation of olefins occurs, and other aromatics are converted to naphthalene. The common catalysts used for hydrogenation are CoMo/Al2O3, NiMo/Al2O3 systems which help in the removal of oxygen and improve the properties of bio-oil (Xiu and Shahbazi 2012). At times hydrogenation is used in conjunction with esterification to convert acids and aldehydes into stable combustibles. This process

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is called one-step hydrogenation esterification (OHE) and bi-functional catalysts that support esterification and hydrogenation are employed for this process – platinum loaded zeolites, 5% Pt/HZSM-5 and amorphous aluminum silicate, 5% Pt/Al2SiO3. OHE is operated at lower temperatures to avoid aldehyde condensation which uses up a large amount of catalyst creating superabundant acid sites which in turn aid aldehyde condensation (Tang et al. 2008). Also, at higher temperatures, there exists higher cracking and coking conditions and increased removal of heteroatoms (O, N) from bio-oil causing lower hydrogen availability, thus leading to reduced bio-oil yields (Castello et al. 2019). Hydrodeoxygenation, a variant of the hydrotreating method is used to remove oxygen under high pressures of 20 MPa and moderate temperatures of 300–450
C with a hydrogen source in the presence of a catalyst. The catalytic reaction of oxygen with high-pressure hydrogen in the presence of commonly used Co, Mo, and Ni. Mo assists in the removal of O, N, and S (Saber et al. 2016). The conventional catalysts such as Al2O3, Pt/ZSM have inherent shortcomings such as product contamination and catalyst deactivation which can be overcome by catalyst selectivity and efficient hydrodeoxygenation of amorphous catalysts such as Ni-Co-B, Ni-W-B, and Co-WB (Liu et al. 2017; Wang et al. 2011).

5.6

The Energy Efficiency of the HTL Process

Direct application of HTL to convert biomass into liquid fuels, which can serve as an alternative to petroleum fuels, is limited due to its thermodynamic instability and questionable economics. In HTL of microalgae, the nutrient medium required for algal growth can be regenerated and recycled or wastewater can be used as a primary growth medium for algae, thus integrating wastewater treatment and biomass feedstock production for the HTL process (Arun et al. 2018). Also, the CO2 produced in the HTL process can be used up by the algal photosynthesis reaction serving the process of CO2 sequestration. Figure 5.1 describes the various products that can be obtained from HTL of microalgae for maximizing energy recovery and efficiency. This process has a cutting edge over the current algal cultivation procedure which consumes large amounts of water, nutrients, and energy. Several value-added products are obtained throughout the process achieving maximum energy recovery at each possible step. Ten to 15% of the energy from the biomass feedstock is used up in the HTL process, ensuring the possibility of an 85–90% energy recovery. Moreover, 70% of the carbon from the feedstock can be recovered in various stages of the process (Gollakota et al. 2018).

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Fig. 5.1 HTL of algal biomass and various products obtained

5.7

Conclusion

Biomass can be converted advantageously into petroleum fuel precursors by the hydrothermal liquefaction process. • The sub-critical water used in the process eliminates the disadvantage faced by the original liquefaction process of usage of solvents. • Using microalgae as biomass feedstock poses several advantages such as availability, rapid growth rates, no prerequisite drying, high yields, and high versatility of value-added by-products. • A plethora of efficient heterogeneous catalysts is available for use to increase the yield and efficiency of the HTL process. • The technique of co-liquefaction can be further employed to increase the yield and quality of bio-oil produced. • To improve the reliability of the process, up-gradation process of the obtained bio-oil to refinery grade liquid fuel is a necessity. • To further increase the economic feasibility of the process, energy recovery is maximized at every step by capturing all value-added by-products and utilizing all opportunities for reuse and recycling. Conflicts of Interest The authors have no conflicts of interest to declare.

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Chapter 6

Carotenoids and Pigment Generation Using the Microalgal Production System Pankaj Kumar Jain, Praveen Jain, Brijesh Pandey, Prakash Kumar Sarangi, Anand Prakash, Akhilesh Kumar Singh, and Rajesh K. Srivastava

Abstract Carotenoids are pigments having a proven role as food colorants, antioxidants, health-promoting substances, food additives, feed additives, vitamins, pharmaceuticals, etc. After experiencing the hazard of synthetic entities in human life, people are again trying to “go natural.” Being natural and part of a healthy ecosystem, microalgae may have immense potential to provide many such entities. In the present scenario, microalgal systems are among the top-ranked bioresources to meet the demands of the fast-growing world population. In addition, being grown in natural water resources provides opportunities to socially backward classes to manage their lifestyle for economic upliftment and nutritional well-being. Carotenoids may be divided into primary and secondary groups. The secondary carotenoids are present in the lipid vesicles in the cytosol or plastids. Also, phycobiliproteins, phycocyanin, phycoerythrins, β-carotenes, lutins, and astaxanthins are the pigments which are commonly produced by microalgae. Many microalgal systems have been investigated so far to produce different pigments, for instance, diatoms and members of Phaeophyceae for fucoxanthins, dinoflagellates for peridinin, cryptophytes for alloxanthins, Porphyridium spp. for β-carotenes, Tetraselmis spp. for lutein, and so

P. K. Jain Department of Botany, Kalyan Post Graduate College, Sector 7, Bhilai Nagar, Durg, Chhattisgarh, India P. Jain Department of Botany, Government Chandulal Chandrakar Arts and Science PG College Patan, Durg, Chhattisgarh, India B. Pandey · A. Prakash · A. K. Singh (*) Department of Biotechnology, School of Life Sciences, Mahatma Gandhi Central University, East Champaran, Bihar, India e-mail: [email protected] P. K. Sarangi College of Agriculture, Central Agricultural University, Imphal, Manipur, India R. K. Srivastava Department of Biotechnology, GIT, GITAM, Visakhapatnam, Andhra Pradesh, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 P. Verma (ed.), Micro-algae: Next-generation Feedstock for Biorefineries, Clean Energy Production Technologies, https://doi.org/10.1007/978-981-19-0680-0_6

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on. This chapter aims to provide an overview of the potential of microalgal systems to generate valuable carotenoids and pigments. Keywords Antioxidant · Microalgae · Carotenoids · Carotenogenesis · Secondary metabolites · Downstream processing

Abbreviation PBRs

6.1

Photobioreactors

Introduction

Pigment molecules have been mainly utilized by the plant system towards the entrapment of photons of the visible spectrum of light. Although they are many, one of these is the carotenoids. The carotenoids can be categorized into primary (associated with photosynthetic process) and secondary (the products of carotenogenesis in stressed conditions) groups. The secondary carotenoids exist in the lipid vesicles of the cytoplasm/plastids. Phycobiliproteins, phycocyanin, phycoerythrins, β-carotenes, lutins, and astaxanthins are typical pigments formed by microalgal cells. The astaxanthins are multifunctional secondary carotenoids produced by Haematococcus pluvialis. Numerous microalgal species can generate diverse pigment molecules, for instance, diatoms as well as members of Phaeophyceae for fucoxanthins, dinoflagellates for peridinin, cryptophytes for alloxanthins, Porphyridium spp. for β-carotenes, Tetraselmis spp. for lutein, and so on. Because of the autotrophic mode of nutrition, the microalgal, as well as cyanobacterial, species are associated with three groups of pigment molecules, i.e., chlorophylls, carotenoids, and phycobiliproteins for harvesting light (Richmond and Hu 2013; Goswami et al. 2021a). Further, their relative ratio as well as occurrence furnishing diverse colors to the organism. Microalgae are the key constituents of numerous ecosystems found in marine/freshwater. These are associated with diverse types of pigment molecules. Microalgae are found to depict oxygenic photosynthesis that occurs with the aid of chlorophyll molecules. Interestingly, chlorophyll molecules are found to occur in every microalgal species (Masojdek et al. 2007). Microalgal carotenoids, i.e., astaxanthin, lutein, and carotene, are well recognized (Masojdek et al. 2011; Mehariya et al. 2021; Saini et al. 2021). Further, phycobiliprotein pigments (phycocyanin as well as phycoerythrin) have been found to occur merely in cyanobacterial as well as red algal species/strains as main light-harvesting pigment molecules (Masojdek et al. 2011; Pagels et al. 2020). Microalgal carotenoid molecules have received huge attention owing to their promising exploitation in food, pharmaceuticals, the cosmetics industry, and so on. This is large because of their color as well as the occurrence of promising

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bioactive constituents (Guedes et al. 2011; Pagels et al. 2020; Kapoor et al. 2021). For instance, approximately 850 kinds of naturally occurring carotenoids are known to have a global market of 1.8 billion US$ (Honda et al. 2020). In other words, these pigments are valuable substances for human beings, where they can be exploited in the form of food colorants, antioxidants, health-promoting substances, and so on. Owing to their role as therapeutic agents and nutraceuticals, the pigments including carotenoids have established their importance in diet and dietary supplements. Further, natural colorants like phycocyanin, β-carotene, and astaxanthin have been extracted from various microalgal species like Spirulina, Dunaliella, and Haematococcus, respectively. Such natural colorants have been attaining significance compared to artificial counterparts because these are nonhazardous as well as noncarcinogenic (Dufoss et al. 2005). In the present scenario, pigments like lutein and phycoerythrin extracted from Scenedesmus almeriensis and Porphyridium spp., respectively, also received huge attention owing to their bioactive potential (Fernández-Sevilla et al. 2010; Li et al. 2019). In the contemporary “go green” era, the demand for natural colors over artificial ones is enhancing progressively from a more sustainable resource. As a result, microalgal species have an edge over industrial setup owing to their ability to grow with minimum nutrient requirements, short lifetime, ability to handle adverse conditions, scalable methods, and economical downstream processing (Acién et al. 2012; Agrawal and Verma 2022). As a result, microalgal systems are among the top-ranked biological resources for meeting out demands of the fast-growing world population. Furthermore, a culture of microalgal species with their exploitation towards pigment/carotenoid molecule generation creates opportunities for socially backward classes for managing their standard of living towards economic upliftment as well as nutritional well-being. The present chapter provides an overview of the strategies adapted towards the production of microalgal carotenoids/pigments along with their biosynthetic routes and extraction techniques.

6.2

Microalgal Pigments and Carotenoids

Microalgae have been a diverse class of cryptogamic plant systems. They consist of 13 big phyla. However, there are some smaller groups which have been so far partly studied (Reynolds 2006). These are varying from unicellular, colonial, filamentous, to siphonous. Among the microalgae, the cyanobacteria are oxygenic photosynthetic prokaryotes. They are depicting huge diversity with respect to morphology, physiology, ecology, and so on. Further, the Chlorophyta are unicellular, multicellular, filamentous, siphonous, thalloid, and largely freshwater algae. However, the cryptophytes are not only unicellular but also extensively found in both freshwaters as well as marine environments. Likewise, dinophytes are unicellular dinokonts found mostly in the marine environment (Reynolds 2006). Various groups of microalgal species hold diverse pigments, for instance, Chlorophyceae (chlorophyll a and b, siphonaxanthin, astaxanthin, β-carotene, and prasinoxanthin), diatoms

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(chlorophyll a and c, β-carotene, fucoxanthin, and diadinoxanthin), Cryptophyceae (chlorophyll a and c, carotenoids, and phycobiliproteins), and Cyanophyceae (chlorophyll a, xanthophyll, phycobiliproteins, and so on) (Graham and Wilcox 2000; Van den Hoek et al. 1995; Lee 1999). Interestingly, chlorophyll molecules are of three types, i.e., a, b, and c. The chlorophyll backbone is composed of porphyrin macrocycle involving tetrapyrrole rings (Humphrey 2004; Scheer et al. 2004). On the other hand, 40-carbon polyene chain-derived terpenoid pigment molecules produce carotenoid molecules.

6.3

Biosynthetic Route of Pigments/Carotenoid Fabrication in Microalgae

The microalgae are capable of synthesizing carotenoids and other pigments using specific metabolic routes (Figs. 6.1 and 6.2). The isopentenyl diphosphate and dimethylallyl diphosphate are five-carbon-containing common precursor metabolites that are needed for the formation of carotenoid molecules. The algal species have been equipped primarily with the methylerythritol phosphate route that takes part in the biogenesis of these precursors (Sathasivam et al. 2020; Goswami et al. 2021b). This route is recognized in algal species as well as plants. Nevertheless, the

Fig. 6.1 Biosynthetic routes of carotene and its derivatives

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Fig. 6.2 Biosynthetic routes of zeaxanthin and violaxanthin

methylerythritol phosphate route is found to vanish in various classes such as Chlorophyceae, Prasinophyceae, Trebouxiophyceae, Cyanidioschyzon merolae (red alga). Hence, the methylerythritol phosphate route is the main route in these algal groups that provides the majority of isopentenyl diphosphate as well as dimethylallyl diphosphate towards carotenoid molecule biogenesis. Further, the amount of geranylgeranyl diphosphate with its precursor molecules in algal species determines the rate as well as a consequent flux for carotenoid biogenesis (Feng et al. 2020). The formation of phytoene constitutes the entry-stage reaction for the carotenoid molecule biogenesis. This is the initial colorless carotenoid molecule that has been produced through condensation of two geranylgeranyl diphosphates in the presence of phytoene synthase enzyme (Sun and Li 2020; Miras-Moreno et al. 2019). The phytoene synthase is one of the crucial rate-limiting as well as main flux-regulating enzymes. It determines the pool size of carotenoid molecules. Further, lycopene is accountable for the biogenesis of both α-carotene and β-carotene in algal species. The α-carotene involves one ε-ring as well as one β-ring at the edge of lycopene. Nevertheless, the β-carotene is found to incorporate two β-rings that are present at the edge of lycopene. Carotene having two ε-ionone rings has been found to be infrequent. This reaction is assisted via two diverse enzymes, i.e., lycopene ε-cyclase and lycopene β-cyclase (Cui et al. 2011). Fabrication of α-carotene using lycopene takes place in two successive stages, where the first stage involves the lycopene ε-cyclase-mediated cyclization at the one open end that results in the formation of δ-carotene. The second stage exploits the lycopene β-cyclase, whose catalytic activity results in β-ionone ring synthesis at another end, and, eventually, α-carotene is produced. Furthermore, the α-carotene so produced is transformed into lutein. Through the enzymatic activity of the same enzyme, i.e., lycopene β-cyclase, the β-carotene is also generated from lycopene. In the first stage, lycopene is found to be transformed into γ-carotene, which is then transformed into β-carotene in the subsequent stage (Deng et al. 2020). It has been found that the formation of

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δ-carotene, α-carotene, and lutein is missing in several classes of algae-like Bacillariophyceae, Chrysophyceae, Phaeophyceae, and Xanthophyceae including several red algae. However, the β-carotene is present in major classes of algae as well as other photosynthetic organisms (Deng et al. 2020; Takaichi 2011). Zeaxanthin is a duple hydroxylation derivative of β-carotene. Biogenesis of zeaxanthin takes place in the entire algal classes. Further, violaxanthin is produced from zeaxanthin (which acts as a precursor) in the presence of the enzyme zeaxanthin epoxidase (Dautermann and Lohr 2017).

6.4

Microalgal Mass Production

Microalgal mass production is carried out in enclosed photobioreactors (PBRs), open ponds, or a combination of both (Mallick et al. 2016; Singh and Mallick 2017; Singh et al. 2017). These have distinct advantages as well as disadvantages. Some key parameters like capital and operational cost, an area available for cultivation, risk of contamination, water accessibility, and so on need to be kept in mind while choosing a cultivation system (Aitken and Antizar-Ladislao 2012; Goswami et al. 2021). Apart from choosing the most appropriate cultivation system, phycologists also face a choice of cultivating/growing a naturally available species, i.e., a wild type or promisingly genetically modified organisms, where targeted features like carotenoid and pigment generation can be boosted. The cultivation of genetically modified organisms has been a debatable subject in various countries (Henley et al. 2013). Therefore, cultivations of genetically modified organisms on a large commercial scale are uncommon. Nevertheless, if such things happen (for instance, Algenol in Florida, USA), then such cultivations are always performed in enclosed photobioreactors with stringent regulations and monitoring, and containment strategies are set up in order to inhibit genetically modified organisms from escaping. The microalgal carotenoid/pigment production approaches are of two types. The first strategy involves screening microalgal genera for choosing a species/strain, which naturally generates higher carotenoid/pigment molecules. The second strategy involves the selection of an appropriate species/strain and then genetically engineering this species/strain for enhancing the formation of carotenoid/pigment molecules. Such genetic modification can be carried out either indirectly through mutagenesis or directly through targeted engineering. In both strategies, the chosen species/strain is then subjected to cultivation for further boosting carotenoid/pigment production. The large-scale microalgal cultivation usually involves a two-stage approach in which the first stage allows the rapid cultivation of the cells for the accumulation of huge biomass. In the second stage, the huge microalgal cell biomass so achieved is exposed to stress environment like nitrogen limitation/deficiency and so on for the enhanced production of molecules of interest like carotenoid/pigment molecules. Figure 6.3 summarizes the processing steps of microalgal carotenoid and other pigment molecules.

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Fig. 6.3 Various steps involved in the processing of microalgal carotenoid/pigments

6.5

Strategies Adapted for Enhancement of Microalgal Carotenoid and Pigment Accumulation

Various parameters like temperature, spectral quality and quantity, pH, nutrient limitation, salinity, pesticides, heavy metal stress, etc., can affect the fabrication of microalgal pigment molecules. For instance, the investigation revealed that cyanobacterial species are capable to regulate their tetrapyrrole content as well as composition with respect to ecological factors like light intensity, light wavelength, temperature, and nutrient availability (Prassana et al. 2004; Agrawal et al. 2020). Likewise, diverse stress factors like cell division inhibitor (vinblastine), nitrogen deficiency, higher salinity, and higher irradiation along higher temperature are found to boost the carotenoid content of microalgal species (Pisal and Lele 2005). Light intensity acts as an important parameter, which regulates the β-carotene formation in algal species. The exposure of light intensity revealed the improved generation of carotenoid molecules from D. salina (Pisal and Lele 2005). It has been found that β-carotene content per cell enhanced rapidly under light intensity. This indicates that β-carotene formation can be significantly boosted under higher irradiation (11.28 mmol photon/m2/s) in blue-green microalgal cells/species. It was observed that astaxanthin formation was higher (30 mg/g) in H. pluvialis at higher light intensity (546 mmol photon/m2/s) (Imamoglu et al. 2009). Further, it was also observed that strong illumination resulted in oxidative stress, which led to enhanced astaxanthin production (Salguero et al. 2003). The temperature is the most important parameter as it influences the metabolic processes of living organisms including microalgae. Also, the optimum growth temperature, as well as tolerance window,

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usually varies for diverse microalgal species/strains (Hemlata and Fatma 2009). Nevertheless, an extreme variation in temperature induces stress in microalgal species/cells. The higher temperature was found to induce carotenoid molecule (for instance, β-carotene) formation in blue-green microalgae (Garcia-Gonzalez et al. 2005). The optimum temperature for the fabrication of phycobiliproteins in Anabaena sp. was recorded at 30  C (Hemlata and Fatma 2009). However, optimum temperatures of 25  C, 35  C, and 36  C were registered for S. platensis, Anabaena sp., and Nostoc sp., respectively (Moreno et al. 1995). Likewise, the Synechococcus sp. depicted optimal phycobiliprotein formation under 36  C. The optimal temperature of 28  C was found to be suitable for the formation of astaxanthin in H. pluvialis (Domınguez-Bocanegra et al. 2004). Apart from this, 25  C and 30  C were reported as optimum temperatures towards β-carotene fabrication in D. salina (Del Campo et al. 2001; Garcia-Gonzalez et al. 2005). Furthermore, 28  C was the optimum temperature reported towards the accumulation of carotenoid molecules (lutein) in Muriellopsis sp. (Del Campo et al. 2000), C. protothecoides (Wei et al. 2008), C. zofingiensis (Wei et al. 2008), and Neospongiococcus gelatinosum (Del Campo et al. 2000). In addition, the impact of pH upon photosynthetic pigments has attracted little attention (Hemlata and Fatma 2009). The solubility and the bioavailability of nutrients are affected through the change in pH. An increase in phycocyanin, phycoerythrin, and allophycocyanin content was recorded in Nostoc sp. strain UAM206 via enhancement in pH (Poza-Carrion et al. 2001). The optimal phycobiliprotein fabrication was registered under pH 8 in S. platensis (Hemlata and Fatma 2009). However, optimal phycobiliprotein fabrication in Nostoc sp. was observed at pH 9. Likewise, pH 9 was reported optimal for the formation of chlorophyll in S. platensis (Chauhan and Pathak 2010). Likewise, the saline environment was also found to affect the formation of pigment content in microalgal species. For instance, a lesser concentration of sodium chloride (10 ppt) showed improved phycobiliprotein accumulation (135.73 mg/g) in Anabaena NCCU-9 (Hemlata and Fatma 2009). Nevertheless, the salinity 15 ppt improved the phycobiliprotein production (66.7 mg/g) in Oscillatoria sp. The maximum chlorophyll and the entire carotenoids were formed at salinity 2 ppt for Dunaliella viridis (Ilkhur et al. 2008). Likewise, Pisal and Lele (2005) revealed that optimal salt concentration towards carotenoid fabrication was 3 ppt. Furthermore, it was found that salinity has a great impact on chlorophyll/β-carotene production (Avron 1992), where the chlorophyll content reduced with enhancement in salinity. However, β-carotene fabrication in blue-green microalgal species was boosted with the enhancement in salinity. Also, parameters like pesticides were found to influence pigment generation in microalgal species. The inhibitory impact of pesticides upon phycobiliproteins is revealed by several phycologists. For instance, the phycobiliprotein fabrication in blue-green microalgal species like Nostoc sphaeroides and Anabaena variabilis reduced under thiobencarb pesticide stress condition (Xia 2005; Battah et al. 2001). Apart from these, nitrogen acts as a key nutrient required for the growth media of any cell. Therefore, the culture organisms could be under stress owing to the deficiency/starvation of nitrogen. During nitrogen deficiency, the microalgal cells stop undergoing division and show extreme

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production of free radicals that subsequently cause enhanced β-carotene content of 7.05 pg/cell from 1.65 pg/cell (Møller et al. 2000). Also, a negative impact was imposed on chlorophyll formation under nitrogen deficiency as chlorophyll holds four nitrogen atoms (Ben-Amotz et al. 1989). Therefore, the microalgal cells failed to actively produce chlorophyll under nitrogen stress. Under nitrogen deficiency, Anabaena NCCU-9 formed a maximum quantity of phycobiliproteins (Hemlata and Fatma 2009). The astaxanthin formation was found to enhance through supplementing iron in media (Choi et al. 2002; Abregas et al. 2003; Kang et al. 2006).

