1
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Liang Q, Yu T, Kofman E, Jagannatha P, Rhine K, Yee BA, Corbett KD, Yeo GW. High-sensitivity in situ capture of endogenous RNA-protein interactions in fixed cells and primary tissues. Nat Commun 2024; 15:7067. [PMID: 39152130 PMCID: PMC11329496 DOI: 10.1038/s41467-024-50363-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Accepted: 07/09/2024] [Indexed: 08/19/2024] Open
Abstract
RNA-binding proteins (RBPs) have pivotal functions in RNA metabolism, but current methods are limited in retrieving RBP-RNA interactions within endogenous biological contexts. Here, we develop INSCRIBE (IN situ Sensitive Capture of RNA-protein Interactions in Biological Environments), circumventing the challenges through in situ RNA labeling by precisely directing a purified APOBEC1-nanobody fusion to the RBP of interest. This method enables highly specific RNA-binding site identification across a diverse range of fixed biological samples such as HEK293T cells and mouse brain tissue and accurately identifies the canonical binding motifs of RBFOX2 (UGCAUG) and TDP-43 (UGUGUG) in native cellular environments. Applicable to any RBP with available primary antibodies, INSCRIBE enables sensitive capture of RBP-RNA interactions from ultra-low input equivalent to ~5 cells. The robust, versatile, and sensitive INSCRIBE workflow is particularly beneficial for precious tissues such as clinical samples, empowering the exploration of genuine RBP-RNA interactions in RNA-related disease contexts.
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Affiliation(s)
- Qishan Liang
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, CA, USA
- Center for RNA Technologies and Therapeutics, University of California San Diego, La Jolla, CA, USA
| | - Tao Yu
- Center for RNA Technologies and Therapeutics, University of California San Diego, La Jolla, CA, USA
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
- Sanford Stem Cell Institute and Stem Cell Program, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Eric Kofman
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
- Sanford Stem Cell Institute and Stem Cell Program, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
- Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, CA, USA
| | - Pratibha Jagannatha
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
- Sanford Stem Cell Institute and Stem Cell Program, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
- Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, CA, USA
| | - Kevin Rhine
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
- Sanford Stem Cell Institute and Stem Cell Program, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Brian A Yee
- Center for RNA Technologies and Therapeutics, University of California San Diego, La Jolla, CA, USA
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
- Sanford Stem Cell Institute and Stem Cell Program, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Kevin D Corbett
- Center for RNA Technologies and Therapeutics, University of California San Diego, La Jolla, CA, USA.
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA.
- Department of Molecular Biology, University of California San Diego, La Jolla, CA, USA.
| | - Gene W Yeo
- Center for RNA Technologies and Therapeutics, University of California San Diego, La Jolla, CA, USA.
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA.
- Sanford Stem Cell Institute and Stem Cell Program, University of California San Diego, La Jolla, CA, USA.
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA.
- Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, CA, USA.
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2
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Vistain L, Keisham B, Xia J, Phan HV, Tay S. Proximity sequencing for the detection of mRNA, extracellular proteins and extracellular protein complexes in single cells. Nat Protoc 2024:10.1038/s41596-024-01030-x. [PMID: 39147984 DOI: 10.1038/s41596-024-01030-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Accepted: 05/24/2024] [Indexed: 08/17/2024]
Abstract
Complex cellular functions occur via the coordinated formation and dissociation of protein complexes. Functions such as the response to a signaling ligand can incorporate dozens of proteins and hundreds of complexes. Until recently, it has been difficult to measure multiple protein complexes at the single-cell level. Here, we present a step-by-step procedure for proximity sequencing, which enables the simultaneous measurement of proteins, mRNA and hundreds of protein complexes located on the outer membrane of cells. We guide the user through probe creation, sample preparation, staining, sequencing and computational quantification of protein complexes. This protocol empowers researchers to study, for example, the interplay between transcriptional states and cellular functions by coupling measurements of transcription to measurements of linked effector molecules, yet could be generalizable to other paired events. The protocol requires roughly 16 h spread over several days to complete by users with expertise in basic molecular biology and single-cell sequencing.
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Affiliation(s)
- Luke Vistain
- Pritzker School of Molecular Engineering, The University of Chicago, Chicago, IL, USA
- Institute for Genomics and Systems Biology, The University of Chicago, Chicago, IL, USA
- Lymphocyte Biology Section, Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Bijentimala Keisham
- Pritzker School of Molecular Engineering, The University of Chicago, Chicago, IL, USA
- Institute for Genomics and Systems Biology, The University of Chicago, Chicago, IL, USA
| | - Junjie Xia
- Pritzker School of Molecular Engineering, The University of Chicago, Chicago, IL, USA
- Institute for Genomics and Systems Biology, The University of Chicago, Chicago, IL, USA
| | - Hoang Van Phan
- Pritzker School of Molecular Engineering, The University of Chicago, Chicago, IL, USA
- Institute for Genomics and Systems Biology, The University of Chicago, Chicago, IL, USA
- Division of Infectious Disease, University of California, San Francisco, San Francisco, CA, USA
| | - Savaş Tay
- Pritzker School of Molecular Engineering, The University of Chicago, Chicago, IL, USA.
- Institute for Genomics and Systems Biology, The University of Chicago, Chicago, IL, USA.
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3
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Huang S, Shi W, Li S, Fan Q, Yang C, Cao J, Wu L. Advanced sequencing-based high-throughput and long-read single-cell transcriptome analysis. LAB ON A CHIP 2024; 24:2601-2621. [PMID: 38669201 DOI: 10.1039/d4lc00105b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/28/2024]
Abstract
Cells are the fundamental building blocks of living systems, exhibiting significant heterogeneity. The transcriptome connects the cellular genotype and phenotype, and profiling single-cell transcriptomes is critical for uncovering distinct cell types, states, and the interplay between cells in development, health, and disease. Nevertheless, single-cell transcriptome analysis faces daunting challenges due to the low abundance and diverse nature of RNAs in individual cells, as well as their heterogeneous expression. The advent and continuous advancements of next-generation sequencing (NGS) and third-generation sequencing (TGS) technologies have solved these problems and facilitated the high-throughput, sensitive, full-length, and rapid profiling of single-cell RNAs. In this review, we provide a broad introduction to current methodologies for single-cell transcriptome sequencing. First, state-of-the-art advancements in high-throughput and full-length single-cell RNA sequencing (scRNA-seq) platforms using NGS are reviewed. Next, TGS-based long-read scRNA-seq methods are summarized. Finally, a brief conclusion and perspectives for comprehensive single-cell transcriptome analysis are discussed.
