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Dannhorn A, Kazanc E, Flint L, Guo F, Carter A, Hall AR, Jones SA, Poulogiannis G, Barry ST, Sansom OJ, Bunch J, Takats Z, Goodwin RJA. Morphological and molecular preservation through universal preparation of fresh-frozen tissue samples for multimodal imaging workflows. Nat Protoc 2024:10.1038/s41596-024-00987-z. [PMID: 38806741 DOI: 10.1038/s41596-024-00987-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Accepted: 02/14/2024] [Indexed: 05/30/2024]
Abstract
The landscape of tissue-based imaging modalities is constantly and rapidly evolving. While formalin-fixed, paraffin-embedded material is still useful for histological imaging, the fixation process irreversibly changes the molecular composition of the sample. Therefore, many imaging approaches require fresh-frozen material to get meaningful results. This is particularly true for molecular imaging techniques such as mass spectrometry imaging, which are widely used to probe the spatial arrangement of the tissue metabolome. As high-quality fresh-frozen tissues are limited in their availability, any sample preparation workflow they are subjected to needs to ensure morphological and molecular preservation of the tissues and be compatible with as many of the established and emerging imaging techniques as possible to obtain the maximum possible insights from the tissues. Here we describe a universal sample preparation workflow, from the initial step of freezing the tissues to the cold embedding in a new hydroxypropyl methylcellulose/polyvinylpyrrolidone-enriched hydrogel and the generation of thin tissue sections for analysis. Moreover, we highlight the optimized storage conditions that limit molecular and morphological degradation of the sections. The protocol is compatible with human and plant tissues and can be easily adapted for the preparation of alternative sample formats (e.g., three-dimensional cell cultures). The integrated workflow is universally compatible with histological tissue analysis, mass spectrometry imaging and imaging mass cytometry, as well as spatial proteomic, genomic and transcriptomic tissue analysis. The protocol can be completed within 4 h and requires minimal prior experience in the preparation of tissue samples for multimodal imaging experiments.
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Affiliation(s)
- Andreas Dannhorn
- Imaging and Data analytics, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge, UK
- Department of Digestion, Metabolism and Reproduction, Sir Alexander Fleming Building, Imperial College London, London, UK
| | - Emine Kazanc
- Department of Digestion, Metabolism and Reproduction, Sir Alexander Fleming Building, Imperial College London, London, UK
| | - Lucy Flint
- Imaging and Data analytics, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge, UK
| | - Fei Guo
- Imaging and Data analytics, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge, UK
- Safety Innovations, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge, UK
| | - Alfie Carter
- Imaging and Data analytics, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge, UK
- Safety Innovations, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge, UK
| | - Andrew R Hall
- Safety Innovations, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge, UK
| | - Stewart A Jones
- Imaging and Data analytics, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge, UK
| | | | - Simon T Barry
- Bioscience, Discovery, Oncology R&D, AstraZeneca, Cambridge, UK
| | | | - Josephine Bunch
- National Centre of Excellence in Mass Spectrometry Imaging (NiCE-MSI), National Physical Laboratory, Teddington, UK
| | - Zoltan Takats
- Department of Digestion, Metabolism and Reproduction, Sir Alexander Fleming Building, Imperial College London, London, UK
| | - Richard J A Goodwin
- Imaging and Data analytics, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge, UK.
- Institute of Infection, Immunity and Inflammation, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK.
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2
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Krestensen KK, Heeren RMA, Balluff B. State-of-the-art mass spectrometry imaging applications in biomedical research. Analyst 2023; 148:6161-6187. [PMID: 37947390 DOI: 10.1039/d3an01495a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2023]
Abstract
Mass spectrometry imaging has advanced from a niche technique to a widely applied spatial biology tool operating at the forefront of numerous fields, most notably making a significant impact in biomedical pharmacological research. The growth of the field has gone hand in hand with an increase in publications and usage of the technique by new laboratories, and consequently this has led to a shift from general MSI reviews to topic-specific reviews. Given this development, we see the need to recapitulate the strengths of MSI by providing a more holistic overview of state-of-the-art MSI studies to provide the new generation of researchers with an up-to-date reference framework. Here we review scientific advances for the six largest biomedical fields of MSI application (oncology, pharmacology, neurology, cardiovascular diseases, endocrinology, and rheumatology). These publications thereby give examples for at least one of the following categories: they provide novel mechanistic insights, use an exceptionally large cohort size, establish a workflow that has the potential to become a high-impact methodology, or are highly cited in their field. We finally have a look into new emerging fields and trends in MSI (immunology, microbiology, infectious diseases, and aging), as applied MSI is continuously broadening as a result of technological breakthroughs.
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Affiliation(s)
- Kasper K Krestensen
- The Maastricht MultiModal Molecular Imaging (M4I) Institute, Maastricht University, 6229 ER Maastricht, The Netherlands.
| | - Ron M A Heeren
- The Maastricht MultiModal Molecular Imaging (M4I) Institute, Maastricht University, 6229 ER Maastricht, The Netherlands.
| | - Benjamin Balluff
- The Maastricht MultiModal Molecular Imaging (M4I) Institute, Maastricht University, 6229 ER Maastricht, The Netherlands.