6.6

Strategies for Microalgal Biomass Harvesting

There are variations in the composition of microalgal pigments, which also vary with ecological conditions. Greater than 600 naturally producing carotenoid pigments are well known/documented as well as characterized in which astaxanthin, β-carotene, and fucoxanthin including lutein have been found to be main carotenoids towards their promising uses in foods (Zhang et al. 2014). Interestingly, there are diverse microalgal species like Spirulina platensis, Haematococcus pluvialis, Dunaliella salina, Botryococcus braunii, and so on available as a good source of carotenoid pigments for promising industrial applications (Ambati et al. 2018). The H. pluvialis, D. salina, and B. braunii have been familiar with the fabrication of astaxanthin, βcarotene, and so on (Lamers et al. 2008; Rao et al. 2010; Zhang et al. 2014). As carotenoids/pigments are intracellular biomolecules, therefore huge microalgal biomass is required (for the large-scale production of carotenoids/pigments). The huge microalgal cell biomass generated in stage first is then subjected to stage second with a specific stress environment that led to enhanced carotenoid/pigment production. Such cell biomass with huge contents of carotenoids/pigments is then harvested (using an appropriate harvesting approach) followed by cell disruption techniques. The approaches available for harvesting the microalgal cells involve physical like flocculation, centrifugation, filtration, and so on (Grima et al. 2013; Chen et al. 2011) and chemical like inorganic salt (for instance, aluminum sulfate) or organic flocculant like chitosan and so on (Uduman et al. 2010; Gorin et al. 2015; Hu et al. 2013; Pragya et al. 2013; McMillan et al. 2013; Utomo et al. 2013).

6.7

Strategies for Microalgal Carotenoid and Pigment Extraction

The cell disruption techniques like grinding (Hu et al. 2013), cryogenic grinding (Grima et al. 2013; Zheng et al. 2011), bead milling (Chan et al. 2013; Taucher et al. 2016), high-pressure homogenizer (Kim et al. 2015), autoclave (Chan et al. 2013),

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microwave (McMillan et al. 2013; Pasquet et al. 2011; Zheng et al. 2011), enzymatic hydrolysis (Deenu et al. 2013; Kadam et al. 2013), pulsed electric field (Lai et al. 2014), alkaline treatment (Halim et al. 2012a, b), and ionic liquids (Park et al. 2015) are available for harvested cell biomass disruption rich in carotenoid/pigment contents. Based on solubility criteria, the microalgal pigments have been classified into two types: (i) fat-soluble like chlorophylls/carotenes and (ii) water-soluble like phycobilins/peridinin. The chlorophylls, carotenoids, and phycobilins are the three main categories of photosynthetic pigments found among the algae. Table 6.1 summarizes the diverse methodologies employed for the extraction of microalgal pigments including carotenoids. Extraction of chlorophylls, as well as carotene pigments, can be carried out from thylakoid membranes using organic solvents like acetone and so on. Nevertheless, water-soluble algal pigments like phycobilins/peridinin can be extracted from those algal cells from which chlorophyll molecules have been already extracted using an organic solvent. The underlying principle of pigment extraction approaches involves the disintegration of cell integrity as far as feasible and, therefore, extracting/taking out pigments from inherent membrane protein molecules. The pigment molecules that have been extracted from algal cells using apposite solvents could be subjected to chromatographic techniques like TLC or HPLC for spectral examination as well as identification. Although the concentration of pigment molecules present in organic solvents could be assessed, the formulas for pigment estimation are predictive and might overestimate the concentration of several pigment molecules (Seely et al. 1972). The uncoupling pigments from the pigment binding protein molecules can alter the absorption patterns of the molecules. This causes shifting in maxima in the range of 10–50 nm over spectra estimated for intact cells.

6.8

Conclusion and Prospects

Microalgal species yield a range of substances, which are valuable to human as well as animal health. Among these substances, microalgal carotenoids/pigments have received huge attention towards industrial uses because of their bioactive potential together with natural product characteristics. Such pigments have been generally sold as extracts to overwhelm purification prices. The biggest limitation concerning carotenoid/pigment bioprocessing arises from the installation as well as operating costs. This is supported by the fact that the standardization of a biomass extraction procedure for obtaining the carotenoid/pigment molecules of interest is still a challenge. The extraction process was found to contribute up to 60% of total costs. To diminish such costs, it is still needed for optimizing the prevailing techniques as well as developing new techniques. Overall, still basic as well as applied research is required for overcoming constraints linked to microalgal carotenoid/pigment production. This will give the microalgal/cyanobacterial industry an opportunity in the global market.

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Table 6.1 Various approaches exploited towards extraction of microalgal pigments including carotenoids Microalgal species Haematococcus pluvialis

Type of extraction method Conventional solvent extraction using acetone as solvent

Pigments Astaxanthin

Arthrospira platensis

Classic solvent extraction using water or sodium phosphate buffer

Phycobiliproteins

Chlorella vulgaris

Pressurized liquid extraction using ethanol/water (9:1, v:v) at 100 bar

Scenedesmus almeriensis

Supercritical CO2 extraction at 400 bar and 60  C

Carotenoids, chlorophyll a and b, lutein, carotene Lutein and β-carotene

Isochrysis galbana Spirulina platensis

Classic solvent extraction using ethanol Ultrasound-assisted extraction solvent using heptane at 167 W per cm2 at 30  C Microwave-assisted extraction solvent using water at 40  C

Porphyridium purpureum

Dunaliella salina

Supercritical CO2 extraction at 400 bar and 30  C

Gloeothece sp.

Continuous pressurized solvent extraction using ethanol as solvent at 180 bar/60  C/three cycles Liquid biphasic flotation solvent with 2-propanol as organic phase and (NH4)2SO4 as salt for the aqueous phase High-pressure homogenization using solvent water and recovered with hexane/isopropanol Pulsed electric fields with solventwater electric field, 5 kV cm 1; frequency, 2 Hz; temperature, 40  C; time, 1500 pulses of 1 s

Haematococcus pluvialis

Nannochloropsis sp. Nostoc commune

Fucoxanthin β-carotene

Phycobiliproteins, phycocyanin/ allophycocyanin, phycoerythrin Carotenoids, β-carotene, and lutein Carotenoids, β-carotene, and lutein Astaxanthin

Carotenoids

Phycocyanin

References MendesPinto et al. (2001) Silveira et al. (2007) Cha et al. (2010) MacíasSánchez et al. (2010) Kim et al. (2012) Dey and Rathod (2013) Juin et al. (2015)

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Bernaerts et al. (2020) Chittapun et al. (2020)

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Conflicts of Interest The authors have no conflict of interest to declare.

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Chapter 7

Molecular Engineering/Metabolic Engineering-Based Advanced Biotechnological Approach in Microalgal Biorefinery D. Vidya and K. Arunkumar

Abstract In the wake of an increase in nutritional problems along with depletion of fossil fuel resources and environmental problems, microalgal biorefineries emerged as an alternative feedstock for biofuels and other valuable coproducts. Microalgae is now crowned as efficient cell factories, having great potential in producing a variety of therapeutically active compounds/biomolecules including astaxanthin, lutein, canthaxanthin, docosahexaenoic acid (DHA), eicosapentaenoic acid (EPA), etc. Presently, microalgal biorefineries are not well established due to their high cultivation cost and low yield. To conquer this scenario, metabolic and genetic engineering techniques were widely applied. Modification of metabolic pathways by gene silencing or overexpressing to increase the accumulation of desired products is a widespread practice in metabolic engineering, while, in genetic engineering, strategies like RNA interference (RNAi), Zinc-finger proteins (ZNFs), Transcription activator-like effector nucleases (TALENs), and Clustered regularly interspaced short palindromic repeats CRISPR/CRISPR-associated protein 9 (CRISPR/Cas9) are used to intensify the quantity and quality of a targeted biomolecule. These transgenic microalgae help to reduce the techno-economic constraints related to the commercialization of microalgae biorefineries. Keywords Biorefineries · Biofuel · Astaxanthin · Genetic engineering · Metabolic engineering

Abbreviations ACC ACCase ACP

Acetyl-CoA carboxylase Acetyl-CoA carboxylase gene Acyl carrier protein

D. Vidya · K. Arunkumar (*) Phycoscience Laboratory, Department of Plant Science, Central University of Kerala, Kasaragod, Kerala, India © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 P. Verma (ed.), Micro-algae: Next-generation Feedstock for Biorefineries, Clean Energy Production Technologies, https://doi.org/10.1007/978-981-19-0680-0_7

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AIV AMPD BC CRISPR/Cas 9 DHA EPA FAD FDX5 HPV KAS MCA MCTK MFA MUFA PDAT PUFA RCA RNAi SAD SFA TALENs TE TRAIL UBC2 ZNF

7.1

Avian influenza virus AMP deaminase Biotin carboxylase Clustered regularly interspaced short palindromic repeats CRISPR/CRISPR-associated protein 9 (CRISPR/Cas9) Docosahexaenoic acid Eicosapentaenoic acid ω-3 fatty acid desaturase Ferredoxins-5 Human papillomavirus 3-ketoacyl-acyl carrier protein synthase gene Metabolic control analysis Malonyl-CoA ACP transacylase Metabolic flux analysis Monounsaturated fatty acid Phospholipid:diacylglycerol acyltransferase Polyunsaturated fatty acids Rubisco activase RNA interference Stearoyl-ACP-desaturase Saturated fatty acid Transcription activator-like effector nucleases Thioesterase Tumor necrosis factor-related apoptosis-inducing ligand Ubiquitin Zinc-finger proteins

Introduction

The overexploitation of petroleum-based fuels has resulted in the shortage of fossil fuels and greenhouse gas accumulation in the environment. The emission of CO2 from fossils during coal combustion is a major cause of various ecological and environmental problems. The generation of a huge amount of waste and its disposal causes an increase in the production cost. Studies reported that CO2 concentration in the atmosphere increased considerably, and this is the main cause of global climate change. To overcome these issues, fossil fuels must be replaced with renewable bioenergy resources. The concept of the microalgal biorefinery is a tool to surpass these obstacles (Ummalyma et al. 2019; Goswami et al. 2020). A biorefinery is the sustainable processing of biomass for the production of energy and marketable products like biofuels, chemicals, etc. Microalgal biorefineries are a reservoir of various bioproducts like biofuels, pharmaceuticals, and nutraceuticals. It facilitates the minimum use of resources, least amount of waste generation, and maximum

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benefits and profitability (Deprá et al. 2018; Bhardwaj et al. 2020; Kumar et al. 2020). The term microalga includes many different organisms capable of producing oxygen through photosynthesis. They have universal occurrence, and they are found in a variety of habitats like freshwater, seawater, on rocks, and on or within the plants and animals. Unicellular microalgae are well known for their importance in aquatic ecosystems, for their utility as environmental indicators, and to produce high-value compounds. Being a rich source of carbohydrates, protein, enzymes, fiber, vitamins, and minerals, microalgae are a major source of food, especially in Asian countries. The potential bioactive compounds such as primary and secondary metabolites of algal organisms have a great role in the pharmaceutical industry. Because of high oil content and rapid biomass production, microalgae have long been recognized as potentially good sources for biofuel production. Microalgae like cyanobacteria, which can fix atmospheric nitrogen, are effectively used as biofertilizers. Besides that, microalgae can be used as the best source of feed in aquaculture (Abedin and Taha 2008; Goswami et al. 2021a; Agrawal and Verma 2022). Even though microalgae have a wide range of advantages to be used as a biorefinery, technical difficulties like high production cost and low biomass yield are major constraints for its commercialization. Genetic and metabolic engineering in microalgae includes a group of techniques for the intentional manipulation of genetic material or metabolic pathways. Modification of wild type of microalgal species for increasing the biomass and bioproduct production through genetic and metabolic engineering will support the commercialization of microalgae biorefineries.

7.2

Microalgal Biorefineries

Microalgal biorefineries include the mass production of biomass for various industrially important bioproducts. The major attraction of microalgal biomass is the production of biofuels. It also has importance in the field of pharmaceutical and nutraceutical industries. They are a rich source of vitamins, proteins, lipids, and minerals such as iron, potassium, magnesium, calcium, manganese, and zinc. Microalgae were the richest source of proteins, amino acids, essential vitamins, and pigments such as chlorophyll, carotenoids, and phycobiliproteins. Majorly chlorella and spirulina are widely used as food because of their high protein content. Algae are the source of polyunsaturated fatty acids (PUFAs) in the food chain and thus provide essential fatty acids (Spolaore et al. 2006; Goswami et al. 2021b) Fig. 7.1 is a schematic representation of microalgae biorefinery. Algal lipids have become attractive because of the algal biodiesel production and their use in the cosmetic industry. Algal fatty acids are of three types, saturated fatty acid (SFA), monounsaturated fatty acid, and polyunsaturated fatty acids (PUFAs). Because of the health benefits, now commercial production of PUFA has been more

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Fig. 7.1 Schematic representation of microalgae biorefinery

focused. They are mainly synthesized in plants, bacteria, and microalgae. Seafood is a good source of PUFAs, but these are not sustainable sources. Microalgae such as phytoflagellates and dinoflagellates, green and red microalgae, and diatoms are a source of commercial omega-3 PUFAs, and macroalgae have also been shown to be a significant source of PUFAs (Eladel et al. 2019). Algal docosahexaenoic acid (22:6 ω3, 6, 9, 12, 15, 18), a commercially available ω3 PUFA, is produced by the microalgae Crypthecodinium cohnii (Walker et al. 2005). γ-Linolenic acid from Spirulina, arachidonic acid from Porphyridium, and eicosapentaenoic acid from Nannochloropsis, Phaeodactylum, or Nitzschia have already demonstrated industrial production potential (Spolaore et al. 2006) The cost of producing microalgal biomass and its conversion into economically valuable products is very huge when compared to the other energy sources. The production cost must be reduced for the sustainable use of microalgal biorefineries. Increasing the biomass and bioproducts with low production costs will attract the industries. Nowadays, studies on various genetic and metabolic engineering techniques for microalgal strain improvement have been performed worldwide. This chapter briefly discusses the genetic and metabolic engineering studies in microalgae for increasing biomass, lipids, biofuels, pigment, therapeutic proteins, and vaccines

7.3

Genetic Engineering Approach in Microalgal Biorefineries

Genetic engineering involves a group of techniques for the manipulation of the genetic material of an organism to alter, repair, or enhance form or function. It is made possible by recombinant DNA technology. Transgenic refers to the movement or insertion of a gene into an organism that normally does not have a copy of that gene. If the genes present in the reproductive cells are altered, the novel characteristics are passed to the next generation. If the genes in the somatic or vegetative cells are altered, the changes can affect that particular individual. Transgenesis is the

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Fig. 7.2 Genetic engineering in microalgae

process in which a new trait is introduced into the organism that was not inherited through normal reproduction (Robert and Baylis 2008; Chaturvedi et al. 2020). Transgenics in algae is a modern, complex, and fast-growing technology. The development of molecular genetic techniques like in vivo analysis of gene function and regulation, the manipulation of endogenous genes, and the introduction and expression of foreign genes will help and support algal research. Figure 7.2 represents an outline of microalgae genetic engineering. The development of molecular toolkits for some algal models, namely, Chlamydomonas reinhardtii and Volvox carteri, and the diatom Phaeodactylum tricornutum helped in understanding the basic biology in these organisms (Harris 2001; Falciatore and Bowler 2002). Researchers are making effort to develop such a toolkit for other commercially important algae, and DNA transformation has been achieved in species like Dunaliella salina and Haematococcus pluvialis (Rasul et al. 2017; Saini et al. 2021; Goswami et al. 2021c).

7.3.1

Biomass

Under the scenario of increased population rate and decreased fossil fuels, microalgae are attracted as a sustainable bioenergy source. But production cost and low biomass yield make them less favorable for commercial use. Enhancing microalgae biomass production by various biotechnological methods will make it favorable for domestic and commercial use. Genetic engineering of microalgae for stress tolerance and higher photosynthetic efficiency can enhance biomass productivity. Rubisco activase (RCA) is an enzyme that determines the rate of carbon fixation by regenerating catalytic sites. Overexpression of RCA in Nannochloropsis oceanica resulted in increased photosynthetic activity and biomass production (Wei et al. 2017). In C. reinhardtii, overexpression of ubiquitin (UBC2) resulted in increased cellular lipid content and growth rate (Fei et al. 2017). For biofuel production, researchers mostly depend on the microalgae Chlamydomonas reinhardtii. As it requires a warm environment for growth, it became unsuitable

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Table 7.1 Techniques used for gene manipulation in microalgae for increasing biomass yield Technique Abiotic stress tolerance

Species Schizochytrium Chlamydomonas reinhardtii

Observation Displayed higher growth rate and lipid productivity

Manipulation of Calvin cycle

S. elongatus Synechocystis Synechococcus sp. N. oceanica D. bardawil C. vulgaris C. reinhardtii N. gladitana

Increase in Rubisco activity Increased growth rate and photosynthesis

Optimizing light use efficiency

Improved solar energy conversion efficiency Higher photosynthetic productivity

Reference Zhang et al. (2018), Luo et al. (2015), Fei et al. (2017) Atsumi and Connor (2010), Wei et al. (2017), Liang and Lindblad (2017)

Kirst et al. (2012a, 2012b) Polle et al. (2003) Verruto et al. (2018)

for culturing in temperate regions. The RNAi-mediated gene knockdown of AMP deaminase (AMPD) resulted in the strain with a threefold higher growth rate and biomass and ~25% higher lipid/oil accumulation compared to wild type under both normal and cold growth conditions (Kotchoni et al. 2016). Manipulation of the Calvin cycle by overexpressing rbcL and rbcS genes in S. elongatus showed a 1.4fold increase in Rubisco activity (Atsumi et al. 2009). Overexpression of the same gene in Synechocystis also showed increased growth rate and photosynthetic activity (Liang and Lindblad 2017). Enhancing photosynthetic activity and cell growth in C. vulgaris by introducing cyanobacterial fructose 1,6-bisphosphate aldolase represented the role of aldolase in promoting the regeneration of ribulose 1,5-bisphosphate in the Calvin cycle (Yang et al. 2017). Unequal distribution of light is another challenge faced by the large-scale cultivation of microalgae. In such cultivation systems, the light will not penetrate to the deeper layer, and it affects the photosynthetic activity of microalgae in the bottom layer. Engineering of chlorophyll antenna to eliminate the excess light absorption and increased photosynthetic capacity under low and high sunlight is achieved in C. reinhardtii. The mutant with a truncated antenna showed improved solar energy conversion efficiency and photosynthetic productivity (Kirst et al. 2012a, b; Goswami et al. 2021d). Furthermore, suppression of tla1and tla2 (CpFTSY) in the same mutant also showed higher photosynthetic activity (Polle et al. 2003; Kirst et al. 2012a, b). Table 7.1 shows the various gene manipulation techniques used in microalgae for increased biomass production.

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Pigments

The engineering of genes directly related to carotenoid biosynthesis will help to improve the cellular carotenoid content. For increasing the astaxanthin accumulation in Haematococcus pluvialis, the mutated pds gene has been overexpressed. The mutant showed a 26% increase in the total carotenoid content (Steinbrenner and Sandmann 2006). In C. zofingiensis, overexpression of an endogenous mutated PDS gene resulted in a 32.1% increase in total carotenoids (Liu et al. 2014). Introducing the bkt gene from H. pluvialis along with chloroplast targeting in D. salina showed a higher BKT expression than the wild type. The mutant showed the presence of astaxanthin and canthaxanthin (Anila et al. 2016). A 2.6-fold increase in lutein accumulation was shown by Chlamydomonas reinhardtii when D. salina-derived PSY encoding gene was overexpressed (Couso et al. 2011). When the PSY encoding gene from Chlorella zofingiensis was overexpressed in the nucleus of C. reinhardtii, a 2.2-fold increase in lutein was reported (Cordero et al. 2011).

