Imaging Mass Spectrometry: Methods and Protocols [2 ed.] 107163318X, 9781071633182

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Methods in Molecular Biology 2688

Laura M Cole Malcolm R Clench Editors

Imaging Mass Spectrometry Methods and Protocols Second Edition

METHODS

IN

MOLECULAR BIOLOGY

Series Editor John M. Walker School of Life and Medical Sciences University of Hertfordshire Hatfield, Hertfordshire, UK

For further volumes: http://www.springer.com/series/7651

For over 35 years, biological scientists have come to rely on the research protocols and methodologies in the critically acclaimed Methods in Molecular Biology series. The series was the first to introduce the step-by-step protocols approach that has become the standard in all biomedical protocol publishing. Each protocol is provided in readily-reproducible step-by step fashion, opening with an introductory overview, a list of the materials and reagents needed to complete the experiment, and followed by a detailed procedure that is supported with a helpful notes section offering tips and tricks of the trade as well as troubleshooting advice. These hallmark features were introduced by series editor Dr. John Walker and constitute the key ingredient in each and every volume of the Methods in Molecular Biology series. Tested and trusted, comprehensive and reliable, all protocols from the series are indexed in PubMed.

Imaging Mass Spectrometry Methods and Protocols Second Edition

Edited by

Laura M. Cole and Malcolm R. Clench Biomolecular Sciences Research Centre, Sheffield Hallam University, Sheffield, UK

Editors Laura M. Cole Biomolecular Sciences Research Centre Sheffield Hallam University Sheffield, UK

Malcolm R. Clench Biomolecular Sciences Research Centre Sheffield Hallam University Sheffield, UK

ISSN 1064-3745 ISSN 1940-6029 (electronic) Methods in Molecular Biology ISBN 978-1-0716-3318-2 ISBN 978-1-0716-3319-9 (eBook) https://doi.org/10.1007/978-1-0716-3319-9 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Humana imprint is published by the registered company Springer Science+Business Media, LLC, part of Springer Nature. The registered company address is: 1 New York Plaza, New York, NY 10004, U.S.A.

Preface This protocol series aims to provide insights into key methodologies and breakthroughs from the past 5 years since the first editorial of Methods in Molecular Biology’s Imaging Mass Spectrometry: Methods and Protocols, published in 2017. Within the last 5 years alone, mass spectrometry imaging (MSI) has continued to ignite enthusiasm amongst the analytical scientific community, enjoying stratospheric success in the analysis and spatial observation of target species. The popularity of MSI amongst scientists appears to be not only due to the vast potential of applications, but also the incessant, emerging technologies that drive the momentum of this powerful technique. The unique, label-free, multiplexing nature of MSI has been known to dramatically unleash a variety of experimental perspectives, all with an aim to offer a distinctive molecular snapshot of the tissue under study. Whether the tissue be a patient biopsy, finger mark, xenograft or 3D culture model, each experiment holds the exciting possibility of visualising that opportunistic molecule, captured in situ. Exploration of lipids, peptides and metabolites using MSI has been extensive, with recent increased interest in metallomics including more intricate molecular acquisitions such as Imaging mass cytometry (IMC). The authors herein work directly or in collaboration with mass spectrometry and all strive to push the boundaries in their specialist subject areas. A range of state-of-the-art techniques are described within this protocol series some of which feature; nano-Desorption Electrospray Ionisation (nDESI), Matrix Assisted Laser Desorption Ionisation-2 (MALDI-2), Laser Ablation – Inductively Coupled Plasma-Mass Spectrometry (LA-ICP-MS) and IMC with a variety of diverse samples including eye tissue, crop analysis, 3D cell culture models and counterfeit goods analysis to mention a few. Collaborative research partnerships have been invaluable for myself as a mass spectrometrist and member of The Centre for Mass Spectrometry Imaging, Biomolecular Sciences Research Centre (BMRC), Sheffield Hallam University. This research centre is directed by co-Editor and Head of Research Professor Malcolm R Clench and is now part of the Sheffield Multimodal Imaging centre (SMIC) maintaining and forming new working relationships with fellow scientists across the globe. This protocol series will demonstrate how MSI is progressing, both with creative scientific methods and technological advancements in high spatial tissue imaging and image processing. Furthermore, a unique perspective of ‘Mass Spectrometry Imaging: The Next Five Years’ concludes this protocol series. The multimodal imaging era is truly upon us! Laura M. Cole

Sheffield, UK

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

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1 MALDI and Trace Metal Analysis in Age-Related Macular Degeneration . . . . . . 1 Joshua Millar, Susan Campbell, Catherine Duckett, Sarah Doyle, and Laura M. Cole 2 HistoSnap: A Novel Software Tool to Extract m/z-Specific Images from Large MSHC Datasets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Kenneth Verheggen, Nivedita Bhattacharya, Marthe Verhaert, Bram Goossens, Raf Sciot, and Peter Verhaert 3 Spatially Resolved Quantitation of Drug in Skin Equivalents Using Mass Spectrometry Imaging (MSI). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 Cristina Russo and Malcolm R. Clench 4 Update DESI Mass Spectrometry Imaging (MSI) . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 Emmanuelle Claude, Mark Towers, and Emrys Jones 5 Liquid Extraction Surface Analysis Mass Spectrometry Imaging of Denatured Intact Proteins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 Emma K. Sisley, James W. Hughes, Oliver J. Hale, and Helen J. Cooper 6 MALDI MS Imaging of Cucumbers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 Robert Bradshaw 7 The Adaptation of the QV600 LLI Milli-Fluidics System to House Ex Vivo Gastrointestinal Tissue Suitable for Drug Absorption and Permeation Studies, Utilizing MALDI MSI and LC-MS/MS . . . . . . . . . . . . 71 Chloe E. Spencer, Catherine J. Duckett, Stephen Rumbelow, and Malcolm R. Clench 8 Ambient Mass Spectrometry Imaging by Water-Assisted Laser Desorption/Ionization for Ex Vivo and in Vivo Applications. . . . . . . . . . . . . . . . . 83 Nina Ogrinc, Paul Chaillou, Alexandre Kruszewski, Cristian Duriez, Michel Salzet, and Isabelle Fournier 9 Cytological Cytospin Preparation for the Spatial Proteomics Analysis of Thyroid Nodules Using MALDI-MSI . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 Isabella Piga, Fabio Pagni, Fulvio Magni, and Andrew Smith 10 Matrix Effects Free Imaging of Thin Tissue Sections Using Pneumatically Assisted Nano-DESI MSI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 Leonidas Mavroudakis and Ingela Lanekoff 11 Laser Ablation Inductively Coupled Plasma Mass Spectrometry Imaging of Plant Materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123 Joseph Ready and Callie Seaman

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Sample Preparation for Metabolite Detection in Mass Spectrometry Imaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ` , Elise Midtbust, Maria K. Andersen, Marco Giampa Therese S. Høiem, Sebastian Krossa, and May-Britt Tessem Multimodal Mass Spectrometry Imaging of an Aggregated 3D Cell Culture Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Lucy Flint Visualization of Small Intact Proteins in Breast Cancer FFPE Tissue . . . . . . . . . . ` , Maria K. Andersen, Sebastian Krossa, Marco Giampa Vanna Denti, Andrew Smith, and Siver Andreas Moestue Negative Ion-Mode N-Glycan Mass Spectrometry Imaging by MALDI-2-TOF-MS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jens Soltwisch and Bram Heijs MS1-Based Data Analysis Approaches for FFPE Tissue Imaging of Endogenous Peptide Ions by Mass Spectrometry Histochemistry (MSHC) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nivedita Bhattacharya, Konstantin Nagornov, Kenneth Verheggen, Marthe Verhaert, Raf Sciot, and Peter Verhaert Perspective: Mass Spectrometry Imaging – The Next 5 Years . . . . . . . . . . . . . . . . . Malcolm R. Clench and Laura M. Cole

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Contributors MARIA K. ANDERSEN • Department of Circulation and Medical Imaging, NTNU – Norwegian University of Science and Technology, Trondheim, Norway NIVEDITA BHATTACHARYA • ProteoFormiX, Beerse, Belgium; MassTech Inc., Columbia, MD, USA ROBERT BRADSHAW • Biomolecular Sciences Research Centre (BMRC), Sheffield Hallam University, Sheffield, UK SUSAN CAMPBELL • Centre for Mass Spectrometry Imaging, Biomolecular Research Centre, Sheffield Hallam University, Sheffield, UK PAUL CHAILLOU • Universite´ de Lille, Inserm, U1192 - Prote´omique Re´ponse Inflammatoire Spectrome´trie de Masse – PRISM, Lille, France EMMANUELLE CLAUDE • Waters Corporation, Wilmslow, UK MALCOLM R. CLENCH • Centre for Mass Spectrometry Imaging, Biomolecular Sciences Research Centre, Sheffield Hallam University, Sheffield, UK LAURA M. COLE • Centre for Mass Spectrometry Imaging, Biomolecular Sciences Research Centre, Sheffield Hallam University, Sheffield, UK HELEN J. COOPER • School of Biosciences, University of Birmingham, Edgbaston, Birmingham, UK VANNA DENTI • Proteomics and Metabolomics Unit, Department of Medicine and Surgery, Vedano al Lambro, Italy SARAH DOYLE • Immunobiology Research Group, Department of Clinical Medicine, Trinity College Institute of Neuro-science (TCIN), School of Medicine, Trinity College Dublin (TCD), Dublin, Ireland CATHERINE J. DUCKETT • Centre for Mass Spectrometry Imaging, Biomolecular Sciences Research Centre, Sheffield Hallam University, Sheffield, UK CRISTIAN DURIEZ • Universite´ de Lille, Inserm, U1192 - Prote´omique Re´ponse Inflammatoire Spectrome´trie de Masse – PRISM, Lille, France LUCY FLINT • Centre for Mass Spectrometry Imaging, Biomolecular Research Centre, Sheffield Hallam University, Sheffield, UK; Imaging and Data Analytics, Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK ISABELLE FOURNIER • Universite´ de Lille, Inserm, U1192 - Prote´omique Re´ponse Inflammatoire Spectrome´trie de Masse – PRISM, Lille, France MARCO GIAMPA` • Department of Clinical and Molecular Medicine, NTNU – Norwegian University of Science and Technology, Trondheim, Norway BRAM GOOSSENS • ProteoFormiX, Beerse, Belgium OLIVER J. HALE • School of Biosciences, University of Birmingham, Edgbaston, Birmingham, UK BRAM HEIJS • Center for Proteomics & Metabolomics, Leiden University Medical Center, Leiden, The Netherlands THERESE S. HØIEM • Department of Circulation and Medical Imaging, NTNU – Norwegian University of Science and Technology, Trondheim, Norway JAMES W. HUGHES • School of Biosciences, University of Birmingham, Edgbaston, Birmingham, UK

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EMRYS JONES • Waters Corporation, Wilmslow, UK SEBASTIAN KROSSA • Department of Circulation and Medical Imaging, NTNU – Norwegian University of Science and Technology, Trondheim, Norway ALEXANDRE KRUSZEWSKI • Universite´ de Lille, Inserm, U1192 - Prote´omique Re´ponse Inflammatoire Spectrome´trie de Masse – PRISM, Lille, France INGELA LANEKOFF • Department of Chemistry – BMC, Uppsala University, Uppsala, Sweden FULVIO MAGNI • Department of Medicine and Surgery, Proteomics and Metabolomics Unit, University of Milano-Bicocca, Monza, Italy LEONIDAS MAVROUDAKIS • Department of Chemistry – BMC, Uppsala University, Uppsala, Sweden ELISE MIDTBUST • Department of Circulation and Medical Imaging, NTNU – Norwegian University of Science and Technology, Trondheim, Norway; Clinic of Surgery, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway JOSHUA MILLAR • Centre for Mass Spectrometry Imaging, Biomolecular Research Centre, Sheffield Hallam University, Sheffield, UK SIVER ANDREAS MOESTUE • Department of Clinical and Molecular Medicine, NTNU – Norwegian University of Science and Technology, Trondheim, Norway; Department of Pharmacy, Nord University, Bodø, Norway KONSTANTIN NAGORNOV • Spectroswiss, Lausanne, Switzerland NINA OGRINC • Universite´ de Lille, Inserm, U1192 - Prote´omique Re´ponse Inflammatoire Spectrome´trie de Masse – PRISM, Lille, France FABIO PAGNI • Department of Medicine and Surgery, Pathology, University of Milan-Bicocca, IRCCS Fondazione San Gerardo dei Tintori, Monza, Italy ISABELLA PIGA • Department of Medicine and Surgery, Proteomics and Metabolomics Unit, University of Milano-Bicocca, Monza, Italy JOSEPH READY • Centre for Mass Spectrometry Imaging, Biomolecular Sciences Research Centre, Sheffield Hallam University, Sheffield, UK STEPHEN RUMBELOW • CRODA Inc (B88), New Castle, DE, USA CRISTINA RUSSO • Centre for Mass Spectrometry Imaging, Biomolecular Sciences Research Centre, Sheffield Hallam University, Sheffield, UK; Department of Natural Sciences, Middlesex University, London, UK MICHEL SALZET • Universite´ de Lille, Inserm, U1192 - Prote´omique Re´ponse Inflammatoire Spectrome´trie de Masse – PRISM, Lille, France RAF SCIOT • ProteoFormiX, Beerse, Belgium; Translational Tissue and Cell Research Unit, Department of Imaging and Pathology, University Hospital, Leuven, Belgium CALLIE SEAMAN • Centre for Mass Spectrometry Imaging, Biomolecular Sciences Research Centre, Sheffield Hallam University, Sheffield, UK EMMA K. SISLEY • School of Biosciences, University of Birmingham, Edgbaston, Birmingham, UK ANDREW SMITH • Department of Medicine and Surgery, Proteomics and Metabolomics Unit, University of Milano-Bicocca, Monza, Italy; Proteomics and Metabolomics Unit, Department of Medicine and Surgery, Vedano al Lambro, Italy JENS SOLTWISCH • Center for Proteomics & Metabolomics, Leiden University Medical Center, Leiden, The Netherlands; Biomedical Mass Spectrometry, Institute of Hygiene, University Hospital Munster, Mu¨nster, Germany CHLOE E. SPENCER • Centre for Mass Spectrometry Imaging, Biomolecular Sciences Research Centre, Sheffield Hallam University, Sheffield, UK

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MAY-BRITT TESSEM • Department of Circulation and Medical Imaging, NTNU – Norwegian University of Science and Technology, Trondheim, Norway; Clinic of Surgery, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway MARK TOWERS • Waters Corporation, Wilmslow, UK MARTHE VERHAERT • ProteoFormiX, Beerse, Belgium; Department of Medical Oncology at Institute Jules Bordet, Brussels, Belgium PETER VERHAERT • ProteoFormiX, Beerse, Belgium KENNETH VERHEGGEN • ProteoFormiX, Beerse, Belgium

Chapter 1 MALDI and Trace Metal Analysis in Age-Related Macular Degeneration Joshua Millar, Susan Campbell, Catherine Duckett, Sarah Doyle, and Laura M. Cole Abstract Age-related macular degeneration (AMD) remains one of the most prevalent causes of blindness throughout the world. Key to prevention of AMD is furthering the understanding of its pathology. In recent years, both the proteins within the innate immune system and essential and non-essential metals have been implicated in the pathology of AMD. Herein, a multidisciplinary and multimodal methodology has been taken to further our understanding of the role of the innate immune proteins and the essential metals within mouse ocular tissue. Key words MALDI-MSI, LA-ICP-MSI, Metals, Copper, Zinc, Innate immune system, SARM1

1

Introduction Mass spectrometry imaging is one of the key multidimensional data acquisition techniques that can provide multiplexing analysis of multiple analytes simultaneously within a wide range of tissues. Multi-omic mass spectrometry imaging can therefore be helpful when tackling complex issues within scientific research. Pathology and the etiology of diseases can be complex and often require decades of research from multiple disciplines. The use of multimodal analysis for such applications can ensure that the tissues being used to research diseases provide multiple scores of multidimensional data that can provide novel information about the subject matter. MALDI-MSI employed in combination with LA-ICPMS offers the monitoring of proteomic and metallomic changes within tissues. Due to the soft ionization involved in MALDI-MSI, tissues remain intact, and so following MALDI-MSI, it is possible to employ LA-ICP-MS on the same section of tissue. Age-related macular degeneration is an ocular degenerative disease prevalent in over 55 s across the globe with over 200 million

Laura M. Cole and Malcolm R. Clench (eds.), Imaging Mass Spectrometry: Methods and Protocols, Methods in Molecular Biology, vol. 2688, https://doi.org/10.1007/978-1-0716-3319-9_1, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2023

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patients worldwide [1]. There are two types of AMD, wet and dry, of which there are limited treatments [2–4]. Wet AMD, for example, cannot be reversed but can be slowed in progression by invasive, periodic intra-ocular injections of antiangiogenics [2]. Dry AMD has no current treatment [2]. Current studies into the pathology of age-related macular degeneration are heavily reliant on immunological studies, and due to a recent dispute over immunological specificity in AMD studies, some assumptions about AMD pathology have been called into question. The multi-omic approach with the combination of MALDI-MSI and LA-ICP-MS is an ideal methodology for tackling the convoluted pathology of ocular disease [5–10]. Detection of analytes in pathobiology can be difficult due to the complexity of biological tissue. With MALDI-MSI, issues come from the unwanted detectable species such as salts and lipids, which may mask peptides in biological tissue, warranting sample preparation for the removal of chemically different species [11]. Ocular tissue is unique in its highly conserved microstructures [12]. Within the retina exist multiple layers that are important to resolve in order to make observations in AMD pathology, meaning the spatial resolution of the instruments used to study ocular tissue via mass spectrometry imaging. This requires optimization of the laser spot size, while maintaining sensitivity, without compromising acquisition speeds. Additionally, the application of enzyme and matrix is essential to the resolution in MALDI-MSI. The application of highly aqueous solutions such as enzyme solvents and high organic solvents used in matrix application can cause the lateral delocalization of the species of interest on the tissue. Furthermore, the way in which the matrix is applied is particularly crucial as it determined the matrix crystal size. While ensuring lateral delocalization is key to ascertaining the spatial distribution of analytes, the matrix crystal size is one of the key factors that predetermines the spatial resolution, with smaller crystal sizes giving optimal results [13]. For LA-ICP-MSI, once the balance between repetition rate, laser fluence, and spot size has been ascertained, image quality can allow the study of multiple tissues by comparison. However, though this qualitative data can be informative, quantitative data can add an extra dimension to the images. However, while quantitative data can provide key information about the wider mechanisms of essential metals within ocular physiology, quantitative LA-ICP is not without its limitations. Reliability of quantitative conclusions drawn from LA-ICP experiments is susceptible to elemental fractionation, a phenomenon that encompasses the effects on the perceived composition of LA-ICP samples caused by factors such as the preferred ablation of more volatile compounds, the timedependent changes in the ion beam, and the transport efficiency of differently sized aerosol particles [14]. Overcoming these issues can

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be fundamental in the success of a quantitative study on biological samples, however, the introduction of imaging, and therefore laser ablation, further factors affecting quantitative analysis are introduced. The main issue stemming from laser ablation is matrix effects. The problem becomes most poignant when using quantitative standards as different matrices will, for example, behave differently when subject to an incident laser beam and will thereby produce aerosols more or less efficiently depending on properties such as thermal conductivity, absorptivity, and reflectivity. This means that when using quantitative standards, the choice of matrix to hold the elemental standards must behave in an analogous manner to the analyte [14, 15].

2 2.1

Materials MALDI Analysis

1. Xtra Adhesive polyline slides. 2. Ethanol (200 proof). 3. Milli-Q-deionized H2O. 4. Ammonium bicarbonate. 5. Octyl-α-β-glucoside (OcGlc). 6. Trypsin (Sequencing Grade). 7. Incubation chamber. 8. CHCA. 9. Aniline. 10. Chloroform. 11. Glacial acetic acid. 12. Trifluoroacetic acid. 13. Sonicator. 14. Millex 0.22 μm syringe-driven filter. 15. HTX M3+ matrix application device (HTX Imaging, Chapel Hill, NC, USA). 16. Flatbed scanner. 17. Phosphorus red. 18. Methanol. 19. High-resolution MALDI-MS: SELECT SERIES MRT (200,000 FWHM), SYNAPT HDMS (40,000 FWHM) (Waters Corporation, Wilmslow, UK).

2.2 LA-ICP-MS Analysis

1. M4 nylon washers. 2. Cyanoacrylate adhesive. 3. ICP Standard Solution mixture(s) (Merck, Darmstadt, Germany).

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4. Gelatin, from porcine skin. 5. NIST 610. 2.3 Software for Data Analysis

1. MassLynx 4.2. 2. HDI 1.6 or SCiLS Lab (Multi-Vendor). 3. Iolite 4. 4. LA-iMageS 1.1.5.

2.4 Reagents: Working Composition

1. Ethanol solutions: Using Milli-Q water to dilute to 70% and 90% (v/v). 2. Wash solution: 90:9:1 ethanol/glacial acetic acid/H2O. 3. Ammonium bicarbonate 50 mM, pH 8.0. 4. Trypsin solution 20 μg mL-1: Add 1 mL of the 50 mM solution to 20 μg of lyophilized trypsin. Add 1 μLof OcGlc to 1 mL of the solution. 5. MALDI matrix solution: Prepare 5 mg mL-1 CHCA in 50% (v/v) and 0.5% (v/v) trifluoroacetic acid with equimolar amounts of aniline (i.e., 1 mL of 5 mg mL-1 CHCA requires 2.4 μL of aniline). 6. Digestion chamber solution 50% MEOH (v/v). 7. Phosphorus solution, 5 mg mL-1 in MeOH. 8. ICP Solution 6 in 1% HNO3. 9. Standard solutions, prepared at 25, 12.5, 6.25, 3.125, and 1.56 ppm in 50:50 ICP Solution 6 in 1% HNO3 and 20% gelatin.

3 3.1

Methods Slide Preparation

1. Place the excised mouse ocular tissue in a suitably sized mold and fill with 1% v/v carboxymethylcellulose and snap freeze (See Note 1). 2. Section at a thickness of 10 μm using a cryostat microtome. 3. To remove salts and lipids, each immerse in the following solutions for 1 min: 70% ethanol, 90% ethanol, CHCl3, and 90:9:1 ethanol/glacial acetic acid/H2O (See Note 2). 4. Allow the sample to dry in ambient conditions.

3.2 Enzyme Application

In order to analyze the proteome of tissue samples using the bottom-up approach, peptides must be created through enzymatic cleavage. When imaging these proteins, it is essential that when cleaved, they remain in situ without lateral displacement, meaning the enzyme must be applied to the tissue in small droplets, so no

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delocalization can take place. The HTX M3+ and other commercially available robot sprayers allow the application of enzyme in micro-droplets at a variable temperature. For trypsin, applying in sequential layers can benefit the lateral resolution of the final image. Additionally, as the HTX M3+ allows variable application temperatures, benefit can be gained by applying the trypsin at temperatures higher than 37 °C in order to activate the enzyme as soon as it touches the tissue while simultaneously allowing for the droplets to dry before the next layer is applied, preventing over-wetting. 1. To activate the enzyme, apply the trypsin at 45 °C. To ensure no delocalization occurs, a lower flow rate of 25 μL min-1, a sheath gas (N2) pressure of 10 psi, a drying time of 5 s, and a velocity of 1200 mm min-1 should be employed. To ensure proper coverage, 15 passes and an overspray of 2 mm should be used for enzyme application. 2. Immediately following the enzyme application, place the tissue in a humidity chamber and incubate (see Fig. 1) at 37 °C overnight within an incubator (16 h). 3.3 Matrix Application

Matrix application is akin to the application of trypsin as one of the key components to determining spatial resolution of the final mass spectrometry image. Like with trypsin, this step is key when avoiding over-wetting and delocalization; however, the matrix crystal size in MALDI-MSI is directly proportional to the spatial resolution achieved. The crystal size is dependent on the droplet size, which in turn is related to the solvent. High organic solvents can aid with crystal and droplet size and additionally can allow for better extraction of bound peptides and proteins within the tissue. Water content within the matrix is, however, essential for proper co-crystallization and extraction of analytes from the sample, so addition of water can aid extraction while also providing protection from organic solvent-induced lateral displacement. The use of a 50% H2O solution, in addition to utilizing a high heat on the HTX

Fig. 1 A Coplin jar filled with 50% MeOH (v/v) with tissue on the lid to prevent condensation and sealed with Parafilm

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M3+ with N2 gas pressure, allows for sufficient extraction and maintained spatial resolution: 1. Following digestion, remove the tissue and allow it to reach ambient temperature, before placing it back in the M3+ sprayer. 2. Prior to aspirating the matrix, take approximately 1.5 mL (See Note 3) of the 5 mg mL-1 CHCA solution and sonicate it at room temperature for 5 min. Following sonication, aspirate with a 2 mL syringe and pass it through a 0.22 μm syringe filter. 3. Application of the matrix is key to sensitivity and spatial resolution, so when using the HTX M3+, ensure no delocalization occurs by setting a high temperature of 80 °C. Due to the volatility of the matrix solution and temperature, a higher flow rate of 100 μL min-1 can be used. With sheath gas (N2) pressure at 10 psi and a velocity of 1200 mm min-1, apply eight layers of matrix to the tissue. 3.4

Sample Storage

Once matrix is applied, the samples can be stored: 1. Place the samples within a slide mailer and vacuum seal. 2. Place the sealed sample in -80 °C storage for up to 4 weeks.

3.5 MALDI Data Acquisition

1. Insert the slide into the slide holder, and load it into a flatbed scanner. 2. Take a scan of the target plate using a scanner with the tissue attached for upload to Quartz software later in the acquisition process. 3. Spot phosphorus red calibrant in the five wells in the center of the MALDI target. Once dry, place into the instrument and load the target plate. 4. Calibrate the instrument within the appropriate mass range for peptide analysis (0–2400 Da). 5. Using Quartz, input acquisition parameters such as MRT Mode acquisition, laser focus (6.00 mm), and laser attenuation (ND Filter Position, 300; ND 1 Filter, Engaged). Additionally, set a Quad profile suitable for the mass range of interest. 6. Upload the image as a MALDI plate and follow the co-registration prompts. Once calibrated, draw a region of interest within your sample target plate. 7. Set up a continuous lock mass correction by picking a known peak within the sample within the MS method. 8. Optionally, enter analyte m/z values of interest for the live imaging feed. 9. Set the image to run in MassLynx. 10. Following analysis, process the most intense 1500 peaks in HDI and with the desired mass accuracy (See Note 4).

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Matrix Washing

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1. Remove matrix prior to LA-ICP analysis by immersing the tissue in 70% EtOH (2 × 1 min) (See Note 5). 2. Subsequently place the tissue within a vacuum desiccator and allow to dry overnight or for a minimum of 2 h (See Note 6).

3.7 Calibration Arrays

Calibration arrays must be representative of analyte as different matrices will behave differently when subject to an incident laser beam and will thereby produce aerosols more or less efficiently depending on properties such as thermal conductivity, absorptivity, and reflectivity. Therefore, calibration arrays must be made from matrices that are representative of the sample (see Fig. 2). To ensure homogeneity of the calibration array, lower aqueous solution must be used to reduce the Marangoni effect (see Fig. 3) meaning that the preparation of hydrocolloidal gels must take place at high temperatures. To avoid coagulation of the gels prior to mixing with calibration standards, prepare the gel standards at 45–60 °C and vortex thoroughly. 1. Prepare 50 mL of 20% (w/v) gelatin by weighing out 10 g of gelatin and lay the Falcon tube on its side on an acute angle. Dissolve the gelatin by using a wash bottle to soak and dissolve the gelatin by making the solution up to 50 mL. 2. Incubate the gelatin at 45–60 °C. 3. Prepare a serial dilution of ICP Standard(s) (See Note 7) at a concentration double to that of the end desired concentration, with a volume of 1.5 mL, using 1% HNO3 as a diluent. 4. Once the gelatin is at temperature, gently mix and pipette 1.5 mL of the gelatin into the ICP standards. Keeping the mixture warm so the gelatin doesn’t solidify, vortex the standards. 5. To each standard, add 115In as an internal standard at 1 ppm or within the mid-range of the calibration range.