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Affiliation(s)
- Shanqing Huang
- Discipline of Intelligent Instrument and Equipment, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
| | - Weixiong Shi
- Discipline of Intelligent Instrument and Equipment, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
| | - Shiyu Li
- Discipline of Intelligent Instrument and Equipment, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
| | - Qian Fan
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China.
| | - Chaoyong Yang
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China.
- Discipline of Intelligent Instrument and Equipment, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
| | - Jiao Cao
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China.
| | - Lingling Wu
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China.
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4
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Fiorentino J, Armaos A, Colantoni A, Tartaglia G. Prediction of protein-RNA interactions from single-cell transcriptomic data. Nucleic Acids Res 2024; 52:e31. [PMID: 38364867 PMCID: PMC11014251 DOI: 10.1093/nar/gkae076] [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: 07/17/2023] [Revised: 01/12/2024] [Accepted: 01/26/2024] [Indexed: 02/18/2024] Open
Abstract
Proteins are crucial in regulating every aspect of RNA life, yet understanding their interactions with coding and noncoding RNAs remains limited. Experimental studies are typically restricted to a small number of cell lines and a limited set of RNA-binding proteins (RBPs). Although computational methods based on physico-chemical principles can predict protein-RNA interactions accurately, they often lack the ability to consider cell-type-specific gene expression and the broader context of gene regulatory networks (GRNs). Here, we assess the performance of several GRN inference algorithms in predicting protein-RNA interactions from single-cell transcriptomic data, and propose a pipeline, called scRAPID (single-cell transcriptomic-based RnA Protein Interaction Detection), that integrates these methods with the catRAPID algorithm, which can identify direct physical interactions between RBPs and RNA molecules. Our approach demonstrates that RBP-RNA interactions can be predicted from single-cell transcriptomic data, with performances comparable or superior to those achieved for the well-established task of inferring transcription factor-target interactions. The incorporation of catRAPID significantly enhances the accuracy of identifying interactions, particularly with long noncoding RNAs, and enables the identification of hub RBPs and RNAs. Additionally, we show that interactions between RBPs can be detected based on their inferred RNA targets. The software is freely available at https://github.com/tartaglialabIIT/scRAPID.
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Affiliation(s)
- Jonathan Fiorentino
- Center for Life Nano- and Neuro-Science, RNA Systems Biology Lab, Fondazione Istituto Italiano di Tecnologia (IIT), 00161 Rome, Italy
| | - Alexandros Armaos
- Centre for Human Technologies (CHT), RNA Systems Biology Lab, Fondazione Istituto Italiano di Tecnologia (IIT), 16152 Genova, Italy
| | - Alessio Colantoni
- Center for Life Nano- and Neuro-Science, RNA Systems Biology Lab, Fondazione Istituto Italiano di Tecnologia (IIT), 00161 Rome, Italy
- Department of Biology and Biotechnologies “Charles Darwin”, Sapienza University of Rome, 00185 Rome, Italy
| | - Gian Gaetano Tartaglia
- Center for Life Nano- and Neuro-Science, RNA Systems Biology Lab, Fondazione Istituto Italiano di Tecnologia (IIT), 00161 Rome, Italy
- Centre for Human Technologies (CHT), RNA Systems Biology Lab, Fondazione Istituto Italiano di Tecnologia (IIT), 16152 Genova, Italy
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5
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Coulter EM, Bewicke-Copley F, Mossner M, Graham TA, Fitzgibbon J, Okosun J. Defining an Optimized Workflow for Enriching and Analyzing Residual Tumor Populations Using Intracellular Markers. J Mol Diagn 2024; 26:245-256. [PMID: 38280422 DOI: 10.1016/j.jmoldx.2024.01.003] [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: 06/23/2023] [Revised: 12/12/2023] [Accepted: 01/11/2024] [Indexed: 01/29/2024] Open
Abstract
Tumor relapse is well recognized to arise from treatment-resistant residual populations. Strategies enriching such populations for in-depth downstream analyses focus on tumor-specific surface markers; however, enrichment using intracellular biomarkers remains challenging. Using B-cell lymphoma as an exemplar, we demonstrate feasibility to enrich B-cell lymphoma 2 (BCL2)high populations, a surrogate marker for t(14;18)+ lymphomas, for use in downstream applications. Different fixation protocols were assessed for impact on antibody expression and RNA integrity; glyoxal fixation demonstrated superior results regarding minimal effects on surface and intracellular expression, and RNA quality, compared with alternative fixatives evaluated. Furthermore, t(14;18)+ B cells were effectively detected using intracellular BCL2 overexpression to facilitate tumor cell enrichment. Tumor cell populations were enriched using the cellenONE F1.4 single-cell sorting platform, which detected and dispensed BCL2high-expressing cells directly into library preparation reagents for transcriptome analyses. Sorted glyoxal-fixed cells generated good quality sequencing libraries, with high concordance between live and fixed single-cell transcriptomic profiles, discriminating cell populations predominantly on B-cell biology. Overall, we successfully developed a proof-of-concept workflow employing a robust cell preparation protocol for intracellular markers combined with cell enrichment using the cellenONE platform, providing an alternative to droplet-based technologies when cellular input is low or requires prior enrichment to detect rare populations. This workflow has wider prognostic and therapeutic potential to study residual cells in a pan-cancer setting.