7.3.3

Lipid and Biofuel

Oil-rich algae which synthesize a very high amount of lipid are the convenient source of biofuels. Understanding the molecular mechanism behind the lipid biosynthesis in algae will help to improve the algal strain and therefore enhance biofuel production. Manipulation of genes involved in lipid biosynthesis is a major way of increasing intracellular lipid content in microalgae. Besides that, many other strategies like stopping other metabolic pathways which affect lipid biosynthesis and modifying fatty acid profiles are widely used techniques. Table 7.2 gives an overview of several techniques used for oil enhancement in microalgae. Increasing the lipid biosynthesis by increasing the fatty acid supply was first attempted in Cyclotella cryptica. In this study, acetyl-CoA carboxylase gene (ACCase), which codes for the enzyme that carboxylates acetyl-CoA to malonylCoA, was overexpressed. A two- to threefold increase in the ACCase activity has been observed with no changes in the lipid content (Dunahay et al. 1995). The overexpression of a subunit of ACCase (accD) along with malic enzyme (ME) was successful in elevating the total lipid content in microalgae D. salina (Talebi et al. 2014). ME is a key enzyme involved in various metabolic reactions like lipogenesis, photosynthesis, and energy catabolism. ME gene overexpression in Phaeodactylum tricornutum significantly enhanced enzyme activity and resulted in a 2.5-fold increase in lipid content (Xue et al. 2015). Overexpression of the acetyl-CoA synthase (ACS) gene in Schizochytrium sp. made an increase in biomass productivity and improved FA profile (Yan et al. 2013). When the same gene was overexpressed in C. reinhardtii, a twofold increase in TAG content was resulted (Rengel et al. 2018).

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Table 7.2 Techniques used for oil enhancement in microalgae Technique used Enhancing fatty acid biosynthesis Manipulation of carbon partitioning

Increasing intracellular reducing equivalents Blocking TAG hydrolysis Increasing TAG content (single-gene) Increasing TAG content (multiple gene) Manipulation of transcription regulators Modifying fatty acid profile

Species C. cryptica, D. salina, Schizochytrium sp., C. reinhardtii, C. merolae P. tricornutum, C. reinhardtii, Coccomyxa sp., T. pseudonana, F. solaris, C. minutissima C. pyrenoidosa, C. reinhardtii P. tricornutum, P. tricornutum, T. pseudonana, C. reinhardtii C. reinhardtii, C. minutissima, N. oceanica, T. pseudonana, S. obliquus C. minutissima, P. tricornutum C. reinhardtii, N. salina, N. gaditana P. tricornutum, D. tertiolecta, C. reinhardtii, N. oceanica, C. vulgaris

References Dunahay et al. (1995), Yan et al. (2013), Talebi et al. (2014), Rengel et al. (2018); Agrawal et al. (2020) Li et al. (2010), Ma et al. (2014), Muto et al. (2015), Xue et al. (2015), Takahashi et al. (2018) Fan et al. (2015a, b), Huang et al. (2015) Trentacoste et al. (2013), Xiang Wang et al. (2015), Wang et al. (2018) Boyle et al. (2012), Hsieh et al. (2012), Deng et al. (2013) Hsieh et al. (2012), Zou et al. (2018) Deng et al. (2015), Zalutskaya et al. (2015), Ajjawi et al. (2017) Radakovits et al. (2012), Hwangbo et al. (2014), Kaye et al. (2015), Lin et al. (2018), Norashikin et al. (2018)

Suppression of starch biosynthesis and directing the carbon flux towards TAG biosynthesis is another strategy used for increasing lipid productivity in microalgae. Transformation by suppressing starch biosynthesis resulted in higher lipid production with a lower growth rate. Strachless mutants of Coccomyxa sp. with a defective gene for the large subunit of AGPL showed an increased lipid content, but the growth rate was low when compared to the parental (Takahashi et al. 2018). Neutral lipid accumulation in the diatom Phaeodactylum tricornutum was increased up to 82% by antisense knockdown of the pdk gene (Ma et al. 2014). Endogenous glycerol kinase (GK) gene overexpression in Fistulifera solaris accelerated glycerol metabolism, biomass productivity, and a 12% increase in lipid productivity (Muto et al. 2015). An increase in intracellular reducing agents like NAD(H) and FDX also plays an important role in switching the starch metabolism to lipid biosynthesis. In Chlorella pyrenoidosa, overexpression of NAD(H) kinase gene from Arabidopsis resulted in increased cellular lipid content by 110.4%, without reducing growth rate (Fan et al. 2015a, b). Transgenic Chlamydomonas reinhardtii with overexpression of ferredoxins (FDX5) showed increased starch and oil yields (Fan et al. 2015a, b). Stopping the breakdown of TAG from storage lipids for increasing the lipid content is practiced in many microalgal species. The tgl1 gene which codes for the TAG lipases is knocked down in P. tricornutum by antisense RNA approach. The mutant

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showed a strong increase in TAG compared to the wild by blocking the catabolism of TAG (Barka et al. 2016). Heterologous gene expression in microalgae for lipid accumulation is now practiced widely. The model system C. reinhardtii was used to investigate the effect of GPDH and LPAAT on lipid production in microalgae. The codon-optimized LPAAT gene from Brassica napus and GPDH1 from Saccharomyces cerevisiae were heterologously expressed in Chlamydomonas, and it resulted in a 44.5% and 67.5% increase in lipid contents, respectively (Wang et al. 2018). Phospholipid: diacylglycerol acyltransferase (PDAT) catalyzes synthesis of TAG in Chlamydomonas reinhardtii. Exogenous PDAT from Saccharomyces cerevisiae was expressed in C. reinhardtii to study the lipid accumulation. It increased the contents of total fatty acids (FAs) and TAG by 22% and 32% (Zhu et al. 2018). A codon-optimized soybean DOF-type TF gene (GenBank ID: DQ857261.1) was subsequently heterologously expressed in Chlamydomonas, and the resulting transgenic lines had an up to a twofold increase in lipid content (Ibáñez-Salazar et al. 2014). Indeed, Chlamydomonas encodes one putative Dof gene (Cre12.g521150. t1.2) and its protein shared over 70% amino acid sequence identity to the known soybean Dof (Ibáñez-Salazar et al. 2014). A possible role of heterologous Dof on intrinsic Dof-binding genomic sequences could be anticipated.

7.3.4

Therapeutic Proteins and Vaccines

The first report of the expression of mammalian protein in the chloroplast was achieved in C. reinhardtii. A high level of protein accumulation has resulted when a large single-chain antibody (HSV8-lsc) of the herpes simplex virus was expressed in the chloroplast (Mayfield et al. 2003). A single-chain variable antibody expression resulted in a 0.54% accumulation of protein (Mayfield and Franklin 2005). Expression of CTB-VP1 gene coding for cholera toxin B subunit fused to foot and mouth disease VP1 resulted in the accumulation of protein up to 3% of the total soluble protein (Sun et al. 2003). The expression of the human metallothionein-2 gene having an anti-radiation function was demonstrated to improve the survivorship of transgenic algae compared to wild-type algae (Zhang et al. 2006). The densitometric analysis by Western blot of protein showed accumulation up to 0.43–0.67% TSP when the human tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) protein is expressed in the chloroplast (Yang et al. 2006). The classical swine fever virus E2 structural protein was expressed in the chloroplast, and the ELISA quantification showed the accumulation of the E2 protein to 1.5–2% TSP (He et al. 2007). An important autoantigenic marker in type I diabetes, human glutamic acid decarboxylase (hGAD65), was also expressed in the chloroplast of Chlamydomonas and accumulated up to 0.25–0.3% TSP (Wang et al. 2008). The human IgG1 monoclonal antibody, against anthrax protective antigen 83 (83K7C), was expressed in the chloroplast of Chlamydomonas (Tran et al. 2009). Accumulation of 10.5% of TSP was achieved, while the white spot syndrome virus protein 28 (VP28) was

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expressed in the chloroplast (Surzycki et al. 2009). The possibility of alga-derived oral vaccine was first demonstrated by Dreesen et al. (2010) through feeding the transgenic algae to the mouse and induced resistance against lethal doses of S. aureus. The transformation was done by a fusion gene with D2 fibronectinbinding domain from a Staphylococcus aureus protein and the B subunit of cholera toxin and expressed in the chloroplast. The expression of seven human proteins in the chloroplast was studied by Rasala et al. (2010). In the seven proteins, 50% was expressed at levels sufficient for commercial production. Three was expressed at 2–3% of total soluble protein, while a fourth protein accumulated to similar levels when translationally fused to a well-expressed serum amyloid protein. Using different molecular tools, a variety of therapeutic proteins have been produced in the microalgal chloroplast. The first report of the therapeutic vaccine in algae is the mucosal vaccine by fusion of CTB adjuvant with structural protein VP1 of foot-and-mouth disease virus. The total soluble protein yield was 3% (Sun et al. 2003). Swine pathogen expression in Chlamydomonas was studied by He et al. (2007). An expression vector containing structural protein E2 of the classical swine fever virus has been transferred to the chloroplast of Chlamydomonas. ELISA quantification of the transformants showed the accumulation of 1.5–2% E2 protein. The white spot syndrome virus protein VP28 was used in one study to identify the expression level in the chloroplast. The codon-optimized gene was inserted into the plasmid and transformed into the chloroplast. The result indicates VP28 protein synthesized up to 28% of TCP (Surzycki et al. 2009). Chloroplast transformation of C. reinhardtii with two genes, acrV and vapA, which encode antigens from the fish pathogen Aeromonas salmonicida resulted in a dramatic increase in the recombinant protein accumulation. A study by comparing the expression of promoters and different 5’UTR of four chloroplast gene in bacterial genome indicated limited expression of chloroplast transgenes due to negative feedback loops. It demonstrates that alteration of the negative feedback loop by manipulating anterograde signaling will improve transgene expression (Michelet et al. 2011). Testing algal chloroplast to produce malaria transmission-blocking vaccine candidates, Plasmodium falciparum surface proteins 25 (Pfs25) and 28 (Pfs28), is another promising study in synthetic biology. The antibodies will recognize Pfs25 and Pfs28 and disrupt the sexual development of parasites within the mosquito midgut, thereby preventing the transmission of malaria from one human host to the next. The result demonstrated that the antigen produced by algal chloroplast is structurally similar to native proteins and exhibits transmission-blocking activity (Gregory et al. 2012). Production of malaria transmission-blocking proteins Pfs48/ 45 is another study conducted in algae chloroplast. Study shows that the C-terminal antigenic region of the Pfs48/45 antigen can be expressed in the chloroplast of the green algae C. reinhardtii (Jones et al. 2013). The E7 protein of the human papillomavirus (HPV) type 16, is a key antigen for developing therapeutic vaccines against HPV-related lesions and cancers. Production of this vaccine antigen in Chlamydomonas reinhardtii chloroplast is practiced

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by Demurtas et al. (2013). A mutated, attenuated form of the E7 oncoprotein E7GGG was introduced into the C. reinhardtii chloroplast genome by homologous recombination. Subcutaneous injection of total algal extract and affinity-purified protein in mice showed induction of specific anti-E7 IgGs and E7-specific T-cell proliferation. In another study, the oncoprotein E7GGG fused with the bacterial aadA gene was introduced to the algae chloroplast. Subcutaneous injection of algal extract into mice showed high production of E7-specific antibodies but low activation of E7-specific CD8+ cells (Vlasák et al. 2013). Expressing HA protein of avian influenza virus (AIV) in microalga chloroplast to produce recombinant antigens was a new approach to control a serious problem in poultry farming. The HA protein of AIV in C. reinhardtii showed antigenic activity by Western blot test and through its application in chickens (Castellanos-Huerta et al. 2016). Producing recombinant allergen in algal chloroplast for the treatment of allergic disease was an approach made for allergen immunotherapy. The pollen allergen Bet v gene was synthesized and integrated into the microalga C. reinhardtii. The transformants showed expression of the allergen with yields between 0.01% and 0.04% of TSP and displayed similar secondary structure elements as the Escherichia coli-produced reference allergen (Hirschl et al. 2017). The genes expressing variable domain of camelid heavy chain-only antibodies (VHH) targeting botulinum neurotoxin were expressed in the chloroplast of green algae for producing soluble proteins capable of binding and neutralizing botulinum neurotoxin. The produced antibody domains bind to botulinum neurotoxin serotype A (BoNT/A) with similar affinities as camelid antibodies produced in Escherichia coli, and they are similarly able to protect primary rat neurons from intoxication by BoNT/A (Barrera et al. 2015).

7.4

Metabolic Engineering Approach in Microalgal Biorefineries

Metabolic engineering is the utilization of recombinant DNA for the modification of metabolic pathways. It includes the production of novel metabolites by inserting new pathways, heterologous peptide production, and improvement of the existing pathways. Improvement of a metabolic pathway using genetic engineering requires understanding the underlying techniques like detailed physiological studies, metabolic flux analysis (MFA), metabolic control analysis (MCA), thermodynamic analysis of pathways, and kinetic modeling (Nielsen 1998). Coupling of metabolic engineering approach with high-throughput computing facilitates the enhancement of multiple traits like product concentrations, yield, productivity, and tolerance (Gan et al. 2016). Metabolic engineering in microalgae mainly focused on enhancing the production of secondary metabolites like fatty acids, steroids, lectins, carotenoids,

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polysaccharides, polyketides, and toxins. Among these, strain improvement for microalgae biofuel production was the widely studied area (Jang et al. 2012).

7.4.1

Pigment

Metabolic engineering of microalgae for increased carotenoid production is first reported in C. reinhardtii. Expression of an archeal heat-stable geranylgeranylpyrophosphate synthase (Fukusaki et al. 2003), nuclear overexpression of the betacarotene ketolase (bkt3), and bkt1 gene from H. pluvialis (León-Bañares et al. 2004) are studied in C. reinhardtii. The resulting mutant does not show carotenoid synthesis. Nuclear transformation of C. reinhardtii with phytoene synthase gene (psy) reported an increase in carotenoid content. Furthermore, point mutation of endogenous pds gene in C. reinhardtii accumulated more lutein, beta-carotene, zeaxanthin, and violaxanthin in vivo (Liu et al. 2013).

7.4.2

Lipid and Biofuel

For the industrial production of microalgal biofuels, the metabolic performance needs to be improved. Understanding the complex lipid metabolic pathway of microalgae is needed before creating the improved strain for biodiesel production. Introduction of acetyl-CoA carboxylase gene (ACC) from Cyclotella cryptica into two species of diatoms, C. cryptica and Navicula saprophila, showed no increase of lipids in the cells (Sheehan et al. 1998). This study showed cloning of single genes related to fatty acid synthesis did not increase the fatty acid contents. Recently, cloning of multiple genes related to fatty acid biosynthesis in Haematococcus pluvialis has been carried out. Cloning of seven fatty acid synthesis-related genes, viz., 3-ketoacyl-acyl carrier protein synthase gene (KAS), acyl-acyl carrier protein thioesterase (FATA), ω-3 fatty acid desaturase (FAD), acyl carrier protein (ACP), malonyl-CoA:ACP transacylase (MCTK), biotin carboxylase (BC), and stearoylACP-desaturase (SAD), and RNA expression analysis showed a mismatched gene expression and fatty acid synthesis (Lei et al. 2012). In Chlamydomonas reinhardtii, a starchless mutant showed 15-fold increase in lipid synthesis (Wang et al. 2009). Inactivation of ADP-glucose pyrophosphorylase in this starchless mutant resulted in a tenfold increase in lipid accumulation (Li et al. 2010). In Phaeodactylum tricornutum, overexpression of thioesterase PtTE increased total fatty acid synthesis to 72% (Gong et al. 2011). The metabolic pathway can be manipulated by protein-protein interactions. Interaction of fatty acid acyl carrier protein (ACP) and thioesterase (TE) in C. reinhardtii resulted in an increased level of short-chain fatty acids. Here the TE functionally interacts with CrACP to release fatty acids (Blatti et al. 2012).

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Economic Feasibility

Microalgae are attracted for their pharmaceuticals, nutraceuticals, and other bioactive compounds. But microalgal biorefineries are now not feasible for commercialization due to their production cost, low yield, and absence of suitable marketing cost. Genetic and metabolic engineering place a vital role in strain improvement and therefore surpass the issues. Increasing biomass and lipid content by genetic engineering will help for the production of renewable biofuel. Improvement in the production of high-value compounds like carotenoids will attract the pharmaceutical and nutraceutical industry. However, genetically modified algae with an optimized photobioreactor will overcome the issues related to the quantity and quality of the bioproducts.

7.6

Conclusion

The utilization of various genetic and metabolic engineering approaches for microalgal biorefineries mainly focuses on minimizing production costs. Among the genetic engineering techniques used for strain improvement, some of them resulted in a genetically modified organism with increased biomass and bioproduct production. But metabolic engineering of microalgae does not yield consistent results. A powerful and successful microalgal biorefinery needs a strong foundation of extensive research using emerging new technologies. Acknowledgments The authors are grateful to the Central University of Kerala for providing the necessary help and support. The authors like to thank CSIR for the financial support. Competing Interests All the authors declare that they have no competing interests.

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Chapter 8

Algae-Bacteria Interactomics Unveils Their Role in Growth and Production of High-Value Biorenewables Abdalah Makaranga and Pannaga P. Jutur

Abstract Microalgae cultivation for biomass and related value biorenewables is gaining interest not only in the research community but also in the industry sector. Many auxotrophic microalgae have been found to be high in critical micronutrients such as vitamin B, although the source is unknown. Although certain microalgae have been shown to be able to synthesize essential micronutrients, many other auxotrophic microalgae have been found to require exogenous metabolites for growth in culture, implying that they are unable to synthesize themselves. Some of the important micronutrient-dependent pathways in auxotrophic microalgae are activated by the extracellular metabolites released by microbes in their natural environment. As a result, there has been a lot of interest to employ extracellular metabolite-producing microorganisms for microalgal culture supplementation at a laboratory scale. This chapter elaborates on previous research on the impact of bacterial functional metabolites on microalgae as well as future potential in industrial applications. Keywords Microalgae · Biorenewables · Interactome · Genetic engineering · Metabolomics · Microorganism

Abbreviations IAA LCMS OGDH PDH

Indole-3-acetic Liquid chromatography with mass spectrometry (LCMS) Oxoglutarate dehydrogenase Pyruvate dehydrogenase

A. Makaranga · P. P. Jutur (*) Omics of Algae Group, Industrial Biotechnology and DBT-ICGEB Centre for Advanced Bioenergy Research, International Centre for Genetic Engineering and Biotechnology, Aruna Asaf Ali Marg, New Delhi, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 P. Verma (ed.), Micro-algae: Next-generation Feedstock for Biorefineries, Clean Energy Production Technologies, https://doi.org/10.1007/978-981-19-0680-0_8

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Tricarboxylic acid Transketolase Thiamine pyrophosphate

Introduction

Microalgae have received a lot of interest for commercial applications, despite the fact that the algae-bacterial interactions are generally regarded as contaminants (Ramanan et al. 2015). Axenic cultivation is very susceptible to contamination, which can result in capital and productivity losses during the process (Hu et al. 2019). This is stimulating significant interest in the concept of utilizing microorganism-microalgae consortia. Several high-value biorenewables from microalgae have already been exploited, such as β-carotene (Mojaat et al. 2008; Goswami et al. 2021a), astaxanthin (Zhang et al. 2009; Saini et al. 2021), lutein (Garbayo et al. 2008), glycerol (Phadwal and Singh 2003), and others (Padmaperuma et al. 2018; Agrawal et al. 2020; Agrawal and Verma 2022). Although still not applicable within all cell systems, the co-culture technique has been demonstrated to increase microalgal biomass and high-value products (Dong and Zhao 2004). Furthermore, it reduces the overall expenditure in terms of production with economically feasible industrial processes (Hu et al. 2019). Interactions between algae and bacteria consortium hold the promise of commercializing these bioproducts and understanding their associations involving cross talk between primary metabolites including carbon dioxide (CO2)-oxygen (O2) exchange, growth mediators such as phytohormones and/or vitamins, and recycling of essential nutrients (such as phosphorous, nitrogen) in the aquatic ecosystems (Higgins et al. 2018a, b; Cirri and Pohnert 2019; Yao et al. 2019; Goswami et al. 2021b; Fallahi et al. 2021). Exogenous compounds produced by bacteria have raised interest among the community to understand their role in microalgal growth and production of biorenewables such as vitamin B (Croft et al. 2005; Kazamia et al. 2012; Grant et al. 2014; Durham et al. 2015; Higgins et al. 2018a, b), phytohormones (De-Bashan et al. 2008; Choix et al. 2014; Amin et al. 2015; Segev et al. 2016; Goswami et al. 2021c; Peng et al. 2021), and siderophore complex (Leyva et al. 2014; Kim et al. 2014; Villa et al. 2014; Rajapitamahuni et al. 2019; Peng et al. 2021) (Table 8.1). For example, most of the microalgal strains are autotrophs and depend on vitamins synthesized by bacteria (Tandon et al. 2017; Bhardwaj et al. 2020). Henceforth, these interactions, in turn, are dependent on different biosynthetic pathways for vitamin processing (Cruz-Lopez and Maske 2016). Also, the addition of phytohormones in the production of high-value biorenewables has gained significance because of their effectiveness in the enrichment of algal biomass. Studies have shown that bacteria Azospirillum brasilense release phytohormones that cause considerable alterations in the metabolism of the strains, i.e., Chlorella vulgaris

Siderophores

Phytohormones

Bacterialexogenous metabolites Vitamins

Azotobacter vinelandii

Azospirillum brasilense and Azospirillum lipoferum Sulfitobacter Azospirillum brasilense, Bacillus megaterium, and Escherichia coli Idiomarina loihiensis RS14

Neochloris oleoabundans, Neochloris oleoabundans, and Scenedesmus sp. BA032

Chlorella variabilis ATCC 12198

Diatom Green microalgae

Chlorella sorokiniana and Auxenochlorella protothecoides Chlorella vulgaris

Phaeobacter inhibens

Azospirillum brasilense

Azospirillum brasilense

Chlorella sorokiniana

Winery wastewater bacteria Chlorella vulgaris and Chlorella sorokiniana Chlorella vulgaris and Chlorella sorokiniana Emiliania huxleyi

Amphidinium operculatum Chlamydomonas nivalis

Halomonas sp. Mesorhizobium sp.