Fig. 2 Standard preparation options: (a) gelatin mounted on a microscope slide. (b) Gelatin standard mounted in epoxy for use in the reference well in the ESL samples

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Fig. 3 LA-ICP-MS images exhibiting 66Zn distribution in hydrocolloidal gels made from (a) 2.5% gelatin, (b) 5% gelatin, and (c) 10% gelatin

6. Freeze the standards at -20 °C until needed. 7. Prepare wells for the standards by securing 4 mm ID nylon washers to a glass microscope slide with adhesive. 8. Upon thawing the samples, heat until 45 °C and pipette 15 μL into the nylon well. 9. Desiccate overnight to ensure all liquid is removed. 10. Using the same parameters as used to acquire the MS image, a line scan of the standards including a blank before and after the image acquisition. 3.8

Data Analysis

Data analysis for MALDI-MSI data acquisition and processing was conducted using MassLynx version 4.2 and SCiLS Lab MVS version 2022b Pro (Bruker GmbH, Bremen, Germany). Data from ICP-MS acquisitions were analyzed using LA-iMageS version 1.1.5 [16] and Iolite version 4.4.6 (Elemental Scientific Lasers, Inc., Bozeman, MT, USA).

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3.9

ICP-MS

3.10

Quantitative ICP

3.11

Laser Ablation

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Dwell times are key to success when monitoring multiple elements simultaneously by ICP-MS. Less abundant elements will require more dwell times, and more sensitive will require less dwell time. The minimum amount of dwell time should be used as this will affect overall imaging time. For quantitative analyses, the use of calibration arrays must be employed both before and after the acquisition of each run and/or sample for optimal results. Utilizing the internal standards and the values of the reference materials, a data reduction scheme can be utilized to account for artifacts of the experiment such as instrumental drift or change in the plasma properties. 1. NIST 610 should be used to ensure consistent mass accuracy and atomization. 2. Following a tune, the laser power should then be optimized for use on biological tissues. 3. Maximum aerosol formation should be achieved where all of the tissue is ablated; however, no glass has been ablated. This can be monitored using the live optical image or by monitoring silicon in the ICP-MS. A sample fluence of 4 J cm-2 should provide consistent ablation without ablation of the glass. 4. In order to ensure over- or under-sampling is not achieved, scan rate should be optimized using the following equation: Scan rate ðμm=sÞ =

Spot sizeðμmÞ Acquisition time ðsÞ:

LA parameters Laser spot size

40 μm

Laser power

46%

Repetition rate

20 Hz

Scan spacing

40 μm

Laser warm-up time

10 s

Cell washout time

40 s

ICP-MS acquisition time (AT)

0.359 s

5. Spot size should be determined by the nature of the sample and the required spatial resolution. Smaller spot sizes will also result in reduced sensitivity, so increasing the repetition rate to appropriately compensate from the lack of sensitivity is recommended.

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6. Dwell times should also be ascertained on a sample-by-sample basis, allocating up to 50 ms at eight sweeps for the least abundant samples and using 1 ms or less for those elements that are less than abundant in the samples of choice.

4

Results The image in Fig. 4 shows an overlay of four ion images within mouse ocular tissue and the observation of SARM1 (m/z 1606.84), a TLR adaptor protein within mouse ocular tissue.

Fig. 4 An overlay image of four ions within mouse ocular tissue, acquired by MALDI-MS on a SELECT SERIES MRT at 25 μm with leptin m/z 1729.10 (red), lens crystallin m/z 1255.55 (orange), SARM1 m/z 1606.84 (green), and histone H32 m/z 1032.60 (purple)

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Fig. 5 Quantitative LA-ICP-MS images acquired with a 10 μm pixel size using an ESL ImageBio266 coupled to a NexION 350X. (a) 66Zn distribution within mouse ocular tissue. (b) 63Cu distribution within mouse ocular tissue

Further ions of interest include leptin (m/z 1729.10), lens crystallin (m/z 1255.55), SARM1 (m/z 1606.84), and histone H32 (m/z 1032.60). The image shows how, even at relatively large pixel sizes of 25 μm, the MALI image can still segment and differentiate at least two layers within the retina. From the image, it can be inferred that SARM1 is present in the posterior region of the ocular tissue, indicating a higher prevalence within the outer segment, outer nuclear area, and chorio-retinal region, as opposed to histone H32, which localizes more specifically to the inner nuclear layer and inner plexiform layer. Additionally, Fig. 5 shows how LA-ICP-MS of ocular tissue previously ablated by MALDI-MSI can still give adequate sensitivity, showing the distribution of both 66Zn and 63Cu within mouse ocular tissue. The images show the distribution of both 66Zn and 63 Cu within ocular tissue. Copper was seen to be localizing to the choroid, iris, and ciliary body within the ocular tissue, whereas zinc was seen to localize to the choroid, iris, retina, and cornea. Additionally, by utilizing the calibration arrays prepared in Sect. 3.7, the image can be seen to be expressed on a ppm scale, allowing the direct comparison of the two images. The images show that 66Zn was in higher quantities in the choroid, retina, lens, and cornea when compared to 63Cu.

5 Conclusions MALDI imaging at high spatial resolution still presents challenges within research labs that possess even the most advanced instrumentation. Robotic sprayers for use in enzyme and matrix application present a sophisticated solution for the analysis of minutia of highly structured anatomy such as those found in the retina.

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Combined with high-throughput, high mass resolution, and high spatial resolution mass spectrometers, they can produce images to a satisfactory quality, with confidence in the localization and identity of mass analytes. When used in tandem with MALDI-MSI, LA-ICP-MS can provide both qualitative and quantitative data from tissue sections, offering a modern workflow, which not only utilizes tissue with efficiency but provides multidimensional datasets that can be used universally for disease pathology. Additionally, the preparation of universally applicable calibration arrays for LA-ICP-MS is long disputed, and the above method describes how to achieve such a workflow in a way that can be applied to multiple instrument and analyte combinations.

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Notes 1. If the tissue sections are not required immediately, at this point, store them at -80 °C in an airtight container. 2. This step should take place within a fume hood, using appropriate PPE. Ethanol solutions may be prepared in Falcon tubes; however, CHCl3 and the final wash solution should be prepared in glass staining jars. In between washes, particularly when moving to and from CHCl3 and at the end of the wash steps, ensure that the slide has dried. A light stream of N2 may be used to aid this step. 3. Sonication and filtering help to mitigate blockages that can potentially occur when matrix falls out of solution within the HTX sprayer. Add 250–500 μL more than required for the tissue slide (indicated on the HTX software) to allow for loss within the syringe filter. 4. Processing the image can be done automatically using Waters Auto-Process function. To take advantage of this, use the “Processing” tab at the beginning of the acquisition in HDI and by ticking the “auto-process” box within the batch run list. 5. This step may be considered optional prior to LA-ICP analysis; however, removing matrix aids with 13C internal standardization and allows for optical images to be taken in the interim period. 6. This step is not optional regardless if matrix washing has taken place. 7. ICP Standards are available as single element standards or as standard mixtures. The standards are often prepared in 5% HNO3 solutions, which may cause coagulation of the gelatin when present in higher concentrations.

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References 1. Wong WL, Su X, Li X, Cheung CM, Klein R, Cheng CY, Wong TY (2014) Global prevalence of age-related macular degeneration and disease burden projection for 2020 and 2040: a systematic review and meta-analysis. The Lancet. Global health, 2(2), e106–e116. https:// doi.org/10.1016/S2214-109X(13)70145-1 2. Papadopoulos Z (2020) Recent developments in the treatment of wet age-related macular degeneration. Curr Med Sci 40:851–857. https://doi.org/10.1007/s11596-0202253-6 3. Rayess N, Houston SKS, Gupta OP, Ho AC, Regillo CD (2015) Treatment outcomes after 3 years in neovascular age-related macular degeneration using a treat-and-extend regimen. Am J Ophthalmol 159:3–8.e1. https:// doi.org/10.1016/j.ajo.2014.09.011 4. Danis RP, Lavine JA, Domalpally A (2015) Geographic atrophy in patients with advanced dry age-related macular degeneration: current challenges and future prospects. Clinical Ophthalmology (Auckland, N.Z.) 9:2159–2174. https://doi.org/10.2147/OPTH.S92359 5. Doyle S, Mulfaul K, Fernando N, Chirco K, Connolly E, Ryan T, Ozaki E, Brennan K, Maminishkis A, Salomon R (2018) Invest Ophthalmol Vis Sci 59:3475 6. Ozaki E, Gibbons L, Neto NG, Kenna P, Carty M, Humphries M, Humphries P, Campbell M, Monaghan M, Bowie A, Doyle SL (2020) SARM1 deficiency promotes rod and cone photoreceptor cell survival in a model of retinal degeneration. Life Science Alliance 3:e201900618. https://doi.org/10. 26508/lsa.201900618 7. Mulfaul K, Ozaki E, Fernando N, Brennan K, Chirco KR, Connolly E, Greene C, Maminishkis A, Salomon RG, Linetsky M, Natoli R, Mullins RF, Campbell M, Doyle SL (2020) Toll-like receptor 2 facilitates oxidative damage induced retinal degeneration. Cell Reports (Cambridge) 30:2209–2224.e5. https://doi.org/10.1016/j.celrep.2020. 01.064

8. Sarah LD, Campbell M, Ozaki E, Robert GS, Mori A, Paul FK, Gwyneth JF, Kiang A-s, Marian MH, Ed CL, Luke AJO, Joe GH, Humphries P (2012) Nat Med 18:791–798. https:// doi.org/10.1038/nm.2717 9. Tarallo V, Hirano Y, Gelfand B, Dridi S, Kerur N, Kim Y, Cho W, Kaneko H, Fowler B, Bogdanovich S, Albuquerque RC, Hauswirth W, Chiodo V, Kugel J, Goodrich J, Ponicsan S, Chaudhuri G, Murphy M, Dunaief J, Ambati B, Ambati J, Ogura Y, ˜ez G, Yoo J, Lee D, Provost P, Hinton D, Nu´n Baffi J, Kleinman M (2012) Cell 149:847–859. https://doi.org/10.1016/j.cell.2012.03.036 10. Kosmidou C, Efstathiou NE, Hoang MV, Notomi S, Konstantinou EK, Hirano M, Takahashi K, Maidana DE, Tsoka P, Young L, Gragoudas ES, Olsen TW, Morizane Y, Miller JW, Vavvas DG (2018) Issues with the Specificity of Immunological Reagents for NLRP3: Implications for Age-related Macular Degeneration. Sci Rep 8:461–412. https://doi.org/10. 1038/s41598-017-17634-1 11. Seeley EH, Oppenheimer SR, Mi D, Chaurand P, Caprioli RM (2008) J Am Soc Mass Spectrom 19:1069–1077. https://doi. org/10.1016/j.jasms.2008.03.016 12. Rashid K, Akhtar-Schaefer I, Langmann T (2019) Front Immunol 10:1975. https://doi. org/10.3389/fimmu.2019.01975 13. Norris JL, Caprioli RM (2013) Chem Rev 113: 2309–2342. https://doi.org/10.1021/ cr3004295 14. Limbeck A, Galler P, Bonta M, Bauer G, Nischkauer W, Vanhaecke F (2015) Anal Bioanal Chem 407:6593–6617. https://doi.org/ 10.1007/s00216-015-8858-0 15. Sˇala M, Sˇelih VS, van Elteren JT (2017) Analyst (London) 142:3356–3359. https://doi.org/ 10.1039/C7AN01361B 16. Lo´pez-Ferna´ndez H, de Pessoˆa GS, Arruda MAZ, Capelo-Martı´nez JL, Fdez-Riverola F, ˜ a D, Reboiro-Jato M (2016) J CheGlez-Pen minform 8:65. https://doi.org/10.1186/ s13321-016-0178-7

Chapter 2 HistoSnap: A Novel Software Tool to Extract m/z-Specific Images from Large MSHC Datasets Kenneth Verheggen, Nivedita Bhattacharya, Marthe Verhaert, Bram Goossens, Raf Sciot, and Peter Verhaert Abstract We describe an informatics tool for comfortable browsing through highly complex, multi-gigabyte mass spectrometry histochemistry (MSHC) datasets, via clever ion-specific image extraction. The package is developed particularly for the untargeted localization/discovery of biomolecules such as endogenous (neuro)secretory peptides on histological sections of biobanked formaldehyde-fixed paraffinembedded (FFPE) samples straight from tissue banks. Atmospheric pressure-MALDI-Orbitrap MSHC data of sections through human pituitary adenomas in which two well-known human neuropeptides are detected are used as an example to demonstrate the key features of the novel software, named HistoSnap. Key words Mass spectrometry histochemistry, MSHC, HistoSnap, (neuro)secretory peptides, Molecule-specific images

1

Introduction Histochemistry comprises a collection of (physico)chemical protocols to generate microscopic images of histological sections of biological tissues. Typically aimed at characterizing tissues in general, histochemistry is also employed to selectively localize, with varying specificity, a wide variety of (bio)molecules, including proteins, peptides, metabolites, carbohydrates, lipids, etc. Depending on the (class of) biomolecules to be imaged, different sample preparation procedures are required in combination with specific histochemical staining techniques. These yield images in which analytes of interest are detected in situ in their tissue context. A well-known example is immunohistochemistry in which specific molecules are localized with (sub)cellular resolution by virtue of their immunoreactivity to antibodies.

Laura M. Cole and Malcolm R. Clench (eds.), Imaging Mass Spectrometry: Methods and Protocols, Methods in Molecular Biology, vol. 2688, https://doi.org/10.1007/978-1-0716-3319-9_2, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2023

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In our lab, we have a longtime interest in peptidomics [1–4], the subdiscipline of proteomics focusing on regulatory secretory peptides, a class of biomolecules with important bioactivities, which reside at the interface between proteomics and metabolomics [5, 6]. Due to the low abundance and relatively poor ionizability of endogenous peptides compared to, for example, (phospho)lipids and the countless (tryptic) peptides generated in respectively largescale lipidomics and mainstream (bottom-up) proteomics experiments, these physiologically vital biomolecules are often overlooked. To specifically localize this intriguing but elusive class of biologically significant signaling molecules, we have been exploring the performance of diverse MSI setups. Because of the great potential of atmospheric pressure (AP)MALDI-Orbitrap for peptide MSI (more specifically MSHC; see below), in particular for the pathological (as well as clinical) laboratory, we focus on formaldehyde-fixed, paraffin-embedded (FFPE) material. FFPE is the standard preservation procedure for tissue samples in clinical settings, for its very efficient and costeffective long-term storage at ambient temperature. Compared to the alternative ultra-low temperature storage of (unfixed) tissues which necessitates expensive freezer installations, FFPE sample safeguarding requires minimal storage space and virtually no maintenance (energy) or no expensive backup generators or other permanent failsafe mechanisms. Furthermore, due to the crosslinking of biomolecules by formaldehyde fixation [7], FFPE samples are both biochemically and physically stable, which makes them the preferred type of sample for histo(patho)logy analysis through microscopy [8]. As a result, the amount of FFPE blocks stored in tissue banks and pathology departments far exceeds that of frozen samples. Routine FFPE sample processing protocols for wax (paraffin) embedding typically involve a dehydration sequence through ethanol baths as well as clearing steps (usually in xylene). These inevitably result in the washout of various (classes of) biomolecules, which obviously precludes their subsequent detectability by MS analyses. Hence FFPE material has been found poorly suitable for lipidomics, since most lipids are removed from a sample by the dehydration and clearing steps. We recently described a variation of the MSI sample preparation, which, unlike what was claimed before, i.e., that FFPE sample prep precludes the detection of endogenous peptides from FFPE material older than 1 year [9, 10], allows for the detection (and thus discovery) of non-tryptic endogenous peptides in FFPE tissues that were stored for decades. Because of its prime relevance for use in histology applications, we designated this MSI variant mass spectrometry histochemistry (MSHC) [11]. MSHC has the potential to uncover the spatial distribution of endogenous peptides as well as other (small) biomolecules in

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sections of biological tissue, by accurately measuring their molecular masses [12, 13]. The ability to reveal molecular information in its biological (tissue) context makes MSHC inherently very powerful to contribute to tissue-based diagnostics, holding great potential for biomarker discovery, especially when combined with other (classic) histochemistry imaging modalities. With a lateral resolution typically better than 20 μm, a scanning MALDI source allows for a 2D grid overlay on top of the tissue section, where MS data are collected at every pixel. Modern AP-MALDI sources have a sample stage and laser focusing precision down to 5 μm. MS images can finally be generated for any specific mass-to-charge (m/z) value acquired. This is done by rasterizing the data relative to the in situ x- and y-coordinates, converting the measured ion intensity into a pixel with predefined colors [14]. Directly proportional to the spatial resolution, AP-MALDIOrbitrap MSHC data acquisition of a FFPE sample easily takes multiple hours, yielding multiple gigabytes worth of highresolution (HR) mass spectra, in which the signals of matrix cluster ions and chemical background noise not seldom overwhelm those of the low abundant endogenous peptides or other small biomolecules. Consequently, extensive data filtering is critical to generate relevant biomolecule-specific images. In several respects, the generation of images of endogenous peptide distributions in FFPE tissue sections from raw MSHC data is comparable to the big data handling required to create astrophotography pictures of galaxies and star systems after multiple hours of nightly camera exposure (Fig. 1).

Fig. 1 (a) Astrophotography of Messier 101, also known as Pinwheel Galaxy, a star system at 21-million lightyear distance from earth (photographed by B. Goossens with ATM 25 cm telescope mounted on EQ8 Skywatcher stand). (b) AP-MALDI-Orbitrap MSHC image showing the overlaid distribution of two neuropeptide ion signals (false colored magenta and turquoise) in archived human FFPE tumor tissue

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Fig. 2 HistoSnap’s intuitive user interface built in Java. Preview images are generated and can be stored as individual frames, as collages of frames, or as animation (GIF). HistoSnap icon is shown on top of screenshot

To this end, we here introduce HistoSnap (Fig. 2), a simple graphical user interface that is developed to aid in the unwrapping of complex MALDI-MSHC datasets and that allows the extraction, annotation, and export of specific images out of the “big data,” in particular of low abundant, poorly ionizable analytes with histologically and biologically relevant tissue distributions.

2

Materials and Methods

2.1

Samples

To demonstrate the key features of HistoSnap, MSHC data were selected of sections through several-year-old Homo sapiens pituitary adenomas archived at the FFPE tissue bank from the Leuven University Hospital Pathology Department. Specific cases were chosen, in which during surgery, a small part of neurohypophysis tissue had been resected along with the malignant tissue. The main reason for this is that the posterior pituitary or neurohypophysis is known to store Arg-vasopressin and oxytocin, two neurosecretory nonapeptides synthesized in different hypothalamic nuclei, which serve as model analytes in this paper.

2.2

Data Acquisition

MALDI-Orbitrap MSHC data were acquired using an LTQ Orbitrap Velos HRMS system (Thermo Fisher Scientific) interfaced with an atmospheric pressure-MALDI source (AP-MALDI UHR, Mass Tech). The resulting *.raw and corresponding *.xml files were converted to the generic imzML format using MSConvert (v. 3.0, ProteoWizard) and MT imzML Converter (ng) (v. 1.2.0, Mass Tech and ProteoWizard). The resulting *.imzml and *.ibd files were used as input for this work.

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HistoSnap is implemented in Java, using an external python library for imzML parsing. Consequently, HistoSnap is dependent on Python 3, pip, and pyimzML (https://github.com/ alexandrovteam/pyimzML), and these dependencies should therefore be available to any system running HistoSnap (laptop or highend computer). Upon loading an imzML file, spectral data are parsed and binned to m/z values with a specific tolerance and optionally limited above an arbitrary intensity threshold. These tolerances and intensity thresholds can be applied through the interface. The set values are then piped into the tool for further processing. No peak-picking or additional filters are applied at this stage, and the signal is only composed of the combined measured intensities, above a threshold, within a bin. The assumption here is that signal noise is uniformly distributed across the measured grid. Dividing the calculated signal by the pooled average signal thus produces a relative measure for the signal strength within a certain m/z range, which in turn can be translated using a color scale. Importing and (post)processing of the spectra is a very resource-intensive operation and can quickly outgrow the capacities of standard hardware. To address this issue, HistoSnap can work in two different operating modes: a memory-based one and the other hard disk-based. The former is the fastest but, evidently, quite memory intensive. The latter mode eliminates the need for extensive amounts of memory and, therefore, can run on a common laptop computer. This operating mode creates a reusable SQLite database (file based) to temporarily store spectra and, consequently, runs significantly slower. To avoid the need for repeated extractions of the same files/ masses, we implemented in HistoSnap the option to persist states. This entails storing the information needed to ensure that interrupted tasks can be resumed at a restart. This means that launched tasks can be reverted or restored, including cases where the program was exited prior to their completion. After importing the spectra, selectable parameters (total ion current (TIC), mean, median, min or max intensity, etc.) are calculated for each individual pixel location and are simultaneously pooled. By dividing the individual parameter with the mean value of the pool and clamping this value between 0 and 1, each data point is converted to a red, green, and blue (RGB) value using a predefined color scale. As the pixel coordinates are known for each resulting value, images are reconstructed per requested m/z bin, further referred to as “frames.” Frames can be collated in a single image or as a grid of frames, to which a cross-frame annotation/ outlining can be applied, which greatly facilitates a quick interpretation of predefined masses (and related isotopes).

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Fig. 3 HistoSnap workflow: (a) *.imzML file is loaded into HistoSnap and contents are parsed, retaining only measured intensities and values in specified m/z range (b). Selected intensity parameters (total ion current, mean, median, max, etc.) are calculated for each spectrum’s m/z bin (c). These values are also pooled (d). By dividing each individual value by means of pooled values (C/D) and applying this normalized result to color scale, RGB values are produced (e). In combination with pixel coordinates of considered spectrum/spectra (f), single frame or animated GIF are reconstructed for selected m/z bins (g). Note that in so called low memory mode (a) is replaced by (SQLite) database connection

Exporting of frames can be as single image files or as a collection of files in the Portable Network Graphics (PNG) format. In addition to browsing through static m/z images, we find that combining individual m/z images into an animation provides an elegant way to quickly overview a sample (Fig. 3). Therefore, an export feature to combine a selection of frames into a Graphics Interchange Format (GIF) file animation has been implemented as well.

3

HistoSnap Operation Sequence 1. The software is opened by double-clicking the HistoSnap icon (see Fig. 2). 2. An *.imzml file is loaded via the File menu item or by pressing the plus-shaped icon in the toolbar on the left of the screen. The corresponding *.ibd file, bearing the same name, needs to be present in the same directory. 3. Images are extracted by using the Extract menu item or by clicking the unboxing icon in the toolbar. HistoSnap can generate a so-called “background” image, either from randomly sampled m/z values or from known MALDI matrix cluster ion m/z values (e.g., DHB clusters [15], well-known artifacts from the sample processing). In MSHC analyses, which typically work on unstained tissue sections, it often is challenging to discern the tissue contours due to the uniform coating of the sample with matrix crystals. A HistoSnap-generated

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Fig. 4 To inspect spatial properties of samples, background (a) can be visualized based on either known matrix molecules (illustrated here) or by random sampling of datasets. Regions of interest annotations (white outline) (b) can be set that will carry over to any subsequently extracted image(s) as overlay (c), to aid with visual interpretation of spatial distribution of compounds, for example by comparing with H&E stained adjacent section (d)

“background” image is an elegant means to visualize the general contours of a tissue section, which we find particularly useful when comparing MSHC data to established histological staining methods such as hematoxylin and eosin (H & E) staining [16], usually carried out on an adjacent section (Fig. 4). 4. Using the annotation icons in the left toolbar, various shapes (rectangle, circle, or free-form polygons) can be selected to outline the contours of a selected surface area in a sample (Fig. 4). This facilitates a quick interpretation of signal localization and, by extension, the histological location of detected ions (m/z values). 5. Next, a range of images can be extracted for targeted masses. Analogous to the background extraction, the Extract menu works with a single, known value, a range surrounding a known value, or a list of known values. For example, generating a sequence of frames with a bin size of 0.2 for oxytocin [M+H]+ (at m/z 1007.4) and its sodium adduct [M+Na]+ at m/z 1029.4 and for vasopressin ([M+H]+ at m/z 1084.4) renders a grid of easily comparable images (Fig. 5). Executing the image extraction using randomly selected intervals in the same mass range verifies that the peptide ion images filtered by HistoSnap do not just represent arbitrary signals.

4 Discussion HistoSnap is developed to be an intuitive software for the extraction and annotation of images from MALDI-MSHC data. The tool includes a feature to extract a background image from a dataset, which can be accomplished either by sampling randomly or by using a list of MALDI matrix cluster ion m/z values. We find

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Fig. 5 Tissue annotation by HistoSnap filters clear signals at m/z 1007.4 (oxytocin [M+H]+) [A], 1029.4 (oxytocin [M+Na]+) [B], and 1084.4 (vasopressin [M+H]+) [C]. Note that for all peptide ions, A + 1 and A + 2 isotopologues are observed as well

such background images helpful to reveal the boundaries of the biological tissue on the matrix coated microscope glass slide. In the example case shown, we demonstrate HistoSnap’s background image generation based on DHB cluster ions (Fig. 4), as well as biomolecular signal data on a shortlist of mass-to-charge ratios of

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1007.4, 1029.4, and 1084.4 (representing protonated oxytocin, its sodium adduct, and protonated vasopressin). In a previous study, we have unequivocally proven that the FFPE sample used here contains these known neuropeptides, using accurate MS on a 7 T MALDI FTICR, as well as tandem MS and ion mobility MS on a focused LESA extracted sample from a MSHC-positive area [16]. We find it noteworthy that the HistoSnap images of protonated and sodiated ion species of both neurosecretory nonapeptides demonstrate that isotopic envelopes of endogenous peptides can readily be observed, with virtually no signal in between the respective isotopologue m/z values. This illustrates how, despite its simplicity and lack of statistical power, HistoSnap can visualize highly detailed spatial biomolecular information. Expanding on the above features, HistoSnap can be employed to aid molecular biomarker MSHC discovery studies, by rapidly filtering biomolecular information based on their histological (spatial) distribution. It should be clear that a full exploitation of the spatial dimension of the data and their integration with all available histopathology and clinical data is extremely useful to allow proper interpretation of MSHC data. HistoSnap, therefore, complements the filtering of MSHC data based on mass spectral features, such as Kendrick mass defect and presence/absence of isotopic envelopes [17]. With increasingly accurate measurements and better resolutions in line with ongoing developments of analytical (MS) instrumentation, it will be possible to predict the presence of relevant biomolecules such as secretory peptides based on their physical metadata (i.e., spatial tissue distribution) which HistoSnap helps to quickly reveal. Ironically, the unprecedented availability of all (meta)data and annotations hampers the straightforward inspection of specific (or predefined range of) m/z value(s) due to larger parsing times and an overall higher data complexity. This is of particular importance when quickly browsing over data or scanning for the presence of signal at known m/z values. HistoSnap reflects a different approach to MSI data assessment than commercial software like SCiLS Lab (Bruker), ImageQuest (Thermo Fisher), Multimaging (ImaBiotech), Lipostar (Molecular Discovery), MSiReader, or Mozaic (Spectroswiss). These packages are largely governed by MS features for the selection of “interesting” peaks from MSI datasets. In MSHC, which we routinely use in discovery mode, MS-specific peak features of very low abundant molecules are not seldom overwhelmed or masked by interfering background signals.