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Affiliation(s)
- Eve M Coulter
- Centre for Haemato-Oncology, Barts Cancer Institute, Queen Mary University of London, London, United Kingdom.
| | - Findlay Bewicke-Copley
- Centre for Haemato-Oncology, Barts Cancer Institute, Queen Mary University of London, London, United Kingdom
| | - Maximilian Mossner
- Centre for Evolution and Cancer, The Institute of Cancer Research, London, United Kingdom; Centre for Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, London, United Kingdom
| | - Trevor A Graham
- Centre for Evolution and Cancer, The Institute of Cancer Research, London, United Kingdom; Centre for Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, London, United Kingdom
| | - Jude Fitzgibbon
- Centre for Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, London, United Kingdom; AstraZeneca, Waltham, Massachusetts
| | - Jessica Okosun
- Centre for Haemato-Oncology, Barts Cancer Institute, Queen Mary University of London, London, United Kingdom.
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6
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Jiménez-Gracia L, Marchese D, Nieto JC, Caratù G, Melón-Ardanaz E, Gudiño V, Roth S, Wise K, Ryan NK, Jensen KB, Hernando-Momblona X, Bernardes JP, Tran F, Sievers LK, Schreiber S, van den Berge M, Kole T, van der Velde PL, Nawijn MC, Rosenstiel P, Batlle E, Butler LM, Parish IA, Plummer J, Gut I, Salas A, Heyn H, Martelotto LG. FixNCut: single-cell genomics through reversible tissue fixation and dissociation. Genome Biol 2024; 25:81. [PMID: 38553769 PMCID: PMC10979608 DOI: 10.1186/s13059-024-03219-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Accepted: 03/18/2024] [Indexed: 04/02/2024] Open
Abstract
The use of single-cell technologies for clinical applications requires disconnecting sampling from downstream processing steps. Early sample preservation can further increase robustness and reproducibility by avoiding artifacts introduced during specimen handling. We present FixNCut, a methodology for the reversible fixation of tissue followed by dissociation that overcomes current limitations. We applied FixNCut to human and mouse tissues to demonstrate the preservation of RNA integrity, sequencing library complexity, and cellular composition, while diminishing stress-related artifacts. Besides single-cell RNA sequencing, FixNCut is compatible with multiple single-cell and spatial technologies, making it a versatile tool for robust and flexible study designs.
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Affiliation(s)
- Laura Jiménez-Gracia
- Centro Nacional de Análisis Genómico (CNAG), 08028, Barcelona, Spain
- Universitat de Barcelona (UB), Barcelona, Spain
| | - Domenica Marchese
- Centro Nacional de Análisis Genómico (CNAG), 08028, Barcelona, Spain
- Universitat de Barcelona (UB), Barcelona, Spain
| | - Juan C Nieto
- Centro Nacional de Análisis Genómico (CNAG), 08028, Barcelona, Spain
- Universitat de Barcelona (UB), Barcelona, Spain
| | - Ginevra Caratù
- Centro Nacional de Análisis Genómico (CNAG), 08028, Barcelona, Spain
- Universitat de Barcelona (UB), Barcelona, Spain
| | - Elisa Melón-Ardanaz
- Inflammatory Bowel Disease Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), Barcelona, Spain
| | - Victoria Gudiño
- Inflammatory Bowel Disease Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), Barcelona, Spain
| | - Sara Roth
- Cancer Immunology Program, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, VIC, Australia
- Monash University Department of Surgery, Alfred Hospital, Melbourne, VIC, Australia
| | - Kellie Wise
- Adelaide Centre for Epigenetics (ACE), University of Adelaide, Adelaide, South Australia, Australia
- South Australian immunoGENomics Cancer Institute (SAiGENCI), University of Adelaide, Adelaide, South Australia, Australia
- Australian Genomics Research Facility, Adelaide, South Australia, Australia
| | - Natalie K Ryan
- South Australian immunoGENomics Cancer Institute (SAiGENCI), University of Adelaide, Adelaide, South Australia, Australia
- Freemasons Foundation Centre for Men's Health, University of Adelaide, Adelaide, South Australia, Australia
- South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia
| | - Kirk B Jensen
- Adelaide Centre for Epigenetics (ACE), University of Adelaide, Adelaide, South Australia, Australia
- South Australian immunoGENomics Cancer Institute (SAiGENCI), University of Adelaide, Adelaide, South Australia, Australia
- Australian Genomics Research Facility, Adelaide, South Australia, Australia
| | - Xavier Hernando-Momblona
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Barcelona, Spain
| | - Joana P Bernardes
- Institute of Clinical Molecular Biology, Kiel University, Kiel, Germany
| | - Florian Tran
- Institute of Clinical Molecular Biology, Kiel University, Kiel, Germany
- Department of Internal Medicine I, University Hospital Schleswig-Holstein (UKSH), Campus Kiel, Kiel, Germany
| | - Laura Katharina Sievers
- Institute of Clinical Molecular Biology, Kiel University, Kiel, Germany
- Department of Internal Medicine I, University Hospital Schleswig-Holstein (UKSH), Campus Kiel, Kiel, Germany
| | - Stefan Schreiber
- Institute of Clinical Molecular Biology, Kiel University, Kiel, Germany
- Department of Internal Medicine I, University Hospital Schleswig-Holstein (UKSH), Campus Kiel, Kiel, Germany
| | - Maarten van den Berge
- Department of Pulmonary Diseases, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
- Groningen Research Institute for Asthma and COPD, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Tessa Kole
- Department of Pulmonary Diseases, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
- Groningen Research Institute for Asthma and COPD, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Petra L van der Velde
- Groningen Research Institute for Asthma and COPD, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
- Department of Pathology & Medical Biology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Martijn C Nawijn
- Groningen Research Institute for Asthma and COPD, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
- Department of Pathology & Medical Biology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Philip Rosenstiel
- Institute of Clinical Molecular Biology, Kiel University, Kiel, Germany
| | - Eduard Batlle
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Barcelona, Spain
- ICREA, Barcelona, Spain
| | - Lisa M Butler
- South Australian immunoGENomics Cancer Institute (SAiGENCI), University of Adelaide, Adelaide, South Australia, Australia
- Freemasons Foundation Centre for Men's Health, University of Adelaide, Adelaide, South Australia, Australia
- South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia
| | - Ian A Parish
- Cancer Immunology Program, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, VIC, Australia
| | - Jasmine Plummer
- St Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Ivo Gut
- Centro Nacional de Análisis Genómico (CNAG), 08028, Barcelona, Spain
- Universitat de Barcelona (UB), Barcelona, Spain
| | - Azucena Salas
- Inflammatory Bowel Disease Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), Barcelona, Spain
| | - Holger Heyn
- Centro Nacional de Análisis Genómico (CNAG), 08028, Barcelona, Spain.