Azospirillum brasilense

Microalgae Lobomonas rostrata Thalassiosira pseudonana CCMP1335

Bacteria Mesorhizobium loti Ruegeria pomeroyi DSS-3

Promotes growth along with lipids and proteins Promotes growth

Promotes growth but ultimately leads to death Promotes growth and lower neutral lipids and starch Promotes growth

Lipid and chlorophyll a and b, lutein, and violaxanthin Starch, lipid, and fatty acid

Biological role/function(s) Promotes growth

(continued)

Rajapitamahuni et al. (2019) Villa et al. (2014)

De-Bashan et al. (2008) Amin et al. (2015) Peng et al. (2021)

Einat Segev et al. (2016) Peng et al. (2020)

References Grant et al. (2014) Durham et al. (2015) Croft et al. (2005) Kazamia et al. (2012) Higgins et al. (2018a, b) De-Bashan et al. (2002) Choix et al. (2012)

Table 8.1 A summary of studies on the impact of extracellular metabolites from bacteria on microalgal growth and high-value biorenewables

8 Algae-Bacteria Interactomics Unveils Their Role in Growth and. . . 167

Bacterialexogenous metabolites

Marinobacter sp. Azospirillum brasilense

Bacteria Marinobacter sp. Halomonas sp. Pelagibaca sp. Halomonas sp.

Table 8.1 (continued)

Scrippsiella trochoidea Chlorella vulgaris and Chlorella sorokiniana

Dunaliella bardawil

Microalgae Dunaliella salina

Biological role/function(s)

References Baggesen et al. (2014) KeshtachereLiebson et al. (1995) Amin et al. (2015) Amin et al. (2015), Leyva et al. (2014)

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and Chlorella sorokiniana (De-Bashan et al. 2008; Peng et al. 2021). Studies demonstrate that the high-value biorenewables which include pigments such as lutein and violaxanthin were increased along with the significant increase in lipid content (De-Bashan et al. 2002; Peng et al. 2021). Also, the addition of phytohormones to these heterotrophic bacteria synthesizes siderophores, the small organic molecules that tightly bind with nitrogen and iron, which results in enhanced solubility and also availability for microalgae (Vraspir and Butler 2009; Villa et al. 2014). Exogenous supplementation of synthetic vitamins and phytohormones in microalgae cultivation is reported to enhance the production of high-value biorenewables (Renuka et al. 2018; Vijay et al. 2021). However, the functional mechanism of these exogenous vitamins, phytohormones, and siderophores on microalgae remains unclear. Henceforth, the understanding of interactions between microalga and bacteria is crucial for the future production of high-value biorenewables. In this chapter, our focus was to discuss the biology of bacterial-associated exogenous metabolites, vitamins, phytohormones, and siderophores, followed by beneficial impacts on microalgal growth and high-value biorenewables. Furthermore, we have also discussed new potential strategies that can be used to produce sustainable high-value biorenewables with industrial significance.

8.2 8.2.1

Bacterial Metabolites Enhancing Growth and High-Value Biorenewables in Microalgae The Effect of Bacterial-Associated Exogenous Vitamins

Microalgae generally obtain vitamins via bacterial metabolic by-products in nature, and the quantity of vitamins is regulated by the size and diversity of the bacterial populations (Higgins et al. 2018a, b). Microalgae exhibit auxotrophy for vitamins B1, B7, and B12, and all these vitamins are normally acquired through bacteria (Higgins et al. 2018a, b). The majority of microalgae depend on different types of vitamins (Tandon et al. 2017). Numerous studies have revealed that variants of these vitamins are important for a wide range of microalgae species including vitamin B12 (Croft et al. 2005), vitamin B1 (Lonsdale 2006; Higgins et al. 2018a, b), and vitamin B7. Each one of these vitamins is generated by bacteria and may interact positively with microalgae (Yao et al. 2019). In co-culture media, Limonia rostrata bacteria regulate vitamin B12 levels and promote the growth of the vitamin B12-dependent L. rostrata in exchange with fixed carbon, resulting in a mutualistic relationship (Grant et al. 2014). Additionally, Ruegeria pomeroyi DSS-3 restored B12 depleted in Thalassiosira pseudonana, enhancing growth rates when supplemented with vitamin B12 exogenously (Durham et al. 2015). Also, the metE gene expression was reduced in co-cultured studies with Chlamydomonas reinhardtii and Mesorhizobium loti (Kazamia et al.

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2012). In conclusion, this study demonstrates that the C. reinhardtii does not require vitamin B12 for growth since it expresses a B12-independent methionine synthase metE gene which is inhibited by exogenous B12 (Kazamia et al. 2012). Thiamine is required by green algae to produce vitamin B1 thiamine pyrophosphate (TPP), a well-known mediator in the metabolism of carbohydrates and amino acids (Lonsdale 2006). TPP is required for pyruvate dehydrogenase (PDH), which transforms pyruvate to acetyl-CoA, followed by their entry into the tricarboxylic acid (TCA) cycle, and/or will be utilized to synthesize fatty acids. TPP also is a cofactor for oxoglutarate dehydrogenase (OGDH), which transforms ketoglutarate into succinyl-CoA in the TCA cycle, and transketolase (TK), which catalyzes reversible events in the pentose phosphate pathway and the Calvin-Benson cycle involved in the CO2 assimilation (Higgins et al. 2018a, b). Studies on two strains of green algae, i.e., C. sorokiniana and Auxenochlorella protothecoides, demonstrate enhanced growth rates using winery-treated wastewaters. The native bacterial populations in winery wastewaters were sequenced, and the findings reported the existence of vitamins B1, B7, and B12, meanwhile liquid chromatography with mass spectrometry (LCMS) and bioassays has revealed the role of thiamine metabolites isolated from the winery wastewaters. Vitamins B1, B7, and B12 are predicted to increase microalgal growth rates in A. protothecoides, which cannot produce thiamine within the cells (Higgins et al. 2018a, b).

8.2.2

The Effect of Phytohormones on Microalgae

Plant growth-promoting bacteria have received significant attention as enhancers of algal growth via the release of phytohormones (De-Bashan et al. 2008; Kim et al. 2014; Amavizca et al. 2017). As stated above, few studies have demonstrated the importance of phytohormones in controlling stress responses in microalgae. Nitrogen (N) signaling in microalgae is strongly influenced by the presence of these phytohormones. For example, when N is low, the levels of cytokinins and gibberellins decline, whereas auxins and abscisic acid had increased significantly. The fundamental mechanism of such signaling and stress response is highly dependent on the ratio of their concentrations. However, the evidence for their existence and function of phytohormones in microalgae needs more attention (Lu and Xu 2015). Conversely, molecular studies have shown that phytohormones promote growth in algae along with other biomolecules. For example, the study involving bacteria A. brasilense adhering to C. vulgaris and C. sorokiniana significantly enhanced the production of carbohydrates (Choix et al. 2012, 2014), lipids (De-Bashan et al. 2008), fatty acids (Leyva et al. 2014), and pigments (De-Bashan et al. 2008) in these microalgae. Also, experiments have shown that co-cultures and the addition of indole-3-acetic acid (IAA) externally stimulated growth in C. sorokiniana (Peng et al. 2020), whereas the substantial decrease in triacylglycerols and starch content has been reported during the exponential growth. Such studies indicate the role of bioactive constituents to be transient or the cell anchorage is essential for the transfer

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of these molecules produced from secretions of A. brasilense (Peng et al. 2020). Overall, the findings suggest that IAA and A. brasilense mobilize the transfer of cellular energy resources towards enhancing growth (Peng et al. 2020). Segev et al. (2016) observed that the bacterium Phaeobacter inhibens interacts with Emiliania huxleyi, thus promoting growth initially but eventually leading to cell toxicity followed by death (Segev et al. 2016). The production of IAA in P. inhibens and attachment to E. huxleyi are significantly increased in the presence of tryptophan that has been well documented in Segev et al. (2016) (Table 8.1).

8.2.3

Role of Siderophores

Iron uptake is one of the most fascinating processes that may require interactions between microalgae and bacteria cells. Mostly, iron is required for photosynthesis and respiration, but due to its poor solubility and extremely low concentration, they restrict primary production and bacterial growth in the photic zones of aquatic ecosystems. In this context, few marine bacteria and cyanobacteria tend to produce siderophores, which are tiny organic molecules that bind strongly with iron to enhance their solubility (Vraspir and Butler 2009). These siderophores are subsequently adsorbed by bacteria via outer membrane receptors that are unique based on the nature of siderophores (Vraspir and Butler 2009). Microalgae are not capable of producing siderophores but can adhere directly (Kustka et al. 2007). Reports have demonstrated that the diatoms/green algae are capable of adsorbing to iron from siderophores and/or other chelates via ferric reductases and iron transporters present on their outer cell membranes (Kustka et al. 2007) (Table 8.1). These siderophores form a complex with the insoluble ferric iron and bind to the bacterial cell’s surface. Microalgae utilize Fe (III) complex as part of the reduction mechanism. Furthermore, the Fe (III) siderophore complex is converted by bacteria cell into the soluble ferrous form Fe (II) which is then accessible for growth by the microalgae. Bacteria is able to synthesize vitamin B12 together with siderophores for improving the yield of biomolecules, i.e., pigments, lipids, and carbohydrates with better growth rates. For example, Rajapitamahuni et al. (2019) reported that co-culture of siderophore-producing bacteria Idiomarina loihiensis RS14 with Chlorella variabilis ATCC12198 enhanced growth by 20% dcw (Rajapitamahuni et al. 2019) with an increase in lipid and protein contents subjected to iron deficiency (Rajapitamahuni et al. 2019). In another study, the green algal strains Neochloris oleoabundans and Scenedesmus sp. employ the Azotobacter vinelandii siderophore as a source of nitrogen for sustainable growth. Furthermore, bacterial siderophore complexes exist in a variety of chemical forms with different nitrogen capacities as demonstrated by Villa et al. (2014) and Yoneyama et al. (2011). These interactions are able to fix nitrogen under aerobic conditions with sucrose or glycerol as the source of carbon (Villa et al. 2014). Thus, it remains unique from other nitrogen-fixing

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Fig. 8.1 Illustrating the role of siderophores produced by bacterial cells when iron is scarce

bacteria, which may require either anaerobic or aerobic conditions (Setubal et al. 2009; Villa et al. 2014). This characteristic also distinguishes A. vinelandii as a potential candidate for co-culture with oxygen-producing microalgae for the production of high-value biorenewables (Ortiz-Marquez et al. 2012; Villa et al. 2014). Also, iron is scarce in aquatic ecosystems and is only present in the insoluble form Fe (III) where microalgae cannot utilize in this form (Fig. 8.1). Henceforth, the bacteria secrete siderophores with strong iron-chelating properties, allowing iron absorption, and thus will be accessible by microalgae for cellular metabolism (Kraepiel et al. 2009; Yoneyama et al. 2011).

8.3

New Perspectives and Concluding Remarks

The understanding of the regulatory mechanisms will contribute towards the role of interactions between microorganism-microalgae consortia which may further assist in the design of biorefinery processes for enhanced production of biomass and highvalue biorenewables (Fuentes et al. 2016; Goswami et al. 2020). In natural environments, different forms of interactions exist, and innovative solutions for increased high-value biorenewables utilizing interactions of these bacterial species have been proposed, and the underlying molecular mechanisms of such interactions are rarely elucidated. One important reason for the absence of such studies is the difficulty in establishing the approach for separating microalgae and bacterium consortium, which requires considerable integrative biology abilities (Heo et al. 2019). Recently,

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a simple and cost-effective approach for determining the unique mechanism of understanding their interactions between microalgae and bacteria employing laboratory setup has been demonstrated. In this study, they identified the target bacterial genome broad genes whose products promote Chlorella vulgaris growth using a whole array of Escherichia coli K-12 ORF clones (Heo et al. 2019, 2020). In conclusion, the designing of a cost-effective and sustainable algae-bacteria system for the production of high-value biorenewables is the futuristic solution for algal biorefineries. Competing Interest The authors have no competing interest to declare.

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Chapter 9

Microalgae and Cyanobacteria: A Potential Source for Drug Discovery Using Genome Mining Approach David Wiseman Lamare and Neha Chaurasia

Abstract Drug discovery has been one of the most widely studied areas of research in the field of science and technology; a new disease has been emerging every year, but the rate of drug discovery in comparison is very low. Fungi, bacteria, and plants have been the major contributors in drug discovery for many decades, but recent studies have shown two major candidates microalgae and cyanobacteria showing huge potential as a source for novel compounds. These organisms are rich in bioactive compounds particularly belonging to the group of alkaloids, tannins, lignins, flavonoids, and carotenoids. Genome studies of cyanobacteria and microalgae species also revealed the potential of these organisms to produce diverse and complex nature of secondary metabolites belonging to nonribosomal peptides, polyketides, or hybrid peptide polyketide compounds. These compounds exhibit a remarkable array of biological activity, and many of them are clinically valuable antimicrobial, antifungal, antiparasitic, antitumor, and immunosuppressive agents. Therefore, in this chapter, we will discuss important natural compounds discovered from microalgae and cyanobacteria. In addition, we will also discuss the genome mining technique in drug discovery with special emphasis on drug discovery from microalgae and cyanobacteria. This technique offers a new alternative approach over the traditional drug discovery method by coupling several bioinformatic tools with next-generation sequencing technology for genetic annotation and identification of important biosynthetic gene clusters (BGCs). Keywords Microalgae · Cyanobacteria · Bioactive compounds · Biosynthetic gene cluster · Genome mining

D. W. Lamare · N. Chaurasia (*) Department of Biotechnology and Bioinformatics, North Eastern Hill University, Shillong, Meghalaya, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 P. Verma (ed.), Micro-algae: Next-generation Feedstock for Biorefineries, Clean Energy Production Technologies, https://doi.org/10.1007/978-981-19-0680-0_9

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Abbreviations AntiSMASH BGC BLAST EBOV HIV HMMs MDR MERS-CoV MGDG NRPS PKS ROS SARS-CoV WHO

9.1

Antibiotics and secondary metabolite analysis shell Biosynthetic gene cluster basic local alignment search tool Ebola virus human immunodeficiency virus hidden Markov models Multidrug-resistant disease Middle East respiratory syndrome coronavirus Monogalactosyl diacylglyceride Nonribosomal peptide synthase Polyketide synthase Reactive oxygen species Severe acute respiratory syndrome coronavirus World Health Organization

Introduction

Natural products are biological compounds with enormous chemodiversity and bioactivity. Because of their structural complexity, pharmacokinetic nature, and their ability to bind to biological targets, they are one of the best candidates for drug discovery. They also act as scaffolds or templates for the design and synthesis of other drug-like molecules for pharmaceutical interest (Newman et al. 2008). Owing to the vast biodiversity of living organisms present within our ecosystem, nature provides us with an inexhaustible resource for the discovery of natural compounds. Since ancient times, natural products have played a key role in traditional healing techniques. The use of plant extracts and plant-based products has been highly documented throughout history for the treatment of many infectious diseases and other illness (Dias et al. 2012). Although the use of natural products as therapeutic agents dated back to thousands of years ago, their application in modern medicines as agents for the treatment of diseases started in the nineteenth century with the discovery of penicillin by Alexander Fleming in the year 1928. Since then natural compounds from plants, microbes, and fungi are used as pharmacological agents for the treatment of many diseases like cancer, Alzheimer’s, cardiovascular diseases, chronic inflammatory diseases, malaria, diabetes, and other infectious diseases (Fleming 1929; Lyddiard et al. 2016). Although bacteria, fungi, and plants are predominant producers of natural compounds, there are still many untapped resources that could be explored for natural compounds. One of such resources is the diverse species of microalgae and cyanobacteria. These organisms have unlimited potential when it comes to bioprospection for natural compounds. They are microscopic unicellular

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photosynthetic organisms with a diameter of approximately 3–100 μm, and they are the primary producers in their ecosystem (Ravindran et al. 2016). Many bioactive compounds with diverse biological properties have been reported from these organisms including high value-added compounds like pigments, polysaccharides, triglycerides, fatty acids, and vitamins. These organisms also have the ability to evolve in extremely competitive environments and are highly exposed to pathogenic microbes such as bacteria, viruses, and fungi. In order to survive, they had to develop tolerance or defense strategies (Falaise et al. 2016). This ability of microalgae to modulate metabolic pathways in response to environmental conditions resulted in a high diversity of compounds, and many of these show very specific chemical structures that are not encountered among terrestrial organisms. This unique ability of microalgae to grow photoautrophically with simple growth requirements and capacity to modulate metabolic processes to produce specific compounds under stress makes them an attractive source for the production of bioactive compounds (Markou and Nerantzis 2013; Mehariya et al. 2021). Another important aspect of these organisms is that they are mixotrophic and are able to switch from phototrophic to heterotrophic growth (Johansen 2012; Goswami et al. 2020). This flexible characteristic of these microorganisms also makes them one of the best candidates when it comes to scaling up production for natural compounds at an industrial level. Since the pioneering work of Pratt et al. (1944) demonstrated the activity of green alga Chlorella against several Gram-positive and Gram-negative bacteria and isolated the first antibacterial compound chlorellin from this species, the interest for mining important natural compounds from these organisms is rising. Numerous studies followed suit to detect compounds from these organisms, and large screening programs were conducted to assess the potential of microalgae and cyanobacterial extracts for bioactivity (Corona et al. 2017; Patel et al. 2015; Goswami et al. 2021a). Based on the number of screening processes performed, many bioactive compounds from microalgae were reported with pharmaceutical applications with antifungal, antibacterial, anticancer, antiviral, anti-inflammatory, antitumoral, and antioxidant activity (Khan et al. 2018; Goswami et al. 2021b). Important bioactive compounds reported from microalgae and cyanobacteria are cyanovirin-N, a virucidal compound isolated from Nostoc ellipsosporum (Colleluori et al. 2005), antimicrobial and anticancer compound borophycin from Nostoc linckia (Hemscheidt et al. 1994), antimicrobial compounds eicosapentaenoic acid from Phaeodactylum tricornutum, and α-linolenic acid from Chloroccocum HS-101 (Desbois et al. 2009; Ohta et al. 1993; Pratt et al. 1944). Apart from the antimicrobial nature of compounds isolated from microalgae and cyanobacteria, several other bioactive compounds from these organisms exhibit different types of biological activity. Recent studies have shown that compounds from microalgae and cyanobacteria have antioxidant properties and can scavenge reactive oxygen species (ROS) and other free radicals (Bule et al. 2018). Mridha et al. (2017) studied the antioxidant potential of methanolic extract of six different freshwater green algae of India. Total phenolics and total flavonoid content were also studied, and it was found out that Spirogyra triplicate showed the highest content. Chaudhuri et al. (2014) studied the antioxidant activity of Euglena tuba and reported that 70% of methanol extract of the algae possesses excellent