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By future inclusion of algorithms detecting relevant mass defects and isotope patterns, and automatically rendering m/z values of interest as images, we intend to make HistoSnap a robust basic discovery tool, a platform for automated browsing through large MALDI-MSHC datasets for downstream biomarker discovery. Presently, HistoSnap is designed to be a prospecting tool prior to downstream in-depth analysis using other MSI software packages. HistoSnap’s main intention is to allow for a rapid visual scan of a tissue section and the location of (bio)molecular ions prior to confident identification of the biomolecules visualized by orthogonal methods. HistoSnap primarily evaluates MSHC data based on their spatial dimension, after which the MS dimension of selected peaks can be further analyzed and processed via the established MSI packages mentioned above. Finally, we want to underline that a major advantage of AP-MALDI MSHC is that it works with FFPE tissue sections mounted on regular (not conductive) microscope glass slides. These are exactly the samples which are routinely produced in the histology lab. In combination with the fact that MSHC sample processing is relatively simple, basically being limited to paraffin removal followed directly by MALDI matrix coating [11, 18], this opens broad perspectives for the general introduction of MSHC in the clinical/pathology laboratory.

5

Notes 1. HistoSnap is a graphical user interface designed to rapidly extract an image from complex, large mass spectrometrybased imaging experiment, such as endogenous peptide MSHC. Its main goal is to prospect data, providing a fast yet robust filter that allows users to identify ions of interest based on the histological distribution of high-resolution m/z signals. 2. Handling large files usually comes with long loading times, which can be quite annoying when the goal is to revise a previously generated image. This may be particularly cumbersome in “low memory” mode. To avoid this, HistoSnap allows the user to save and load sessions, eliminating the need to re-extract from scratch. 3. Not seldom, an animation can give a clearer impression on a sample than static images. We personally prefer HistoSnap’s feature to create a GIF sequence of selected images, which is achieved by simply clicking the camera icon in the toolbar to generate such file from the selected frames. 4. The latest release of HistoSnap and the recommended tutorial files will be made downloadable through the ProteoFormiX

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website (www.proteoformix.com) where also license details will be available. 5. The datasets used to demonstrate HistoSnap features in this chapter are available at https://drive.google.com/file/d/1b3 eXc2hJNzeLYxN6nw9NBC4GEzkj1ryN/view?usp=sharing.

Acknowledgments The authors gratefully acknowledge support to ProteoFormiX by Flanders Innovation and Entrepreneurship [VLAIO research project HBC.2019.2796], as well as from imec.istart and BlueHealth Innovation Center. We thank Werner Vandevelde for designing the HistoSnap icon. References 1. Baggerman G, Husson S, Wegener C, Verhaert P (2014) Peptidomics state-of-the-art. EUPA Open Proteomics 3:76–77. https://doi.org/ 10.1016/j.euprot.2014.02.011 2. Verhaert PDEM (2018) The bright future of peptidomics. Methods Mol Biol 1719:407– 416 3. Shaw C, Verhaert PDEM (2007) Peptidomics and Biology: Two Scientific Disciplines Driving Each Other. In: “Peptidomics Methods and Applications” (Soloviev M, Andren P, Shaw C, Eds) pp 387–396. https://doi.org/ 10.1002/9780470196502.CH17 4. Verhaert PDEM, Pinkse MWH, PrietoConaway MC, Kellmann M (2007) A short history of insect (neuro)peptidomics—a personal story of the birth and youth of an excellent model for studying peptidome biology. In: “Peptidomics Methods and Applications” (Soloviev M, Andren P, Shaw C, Eds) pp 2 5 – 5 4 . h t t p s : // d o i . o r g / 1 0 . 1 0 0 2 / 9780470196502.CH2 5. Verhaert P, Uttenweiler-Joseph S, de Vries M, Loboda A, Ens W, Standing KG (2001) Matrix-assisted laser desorption/ionization quadrupole time-of-flight mass spectrometry: an elegant tool for peptidomics. Proteomics 1: 118–131 6. Verhaert PD, Conaway MCP, Pekar TM, Miller K (2007) Neuropeptide imaging on an LTQ with vMALDI source: the complete ‘all-inone’ peptidome analysis. Int J Mass Spectrom 260:177–184 7. Fox CH, Johnson FB, Whiting J, Roller PP (1985) Formaldehyde fixation. J Histochem Cytochem 33:845–853

8. Gaffney EF, Riegman PH, Grizzle WE, Watson PH (2018) Factors that drive the increasing use of FFPE tissue in basic and translational cancer research. Biotech Histochem 93:373–386 9. Lemaire R, Desmons A, Tabet JC, Day R, Salzet M, Fournier I (2007) Direct analysis and MALDI imaging of formalin-fixed, paraffinembedded tissue sections. J Proteome Res 6: 1295–1305 10. Groseclose MR, Massion PP, Chaurand P, Caprioli RM (2008) High-throughput proteomic analysis of formalin-fixed paraffin-embedded tissue microarrays using MALDI imaging mass spectrometry. Proteomics 8:3715–3724 11. Paine MRL, Ellis SR, Maloney D, Heeren RMA, Verhaert PDEM (2018) Digestion-free analysis of peptides from 30-year-old formalinfixed, paraffin-embedded tissue by mass spectrometry imaging. Anal Chem 90:9272–9280 12. Buchberger AR, DeLaney K, Johnson J, Li L (2018) Mass spectrometry imaging: a review of emerging advancements and future insights. Anal Chem 90:240–265 13. Castellino S, Groseclose MR, Wagner D (2011) MALDI imaging mass spectrometry: bridging biology and chemistry in drug development. Bioanalysis 3:2427–2441 14. Spraggins JM, Caprioli RM (2011) Highspeed MALDI-TOF imaging mass spectrometry: rapid ion image acquisition and considerations for next generation instrumentation. J Am Soc Mass Spectrom 22:1022–1031 15. Ovchinnikova K, Kovalev V, Stuart L, Alexandrov T (2020) OffsampleAI: artificial intelligence approach to recognize off-sample mass spectrometry images. BMC Bioinform 21

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16. Titford M (2005) The long history of hematoxylin. Biotech Histochem 80:73–78 17. Bhattacharya N, Nagornov K, Verheggen K, Tsybin Y, Verhaert M, Sciot R (2022) MS1-based data analysis approaches for FFPE tissue imaging of endogenous peptide ions by mass spectrometry histochemistry. This volume 18. Cintron-Diaz YL, Gomez-Hernandez ME, Verhaert MMHA, Verhaert PDEM,

Fernandez-Lima F (2022) Spatially resolved neuropeptide characterization from neuropathological formalin-fixed, paraffin-embedded tissue sections by a combination of imaging MALDI FT-ICR mass spectrometry histochemistry and liquid extraction surface analysis-trapped ion mobility spectrometrytandem mass spectrometry. J Am Soc Mass Spectrom 33:681–687

Chapter 3 Spatially Resolved Quantitation of Drug in Skin Equivalents Using Mass Spectrometry Imaging (MSI) Cristina Russo and Malcolm R. Clench Abstract Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) has seen a growing interest as a leading technique in the pharmaceutical industry for mapping label-free exogenous and endogenous species in biological tissues. However, the use of MALDI-MSI to perform spatially resolved absolute quantitation of species directly in tissues is still challenging, and robust quantitative mass spectrometry imaging (QMSI) methods need to be developed. In this study, we describe the microspotting technique for analytical and internal standard deposition, matrix sublimation, powerful QMSI software, and mass spectrometry imaging setup to obtain absolute quantitation of drug distribution in 3D skin models. Key words MALDI-MSI, Quantitation, QMSI, Internal standard, Microspotting, 3D skin models

1

Introduction The simultaneous visualization and quantitation of endogenous (i.e., lipids and proteins) and exogenous species (i.e., drugs) directly within tissue samples are essential to provide insights into a disease’s onset/progression as well as pharmacological/toxic effects of drug exposure. To estimate drug concentration in tissues, it is common to measure the levels of drugs in liquid matrices, such as serum, plasma, and blood. However, this approach presents limitations; several factors could generate irregularity between drug levels in liquids and tissue, leading to misinterpretations [1]. This points out the necessity of measuring drug concentration directly at the site of action (tissue level) in order to obtain an accurate evaluation of drug activity within the body. Over the last decade, the use of MALDI-MSI has rapidly expanded in pharmaceutical research for the analysis of spatial lipidomics, metabolomics and proteomics, and small molecules, such as pharmaceuticals [2–4]. Although MALDI-MSI has been

Laura M. Cole and Malcolm R. Clench (eds.), Imaging Mass Spectrometry: Methods and Protocols, Methods in Molecular Biology, vol. 2688, https://doi.org/10.1007/978-1-0716-3319-9_3, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2023

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extensively used for qualitative analysis, its application for absolute quantitative analysis is still controversial and remains one of the hottest topics debated among MSI experts. The main limitations hindering the use of MALDI-MSI for quantitative analysis include variations of protonation/deprotonation efficiency of different compounds, analyte extraction efficiency, and “ion suppression” effects. This latter aspect indicates the reduced ionization efficiency for analyte(s) of interest (AOIs), derived from ion competition with surrounding chemical species and tissue heterogeneity [5, 6]. In the MALDI-MSI technique, the presence of a laser energy-absorbing matrix also has to be considered for QMSI analysis. Matrix size and morphology have an important impact on ionization efficiency, and a heterogeneous deposition of matrix onto a sample results in AOI ion signal variations, causing an additional problem to overcome. The sublimation technique has been proven to homogenously deposit highly pure matrix crystals of micrometer size and avoid AOI delocalization [7, 8], clearly enhancing the MALDI process for high-resolution quantitative analysis. To accurately determine the concentration of AOIs within tissues, a calibration curve is essential. Calibration curves are generated by using a serial dilution of standards, which are most commonly spotted onto a control tissue section [9–12]. An acoustic robotic spotter can be used to apply picoliter volumes of standards accurately directly onto a specific tissue microenvironment from which the AOI is extracted, allowing to overcome signal ion variations associated with tissue heterogeneity. Also, the microspots generated are highly reproducible in size and diameter, offering precise control of the standard amount applied [13, 14]. It has been established that the use of an internal standard (IS) in the MSI workflow enhances QMSI capabilities. An internal standard, usually a stable isotope labeled (SIL) version of the AOI or a structurally similar molecule, mimics the AOI in terms of ionization and extraction efficiency. The AOI signal normalization against an internal standard has proven to increase relative signal ion reproducibility. A constant concentration of internal standard has to be added into MSI experiments, and it has to be detected in the same MS scan as the targeted analyte in order to correct for signal ion variations [12, 14–16]. Alongside continuous research in method development for QMSI analysis, many software packages designed for analyzing and processing QMSI data have seen a quick evolution, such as the msIQuant freeware developed by Uppsala University (Sweden). This software offers a variety of features to process large datasets for quantitative analysis, such as multiple visualization methods and multiple options for the creation of regions of interest (ROIs) [17]. The intense efforts toward developing robust methods and software packages for QMSI analysis have a significant value,

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opening up the possibility in the future of routinely using MSI for spatially resolved quantitation of exogenous/endogenous species distribution directly within tissue samples without requiring validation with gold standard traditional techniques, such as liquid chromatography-mass spectrometry (LC-MS).

2

Materials Unless otherwise stated, all solutions are prepared using ultrapure, deionized water (dH2O) and analytical grade reagents of purity 99.8% or above.

2.1

Tissue Treatment

1. Terbinafine hydrochloride (TBF HCl) standard. 2. Isosorbide dimethyl ether (DMI). 3. Methanol. 4. Olive oil. 5. Labskin living skin equivalent (LSE) samples (Innovenn (UK), Ltd. (York, England)). 6. Labskin maintenance medium. 7. Sterile inoculating loop.

2.2

Tissue Washing

2.3 Tissue Freezing (Cryopreservation)

1. LC-grade MeOH. 1. Isopentane (2-methylbutane). 2. Liquid nitrogen, in a suitable insulator container. 3. Weighing boat. 4. Blade. 5. Tweezers.

2.4 Tissue Sectioning

1. Polylysine-coated glass slides (see Note 1) (indium tin oxidecoated glass slides can be used if a conductive surface is needed). 2. dH2O. 3. Blade. 4. Chuck. 5. Cork disk. 6. Optimal cutting temperature (OCT) medium. 7. Cryostat (Leica 200 UV, Leica Microsystems, Milton Keynes, UK).

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Tissue Drying

1. Glass jar. 2. Freeze drier.

2.6 Analytical and Internal Standards

1. Calibration standards: Prepare calibration standards in concentrations of 0.01, 0.1, 1, 10, 100, 500, 1000, and 1500 ng/μL of TBF HCl with 100 ng/μL of the internal standard TBF-d7 HCl in MeOH/H2O (50:50). 2. Internal standard: Prepare 100 ng/μL of TBF-d7 HCl in MeOH/H2O (50:50). 3. Acoustic robotic spotter (Portrait 630, Labcyte Inc., Sunnyvale, CA, USA).

2.7

Matrix Coating

1. Sublimation chamber (Sigma-Aldrich, Gillingham, UK). 2. Alpha-Cyano-4-hydroxycinnamic acid (CHCA).

2.8 MS Setup and Data Acquisition

1. Traditional flatbed scanner. 2. MALDI mass spectrometer: Waters MALDI HDMS Synapt G2 mass spectrometer (Waters Corporation, Manchester, UK) equipped with a neodymium/yttrium aluminum garnet (Nd:YAG) laser operated at 1 kHz. 3. Phosphorus red calibrant: Prepare a saturated solution of phosphorus red in 100% acetone.

2.9 Software Processing

1. MassLynx 4.1 (Manchester) for configuration of Waters parameters and control of spectral acquisition. See the user manual for more details. 2. HDI 1.4 (Waters Corporation, UK) for imaging acquisition and visualization and converting MSI raw data files into imzML format. 3. msIQuant freeware software available from https://msimaging.org/paquan/ for processing imzML format data and performing quantitative investigations.

3 3.1

Methods Sample Handling

All preparation of Labskin should be carried out in a category 2 laminar flow hood in order to maintain a sterile environment and reduce the risk of contamination. 1. Transfer in vitro tissue (Labskin) into new 12 deep well plates, suspend them in fresh maintenance medium, and leave to incubate for 24 h with 5% CO2, at 37 °C (see Note 2). 2. After 24 h, change the medium with fresh Labskin maintenance medium and prepare treated, vehicle control Labskin tissues by

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applying appropriate formulations onto the skin surface including or not including the active ingredient terbinafine hydrochloride (see Note 3). For the blank group, leave three Labskin tissues untreated. Incubate all Labskin tissues for 24 h. 3.2 Cryoconservation of Tissue

1. Remove Labskin tissue from the well using a scalpel; use tweezers to maintain the sample at an incline and, with the aid of a pipette, wash the tissue surface with LC-grade MeOH to remove excess formulation (see Note 4). 2. Instantly place the tissue into the correct orientation onto a weighing boat containing isopentane cooled by liquid nitrogen (see Note 5). 3. Store the tissue in the freezer at -80 °C.

3.3 Cryo-sectioning of Tissue

1. Set the temperature of the Leica 200 UV cryostat with a new clean blade fitted to -25 °C. 2. Use ~50–100 μL of dH2O to fix the frozen tissue onto a cork disk, ensuring the tissue is correctly positioned. Work within the cryostat at -25 °C (see Note 6). 3. Fix the cork disk with the tissue to a cryostat chuck using ~50–100 μL of either dH2O or 2% optimal cutting temperature (OCT) (see Note 7). 4. Prior to cryo-sectioning, leave the mounted tissue in the cryostat for 30 min to allow it to thermally equilibrate. Cut the sections to 12 μm thickness (see Note 8). 5. Adhere the tissue sections onto polylysine glass slides by the thaw-mounting process (see Note 9). 6. Place the sample slides into a slide holder and store them at 80 °C.

3.4 Calibration Curve Construction

The calibration curve is created by applying analytical and internal standards onto a blank tissue section using the acoustic microspotter Portrait 630 (see Note 10). 1. Before applying the calibrants, freeze-dry the slides containing the tissue sections under vacuum (0.035 mbar) for 2 h (see Note 11). 2. Calibrate the acoustic robotic spotter Portrait 630. Fix a clean calibration slide to the target plate and load it into the Portrait instrument. Pipette between 500 and 800 μL solution of 50% MeOH into the source reservoir between the baffle and reservoir wall. Optimize the focus and power values for the transducer to eject the reagent onto the calibration slide (see Note 12). Please consult the user manual for more information.

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3. After calibration, remove the calibration slide and position an untreated tissue section (blank) onto the target plate holder using double-sided tape. Introduce the plate into the Portrait instrument. 4. Click the PREVIEW SCAN button to visualize the entire target holder containing the blank sample. By using the REGION tool, indicate the area of the sample (epidermis) to be spotted. 5. Press the SCAN button to obtain a high-resolution scan of the selected area. 6. Use the SCATTER PATTERN method to allocate the exact points within the specimen where the reagent will be ejected. 7. Load the source reservoir with the reagent, which corresponds to the first calibration point. The first calibration point corresponds to the blank point, consisting of MeOH 50% (see Note 13). 8. Eject reagent spots onto the selected sample area using the START/STOP spotting mode. Set the number of cycles to 20 for a total volume of 3.4 nL of the blank spot. 9. For spotting the following calibration standards, repeat steps 4–6. Load the source reservoir, in turn, with the serial concentrations of analytical standards mixed with the internal standard. The working standards are made to 0.01, 0.1, 1, 10, 100, 500, 1000, and 1500 ng/μL of TBF HCl with 100 ng/μL of the internal standard TBF-d7 HCl in MeOH/H2O (50:50) (see Note 14). 10. Repeat step 9 for each run. 3.5 Acoustic Spotter Portrait 630: Application of Internal Standard onto the Treated Samples

In the control and treated sample groups, a constant concentration of an internal standard has to be included. 1. Fix the control and the two treated Labskin sections onto the Portrait target plate holder using double-sided tape. 2. Click the PREVIEW SCAN button to visualize the entire target holder containing the sample sections. By using the REGION tool, indicate the area of the samples (epidermis) to be spotted. 3. Press the SCAN button to obtain a high-resolution scan of the selected area. 4. Use the SCATTER PATTERN method to allocate the exact points within the specimen where the reagent will be ejected. Select 9 points across the epidermal layer of each sample. 5. Load the internal standard solution (100 ng/μL of TBF-d7 HCl in MeOH/H2O (50:50)) into the source reservoir.

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6. Eject the internal standard spots onto the selected sample area using START/STOP spotting mode. Set the number of cycles to 20 for a total volume of 3.4 nL per spot. 3.6 Matrix Application

Apply matrix onto the microspotted skin slides using sublimation as a matrix deposition technique (see Note 15). 1. After microspotting, attach the glass slides containing the blank, control, and treated skin sections to the underneath of the top section of the sublimation apparatus by using doublesided tape. 2. Spread α-CHCA (300 mg) at the bottom of the sublimation apparatus (Sigma-Aldrich). 3. Attach the flat top of the chamber to the bottom using an O-ring seal and apply the vacuum. 4. When a stable vacuum of 2.5 × 10-2 Torr is achieved, fill the top with cold water (5 °C) and set the temperature to 180 °C to start the sublimation process. 5. Perform the sublimation process until the optimal amount of α-CHCA (0.2 mg/cm2) is deposited (see Note 16). The time taken to complete this process is around 20 min. 6. Ideally, samples should be analyzed on the same day as matrix deposition. If it is impossible to continue the analysis, samples can be stored in sealed boxes at +4 °C overnight.

3.7 Instrumentation and Data Acquisition

1. Calibrate the MALDI HDMS Synapt G2 mass spectrometer (Waters Corporation, Manchester, UK) across a range of m/z 100–1500 using 0.5 μL of phosphorus red. 2. Attach the Labskin sections covered with sublimed matrix to the IMAGE MALDI target using double-sided tape (see Note 17). 3. Scan the slide with the sample using a traditional flatbed scanner and save the image in .jpeg format. 4. Upload the .jpeg within the high-definition imaging (HDI) software for co-registration and image setup. 5. Load the imaging plate with the sample into the mass spectrometer, and acquire MALDI-MS image in positive mode, in full scan “sensitivity” mode at a range of m/z 100–1500 (resolution 10,000 FWHM). Set the spatial resolution to 60 μm × 60 μm and the laser energy to 250 arbitrary units. Do not enable the ion mobility function of the instrument (see Note 18).

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Data Analysis

1. Process the MALDI-MS imaging data using the HDI 1.4 software (Waters Corporation, Manchester, UK). 2. Convert the MSI raw data file in imzML format and import data to msIQuant software for quantitative investigation (see Note 19). msIQuant software offers a number of features, including normalization, visualization methods, color scales, and the possibility of drawing different region of interest (ROI) types. 3. Select both endogenous peaks to visualize relevant features in your sample and the ion signals from the IS and/or the AOI (see Note 20). Multiple signals can be simultaneously visualized by choosing different colors. 4. Define a region of interest (ROI) around each calibrant applied onto the epidermal layer of the blank tissue section. Extract the average m/z intensity of the AOI and internal standard from each ROI. A tabulated list containing the selected ROIs is displayed. Indicate the quantity of each calibrant standard associated with each ROI. Choose an appropriate normalization method; the msIQuant software automatically will create a calibration curve in which slope, intercept, and regression coefficient are shown (see Fig. 1) (see Note 21). 5. Calculate the limit of detection (LOD) and limit of quantitation (LOQ) (see Note 22). 6. Define regions of interest (ROIs) around the spots of internal standards spotted onto the vehicle control and drug-treated Labskin sections. From each ROI, extract the m/z intensity of the AOI present in the tissues and the internal standard applied onto the tissue. Choose an appropriate normalization method to detect the signal intensity of the AOI. Use the same normalization method across your experiment. 7. Determine the unknown concentration of the AOI from the vehicle control and drug-treated tissue sections by resolving the calibration equation (see Note 23). 8. Repeat the experiment and perform multiple MALDI-MSI runs using three technical replicate Labskin sections (see Note 24).

4

Notes 1. Any slides with a positive charge surface can be used as an alternative to the polylysine slides. The positively charged surface is ideal for promoting tissue adhesion. 2. A 5% CO2 incubator is used to maintain an optimal environment for cell growth by imitating physiological-like conditions:

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Fig. 1 (a) MALDI-MSI of the epidermis of the blank section of Labskin microspotted with the serial dilution of TBF HCl mixed with the standard internal TBF-d7 HCl, acquired at a spatial resolution of 60 μm x 60 μm. Ion images show the distribution of phosphocholine head group in blue (m/z 184), the ceramide fragment peak in green (m/z 264), and the internal standard TBF-d7 source-generated fragment ion in red (m/z 148). Graphs B and C show the calibration curves of TBF standards obtained with (b) and without (c) IS-based normalization

pH of about 7, the temperature of 37 °C, and relative humidity of about 97%. 3. To prepare the drug-treated group, apply 20 μL of terbinafine hydrochloride (1% w/w) dissolved in an emulsion made up of water/olive oil (80:20 v/v) with either 10% or 50% isosorbide dimethyl ether onto the surface of six Labskin tissues (three for each treatment). To prepare the vehicle control group, apply 20 μL of the emulsion water/olive oil (80:20 v/v) alone onto the three Labskin samples. Including a vehicle control tissue section is crucial in quantitative experiments, as it allows to determine whether the AOI signal derives only from the drug treatment or is also a result of background interference.

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NB: When applying the formulation onto the skin, it is beneficial to use a sterile inoculating loop to spread the formulation evenly on the skin’s surface. This is done to avoid different areas of the skin receiving different amounts of the formulation, compromising the experiment’s reliability and reproducibility. 4. Any other organic solvents in which terbinafine is soluble can be used as an alternative to MeOH to remove excess formulation. The washing step is recommended before cryoconservation to ensure that the concentration of the drug measured in MSI analysis corresponds only to the drug absorbed in the skin and not to the excess formulation retained on the skin surface. 5. It is recommended to use isopentane cooled with liquid nitrogen to snap-freeze tissue samples to preserve tissue structure by avoiding ice crystal artifacts. Note that the process has to be performed quickly. 6. Commonly optimal cutting temperature (OCT) is used to embed or fix tissues prior to cryo-sectioning; however, the peaks derived from OCT can negatively impact MSI analysis. The OCT medium consists of water-soluble resins and glycols, which add peaks’ interference within the spectra, causing AOI peak suppression [18]. To avoid this, dH2O can be used to fix the tissue onto a cork disk mounted on a chuck. 7. For mounting the cork circle with tissue onto a cryostat chuck, OCT can be used as it will not be in contact with the tissue and risks of contamination are unlikely. 8. A paper by Sugiura et al. discusses the influence of thickness on spectral quality, i.e., peak sensitivity and S/N ratio [19]. The thickness value commonly used for human skin samples is between 8 and 12 μm [18]. 9. Thaw mounting: It is the process by which the tissue section is attached to the glass slide electrostatically. To perform this process, place the glass slide close to the sectioned tissue to allow it to be transferred to the glass and then fix the tissue to the slide using heat generated by rubbing the underside of the slide with a gloved finger. 10. The acoustic spotter Portrait 630 deposits sub-microliter volumes (3.4 nL) of analyte and internal standards precisely onto a defined location (epidermal layer) of a blank Labskin section of 12 μm thickness. The epidermis represents the histological microenvironment where the AOI is localized in the treated samples. The application of microspots selectively onto the well-defined epidermal region of the blank section allows obtaining “matrix-matched standards” that mimic cell type-

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based ionization response of the analyte from the treated tissues, reducing signal ion variations. 11. Freeze-drying is preferred over traditional drying methods (i.e., vacuum desiccation) as it better preserves tissue integrity and minimizes the analyte’s delocalization. Freeze-drying works by instantly freezing and subliming the ice generated upon removal of the sample from the freezer at -80 °C. 12. The reagent used for calibrating the Portrait 630 instrument has to be the same or similar to the solvent in which the analyte and internal standards are dissolved. 13. Including a blank point in the calibration curve is important to evaluate whether it interferes with the AOI signal or adds any background signal to it. The blank point should contain the solvent solely without the AOI and undergo the same analytical procedures. 14. With regard to the construction of a calibration curve, a work by Stauffer examines methodologies in analytical calibration and validation [20]. A calibration curve should contain between 6 and 8 standard points and a blank point [21]. Carefully choose the concentration of the calibration standards to use; these should be evenly spread across the calibration range. 15. Sublimation is chosen as a matrix deposition technique for high spatial resolution. Sublimation guarantees a homogenous deposition of the matrix with microcrystalline morphology and less spreading (delocalization) of the analyte due to the absence of solvents [22]. 16. To monitor the amount of deposited matrix, subtract the weight (mg) of the slide measured before sublimation from the weight of the slide with the sublimated matrix. Then, divide the difference obtained (in mg) by the area of the sublimated slide in order to obtain the value of the matrix deposited in mg/cm2. 17. Include the calibration, vehicle control, and drug-treated tissue slides in each MSI run to facilitate appropriate normalization of the analyte signal. 18. Make sure not to enable the instrument’s ion mobility function in order to convert the raw MSI data to imZML format and process it into msIQuant software. 19. imzML is a widely used open-access format for MSI data. MSI data converted to imzML format can be handled and read by many software packages, regardless of the MS manufacturer, promoting easy exchange and processing of MSI data [23]. 20. The mapping of endogenous species can help distinguish a specific histological microenvironment across the sample. To visualize the epidermal layer of the sample, select the signals

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derived from endogenous lipid species, such as the phosphocholine ion signal (m/z 184) to define the epidermis and the ceramide fragment ion (m/z 264) to define the stratum corneum. 21. The calibration curve presents the average intensity ratio (AOI/IS) versus the amount of standards applied onto the tissue, which is expressed in ng/mm2. The concentration of the standards can also be reported in units of moles or moles per unit area. 22. With the calibration curve construction, the limit of detection (LOD) and limit of quantitation (LOQ) can be measured using the following formulas, LOD = 3 s/m and LOQ = 10 s/m, where s is the standard deviation of the signal intensity and m is the slope of the calibration curve. NB: LOD and LOQ can differ depending on the QMSI method and the MALDI instrument used. 23. The calibration equation is y = mx + b, where m is the slope of the linear calibration curve and b is the y-intercept. Knowing the y value (average intensity of the AOI/IS), it is possible to rearrange the equation to obtain the amount of drug (x) in the treated samples, expressed in ng/mm2. Convert the amount of drug from ng/mm2 to mg/g tissue following the steps: ● Multiply the area (1 mm2) by the thickness of the section (0.012 mm) to determine the volume of tissue in 1 mm2, which is equal to 0.012 mm3. ● Multiply the volume (0.012 mm3) by the density of the tissue Labskin (1 mg/mm3) to determine the amount of tissue (in gram) in 1 mm2, which is equal to 0.000012 g. ● Divide the drug concentration from each spot (ng/mm2) by the gram of tissue in 1 mm2 to determine the drug concentration in mg/g tissue. ● Average the values (mg/g tissue) obtained from the spots applied onto each Labskin treated section to obtain the final value of drug (mg/g tissue) present in each section. 24. In order to assess the robustness, reproducibility, and reliability of QMSI methods, replicates are essential. Technical replicate sections are sections taken from the same tissue sample, whereas biological replicate sections are sections obtained from different tissue samples under the same conditions. Although technical replicates are widely used for QMSI experiments, these fail to investigate biological variations that may occur among tissues derived from different sources. It would be ideal to repeat QMSI experiments using at least three biological replicates [21].