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3
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Correia GD, Marchesi JR, MacIntyre DA. Moving beyond DNA: towards functional analysis of the vaginal microbiome by non-sequencing-based methods. Curr Opin Microbiol 2023; 73:102292. [PMID: 36931094 DOI: 10.1016/j.mib.2023.102292] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 02/10/2023] [Accepted: 02/14/2023] [Indexed: 03/17/2023]
Abstract
Over the last two decades, sequencing-based methods have revolutionised our understanding of niche-specific microbial complexity. In the lower female reproductive tract, these approaches have enabled identification of bacterial compositional structures associated with health and disease. Application of metagenomics and metatranscriptomics strategies have provided insight into the putative function of these communities but it is increasingly clear that direct measures of microbial and host cell function are required to understand the contribution of microbe-host interactions to pathophysiology. Here we explore and discuss current methods and approaches, many of which rely upon mass-spectrometry, being used to capture functional insight into the vaginal mucosal interface. In addition to improving mechanistic understanding, these methods offer innovative solutions for the development of diagnostic and therapeutic strategies designed to improve women's health.
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Affiliation(s)
- Gonçalo Ds Correia
- Institute of Reproductive and Developmental Biology, Department of Metabolism, Digestion and Reproduction, Imperial College London, London W12 0NN, UK; March of Dimes Prematurity Research Centre at Imperial College London, London, UK
| | - Julian R Marchesi
- March of Dimes Prematurity Research Centre at Imperial College London, London, UK; Centre for Digestive Diseases, Department of Metabolism, Digestion and Reproduction, Imperial College London, Imperial College London, London W2 1NY, UK
| | - David A MacIntyre
- Institute of Reproductive and Developmental Biology, Department of Metabolism, Digestion and Reproduction, Imperial College London, London W12 0NN, UK; March of Dimes Prematurity Research Centre at Imperial College London, London, UK.
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4
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Zhao C, Dong J, Deng L, Tan Y, Jiang W, Cai Z. Molecular network strategy in multi-omics and mass spectrometry imaging. Curr Opin Chem Biol 2022; 70:102199. [PMID: 36027696 DOI: 10.1016/j.cbpa.2022.102199] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2022] [Revised: 06/01/2022] [Accepted: 07/10/2022] [Indexed: 11/30/2022]
Abstract
Human physiological activities and pathological changes arise from the coordinated interactions of multiple molecules. Mass spectrometry (MS)-based multi-omics and MS imaging (MSI)-based spatial omics are powerful methods used to investigate molecular information related to the phenotype of interest from homogenated or sliced samples, including the qualitative, relative quantitative and spatial distributions. Molecular network strategy provides efficient methods to help us understand and mine the biological patterns behind the phenotypic data. It illustrates and combines various relationships between molecules, and further performs the molecule identification and biological interpretation. Here, we describe the recent advances of network-based analysis and its applications for different biological processes, such as, obesity, central nervous system diseases, and environmental toxicology.
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Affiliation(s)
- Chao Zhao
- Bionic Sensing and Intelligence Center, Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Jiyang Dong
- Department of Electronic Science, National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, China
| | - Lingli Deng
- Department of Information Engineering, East China University of Technology, China
| | - Yawen Tan
- Department of Breast and Thyroid Surgery, Shenzhen Second People's Hospital, Shenzhen, China
| | - Wei Jiang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - Zongwei Cai
- State Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong SAR, China.
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Strittmatter N, Richards FM, Race AM, Ling S, Sutton D, Nilsson A, Wallez Y, Barnes J, Maglennon G, Gopinathan A, Brais R, Wong E, Serra MP, Atkinson J, Smith A, Wilson J, Hamm G, Johnson TI, Dunlop CR, Kaistha BP, Bunch J, Sansom OJ, Takats Z, Andrén PE, Lau A, Barry ST, Goodwin RJA, Jodrell DI. Method To Visualize the Intratumor Distribution and Impact of Gemcitabine in Pancreatic Ductal Adenocarcinoma by Multimodal Imaging. Anal Chem 2022; 94:1795-1803. [PMID: 35005896 DOI: 10.1021/acs.analchem.1c04579] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Gemcitabine (dFdC) is a common treatment for pancreatic cancer; however, it is thought that treatment may fail because tumor stroma prevents drug distribution to tumor cells. Gemcitabine is a pro-drug with active metabolites generated intracellularly; therefore, visualizing the distribution of parent drug as well as its metabolites is important. A multimodal imaging approach was developed using spatially coregistered mass spectrometry imaging (MSI), imaging mass cytometry (IMC), multiplex immunofluorescence microscopy (mIF), and hematoxylin and eosin (H&E) staining to assess the local distribution and metabolism of gemcitabine in tumors from a genetically engineered mouse model of pancreatic cancer (KPC) allowing for comparisons between effects in the tumor tissue and its microenvironment. Mass spectrometry imaging (MSI) enabled the visualization of the distribution of gemcitabine (100 mg/kg), its phosphorylated metabolites dFdCMP, dFdCDP and dFdCTP, and the inactive metabolite dFdU. Distribution was compared to small-molecule ATR inhibitor AZD6738 (25 mg/kg), which was codosed. Gemcitabine metabolites showed heterogeneous distribution within the tumor, which was different from the parent compound. The highest abundance of dFdCMP, dFdCDP, and dFdCTP correlated with distribution of endogenous AMP, ADP, and ATP in viable tumor cell regions, showing that gemcitabine active metabolites are reaching the tumor cell compartment, while AZD6738 was located to nonviable tumor regions. The method revealed that the generation of active, phosphorylated dFdC metabolites as well as treatment-induced DNA damage primarily correlated with sites of high proliferation in KPC PDAC tumor tissue, rather than sites of high parent drug abundance.