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antioxidant and free radical scavenging properties. Further, phytochemical analysis reveals the presence of antioxidant compounds such as phenolics, flavonoids, alkaloids, and tannins. Other class of bioactive compounds reported from microalgae includes cyanobactins reported from a diverse selection of Cyanobacteria sp. (Sivonen et al. 2010), carotenoids such as lutein and β-carotene, phenolic compounds, and nitrogen-containing alkaloid compounds (Michalak and Chojnacka 2015). To date, only a few numbers of microalgae and cyanobacterial species are being investigated for their bioactive potential. Of the estimated millions of existing species, only a dozen are studied as a source for novel compounds. With the advent of next-generation sequencing and genome mining technologies, several microorganisms have been reported to have a remarkable capacity to synthesize a large number of structurally diverse antibiotics and other specialized metabolites (Yamanakaa et al. 2013). Similarly, genome studies in cyanobacteria and microalgae species revealed the potential of these organisms to produce diverse and complex nature of secondary metabolites belonging to nonribosomal peptides, polyketides, or hybrid peptide polyketide compounds (Dittmann et al. 2015). These compounds exhibit a remarkable array of biological activity, and many of them are clinically valuable antimicrobial, antifungal, antiparasitic, antitumor, and immunosuppressive agents (Ansari et al. 2004a, b). Studies by Micallef et al. (2015) reveal 103 NRPS/PKS/hybrid orphan gene clusters from the subsection V of cyanobacterial genomes. These genes were also reported from diatom Gelidibacter algens (Bowman 2016) and dinoflagellates (Kellmann et al. 2010) Nodularia sp., Nostoc sp., Calothrix sp., and Scytonema sp. (Dittmann et al. 2012). Two important novel compounds isolated from microalgae synthesized by these genes are anabaenolysin, an effective antifungal agent reported from Anabaena sp., and nocuolin A, an anticancer compound isolated from Nostoc sp. (Shishidoa et al. 2015; Voráčová et al. 2017). Most of the natural compounds discovered today are done by the traditional screening method, but despite the urgent need for new drugs, the rate of drug discovery has slowed dramatically over the past 30 years. Over 20 classes of antibiotics were discovered before the 1960s, but only a handful was discovered in the past decades, and many do not have the potential to address the most critical Gram-negative pathogens on the WHO antibiotic-resistant priority pathogen list such as carbapenem-resistant Enterobacteriaceae, Pseudomonas aeruginosa, and Acinetobacter baumannii (Medina and Pieper 2016). This rapid decline in drug discovery is because many pharmaceutical industries have rolled back research on natural compounds and focused more on combinatorial chemistry for the synthesis of a drug-like synthetic compound, although these compounds can be synthesized at a much faster rate and lower cost. Nevertheless, their safety and efficiency have always been a concern, and they still have not yet been able to identify synthetic compounds that can treat deadly diseases like cancer, AIDS, and multidrug-resistant disease (MDR) (Hughes and Karlen 2014). Also, another reason for pharmaceutical industries showing little interest in natural compounds is because the conventional screening method is no longer an effective approach for discovering new natural products. It has a very high rediscovery rate, and many biosynthetic gene clusters

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(BGCs) which are responsible for the biosynthesis of novel compounds are silent or cryptic under laboratory conditions (Rutledge and Challis 2015). The method also does not give any knowledge about the genes and enzymes involved in the biosynthesis of natural compounds, thereby limiting the full potential of microorganisms for bioprospection of natural compounds (Zerikly and Challis 2009). With the surge of new infectious diseases like COVID-19, it is imperative that we find new and effective strategies to feed potential drugs into the clinical trial pipeline at a much faster rate. Several strategies have come up to tackle this problem, but the most promising one is the genome mining technique. This technique involves the use of bioinformatic tools for genetic annotation and identification of important BGCs for natural products within the genome of the sequenced organisms, analysis of the enzymes encoded by the gene clusters, and the identification of their natural products (Chavali and Rhee 2017). This technique also helps in selecting genes for heterologous expression in a genetically or molecular tractable host to identify and obtain higher yields of the corresponding compound. Therefore, in this chapter, we will discuss important natural compounds discovered from microalgae and cyanobacteria. We will also discuss how genome mining can be used to identify important BGCs from both microalgae and cyanobacteria.

9.2

Bioactivity of Natural Compounds from Microalgae and Cyanobacteria

As discussed above, microalgae and cyanobacteria have a high diversity of bioactive compounds that exhibit a remarkable array of biological activity like antitumor, antimicrobial, antiviral, anti-inflammation, antimalarial, antifungal, anticancer, and compounds effective against drug-resistant microbes (Tables 9.1 and 9.2). Most of the compounds from these organisms have undergone phase 1 and phase 2 clinical trials, and many of these have been found to be effective in curing clinical diseases. With new technologies and computational-based screening methods, these organisms hold a bright and promising future for drug discovery. In the section below, the application of natural compounds from these organisms is briefly discussed for pharmaceutical applications.

9.2.1

Antimicrobial Compounds

Although mankind has made a lot of progress in drug discovery, there is a growing trend in the rise of MDR across the globe. Many clinical isolates which can be easily treated before like S. aureus, S. pyogenes, and Mycobacterium tuberculosis are now considered highly resistant to most commercially available antibiotics (Duin and Paterson 2016). In a few years, MDR will cause a global health crisis and will result

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Table 9.1 An overview of various bioactive compounds isolated from microalgae and their biological activity

Bioactive molecule Chlorellin Phenolic compounds Butanoic acid

Natural compound class Fatty acids

Lipophilic

Docosapentaenoic acid (DPA) Eicosapentaenoic acid (EPA) Hexadecatrienoic acid ɑ-Linolenic acid

Lipophilic

Palmitoleic acid

Lipophilic

Palmitic acid

Fatty acids

Monoacylglycerides

Lipids

Oxylipins

Lipids

Chrysolaminarin

Polysaccharide

Fucoxanthin

Carotenoids

Stigmasterol

Sterols

Lipophilic Lipophilic Lipophilic

Microalgae Chlorella sps.

Bioactivity Antibacterial

Chlorella vulgaris Haematococcus pluvialis Chaetoceros muelleri Phaeodactylum tricornutum Dunaliella salina

Antibacterial

Chlorococcum HS-101 Scenedesmus obliquus Scenedesmus intermedius Skeletonema marinoi Chlamydomonas debaryana Synedra acus

Antibacterial

Antimicrobial Antimicrobial Antibacterial Antibacterial

Antibacterial Antibacterial and antifungal Anticancer Anticancer Anticancer

Phaeodactylum tricornutum Navicula incerta

Anticancer

Polyunsaturated aldehydes Methanol extract

Skeletonema marinoi Euglena tuba

Anticancer

Angiotensin-Iconverting enzyme Monogalactosyl diacylglyceride Extracellular polysaccharides Anionic polysaccharides Naviculan

Anticancer

Fatty acids

Nannochloropsis oculata Coccomyxa sp.

Polysaccharide

Porphyridium cruentum Porphyridium purpureum Navicula directa

Anticancer

Anticancer

Antiviral Antiviral Antiviral Antiviral

References Pratt et al. (1944) Syed et al. (2015) Santoyo et al. (2009) Rojas et al. (2020) Desbois et al. (2009) Rojas et al. (2020) Ohta et al. (1993) Alsenani et al. (2020) Davoodbasha et al. (2018) Miceli et al. (2019) Avila-Roman et al. (2016) Kusaikin et al. (2010) Neumann et al. (2019) Kim et al. (2014) Sansone et al. (2014) Panja et al. (2016) Samarakoon et al. (2013) Hayashi et al. (2019) de Jesus Raposo et al. (2015) Radonić et al. (2011) Lee et al. (2006)

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Table 9.2 An overview of various bioactive compounds isolated from cyanobacteria and their biological activity Bioactive molecule Ambiguine

Natural compound class Alkaloid

Cyanobacteria Fischerella sp.

Bioactivity Antimicrobial

Hepalindoles

Alkaloids

Stigonematales

Tolyporphin

Pigment

Muscoride

Alkaloids

Parsiguine

Cyanopeptides

Malyngolide

Polyketide

Tanikolide

Polyketide

Tolypothrix nodosa Nostoc muscorum Fischerella ambigua Lyngbya majuscula Lyngbya sp.

Antimicrobial and anticancer Anticancer

Carbamidocyclophane

Antibacterial and antifungal Antibiotic Antifungal

Nostocyclyne A

Polyketide

Nostoc sp.

Antibacterial and antifungal Antibacterial

Nostocionone

Alkaloids

Nostoc sp.

Antibacterial

Pitiprolamide

Cyclic depsipeptide Diterpenoids

Lyngbya majuscula Nostoc commune Lyngbya majuscula Anabaena sp.

Antibacterial

Comnostins A–E Pitipeptolides

Nostoc sp.

Antibacterial

Anabaenolysins

Cyclic depsipeptide Lipopeptides

Lobocyclamides

Lipopeptides

Laxaphycins

Lipopeptides

Hassallidin

Antibacterial Antibacterial Antifungal Antifungal

Lipopeptides

Lyngbya confervoides Anabaena laxa II Hassallia sp.

Dolastatin 10

Pentapeptide

Symploca sp.

Anticancer

Apratoxins

Lyngbya sp.

Anticancer

Borophycin

Cyclic depsipeptides Lipophilic

Nostoc linckia

Anticancer

Curacin A

Lipophilic

Lyngbya majuscula

Anticancer

Antifungal Antifungal

References Raveh and Carmeli (2007) Hohlman et al. (2021) Prinsep et al. (1992) Mattila et al. (2019) Ghasemi et al. (2004) Cardellina et al. (1979) Singh et al. (1999) Thuan et al. (2019) Ploutno and Carmeli (2000) Itoh et al. (2014) Montaser et al. (2011) Jaki et al. (2000) Luesch et al. (2001) Shishido et al. (2015) MacMillan et al. (2002) Frankmolle et al. (1992) Neuhof et al. (2005) Taori et al. (2009) Matthew et al. (2008) Hemscheidt et al. (1994) Gerwick et al. (1994) (continued)

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Table 9.2 (continued) Bioactive molecule Trikoramide A

Natural compound class Lipophilic

Calcium spirulan

Polysaccharides

Nostoflan

Polysaccharides

Cyanovirin

Protein

Scytovirin

Protein

Aplysiatoxin

Sulfolipids

Gallimide A

Peptide

Symplostatin 4 Venturamides A and B Lagunamides A and B

Linear depsipeptide Cyclic hexapeptides Cyclodepsipeptides

Bastimolide A Ikoamide

Cyanobacteria Symploca hydnoides Spirulina platensis Nostoc flagelliforme Nostoc ellipsosporum Scytonema varium Trichodesmium erythraeum Schizothrix sp.

Bioactivity Anticancer

Antimalaria

Symploca sp.

Antimalaria

Oscillatoria sp.

Antimalaria Antimalaria

Macrolide

Lyngbya majuscule Okeania hirsute

Lipopeptide

Okeania sp.

Antimalaria

Antiviral Antiviral Antiviral Antiviral Antiviral

Antimalaria

References Phyo et al. (2019) Lee et al. (1998) Kanekiyo et al. (2005) Boyd et al. (1997) Xiong et al. (2006) Gupta et al. (2014) Linington et al. (2009) Stolze et al. (2012) Linington et al. (2007) Tripathi et al. (2010) Shao et al. (2015) Iwasaki et al. (2020)

in the death of millions of people threatening to undo decades of work in treating infectious diseases. Thus, the outlook for the use of antimicrobial drugs in the future is very uncertain if we don’t find alternative measures to source antimicrobial compounds (Seyedsayamdost 2014). Most of the antimicrobial drugs available in the market are either from fungi, bacteria, or plants. However, recent studies showed that microalgae and cyanobacteria show huge potential as a source for antimicrobial compounds. Several screening programs report the presents of antimicrobial and antifungal agents from both microalgae and cyanobacterial extracts. Examples of antibacterial compounds isolated from microalgae are eicosapentaenoic acid from Phaeodactylum tricornutum, α-linolenic acid from Chloroccocum HS-101, and ethanolic extract of Chlorella vulgaris (Desbois et al. 2009; Ohta et al. 1993; Sanmukh et al. 2014). Microalgae and cyanobacteria also show remarkable activity against fungi. Anabaenolysin isolated from Anabaena sp. is effective antifungal agents against C. albicans (Shishidoa et al. 2015). The phenolic extract of Spirulina sp. and Nannochloropsis sp. significantly inhibits the growth of Fusarium sp. (Scaglioni et al. 2018). Antifungal compounds such as butanoic acid and methyl lactate were also reported from a number of microalgae species. These include Haematococcus pluvialis, Chlorella pyrenoidosa, and Scenedesmus quadricauda

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(Santoyo et al. 2009; Abedin and Taha 2008). Significant antimicrobial properties against plant pathogens were also reported from several algal species making them valuable candidates for the substitution of pesticides and insecticides in the near future (Kim et al. 2009). Further investigation on antibacterial and antifungal compounds from cyanobacteria and microalgae reveals the presence of specialized polyketide and nonribosomal peptide compounds. Malyngolide, a natural δ-lactones polyketide compound synthesized by Lyngbya majuscula, is one of the first antibiotic compounds reported from cyanobacteria. This compound inhibits the growth of disease-causing bacteria like Streptococcus pyogenes, Staphylococcus aureus, and Mycobacterium smegmatis. Similarly, δ-lactone compound tanikolide was also reported from Lyngbya sp., but this compound is found to have cytotoxicity against brine shrimp as well as antifungal activity and molluscicidal activity (Cardellina et al. 1979, Singh et al. 1999). Among many genera of cyanobacteria capable of producing natural compounds, species belonging to the genus of Nostoc, Lyngbya, and Microcystis are some of the main producers of bioactive compounds. Carbamidocyclophane is a commonly reported bioactive compound from Nostoc sp. This compound is under clinical trial and preclinical trial because of its high antimicrobial activity against methicillin-resistant Staphylococcus aureus and Streptococcus pneumonia. Other compounds reported from Nostoc and Lyngbya species with antagonistic activity against fungi and microbes include nostocyclyne A, nostocionone and its derivative, comnostins A–E, pitipeptolides C–F, and pitiprolamide (Thuan et al. 2019; Ploutno and Carmeli 2000; Montaser et al. 2011; Jaki et al. 2000; Luesch et al. 2001). Cyanobacteria also produce wide varieties of lipopeptides with antibiotic properties. Lipopeptides are amphipathic structures comprising polar peptides with hydrophobic fatty acid chains. Many of the compounds belonging to this class exhibit antifungal activities and are structurally related to anabaenolysins, lobocyclamides, laxaphycins, and hassallidin (Shishido et al. 2015; MacMillan et al. 2002; Frankmolle et al. 1992; Neuhof et al. 2005). From microalgae, many compounds have been isolated and characterized because of their ability to inhibit the growth of many microorganisms. Chlorellin is the first antibiotic compound reported from microalgae. It is a mixture of fatty acids from the green microalgae Chlorella sp., and it was shown to have antibacterial activity against various Gram-positive (G+) and Gram-negative (G ) bacteria (Pratt et al. 1944). Further studies have also identified compounds belonging to fatty acids, polysaccharides, polyphenols, pigments, alkaloids, and peptides that inhibit the growth of many human pathogens (Syed et al. 2015; Dewi et al. 2018). Screening for antimicrobial activity of microalgae is mainly done using organic and inorganic extracts. From several studies conducted, the lipophilic extract shows better results when tested for antimicrobial activities. This can be due to the presence of lipophilic compounds like butanoic acid, docosapentaenoic acid (DPA), eicosapentaenoic acid (EPA), hexadecatrienoic acid, ɑ-linolenic acid (ALA), methyl lactic acid, and palmitoleic acid (Abedin and Taha 2008; Santoyo et al. 2009; Rojas et al. 2020; Desbois et al. 2009; Ohta et al. 1993; Alsenani et al. 2020). This lipophilic nature of the antibacterial compound was also reported by Sibi (2015). He showed that the

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lipid extract of Chlorella sp. has inhibitory activity on Propionibacterium acnes by inhibiting the lipase activity and limiting the ROS production. Davoodbasha et al. (2018) also reported that fatty acid methyl esters (FAME) derived from lipids of Scenedesmus intermedius exhibit antimicrobial and antifungal activity. Based on GC results, he confirmed that the presence of palmitic acid at a high percentage may be the source of the activity. Other compounds reported from microalgae with antimicrobial potential are neophytadiene, acrylic acid, B-cyclocitral, phytol, and methyl lactate (Teco-Bravo et al. 2021; Qasem et al. 2016).

9.2.2

Anticancer Compounds

Cancer is the second leading cause of death worldwide, accounting for an estimated 9.6 million death or 1 in 6 deaths in 2018. Based on the World Health Organization (WHO) report, by 2030, there will be 21 million new cases of cancer and 13 million deaths due to this disease. Chemotherapy is the main treatment used to stop the growth of cancer cells and prevent it from spreading to other tissues in the body. However, a major drawback of using this treatment is that it can have life-threatening side effects, thereby limiting its use in the treatment of cancer (Swain et al. 2015). Nearly all anticancer medications available in the market have an adverse effect on the body; therefore, the quest to find safe and efficient anticancer drugs is always desirable (Hussein and Abdullah 2020). Nature remains a rich source of natural compounds, and microalgae, as well as cyanobacteria, are rich in bioactive compounds with pharmaceutical properties. Many compounds from these organisms exhibit anticancer properties by disrupting tubulin and microfilaments during cell division, modulating cell death and apoptosis in cancer cells as well as target enzymes such as histone deacetylase (Tan 2010). Dolastatin 10, curacin, and desmethoxymajusculamide are some of the anticancer compounds reported from cyanobacteria that have entered phase I, phase II, and phase III clinical trials. Dolastatin 10 isolated from cyanobacteria Symploca sp. is a pentapeptide with four unique amino acids dolavaline, dolaisoleucine, dolaproline, and dolaphenine. It acts as an antiproliferative agent by binding to the tubulin structure and disrupts the microtubule assembly, thereby arresting the cell into the G2/M phase. Dolastatin 10 also acts as a scaffold for the synthesis of several analogue structures like TZT-1027. This compound has reduced toxicity in comparison to dolastatin and is under clinical trial in several countries like the USA, Europe, and Japan for its anticancer activity (Taori et al. 2009). Apratoxins are another class of cytotoxic cyclic depsipeptides isolated from many Lyngbya sp.; these molecules belong to the hybrid PKS-NRPS structural class consisting of tetrapeptide chain, a thiazoline unit, and a polyketide chain as part of the cyclic carbon skeleton. Apratoxin A has antiproliferative effects by arresting cell division at the G1 phase and initiating apoptosis. Through in vivo studies against the pancreatic tumor, the scientist revealed that Sec 61 complex is the molecular target of apratoxin A. Many synthetic analogues of apratoxin A are available in the market, and one common example is

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oxazoline A. This particular analogue initiates cell death in cancer cells via chaperone-mediated autophagy (Matthew et al. 2008). Borophycin is another compound reported from cyanobacteria effective against human colorectal cancer and human carcinoma (Hemscheidt et al. 1994). Several investigations on bioactive compounds from cyanobacteria also reveal compounds belonging to lipopeptides and cyanobatins with anticancer activity. Curacin A is a common example of lipopeptide with cytotoxic activity; it is isolated from Lyngbya majuscule and inhibits tubulin polymerization arresting the cell at the G2/M phase of the cell cycle (Gerwick et al. 1994). An investigation by Phyo et al. (2019) on the bioactive compound from marine cyanobacteria Symploca hydnoides has led to the discovery of cyanobactin trikoramide A. This compound is a C-prenylated cyclotryptophan containing cyanobactin which possesses cytotoxicity against the MOLT-4 and AML2 cancer cell lines. Other cyanobactins reported having cytotoxic activity against cancer lines include sphaerocyclamide, trunkamide, ulithiacyclamide, and lissoclinamide (Phyo et al. 2019). Microalgae offer a lot of potentials when it comes to mining natural compounds with cytotoxic activity. But, on the other hand, despite extensive research work, only a few metabolites from microalgae showed the potential to be developed as anticancer drugs. Nevertheless, compounds like monoacylglycerides, oxylipins, chrysolaminarin, polysaccharides, fucoxanthin, lipids, fatty alcohol esters, and stigmasterol have been identified as potential anticancer compounds from the microalgae diatoms (Miceli et al. 2019; Avila-Roman et al. 2016; Kusaikin et al. 2010; Neumann et al. 2019; Kim et al. 2014; Agrawal and Verma 2022; Saini et al. 2021). Studies have also shown that methanol extract of Euglena tuba also shows antiproliferative activity against cancer cell lines (Panja et al. 2016). Anticancer activity of microalgae extract was also reported by Ramaswamy et al. (2016) indicating that microalgae can be a potential source for bioactive compounds with anticancer properties. Samarakoon et al. (2013) isolated a novel bioactive compound angiotensin-I-converting enzyme (ACE) inhibitory peptide from marine microalgae Nannochloropsis oculata. Other important applications of microalgae include the antiproliferative effects which are reported by Renju et al. (2014) and Rajavel et al. (2009). Also, a number of researchers have reported the anticancer activity of carotenoid compounds from microalgae like β-carotene, lutein, astaxanthin, and fucoxanthin, but no clinical trials have yet been reported for these compounds (Hussein and Abdullah 2020; Mondal et al. 2020).