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Acknowledgments This work was supported by the Centre for Mass Spectrometry Imaging, Biomolecular Sciences Research Centre of Sheffield Hallam University, and Croda Plc. Innovenn (UK) Ltd. References 1. Zhang D, Hop CECA, Patilea-Vrana G, Gampa G, Seneviratne HK, Unadkat JD, Kenny JR, Nagapudi K, Di L, Zhou L, Zak M, Wright MR, Bumpus NN, Zang R, Liu X, Lai Y, Cyrus Khojasteh S (2019) Drug concentration asymmetry in tissues and plasma for small molecule-related therapeutic modalities. Drug Metab Dispos 47(10):1122–1135 2. Russo C, Heaton C, Flint L, Voloaca O, Haywood-Small S, Clench MR, Francese S, Cole LM (2020) Emerging applications in mass spectrometry imaging; enablers and roadblocks. J Spectral Imaging 9:1–21 3. Amstalden van Hove ER, Smith DF, Heeren RMA (2010) A concise review of mass spectrometry imaging. J Chromatogr A 1217(25):3946–3954 4. Sommella E, Salviati E, Caponigro V, Grimaldi M, Musella S, Bertamino A, Cacace L, Palladino R, di Mauro G, Marini F, D’Ursi AM, Campiglia P (2022) MALDI mass spectrometry imaging highlights specific metabolome and Lipidome profiles in salivary gland tumor tissues. Meta 12(6):530 5. Unsihuay D, Mesa Sanchez D, Laskin J (2020) Quantitative mass spectrometry imaging of biological systems. Annu Rev Phys Chem 72: 307–329 6. Ellis SR, Bruinen AL, Heeren RMA (2014) A critical evaluation of the current state-of-theart in quantitative imaging mass spectrometry. Anal Bioanal Chem 406(5):1275–1289 7. Phan NTN, Mohammadi AS, Dowlatshahi Pour M, Ewing AG (2016) Laser desorption ionization mass spectrometry imaging of drosophila brain using matrix sublimation versus modification with nanoparticles. Anal Chem 88(3):1734–1741 8. Thomas A, Charbonneau JL, Fournaise E, Chaurand P (2012) Sublimation of new matrix candidates for high spatial resolution imaging mass spectrometry of lipids: enhanced information in Both positive and negative polarities after 1,5-Diaminonapthalene deposition. Anal Chem 84(4):2048–2054 9. Nilsson A, Fehniger TE, Gustavsson L, Andersson M, Kenne K, Marko-Varga G, Andre´n PE (2010) Fine mapping the spatial

distribution and concentration of unlabeled drugs within tissue micro-compartments using imaging mass spectrometry. PloS One 5(7):e11411 10. Lagarrigue M, Lavigne R, Tabet E, Genet V, Thome´ J-P, Rondel K, Gue´vel B, Multigner L, Samson M, Pineau C (2014) Localization and in situ absolute quantification of Chlordecone in the mouse liver by MALDI imaging. Anal Chem 86(12):5775–5783 11. Barre´ FPY, Flinders B, Garcia JP, Jansen I, Huizing LRS, Porta T, Creemers LB, Heeren RMA, Cillero-Pastor B (2016) Derivatization strategies for the detection of triamcinolone Acetonide in cartilage by using matrix-assisted laser desorption/ionization mass spectrometry imaging. Anal Chem 88(24):12051–12059 12. Tang W, Chen J, Zhou J, Ge J, Zhang Y, Li P, Li B (2019) Quantitative MALDI imaging of spatial distributions and dynamic changes of tetrandrine in multiple organs of rats. Theranostics 9(4):932–944 13. Handler AM, Pommergaard Pedersen G, Troensegaard Nielsen K, Janfelt C, Just Pedersen A, Clench MR (2021) Quantitative MALDI mass spectrometry imaging for exploring cutaneous drug delivery of tofacitinib in human skin. Eur J Pharm Biopharm 159:1–10 14. Russo C, Brickelbank N, Duckett C, Mellor S, Rumbelow S, Clench MR (2018) Quantitative investigation of terbinafine hydrochloride absorption into a living skin equivalent model by MALDI-MSI. Anal Chem 90(16):10031–10038 15. Pirman DA, Heeren RMA, Yost RA (2013) Identifying tissue-specific signal variation in MALDI mass spectrometric imaging by use of an internal standard. Anal Chem 85(2):1090–1096 16. Prentice BM, Chumbley CW, Caprioli RM (2017) Absolute quantification of rifampicin by MALDI imaging mass spectrometry using multiple TOF/TOF events in a single laser shot. J Am Soc Mass Spectrom 28(1):136–144 17. K€allback P, Nilsson A, Shariatgorji M, Andre´n PE (2016) msIQuant - quantitation software for mass spectrometry imaging enabling fast

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access, visualization, and analysis of large data sets. Anal Chem 88(8):4346–4353 18. de Macedo CS, Anderson DM, Schey KL (2017) MALDI (matrix assisted laser desorption ionization) imaging mass spectrometry (IMS) of skin: aspects of sample preparation. Talanta 174:325–335 19. Sugiura Y, Shimma S, Setou M (2006) Thin sectioning improves the peak intensity and signal-to-noise ratio in direct tissue mass spectrometry. J Mass Spectrometry Soc Japan 54(2):45–48 20. Stauffer M (2018) Calibration and validation of analytical methods - a sampling of current approaches. IntechOpen, London 21. Campbell A, Stauber J (2021) Chapter 6. Quantitative MSI: a review of biomarker and

drug quantifications using mass spectrometry imaging. In: Siegel TP (ed) MALDI mass spectrometry imaging: from fundamentals to spatial omics. Royal Society of Chemistry, pp 105–130 22. Hankin JA, Barkley RM, Murphy RC (2007) Sublimation as a method of matrix application for mass spectrometric imaging. J Am Soc Mass Spectrom 18(9):1646–1652 23. Schramm T, Hester A, Klinkert I, Both JP, Heeren RMA, Brunelle A, Lapre´vote O, Desbenoit N, Robbe MF, Stoeckli M, Spengler B, Ro¨mpp A (2012) ImzML - a common data format for the flexible exchange and processing of mass spectrometry imaging data. J Proteome 75(16):5106–5110

Chapter 4 Update DESI Mass Spectrometry Imaging (MSI) Emmanuelle Claude, Mark Towers, and Emrys Jones Abstract Desorption electrospray ionization (DESI) is an ambient technique that allows chemical information to be obtained directly from a wide range of surfaces, without pretreatment. Here we describe the improvements that have been developed to be able to achieve low tens of microns pixel size MSI experiments with high sensitivity for metabolites and lipids from biological tissue sections. In the last decade, DESI mass spectrometry has undergone developmental improvements, with regard to the method of desorption and ionization as well as the mass spectrometer to which the DESI source has been coupled to. DESI is becoming a mass spectrometry imaging technique, which can match and complement the currently most widely adopted ionization technique, the matrix-assisted laser desorption/ionization (MALDI). Key words DESI, Ambient, Heated transfer line, High definition imaging, Co-registration

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Introduction Desorption electrospray ionization (DESI), firstly introduced by Cooks et al. [1] in 2004, has emerged as a powerful and versatile ambient ionization technique. The DESI technique consists of charged solvent droplets, carried by a nebulizing gas, that impact upon the surface, desorbing and ionizing molecules that are then carried toward the atmospheric pressure inlet of the mass spectrometer, directly from the surface with no or minimal sample preparation. DESI differs from other MSI techniques such as matrixassisted laser desorption/ionization (MALDI) where a coating of suitable matrix is required on the sample and is most commonly performed in vacuum. It opens up a range of novel applications while greatly simplifying the analysis. Using DESI MS, a wide range of molecules including glycans [2], lipids [3], polymers [4], pharmaceutical compounds [5], peptides [6], and proteins [7] can be detected directly from a surface. Particular attention has been focused on biological tissues, where it has been shown that the technique allows for the detection of a

Laura M. Cole and Malcolm R. Clench (eds.), Imaging Mass Spectrometry: Methods and Protocols, Methods in Molecular Biology, vol. 2688, https://doi.org/10.1007/978-1-0716-3319-9_4, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2023

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Fig. 1 DESI XS high-performance sprayer cross-sectional images. (Printed with permission by Waters)

Fig. 2 Image of the ion inlet tube. (Printed with permission by Waters)

multitude of endogenous small metabolites and lipids that can be correlated with biochemical processes and disease progression [8]. With a host of recent publications indicating that the phospholipid signature can be used to classify tissue types, DESI shows significant potential to be a powerful technique in oncology [9], in the form of molecular histopathology. In recent years, DESI has gained momentum and uptake from scientists worldwide, despite concerns ranging from the ease of setup, reproducibility, sensitivity, and spatial resolution compared to other MSI modalities. There have been some studies reporting the repeatability and reproducibility of DESI examining human esophageal tissue [10] section and a large-scale inter-laboratory study using rhodamine-coated slides [11]. To address these issues, a re-engineering of the core component of the system (Fig. 1), the DESI sprayer, resulted in the release of the high-performance DESI sprayer, simplifying the optimization as well as improving the robustness, and the heated transfer line (HTL) (Fig. 2), increasing sensitivity and molecular coverage. Here we describe the workflows for DESI optimization and MSI setup to obtain DESI MS image maps of small molecule metabolites and lipid signals directly from tissue sections (porcine

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liver and mouse brain) using a Waters™ DESI XS source that can be mounted on a hybrid quadrupole orthogonal acceleration time-offlight (Q-TOF) mass spectrometer (Xevo™ G2-XS, Xevo G3, SYNAPT™ XS, SELECT SERIES™ Cyclic™ IMS, or SELECT SERIES MRT mass spectrometers).

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Materials

2.1

Tissue Sections

2.2

Reagents

1. Tissue sections are generated using the same protocol [12] as for other MSI techniques. Typically, a snap-frozen tissue block is allowed to warm to the desired cutting temperature and then sectioned at 10–20 μm thickness, using a cryostat-microtome (e.g., CM3050 S, Leica™, Buffalo Grove, IL, USA), onto standard glass microscope slides. If not analyzed immediately, these slides are then stored in a -80 °C freezer until required. It is highly recommended that fresh solutions should be prepared frequently to provide optimal results by avoiding contamination issues that can arise from refilling the solvent syringe from the same solution repeatedly. 1. Solvents: water (ultrapure) and methanol HPLC grade or higher. A typical composition for DESI imaging is 95% methanol and 5% water. 2. Red Sharpie™ containing Rhodamine 6G dye. 3. Black permanent marker Staedtler™ Lumocolor™, black ink.

2.3

Equipment

1. DESI source is a Waters DESI XS (Waters Corporation, Wilmslow, UK) (Fig. 3). 2. Solvent delivery options: 1. Syringe Pump 11 Elite infusion-only single syringe pump (Harvard Apparatus, Holliston, MA, USA). 2. Waters μBSM/ASM: nano-LC pump can be in standalone or as part of a Waters ACQUITY™ M-Class system (Waters Corporation, Milford, MA, USA). 3. Mass spectrometer: Xevo G2-XS QTof, SYNAPT XS HDMS, SELECT SERIES Cyclic IMS, or SELECT SERIES MRT (Waters Corporation, Milford, MA, USA). 4. The DESI sprayer is the DESI XS High-Performance Sprayer (Waters Corporation, Milford, MA, USA). This contains a cartridge with a 30-μm-inner-diameter metal emitter insert. The tip of the emitter is positioned behind the orifice of the nozzle, in a fixed position (Fig. 1).

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Fig. 3 Image of the heated transfer line (HTL) mounted on the mass spectrometer. (Printed with permission by Waters)

5. Ion inlet tube 1. Standard ion inlet tube (Waters Corporation, Milford, MA, USA). 2. Heated transfer line (HTL) (Waters Corporation, Milford, MA, USA): the HTL temperature is defined in MassLynx™ tune page from room temperature (RT) up to 450 °C. 2.4

Software

1. Prosolia Omni Spray® 2D: software to control the DESI source for DESI sprayer optimization (Prosolia, Inc., Indianapolis, IN, USA). 2. MassLynx™ v4.2: software to control the DESI source (for DESI optimization and DESI imaging experiments) and to control the mass spectrometer (Waters Corporation, Wilmslow, UK). The SELECT SERIES MRT and Cyclic IMS mass spectrometer include QUARTZ software control. 3. High Definition™ Imaging (HDI™) v1.6: MSI software is used to set up DESI imaging experiment, processing and visualization of the DESI imaging data (Waters Corporation, Wilmslow, UK).

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Methods

3.1 Sprayer Construction

1. Place the emitter cartridge (Fig. 4b) inside the main body. 2. Place the gas metal nozzle (Fig. 4a) to the front of the main body (Fig. 4c). Push inward and turn the nozzle 1/4 turn clockwise and ensure that it is correctly locked in place.

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Fig. 4 Three parts of the Waters DESI high-performance sprayer. (Printed with permission by Waters)

3. Mount the HP sprayer assembly using the mounting bracket onto the arm of the DESI XS source. 4. Connect the solvent line (Fig. 5a), high-voltage cable (Fig. 5b), gas tube (Fig. 5c), and grounding cable (Fig. 5d). 3.2 DESI Signal Optimization

As described previously in the 2017 edition, the critical aspect to a successful DESI experiment is the formation of a focused, stable, and correctly aligned electrospray (Fig. 6). With the highperformance (HP) sprayer, the spray is defined by the relationship between the solvent flow, the gas flow, and the voltage applied to the primary droplets. In this design, the position of the emitter is fixed inside the sprayer, which removes the largest source of sprayer variation and critical optimization parameter, the protrusion of the emitter through the gas cone orifice. Furthermore, spraying the electrospray droplets through an orifice (200 μm diameter) leads to a more directionally uniform point on the surface. The electric fields are confined to the internal components of the sprayer, such that the potential drop from the end of the emitter is constant to the grounded nozzle, unlike the previous configuration where the

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Fig. 5 Waters DESI high-performance sprayer mounted on the DESI XS arm. (Printed with permission by Waters)

Fig. 6 Schematic of DESI with the Waters sprayer showing the gas, solvent, and high voltage applied onto the sprayer with the capture of the desorbed charged droplets into the metal capillary toward the mass spectrometer. (Printed with permission by Waters)

drop could be to the surface or the inlet of the MS, generating an unstable spray. Overall, the HP DESI sprayer is more robust and easy-to-use, as well gaining some sensitivity and spatial resolution with a more focused spray.

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Table 1 Starting DESI imaging settings Height of emitter above surface

0.5–2 mm

Emitter to inlet distance

3–5 mm

Sprayer angle

70–80° for imaging

Solvent flow

1–2 μL/min

Gas pressure

0.05–0.1 MPa

Solvent composition

95:5 methanol water

Voltage

0.6–1.2 kV

MS scan time

1s

1. Typical starting positions are described in Table 1. 2. Solvent composition for DESI imaging depends on the analyte of interest and the tissue surface. For lipids in negative and positive mode, 95–98% aqueous methanol is recommended as a starting point (see Notes 1 and 2). Many different solvent compositions and additives have been reported [13] and may also be used. 3. The flow of the solvent can be provided by using the mass spectrometer internal fluidics, external syringe pump, or nano-LC pump. It is critical that the system provides a stable flow rate at the microliter per minute range (see Note 3). 4. Allow the DESI solvent to flow through the DESI HP sprayer without any N2 gas and voltage for a few minutes. From MassLynx tune page, turn on the API N2 gas; some ejected solvent should be observed on the DESI XS source video camera just below the spray nozzle. Increase the voltage into the operating range (0.6–1.2 kV) until the strongest solvent peak signal is observed. This will be the starting point for optimization. Move the sprayer above an empty region of the glass side to ensure that solvent peaks are being detected. If no solvent ejection from the DESI sprayer is observed when the API N2 gas is turned on, check that solvent is flowing correctly and there are no leakages or blockages in the solvent line. If solvent peaks are not observed after the appearance of the solvent, repeat the last few steps by switching the N2 gas off and leave the DESI solvent go through the DESI HP sprayer. 5. Take a glass slide with a tissue section mounted from the -80 °C freezer. Let it defrost at room temperature for less than 30 min. Alternatively, a vacuum desiccation step can be used. No other sample preparation is required. Place the sample onto the DESI XS stage (see Note 4).

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6. Place the sprayer head above a tissue section (or drawn ink region; see Note 5). A tissue sample similar to the tissue intended for the study should be used for signal optimization, i.e., use a consecutive tissue section. However, if the optimization tissue sample is heterogeneous, the optimization can be difficult. We recommend a porcine liver tissue section for its relatively homogeneous nature. 7. From the MassLynx tune page, set the origin of the rectangle area of tissue to perform the optimization. Enter the width of the area, the DESI stage speed, the number of rows, and the distance between the rows. With the constant movement across the tissue, optimization of the DESI parameters can be carried out. 8. The N2 gas pressure (max 0.2 MPa) and the voltage (max 1.7 kV) are the main parameters to generate a tightly focused, stable spray (see Note 6). It should be followed by the optimization of the geometry parameters such as the alignment between the sprayer head and the ion inlet tube (X-direction), the distance between the sprayer head and the ion inlet tube (Y-direction), the distance between the sprayer head and sample surface (Z-direction), and the distance between the ion inlet tube and sample surface. (see Note 7). Further iterations of the cycle can be repeated for fine tuning. 9. If the HTL option is used, the temperature of the HTL should be optimized for the molecules or class of molecules of interest (see Note 8). 3.3 Mass Calibration Using the DESI Source 3.3.1 Preparation of the Polyalanine Thin Film Sample

3.3.2

MS Calibration

1. Dissolve polyalanine in a solution of methanol/water (i.e., 95: 5) at a concentration of 5 mg/mL. 2. Warm the glass slide at 70 °C in a laboratory oven or on a hot plate. *Care should be taken in handling these heated slides. 3. Spot 100 μL of the polyalanine solution on the warm glass slide and let it dry. If a more aqueous solution of polyalanine is made, use the side of the pipette to smear the solution over the slide to spread the solution on the glass slide and then let it dry. With the rapid evaporation, a thin film forms on the top of the glass slide (see Note 9). 1. Manually acquire an MS experiment in the ionization polarity desired for the experiments (Fig. 7). Use a collision energy of 30 V to generate low m/z peaks. 2. Combine at least 60 s of data with a constant movement of the DESI stage where the sprayer head is on the polyalanine film, and then process the MS spectrum using “Automated Peak Detection” to centroid the peaks (Fig. 8). Save the spectrum.

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Fig. 7 Negative mode MS spectra for DESI optimization of lipid signals on porcine liver tissue section; sprayer head (a) on the glass slide with HTL at RT, (b) on porcine liver tissue section with HTL at RT, (c) on porcine liver tissue section with HTL at 350 °C, and (d) on porcine liver tissue section with HTL at 450 °C. (Printed with permission by Waters)

Fig. 8 (a) DESI positive ionization mode MS spectrum of thin film polyalanine used for MS calibration; (b) DESI negative ionization mode MS spectrum of thin film polyalanine used for MS calibration. (Printed with permission by Waters)

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3. In IntelliStart/Calibration Profile Editor, select Manual for the type of calibration. Select the appropriate reference file and the saved MS spectrum by clicking on History. 3.4 DESI Imaging Setup

1. Acquire an optical image (photograph or flatbed scanner) of the tissue section(s) mounted on a conventional glass slide (see Note 10). Place the sample onto the DESI 2D™ stage. 2. Co-register the optical image using fiducial markers using High Definition Imaging (HDI) software or SELECT SEREIS tune page (see Note 11). 3. Define the rectangular region to be imaged from the co-registered optical image containing the tissue section. 4. For HDI, define the pixel size (μm) and the speed of the stage (μm/s). The acquisition rate is therefore calculated automatically. Typically, for maximum sensitivity, a slower scan rate such as 1 pixel per second gives an optimized sensitivity. For example, at 100 μm pixel size (X and Y), the speed of the stage is set at 100 μm/s. However, in TOF mode, the scan rate can be up to 30 pixels per second; in this case, the stage speed should be set to 3000 μm/s for the same pixel size. 5. For SELECT SERIES tune page, define the pixel size (μm) and the acquisition scan rate (s). The stage speed (μm/s) is therefore calculated automatically. 6. In HDI, MS parameters such as the type of experiment (MS, MS/MS, in TOF mode only, or with ion mobility separation IMS), mass range, polarity, and collision energy are defined. Processing parameters can also be set prior to the acquisition. Save the experiment parameters and create the worksheet to be loaded into MassLynx. 7. For SELECT SERIES tune page, MS parameters such as the type of experiment (MS, MS/MS, in TOF mode only, or with ion mobility separation IMS in the case of the Cyclic IMS mass spectrometer), mass range, polarity, and collision energy are defined. The acquisition can be started directly from the tune page or from the MassLynx sample list. 8. Start the acquisition using MassLynx, with the optional automatic processing step (see Note 12). 9. Load the processed DESI imaging data into HDI for visualization of the DESI imaging experiment.

3.5

Maintenance

3.5.1 Cleaning of the HP DESI Sprayer Emitter Cartridge and Nozzle

1. Remove the HP DESI XS sprayer from the DESI XS source arm, and remove the nozzle (1/4 turn counterclockwise) and the emitter cartridge.

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2. Remove the O-ring from the emitter cartridge. Sonicate the nozzle and the emitter cartridge in 50:50 methanol/water for 5 min. 3. Allow both items to dry (dry nitrogen stream can be used) and reassemble the DESI sprayer as previously described. If Leu-enkephalin (Leu-Enk) is used in the DESI solvent as an internal lock mass, ensure that the emitter should be cleaned with 95:5 methanol/water to remove any risk of crystallization of the Leu-Enk. Once the sprayer is reattached, leave for 30 min before attempting analysis. 3.5.2 Cleaning of the Ion Inlet Tube

1. Close the isolation valve and carefully remove the ion inlet tube from the ion block. 2. Remove the cone and O-ring using the cone extraction tool. 3. For a light clean, rinse through using water and methanol. Ensure that solvent go inside the tube. 4. For intensive clean, firstly sonicate the inlet tube in 50:50 acetonitrile/methanol +5% formic acid for 10 min, followed by a second sonication step in water for 5 min, and finish with a last 5 min sonication in methanol. Note: This does not apply to the HTL; see below for this procedure. 5. Dry under dry nitrogen stream.

3.5.3 Cleaning of the Heated Transfer Line (HTL)

1. Close the isolation valve and carefully remove the HTL from the ion block. 2. Remove the cone and O-ring using the cone extraction tool. 3. Rinse through with water and methanol. Ensure that solvent passes through the inlet tube (see Note 13). 4. Dry under dry nitrogen stream. 5. Allow to dry for at least 30 min before use.

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Notes 1. Solvent composition can vary depending on the analytes of interest and also the surface. For mammalian tissue sections, 95–98% aqueous methanol solvent composition is a good starting point to analyze metabolites and lipids, for either negative or positive mode. 0.1% formic acid can be added to the solvent for positive mode. 2. The use of an internal lock mass is recommended to generate high mass accuracy data, especially when the data is acquired using a SELECT SERIES MRT mass spectrometer. An example of an internal lock mass is Leu-enkephalin (Leu-Enk) in the DESI solvent at 50–200 pg/μL.

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3. Solvent delivery needs to be stable. Any fluctuation may cause signal instability, which will subsequently be reflected in the ion images. Re-filling the syringe in the middle of a DESI imaging experiment will affect the spray and therefore the quality of the ion images. With the mass spectrometer internal fluidics, the syringe volume options are 250 or 500 μL, limiting the length of time to acquire one experiment. Using an external syringe pump and a 1 mL syringe allows a DESI imaging experiment to last for 11 h at 1.5 μL/min flow rate. Ideally the use of nanoLC pump such as uBSM/ASM allows stable solvent delivery at 1–2 μL/min for weeks/months. 4. When ready to begin the imaging study, take the glass slide with the tissue section mounted from the cryostat if freshly sectioned or the -80 °C freezer. Let it defrost at room temperature (optionally under nitrogen gas or in vacuum desiccator for up to 30 min). 5. To determine if the system is operational and to obtain suitable starting position for the optimization on tissue, draw a large rectangle on a glass slide with a red Sharpie containing Rhodamine 6G dye (m/z 443.2335) for positive mode analysis or black permanent marker Staedtler Lumocolor, black ink (m/z 666.0600) for negative mode. The high desorption/ionization efficiency of these ink samples allows for a preliminary check that the system is operational. Due to the very different nature of these surfaces, it should not be assumed that a setup which yields the greatest signal for the ink will be the optimal conditions for the tissue sections under investigation. 6. With the HP DESI sprayer, small change (less than 0.1 kV) in voltage can have a drastic effect on the spray and therefore the signal intensity; therefore, the optimization of this parameter should be done with care. 7. This optimization step needs only to be carried out in full on first installation or after changing the emitter in the sprayer or if a completely different sample type is to be analyzed. 8. HTL temperature vs. signal intensity profile on the class of molecules. See Figs. 9 and 10.