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Affiliation(s)
- Nicole Strittmatter
- Imaging and Data Analytics, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge CB4 0WG, United Kingdom
- Department of Chemistry, Technical University of Munich, 85748 Garching, Germany
| | - Frances M Richards
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge CB2 0RE, U.K
- Translational Medicine, Oncology R&D, Astra Zeneca, Cambridge CB4 0WG, United Kingdom
| | - Alan M Race
- Institute of Medical Bioinformatics and Biostatistics, Philipps University of Marburg, 35032 Marburg, Germany
| | - Stephanie Ling
- Imaging and Data Analytics, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge CB4 0WG, United Kingdom
| | - Daniel Sutton
- Imaging and Data Analytics, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge CB4 0WG, United Kingdom
| | - Anna Nilsson
- Department of Pharmaceutical Biosciences, Medical Mass Spectrometry Imaging, Uppsala University, 751 24 Uppsala, Sweden
- Science for Life Laboratory, Spatial Mass Spectrometry, Uppsala University, 751 24 Uppsala, Sweden
| | - Yann Wallez
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge CB2 0RE, U.K
- Bioscience, Oncology R&D, AstraZeneca, Cambridge CB2 0RE, United Kingdom
| | - Jennifer Barnes
- Imaging and Data Analytics, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge CB4 0WG, United Kingdom
| | - Gareth Maglennon
- Imaging and Data Analytics, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge CB4 0WG, United Kingdom
| | - Aarthi Gopinathan
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge CB2 0RE, U.K
| | - Rebecca Brais
- Cambridge University Hospitals NHS Trust, Cambridge CB2 0QQ, United Kingdom
| | - Edmond Wong
- Biologics Engineering, R&D, AstraZeneca, Cambridge CB12 6GH, United Kingdom
| | - Maria Paola Serra
- Imaging and Data Analytics, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge CB4 0WG, United Kingdom
| | - James Atkinson
- Imaging and Data Analytics, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge CB4 0WG, United Kingdom
| | - Aaron Smith
- DMPK, Oncology R&D, AstraZeneca, Cambridge CB2 0RE, United Kingdom
| | - Joanne Wilson
- DMPK, Oncology R&D, AstraZeneca, Cambridge CB2 0RE, United Kingdom
| | - Gregory Hamm
- Imaging and Data Analytics, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge CB4 0WG, United Kingdom
| | - Timothy I Johnson
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge CB2 0RE, U.K
| | - Charles R Dunlop
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge CB2 0RE, U.K
| | - Brajesh P Kaistha
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge CB2 0RE, U.K
- Clinical IO group, Early Oncology, AstraZeneca, Cambridge CB12 6GH, United Kingdom
| | - Josephine Bunch
- National Centre of Excellence in Mass Spectrometry Imaging, National Physical Laboratory, Teddington TW11 0LW, United Kingdom
- Rosalind Franklin Institute, Didcot OX11 0QS, United Kingdom
| | - Owen J Sansom
- Cancer Research UK Beatson Institute, Glasgow G61 1BD, United Kingdom
- Institute of Cancer Sciences, University of Glasgow, Glasgow G61 1QH, United Kingdom
| | - Zoltan Takats
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London SW7 2AZ, United Kingdom
- Rosalind Franklin Institute, Didcot OX11 0QS, United Kingdom
| | - Per E Andrén
- Department of Pharmaceutical Biosciences, Medical Mass Spectrometry Imaging, Uppsala University, 751 24 Uppsala, Sweden
- Science for Life Laboratory, Spatial Mass Spectrometry, Uppsala University, 751 24 Uppsala, Sweden
| | - Alan Lau
- Bioscience, Oncology R&D, AstraZeneca, Cambridge CB2 0RE, United Kingdom
| | - Simon T Barry
- Bioscience, Oncology R&D, AstraZeneca, Cambridge CB2 0RE, United Kingdom
| | - Richard J A Goodwin
- Imaging and Data Analytics, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge CB4 0WG, United Kingdom
- Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow G12 8TA, United Kingdom
| | - Duncan I Jodrell
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge CB2 0RE, U.K
- Department of Oncology, University of Cambridge, Cambridge CB2 0XZ, United Kingdom
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