9.2.3

Antioxidant Compounds

One important class of bioactive compounds from microalgae and cyanobacteria is antioxidant compound. Nowadays, due to the widespread use of synthetic antioxidants in food and pharmaceuticals, the attempt has been made to discover new and efficient antioxidants from natural resources. Oxidative damage due to ROS could induce atherosclerosis, cataracts, muscular dystrophy, rheumatoid arthritis,

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neurological damage, cancer, and aging. Recent studies have shown that some species of algae contain a large amount of antioxidants and phenolic compounds that can scavenge ROS and other free radicals (Shebis et al. 2010; Bule et al. 2018). Khatib et al. (2018) reported the antiatherogenic effect of Nannochloropsis sp. extract by preventing the oxidative of macrophages and LDL, which is the first step in the development of the disease atherosclerosis. Extract from microalgae was also shown to have protective effects in hepatic injury, and several polysaccharides from microalgae exhibit protective effects against oxidative stress (Park et al. 2011). Wei et al. (2013) observed the hepatic protective effects of Chlorella vulgaris extract on carbon tetrachloride (CCl4) which is a potent hepatotoxin producing centrilobular hepatic necrosis causing lipid peroxidation of membranes that leads to liver injury. Certain polysaccharides from microalgae were also shown to induce protective effects against oxidative stress. This is reported by Mohamed (2008), where microcystin-induced oxidative stress was studied in Chlorella vulgaris and Scenedesmus quadricauda, and for the first time it was shown that polysaccharides play a protective role in some microalgae against microcystin toxins. There are several reports on the evaluation of the antioxidant activity of microalgae and Cyanobacteria species; these include a genus of Botryococcus, Chlorella, Dunaliella, Nostoc, Phaeodactylum, Spirulina, Nannochloropsis, Chaetoceros, and Spirogyra triplicate (Mridha et al. 2017; Goh et al. 2010; Rao et al. 2006; Wu et al. 2005; Guzman et al. 2001).

9.2.4

Antiviral Compounds

Throughout history, viruses, in particular RNA viruses, are responsible for major outbreaks and global health crises in many parts of the world. Millions of people have died from pandemics caused by viral disease putting them at the top spot of the current list of ten global threats by the WHO. This list included deadly diseases like AIDS caused by human immunodeficiency virus (HIV), Ebola virus (EBOV) which is responsible for the outbreak during the year 2014–2016, Zika virus epidemic in the year 2016, Middle East respiratory syndrome coronavirus (MERS-CoV), Zika virus, and severe acute respiratory syndrome coronavirus (SARS-CoV) (Reynolds et al. 2021). Recently, SARS-CoV-2 or COVID-19 is responsible for the global pandemic that started in the year 2019, on January 30, 2020; WHO declared it as the sixth “Public Health Emergency of International Concern” and on March 11, 2020, it was announced as a global pandemic (Jafari Porzani et al. 2021). To date, more than 2.4 million people have lost their lives to this deadly disease, and the global economy is drastically declining with tens of millions of people lacking access to food, income, and health security (Jafari Porzani et al. 2021). Amidst the devastation caused by COVID-19, there is no current medication available to fight it. Although antiviral drug ribavirin is commonly used to treat COVID-19, statistical studies have shown it to be ineffective in a patient with severe SARS-Cov-2 infection (Tong et al. 2020). To date, many life-threatening viral diseases like AIDS and SARS-CoV-2 do

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not have effective antiviral therapies. Thus, there is an urgent need for the exploration of natural resources and the development of a broad-spectrum class of effective antiviral agents. In recent years, cyanobacteria and microalgae have emerged as one of the most prolific producers of bioactive compounds, and many of these compounds have shown important biological activities. This extensive research work on bioactive metabolites from cyanobacteria and microalgae has also led to the discovery of many antiviral agents. Antiviral compounds from these organisms particularly belong to three classes of compounds, polysaccharides, carbohydrate-binding proteins, and sulfoglycolipids (Carpine and Sieber 2021). Calcium spirulan (Ca-SP), a novel sulfated polysaccharide, is an effective antiviral agent isolated from Spirulina sp.; this compound shows potent and broad-spectrum activity against HIV-1, HIV-2, influenza, and a series of other enveloped viruses. Their mode of action involves the inhibition of the reverse transcriptase activity of HIV-1 and selectively inhibits viruscell attachment, thereby preventing the entry of the virus into the host cell. They also prevent viral pathogenicity by inhibiting the fusion between healthy CD4+ lymphocytes and HIV-infected ones (Lee et al. 1998). Nostoflan is another polysaccharide isolated from Nostoc flagelliforme with virucidal activity. It is a broad-spectrum antiviral compound and showed potent activity against herpes simplex virus type 1 and type 2, human cytomegalovirus, and influenza virus. It binds to the carbohydrate receptors of the envelope virus and prevents them from entering into the host cell (Kanekiyo et al. 2005). From microalgae, Hayashi et al. (2019) discovered the antiviral compound monogalactosyl diacylglyceride (MGDG) from Coccomyxa sp. In his research, it was found that MDGD compounds have a prophylactic effect against herpes simplex virus type 2 infection by damaging the viral envelope and inhibiting the viral particle from entering the host cell. It was also found that intravaginal administration of MDGD in HSV-2-infected mice prevents viral yields and hepatic lesions in the genital cavity resulting in higher survival in treated mice than in control. Carbohydrate-binding proteins represent another class of antiviral compounds, and two well-documented compounds of this class are cyanovirin-N and scytovirin. Cyanovirin is an 11-kDa virucidal protein isolated by Boyd et al. (1997) from Nostoc ellipsosporum. In his experiment, it was discovered that cyanovirin inhibits cell-cell fusion and transmission of HIV infection by interfering with the binding of the gp 120 proteins and the CD4+ receptors. Cyanovirin-N also shows potent virucidal activity against simian immunodeficiency virus (SIV) and other envelope viruses making it a broad-spectrum antiviral agent. Sytovirin is a 95-amino-acid-long polypeptide, isolated from the aqueous extract of Scytonema varium. It is an antihuman immunodeficiency virus protein that binds to the glycoprotein of the HIV envelope and inactivates it (Xiong et al. 2006). Sulfolipids represent another intriguing class of AIDS antiviral compounds that have a different mode of inhibitory action in comparison to polysaccharides and carbohydrate-binding protein. Marine cyanobacteria also offer a lot of potentials when it comes to mining for virucidal compounds. Gupta et al. (2014) reported aplysiatoxin-related compounds, including two new analogues, 3-methoxyaplysiatoxin and 3-methoxydebromoaplysiatoxin, for the first time from

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the marine cyanobacterium, Trichodesmium erythraeum. These compounds showed anti-chikungunya activity by targeting the replication machineries of the virus after it entered the host cell (Gupta et al. 2014).

9.2.5

Antimalarial Compounds

Recent expedition from marine cyanobacteria has led to the discovery of many compounds with antiprotozoal activity. Of these, gallimide A, which is structurally related to dolastatin A, has been shown to exhibit antimalarial activity in a mammalian cell against chloroquine-resistant strain of Plasmodium falciparum (Linington et al. 2009). Another important antimalarial compound reported from cyanobacteria is symplostatin 4. Symplostatin 4 is a linear depsipeptide bearing a dimethylated N-terminal amino acid and C-terminal pyrrolinone moiety; it was first isolated in 2009 from Symploca sp. and shows promising antimalarial activity against Plasmodium falciparum. Its mode of action involves permeabilization into the P. falciparum cell membrane and causes food vacuole phenotype and inhibits pathogen replication. Under subsequent investigation by Stolze et al. (2012), they also found out that falcipains are the main target of symplostatin 4; falcipains are cysteine proteases that are involved in the breakdown of host hemoglobin, erythrocyte invasion, and rupture (Stolze et al. 2012). Other antimalarial compounds reported from marine cyanobacteria are venturamides A and B isolated from Oscillatoria sp., lagunamides A and B isolated from Lyngbya majuscule, bastimolide A from Okeania hirsute, and ikoamide from marine cyanobacteria Okeania sp. (Linington et al. 2007; Tripathi et al. 2010; Shao et al. 2015; Iwasaki et al. 2020).

9.3

BGCs and Genome Mining

BGCs are groups of genes linked together that encode enzymes involved in a biosynthetic pathway for the assembly of secondary metabolites. With the advent of next-generation sequencing, the complete genome sequence of several microorganisms reveals the presence of huge diversity of cryptic BGC with remarkable potential to synthesize a large number of structurally diverse compounds. Recent studies show that species belonging to the genus of Streptomyces has the capacity to produce as many as 100,000 secondary metabolites and yet only a small fraction of these have been discovered to date (Yamanakaa et al. 2013). Doroghazi et al. (2014) also discovered that the genome of the actinomycetes family has a huge diversity of natural product BGCs which is much higher than the number of molecules reported from the traditional screening method. According to their research, 77% of the actinomycetes BGCs are cryptic or silent without any knowledge of the products and their biological activity. The majority of the BGC belongs to the PKS and NRPS gene clusters. PKS and NRPS enzymes are involved in the biosynthesis of

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polyketides and nonribosomal peptide compounds which exhibit a remarkable array of biological activity, and many of them are clinically valuable antimicrobial, antifungal, antiparasitic, antitumor, and immunosuppressive agents (Ansari et al. 2004a, b; Wang et al. 2011). NRPS enzymes are multimodular enzymes consisting of four major catalytic domains, adenylation domain for substrate specificity and activation, followed by transfer to peptidyl carrier protein domain, and then the condensation domain for peptide formation, followed by chain elongation and termination by the thioesterase domain. Similarly, PKS enzymes consist of three main domains, acyltransferase domain that attaches the substrate to the acyl carrier protein domain and then the ketosynthase domain that catalyzes substrate condensation, followed by stepwise processing by other domains to form the end products (Chen et al. 2019). The discovery of silent gene clusters has given birth to a new area of research focusing on identifying BGCs that may have the potential to produce novel compounds referred to as genome mining. Genome mining coupled bioinformatics and functional genomic tools to select genes for heterologous expression in a genetically or molecularly tractable host to identify and obtain higher yields of a corresponding compound. In this method, bioinformatics plays an important role in analyzing genome sequence and identifying gene clusters that are likely to be involved in the biosynthesis of natural products using computational sequence comparison tools (Chavali and Rhee 2017). Based on analysis of experimentally characterized PKS and NRPS biosynthetic clusters, bioinformatic resources have been developed as knowledge bases for domain organization and substrate specificities of PKS and NRPS genes and connecting these genes to metabolites. Several bioinformatic tools like antiSMASH, NP.searcher, ClustScan, and SMURF are capable of identifying gene clusters from genome sequence by aligning the query sequences against reference libraries containing NRPS or PKS domains. These tools not only permit gene annotation but are capable of protein domain identification and conserved motif assessment in NRPS/PKS enzymes as well as substrate specificity prediction (Khater et al. 2016). Applying such bioinformatic tools to cryptic biosynthetic systems can give important insight into the structural features of the metabolic product. Such structural information can lead to the prediction of putative physicochemical properties, which allows only metabolites with the predicted properties to be targeted (Zerikly and Challis 2009). Genome mining studies of Cyanobacteria species revealed the potential of these organisms to produce diverse and complex nature of secondary metabolites belonging to nonribosomal peptides, polyketides, or hybrid peptide polyketide compounds (Dittmann et al. 2015). Studies by Wang et al. (2011) reveal 145 bacteriocin gene clusters identified through genomic mining of 58 cyanobacterial genomes and through molecular screening of 21 cyanobacteria strains, and Barrios-Llerena et al. (2007) identified 18 NRPS and 17 PKS genes from three families of cyanobacteria Nostocales, Chroococcales, and Oscillatoriales (Barrios). These genes were also reported by Ehrenreich et al. (2005) from freshwater cyanobacteria; using degenerate primers and sequencing of the cloned PCR products, they were able to detect the presence of pks and nrps genes and identify these gene clusters using specialized

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bioinformatic tools. In their studies, they found that filamentous and heterocystous cyanobacteria are the richest source of these genes and most likely sources of novel natural products (0662). The dominant presence of pks and nrps genes in a filamentous strain of cyanobacteria was also highlighted by Brito et al. (2015). Furthermore, through LC-MS analysis, he discovered metabolites with untapped chemodiversity from 61 cyanobacterial strains, indicating that these microorganisms have a huge potential as prospects for drug discovery. Many other researchers also reported that cyanobacteria possess an untapped source of secondary metabolites highlighting a huge disparity in cyanobacteria metabolic profile and diversity of BGCs found in these organisms. In microalgae, distribution of nrps genes is more limited in comparison to pks genes as reported by Vingiani et al. (2019); nevertheless, these genes have been reported from Chlamydomonas reinhardtii, Chlorella variabilis, Coccomyxa sp., diatoms, and dinoflagellates (Sasso et al. 2012). Most of the natural products available right now represent less than 10% of the biosynthetic capacity of the microbial world. The discovery of cryptic gene clusters through genome mining will lead to the renaissance of drug discovery, and, if functional, these gene clusters can encode new enzymes within NRPS/PKS gene clusters performing new biosynthetic reactions, which may potentially produce natural products with enhanced or new bioactivities (Ongley et al. 2013).

9.4

Identification of BGCs

With the increasing demands of antibiotics, genome mining has been a common method for drug discovery by deciphering cryptic gene clusters. In this process, bioinformatics have been widely used to identify gene clusters, mainly the polyketide synthase, nonribosomal peptide synthase, and hybrid PKS-NRPS genes (Ziemert et al. 2016). With the advancement in the genetic sequencing method, a large quantity of DNA sequences including cyanobacteria is available within the public database. The genetic sequences of several BGC encoding genes including PKs and NRPS enzymes are available within these databases, and with the help of several bioinformatic tools, one can compare with those of known functions and predict the products of these genes (Velásquez and Van der Donk 2011). Most bioinformatic tools used in genome mining differ in their algorithm search and require protein or DNA sequence or the location of gene coordinates to identify gene clusters. But one common feature of all search tools is that they used a common backbone, mainly signature enzyme which is a central part of the gene cluster and performs a sequence similarity search against other sets of known signature enzymes belonging to an experimentally proven pathway. Some of the most common bioinformatic tools used for gene cluster identifications in microorganisms are ClustScan, NP.searcher, BAGEL, SMURF, ClusterFinder, and antiSMASH. These bioinformatic tools utilized the hidden Markov models or basic local alignment

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search tool (BLAST) to identify signature enzymes for gene clusters (Chavali and Rhee 2017).

9.4.1

ClustScan

ClustScan (Cluster Scanner) is a cluster identification search tool specifically for polyketide synthases (PKS), nonribosomal peptide synthetases (NRPS), and hybrid (PKS/NRPS) enzymes. This software uses the hidden Markov models (HMMs) for the alignment of the query sequence against the reference sequences within the database for the annotation and identification of gene clusters encoding for metabolic protein domains like ketosynthase domain for PKS clusters and condensation domains for NRPS clusters. ClustScan can also be used to predict the chemical structure of both PKS and NRPS gene clusters using specifically constructed HMM profiles, and when used in combination with other bioinformatic tools, they can predict multiple chemical structures from a gene cluster depending on the accessory modification genes present within the cluster (Starcevic et al. 2008).

9.4.2

NP.searcher

NP.searcher is another bioinformatic search tool used for the identification and annotation of PKS, NRPS, and hybrid PKS/NRPS gene clusters from microbial genomes. It also predicts chemical structures and uses BLAST in its algorithm to not only identify signature enzymes but also determine the auxiliary domains of gene clusters. These auxiliary domains play a very important role in tailoring and determining the final chemical structures of the product which may include reactions like methylation, epimerization, and reduction. During the identification, a process blast is run to align sequences with the standard PKS and NRPS sequences and determine the signature residues that predict substrate specificity. It also uses blast to recognize auxiliary domains such epimerization, reduction, and methylation domain. During the initial process, BLAST is run first to match the known NRPS/PKS domain against the unknown NRPS/PKS domain. This will allow the software to determine the key residues of the unknown NRPS/PKS domains. The program then runs BLAST for the second time to align the discovered sequence with the known signature sequence derived from published literature to determine the substrate specificity. NP.searcher uses BLAST twice more to recognize auxiliary domains and identify additional enzymes within the gene cluster which further tailor the end product by catalyzing reactions such as glycosylation, halogenation, and hydroxylation. This software has a database of 187 NRPS signature sequences of ten residues and 18PKS residues, which is then used to compare with query sequence to determine the substrate specificity of the catalytic domain (Helfrich et al. 2014; Li et al. 2009).

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AntiSMASH

AntiSMASH is a sophisticated bioinformatic tool capable of identifying a wide range of secondary metabolite compounds belonging to polyketides, nonribosomal peptides, terpenes, bacteriocins, nucleosides, beta-lactams, butyrolactones, and siderophores. It aligns the sequences at the gene cluster level to their nearest relatives by scanning through its database containing other known gene clusters and rapidly detects secondary metabolite BGCs, provides detailed NRPS/PKS functional annotation, and predicts the chemical structure of NRPS/PKS compounds at higher accuracy than existing methods. AntiSMASH identifies gene clusters of the query sequence on the basis of the built-in library profile HMMs of experimentally characterized signature proteins or protein domains. To detect the flanking accessory gene, it uses a greedy algorithmic approach by extending the scanning process by 10 or 20 kb on both sides; therefore, gene clusters spaced closely together may be merged into “superclusters.” These superclusters are later known as “hybrid clusters” and may either represent a single gene cluster that produces a hybrid compound or may represent two separate gene clusters that just happen to be spaced close together. Furthermore, antiSMASH also provides the detailed architecture of the NRPS/PKS domain, the substrate specificity of the acyltransferase domain (AT) and adenylation domain, and prediction of the chemical structure and stereochemistry of the polyketides and nonribosomal peptide. It also uses Cluster BLAST for comparative analysis of gene clusters that may show similarity to one another, and, finally, all pipeline analysis results are visualized in a user-friendly interactive XHTML page (Medema et al. 2011; Blin et al. 2019). In addition to the above bioinformatic tools, we also have SMURF (secondary metabolite unknown region finder), which is specifically meant for mining secondary metabolite BGCs in fungi, PlantiSMASH for plants, and ClusterFinder (Boddy 2014).

9.5

Activation of BGCs

Through genome mining studies, scientists have found that there is a huge disparity between the number of the discrete BGCs and the current rate of drug discovery. To meet this challenge, a new and novel approach was developed by combining genome sequencing with gene cluster prediction tools to identify cryptic BGCs, followed by heterologous expression of these genes to produce new natural products (Li et al. 2015b; Bergmann et al. 2007). Using this strategy, Ross et al. (2015) identified the alt BGC from Pseudoalteromonas piscicida JCM 20779 using antiSMASH bioinformatic tool and heterologously express this gene cluster through the transformation-associated cloning method to produce a novel compound alterochromide. Genomic mining along with the direct cloning method was also used to activate the syringolin BGC. Here, the syringolin gene cluster was directly

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cloned from genomic DNA of P. syringae using Rec E/RecT-mediated LLHR in E. coli, and this gene cluster is heterologously expressed to produce the novel compound (Bian et al. 2012). In this method, a linear cloning vector carrying the inducible promoter, ampicillin-resistant gene, and Ori will be constructed by introducing two PCR-amplified homology arms corresponding to flanking regions outside the boundary of the gene cluster. The predigested genomic DNA mixture is then mixed with the linear cloning vector and co-transformed into recombineering proficient E. coli GB05-dir cells by electroporation. The homologous recombination between two linear DNA molecules, the cloning vector, and the targeted gene cluster will be completed by using RecE/RecT in E. coli. The resulting recombinants are then identified by selection for the ampicillin resistance gene present on the linear cloning vector and subsequent DNA restriction analysis and sequencing. The positive clones will undergo heterologous expression under the control of an inducible promoter (Fu et al. 2012; Chai et al. 2012). Similarly, by scanning the whole genome of Streptomyces scopuliridis, Li et al. (2015a) identified a 39-kb dsa BGC. The gene cluster was then expressed in S. coelicolor to produce a potent antibacterial compound desotamides (DSA). In another study, Chen et al. (2017) carried out the genomic mining for the tot gene clusters from six Streptomyces strains and activate these gene clusters for the production of totopotensamides (TPMs). Other examples of BGCs identified and expressed include enediyne biosynthesis genes from actinomycete strains which synthesize enediynes, a potent class of antitumor antibiotics, and taromycin A biosynthetic pathway from Saccharomonospora sp. In the latter case, transformation-associated recombination (TAR) cloning was exploited to express a 67-kb nonribosomal peptide synthetase BGC from the marine actinomycete Saccharomonospora sp., producing the dichlorinated lipopeptide antibiotic taromycin A in the model expression host S. coelicolor (Zazopoulos et al. 2003; Yamanakaa et al. 2013). Using similar approach, BGCs from microalgae and cyanobacteria can also be cloned and expressed in another host to obtain the corresponding compound. The compounds can then be extracted, purified, and identified using different extraction techniques, HPLC, and MS-MS analysis.