Fig. 9 HDI/MassLynx DESI IMS workflow. (Printed with permission by Waters)

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Fig. 10 Normalized signal intensity vs. HTL temperature for (a) positive ionization mode phospholipids, (b) positive ionization mode glycerides, and (c) negative ionization mode phospholipids. (Printed with permission by Waters)

For small molecules, especially labile compounds, the HTL is run at room temperature. 9. The thin film polyalanine sample can be used for the MS calibration in positive and negative ionization mode. The sample is stable for months. 10. The fiducial points for co-registration of the optical image are the four glass slide corners, so they need to be present in the optical image. 11. DESI XS source mounted on Xevo G2-XS, Xevo G3, and SYNAPT XS uses HDI software to set up the DESI MSI experiments. DESI XS source mounted on SELECT SERIES Cyclic IMS and MRT mass spectrometers uses the tune page of the MassLynx Quartz software to set up DESI MSI experiments. 12. Using HDI workflow, processing parameters can be defined before the acquisition, and therefore, the processing step is automatically performed following the acquisition. 13. Do not sonicate or immerse the HTL in liquid. References 1. Takats Z, Wiseman JM, Gologan B, Cooks RG (2004) Mass spectrometry sampling under ambient conditions with desorption electrospray ionization. Science 306(5695):471–473 2. Friia M, Legros V, Tortajada J, Buchmann W (2012) Desorption electrospray ionization orbitrap mass spectrometry of synthetic polymers and copolymers. JMS 47:1023–1033 3. Chen H, Talaty NN, Takats Z, Cooks RG (2005) Desorption electrospray ionization mass spectrometry for high-throughput analysis of pharmaceutical samples in the ambient environment. Anal Chem 77:6915–6927

4. Manicke NE, Nefliu M, Wu C, Woods JW, Reiser V, Hendrickson RC, Cooks RG (2009) Imaging of lipids in atheroma by desorption electrospray ionization mass spectrometry. Anal Chem 81:8702–8707 5. Bereman MS, Williams TI, Muddiman DC (2015) Carbohydrate analysis by desorption electrospray ionization fourier transform ion cyclotron resonance mass spectrometry. Anal Chem 79:8812–8815 6. Takats Z, Wiseman JM, Ifa DR, Cooks RG (2008) Desorption Electrospray Ionization

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(DESI) Analysis of Tryptic Digests/Peptides CSH/ Protocol, prot4993 7. Takats Z, Wiseman JM, Ifa DR, Cooks RG (2008) Desorption Electrospray Ionization (DESI) Analysis of Intact Proteins/Oligopeptides CSH Protocol, prot4992 8. Tamura K, Horikawa M, Sato S, Miyake H, Setou M (2019) Discovery of lipid biomarkers correlated with disease progression in clear cell renal cell carcinoma using desorption electrospray ionization imaging mass spectrometry. Oncotarget 10(18):1688–1703 9. Guenther S, Muirhead LJ, Speller AVM, Golf O, Strittmatter N, Ramakrishnan R, Goldin RD, Jones EA, Veselkov K, Darzi A, Takats Z (2015) Spatially resolved metabolic phenotyping of breast cancer by desorption electrospray ionization mass spectrometry. Cancer Res 75:1828–1837

10. Kertesz V, Van Berkel GJ (2008) Improved imaging resolution in desorption electrospray ionization mass spectrometry. Rapid Commun Mass Sp 22:2639–2644 11. Gurdak E, Green FM, Rakowska PD, Seah MP, Salter TL, Gilmore IS (2014) VAMAS Interlaboratory Study for Desorption Electrospray Ionization Mass Spectrometry (DESI MS) Intensity Repeatability and Constancy. Anal Chem 86:9603–9611 12. Schwartz SA, Reyzer ML, Caprioli M (2003) Direct tissue analysis using matrix-assisted laser desorption/ionization mass spectrometry: practical aspects of sample preparation. JMS 38:699–708 13. Honarvar E, Venter AR (2018) Comparing the Effects of Additives on Protein Analysis Between Desorption Electrospray (DESI) and Electrospray Ionization (ESI). JASMS 29: 2443–2455

Chapter 5 Liquid Extraction Surface Analysis Mass Spectrometry Imaging of Denatured Intact Proteins Emma K. Sisley, James W. Hughes, Oliver J. Hale, and Helen J. Cooper Abstract Liquid extraction surface analysis (LESA) is an ambient surface sampling technique that can be coupled with mass spectrometry (MS) to analyze analytes directly from biological substrates such as tissue sections. LESA MS involves liquid microjunction sampling of a substrate by use of a discrete volume of solvent followed by nano-electrospray ionization. As the technique makes use of electrospray ionization, it lends itself to the analysis of intact proteins. Here, we describe the use of LESA MS to analyze and image the distribution of intact denatured proteins from thin fresh frozen tissue sections. Key words Intact proteins, LESA, Liquid extraction surface analysis, Mass spectrometry imaging, Tissue imaging, Ambient ionization

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Introduction Direct analysis of molecules from biological substrates is enabled by ambient ionization techniques, many of which may be operated in mass spectrometry imaging (MSI) modes. Liquid extraction surface analysis (LESA) [1] is one such technique and has proven versatile for in situ analysis of intact proteins, for example, those extracted from fresh frozen tissue, bacteria, and dried blood spots [2–5]. Although intact proteins are typically more challenging to analyze by mass spectrometry than proteolytic peptides, owing to their higher mass and complex fragmentation spectra, there are compelling reasons to study these molecules. Analysis of intact proteins allows identification of proteoforms including splice variants and single nucleotide polymorphisms, as well as providing a more complete picture of post-translation modifications and their connectivity, information not available from protein digests. LESA is performed by use of the Triversa NanoMate (Advion) robotic sample handling platform and first involves the collection of a small volume (typically ~5 μL) of extraction solvent from a solvent

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well into a pipette tip by the robot [1]. The pipette tip moves to a position above the sample, which is mounted on the robot’s sample bed, and a liquid junction is formed between the pipette tip and the sample by ejection of a (major) fraction of the solvent. A variant of LESA, known as contact LESA [2], in which the pipette tip is brought into contact with the substrate, may also be used. In mass spectrometry imaging experiments, contact LESA may be used to improve spatial resolution, a consequence of the decreased solvent spread. Whether standard or contact LESA, the liquid junction is maintained for a few seconds to allow analytes to be dissolved. The sample is drawn back into the pipette tip, which is then aligned with a chip-based nanoelectrospray ionization (nESI) nozzle. On application of a high voltage, analyte molecules are ionized by nESI for analysis in the mass spectrometer. By sequential sampling of locations across the sample surface in a grid-like pattern and subsequent analysis of the extract, a map of analyte distribution can be constructed (see Fig. 1). The commercialized implementation of LESA, i.e., the Triversa NanoMate, uses pipette tips with an outer diameter of 600 μm allowing for low-resolution ion maps to be generated. LESA takes advantage of nESI to generate multiply charged intact protein ions which are compatible with the m/z range of high-performance mass spectrometers, e.g., Orbitrap and QTOF [6–7]. In this chapter, we describe the workflow for mapping the distribution of proteins under denaturing conditions using LESA coupled to a hybrid Orbitrap mass spectrometer.

Fig. 1 (a) LESA uses a pipette tip to sample discrete locations across a sample. The sampled area is represented by the orange circles. (b) Each analyzed location results in a mass spectrum and represents one pixel in the ion image. Ion images can be generated for specific m/z values

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2.1 Tissue Sample Preparation

1. Tissue sample (organ or block) (see Note 1). 2. Liquid nitrogen or dry ice-chilled isopentane. 3. Cryostat for tissue sectioning. (We use the Leica CM1810.) 4. Glass microscope slides, uncoated. 5. (Optional) Washing solution. 80% EtOH(aq) made up from mass spectrometry-grade solvents.

2.2

LESA Solvents

1. Mass spectrometry-grade solvents, 40% acetonitrile/60% water with the addition of 1% formic acid (see Note 2).

2.3

Analysis

1. Triversa NanoMate ion source (Advion) controlled by ChipSoft software with the LESA license. 2. Triversa NanoMate mounting bracket for Thermo NG mass spectrometers (Advion part number BRK212). 3. Epson Perfection V370 Photo scanner. 4. Orbitrap Eclipse Tribrid mass spectrometer (Thermo) controlled by Orbitrap Eclipse Instrument Control Software (ICS, v3.3 and higher). The method described here is for this mass spectrometer but is generally applicable to all Orbitrapbased Thermo NG mass spectrometers. Some settings will not be available on all platforms.

3

Methods

3.1 Preparation of Tissue Sample

1. Tissue samples should be flash frozen as soon as possible after dissection by submerging the tissue in either liquid nitrogen or dry ice-chilled isopentane (see Note 3). Frozen tissue should be stored at -80 °C until use. 2. Prepare the cryostat for tissue sectioning by adjusting the cryostat temperature to approximately -20 °C. Place the tissue inside the cryostat. Place the chuck in the cryostat and allow it to cool. Dispense a small droplet of pure (analytical grade) water onto the center of the cooled chuck and quickly place the tissue onto the droplet using tweezers, orientating the tissue as desired for cutting. The low temperature of the chuck and the tissue will cause the water to rapidly freeze and adhere the tissue to the chuck. Allow the tissue to warm to the cryostat temperature (-20 °C) (see Note 4). 3. Ensure the mounting plate has been moved to the rear of the device such that there is sufficient distance between the blade and the mounting plate to affix the chuck. Take care around the

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exposed blade. Place the chuck in the mounting plate and tighten. If the mounting plate allows the angle of the chuck to be adjusted, it can be helpful to adjust the tissue to find a suitable cutting face. 4. Move the cutting plate forward until the tissue is close to the blade but without bringing the tissue and blade into contact. Set the cutting distance as desired. 20 μm can be used to “rough cut” the tissue to create a larger cutting face. When rough cutting, there is no need to use the anti-roll plate, and excess cut tissue can simply be removed. 5. Rotate the cutting handle in a smooth continuous manner taking approximately 1 s to complete the motion. 6. To cut tissue samples for imaging experiments, set the cutting thickness to 10 μm and lower the anti-roll plate. Rotate the cutting handle as described in step 5. 7. Use a fine paint brush to detach tissue from the razor blade and position it as desired on the cutting stage. A larger, coarse paint brush can be used to remove debris from the razor blade before the next cut. 8. To thaw mount the tissue, take a clean room temperature glass slide and slowly lower the slide onto the tissue section while keeping the slide and the cutting stage parallel such that the whole tissue section comes into contact with the glass simultaneously. Do not apply pressure to the tissue section with the slide. 9. Tissue washing to remove interfering salts, lipids, and other biological chemical contaminants may be performed by submerging the slide-mounted tissue section in a solvent well. The choice of solvent for washing will depend on the desired analyte. Submersion in 80% EtOH(aq) for 10 s and then leaving to air dry is a simple method for the removal of lipids. 3.2 Liquid Extraction Surface Analysis

1. Position the sample slide on a LESA universal adapter plate. 2. Scan the mounted slide on a photo scanner using 600 dpi, and load the resulting digital image into the LESA Points software following the import wizard steps (see Note 5). 3. Using the grid function, with the spacing set to 1 mm, select the desired sampling location on the tissue using the LESA Points software (see Note 6). 4. In ChipSoft, make sure LESA is selected under the “interface settings” tab. Then, under the “method manager” tab, set up a LESA method. A good starting method is as follows: solvent volume 4.0 μL, depth 0.6 mm, dispense volume 1.5 μL, delay (dispense) 25 s, reaspirate 2.0 μL, repeat mix 0, and delay (aspirate) 1 s. The ESI voltage should be set to ~1.7 kV and

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the gas pressure to 0.3 psi. The duration of the method should be set to ~2.5 min. Define the solvent reservoir location. Define contact closure settings for the Triversa NanoMate. Save this method. The above method is a “contact” sampling method (see Note 7). 5. In the LESA Points software, highlight all the sampling points in the right-hand panel (right click, select all), and then add the saved LESA method from ChipSoft to each of the sampling points (right click, add method, and then add your saved method file). Save this as a sequence file. 6. Open the saved sequence file in the ChipSoft software in the sequence tab. 3.3 Mass Spectrometry

1. Position the LESA plate adapter in the Triversa NanoMate sample bed with arrows pointing toward the chip holder. 2. Load a nESI chip into the chip holder and select the correct chip in ChipSoft (if not already loaded). 3. Add approx. 1 mL extraction solvent to the PEEK reservoir specified in the LESA method. 4. Define the mass spectrometer method in the Orbitrap Eclipse Tune software or within the Xcalibur module “Instrument Setup” software. Table 1 provides a guideline for MS settings (see Note 8). 5. Acquire data per sampled location.

Table 1 Optimized mass spectrometer settings for LESA mass spectrometry imaging of denatured proteins Polarity

Positive

IRM pressure

Standard (default = 8 mTorr)

Mode

Intact protein

Mass analyzer

FTMS (Orbitrap)

Mass range

600–2000 m/z

Resolution

120,000

Scan type

Normal

Microscans

1

Max injection time

100 ms

AGC target

1250%

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(a) Automatic acquisition: the Triversa NanoMate must be connected to the contact closure connection on the mass spectrometer as per the manufacturers’ guidance. (i) Write and save a sequence in Xcalibur (Thermo) including the mass spectrometer method. (ii) In Xcalibur, set the mass spectrometer to begin the method on contact closure signal from the Triversa NanoMate. (iii) Submit the sequence, and the mass spectrometer will equilibrate and wait for contact closure signal. (iv) Start the sequence that was written in ChipSoft. Contact closure from the Triversa NanoMate will initiate the mass spectrometer method once sampling completes and ionization begins (see Note 9). (v) The sequence will run through all samples defined in ChipSoft. The mass spectrometer will wait for electrospray initiation after each sampling event before collecting data. (b) Supervised acquisition (useful when evaluating LESA method performance). (i) Load the mass spectrometer method in the Instrument Control Software or define mass spectrometer parameters manually. (ii) Initiate the Triversa NanoMate sequence in ChipSoft. (iii) Wait for ionization to begin and evaluate the protein signals. (iv) Initiate data recording. 6. Data files can be viewed using the Thermo Fisher FreeStyle data analysis software. Protein identification by top-down LESA mass spectrometry is beyond the scope of this chapter; however, a number of articles are available in the literature detailing this process including, for example [3, 5]. 3.4 Visualizing Mass Spectrometry Imaging Data

Each pixel in a LESA mass spectrometry imaging experiment is collected as an individual file comprised of multiple scans. Each data file must be processed to create a single sum spectrum per pixel. 1. Open each pixel in the FreeStyle software and select the chromatogram. 2. Select the “Workspace processing” tab from the ribbon. Select the sum icon, and in the dialog box labeled “Avg Range,” enter the start and end scan times, e.g., 0–2 min.

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3. Select the mass spectrum. Navigate to the “Workspace options” tab in the ribbon and click on the ion labeled “Exports.” Select “Write to. RAW” and save the spectrum. 4. Repeat this process for each pixel. 5. Convert each of the summed. RAW files into .mzML using ProteoWizard MSConvert (https://proteowizard.sourceforge. io/). 6. Convert the individual .mzML files into a .imzML file using . i m z M L c o n v e r t e r ( h t t p s : // c s . b h a m . a c . u k / ~ i b s / imzMLConverter/). 7. It is possible to visualize mass spectrometry imaging data in . imzML format using the vendor-neutral and free software packages, Spectral Analysis (https://github.com/AlanRace/ SpectralAnalysis/releases) or MSiReader (https://msireader. wordpress.ncsu.edu). User manuals and documentation accompany both software packages.

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Notes 1. Fresh frozen tissue (not formalin-fixed paraffin-embedded (FFPE) tissue) is recommended for the analysis of proteins by this method. The fixation cross-links the proteins making them difficult to extract, while the embedding material can interfere with the mass spectra. Optimal cutting temperature (OCT) compound, another embedding material, causes contamination of the mass spectra and should be avoided. 2. This solvent system is a good starting point for protein analysis, but other solvent systems may be used to tune the observed protein profile. 3. Chilled isopentane is preferable as it freezes the tissue more rapidly than liquid nitrogen reducing the incidence of tissue cracking. 4. If the water droplet freezes on the chuck before the tissue adheres, remove the chuck from the cryostat and allow the ice to melt. Dry the chuck and repeat the protocol. The optimal cutting temperature for different tissue types varies from -25 °C ± 5 °C. Typically, we use ~ - 24 °C for brain, kidney, and liver tissue. 5. If using the newer version of ChipSoft (ChipSoft X), the LESA Points software is no longer a standalone program and has been integrated into ChipSoft. 6. 1 mm spacing is recommended for “contact” LESA sampling, while 2 mm spacing is recommended for standard (non-contact) LESA sampling. Use of these spacings prevents oversampling of locations.

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7. For contact LESA sampling, the size of the sampled location is defined by the size of the pipette (~600 μm), but you need to make sure the dispense volume is not so large that it creates a leak (a dispense volume of up to ~2 μL works well). For traditional non-contact LESA sampling, the size of the sampled location is dependent on the volume of solvent dispensed and the height of the pipette from the sample. 8. It is important that the duration of the electrospray ionization is longer than or equal to the duration of the mass spectrometer method in order to keep the ChipSoft and Xcalibur sequences synchronized. 9. If the current readback from the chip is too high (> 1000 mA), the ESI chip has shorted, and the voltage in ChipSoft should be reduced. References 1. Kertesz V, Van Berkel GJ (2010) Fully automated liquid extraction-based surface sampling and ionization using a chip-based robotic nanoelectrospray platform. J Mass Spectrom 45:252– 260 2. Randall EC, Bunch J, Cooper HJ (2014) Direct analysis of intact proteins from Escherichia coli colonies by liquid extraction surface analysis mass spectrometry. Anal Chem 86:10504– 10510 3. Sarsby J, Martin NJ, Lalor PF, Bunch J, Cooper HJ (2014) Top-down and bottom-up identification of proteins by liquid extraction surface analysis mass spectrometry of healthy and diseased human liver tissue. J Am Soc Mass Spectrom 25:1953–1961

4. Griffiths RL, Dexter A, Creese AJ, Cooper HJ (2015) Liquid extraction surface analysis field asymmetric waveform ion mobility spectrometry mass spectrometry for the analysis of dried blood spots. Analyst 140:6879–6885 272 5. Kocurek KI, Stones L, Bunch J, May RC, Cooper HJ (2017) Top-down LESA mass spectrometry protein analysis of gram-positive and gramnegative bacteria. J Am Soc Mass Spectrom 28:2066–2077 6. Fenn JB, Mann M, Meng CK, Wong SF, Whitehouse CM (1989) Electrospray ionization for mass spectrometry of large biomolecules. Science 246:64–71 277 7. Wilm M, Mann M (1996) Analytical properties of the nanoelectrospray ion source. Anal Chem 68:1–8 278

Chapter 6 MALDI MS Imaging of Cucumbers Robert Bradshaw Abstract There are many different methodologies in the literature for the preparation of plant material for subsequent MALDI MSI analysis. This chapter overviews preparation of cucumbers (Cucumis sativus L.), with emphasis on sample freezing, cryosectioning, and matrix deposition. This should act as a representative example of sample preparation for plant tissue, and due to wide sample variation (e.g., leaves, seeds, and fruit) and analytes of interest, method optimization will be required for different samples. Key words MALDI MS, Mass spectrometry imaging, Matrix, Plant tissue, Cucumber

1

Introduction Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) is an advanced analytical technique that can determine molecular distribution within many different sample types. Plant tissue is diverse, and examples of MALDI MSI analysis of this sample type include leaves [1–4], seeds [5–7], and fruit [9– 11], each of which have many sample preparation variations. When considering fruit, there are diverse methodologies in the literature, including blotting of strawberries onto an appropriate substrate (removing the necessity to prepare tissue sections) [12], microtome sectioning of apples (200 μm) followed by sandpaper grinding to reduce thickness [10], embedding in 10% gelatin prior to freezing and cryosectioning of wolfberries (30 μm) [11], and cryosectioning of whole tomatoes (10 μm) [9]. There is also an array of options for MALDI matrix/solvent composition (both of which are selected based on the analyte of interest) and the matrix deposition methodology (spraying, sublimation, etc.). This chapter is focused on the cucumber (Cucumis sativus L.), which is a highly perishable fruit [13] with many domesticated varieties that differ in size, appearance, and flavor [14]. Importantly, for sample preparation considerations, the water content of

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cucumbers is high (~95%) [15]. Therefore, commercially sold cucumbers are typically wrapped in polyethylene (“shrink-wrap”) to prevent damage, water loss, and contamination. Ultimately, this helps to increase shelf-life and prevent food waste [11]. Although this chapter cannot provide an overview of all the variables that could be encountered for the preparation of plant tissue, the methodologies presented here could be transferred to different plant tissue types. The specific focus will be on sample freezing, cryosectioning, and matrix deposition.

2

Materials

2.1 Preparation of Cucumber Sections

1. Whole cucumber. 2. Substrate (A): glass microscope slides. 3. Substrate (B): ALUGRAM1 SIL G/UV254 pre-coated aluminum sheets. 4. Dry ice. 5. 100 mL glass beaker. 6. 1 L glass beaker. 7. Acetone. 8. TAAB double-sided carbon tape. 9. Clean scalpel. 10. Metal tweezers.

2.2 Matrix Deposition

1. Typical MALDI MS matrices: α-Cyano-4-hydroxycinnamic acid (α-CHCA). Sinapinic acid (SA). Dihydroxybenzoic acid (DHB). 9-Aminoacridine (9-AA). 2. Typical solvents Acetonitrile (ACN) 0.1–0.5% trifluoroacetic acid (TFA) in deionized water. Ethanol (EtOH). Methanol (MeOH). Acetone.

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Fig. 1 Schematic representation of the sample preparation protocol for cucumbers, including (a) cutting of whole cucumbers into 2 cm pieces, (b) sample freezing, and (c) cryosectioning and mounting onto an appropriate substrate

3

Methods

3.1 Cucumber Preparation

Due to the high-water content of cucumbers, snap freezing in liquid nitrogen can cause fracturing of the tissue; therefore, a slower freezing process using dry ice is employed to help maintain structural integrity and prevent contamination of the sample. A schematic representation of the full protocol is provided in Fig. 1. 1. Using a clean scalpel, cut the cucumber into 2 cm-thick pieces with a lateral cross section size which would be suitable for MSI on the instrument of choice. 2. Place the cucumber piece into the center of a clean 100 mL beaker using tweezers (see Note 1). 3. Cover the base of a 1 L beaker with dry ice to a depth of 3–5 cm (see Fig. 2a). 4. Place the 100 mL beaker inside the 1 L beaker (see Fig. 2b) and gradually pour acetone into the dry ice. This will speed up the transfer of temperature from the dry ice, freezing the cucumber (see Note 2). 5. Following freezing, use tweezers to transfer the cucumber into an appropriate storage vessel (e.g., petri dish or Falcon tube), and store at -80 °C. A frozen cucumber piece is shown in Fig. 2c. 6. Cryosection the cucumber piece at an appropriate thickness (see Note 3), and mount onto a glass slide or pre-prepared aluminum sheet (see Sect. 3.1). 7. Store the cryosectioned samples in a Falcon tube and transfer to -80 °C until ready for analysis.

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Fig. 2 Cucumber freezing protocol including (a) dry ice at a depth of 3–5 cm within the 1 L beaker, (b) the orientation of the cucumber and glassware, and (c) a frozen cucumber piece following application of the protocol

Fig. 3 A 40 μm cryosectioned cucumber piece on a glass slide (a) before and (b) after deposition of the MALDI matrix

8. Once removed from -80 °C, immediately transfer the sample to a vacuum desiccator for 5–10 min (see Note 4). An example of a cryosectioned cucumber piece is shown in Fig. 3a. 9. Attach the substrate to the MALDI plate holder according to manufacturer guidelines or using double-sided carbon tape. 3.2 Preparation of Aluminum Substrate

The choice of substrate for mounting the cucumber sections is dependent on the instrument being used for analysis. Glass slides are the conventional option, and they are suitable for this application, but an alternative is ALUGRAM1 SIL G/UV254 pre-coated aluminum sheets, which have been used previously for other sample types [16, 17]. They provide a conductive surface suitable for subsequent MS analysis and can be easily cut into appropriate sizes. A previously reported protocol for the preparation of aluminum sheets for MALDI MSI analyses remains mostly unchanged [18] but is reported below:

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1. Place the TLC plate onto a flat surface with the silica coating facing upward. 2. Deposit approximately 10 mL of acetone directly onto the silica. 3. Using absorbent tissue, gently rub the surface until the silica coating is removed. Avoid excessive manipulation of the aluminum sheets as they may bend (see Note 5). 4. Repeat steps 3 and 4 until the aluminum plate is devoid of any silica. 5. Clean both sides of the TLC plate thoroughly using approximately 10 mL of acetone. 6. Measure the aluminum plate for the size required and cut using a ruler and clean scalpel (see Note 6). 7. Once the sample has been prepared, the aluminum substrate can be attached to the MALDI target plate using double-sided conductive carbon tape. 8. Use the end point of a scalpel to ensure that the aluminum plate is completely secured to the MALDI target plate by pushing down around the entirety of the perimeter at 5 mm increments. 3.3 Matrix Deposition

A range of MALDI matrices have been previously employed for the analysis of plant tissue. Typical examples shown in the literature include sinapinic acid [1], 9-AA [9, 11], DHB [2–7, 9–11], and α-CHCA [8]. The selection of the MALDI matrix and solvent composition is dependent on the specific application required and the analytes of interest; therefore, optimization of this step is necessary.

3.3.1 Matrix Deposition: Spraying

The following protocol is written for the “Suncollect” autosprayer (SunChrom GmbH, Friedrichsdorf, Germany): 1. Fill the syringe with ACN and flush the capillaries for at least 30 min at a flow rate of 2 μL/min. 2. Prepare 1 mL of the matrix solution (e.g., 5 mg/mL α-CHCA in 70:30 ACN/0.1% TFA). 3. Remove ACN from the syringe and fill with the matrix solution. Flush the capillaries for a further 15 min (see Note 7). 4. Set the coordinates of the sample (perimeter and height). 5. Turn on the gas flow and spray the sample with a total of five layers at a flow rate of 2 μL/min using the “slow” raster setting. An example of a sprayed cucumber section is shown in Fig. 3b. 6. Remove matrix from the syringe and fill with ACN. Flush the capillaries for at least 30 min at a flow rate of 2 μL/min.

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Notes 1. Clean glassware and tweezers thoroughly with HPLC grade solvents prior to use. Position the cucumber piece in a manner which will allow sectioning from an area that has not had direct contact with the glassware. 2. Do not allow acetone to enter the 100 mL beaker, to avoid contamination and damage to the cucumber sample. The freezing time depends on the size of the piece of cucumber; a 2 cm piece should take ~2–3 min. 3. It has been determined that a cucumber section of ~40–60 μm will allow for structural integrity to be maintained. 4. Vacuum desiccation of the frozen sections will avoid the formation of aqueous droplets on the sample surface and therefore prevents lateral diffusion of the analytes when the sample thaws at room temperature. 5. Ensure that the surface underneath the TLC plate is clean, as any particulate could result in indentation or bending of the aluminum surface following the silica removal process. 6. Using scissors to cut the aluminum plate may result in upturned edges, whereas a scalpel produces a flatter finish to the plates. Once the initial scalpel cut has been made, take care to bend the plate back and forth at the cut line slowly, until it is separated. 7. Flushing for 15 min with the MALDI matrix ensures the capillaries are filled prior to spraying the sample. For the last 5 min, flush at a flow rate that will be used for the first layer on the sample (2 μL/min).