- Universitat de Barcelona (UB), Barcelona, Spain.
- Omniscope, Barcelona, Spain.
| | - Luciano G Martelotto
- Adelaide Centre for Epigenetics (ACE), University of Adelaide, Adelaide, South Australia, Australia.
- South Australian immunoGENomics Cancer Institute (SAiGENCI), University of Adelaide, Adelaide, South Australia, Australia.
- Omniscope, Barcelona, Spain.
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7
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Grones C, Eekhout T, Shi D, Neumann M, Berg LS, Ke Y, Shahan R, Cox KL, Gomez-Cano F, Nelissen H, Lohmann JU, Giacomello S, Martin OC, Cole B, Wang JW, Kaufmann K, Raissig MT, Palfalvi G, Greb T, Libault M, De Rybel B. Best practices for the execution, analysis, and data storage of plant single-cell/nucleus transcriptomics. THE PLANT CELL 2024; 36:812-828. [PMID: 38231860 PMCID: PMC10980355 DOI: 10.1093/plcell/koae003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 10/17/2023] [Accepted: 10/24/2023] [Indexed: 01/19/2024]
Abstract
Single-cell and single-nucleus RNA-sequencing technologies capture the expression of plant genes at an unprecedented resolution. Therefore, these technologies are gaining traction in plant molecular and developmental biology for elucidating the transcriptional changes across cell types in a specific tissue or organ, upon treatments, in response to biotic and abiotic stresses, or between genotypes. Despite the rapidly accelerating use of these technologies, collective and standardized experimental and analytical procedures to support the acquisition of high-quality data sets are still missing. In this commentary, we discuss common challenges associated with the use of single-cell transcriptomics in plants and propose general guidelines to improve reproducibility, quality, comparability, and interpretation and to make the data readily available to the community in this fast-developing field of research.
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Affiliation(s)
- Carolin Grones
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent 9052, Belgium
- VIB Centre for Plant Systems Biology, Ghent 9052, Belgium
| | - Thomas Eekhout
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent 9052, Belgium
- VIB Centre for Plant Systems Biology, Ghent 9052, Belgium
- VIB Single Cell Core Facility, Ghent 9052, Belgium
| | - Dongbo Shi
- Centre for Organismal Studies, Heidelberg University, 69120 Heidelberg, Germany
- Institute of Biochemistry and Biology, University of Potsdam, 14476 Potsdam, Germany
| | - Manuel Neumann
- Institute of Biology, Humboldt-Universität zu Berlin, 10115 Berlin, Germany
| | - Lea S Berg
- Institute of Plant Sciences, University of Bern, 3012 Bern, Switzerland
| | - Yuji Ke
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent 9052, Belgium
- VIB Centre for Plant Systems Biology, Ghent 9052, Belgium
| | - Rachel Shahan
- Department of Biology, Duke University, Durham, NC 27708, USA
- Howard Hughes Medical Institute, Duke University, Durham, NC 27708, USA
| | - Kevin L Cox
- Donald Danforth Plant Science Center, St. Louis, MO 63132, USA
| | - Fabio Gomez-Cano
- Department of Molecular, Cellular, and Developmental Biology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Hilde Nelissen
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent 9052, Belgium
- VIB Centre for Plant Systems Biology, Ghent 9052, Belgium
| | - Jan U Lohmann
- Centre for Organismal Studies, Heidelberg University, 69120 Heidelberg, Germany
| | - Stefania Giacomello
- SciLifeLab, Department of Gene Technology, KTH Royal Institute of Technology, 17165 Solna, Sweden
| | - Olivier C Martin
- Universities of Paris-Saclay, Paris-Cité and Evry, CNRS, INRAE, Institute of Plant Sciences Paris-Saclay, Gif-sur-Yvette 91192, France
| | - Benjamin Cole
- DOE-Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - Jia-Wei Wang
- National Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences (CEMPS), Institute of Plant Physiology and Ecology (SIPPE), Chinese Academy of Sciences (CAS), Shanghai 200032, China
| | - Kerstin Kaufmann
- Institute of Biology, Humboldt-Universität zu Berlin, 10115 Berlin, Germany
| | - Michael T Raissig
- Institute of Plant Sciences, University of Bern, 3012 Bern, Switzerland
| | - Gergo Palfalvi
- Department of Comparative Development and Genetics, Max Planck Institute for Plant Breeding Research, 50829 Cologne, Germany
| | - Thomas Greb
- Centre for Organismal Studies, Heidelberg University, 69120 Heidelberg, Germany
| | - Marc Libault
- Division of Plant Science and Technology, Interdisciplinary Plant Group, College of Agriculture, Food, and Natural Resources, University of Missouri-Columbia, Columbia, MO 65201, USA
| | - Bert De Rybel
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent 9052, Belgium
- VIB Centre for Plant Systems Biology, Ghent 9052, Belgium
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8
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Hume AJ, Olejnik J, White MR, Huang J, Turcinovic J, Heiden B, Bawa PS, Williams CJ, Gorham NG, Alekseyev YO, Connor JH, Kotton DN, Mühlberger E. Heat Inactivation of Nipah Virus for Downstream Single-Cell RNA Sequencing Does Not Interfere with Sample Quality. Pathogens 2024; 13:62. [PMID: 38251369 PMCID: PMC10818917 DOI: 10.3390/pathogens13010062] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 01/04/2024] [Accepted: 01/05/2024] [Indexed: 01/23/2024] Open
Abstract
Single-cell RNA sequencing (scRNA-seq) technologies are instrumental to improving our understanding of virus-host interactions in cell culture infection studies and complex biological systems because they allow separating the transcriptional signatures of infected versus non-infected bystander cells. A drawback of using biosafety level (BSL) 4 pathogens is that protocols are typically developed without consideration of virus inactivation during the procedure. To ensure complete inactivation of virus-containing samples for downstream analyses, an adaptation of the workflow is needed. Focusing on a commercially available microfluidic partitioning scRNA-seq platform to prepare samples for scRNA-seq, we tested various chemical and physical components of the platform for their ability to inactivate Nipah virus (NiV), a BSL-4 pathogen that belongs to the group of nonsegmented negative-sense RNA viruses. The only step of the standard protocol that led to NiV inactivation was a 5 min incubation at 85 °C. To comply with the more stringent biosafety requirements for BSL-4-derived samples, we included an additional heat step after cDNA synthesis. This step alone was sufficient to inactivate NiV-containing samples, adding to the necessary inactivation redundancy. Importantly, the additional heat step did not affect sample quality or downstream scRNA-seq results.