9.6

Conclusion

One of the major problems we are facing in this era is the emerging of new infectious diseases, viral infections (epidemic and pandemic), rise in antibiotic-resistant microbes, and lack of effective compounds to treat a deadly disease like cancer and AIDS. Thus, there is an urgent demand to find other alternative sources for the discovery of natural compounds and also develop a new and effective technique to isolate and identify these compounds. In this review, we can find that microalgae and cyanobacteria have a lot of potential in drug discovery, and we also provided a comprehensive detail on the different types of bioactive compounds found from these organisms along with their biological activity and mode of action. Also, most of the clinical drugs available in the market belong either to the polyketides or

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Fig. 9.1 The genome mining approach for natural product discovery in microorganisms: Following the identification and growth of a microorganism of interest, the genome sequence is obtained. Bioinformatic tools are then used to analyze the genome and identify cryptic BGCs. Silent BGCs are activated through heterologous expression in E. coli under the control of an inducible promoter. Novel metabolites are identified in culture extracts or supernatants, followed by their purification and characterization, typically using a combination of high-resolution mass spectrometry and 1D and 2D NMR spectroscopy

nonribosomal peptide classes of compounds, and, in this review, we found that cyanobacteria and microalgae are both highly rich in these compounds with many species showing high diversity of both pks and nrps genes. Because drug discovery in the past few decades is drastically declining, another alternative approach known as genome mining is promising (Fig. 9.1). This approach offers better results in comparison to the traditional screening method, and many important novel compounds have been discovered and identified through this technique. It involves the use of specialized bioinformatics as described above to identify various types of secondary metabolites BGCs and also predict the structure and chemistry of compounds from these gene clusters. This technique can also help in identifying BGCs from cyanobacteria and microalgae, and through heterologous expression we can isolate and identify the compounds and study for their bioactivity. Through this review, it can be concluded that microalgae and cyanobacteria can be the nextgeneration novel compound producers, and with the help of genome mining techniques, the depth and diversity of bioactive compounds at the genetic level can be assumed. Acknowledgments The author is thankful to CSIR-HRDG for financial support. Conflict of Interest The authors do not have any conflict of interest to declare.

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Chapter 10

Synthetic Biology-Based Advanced Biotechnological Approach in Microalgal Biorefinery Saeed Uz Zafar, Anju Mehra, and Pannaga P. Jutur

Abstract As fossil fuels are declining, global economies need sustainable energy sources. Biofuel, the most promising candidate for the energy crisis, is still not competitive as compared to fossil fuels. Thus, higher yields of biofuel and simultaneous production of high-value commodities (HVCs) to compensate for the production cost are a plausible strategy. Microalgae in this context are a successful candidate, due to their ability to produce various nutraceuticals, pharmaceuticals, and many other HVCs alongside biofuels. Higher sequestration of greenhouse gases (GHGs) to biomass and the ability to recycle nutrient-rich cosmopolitan waste with a biorefinery-based approach give microalgae an advantage over other photoautotrophs. This biofuel and HVC-rich biomass can be further enhanced by regulating some specific targets like pathway genes, transcription factors, enhancers, and repressors. Zinc finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs), and Clustered regulatory interspaced short palindromic repeats / CRISPR-associated protein 9 (CRISPR/Cas9) are some technologies used for this purpose. The combination of these synthetic biology approaches with bioprocess improvement can help in increasing biofuel and HVC production. However, the unavailability of microalgal genomes is a bottleneck in their genetic engineering for a sustainable biorefinery. The advances in multi-omics technologies give possible solutions for effectively understanding the microalgal genomes. Thus, in this chapter, we discuss microalgal physiology in light of synthetic biology and aforementioned genome editing techniques in combination with major bottlenecks and their solutions. Keywords Microalgae · Biorefinery · Synthetic biology · Genetic engineering · Biofuels

Saeed Uz Zafar and Anju Mehra contributed equally to this work. S. U. Zafar · A. Mehra · P. P. Jutur (*) Omics of Algae Group, Industrial Biotechnology and DBT-ICGEB Centre for Advanced Bioenergy Research, International Centre for Genetic Engineering and Biotechnology, Aruna Asaf Ali Marg, New Delhi, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 P. Verma (ed.), Micro-algae: Next-generation Feedstock for Biorefineries, Clean Energy Production Technologies, https://doi.org/10.1007/978-981-19-0680-0_10

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Abbreviations AB AD CRISPR/Cas9 DGDG DGTS FAMEs FAO FDA G3P GHGs GMP HEFA HHV HVCs NOx NPQ PAM RAAs RuBisCo RVD SOx TAGs TALENs UOP VS WHO ZGNs

10.1

Acetone-butanol Anaerobic digestion Clustered regulatory interspaced short palindromic repeats / CRISPR-associated protein 9 Digalactosyldiacylglycerol Diacylglyceroltrimethylhomoserine Fatty acid methyl esters Food and Agriculture Organization Food and Drug Administration Glycerol-3-phosphate Greenhouse gases Good manufacturing practice Hydrotreated fatty acids and esters High heating value High-value commodities Nitrogen oxides Non-photochemical quenching Protospacer adjacent motif Renin-angiotensin aldosterone system Ribulose-1,5-bisphosphate carboxylase/oxygenase Repeat variable domain Sulfur oxides Triacylglycerols transcription activator-like effector nucleases Universal oil products Volatile solid World Health Organization Zinc-finger nucleases

Introduction

Supporting microalgae-based bio-economy needs exploration to the potential and constraints toward biofuel and bioproducts. Some specific technological and economic barriers to the deployment of algae-derived biofuels include the cost of cultivation, production, and harvesting of biomass and products. The ongoing techno-economic article suggests that a cost-production cutting can be an important factor to make biofuel economic (Davis et al. 2016; Kumar and Verma 2021). A further approach that has been found is the simultaneous production of HVCs along with the biofuels, intending to strengthen the value of algal biomass. To enhance the production of bioproducts, a better understanding of relevant pathways, mechanisms, proteins, and enzymes involved in the conversion process is needed. This

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can help to establish a link between industrial-scale production and their stability in the respective markets. In this regard, microalgal cell factories can act as biorefinery facilities where biomass can be processed efficiently into different energy products (biodiesel, biogas, bioethanol, biojet fuel, bio-hydrogen, etc.) and non-energy products (proteins, nutraceuticals) along with HVCs (pigments, antioxidants, vitamins). Temperature, salinity, light, pH, medium composition, and CO2 supply are all environmental elements that can significantly alter the biochemical composition of algal biomass. For example, high light irradiance and nitrogen starvation are wellknown stress conditions that direct the carbon channel toward lipid synthesis (Goswami et al. 2021a; Wang et al. 2013). Before the selection of biofuel/any bioproduct from a suitable microalgal strain, a thorough physicochemical evaluation is considered as a critical step (Batista et al. 2013). In addition, fatty acid profiles play a key role in deciding the appropriate use of algal lipids and employing different methods to improve the analysis where direct transmethylation of lipids to fatty acid methyl esters (FAMEs) is a single step (Vanthoor-Koopmans et al. 2013; Bhardwaj et al. 2020). Based on the profile, algal lipids are used for different energy products. Moreover, microalgae have the potential to coproduce some non-energy products including proteins, carbohydrates, etc., that are used as food-feed (animal and fish food), functional food, etc. Some microalgae are available in the form of tablets as a health food supplement in many countries (Yen et al. 2013; Griffiths et al. 2012; Mata et al. 2010; Agrawal and Verma 2022). Other than that, microalgae produce some HVCs including pigments, vitamins, antioxidants, etc., that are used in the market as pharmaceuticals, nutraceuticals, cosmetics, and natural colorants but at a high price. Some specific microalgae are considered as commercial producers of carotenoids including H. pluvialis and D. salina for astaxanthin and β-carotene (Chow et al. 2013; Saini et al. 2021). Furthermore, synthetic biology is one of the potential technologies arising to make microalgal biomass more feasible for industrial applications. As there are advances in molecular biology techniques, methods for foreign gene integration, gene silencing, overexpression, and pathway engineering are becoming more and more available (Guihéneuf et al. 2016; NoorMohammadi et al. 2012; Kim et al. 2015). Although a certain lacuna remains in the form of codon bias, inefficiency exogene delivery systems, etc., the availability of high-level genome editing technologies such as ZFN, TALEN, and CRISPR/ Cas9-based gene editing has revolutionized microalgal nuclear, chloroplast, and mitochondrial genomic engineering (Guihéneuf et al. 2016; Chaturvedi et al. 2020). In this chapter, biorefineries are highlighted as the most promising approach for establishing a biomass-based economy. One of the main steps in biorefineries is to convert biomass into biofuels and high-value-added products; both traditional and advanced technologies for these transformations must be assessed, as these technologies must be used in tandem in a biorefinery.

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Algal-Based Biorefinery and Its Products

Biorefineries are similar to petroleum refineries by their use of biomass in the same manner as petroleum refineries use crude oil as a starting source to produce a variety of fuels and chemicals (Fig. 10.1). Biorefining is the long-term processing of biomass to produce energy, biofuels, and HVCs using biomass transformation methods and equipment (Agrawal et al. 2020; González-Delgado and Kafarov 2011). The IEA Bioenergy Task 42 document provides a more detailed and comprehensive description of a biorefinery, stating that it is “the sustainable processing of biomass into a spectrum of marketable products and energy” (Cherubini et al. 2007). Biorefineries have been recognized as the most promising method of establishing a biomass-based business. The application of algal feedstock for environment cleaning purposes has also been described.

10.2.1 Algae-Based Energy Products Microalgal biomass can be used for producing numerous energy products such as next-generation biofuels, bioactive compounds, food and feed additives, etc. (Mehariya et al. 2021; Benedetti et al. 2018). Because of these, approximately 7000 tons of dry algal biomass is produced worldwide annually, and the global market ranges between USD 3.8 and 5.4 billion (Brasil et al. 2017).

Fig. 10.1 Schematic representation of microalgal biorefinery with the significant potential of algalderived products

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Biodiesel

The notion of generating biofuels from microalgae emerged in the 1960s (Oswald and Golueke 1960). As oil prices and global warming increased, algae-based biodiesel again gained attraction because of its significance. Algal biodiesel is a carbon-neutral fuel since it absorbs about the same amount of CO2 as it releases during fuel combustion. Consequently, algae-based fuels are considered to be the most effective and sustainable to climate change (Ziolkowska and Simon 2014; Goswami et al. 2020a). Algal biodiesel and petroleum diesel are comparable in terms of energy density and high heating value (HHV) of 42.7 MJ/kg which is comparable to the algae-derived biodiesel, i.e., 41 MJ/kg (Rakopoulos et al. 2006; Xu et al. 2006). In addition, biodiesel improves the engine life as it has a higher viscosity (Bowman et al. 2006). When compared to conventional fuels, algal biodiesel emits 41% lower GHG emissions. In addition, saturated fatty acids (such as C16:0 and C18:0) are beneficial for winter operability, whereas monounsaturated fatty acids (such as C18:1) and polyunsaturated fatty acids (such as C18:3) are preferred for oxidation stability usually present in microalgal-based biodiesel (Chandra et al. 2019). There are different techniques used for lipid extraction from microalgae such as micro-emulsification, pyrolysis, etc., but the most common conversion technique used is transesterification (Robles-Medina et al. 2009), in which biodiesel is made up of monoalkyl esters produced from lipid (Demirbas 2007) and the reaction is very simple: Triglyceride þ 3 methanol $ glycerine þ 3 methyl esters ðbiodieselÞ

ð10:1Þ

an equilibrium reaction where an organic oil, or triglyceride, converts to biodiesel with the use of a catalyst (Demirbas 2007) and excess methanol makes the reaction go in the right direction. Moreover, some enzyme conversion techniques are employing lipases (extracellular and intracellular) due to comparatively simple downstream processing for the purification of other by-products with biodiesel. But they are expensive as compared to conventional chemical processes, and methanol and glycerol have to be used for their inactivation. Microalgal species selection for biodiesel production is influenced by fuel qualities and oil content (Islam et al. 2013) such as Chlorella, Crypthecodinium, Cylindrotheca, Dunaliella, Isochrysis, Nannochloropsis, Neochloris, Phaeodactylum, Porphyridium, Schizochytrium, and Tetraselmis genus that have lipid content up to 20–50% dry weight of microalgal biomass (Saifullah et al. 2014; Jalilian et al. 2020; Trivedi et al. 2015).

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Biogas

Biogas is generally produced by a naturally occurring process called anaerobic digestion (AD), combined action of bacteria and some archaea. The actual composition of biogas made from biomass is CH4 (55–70%) and CO2 (30–45%), and small quantities of H2S (50–2000 ppm), H2O, O2, and some trace hydrocarbons after that, the leftover contains nitrogen (Harun et al. 2010a, b; Braun 2007). Biogas generation from microalgae has numerous advantages compared to other sources since they can use versatile water, efficiently biomass utilization, cost-effective, nutrients recycling while producing sustainable biogas (Adarme et al. 2017; Saratale et al. 2018; Goswami et al. 2020b). Golueke and coworkers reported microalgae-based AD in 1957, employing Chlorella sp. and Scenedesmus sp. to generate 0.17–0.32 L CH4/g volatile solid (VS) (Golueke et al. 1957). Microalgae are the potential candidate for biogas production both characteristically and techno-economically. Specifically, microalgal methane yield is higher as compared to other sources such as green algae methane yield is 0.227 m3 kg1 VS and 0.262 m3 kg1 VS in brown algae while 0.189 m3 kg1 VS in sugar crops and 0.172 m3 kg1 VS of other lignocellulosic biomass (Song et al. 2015). Therefore, microalgae-based biogas is considered efficient and cost-effective (Ward et al. 2014; Saratale et al. 2018; Zamalloa et al. 2012). A problem with the biodegradability of lignocellulosic biomass is sluggish because of its structural complexity and lignin-resistant property to hydrolysis along with its toxicity to some organisms used in AD (Hossain et al. 2017; Kumar and Verma 2021; Passos et al. 2018; Neves et al. 2006). On the other hand, microalgal biomass has higher biodegradability since it has no lignin part (Saratale et al. 2018). Moreover, the leftover biomass slurry which is a by-product of biogas plants is another major issue (Holm-Nielsen et al. 2009; Xia and Murphy 2016). This leftover biomass after biogas production can be utilized by microalgae (Zhao et al. 2015; Bahr et al. 2014; Yan and Zheng 2013). In previous studies, biogas yields from some known microalgae were reported (ml/g VS) 587 for Chlamydomonas reinhardtii, 505 for Dunaliella salina, 335 for Chlorella kessleri (Mussgnug et al. 2010), 464 for Chlorella pyrenoidosa, and 369 for Chlorella vulgaris (Prajapati et al. 2014). Yet some considerable factors before selecting good microalgal strains are that it should have more cytoplasmic components, high growth rate, and stress resistance, and a major one is it should have a thin or no cell wall (Tijani et al. 2015). Lastly, the selected strain should be amenable to genetic modification to regulate metabolic processes and can improve tolerance to nutritional and environmental stressors.

10.2.1.3

Bioethanol

In general, bioethanol may be produced from any microalgae employing fermentation with specific microorganisms after converting the polysaccharides into simple sugars. Cholorococcum sp., Chlamydomonas sp., and Chlorella sp. are some microalgae widely used for this purpose. Moreover, brown algae are considered as

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the primary feedstock for bioethanol since it has a high carbohydrate content (Harun et al. 2010a, b, 2011; Nguyen et al. 2009; Kumar et al. 2020a, b; Choi et al. 2010; Lee et al. 2011; Daroch et al. 2013), and butanol can be a by-product during the fermentation (acetone-butanol) of algal biomass (Jung et al. 2013). Three possible ways are used to generate bioethanol from biomass where the traditional technique involves some pretreatment and enzymatic hydrolysis, followed by bacterial or yeast fermentation. The second technique includes the utilization of different metabolic processes which divert photosynthesis into alcohol and other products. Furthermore, a method called photo-fermentation requires genetic engineering to redirect the already existing pathways toward ethanol production (de Farias Silva and Bertucco 2016).

10.2.1.4

Bio-jet Fuel

One of the significant issues is the rising air transport demands. Some harmful oxides, such as carbon dioxide (CO2), nitrogen oxides (NOx), carbon monoxide (CO), sulfur oxides (SOx), and partly combusted hydrocarbons, are many trace chemicals emitted during the combustion of aviation jet fuel that is a problem for the aviation sector. As a result, it changes the atmosphere worldwide, which leads to ozone depletion (Lee et al. 2010). Renewable jet fuel has the potential to cut flightrelated GHG emissions by 60–80% as compared to fossil-fuel-based jet fuel. This jet fuel can be generated from algal biomass through different techniques, e.g., hydrotreatment (hydrotreated fatty acids and esters, HEFA) and Fischer-Tropsch (Sandquist and Guell 2012). In the HEFA process, the standard cleaning eliminates oxygen molecules and olefins and converts them into short-range diesel chain paraffin to increase the thermal and oxidative stability of this biomass-derived fuel increase (Eswaran et al. 2021). On the other hand, the gasification step is used for the formation of syngas (CO and H2) through the Fischer-Tropsch process. In this context, extensive research is going on in international companies named Shell and UOP (Universal Oil Products). In addition, renewable jet fuel was tested for two flights dated January 7 and 30, 2009 (Hendricks et al. 2011).

10.2.2 Algae-Based Non-energy Products 10.2.2.1

Carbohydrates

In general, microalgae accumulate carbohydrates by sequestering environmental CO2 using ATP/NADPH energy through the Calvin cycle (Nelson et al. 2008). Carbohydrates and lipid both can act as precursors for TAG synthesis as the glycerol-3-phosphate (G3P), a precursor to generate via glycolysis process (Ho et al. 2012; Rismani-Yazdi et al. 2011; Goswami et al. 2021c). Therefore, for the advancements in carbohydrate-based biofuel production, understanding and

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related metabolic pathways are crucial. Numerous cultivation strategies can be used to enhance the accumulation including CO2 supplementation, pH variation, nitrogen limitation, and temperature variation (Sukenik 1991; D'Souza and Kelly 2000; De Oliveira et al. 1999; Khalil et al. 2010). Most of the algal carbohydrates are made up of glucose, starch, and cellulose/hemicellulose with some other polysaccharides (John et al. 2011). Moreover, carbohydrates present in the cell walls are also used in biofuel production. In red algae, galactans (carrageenan and agar) are the major polysaccharides (Lobban and Wynne 1981; McHugh 2003) which can be extracted by directly dissolving them into an aqueous solution. On the other hand, alginate (40% of dry weight), mannitol, and glucans are present in brown macroalgae (Draget et al. 2005). Nowadays, algal polysaccharides are considered a class of high-value compounds with several applications in different industries such as food, textiles, cosmetics, and pharmaceuticals. In addition, sulfated polysaccharides have a wide range of applications because of their pharmacological activity.

10.2.2.2

Pigments

Natural pigments play a vital role in photosynthetic metabolism and algal coloring. Microalgae include at least three types of pigments: phycobilins, chlorophylls, and carotenoids. Therefore, apart from chlorophyll, phycobiliproteins have significance in improving the efficiency of light energy utilization. In addition, carotenoids also have antioxidant, anticancer, and other therapeutic properties (Ciccone et al. 2013; Guedes et al. 2011; Goswami et al. 2021b). Some carotenoid compounds have importance in pharmaceuticals such as astaxanthin used in chronic inflammatory illnesses, eye infections, skin diseases, etc., and H. pluvialis, a green microalga, is considered the prime natural producer of astaxanthin (1.5–3.0% of dry weight) (Batista et al. 2013). Furthermore, lutein, zeaxanthin, and canthaxanthin are used for coloration in food industries and some in pharmaceuticals. Phycobiliproteins, phycocyanin, and phycoerythrin are also being employed in food and cosmetics. In addition, β-carotene is used in the food industry as a precursor of vitamin A. In addition, major HVCs and specific producers with their properties were shown in Table 10.1.

10.2.2.3

Protein

Proteins are the major macromolecules present in microalgae (60% of dry weight) that are utilized in different sectors including food and feed industries (fish/animal feeds), bioplastics and fertilizers, etc. (Gnansounou and Raman 2016; Brennan and Owende 2010). Some selected microalgae are Chlorella sp. and Dunaliella sp. which have high protein content. The US Food and Drug Administration (FDA) has categorized some genus such as Chlorella, Dunaliella, Haematococcus, and Schizochytrium as GRAS food sources (Walker et al. 2005). Furthermore, proteins, protein hydrolysate concentrates, and peptide products may offer health

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Table 10.1 Summary of potential high-value products from different microalgae S. no. 1. 2.

Microalgae Botryococcus braunii Chlorella zofingiensis

Product Echinenone

Application Antioxidant

Astaxanthin

Pigmenter (aquaculture), antioxidant Pigmenter (aquaculture, poultry and food) Antioxidant, food pigmenter Pigmenter (food), pro-vitamin A, antioxidant

3.

Chlorella sp.

Canthaxanthin

4.

Chlorella ellipsoidea Dunaliella salina

Zeaxanthin

5.

β-carotene

6.

Dunaliella

Phytoene, phytofluene

Antioxidant, cosmetics

7.

Phaeodactylum tricornutum

Fucoxanthin

Antioxidant

8.

Scenedesmus sp. Rhodophyta, Cryptophyta, Glaucophyta

Lutein

Antioxidant

Phycobilins (phycocyanin, phycoerythrin, allophycocyanin)

Natural pigment (e.g., cosmetics and food products), fluorescent conjugates, antioxidant, etc.

9.