Acknowledgments The author would like to thank Anna Mirza, Dara McMorrow, Alaa Salime, and Phoebe Bray who have all contributed to the development of the protocols described in this chapter. References 1. Carmo L, Ribeiro D, Barbosa E et al (2021) MALDI-MSI method for the detection of large biomolecules in plant leaf tissue. J Plant Sci Phytopathol 5:058–061 2. Becker L, Carre´ V, Poutaraud A et al (2014) MALDI mass spectrometry imaging for the simultaneous location of resveratrol, Pterostilbene and Viniferins on grapevine leaves. Molecules 19:10587–10600

3. Dreisbach D, Petschenka G, Spengler B et al (2021) 3D-surface MALDI mass spectrometry imaging for visualising plant defensive cardiac glycosides in Asclepias curassavica. Anal Bioanal Chem 413:2125–2134 4. Pereira A, Auer A, Biedel L et al (2022) Analysis of Gliricidia sepium leaves by MALDI mass spectrometry imaging. J Am Soc Mass Spectrom 33:573–583

MALDI MS Imaging of Cucumbers 5. Gorzolka K, Ko¨lling J, Nattkemper T et al (2016) Spatio-temporal metabolite profiling of the barley germination process by MALDI MS imaging. PLoS One 11(3):e0150208 6. Sarabia L, Boughton B, Rupasinghe T et al (2018) High-mass-resolution MALDI mass spectrometry imaging reveals detailed spatial distribution of metabolites and lipids in roots of barley seedlings in response to salinity stress. Metabolomics 14:63 7. Gupta S, Rupasinghe T, Callahan D et al (2019) Spatio-temporal metabolite and elemental profiling of salt stressed barley seeds during initial stages of germination by MALDI-MSI and μ-XRF spectrometry. Front Plant Sci 10:1139 8. Taira S, Shimma S, Osaka I et al (2012) Mass spectrometry imaging of the capsaicin localization in the capsicum fruits. Int J Biotechnol Wellness Ind 1:61–65 9. Nakamura J, Morikawa-Ichinose T, Fujimura Y et al (2017) Spatially resolved metabolic distribution for unraveling the physiological change and responses in tomato fruit using matrixassisted laser desorption/ionization–mass spectrometry imaging (MALDI–MSI). Anal Bioanal Chem 409:1697–1706 10. Horikawa K, Hirama T, Shimura H et al (2019) Visualization of soluble carbohydrate distribution in apple fruit flesh utilizing MALDI–TOF MS imaging. Plant Sci 278:107–112 11. Zhao W, Zhang Y, Shi Y (2021) Visualizing the spatial distribution of endogenous molecules in wolfberry fruit at different development stages by matrix-assisted laser desorption/ionization

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mass spectrometry imaging. Talanta 234: 122687 12. Enomoto H, Kotani M, Ohmura T (2020) Novel blotting method for mass spectrometry imaging of metabolites in strawberry fruit by desorption/ionization using through hole alumina membrane. Foods 9:408 13. Dhall R, Sharma S, Mahajan B (2012) Effect of shrink wrap packaging for maintaining quality of cucumber during storage. J Food Sci Technol 49(4):495–499 14. Che G, Zhang X (2019) Molecular basis of cucumber fruit domestication. Curr. Opin. Plant Biol 47:38–46 15. Public Health Directorate (2013) Nutrient analysis of fruit and vegetables. https:// wwwgovuk/government/publications/nutri ent-analysis-of-fruit-and-vegetables Accessed 23 June 2022 16. Wolstenholme R, Bradshaw R, Francese S (2009) Study of latent fingermarks by matrixassisted laser desorption/ionisation mass spectrometry imaging of endogenous lipids. Rapid Commun Mass Spectrom 23:3031–3039 17. Bradshaw R, Denison N, Francese S (2016) Development of operational protocols for the analysis of primary and secondary fingermark lifts by MALDI-MS imaging. Anal Methods 8: 6795–6804 18. Bradshaw R (2021) MALDI Mass Spectrometry Imaging Profiling and Imaging Applied to the Analysis of Fingermarks. In: Cole L (ed) Imaging mass spectrometry – methods and protocols. Springer Nature, New York, pp 149–163. Methods mol. biol. 1618

Chapter 7 The Adaptation of the QV600 LLI Milli-Fluidics System to House Ex Vivo Gastrointestinal Tissue Suitable for Drug Absorption and Permeation Studies, Utilizing MALDI MSI and LC-MS/MS Chloe E. Spencer, Catherine J. Duckett, Stephen Rumbelow, and Malcolm R. Clench Abstract Careful formulation of pharmaceuticals for oral delivery is essential to ensure that the optimal amount of the active ingredient reaches its intended site of action. This chapter demonstrates how mass spectrometry can be used in conjunction with ex vivo tissue and an adapted milli-fluidics system to carry out a drug absorption study. MALDI MSI is used to visualize the drug within the small intestine tissue from the absorption experimentation. LC-MS/MS is used to complete a mass balance of the experiment and quantify the amount of drug that has permeated through the tissue. Key words Milli-fluidics system, Gastrointestinal, Pharmaceuticals, Transepithelial, Transendothelial electrical resistance

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Introduction The careful formulation of all pharmaceuticals is essential to ensure that the optimal amount of the active ingredient reaches its intended site of action. Particularly with the oral administration route, there are many obstacles in between administration and the intended target that can hinder the delivery of the active ingredient. The low gastric pH within the stomach can cause the drug to be released prematurely from the solid dosage form and, therefore, drastically reduces the amount of active ingredient that has reached the intended site of action, thereby diminishing the efficiency and effectivity of the drug [1, 2]. In addition to this, the presence of digestive and intestinal enzymes within the gastrointestinal (GI) tract can degrade certain drug classes before they reach the intended target [2, 3]. It is therefore crucial that drugs intended

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for oral delivery must be carefully formulated to ensure that the drug is absorbed and released at the correct time to ensure the correct dose has been administered. Before human consumption, the active ingredient and the formulated solid dosage form must be closely studied. There is considerable difficulty in replicating the human GI tract in vitro for the purpose of performing reliable drug absorption studies. In addition to the previously mentioned factors, the oral administration route includes multiple organs that differ in physiological structure as well as chemical environment which affect the rate of drug absorption. Parameters such as the gastric emptying rate vary between individuals as well as with food intake and the general health of an individual; this affects the time allowed for drug absorption and, thus, the amount of drug absorbed [4]. The fluctuating and, arguably, unpredictable changes that occur when moving through the GI tract present a host of challenges when attempting to model the GI tract. The most apparent GI model to overcome these challenges would be to utilize animals that closely resemble humans for drug absorption studies. In vivo and in situ animal models were at one time the most commonly used and widely accepted methods of studying drug absorption due to the similarity of the GI tract between select animals and humans. Animal testing is a practice that attracts much controversy due to obvious ethical reasons. It has since become decreasingly accepted by today’s society and a portion of the scientific community. The growing opposition to animal testing became evident when Directive 76/768/EEC from 1976 was replaced by Regulation (EC) No. 1223/2009 in 2013, which imposed an EU-wide ban on testing cosmetic products and ingredients on animals [5]. In addition, a marketing ban was enforced to prevent the promotion of products containing such ingredients. This movement (along with the high cost of and concerns about translation into humans from animal experiments) has undoubtedly influenced many research groups involved in fields other than cosmetics to develop viable models without the use of live animals. Cultured 2D cell lines are a well-established model for the study of drug permeation through membranes, with the human colon carcinoma (Caco-2) cell line being the gold standard for oral drug absorption studies [6, 7]. A major benefit to using the Caco2 cell models is that the data is highly reproducible and sports a high-throughput capability. Despite the cell line being highly reproducible, the culture of a monolayer of cells is a poor imitation of the several varying layers of cells found in the intestinal tissue of the human gut. The development of 3D cell culture addresses the limitation of the original 2D cell lines; the addition of a third dimension makes the model more physiologically relevant and, thereby, a more predictive tool. Regardless of the benefits provided by 3D cell culture models, 2D cell lines are still widely used due to

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the low cost and amount of comparative literature available due to decades of research. The most physiologically relevant model without the use of living animals would be ex vivo tissue. Ex vivo gut tissue is often used in combination with the Ussing chamber. The Ussing chamber allows drug absorption and permeation studies to be performed on a small piece of tissue; the viability of this tissue can be assessed throughout the experiment using built-in probes to measure transepithelial/transendothelial electrical resistance (TEER). The transition from tissue to cell culture can be a difficult shift for wellestablished research groups. The loss of structures (e.g., plicae circulares) and pathways that are known to be routes for enhancing drug absorption can mean that years of research is no longer directly comparable. However, advances in organoid development have created a strong rival to current animal tissue models. An organoid, in contrast to a simple 3D cell model, is a 3D model made from more than one type of organ-specific cells, giving the organoid a structure, which mimics tissue more closely. As with every model, however, organoids do come with their own limitations: organoid culture is very complex and therefore requires a higher level of knowledge and experience. Despite their physiological relevance, organoids lack inter-organ communication, although this issue can be addressed by the use of multi-organon-a-chip models [8]. Here we describe the adaption of the QV600 LLI milli-fluidics system (Kirkstall Ltd., York, UK) for the study of absorption of drugs in the GI tract using ex vivo porcine small intestine. For the quantification and imaging of the drug used in the absorption experiments, mass spectrometry was utilized. Mass spectrometry imaging (MSI) is ideal for the detection of small drug molecules in ex vivo tissue as it can simultaneously detect other compounds such as lipids and proteins commonly found in tissue [9, 10]. The use of MSI in an absorption experiment is particularly useful as it provides spatial information that allows us to visualize the distribution of the drug within the tissue. In addition to this, it is possible to stain the previously imaged tissue section and overlap the MS images with an optical image of the histological stain, thereby providing further information on where the drug has localized within the tissue. LC-MS/MS was used to complete a mass balance for the experiment and to quantify the amount of drug that had permeated through the tissue.

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Materials Unless otherwise specified, all reagents were of laboratory grade and purchased from Thermo Fisher Scientific (Loughborough, UK).

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QV600 LLI Setup

QV600 LLI kit from Kirkstall Ltd. (York, UK). 0.22 μm membrane syringe filters.

2.2 Fresh Tissue Collection

Cool bag. Ice packs.

2.3 Fresh Tissue Preparation

Two pairs of tweezers. Scalpel. Ice packs. Inner O-rings. Millicell inserts.

2.4 QV600 LLI Experiment Setup

Bottom circuit fluid: Gibco BenchStable DMEM/F12. Top circuit fluid: phosphate-buffered saline (PBS), atorvastatin calcium, and Super Refined Polysorbate (80) LQ.

2.5 Snap-Freezing Disks of Tissue from QV600 LLI

Isopentane. Liquid nitrogen.

2.6 LLI

Methanol and purified water. PBS.

Cleaning QV600

2.7 Cryosectioning Disks of Tissue

Cryo-M-Bed. Cork disks.

2.8 MALDI Matrix Application

2,5-Dihydroxybenzoic acid (DHB).

2.9 Preparation of Samples for LC-MS/ MS Analysis

HPLC grade methanol. Purified water. 1× PBS. DMEM/F12. HPLC grade acetonitrile. Formic acid. Atorvastatin-(anilide ringd5) calcium salt. Atorvastatin calcium.

2.10

Software

MALDI-MS imaging: HDI software. LC-MS/MS: Agilent MassHunter Quantitative Analysis version 8.09 software.

2.11

Instrumentation

MALDI MSI was performed on a Waters SELECT SERIES MRT mass spectrometer. LC-MS/MS experiments were performed on an Agilent 6420 Triple Quad mass spectrometer in negative ion mode with an Agilent Eclipse Plus C18 RRHD 1.8 μm, 2.1 × 50 mm column. Sublimation of MALDI matrix was performed on a Merck Ace vacuum-sublimation apparatus.

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Methods QV600 LLI Setup

1. Maintaining sterility, set up the QV600 LLI following the diagram shown in Fig. 1. 2. Ensure that the QV600 LLI apparatus is set up prior to collecting tissue.

3.2 Fresh Tissue Collection and Transport

1. Collect porcine small intestine from the nearest abattoir straight after removal from the animal. Make a note of the time that the animal was slaughtered. 2. Immediately seal the intestine into a plastic bag and place on ice inside a closed cool bag for transport.

3.3 Fresh Tissue Preparation and QV600 LLI Experiment Setup

1. Remove the intestine from the cool bag and place on ice under a flow hood. 2. Identify the relevant section of the small intestine. Cut away and dispose of any areas that are not needed. 3. Carefully cut the remaining intestine along its length to open the intestine into a flat sheet. 4. Cut a small (~5 cm × 5 cm) piece of tissue from the sheet and dispose of the rest. Ensure that there is no damage to the surface of the remaining tissue. 5. Place the remaining sheet of tissue on an ice block with the villi facing upward.

Fig. 1 A diagram showing how the QV600 LLI should be set up with three chambers in the system

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Fig. 2 (a) An optical image of the edge of duodenum small intestine tissue showing the natural separation of the muscle-serosal layer when in a cold environment. (b) An optical image of the muscle-serosal layer being stripped from the submucosal layer of the small intestine

Fig. 3 (a) An optical image of the small intestine tissue disk fitted into the insert taken from the aerial view showing the villi. (b) An optical image of the small intestine tissue disk fitted into the insert taken from underneath the insert showing the submucosal layer

6. Carefully remove the muscle-serosal layer from the tissue and dispose of this layer as shown in Fig. 2. 7. Use a 10 mm biopsy punch to remove a disk of tissue and place this into a Millicell insert with the villi facing upward as shown in Fig. 3. 8. Allow time for the basal layer of the tissue to adhere to the mesh within the insert before placing an O-ring into the insert on top of the tissue disk. The O-ring should seal the edges between the insert and the tissue disk as shown in Fig. 4. 9. Add an additional O-ring to the outside of the insert.

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Fig. 4 (a) An optical image of the small intestine tissue disk fitted into the insert with an internal O-ring taken from the aerial view showing the villi. (b) An optical image of the small intestine tissue disk fitted into the insert with an internal O-ring taken from underneath the insert showing the submucosal layer

10. Fill the bottom circuit reservoir with 30 mL of a nutritional solution such as DMEM/F12. Remove some of the solution and add a small amount to the bottom of each chamber without exceeding the first level of tubing. 11. Individually position each insert containing tissue into a chamber ensuring that the outer O-ring sits in between the top and bottom circuit tubing. 12. Once fitted, add 30 mL of pre-prepared top circuit solution to the relevant reservoir. Remove some of this solution and fill the insert in each chamber. The top circuit solution is largely 1× PBS with the relevant drug and excipient added. 13. Close the system and temporarily remove the air filter from the bottom circuit reservoir. Move the bottom circuit reservoir to a position lower than the QV600 LLI apparatus. 14. Turn the peristaltic pump on and set the speed to create a flow rate in the top circuit that is at least double that of the bottom circuit ensuring a positive driving force. 15. Angle the chambers while filling the system to prevent the formation of bubbles in the bottom circuit. 16. Once the system is filled, fit the air filter onto the bottom circuit reservoir and leave at a position lower than the rest of the apparatus. 17. Move the entire system, including the peristaltic pump, into an incubator set at 37 °C for the desired amount of time.

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3.4 Stopping the Experiment and Emptying the QV600 LLI

1. At the end of the experiment, turn the peristaltic pump off. 2. Collect the fluid from the reservoir and offset the lid so that the output tube will empty into the collected fluid and the input tube will pull in air. 3. Turn the pump back on with higher flow rates while maintaining a higher pressure in the top circuit. 4. Tilt the chambers to fully empty the bottom circuit and collect the remaining fluid (sample name = acceptor circuit). 5. Repeat this for the top circuit (sample name = donor circuit). 6. After the top and bottom circuits have been emptied, remove the Millicell insert and place the insert into a vial of 1× PBS. 7. Use tweezers to carefully remove the tissue disk from the insert without damaging the tissue. 8. Rinse the tissue in 1× PBS and collect the solution (sample name = tissue rinse). 9. Repeat for each tissue disk used. Immediately after rinsing the tissue disks, follow step 3.5.

3.5 Snap-Freezing Disks of Tissue from QV600 LLI

1. Individually place each tissue disk into a plastic weighing boat and submerge in isopentane. 2. Ensure the tissue disk is flat before snap-freezing in liquid nitrogen. 3. Once fully frozen, place the tissue disk in a bijoux tube and vacuum seal. 4. Store at -80 °C immediately.

3.6 LLI

Cleaning QV600

1. Remove both air filters from the reservoirs. 2. Under a flow hood, attach a syringe filled with 70% methanol to a luer connector on the top circuit. 3. Force the solution through the tubing to clear any of the remaining drug solution. 4. Collect the solution by emptying the reservoirs and repeat until the system is analytically clean, alternating between the top and bottom circuit. 5. Clear the system of any remaining solvent and collect (sample name = initial system rinse). 6. Flush the system with sterile 1× PBS and collect the liquid (sample name = final system rinse). 7. Replace the air filters on both reservoirs and close the system before removing from the flow hood to store empty. 8. Collect all solutions used for LC-MS/MS analysis and store at 4 °C.

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Fig. 5 An optical image of a section of intestinal tissue with the muscle/serosal layers removed scanned using a Super CoolScan 5000 ED Film Scanner. Orientated with the apical layer at the top and the submucosal layer at the bottom 3.7 Cryosectioning Disks of Tissue

1. Set the chamber and specimen head of the Leica CM 1950 Cryostat to 20 °C. 2. Place the frozen tissue disk into the cryostat and allow 1 h for acclimatization. 3. Use a mounting medium (Cryo-M-Bed embedding compound) to fix the tissue disk to a cork ring in the correct orientation. 4. Avoid contaminating sections with any mounting medium. 5. Cut 14 μm cryosections from the tissue disk and thaw mount onto a suitable microscope slide. See Fig. 5 for an example of the correct orientation of tissue. 6. Collect a few sections per slide. 7. Vacuum pack the sections and store at -80 °C until needed.

3.8 MALDI Matrix Application

1. Add 19 mg of DHB into the bottom of the sublimation apparatus. 2. On the underside of the top section of the sublimation apparatus, secure the microscope slide containing the relevant tissue section. 3. Assemble the top and bottom of the sublimation apparatus and switch the vacuum on to secure both pieces together. 4. Fill the top of the sublimation apparatus with ice. 5. Once the pressure has reached ~5 × 10-2 Torr, place the sublimation apparatus in a glass dish containing sand that has been heated to 180 °C via a hotplate.

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6. Stop the sublimation process after 15 min. 7. Retrieve the glass slide ready for MALDI MS imaging. 3.9 MALDI MS Imaging

1. Insert the tissue sections into a Waters MRT mass spectrometer and calibrate the instrument before imaging with a suitable calibrant. 2. Set the instrument to positive ion mode with a focus on the mass range m/z 100–1500 Da. 3. Within the same batch, acquire an image of each whole tissue section with a spatial resolution to 25 μm × 25 μm. 4. After imaging, process the image in HDI software. 5. Set the image to total ion count (TIC) and identify the expected drug peaks in addition to any peaks that relate to and highlight important structures within the tissue structure. See Fig. 6. 6. Use the software to overlay these ion images to clearly show the spatial distribution of the drug within the tissue section. See Fig. 7.

3.10 Preparation of Samples for LC-MS/ MS Analysis

1. Make a note of the weight of each tissue disk and measure the volume of each sample collected. 2. Add 30 mL of methanol/water (9:1, v/v) to each tissue disk separately and homogenize the tissue. 3. Separately add the donor circuit, acceptor circuit, tissue rinse, and final system rinse samples 50:50 v/v to methanol/water (9:1, v/v). 4. Centrifuge all samples for 5 min at 3000× g and collect the supernatant for LC-MS/MS analysis.

Fig. 6 A MALDI MS image showing protonated atorvastatin (m/z 559) in green, m/z 369 in red, m/z 825 in purple, and m/z 688 in light blue

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Fig. 7 The MALDI MS image from Fig. 6 aligned and overlaid with the optical image from Fig. 5. The image shows protonated atorvastatin (m/z 559) in green, m/z 369 in red, m/z 825 in purple, and m/z 688 in light blue

5. Prepare a 50 μg/mL atorvastatin stock solution made up with methanol/water (9:1, v/v). Using the stock solution, prepare seven matrix-matched standards (including a blank) with the concentration ranging from 0 to 10 μg/mL. 6. Prepare a 0.02 mg/mL atorvastatin stock solution made up with Gibco BenchStable DMEM/F12. Dilute the stock solution 50:50 with methanol/water (9:1, v/v). Using the new stock solution, prepare seven matrix-matched standards (including a blank) with the concentration ranging from 0 to 1 μg/mL. 7. To all standards and samples prepared, add the internal standard, Atorvastatin-d5, to give a concentration of 2.5 μg/mL. 8. All LC vials must be matrix matched accordingly. 3.11

LC-MS/MS

1. Set the analyzer to detect the product ion of atorvastatin calcium salt (m/z 557 -> m/z 453) and Atorvastatin-d5 calcium salt (m/z 562 -> m/z 458) in multiple-reaction monitoring (MRM) mode. 2. Use a mobile phase consisting of water/ACN/methanol (41: 19:40, v/v/v) with 0.005% formic acid and a needle wash consisting of water/ACN/methanol (41:19:40, v/v/v). 3. Set the flow rate to 0.275 mL/min and the column oven temperature to 45 °C. Run all standards and samples in triplicate. 4. Process the raw LC-MS/MS data with the Agilent MassHunter Quantitative Analysis version 8.09 software to integrate the chromatographic peaks and create a calibration curve for each type of sample.

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5. Back-calculate to establish the amount of drug in each sample. 6. Complete the mass balance calculation below to establish whether an acceptable amount of the drug has been recovered and quantified; the acceptable range is between 85% and 115%. Mass balance ð%Þ =

4

Amount of drug recovered × 100 Amount of drug originally added

Notes 1. It is essential that for the QV600 LLI to be used in a successful drug absorption experiment, there should be a positive driving force from the top to the bottom circuit. 2. When setting up and running the QV600 LLI for the purpose of a drug absorption experiment, there must be no mixing of the top and bottom circuit fluids. The two circuits must be completely separated by the tissue disk. 3. The tissue can be previously frozen or fresh and viable. Ensure that the drug chosen is suited to the state of the tissue. 4. The viability of the tissue used should be established taking into account the desired experiment duration, travel conditions, and type of tissue.

References 1. Qiu Y, Chen Y, Zhang G, Yu L, Mantri R (2017) Developing solid Oral dosage forms. Mica Haley 2. Homayun B, Lin X, Choi H (2019) Pharmaceutics 11:129. https://doi.org/10.3390/ pharmaceutics11030129 3. Werle M, Bernkop-Schnu¨rch A (2008) J Pharm Pharmacol 60:273–281. https://doi.org/10. 1211/jpp.60.3.3001 4. Stillhart C, Pepin X, Tistaert C, Good D, Van Den Bergh A, Parrott N, Kesisoglou F (2019) AAPS J 21:1–13. https://doi.org/10.1208/ s12248-019-0292-3 5. Russo C, Lewis EEL, Flint L, Clench MR (2018) PROTEOMICS 18:e1700462. https://doi.org/10.1002/pmic.201700462 6. Berben P, Bauer-Brandl A, Brandl M, Faller B, Flaten GE, Jacobsen A, Brouwers J, Augustijns

P (2018) Eur J Pharm Sci 119:219–233. https://doi.org/10.1016/j.ejps.2018.04.016 7. Dahlgren D, Lennern€as H (2019) Pharmaceutics 11:411. https://doi.org/10.3390/ pharmaceutics11080411 8. Picollet-D’hahan N, Zuchowska A, Lemeunier I, Le Gac S (2021) Multiorganon-a-Chip: A systemic approach to model and decipher inter-organ communication. Elsevier BV 9. Karlsson O, Hanrieder J (2017) Arch Toxicol 91:2283–2294. https://doi.org/10.1007/ s00204-016-1905-6 10. Tobias F, Hummon AB (2020) J Proteome Res 19:3620–3630. https://doi.org/10.1021/ acs.jproteome.0c00443

Chapter 8 Ambient Mass Spectrometry Imaging by Water-Assisted Laser Desorption/Ionization for Ex Vivo and in Vivo Applications Nina Ogrinc, Paul Chaillou, Alexandre Kruszewski, Cristian Duriez, Michel Salzet, and Isabelle Fournier Abstract Water-assisted laser desorption/ionization mass spectrometry (WALDI-MS), also known as SpiderMass, is an emerging ambient ionization technique for in vivo and real-time analysis. It employs a remote infrared (IR) laser tuned to excite the most intense vibrational band (O-H) of water. The water molecules act as an endogenous matrix leading to the desorption/ionization of a variety of biomolecules from tissues, particularly metabolites and lipids. WALDI-MS was recently advanced into an imaging modality for ex vivo 2D sections and 3D in vivo real-time imaging. Here, we describe the methodological aspects for performing 2D and 3D imaging experiments with WALDI-MSI and the parameters for optimizing the image acquisition. Key words Mass spectrometry imaging, Ambient ionization mass spectrometry, In vivo, 3D, Robotics, Topography

1

Introduction In the last two decades, several mass spectrometry (MS) systems have developed which has expanded the application of MS in the fields of biology and clinics by providing gross tissue analysis with minimum or no sample preparation. These systems form a class of their own so-called ambient ionization mass spectrometry (AIMS) [1–3]. Some of these AIMS technologies have even been designed for translational clinical research targeting intraoperative analysis including a few that suit in vivo analysis and real-time diagnostics [4–8]. The water-assisted laser desorption ionization (WALDI) by SpiderMass was introduced in 2014 for in vivo and real-time microinvasive analysis [7, 9, 10]. The SpiderMass system is composed of laser source based on an OPO (optical parametric oscillator) coupled to a Nd:YAG pump with accordable wavelength providing 6 ns

Laura M. Cole and Malcolm R. Clench (eds.), Imaging Mass Spectrometry: Methods and Protocols, Methods in Molecular Biology, vol. 2688, https://doi.org/10.1007/978-1-0716-3319-9_8, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2023

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pulse duration. The wavelength is set to 2.94 μm which excites the most intense vibrational band (O-H) of water. The water acts as an endogenous matrix leading to the water-assisted laser desorption/ ionization process. The OPO is fibered and the laser beam exiting from the OPO is thus injected in an optical fiber ending in a handheld. In the used condition (wavelength, fluence, and pulse duration), the laser beam is micro-invasive (limited penetration depth) allowing for fast screening along the tissue. Because the analysis doesn’t require contact of the laser probe with the tissue and the handpiece is positioned a few centimeters away from the surface, contamination with the tissue is avoided. The resulting desorption plume is aspirated via a polymer-based biocompatible tubing (1.5–5 mm OD), which is placed just above the analyzed tissue. The system is coupled to a Q-TOF mass analyzer (XEVO G2Si, Waters) equipped with a custom-made REIMS interface [9]. Typically, the MS spectra generated by the direct analysis of a biological tissue consist of lipid and metabolite species in both positive and negative ion modes. Despite the SpiderMass system has been developed fro in vivo and real-time applications in oncology, it can be applied to a variety of different research areas in biology and clinics such as plant biology, dermatology, food safety, bacterial typing, toxicology, forensics, and drug pharmacokinetics. The SpiderMass system has been successfully applied to analyze ex vivo ovarian cancer biopsies and in vivo human skin, genetically modified macrophage cell lines, bacterial biotyping, and intact proteins in solution [7, 11, 12]. The SpiderMass was also tested on ex vivo samples of a dog sarcoma biopsy cohort, and multivariate statistical analysis allowed for the correct classification (97% of specificity) of tumor type and grading. Furthermore, the system has demonstrated its applicability in vivo during surgery in a veterinary surgery room [13]. Recently it has also demonstrated its applicability for the analysis of unprocessed FFPE samples [14] and classification of sarcoma [14] and oral squamous cell carcinoma [15] and even in vivo on cannabis leaves [16]. The system was further developed for imaging, capable of acquiring 2D images from tissue sections as well as 3D topographical direct postmortem and in vivo imaging [17]. As with other AIMS techniques, WALDIMS by SpiderMass does not require extensive sample preparation. SpiderMass MS Imaging was demonstrated on different model samples (piece of sponge, piece of apple, and a human skin disk), on rat brain tissue sections, and in vivo on a finger as well as inside of a body of a mouse postmortem [17]. These examples offer foresight into the next generation of in vivo molecular image guidance that will be used in a surgical room. However, depending on the sample type, several important factors need to be taken into consideration regarding the sample preparation and preparation for acquisition. In this chapter, we describe methods and protocols for carefully executing 2D analysis of frozen and FFPE tissue sections

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and fresh tissue pieces and 3D topographical in vivo MSI using WALDI-MSI, a new and upcoming ambient MSI technique.

2

Materials

2.1 Preparation of Snap Frozen Tissues 2.1.1

Snap Freezing

2.1.2 Tissue CryoSectioning

1. Liquid nitrogen (-196 °C) or isopentane cooled in liquid nitrogen. Use protective equipment when handling liquid nitrogen as it may cause burns. Vapors may cause drowsiness; therefore, working under the fume hood is advised. 1. Polylysine-coated glass slides or regular glass slides (Thermo Fisher Scientific cat. Num. 22–037-246). 2. Deionized water. 3. A cryo-microtome, Leica CM 1510S (Leica Microsystems, France).

2.2 Preparation of FFPE Tissue Sections

1. Polylysine-coated glass slides or regular glass slides (Thermo Fisher Scientific cat. Num. 22–037-246).

2.2.1

Tissue Sectioning

2. Water: 100 mL of water (HPLC grade). Prepare fresh.

2.2.2

Glycerol Deposition

1. 10 mL of 20% glycerol solution: 2 mL of glycerol (Laboratory reagent grade) and 8 mL isopropyl alcohol (IPA) (LC-MS grade).

3. A microtome and a hotplate warmed at 50 °C.

2. Manual sprayer Agilent CE ESI-MS. 3. The syringe pump (74,900 series, Cole-Parmer Instrument Company). 2.3 WALDI Mass Spectrometry Imaging Analysis

1. 1.5 m Tygon® ND 100–65 tube (2.4 mm inner diameter, 4 mm outer diameter, Saint-Gobain, France, VWR cat. Num. VERNADF00004, or Thermo Fisher Scientific cat. Num. 14–171-296). 2. OPO laser tunable between 2.8 μm and 3.1 μm (Radiant version 1.0.1, OPOTEK, Inc., Carlsbad, USA) pumped by a pulsed Nd:YAG laser (pulse duration 5 ns, λ = 1064 nm, Quantel, Les Ulis, France). 3. Biocompatible laser fiber (450 μm core diameter; 1 m; Infrared Fiber Systems, Silver Spring, USA). 4. Q-TOF Xevo Mass analyzer (Waters, Manchester, UK). 5. MassLynx v4.1 software (Waters, provided by the vendor). 6. Stiff 6D-axis precision MECA robotic arm (Mecademic, Montreal, Canada).