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Affiliation(s)
- Adam J. Hume
- Department of Virology, Immunology and Microbiology, Chobanian & Avedisian School of Medicine, Boston University, Boston, MA 02118, USA; (A.J.H.); (J.O.); (M.R.W.); (J.T.); (B.H.); (J.H.C.)
- National Emerging Infectious Diseases Laboratories, Boston University, Boston, MA 02218, USA
| | - Judith Olejnik
- Department of Virology, Immunology and Microbiology, Chobanian & Avedisian School of Medicine, Boston University, Boston, MA 02118, USA; (A.J.H.); (J.O.); (M.R.W.); (J.T.); (B.H.); (J.H.C.)
- National Emerging Infectious Diseases Laboratories, Boston University, Boston, MA 02218, USA
| | - Mitchell R. White
- Department of Virology, Immunology and Microbiology, Chobanian & Avedisian School of Medicine, Boston University, Boston, MA 02118, USA; (A.J.H.); (J.O.); (M.R.W.); (J.T.); (B.H.); (J.H.C.)
- National Emerging Infectious Diseases Laboratories, Boston University, Boston, MA 02218, USA
| | - Jessie Huang
- Center for Regenerative Medicine of Boston University and Boston Medical Center, Boston, MA 02118, USA; (J.H.); (P.S.B.); (D.N.K.)
- The Pulmonary Center and Department of Medicine, Chobanian & Avedisian School of Medicine, Boston University, Boston, MA 02118, USA
| | - Jacquelyn Turcinovic
- Department of Virology, Immunology and Microbiology, Chobanian & Avedisian School of Medicine, Boston University, Boston, MA 02118, USA; (A.J.H.); (J.O.); (M.R.W.); (J.T.); (B.H.); (J.H.C.)
- National Emerging Infectious Diseases Laboratories, Boston University, Boston, MA 02218, USA
| | - Baylee Heiden
- Department of Virology, Immunology and Microbiology, Chobanian & Avedisian School of Medicine, Boston University, Boston, MA 02118, USA; (A.J.H.); (J.O.); (M.R.W.); (J.T.); (B.H.); (J.H.C.)
- National Emerging Infectious Diseases Laboratories, Boston University, Boston, MA 02218, USA
| | - Pushpinder S. Bawa
- Center for Regenerative Medicine of Boston University and Boston Medical Center, Boston, MA 02118, USA; (J.H.); (P.S.B.); (D.N.K.)
| | - Christopher J. Williams
- Department of Medicine, Single Cell Sequencing Core Facility, Chobanian & Avedisian School of Medicine, Boston University, Boston, MA 02118, USA;
| | - Nickolas G. Gorham
- Microarray and Sequencing Resource Core Facility, Chobanian & Avedisian School of Medicine, Boston University, Boston, MA 02118, USA;
| | - Yuriy O. Alekseyev
- Department of Pathology and Laboratory Medicine, Chobanian & Avedisian School of Medicine, Boston University, Boston, MA 02118, USA;
| | - John H. Connor
- Department of Virology, Immunology and Microbiology, Chobanian & Avedisian School of Medicine, Boston University, Boston, MA 02118, USA; (A.J.H.); (J.O.); (M.R.W.); (J.T.); (B.H.); (J.H.C.)
- National Emerging Infectious Diseases Laboratories, Boston University, Boston, MA 02218, USA
| | - Darrell N. Kotton
- Center for Regenerative Medicine of Boston University and Boston Medical Center, Boston, MA 02118, USA; (J.H.); (P.S.B.); (D.N.K.)
- The Pulmonary Center and Department of Medicine, Chobanian & Avedisian School of Medicine, Boston University, Boston, MA 02118, USA
| | - Elke Mühlberger
- Department of Virology, Immunology and Microbiology, Chobanian & Avedisian School of Medicine, Boston University, Boston, MA 02118, USA; (A.J.H.); (J.O.); (M.R.W.); (J.T.); (B.H.); (J.H.C.)
- National Emerging Infectious Diseases Laboratories, Boston University, Boston, MA 02218, USA
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9
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Wyler E. Single-Cell RNA-Sequencing of RVFV Infection. Methods Mol Biol 2024; 2824:361-372. [PMID: 39039423 DOI: 10.1007/978-1-0716-3926-9_22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/24/2024]
Abstract
On the RNA level, viral infections are characterized by perturbations in the host cell transcriptome as well as the development of viral genetic information. Investigating the abundance and dynamic of RNA molecules can provide ample information to understand many aspects of the infection, from viral replication to pathogenesis. A key aspect therein is the resolution of the data, as infections are generally highly heterogeneous. Even in simple model systems such as cell lines, viral infections happen in a very asynchronous way. Quantifying RNAs at single-cell resolution can therefore substantially increase our understanding of these processes.Whereas measuring the RNA in bulk, that is, in samples containing thousands to hundreds of thousands of cells, is established and widely used since many years, methods for studying not only just a few different RNAs in individual cells became widely available only recently. Here, I outline and compare current concepts and methodologies for using single-cell RNA-sequencing to study virus infections. This covers sample preparation, cell preservation, biosafety considerations, and various experimental methods, with a special focus on the aspects that are important for studying virus infections. Since there is not "the one" method for doing single-cell RNA-sequencing, I will not provide a detailed protocol. Rather, this chapter should serve as a primer for getting started with single-cell RNA-sequencing experiments of virus infections and discusses the criteria that allow readers to choose the best procedures for their specific research question.