References Jäger et al. (2002), Matsuura et al. (2012) Lemoine and Schoefs (2010), Gorgich et al. (2021) Sibi et al. (2020) Bouyahya et al. (2021), Qi and Kim (2018) Pourkarimi et al. (2020), Harvey and Ben-Amotz (2020), Xu et al. (2018), Keramati et al. (2021) Srinivasan et al. (2017), Xu and Harvey (2020) McClure et al. (2018), Yang and Wei (2020);, Pereira et al. (2021) Molino et al. (2020), Rajendran et al. (2020) Montoya et al. (2021), Eltanahy and Torky (2021)

advantages such as heart-health benefits due to their capacity to block enzymes in the renin-angiotensin-aldosterone system (RAAS) and lower blood pressure (Neklyudov et al. 2000). Algal proteins are approved for human consumption by the Food and Agriculture Organization (FAO) and the World Health Organization (WHO); however, caution must be taken due to reports of toxins in microalgae (Heussner et al. 2012).

10.2.2.4

Biomaterials and Bioproducts

Microalgae have potential applications as biomaterials and bioproducts due to their immense properties such as agar, a by-product of microalgal biorefinery used for gel formation. Some microalgal extracts have the antiaging property; even Chlorella sp. have a long history of usage in the skincare industry as antiaging, invigorating, or regenerative lotions (Chen et al. 2013). The most significant component in Chlorella sp. from a medicinal perspective is 1,3-glucan, which is a powerful immunostimulator, antioxidant, antiatherosclerotic, etc. (Spolaore et al. 2006). In

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general, microalgae are considered as the source of all vitamins also (Richmond 2008). Biochemicals and other products are influenced by the type of microalgal strain and their cultivation conditions. Furthermore, the yield of the product depends on the different factors affected during growth. Therefore, selecting algal strains and their growth conditions are primary factors to produce the desired product. In addition, supplementation of some low-cost nutrients or flue gas can reduce the production along with the higher production. To increase product yield while lowering total operating costs, a significant R&D effort is necessary.

10.3

Bioprocess for Production of Microalgal Biomass and Bioproducts

Microalgal biomass and fine chemical synthesis from microalgae have developed algal bioprocess technologies with low constraints such as lab to industry. However, this lab-to-industry concept is hampered by numerous limitations including costly culturing techniques especially used in large-scale cultivation. So, focusing on the economic benefits requires the intricate assessment of bioprocesses used for biomass and its bioproducts. Improving the culturing strategy and employing better bioreactor design and synthetic biology are good approaches for higher production of biomass and bioproducts.

10.3.1 Microalgal Cell Physiology, Biochemistry, and Metabolism Culturing conditions such as nutrient starvation, light regime, intensity, etc., can easily influence lipid accumulation in microalgal cell factories, due to cell’s potential to change the cellular mechanisms to combat any stressed condition, especially lipids. These stress conditions are considered as different parameters in several studies to enhance the lipid content inside the cell, although these restrict the proper growth of cells. As a result, cellular mechanisms direct the metabolic pathways toward the lipid biosynthesis and store the lipid in the form of triacylglycerol (TAG) molecules (Courchesne et al. 2009; Opute 1974; Hu et al. 2008). This concept has been studied in different microalgal strains (Hu et al. 2008; Karemore et al. 2013; Illman et al. 2000), and the reason might be the activation of critical enzymes which are responsible for acyl-CoA to TAG, including DGAT which converts diacylglycerols to TAGs and malic enzyme which provides NADPH which get activated under nitrogen starvation (Boyle et al. 2012; Fan et al. 2014). In the case of phosphate starvation, diacylglycerol trimethyl homoserine (DGTS) and digalactosyldiacylglycerol (DGDG) enzymes are activated which leads to the accumulation of lipid droplets inside the cell (Khozin-Goldberg and Cohen 2006). James

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and Nachiappan (2014) worked on the concept of phosphate starvation in yeast and observed that phospholipids act as phosphate sources under these starved conditions; as a result, cells grow well without accumulating lipid. In some cases, the mutation of phosphate transporters can lead to the activation of different acyltransferase genes; as a result, cells produce neutral lipids (James and Nachiappan 2014). Other than that, some chemical modulators epigallocatechin gallate and butylated hydroxyanisole can also enhance lipid content inside the cell through some signaling pathways (Franz et al. 2013). Metabolic engineering is considered an advanced tool for the implementation of biopharmaceuticals as it has been successfully done in some photosynthetic organisms (Sen 2007; Bhattacharya 2007; De Bhowmick et al. 2015). Furthermore, nowadays, DNA editing, molecular biotechnology, random mutagenesis, and nanotechnology are popular technologies to improve the interested product yield without restricting the growth of the cell.

10.3.2 Commercial Production of HVCs from Microalgae The commercialization of HVCs from microalgae depends on the stability of a suitable market that can create reasonable prices, while the typical supply and demand rules also apply to the products. These are subjected to specific regulations and standards as most of them are nutraceuticals, which overall affect the production process as well as other attributes such as labeling requirements, which varied on the country’s basis. All of these enhanced the cost of the product. As a result, getting an algal product to market is a difficult procedure. Grobbelaar (2003) (Grobbelaar 2003), Gershwin and Belay (2008) (Belay 2007; Gershwin and Belay 2007), and Gellenbeck (2012) (Gellenbeck 2012) examined several of the regulatory and product quality challenges. Some standards which required algal products to be used as a food additive were discussed by Zeller (2005) and Ryan et al. (2010). The FDA made a food safety modernization act into law, which necessitates a food additive petition with the FDA which must be supported by some clinical or nonclinical studies that show the product’s safety. A few instances of such studies are Hammond et al. (2001, 2002) (Hammond et al. 2001; Abril et al. 2003) and Kroes et al. (2003) (Kroes et al. 2003) for the usage of Schizochytrium sp. for DHA oils and Spiller and Dewell (2003) (Spiller and Dewell 2003) for the usage of Haematococcus sp. for astaxanthin (Borowitzka 2013; Saini et al. 2021). There is a major challenge for microalgae-based product industries that have to compete with the price and have a differential edge from other available products to be in high demand. However, to increase microalgal bioproducts, a schematic pathway is required, which includes a selection of suitable strains on the basis of the accumulation of these HVCs, culture conditions that influence these HVCs, genetic engineering that leads to improvement of the strain, and greater accumulation of these HVCs and scale-up at industrial level (Guihéneuf et al. 2016).

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Synthetic Biology in Microalgae Toward Biofuels and Bioproducts

Synthetic biology, an emerging discipline aiming toward redesigning or rebuilding artificial life through existing biological methods, is one of the major approaches for enhancing microalgal biofuel and bioproduct productivities. It involves the modulation and manipulation of genetic circuitry for enhancing desired products by redesigning metabolic and genetic tools (Anand et al. 2017). Synthetic biology differs from molecular biology in terms of attaining defined and predictable genetic structures for complex results like the repression or enhancement of genes (Saini et al. 2020). Thus, a much wider knowledge of regulatory systems is required in synthetic biology. One of the most important requirements for synthetic biology is BioBricks, the interchangeable segments of DNA involved in the genetic and metabolic regulation of cellular functioning. Identification of regulatory targets is also essential for identifying these BioBricks.

10.4.1 Key Regulatory Networks in Microalgae Promoters, ribosome-binding sites, enhancers, etc., are essential BioBricks used in synthetic biology (Saini et al. 2020). One strategy for the improvement of microalgal productivities can be targeting the biochemical pathways (Naduthodi et al. 2021). Metabolic networks, key enzymes involved, regulatory hubs like transcription factors, etc., can be important targets for enhancing microalgal biomass, biofuel, and bioproduct productivities. One method to increase the expressions of native proteins is by using strong promoters (Kong et al. 2019). Thus, the use of both native and foreign promoters as BioBricks has been done to express target genes (Saini et al. 2020). For example, enhancing photo-generation of reducing power and CO2 fixation to improve biomass has been a widely adopted strategy. Enhanced concentration of native ribulose-1,5bisphosphate carboxylase/oxygenase (RuBisCo) led to improved growth rates in Nannochloropsis salina (Wei et al. 2017). Another aspect is the replacement of the native cellular protein with a better homolog. For example, RuBisCo with superior or engineered variants with either higher catalytic activity or CO2/O2 specificity can be transferred to enhance C3 cycle and thus CO2 fixation. Chlamydomonas reinhardtii RuBisCo had been replaced by Arabidopsis sp., spinach, and sunflower RuBisCo using plasmid transformation through electroporation, which resulted in 3–11% increased specificity (Genkov et al. 2010). Other than replacement, upregulation of RuBisCo in N. oceanica led to enhancement in photosynthetic biomass (Wei et al. 2017). Besides RuBisCo, many other enzymes of the C3 cycle have been targeted such as sedoheptulose bisphosphatase (SBP) (De Porcellinis et al. 2018) and fructose bisphosphate aldolase (FBA) (Janasch et al. 2019) for improving

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CO2 fixation. SBP from C. reinhardtii improved photosynthetic activity when overexpressed in Dunaliella bardawil (Fang et al. 2012). Another major strategy for improving biomass productivities is decreasing photorespiration which generates toxic compounds like 2-phosphoglycolate. Photosynthetic microbes have evolved an efficient strategy called carbon-concentration mechanism or CCM to avoid photorespiration by increasing CO2 concentration in the proximity of RuBisCo (Kumar et al. 2020a, b). Certain regulatory factors for CCM such as carbonic anhydrases and the inorganic carbon transporters are considered potential genetic engineering targets (Wang et al. 2015). Overexpression of C. reinhardtii bicarbonate transporter in N. salina improved biomass accumulation (Vikramathithan et al. 2020). However, strategies such as engineering heterologous pathways like the malate cycle, glycerate pathway, etc., are more prevalent. They have been found in plants to improve CO2 concentrations in chloroplasts and reduce photorespiration (Claassens et al. 2020; Kebeish et al. 2007). Other checkpoints such as repressors can be negatively regulated in order to enhance microalgal biomass. Microalgal lipids have gained attention due to several industrial importance. Both the quantity and the quality of lipids have an influence on the industrial use of microalgal feedstocks. Various lipid pathway genes over the past few decades have been a target of knockdowns and overexpression. Overexpression of the malic enzyme gene led to an increased lipid content in Phaeodactylum tricornutum (Xue et al. 2015). This can be increased by enhancing acetyl-CoA carboxylase or ACC expression, which otherwise increases only under nutrient limitation conditions (Kumar et al. 2017). ACC was first overexpressed in Cyclotella cryptica and Navicula saprophila using plasmid transformation and found enhancement in fatty acid synthesis (Dunahay et al. 1996). Insertion of heterologous pathways has also proven to be a beneficial aspect of synthetic biology. One example could be chl-f biosynthesis in microalgae, which improved the biomass yields by enhancing the light harvesting mechanism (Ho et al. 2016). Another example is the insertion of heterologous β-carotene ketolase (BKT) in Chlamydomonas reinhardtii that started astaxanthin production in this alga (Lee et al. 2018). Thus, a thorough understanding of the metabolic pathways and their regulation is required for enhancing a bioproduct using synthetic biology tools. The combination of these efficient and transplantable pathways with the state-of-the-art techniques available for heterologous protein expression can help improve photosynthetic efficiency in microalgae.

10.4.2 Genetic Engineering and Genome Editing in Microalgae Genetic engineering is the delivery of genetic material to the genome, thus resulting in genetic modifications. Microalgae can have genome transformations at nuclear, plastidial, and mitochondrial levels (Specht et al. 2010). Techniques such as

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electroporation, glass-bead-mediated stress, and gene-gun bombardment have been used for microalgal transformation (Coll 2006; Purton et al. 2013). Recently, there have been promising developments in microalgal genome-editing toolbox including inducible promoters for multi-cistronic expression of heterologous proteins, gene stacking, CRISPR, etc. (Naduthodi et al. 2021). A recent development was made for a stable nuclear transformation via the protoplast transformation method with a fluorescent reporter system in Chlorella vulgaris (Yang et al. 2015). However, for any polyethylene glycol (PEG)-mediated electroporation and transformation, cell wall can be a barrier. Cellulase and hemicellulase treatment has shown an effective strategy to achieve Chlorella vulgaris protoplasts (Hawkins and Nakamura 1999). Even so, the delivery of genetic material is less efficient in microalgae as compared to plants. Successful genome editing is based on robust transformation technology in an organism (Jeon et al. 2017). Nevertheless, progress has been made toward improving the catalog of genetic engineering tools for microalgae. Certain technologies such as ZFN, TALENs, CRISPR/Cas9/Cpf, homologous recombination, and RNAi are shown in Fig. 10.2 and exemplified in Table 10.2. RNAi is one molecular method at transcript level similar to upregulation of photosynthetic carbon fixation, strategies such as knockdown of the competitive pathways, or upregulation of the target pathways that is a widely adopted strategy in synthetic biology for enhancing the desired products (Saini et al. 2020). Genome editing tools such as nucleases, ZFNs, TALENs, and clustered regularly interspaced short palindromic repeats and CRISPR-associated systems (CRISPR/ Cas), have been widely used in many organisms (Kumar et al. 2020a, b). All these tools insert double-stranded breaks in the genome that can be repaired either by nonhomologous end joining (NHEJ), which can cause insertions and deletions, or homology-directed repair (HDR), which requires an exogenous donor DNA that does insertion or deletion in a gene. ZFNs are small endonucleases with multiple zinc finger domains to bind to the DNA target sites and a Fok1 endonuclease domain that creates double-stranded breaks, few base pairs apart from the site. ZFNs are incorporated in the microalgal cells through a plasmid containing the nuclease sequence, which is incorporated in the cell (Greiner et al. 2017). ZFNs have been used for multiple microalgal targets such as C. reinhardtii (Sizova et al. 2013). ZFNs are easier to transform due to their smaller sizes and have been effectively shown on multiple microalgal targets. However, ZFNs prefer homology-directed repair and need developments to make them more specific and less resource-intensive (Kumar et al. 2020a, b). One very specific and less resource-intensive nuclease is TALEN. These are also Fok1 conjugates; however, their DNA binding motifs are repeat variable domain (RVD). An RVD is a bunch of helix-turn-helix motifs which recognize individual bases for specifically interdigitating in DNA. Functionally TALENs and ZFNs are similar to each other due to Fok1 domain. However, TALENs have gained much more specificity in the DNA binding domain. TALENs have been used for model microalga Phaeodactylum tricornutum to generate knockouts of multiple genes including UMP synthase (Serif et al. 2018). Similarly, gene editing was done using TALENs in Chlamydomonas reinhardtii for endogenous expression of

Synthetic Biology-Based Advanced Biotechnological Approach in. . .

Fig. 10.2 Mechanism of genome editing and genetic engineering techniques used in synthetic biology: (a) Zn-finger nucleases; (b) TALEN, each conjugated with nuclease Fok1; (c) CRISPR/Cas9 system; (d) template-based, nonhomologous end joining; (e) homologous recombination; (f) insertion/deletions caused during repair; (g) type II restriction enzyme-based homologous recombination; (h) RNA interference (Jeon et al. 2017)

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Table 10.2 Examples of genetic engineering and gene editing techniques used in microalgae Technique Homologous recombination Plasmid transformation RNA interference

Strain Nannochloropsis sp. Chlamydomonas reinhardtii C. reinhardtii

ZFNs

C. reinhardtii

TALEN

Phaeodactylum tricornutum Dunaliella salina

CRISPR/Cas9

Genetic transformation Native nitrate reductase and nitrite reductase knockout PSY from Chromochloris zofingiensis overexpressed Light harvesting complex LHCBM1-11 downregulation Channelrhodopsin 3 or COP3 knockdown Native UMP synthetase knockout Native CHYB gene knocked down (mutated)

References Kilian et al. (2011) Cordero et al. (2011) Mussgnug et al. (2007) Sizova et al. (2013) Serif et al. (2018) Hu et al. (2021)

ARS1 and ARS2 (Gao et al. 2014). However, to date, not much use of TALENs has been done for Chlamydomonas reinhardtii despite the exemplification of TALENs being used in other organisms (Kumar et al. 2020a, b). Due to their increased specificity as compared to ZFNs, and no repeats between the linkages, TALENs are a widespread tool for gene editing. However, large construct and protein sizes, undesirable recombination events triggered by repetitive sequences, etc., are a few of the considerable bottlenecks. Moreover, both ZFNs and TALENs need two proteins per target, due to dimeric binding. However, genome editing tools require no protein dimerization. CRISPR/cas9 system is a bacterial immune response system against bacteriophages that can be used for genome editing in microalgae. The technology utilizes a single guide RNA strand and a recombinant enzyme called Cas9 protein which binds to this guide RNA. The small guide RNA binds to the target site where a doublestranded break is to be made. The Cas9 is the protein that binds to this guide RNA and creates double-stranded breaks at the protospacer adjacent motif (PAM) after a 2–6 bp DNA sequence following the CRISPR binding site. CRISPR/Cas9 system has been successfully used in C. reinhardtii (Jiang et al. 2014). However, the study used constitutive expression of Cas9, causing cytotoxic effects. Transient delivery of Cas9 protein and CRISPR RNA complex through electroporation is also established (Shin et al. 2016). Other methods such as lentiviral transduction and plasmid transformation are also widely used for CRISPR/Cas9 system administration in the microalgal cell. An ortholog of Cas9 called Cpf1 is also widely used for single-step co-delivery of CRISPR/Cpf1 RNP complexes, leading to increased efficiency (Ferenczi et al. 2017). Moreover, CRISPR technology has also demonstrated fruitful in other model organisms like P. tricornutum. Successful simultaneous knockdown of multiple genes was also demonstrated in P. tricornutum using CRISPR technology (Serif et al. 2018). Various transcription factors have also been edited by CRISPR and intrinsically expressed Cas9 in an N. oceanica editor line (Wang et al. 2016). CRISPR/Cas9 systems have revolutionized the genome editing process, but there are reports with inconsistencies in the editing efficiency with the system

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and also constitutive Cas9 expression leading to undesired reediting (Slattery et al. 2018). One solution to this could be the episomal-vector system with transient Cas9. However, episomal maintenance is a species-specific adaptation process that needs to be optimized prior to microbial engineering (Kumar et al. 2020a, b).

10.5

Bottlenecks and Future Perspectives

One reason for attempts of microalgal genome editing having a limited success rate (Jeon et al. 2017) is the very limited number of BioBricks such as promoters, regulatory hubs, etc., being defined in microalgae that do not fulfill the need for synthetic biology (Ginsberg et al. 2017). Hence, a need of understanding the key regulatory mechanisms arises here, in order to develop new sets of BioBricks. Due to the oxygenic nature of photosynthesis, it is difficult to synthesize oxygen-sensitive enzymes in microalgae. However, many cyanobacteria fix nitrogen, an oxygensensitive process, in the form of heterocysts and that can provide a solution to this problem (Saini et al. 2020). Another issue with microalgae is non-photochemical quenching (NPQ), a protective mechanism against photo-oxidative damage that generates no reducing power for CO2 fixation. Disruption of chloroplast signal recognition particle led to the truncation of antenna size which led to better light utilization and thus avoided NPQ leading to improved photosynthetic efficiency (Jin et al. 2001; Shin et al. 2016). The lack of known selection markers and low transformation efficiency has proven to be the major difficulties in the development of genome editing toolbox in microalgae. Microalgae still have a low transformation efficiency, even compared to plants (Jeon et al. 2017). Although higher transgenic protein expression is observed in chloroplast transformation (Giardi et al. 2011), it has its perks as the lack of PTMs, codon bias, untranslated region variation, etc. (Gimpel and Mayfield 2013; Specht et al. 2010). The biggest bottleneck for microalgal genome editing, however, is the lack of genomic data (Guihéneuf et al. 2016). However, with the advancement in next-generation sequencing and omicsbased technologies, microalgal genomes are becoming more available. Omics technologies, known as “algomics,” specifically for algae, help in designing a broad view of the algal system. Functionally, it provides huge and computationally decipherable datasets. This could allow for the development of better transformation vectors, and new BioBricks could be made available for synthetic biologists for microalgae.

10.6

Conclusions

Due to their ability to coproduce multiple bioproducts along with biofuels, microalgae are a potential target for industries. Combined with the potential to reduce the carbon footprint and GHGs, microalgae can be used for treating wastewaters. However, an effective biorefinery needs a schematic workflow, where

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microalgae that can produce various relevant products such as pigments, proteins, nutraceuticals, etc., can be cultivated in HVC enhancing conditions and also engineered to produce enhanced contents of these HVCs. Synthetic biology holds great potential for microalgae. Many technologies such as genetic engineering tools like homologous recombination and RNAi, combined with advanced genome editing tools like ZFNs, TALENs, and CRISPR/Cas9 systems, can help to engineer microalgae in a regulated way for specific bioproducts. Multiple genetic targets such as those targeting photosynthesis, growth, lipid biosynthesis, and HVC biosynthesis can be manipulated and can thus be potential BioBricks. Regulatory elements such as promoters, transcription factors, repressors, etc., can also be manipulated, inserted, or deleted to study, modify, enhance, or repress a specific pathway which can help in increasing the potential of microalgal biorefinery. However, the unavailability of microalgal genomes, lack of information regarding regulatory mechanisms, unique physiology, etc., pose a potential bottleneck for microalgal genome editing. Yet, the ongoing research using multi-omics platforms and increasing information regarding microalgal genome and epigenome is aiding synthetic biologists in deciphering potential targets and designing new BioBricks. Competing Interest The authors declare there is no competing interest to declare.

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