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7. Distance sensor composed of a laser optical displacement sensor ILD1320–25(Micro-Epsilon,France)andlaserpointerLED. 8. Home-built Matlab interface (Matlab v2020, Matlab, Inc.). 2.4

Data Analysis

1. MSConvert (ProteoWizard).

2.4.1 Image coRegistration

2. Home-built Matlab interface (Matlab v2020, Matlab, Inc.).

2.4.2 Data Processing with SCiLS

1. MSConvert (ProteoWizard). 2. imzML converter. 3. SCiLS software (SCiLS™ Lab 2021, MVA, Bruker).

3

Methods The methods described follow workflows adapted for ambient mass spectrometry imaging of small molecules (metabolites, lipids). WALDI-MSI can be performed directly on fresh samples (excised tissue, postmortem organs, or in vivo analysis) or cryo-preserved or formalin-fixed paraffin-embedded (FFPE) tissues (see Fig. 1). Since fresh tissues do not require any additional sample preparation, the first steps describe the preparation of fresh-frozen and FFPE tissue sections. FFPE tissues can be analyzed directly without any sample preparation or by coating the samples with a thin layer of 20% glycerol in IPA as previously described in order to compensate for tissue dryness [14]. Thus, this process will increase the desorption/ ionization efficiency of detected metabolite and lipid species from FFPE tissues. However, the coating must contain small droplets (lower than the ablation spot size) of uniform distribution (see Fig. 2). The droplets shouldn’t be larger than 100 μm. In the second part of the methods, we describe how to perform mass spectrometry imaging analysis for either 2D imaging of tissue sections or 3D in vivo/fresh tissue imaging. The imaging can be performed by using the home-built interface with two different modules: (i) automatized user interface and (ii) image reconstruction (see Fig. 3). The complete automatized user interface controls the hardware components such as the positioning of the robotic arm, laser firing, and mass spectrometry acquisition (see Fig. 3a). To start the 3D workflow, we first calibrate the distance sensor by measuring the distance between the LED and the center of the observed camera field. Then the investigated specimen is placed under the arm, and the coordinates (x, y, z) are recorded point by point at the desired step size to create the topographical image. The topography is used to correctly position the laser probe. In parallel, the mass spectrometry data is collected. The speed of analysis is dependent on the number of laser shots fired at the pixel position,

Ambient Mass Spectrometry Imaging by Water-Assisted Laser Desorption/Ionization. . . A

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Analysis

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500µm

2D imaging of tissue sections 500µm

250µm

Transfer tubing

250µm Laser Fiber

SCiLS

Adapter Microprobe

CameraLED

B

Height calibration

Real time 3D analysis

Data analysis

MECA-500 6-axis robot

3D topography and in vivo imaging of fresh samples Height (mm)

Fig. 1 Water-assisted laser desorption/ionization mass spectrometry imaging workflow for 2D and 3D topographical imaging. (a) The 2D imaging procedure contains step-by-step instructions from sample preparation to data processing of 2D tissue sections. Samples are first carefully prepared before analysis by sectioning in the cryostat or microtome at the desired thickness. In case of formalin-fixed paraffinembedded tissues, the slide can also be covered with the glycerol spray. After, the imaging is normally performed with 500 μm or 250 μm step size with oversampling using the home-built interface. Then, the data can be processed using the home-built interface to display the distribution at a specific m/z value or imported into commercially available SCiLS software. (b) The 3D topographical or in vivo imaging of fresh samples does not require any sample preparation. First, the distance sensor is well calibrated resulting in a linear calibration curve for the z-height detection increasing by 250 μm increments in the z-height. The sample is then directly placed underneath the sensor and SpiderMass probe for real-time analysis. The topographical and molecular data are acquired simultaneously. The mass spectrometry data is then plotted back to the topographical image using the home-built interface. (A part of the figure was reprinted with permission from Ogrinc et al. [17]. Copyright 2022 American Chemical Society)

waiting time, and step size. These can be adjusted accordingly. The pixel size is dependent on the laser spot size which is currently limited to 500 μm. The step size can be reduced to 250 μm by oversampling [18]. This is used to improve the spatial resolution (see Fig. 3b). The TIC intensities should reach at least 1e5 per pixel for good signal reproducibility. With the optimal setup of parameters, the acquisition speed can reach 1.7 pixels/s. The third part of the methods consists of ways to perform image reconstruction and data processing. The m/z values of interest are selected, and the images are reconstructed and displayed. Two-dimensional images can also be converted into imZML format [19, 20] and processed by commercially available software(e.g., SCiLS). Several examples are showninFig.4.SincetheWALDI-MSIcanproducecomplexmetabolite and lipid spectra, MS/MS experiments can be performed for

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A

B

D

With glycerol

No glycerol

With glycerol

No glycerol

With glycerol

Positive ion mode

No glycerol

C

Negative ion mode

E

G

F No glycerol

No glycerol

Glycerol

Glycerol

906.73 885.63

701.58 747.58

Fig. 2 Formalin-fixed paraffin-embedded (FFPE) sample analysis. In order to compensate for tissue dryness and increase the lipid detection by increasing the desorption/ionization efficiency, FFPE samples can be sprayed with 20% glycerol in IPA using the (a) manual sprayer. The manual sprayer is connected to a syringe pump and nitrogen gas. Glycerol spray deposition and droplet size after (b) two layers and (c) six layers. FFPE tissue optical and selected m/z images of the analyzed rat brain cerebellum in (d) positive ion mode with and without glycerol and (e) negative ion mode with and without glycerol. All images were acquired with 250 μm step size. Resulting overview spectra in (f) positive ion mode with and without glycerol and (g) negative ion mode with and without glycerol

structural elucidation. The MS/MS lipid spectra can be compared to librariessuchasLIPIDMAPS[21,22],METLIN[23],ALEX123[24], andMetFrag[25]toconfirmtheiridentification. 3.1 Preparation of Fresh Tissues

1. After dissection or surgical removal, the fresh tissues can be analyzed directly or snap frozen in liquid nitrogen. 2. When the tissues are well frozen, label and store them in -80 °C freezer until use.

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[PE (18:1/18:1)-H]-

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250 µm step size

Mapping selection

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Fig. 3 Image acquisition and data reconstruction. (a) An automatized user interface controls the hardware components such as the positioning of the robotic arm, laser firing, and mass spectrometry acquisition. Several imaging parameters can be selected such as: (i) The mapping step (500 μm or 250 μm) and imaging area. (ii) If performing 3D topographical imaging, the sensor must first be calibrated. (iii) Adjust the time between two pixels and the number of laser shots fired. (iv) Mapping selection (2D or 3D imaging). The images can be acquired and reconstructed at the desired spatial resolution at (b) 500 μm or (c) 250 μm with oversampling. The images at the selected m/z value can be reconstructed using the processing tab. The selected rat brain images are TIC normalized. (A part of the figure was adapted with permission from Ogrinc et al. [17]. Copyright 2022 American Chemical Society)

3. Thaw the tissues for 5 min prior to analysis. The analysis of fresh tissues doesn’t require sectioning. 3.2 Preparation of Fresh-Frozen Section 3.2.1

Snap Freezing

1. The organ is dissected and rinsed with a saline solution. This removes blood and other tissue fragments from the surface. Alternative: prior to killing, the animal can be perfused with the saline solution to remove blood inside the organ. After removal, put the fresh tissues into cryogenic tubes and snapfreeze them in liquid nitrogen. 2. Morphology of the organ needs to be carefully maintained. Thus, the tissue should not be placed in a tube or wrapped in an aluminum foil to avoid deformation of the organ (otherwise, it adapts to the outlines of the container). 3. Snap freezing procedures are applied for tissue preservation to maintain tissue morphology and to prevent ice crystal formation and cell explosion. In fact, different cooling rates for some parts of the organ or direct dipping of the organ into liquid nitrogen leads to the formation of cracks and fragmentation of

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Fig. 4 Examples of 3D topographical and in vivo mass spectrometry imaging. (a) In vivo topography MSI of the nail plate, cuticle, and skin. An optical and topographical image at 1 mm step as well as selected ion images at m/z 411.3 ± 0.1, m/z 505.3 ± 0.1, and m/z 803.6 ± 0.1. (b) 3D topographical MSI of the fresk skin biopsy acquired from the bottom at m/z 597.3 ± 0.1 (red), m/z 701.6 ± 0.1 (green), and m/z 760.6 ± 0.1 (blue). (c) Postmortem mouse imaging experiments. Optical images of the (a) whole mouse and selected imaging zones, (d) mammary gland, (g) heart and lungs, and (j) brain. All the selected ion images were normalized to the TIC. (The figure was adapted with permission from Ogrinc et al. [17]. Copyright 2022 American Chemical Society)

the tissue. Therefore, the use of isopentane cooled in liquid nitrogen is recommended. 3.2.2

Tissue Sectioning

1. When the tissues are well frozen, label and store them in -80 °C freezer until use. 2. Before sectioning, place the tube containing the tissue in the cryo-microtome at -20 °C. The cryo-sectioning temperature may vary depending on the tissue type. It should be set between -10 °C and - 30 °C. Stabilize the tissue for 15 min. 3. Use a water droplet to mount the tissue onto the sectioning chuck. 4. Section the tissue into 20-μm-thick sections. Collect the tissue section onto a pre-cooled slide. Thaw-mount an individual tissue section on the glass slide by using your finger underneath the glass slide. When sectioning the tissue sections, wear

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protective cutting gloves. Store the samples at -80 °C until further use. 3.3 Formalin-Fixed Paraffin-Embedded (FFPE) Tissues 3.3.1

Tissue Sectioning

3.3.2 Glycerol Spray Deposition

1. Section FFPE tissues into 7 μm tissue sections using a microtome at room temperature on regular glass slide. 2. Sections are transferred onto a regular or polylysine-coated slide on top of a water droplet. 3. The glass slide is then warmed up on a hotplate at 50 °C and left to unfold. The excess water is removed by incubation at 30 °C for 20 min. The sections can be stored at room temperature prior to analysis. 1. A FFPE tissue section is used. 2. Prepare 5 mL of the 20% glycerol solution in isopropyl alcohol (IPA). Mix the solution by using a vortex. 3. Deposit the glycerol solution by using the Agilent manual sprayer or similar linked to a syringe set to a 300 μL/min flow rate. The pressure of the nitrogen flow should be set at 2 bars. 4. Spray six layers over the tissue keeping the sprayer at approx. 6–8 cm distance. 5. Verify the droplet size under a microscope. The size of droplets should not be larger than 100 μm.

3.4 Mass Spectrometry Imaging Analysis 3.4.1 2D Imaging of Tissue Sections

1. Using the home-built interface, select the size of the imaged area in a rectangular form. 2. Select the different parameters such as the mapping step (>250 μm), the surface offset, the time between the two laser shots, and the number of laser shots. The latter two parameters will also determine the length of the acquisition. 3. The investigated specimen is placed under the arm at the start position indicated by the LED laser. 4. An automatic acquisition is set in MassLynx (Waters) commercial software which is waiting for the triggering through the Matlab interface. 5. The collection of mass spectrometry data is automatic. The data can be acquired in either positive or negative ion mode. The raw data is saved and stored for further data processing.

3.4.2 3D and in Vivo Imaging

1. Using the home-built interface, select the size of the imaged area in a rectangular form. 2. Launch the 3D sensor height calibration. This will ensure the sensor height is accurate when creating the 3D topographical image and positioning of the laser microprobe. The laser points

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are calibrated in increments of 250 μm in the z dimension, resulting in a calibration curve. R2 should not be less than 0.95. If outliers are observed, the calibration needs to be repeated. 3. Select the different parameters such as the mapping step (≥250 μm), the surface offset, the time between the two laser shots, and the number of laser shots. 4. The investigated specimen is placed under the arm at the start position indicated by the LED laser. 5. An automatic acquisition is set in MassLynx (Waters) commercial software which is waiting for the start signal through the Matlab interface. 6. The collection of parallel topographical images and mass spectrometry data is automatic and in real time. The topographical images are saved as .map files, and the mass spectrometry raw data is saved and stored for further processing. The data can be acquired in either positive or negative ion mode. 3.4.3

MS/MS Analysis

1. The Water Xevo G2S is equipped with a collision cell to achieve ion activation by collision induced dissociation (CID). Argon was used as collision gas for the experiments. The selected ion is isolated with the 1 Da window selection and fragmented with 25–40 V energies. 2. Metabolite and lipid species are identified by searching MS/MS fragments against different databases such as LIPID MAPS, METLIN, ALEX123, or MetFrag.

3.5 Image Reconstructions 3.5.1 Plotting M/z Images onto 2D and 3D Topographical Maps

1. 2D- or 3D-acquired mass spectrometry data is used. 2. The mass spectrometry raw data files are first converted into mzXML files using MSConvert (ProteoWizard). 3. The mzXML file is used for peak detection. Each chromatographic TIC peak from Waters raw data corresponds to one pixel on the topographical map. Each pixel corresponds to one individual mass spectrum. 4. By launching the preprocessing step, the raw data is binned to a desired value and a .mat file is created. The .mat and the topographical .map file allow us to plot the mass spectrometry data back onto the topographical image at the selected m/z value. 5. It is also possible to perform RGB overlays or process the data.

3.5.2 Importation of 2D Images into SCiLS Software

1. 2D mass spectrometry data is used. 2. The mass spectrometry raw data files are first converted into mzML files using MSConvert (ProteoWizard).

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3. Imaging files are reconstructed using imzML converter. The imzML files are created and stored for further use. 4. The created imzML files can be imported into SCiLS MVA software for further processing.

References 1. Cooks RG, Ouyang Z, Takats Z, Wiseman JM (2006) Ambient mass spectrometry. Science 311:1566–1570. https://doi.org/10.1126/ science.1119426 2. Wu C, Dill AL, Eberlin LS, Cooks RG, Ifa DR (2013) Mass spectrometry imaging under ambient conditions. Mass Spectrom Rev 32: 218–243. https://doi.org/10.1002/mas. 21360 3. Feider CL, Krieger A, DeHoog RJ, Eberlin LS (2019) Ambient ionization mass spectrometry: recent developments and applications. Anal Chem 91:4266–4290. https://doi.org/10. 1021/acs.analchem.9b00807 4. Zhang J, Rector J, Lin JQ, Young JH, Sans M, Katta N, Giese N, Yu W, Nagi C, Suliburk J, Liu J, Bensussan A, DeHoog RJ, Garza KY, Ludolph B, Sorace AG, Syed A, Zahedivash A, Milner TE, Eberlin LS (2017) Nondestructive tissue analysis for ex vivo and in vivo cancer diagnosis using a handheld mass spectrometry system. Sci Translat Med 9: eaan 3968. https://do i.org/10.1126/ scitranslmed.aan3968 5. Zhang J, Sans M, DeHoog RJ, Garza KY, King ME, Feider CL, Bensussan A, Keating MF, Lin JQ, Povilaitis SC, Katta N, Milner TE, Yu W, Nagi C, Dhingra S, Pirko C, Brahmbhatt KA, Van Buren G, Carter S, Thompson A, Grogan RH, Suliburk J, Eberlin LS (2021) Clinical translation and evaluation of a handheld and biocompatible mass spectrometry probe for surgical use. Clin Chem. https://doi.org/10. 1093/clinchem/hvab098 6. Balog J, Sasi-Szabo´ L, Kinross J, Lewis MR, Muirhead LJ, Veselkov K, Mirnezami R, ˝ B, Damjanovich L, Darzi A, Nicholson Dezso JK, Taka´ts Z (2013) Intraoperative tissue identification using rapid evaporative ionization mass spectrometry. Sci Translat Med 5: 194ra93–194ra93. https://doi.org/10.1126/ scitranslmed.3005623 7. Fatou B, Saudemont P, Leblanc E, Vinatier D, Mesdag V, Wisztorski M, Focsa C, Salzet M, Ziskind M, Fournier I (2016) In vivo real-time mass spectrometry for guided surgery application. Sci Rep 6:25919. https://doi.org/10. 1038/srep25919

8. Woolman M, Gribble A, Bluemke E, Zou J, Ventura M, Bernards N, Wu M, Ginsberg HJ, Das S, Vitkin A, Zarrine-Afsar A (2017) Optimized Mass Spectrometry Analysis Workflow with Polarimetric Guidance for ex vivo and in situ Sampling of Biological Tissues. Sci Rep:7. https://doi.org/10.1038/s41598-01700272-y 9. Ogrinc N, Saudemont P, Balog J, Robin Y-M, Gimeno J-P, Pascal Q, Tierny D, Takats Z, Salzet M, Fournier I (2019) Water-assisted laser desorption/ionization mass spectrometry for minimally invasive in vivo and real-time surface analysis using SpiderMass. Nat Protoc 14:3162–3182. https://doi.org/10.1038/ s41596-019-0217-8 10. Salzet M, Fournier I, Focsa C, Ziskind M, Fatou B, Wisztorski M (2016) Device for realtime in vivo molecular analysis 11. Fatou B, Ziskind M, Saudemont P, Quanico J, Focsa C, Salzet M, Fournier I (2018) Remote atmospheric pressure infrared matrix-assisted laser desorption-ionization mass spectrometry (remote IR-MALDI MS) of proteins. Mol Cell Proteomics 17:1637–1649. https://doi.org/ 10.1074/mcp.TIR117.000582 12. Fatou B, Saudemont P, Duhamel M, Ziskind M, Focsa C, Salzet M, Fournier I (2018) Real time and in vivo pharmaceutical and environmental studies with SpiderMass instrument. J Biotechnol 281:61–66. https:// doi.org/10.1016/j.jbiotec.2018.06.339 13. Saudemont P, Quanico J, Robin Y-M, Baud A, Balog J, Fatou B, Tierny D, Pascal Q, Minier K, Pottier M, Focsa C, Ziskind M, Takats Z, Salzet M, Fournier I (2018) Real-time molecular diagnosis of tumors using water-assisted laser desorption/ionization mass spectrometry technology. Cancer Cell. https://doi.org/10. 1016/j.ccell.2018.09.009 14. Ogrinc N, Caux P-D, Robin Y-M, Bouchaert E, Fatou B, Ziskind M, Focsa C, Bertin D, Tierny D, Takats Z, Salzet M, Fournier I (2021) Direct water-assisted laser desorption/ionization mass spectrometry Lipidomic analysis and classification of formalinfixed paraffin-embedded sarcoma tissues

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without dewaxing. Clin Chem. https://doi. org/10.1093/clinchem/hvab160 15. Ogrinc N, Attencourt C, Colin E, Boudahi A, Tebbakha R, Salzet M, Testelin S, Dakpe´ S, Fournier I (2022) Mass spectrometry-based differentiation of oral tongue squamous cell carcinoma and nontumor regions with the spidermass technology Front Oral Health 3 16. Ogrinc N, Schneider S, Bourmaud A, Gengler N, Salzet M, Fournier I (2022) Direct in vivo analysis of CBD- and THC-acid cannabinoids and classification of cannabis cultivars using SpiderMass. Meta 12:480. https://doi. org/10.3390/metabo12060480 17. Ogrinc N, Kruszewski A, Chaillou P, Saudemont P, Lagadec C, Salzet M, Duriez C, Fournier I (2021) Robot-assisted SpiderMass for in vivo real-time topography mass spectrometry imaging. Anal Chem 93: 14383–14391. https://doi.org/10.1021/acs. analchem.1c01692 18. Jurchen JC, Rubakhin SS, Sweedler JV (2005) MALDI-MS imaging of features smaller than the size of the laser beam. J Am Soc Mass Spectrom 16:1654–1659. https://doi.org/ 10.1016/j.jasms.2005.06.006 19. Ro¨mpp A, Schramm T, Hester A, Klinkert I, Both J-P, Heeren RMA, Sto¨ckli M, Spengler B (2011) imzML: imaging mass spectrometry markup language: a common data format for mass spectrometry imaging. In: Hamacher M, Eisenacher M, Stephan C (eds) Data Mining in Proteomics: from standards to applications. Humana Press, Totowa, NJ, pp 205–224

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Chapter 9 Cytological Cytospin Preparation for the Spatial Proteomics Analysis of Thyroid Nodules Using MALDI-MSI Isabella Piga, Fabio Pagni, Fulvio Magni, and Andrew Smith Abstract The application of innovative spatial omics approaches in the context of cytological specimens may open new frontiers for their diagnostic assessment. In particular, spatial proteomics using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) represents one of the most promising avenues, owing to its capability to map the distribution of hundreds of proteins within a complex cytological background in a multiplexed and relatively high-throughput manner. This approach may be particularly beneficial in the heterogeneous context of thyroid tumors where certain cells may not present clear-cut malignant morphology upon fine-needle aspiration biopsy, highlighting the necessity for additional molecular tools which are able to improve their diagnostic performance. This chapter aims to provide a detailed overview of a cytospin-based preparation workflow that has been optimized to facilitate the reliable spatial proteomics analysis of cytological thyroid specimens using MALDI-MSI, indicating the key aspects which should be considered when handling such samples. Key words Fine-needle aspiration biopsy, Thyroid, Cancer, MALDI-MS imaging, Proteomics, Cytocentrifugation

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Introduction The art of establishing a pathological diagnosis based on the morphological assessment of clinical samples is challenging, and this is particularly true of cytological specimens which often require the further integration of molecular findings. However, within the often complex setting of cytopathology, where only a small number of cells that are presenting a molecular alteration may occur, obtaining information at the spatial as well as the molecular level is paramount. Therefore, the application of innovative spatial omics approaches in the context of cytological specimens is opening new frontiers for their diagnostic assessment. In particular, spatial proteomics using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) represents one of the most promising avenues, owing to its capability to map the

Laura M. Cole and Malcolm R. Clench (eds.), Imaging Mass Spectrometry: Methods and Protocols, Methods in Molecular Biology, vol. 2688, https://doi.org/10.1007/978-1-0716-3319-9_9, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2023

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distribution of hundreds of proteins within a complex cytological background in a multiplexed and relatively high-throughput manner [1]. Moreover, being generally a non-destructive technique, the cytological specimens may then also be subjected to routine histological staining and evaluation in order to be integrated within the diagnostic workflow. One such disease setting which may benefit most from this approach is thyroid cancer, which represents the most frequent endocrine malignancy worldwide and whose incidence has raised significantly in recent decades [2]. In these instances, fine-needle aspiration (FNA) biopsies represent the gold standard to confirm the malignant nature of thyroid nodules, which may only be indicated by a small number of cells that have undergone transformation. In addition to confirmed cases, after cytomorphological evaluation, 20–30% of cases are also deemed “indeterminate for malignancy” and, as a consequence, undergo surgery. However, following more extensive histopathology post-thyroidectomy, 70–80% of these nodules are determined to be benign which represents an important problem in terms of pursuing standardized treatments as well as preventing unnecessary thyroid surgery and increased healthcare costs [3]. Thus, the development of a MALDI-MSI-based tool which can improve the diagnostic performance of FNAs could be highly sought after and help reduce the burden of this diagnostic challenge. Preliminary work was first performed using conventional smears of ex vivo fine-needle aspirations deriving from benign and malignant thyroid nodules [4, 5]. Doing so highlighted the feasibility of this approach, detecting distinct protein profiles that were associated with various types of nodules including the conventional (cv) and follicular variants (fv) of papillary thyroid carcinoma (PTC), medullary thyroid carcinoma (MTC), as well as hyperplastic nodules. This indicated that it may not only be possible to discriminate benign from malignant lesions but also distinguish the different malignant subtypes which make up this oncological umbrella. Subsequently, the protein profiles obtained from the aforementioned patients were used as a reference to generate a preliminary classifier that was able to assign a test cohort of FNAs to a malignant or benign class with classification accuracy of 90.9% [6]. However, the conventional smears utilized in this preliminary work are hampered due to interference from hemoglobin, resulting in significant ion suppression, as previously reported in Mosele et al. [7]. This aspect is also further exacerbated with diagnostic in vivo samples due to sample contamination from neck vasculature during the collection process. This issue limitation was overcome by Piga et al. by employing a cytospin-based preparation, obtaining a consistent and reliable reduction in hemoglobin and, as a consequence, reduced inter-patient sample variability [8]. Moreover, this cytospin-based approach also helps to stabilize the proteomic and

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morphological integrity of the aspirated cells due to collection in a methanol-based solution, facilitating the exchange of specimens among multiple centers [9]. Considering these technical advancements, subsequent studies have focused on assessing the possible complementary role of MALDI-MSI in the diagnosis of thyroid nodules using challenging samples such as needle washes. This was first highlighted by Capitoli et al. where samples from benign and malignant nodules were used to compute a logistic regression model using with a Lasso regularization method and demonstrated how the output of this approach could be presented using a pixel-by-pixel approach to highlight cells of possible malignancy in a manner that could be integrated with the histological overview of the sample [10]. This approach then recently culminated in a clinical study conducted in order to build a classification model for the characterization of thyroid nodules in a large cohort of 240 samples, showing that MALDI-MSI can be effective in separating areas with benign/ malignant cells and presented a specificity and sensitivity of 82.9% and 76.5%, respectively, in FNAs with adequate cellularity [11]. This chapter therefore aims to provide a detailed overview of the cytospin-based preparation workflow that has been optimized to facilitate the reliable spatial proteomics analysis of cytological thyroid specimens using MALDI-MSI.

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Materials 1. 25-Gauge fine needles. 2. Papanicolaou staining (Pap stain) solution. 3. Standard microscope glass slides. 4. 50 mL centrifuge tubes. 5. ThinPrep CytoLyt solution from Hologic (Marlborough, MA, USA). 6. ThinPrep PreservCyt from Hologic (Marlborough, MA, USA). 7. 1.5 mL microcentrifuge safe-lock snap-cap tubes. 8. Cyto-chambers: multi-funnel chambers 6.2 mm diameter, four-place chambers, capacity 4 × 1 mL (cat. no. 1668, Hettich Lab Technology, Tuttlingen, Germany). 9. Filter cards for multi-funnel cyto-chambers (cat. no. 1693, Hettich Lab Technology, Tuttlingen, Germany). 10. Carrier (cat. no. 1660) and slide carrier (cat. no. 1670) for two chambers (Hettich Lab Technology, Tuttlingen, Germany). 11. Indium tin oxide (ITO)-coated glass slides (Bruker Daltonik GmbH, Bremen, Germany) or other MALDI targets (instrument compatible).

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12. Ethanol solutions (A, B, C: 70, 90, 95%). 13. Sinapinic acid (SA) matrix, working solution: SA (10 mg/mL) in 60/40 ACN:H2O with 0.2% TFA. 14. Protein calibration standard: angiotensin II, angiotensin I, substance P, bombesin, ACTH clip 1–17, ACTH clip 18–39, somatostatin 28 (Bruker Daltonik GmbH, Bremen, Germany). 15. Hematoxylin and eosin. 2.1

Instrumentation

1. Centrifuge 5804 R equipped with an FA-45-24-11 rotor and an S-4-72 rotor (Eppendorf, Hamburg, Germany). 2. Hettich ROTOFIX 32A centrifuge equipped with a SwingOut rotor 1624 (Hettich Lab Technology, Tuttlingen, Germany). 3. Standard desktop digital scanner. 4. iMatrixSpray (for matrix deposition) (Tardo GmbH, Subingen, Switzerland). 5. MALDI mass spectrometer: ultrafleXtreme (Bruker Daltonik GmbH, Bremen, Germany). 6. Scanscope CS2 digital scanner (Aperio, USA).

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1. FlexControl 3.4 (Bruker Daltonik GmbH, Bremen, Germany) – for setting the parameters for spectral acquisition. 2. FlexImaging 4.1 (Bruker Daltonik GmbH, Germany) – for image acquisition andvisualization.

Bremen,

3. SCiLS Lab MVS v. 2019c Pro (http://scils.de/; Bremen, Germany) – for extensive data elaboration. 4. R software v.3.4.3 open source to perform the pre-processing operations and statistical elaboration using MALDIquant and glmnet packages, respectively.