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Affiliation(s)
- Emanuel Wyler
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine, Helmholtz Association, Berlin, Germany.
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10
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Madaci L, Gard C, Nin S, Sarrabay A, Baier C, Venton G, Rihet P, Puthier D, Loriod B, Costello R. Single-Cell Transcriptome Analysis of Acute Myeloid Leukemia Cells Using Methanol Fixation and Cryopreservation. Diseases 2023; 12:1. [PMID: 38275564 PMCID: PMC10814800 DOI: 10.3390/diseases12010001] [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: 11/16/2023] [Revised: 12/08/2023] [Accepted: 12/18/2023] [Indexed: 01/27/2024] Open
Abstract
INTRODUCTION The application of single-cell RNA sequencing has greatly improved our understanding of various cellular and molecular mechanisms involved in physiological and pathophysiological processes. However, obtaining living cells for this technique can be difficult under certain conditions. To solve this problem, the methanol fixation method appeared as a promising alternative for routine clinical use. MATERIALS AND METHODS In this study, we selected two AML samples that had been fixed in methanol for 12-18 months. Once the cells were rehydrated, these samples were subjected to single-cell RNA sequencing. We then compared the results obtained from these samples with those obtained from the same samples cryopreserved in DMSO. RESULTS We used a previously validated methanol fixation protocol to perform scRNA-seq on DMSO cryopreserved cells and cells fixed in methanol for more than one year. Preliminary results show that methanol fixation induces some genetic and transcriptional modification compared with DMSO cryopreservation but remains a valuable method for single-cell analysis of primary human leukemia cells. CONCLUSIONS The initial findings from this study highlight certain resemblances in methanol fixation over a 12-month period and cryopreservation with DMSO, along with associated transcriptional level modifications. However, we observed genetic degradation in the fixation condition when extending beyond one year. Despite certain study limitations, it is evident that short-term methanol fixation can be effectively used for leukemia blast samples. Its ease of implementation holds the potential to simplify the integration of this technique into routine clinical practice.
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Affiliation(s)
- Lamia Madaci
- TAGC, TGML, INSERM, UMR1090, Aix-Marseille University, Parc Scientifique de Luminy, 13009 Marseille, France; (L.M.); (C.G.); (S.N.); (G.V.); (P.R.); (D.P.); (B.L.)
| | - Charlyne Gard
- TAGC, TGML, INSERM, UMR1090, Aix-Marseille University, Parc Scientifique de Luminy, 13009 Marseille, France; (L.M.); (C.G.); (S.N.); (G.V.); (P.R.); (D.P.); (B.L.)
| | - Sébastien Nin
- TAGC, TGML, INSERM, UMR1090, Aix-Marseille University, Parc Scientifique de Luminy, 13009 Marseille, France; (L.M.); (C.G.); (S.N.); (G.V.); (P.R.); (D.P.); (B.L.)
| | - Alexandre Sarrabay
- TAGC, TGML, INSERM, UMR1090, Aix-Marseille University, Parc Scientifique de Luminy, 13009 Marseille, France; (L.M.); (C.G.); (S.N.); (G.V.); (P.R.); (D.P.); (B.L.)
| | - Céline Baier
- Advanced BioDesign, Parc Technologique de Lyon, 655 Allée des Parcs, 69800 Saint Priest, France
| | - Geoffroy Venton
- TAGC, TGML, INSERM, UMR1090, Aix-Marseille University, Parc Scientifique de Luminy, 13009 Marseille, France; (L.M.); (C.G.); (S.N.); (G.V.); (P.R.); (D.P.); (B.L.)
- Hematology and Cellular Therapy Department, Conception University Hospital, 13005 Marseille, France
| | - Pascal Rihet
- TAGC, TGML, INSERM, UMR1090, Aix-Marseille University, Parc Scientifique de Luminy, 13009 Marseille, France; (L.M.); (C.G.); (S.N.); (G.V.); (P.R.); (D.P.); (B.L.)
| | - Denis Puthier
- TAGC, TGML, INSERM, UMR1090, Aix-Marseille University, Parc Scientifique de Luminy, 13009 Marseille, France; (L.M.); (C.G.); (S.N.); (G.V.); (P.R.); (D.P.); (B.L.)
| | - Béatrice Loriod
- TAGC, TGML, INSERM, UMR1090, Aix-Marseille University, Parc Scientifique de Luminy, 13009 Marseille, France; (L.M.); (C.G.); (S.N.); (G.V.); (P.R.); (D.P.); (B.L.)
| | - Régis Costello
- TAGC, TGML, INSERM, UMR1090, Aix-Marseille University, Parc Scientifique de Luminy, 13009 Marseille, France; (L.M.); (C.G.); (S.N.); (G.V.); (P.R.); (D.P.); (B.L.)
- Hematology and Cellular Therapy Department, Conception University Hospital, 13005 Marseille, France
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11
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Zhang T, Jia H, Song T, Lv L, Gulhan DC, Wang H, Guo W, Xi R, Guo H, Shen N. De novo identification of expressed cancer somatic mutations from single-cell RNA sequencing data. Genome Med 2023; 15:115. [PMID: 38111063 PMCID: PMC10726641 DOI: 10.1186/s13073-023-01269-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 12/04/2023] [Indexed: 12/20/2023] Open
Abstract
Identifying expressed somatic mutations from single-cell RNA sequencing data de novo is challenging but highly valuable. We propose RESA - Recurrently Expressed SNV Analysis, a computational framework to identify expressed somatic mutations from scRNA-seq data. RESA achieves an average precision of 0.77 on three in silico spike-in datasets. In extensive benchmarking against existing methods using 19 datasets, RESA consistently outperforms them. Furthermore, we applied RESA to analyze intratumor mutational heterogeneity in a melanoma drug resistance dataset. By enabling high precision detection of expressed somatic mutations, RESA substantially enhances the reliability of mutational analysis in scRNA-seq. RESA is available at https://github.com/ShenLab-Genomics/RESA .