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3.1 Sample Collection

Fine-needle aspirations (FNAs) are collected with a 25-G needle and are obtained from patients who underwent ultrasound-guided procedures. The general workflow is depicted in Fig. 1. Briefly: 1. For each target nodule, one or two passes are performed in order to provide a sample which accurately represents the nature of the nodule. 2. An FNA sample is immediately smeared onto a microscope glass slide and stained with a Pap stain method for traditional morphologic diagnosis.

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Fig. 1 Overview of workflow of cytological sample preparation for MALDI-MSI analysis. Once in PreservCyt, the sample can be transferred immediately (t0) onto the ITO slide or stored at 4 °C for 7 or 14 days (see Note 2)

3. Needle washing from every pass is sent for spatial proteomics analysis with MALDI-MSI by washing the needle in a 50 mL centrifuge tube containing ThinPrep CytoLyt solution (see Note 1). 4. Samples are stored at room temperature and immediately processed. (CytoLyt is a methanol-based buffered preservative media used to lyse red blood cells and to reduce hemoglobin contamination. The solution is used to preserve cellular morphology and allow sample transportation at room temperature). 3.2 Cytospin Sample Preparation and Stocking

1. Fine-needle wash samples deposited into CytoLyt solution are then centrifuged at 800 g for 10 min at room temperature, using a Centrifuge 5804 R equipped with an S-4-72 rotor. The supernatant is discarded. 2. The pellet is re-suspended in 200 μL of PreservCyt methanolbased buffered preservative solution and transferred in a 1.5 mL microcentrifuge safe-lock tube. 3. Samples are centrifuged at 800 g for 10 min at room temperature using a Centrifuge 5424 R equipped with an FA-45-24-11 rotor. The supernatant is discarded and the pellet re-suspended in a final volume of 100 μL of PreservCyt media (see Note 2). 4. The cyto-chamber has to be prepared in order to transfer the sample onto the ITO glass slide (see Fig. 2): (i) An ITO glass slide is inserted into the slide carrier 1670, (ii) filter card 1693 is inserted in the carrier and placed on the top of the ITO glass slide, (iii) two multi-funnel cyto-chambers with four places each (for a total of eight samples at maximum) are placed

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Fig. 2 Preparation of the cyto-chamber. In order to prepare a cyto-chamber, all of these elements will be necessary: (a) cyto-chamber 1670, (b) the ITO glass slide, (c) filter card, (d) two multi-funnel cyto-chambers, (e) two sealing rings, (f) cyto-chamber correct configuration, and (g) cyto-chamber ready to be centrifuged

onto the filter card in the appropriate position and sealed (see Note 3), and (iv) the slide carrier is then placed into the carrier 1660. 5. Once the ITO glass slide has been positioned in the slide carrier along with the filter and cyto-chambers, the entire 100 μL volume of sample suspended in PreservCyt is transferred in one funnel in order to allow the transfer of cytological samples onto ITO glass slides. This enables a thin layer of cells adequate for cytological evaluation to be obtained. 6. Finally, cytological samples are transferred onto ITO slides by centrifugation at 800 g for 15 min at room temperature using a Hettich ROTOFIX 32A centrifuge equipped with a SwingOut rotor 1624. 7. After the cytospin deposition of samples onto ITO slides, samples are dried in a desiccator for 30 minutes.

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8. ITO slides are then placed sequentially into Petri dishes containing increasing concentrations of ethanol (A, B, C) and gently agitated for 30 s during each wash in order to reduce salt contamination. Excess ethanol is then quickly removed from the slide by gently wiping with tissue paper. 9. Slides are then dried under vacuum for 15 minutes, packaged, and stored in a freezer at -80 °C until the day of MALDI-MSI analysis. 3.3 Sample Preparation for MALDIMSI

1. Following removal from the freezer, the ITO glass slides onto which the cytospin cytological specimens were deposited are brought to room temperature and dried under vacuum for 30 minutes. 2. At least three teaching points are then positioned around each cytospin spot prior to scanning. The scanned image of the ITO slide is acquired before matrix deposition in order to obtain a well-defined image of the specimens which is then used to configure the mass spectrometry imaging analysis by associating the scanned image visualized on the acquisition software (FlexImaging) with the real image visualized on the camera of the mass spectrometer’s software (FlexControl) that controls the geometry of the target. The resolution of the scanned image should be selected based upon the spatial resolution of the planned MALDI-MSI analysis (2600 dpi is usually sufficient for 50 μm spatial resolution MALDI-MSI acquisitions). 3. The SA matrix solution is deposited onto the tissue using the iMatrixSpray automated spraying device. Given that a balance between spatial localization and sensitivity is required for this application, example spraying parameters are as follows: spray height, 60 mm; speed, 180 mm/s; line distance, 1 mm; density, 4 μL/cm2; break, 30 s; and number of cycles, 1011. However, if instrumentation that is capable of obtaining MALDI-MS images at spatial resolutions of less than 30 μm is being used, and such spatial resolutions are desired by the user, the spray “height,” “density,” and “break” may need to be adjusted accordingly. 4. Matrix is removed from the edges of the slide using ethanol and tissue paper in order for the conductivity of the slide to be completely maintained. Matrix is also removed from a small area at the center of the ITO slide, between the two sets of four cytospin spots in order to add protein calibrant. 5. A solution containing a 1:1 ratio between SA and the protein calibrant is prepared, and 0.8 μL of this calibrant solution is spotted onto a clean area of the ITO slide.

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3.4 MALDI-MSI Analysis

1. The teaching points placed earlier are used for teaching the instrument and to set the X and Y axes. A different FlexImaging file is created for each cytospin spot. The measurement region is then set using FlexImaging software, and information related to the geometry is sent to the instrument using FlexControl. Other parameters, such as the rastering, are configured in FlexImaging and selected based upon the dimension of the cells to be analyzed and the matrix crystal dimensions. The selected rastering for cytospin spots should be considered prior to the analysis, with a compromise between spatial resolution and acquisition time being made. Considering the diameter of each spot is 6.2 mm, a raster of 50 μm is recommended in order to obtain sufficient proteomic information from the cellular aggregates while ensuring that the acquisition time is standardized and equal to about 4 h. For each raster position, a mass spectrum is acquired by accumulating between 300 and 500 shots per spot. The number of shots is dependent upon the amount of matrix on the sample and its homogeneity, which can vary due to the inherent differences in the morphology of each specimen. After setting FlexImaging files, each analysis is saved as an AutoExecute sequence. 2. Before starting the MALDI-MSI analysis, the method is calibrated using the calibration protein standard spot. 3. The AutoExecuteBatch Runner is then opened in order to set the MALDI-MSI sequence of analysis, in order to automatically run each single cytospin spot analysis one after the other. 4. Each cytospin spot is analyzed using a Bruker UltrafleXtreme mass spectrometer equipped with a Smartbeam laser (Nd:YAG, 355 nm wavelength, 2 kHz laser repetition rate), and mass spectra are recorded in the mass range 3–20 kDa, operating in positive linear mode.

3.5 Cytological Evaluation

1. Following MALDI-MSI analysis, the matrix can be removed from the cytospin spots by washing sequentially in increasing concentrations of ethanol (A, B, C) and gently agitating the slide in a Petri dish for 30 s during each wash. Excess ethanol is then quickly removed from the slide by wiping gently with tissue paper. 2. The ITO slide is then stained with hematoxylin and eosin. 3. The slides are then converted to digital format using the ScanScope CS digital scanner in order to integrate molecular and morphological images. 4. Regions of interest (ROIs) of homogeneous and wellpreserved cells are carefully selected by the pathologist, excluding areas with artifacts.

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Data Elaboration

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1. The acquired data is first visualized in FlexImaging for preliminary evaluation and pre-processing. Spectra are normalized in total ion count (TIC). The cytological image of the H & E-stained slide is co-registered with the molecular image. 2. Regions of interest (ROIs) of benign and malignant thyrocyte cells are drawn on the molecular images following pathologist annotations. 3. Each analysis can be imported into SCiLS Lab MVS v. 2019c Pro, and (i) without applying any further processing, the entire analysis as well as all ROIs can be extracted from each specimen in imzML format by obtaining both .ibd and .imzML files, in order to be processed with MALDIquant R package [12] and statistically elaborated with glmnet R package using opensource R software; (ii) spectra can be pre-processed with the following steps: baseline subtraction (top-hat algorithm), normalization (TIC algorithm), peak picking (orthogonal matching pursuit algorithm), and spatial denoising (medium denoising). The minimal interval width is set at ±4 Da. All these steps are performed in order to generate representative average spectra. Then statistical tools such as principal component analysis (PCA) and receiver operating characteristic (ROC) can be used for deeper data elaboration [13].

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Notes 1. The same protocol can be applied also to fine-needle aspiration biopsy samples completely dedicated to MALDI-MSI analysis or cytological samples obtained from surgical specimens of thyroid nodules [14]. 2. Whenever samples cannot be prepared for MALDI-MSI analysis the same day of FNA sample collection, the morphological integrity and proteomic stability of cytological samples are maintained for up to 14 days when storing the samples in PreservCyt media at 4 °C [9]. 3. One single ITO glass slide can hold up to eight cytospin spots with a diameter of 6.2 mm. However, if only two FNA samples are collected and have to be spotted onto the slide, instead of the multi-funnel chambers, it is possible to use two one-funnel cyto-chambers (cat. no. 1663) and filter cards with two positions (cat. no. 1692) available for the slide carrier 1670.

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Acknowledgments The research was funded by FAR 2017–2020, Fondazione Gigi & Pupa Ferrari Onlus, Associazione Italiana Ricerca sul Cancro (AIRC) MFAG Grant 2016 Id. 18445, Ricerca Finalizzata GR -2019-12368592, Regione Lombardia POR FESR 2014–2020, Call HUB Ricerca e Innovazione: ImmunHUB, and by Regione Lombardia, regional law n° 9/2020, resolution n° 3776/2020: programma degli interventi per la ripresa economica: sviluppo di nuovi accordi di collaborazione con le universita` per la ricerca, l’innovazione e il trasferimento tecnologico: Nephropathy. References 1. Smith A, Piga I, Galli M, Stella M, Denti V, del Puppo M, Magni F (2017) Matrix-assisted laser desorption/ionisation mass spectrometry imaging in the study of gastric cancer: a mini review. Int J Mol Sci 18(12). https://doi.org/ 10.3390/ijms18122588 2. Kitahara CM, Sosa JA (2016) The changing incidence of thyroid cancer. Nat Rev Endocrinol 12(11):646–653. https://doi.org/10. 1038/nrendo.2016.110 3. Nardi F, Basolo F, Crescenzi A, Fadda G, Frasoldati A, Orlandi F, Palombini L, Papini E, Zini M, Pontecorvi A, Vitti P (2014) Italian consensus for the classification and reporting of thyroid cytology. J Endocrinol Investig 37(6):593–599. https://doi.org/10. 1007/s40618-014-0062-0 4. Mainini V, Pagni F, Garancini M, Giardini V, De Sio G, Cusi C, Arosio C, Roversi G, Chinello C, Caria P, Vanni R, Magni F (2013) An alternative approach in endocrine pathology research: MALDI-IMS in papillary thyroid carcinoma. Endocr Pathol 24(4):250–253. https://doi.org/10.1007/s12022-0139273-8 5. Pagni F, Mainini V, Garancini M, Bono F, Vanzati A, Giardini V, Scardilli M, Goffredo P, Smith AJ, Galli M, De Sio G, Magni F (2015) Proteomics for the diagnosis of thyroid lesions: preliminary report. Cytopathology 26(5): 318–324. https://doi.org/10.1111/cyt. 12166 6. Pagni F, De Sio G, Garancini M, Scardilli M, Chinello C, Smith AJ, Bono F, Leni D, Magni F (2016) Proteomics in thyroid cytopathology: relevance of MALDI-imaging in distinguishing malignant from benign lesions. Proteomics 16(11–12):1775–1784. https://doi.org/10. 1002/pmic.201500448

7. Mosele N, Smith A, Galli M, Pagni F, Magni F (2017) MALDI-MSI analysis of cytological smears: the study of thyroid cancer. Methods Mol Biol 1618:37–47 8. Piga I, Capitoli G, Denti V, Tettamanti S, Smith A, Stella M, Chinello C, Leni D, Garancini M, Galimberti S, Magni F, Pagni F (2019) The Management of Haemoglobin Interference for the MALDI-MSI proteomics analysis of thyroid fine needle aspiration biopsies. Anal Bioanal Chem 411(20):5007–5012. https://doi.org/10.1007/s00216-01901908-w 9. Piga I, Capitoli G, Tettamanti S, Denti V, Smith A, Chinello C, Stella M, Leni D, Garancini M, Galimberti S, Magni F, Pagni F (2019) Feasibility study for the MALDI-MSI analysis of thyroid fine needle aspiration biopsies: evaluating the morphological and proteomic stability over time. Proteomics - Clin Appl 13(1):1700170. https://doi.org/10.1002/ prca.201700170 10. Capitoli; Piga; Galimberti; Leni; Pincelli; Garancini; Clerici; Mahajneh; Brambilla; Smith; Magni; Pagni. (2019) MALDI-MSI as a complementary diagnostic tool in cytopathology: a pilot study for the characterization of thyroid nodules. Cancers (Basel) 11(9):1377. https:// doi.org/10.3390/cancers11091377 11. Capitoli G, Piga I, L’Imperio V, Clerici F, Leni D, Garancini M, Casati G, Galimberti S, Magni F, Pagni F (2022) Cytomolecular classification of thyroid nodules using fine-needle washes aspiration biopsies. Int J Mol Sci 23:8. https://doi.org/10.3390/ijms23084156 12. Gibb S, Strimmer K (2012) MALDIquant: a versatile R package for the analysis of mass spectrometry data. Bioinformatics 28(17): 2270–2271. https://doi.org/10.1093/bioin formatics/bts447

Cytological Cytospin Preparation for the Spatial Proteomics Analysis of. . . 13. Smith A, Piga I, Denti V, Chinello C, Magni F (2021) Elaboration pipeline for the management of MALDI-MS imaging datasets. Methods Mol Biol 2361:129–142. https://doi.org/ 10.1007/978-1-0716-1641-3_8 14. Piga I, Capitoli G, Clerici F, Mahajneh A, Brambilla V, Smith A, Leni D, L’Imperio V,

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Chapter 10 Matrix Effects Free Imaging of Thin Tissue Sections Using Pneumatically Assisted Nano-DESI MSI Leonidas Mavroudakis and Ingela Lanekoff Abstract Mass spectrometry imaging has the potential to reveal important molecular interaction in morphological regions in tissue. However, the simultaneous ionization of the continuously altered and complex chemistry in each pixel can introduce artifacts that result in skewed molecular distributions in the compiled ion images. These artifacts are known as matrix effects. Mass spectrometry imaging using nanospray desorption electrospray ionization (nano-DESI MSI) enables the elimination of matrix effects by doping the nanoDESI solvent with internal standards. Carefully selected internal standards ionize similarly and simultaneously with the extracted analytes from thin tissue sections, and the matrix effects are eliminated through a robust data normalization method. Herein we describe the setup and use of pneumatically assisted (PA) nano-DESI MSI with standards doped in the solvent for elimination of matrix effects in ion images. Key words Nanospray desorption electrospray ionization, Matrix effects, Internal standards, Ionization suppression, Mass spectrometry imaging, Tissue sections

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Introduction Matrix effects is a well-known phenomenon in mass spectrometry imaging (MSI) due to the direct sampling and ionization of molecules from the chemically complex tissue sections without any clean-up steps or pre-separation of molecules. Given the complex events that occur during electrospray ionization, proper data normalization is crucial for reporting unbiased results and misinterpretation of molecular distributions in MSI. Nanospray desorption electrospray ionization (nano-DESI) is an ambient liquid extraction technique developed by Roach et al. [1] that is coupled with mass spectrometry and can be used for MSI [2–8]. In nano-DESI MSI, the solvent is propelled through a fused silica primary capillary to form a liquid bridge with an aligned secondary capillary. The secondary capillary serves as a self-aspirating capillary due to the applied high voltage and the proximity to the inlet of the mass

Laura M. Cole and Malcolm R. Clench (eds.), Imaging Mass Spectrometry: Methods and Protocols, Methods in Molecular Biology, vol. 2688, https://doi.org/10.1007/978-1-0716-3319-9_10, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2023

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spectrometer. Alternatively, the secondary capillary can be fitted with a modified nebulizer that causes self-aspiration through to the Venturi effect [9, 10]. The main advantage of the pneumatically assisted (PA) nano-DESI MSI is the observed increased sensitivity for small metabolites due to enhanced desolvation efficiency, compared to the conventional nano-DESI [9]. In both conventional and PA nano-DESI, a high voltage of 3–3.5 kV is applied to the solvent to promote electrospray ionization. Nano-DESI MSI has been used both for method development [11–14] and biological studies [15–18]. The most attractive feature of nano-DESI compared to other MSI techniques, such as MALDI, SIMS, and DESI, is the decoupling of the events for desorption/extraction and ionization. Specifically, in nano-DESI, the molecules from the surface are desorbed into the solvent for subsequent ionization in a second step in front of the mass spectrometer inlet. This separation of the desorption and ionization events allows for the inclusion of dopants in the nano-DESI solvent. These dopants can be selected to aid in ionization [11, 12], promote secondary detection [19], or perform targeted reactions [13]. Alternatively, the dopants can serve as internal standards that experience the same matrix effects during ionization and be used for eliminating matrix effects by signal normalization [20]. For efficient elimination of matrix effects, it is crucial that the selected internal standard has the same physicochemical properties as the endogenous molecule and that their signals do not overlap with other signals in the mass spectrum. In this chapter, we provide detailed instructions on the construction of a PA nano-DESI probe, selection of internal standards, and data normalization that enables acquisition and presentation of ion images free of matrix effects.

2 2.1

Materials Solvent

Theoretically, any solvent system that is compatible with fused silica capillaries can be used to extract molecules from the tissue surface. The most commonly used solvent that provides desorption of various classes of metabolites and lipids is methanol/water 9:1 v/v, although different solvent systems can be used depending on the target analytes [8, 12, 21]. The 90% methanol solvent also extracts sodium and potassium from biological tissues and thus generates analyte signals as protonated, sodiated, and potassiated adducts. Although not necessary, formic acid at 0.1% v/v can be added to the PA nano-DESI solvent to further promote protonation of molecules and increase the solvent conductivity. The components of this solvent include:

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1. Deionized water (18.2 MΩ). 2. Methanol (LC-MS or HPLC-MS grade). 3. Formic acid (98–100% purity). 4. Isotopically labeled standards or structurally similar standards (see Note 1). 2.2 Pneumatically Assisted Nano-DESI

1. Fused silica capillaries (e.g., 50 μm ID × 150 μm OD) (see Note 2). 2. Ceramic capillary cutter. 3. Micropipette beveler with alumina lapping film (World Precision Instruments, model 48000). 4. PEEK tubing (1/16” OD × 0.010” ID). 5. PEEK fittings, one-piece hex-head short, 10–32. 6. High-pressure PEEK tee (0.05” hole). 7. PTFE tubings (1/16” OD × 0.18 mm ID and 1/16” OD × 0.5 mm ID, 1/16” OD × 0.75 mm ID). 8. PEEK fittings 1/16”. 9. High-pressure microtight PEEK union assembly, 6–32 coned (e.g., Idex P-720). 10. Microtight yellow sleeve (0.007” ID × 0.025” OD). 11. Micromanipulators with flexible arms and holder for the capillaries. 12. Ion source that has been modified with a voltage cable and alligator clip (see Note 3). 13. Digital microscope cameras positioned to visualize the capillary junction and mass spectrometer’s inlet. 14. Flat-head syringe (500 μL or higher, gas tight, Luer tip cemented needle, 51 mm needle length). 15. Syringe pump that operates at sub-microliter per minute flow rates. 16. Motorized XYZ stages that are controlled externally with attached sample holder (see Note 4). 17. Nitrogen gas supply for delivering gas to the PEEK tee.

2.3 Preparation of Sample

Thin tissue sections, cells, microbial cultures, or intact tissue can be readily analyzed with PA nano-DESI MSI. For imaging of thin tissue sections, the following are needed: 1. Flash frozen biological tissue. 2. Glass slides (see Note 5). 3. Cryotome.

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Methods

3.1 Thin Tissue Section Preparation

1. Cut 10–16-μm-thick tissue sections using a cryotome and fix them on glass slides or other slides of choice (see Note 6). 2. Store the tissue sections at -80 °C. 3. Before the analysis, rapidly thaw the tissue section on the glass slide (see Note 7).

3.2 Preparation of PA Nano-DESI Solvent 3.2.1 Identification and Use of Appropriate Internal Standards

1. Isotopically labeled versions of the target analytes or structurally similar compounds can be used for signal normalization (see Note 8). 2. Ensure that there are no previously detected isobaric overlaps in the expected mass channels of the selected internal standards (see Note 9). 3. Estimate the appropriate concentration range of each internal standard (see Note 10). 4. Confirm the elimination of matrix effects to ensure that the ion images are truly unbiased (see Note 11).

3.2.2 Preparation of Doped PA Nano-DESI Solvent with Internal Standards

1. Prepare solutions of each internal standard at an appropriate concentration (stock solutions) and in appropriate solvent (see Note 12). 2. Mix appropriate volumes of methanol, water, formic acid (if used), and each of internal standard or other dopant stock solution (see Note 13). 3. Make a large volume of solvent, e.g., 10–20 mL, that can be stored at -20 °C and be readily available for multiple analyses (see Note 14). 4. The prepared solvent can be stored in the freezer (-20 °C) for several months (see Note 15).

3.2.3 Crown Ethers for Determining Alkali Metal Ion Changes

Crown ethers can be used for determining alterations of alkali metal ions such as Na+ and K+ [19]. We have shown that the dibenzo-18crown-6 can be used for monitoring relative changes of Na+/K+ ratios directly from thin tissue sections. 1. Prepare a stock solution of the crown ether in methanol/water 9:1 v/v. 2. Spike an appropriate amount of the crown ether stock solution in the PA nano-DESI solvent (see Sect. 3.2.2) so that the final concentration is about 0.1–1 μM. 3. The crown ether can be used in combination with internal standards.

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Fig. 1 Pictures of the nebulizer and PA nano-DESI setup. (a) Constructed nebulizer for PA nano-DESI. Both designs are perfectly functional, and their difference is the modification of the back-end PEEK fitting for reducing the length of secondary fused silica capillary. (b) Setup for PA nano-DESI MSI experiments in front of the mass spectrometer inlet. (1) Holder for the primary capillary, (2) junction of the primary and secondary capillary, (3) holder for the secondary capillary, (4) gas supply line, and (5) PEEK tee that is used as the nebulizer with the secondary capillary 3.3 Pneumatically Assisted Nano-DESI Setup

3.3.1 Construction of the Nebulizer Device for the Secondary Capillary

The PA nano-DESI setup consists of a primary capillary that delivers the solvent that is propelled by a syringe pump to form a liquid bridge to a secondary capillary. As the liquid bridge makes contact with the sample surface, molecules from the surface are desorbed into the continuously flowing liquid bridge and transported into the secondary capillary. In PA nano-DESI, the flow through the secondary capillary to the inlet of the mass spectrometer is assisted by nitrogen gas that also supports desolvation during the electrospray ionization process [9]. Finally, the sample is placed on a sample holder on the XYZ stage that moves it under the PA nano-DESI probe during analysis. The nebulizer device for the secondary capillary is shown in Fig. 1a. 1. Screw a 1/16” ID PEEK nut on the front end of the PEEK tee and cut along the thread section so that the final protruding length of the PEEK nut is 0.3–0.5 cm. Insert the 1/16” OD × 0.5 mm ID PTFE tubing into the cut PEEK nut. Adjust the PTFE tubing so that it protrudes approximately 1 mm from the cut end of the PEEK nut and that the front end is cut straight. Cut any large excess of PTFE tubing from the back end of the PEEK nut.

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2. Use a short hex-head PEEK fitting with an appropriate PTFE tubing as a sleeve for the back end of the PEEK tee. The inner diameter of the PTFE sleeve should be matching that of the fused silica capillary that is used (see Note 16). 3. Cut approximately 4–5 cm of a fused silica capillary. 4. Use one edge of the fused silica capillary as the spray tip and ensure that the cut is straight and even. Bevel if necessary to remove ragged edges. 5. Insert the fused silica capillary into the nebulizer device using the non-beveled edge and starting from the top of the PEEK tee. This ensures that the beveled nanospray tip will not be damaged during the insertion of the fused silica capillary. 6. Cut away any large excess of PTFE sleeve and fused silica capillary from the back end of the nebulizer device and bevel the cut end so that there are no ragged edges (see Note 17). 7. Adjust the fused silica capillary at the front end of the nebulizer device so that the spray tip protrudes 0.5–1 mm from the PTFE sleeve (see Note 18). 8. Connect a gas line supply onto the PEEK tee using PTFE tubing (1/16” OD × 0.75 mm ID) and a standard 1/16” PEEK fitting. 9. Ensure that all PEEK fittings are connected properly onto the PEEK tee and that there are no gas leakages. The gas should only be exiting from the area between the front end of PTFE sleeve and the spray tip. 3.3.2 Construction of the Primary Capillary

1. Cut an appropriate length of fused silica capillary (e.g., 50 μm ID × 150 μm OD) so that it can reach from the syringe pump until roughly the inlet of the mass spectrometer, e.g., 50–60 cm. 2. Ensure that one edge of the fused silica capillary has a clean and straight cut. Bevel if necessary to remove ragged edges. 3. Cut approximately 1–2 cm of PEEK tubing (1/16” OD × 0.010” ID), insert the fused silica capillary, and slide it so that the straight and beveled edge protrudes about 2–3 cm. This will help to easily hold the capillary in position. 4. Use a small amount of cyanoacrylate glue to ensure that the PEEK tubing is glued onto the fused silica capillary. 5. At the opposite end of the fused silica capillary, insert the capillary in a microsleeve that is sitting in a PEEK fitting. Ensure that the sleeve and the capillary are flush. 6. Tighten the PEEK fitting finger-tight around the sleeve and the fused silica capillary inside a PEEK union. Check that the fused silica capillary is firmly positioned and does not move when the fitting is screwed.

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7. On the other end of the PEEK union, attach a finger-tight PEEK fitting and firmly insert the needle of the syringe containing the nano-DESI solvent into it. Screw finger-tight. 8. Ensure that there are no liquid leaks through the union by pushing some solvent using the syringe pump. 9. Attach the high voltage to the metal needle of the syringe with a clip. Caution should be taken to not touch the high-voltage clip. Ideally, a safety box can be placed around the syringe pump. 3.3.3 Setting Up the PA Nano-DESI

1. The holes of the PEEK tee that serves as the nebulizer can accommodate a small metal rod (e.g., a screw) that can be used as the holding point for the micromanipulator arm (see Fig. 1a). 2. Adjust the spray tip of the nebulizer so that it is aligned with the inlet of the mass spectrometer as shown in Fig. 1b. The nebulizer is at an angle of about 45° relative to the mass spectrometer’s inlet (see Note 19). 3. Use a second micromanipulator to hold the primary capillary using the PEEK tubing as the holding point. 4. Align the primary and the secondary capillary at an angle of about 90° with the primary capillary being slightly below the secondary [22]. The final setup is shown in Fig. 1b (see Note 20). 5. Start by pushing some solvent to fill the capillaries and then set the syringe pump at a flow rate of 0.5 μL min-1 (see Note 21). 6. Turn on the nitrogen gas supply at an initial backpressure of 4–5 bar (see Note 22). 7. Ensure that the liquid droplet between the two capillaries is being aspirated and start adjusting the nitrogen gas backpressure until a stable liquid bridge is achieved (see Note 23). 8. Adjust the relative position of the two capillaries until the liquid bridge is stable. 9. Attach the alligator clip of the voltage cable onto the metal needle of the syringe and turn on the voltage from the mass spectrometer’s interface. 10. If necessary, readjust the relative position of the two capillaries until the liquid bridge is stable, the injection time (for trapping instruments) is as low as possible, and the total ion current variation is stable and low (