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Affiliation(s)
- Tianyun Zhang
- Department of Hepatobiliary and Pancreatic Surgery of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 311121, China
| | - Hanying Jia
- Department of Hepatobiliary and Pancreatic Surgery of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 311121, China
- Kidney Disease Center, the First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, 311121, China
| | - Tairan Song
- Department of Hepatobiliary and Pancreatic Surgery of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 311121, China
| | - Lin Lv
- Department of Hepatobiliary and Pancreatic Surgery of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 311121, China
| | - Doga C Gulhan
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, 02115, USA
| | - Haishuai Wang
- College of Computer Science, Zhejiang University, Hangzhou, 311121, Zhejiang, China
| | - Wei Guo
- Zhejiang University-University of Edinburgh Institute, School of Medicine, Zhejiang University, Jiaxing, 314400, China
| | - Ruibin Xi
- School of Mathematical Sciences and Center for Statistical Science, Peking University, 5 Yiheyuan Road, Beijing, 100871, China
| | - Hongshan Guo
- Department of Hepatobiliary and Pancreatic Surgery of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 311121, China
- Bone Marrow Transplantation Center, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, Zhejiang, China
| | - Ning Shen
- Department of Hepatobiliary and Pancreatic Surgery of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 311121, China.
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12
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Sánchez-Carbonell M, Jiménez Peinado P, Bayer-Kaufmann C, Hennings JC, Hofmann Y, Schmidt S, Witte OW, Urbach A. Effect of methanol fixation on single-cell RNA sequencing of the murine dentate gyrus. Front Mol Neurosci 2023; 16:1223798. [PMID: 37860083 PMCID: PMC10582346 DOI: 10.3389/fnmol.2023.1223798] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 09/18/2023] [Indexed: 10/21/2023] Open
Abstract
Single-cell RNA sequencing (scRNA-seq) provides a powerful tool to evaluate the transcriptomic landscape and heterogeneity of thousands of cells in parallel. However, complex study designs or the unavailability of in-house instruments require the temporal disconnection between sample preparation and library construction, raising the need for efficient sample preservation methods which are compatible with scRNA-seq downstream analysis. Several studies evaluated the effect of methanol fixation as preservation method, yet none of them deeply assessed its effect on adult primary dissociated brain tissue. Here, we evaluated its effect on murine dentate gyrus (DG) single cell suspensions and on subsequent scRNA-seq downstream analysis by performing SOrting and Robot-assisted Transcriptome SEQuencing (SORT-seq), a partially robotized version of the CEL-seq2 protocol. Our results show that MeOH fixation preserves RNA integrity and has no apparent effects on cDNA library construction. They also suggest that fixation protects from sorting-induced cell stress and increases the proportion of high-quality cells. Despite evidence of mRNA leakage in fixed cells, their relative gene expression levels correlate well with those of fresh cells and fixation does not significantly affect the variance of the dataset. Moreover, it allows the identification of all major DG cell populations, including neural precursors, granule neurons and different glial cell types, with a tendency to preserve more neurons that are underrepresented in fresh samples. Overall, our data show that MeOH fixation is suitable for preserving primary neural cells for subsequent single-cell RNA profiling, helping to overcome challenges arising from complex workflows, improve experimental flexibility and facilitate scientific collaboration.
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Affiliation(s)
| | | | | | | | - Yvonne Hofmann
- Department of Internal Medicine V, Jena University Hospital, Jena, Germany
| | - Silvio Schmidt
- Department of Neurology, Jena University Hospital, Jena, Germany
- Jena Center for Healthy Aging, Jena University Hospital, Jena, Germany
- Brain Imaging Center, Jena University Hospital, Jena, Germany
| | - Otto W. Witte
- Department of Neurology, Jena University Hospital, Jena, Germany
- Jena Center for Healthy Aging, Jena University Hospital, Jena, Germany
- Aging Research Center (ARC) Jena, Jena, Germany
| | - Anja Urbach
- Department of Neurology, Jena University Hospital, Jena, Germany
- Jena Center for Healthy Aging, Jena University Hospital, Jena, Germany
- Aging Research Center (ARC) Jena, Jena, Germany
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13
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Bageritz J, Krausse N, Yousefian S, Leible S, Valentini E, Boutros M. Glyoxal as an alternative fixative for single-cell RNA sequencing. G3 (BETHESDA, MD.) 2023; 13:jkad160. [PMID: 37494060 PMCID: PMC10542564 DOI: 10.1093/g3journal/jkad160] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/16/2023] [Revised: 07/10/2023] [Accepted: 07/11/2023] [Indexed: 07/27/2023]
Abstract
Single-cell RNA sequencing has become an important method to identify cell types, delineate the trajectories of cell differentiation in whole organisms, and understand the heterogeneity in cellular responses. Nevertheless, sample collection and processing remain a severe bottleneck for single-cell RNA sequencing experiments. Cell isolation protocols often lead to significant changes in the transcriptomes of cells, requiring novel methods to preserve cell states. Here, we developed and benchmarked protocols using glyoxal as a fixative for single-cell RNA sequencing applications. Using Drop-seq methodology, we detected a large number of transcripts and genes from glyoxal-fixed Drosophila cells after single-cell RNA sequencing. The effective glyoxal fixation of transcriptomes in Drosophila and human cells was further supported by a high correlation of gene expression data between glyoxal-fixed and unfixed samples. Accordingly, we also found highly expressed genes overlapping to a large extent between experimental conditions. These results indicated that our fixation protocol did not induce considerable changes in gene expression and conserved the transcriptome for subsequent single-cell isolation procedures. In conclusion, we present glyoxal as a suitable fixative for Drosophila cells and potentially cells of other species that allow high-quality single-cell RNA sequencing applications.
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Affiliation(s)
- Josephine Bageritz
- Division Signaling and Functional Genomics, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 580, 69120 Heidelberg, Germany
| | - Niklas Krausse
- Division Signaling and Functional Genomics, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 580, 69120 Heidelberg, Germany
| | - Schayan Yousefian
- Division Signaling and Functional Genomics, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 580, 69120 Heidelberg, Germany
| | - Svenja Leible
- Division Signaling and Functional Genomics, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 580, 69120 Heidelberg, Germany
| | - Erica Valentini
- Division Signaling and Functional Genomics, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 580, 69120 Heidelberg, Germany
| | - Michael Boutros
- Division Signaling and Functional Genomics, BioQuant and Medical Faculty Mannheim, German Cancer Research Center (DKFZ), Heidelberg University, D-69120 Heidelberg, Germany
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14
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Speranza E. Understanding virus-host interactions in tissues. Nat Microbiol 2023; 8:1397-1407. [PMID: 37488255 DOI: 10.1038/s41564-023-01434-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 06/20/2023] [Indexed: 07/26/2023]
Abstract
Although virus-host interactions are usually studied in a single cell type using in vitro assays in immortalized cell lines or isolated cell populations, it is important to remember that what is happening inside one infected cell does not translate to understanding how an infected cell behaves in a tissue, organ or whole organism. Infections occur in complex tissue environments, which contain a host of factors that can alter the course of the infection, including immune cells, non-immune cells and extracellular-matrix components. These factors affect how the host responds to the virus and form the basis of the protective response. To understand virus infection, tools are needed that can profile the tissue environment. This Review highlights methods to study virus-host interactions in the infection microenvironment.
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Affiliation(s)
- Emily Speranza
- Cleveland Clinic Lerner Research Institute, Port Saint Lucie, FL, USA.
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15
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Koiwai K, Kondo H, Hirono I. scRNA-seq Analysis of Hemocytes of Penaeid Shrimp Under Virus Infection. MARINE BIOTECHNOLOGY (NEW YORK, N.Y.) 2023:10.1007/s10126-023-10221-8. [PMID: 37326798 DOI: 10.1007/s10126-023-10221-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Accepted: 06/02/2023] [Indexed: 06/17/2023]
Abstract
The classification of cells in non-model organisms has lagged behind the classification of cells in model organisms that have established cluster of differentiation marker sets. To reduce fish diseases, research is needed to better understand immune-related cells, or hemocytes, in non-model organisms like shrimp and other marine invertebrates. In this study, we used Drop-seq to examine how virus infection affected the populations of hemocytes in kuruma shrimp, Penaeus japonicus, which had been artificially infected with a virus. The findings demonstrated that virus infection reduced particular cell populations in circulating hemolymph and inhibited the expression of antimicrobial peptides. We also identified the gene sets that are likely to be responsible for this reduction. Additionally, we identified functionally unknown genes as novel antimicrobial peptides, and we supported this assumption by the fact that these genes were expressed in the population of hemocytes that expressed other antimicrobial peptides. In addition, we aimed to improve the operability of the experiment by conducting Drop-seq with fixed cells as a source and discussed the impact of methanol fixation on Drop-seq data in comparison to previous results obtained without fixation. These results not only deepen our understanding of the immune system of crustaceans but also demonstrate that single-cell analysis can accelerate research on non-model organisms.
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Affiliation(s)
- Keiichiro Koiwai
- Laboratory of Genome Science, Tokyo University of Marine Science and Technology, Tokyo, Japan.
| | - Hidehiro Kondo
- Laboratory of Genome Science, Tokyo University of Marine Science and Technology, Tokyo, Japan
| | - Ikuo Hirono
- Laboratory of Genome Science, Tokyo University of Marine Science and Technology, Tokyo, Japan
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16
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Sant P, Rippe K, Mallm JP. Approaches for single-cell RNA sequencing across tissues and cell types. Transcription 2023; 14:127-145. [PMID: 37062951 PMCID: PMC10807473 DOI: 10.1080/21541264.2023.2200721] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 03/30/2023] [Indexed: 04/18/2023] Open
Abstract
Single-cell sequencing of RNA (scRNA-seq) has advanced our understanding of cellular heterogeneity and signaling in developmental biology and disease. A large number of complementary assays have been developed to profile transcriptomes of individual cells, also in combination with other readouts, such as chromatin accessibility or antibody-based analysis of protein surface markers. As scRNA-seq technologies are advancing fast, it is challenging to establish robust workflows and up-to-date protocols that are best suited to address the large range of research questions. Here, we review scRNA-seq techniques from mRNA end-counting to total RNA in relation to their specific features and outline the necessary sample preparation steps and quality control measures. Based on our experience in dealing with the continuously growing portfolio from the perspective of a central single-cell facility, we aim to provide guidance on how workflows can be best automatized and share our experience in coping with the continuous expansion of scRNA-seq techniques.
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Affiliation(s)
- Pooja Sant
- Single-cell Open Lab, German Cancer Research Center (DKFZ) and Bioquant, Heidelberg, Germany
| | - Karsten Rippe
- Division Chromatin Networks, German Cancer Research Center (DKFZ) and Bioquant, Heidelberg, Germany
| | - Jan-Philipp Mallm
- Single-cell Open Lab, German Cancer Research Center (DKFZ) and Bioquant, Heidelberg, Germany
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17
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Scully T, Klein A. A mannitol-based buffer improves single-cell RNA sequencing of high-salt marine cells. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.26.538465. [PMID: 37163054 PMCID: PMC10168337 DOI: 10.1101/2023.04.26.538465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Single-cell RNA sequencing (scRNA-seq) enables discovery of novel cell states by transcriptomic profiling with minimal prior knowledge, making it useful for studying non-model organisms. For most marine organisms, however, cells are viable at a higher salinity than is compatible with scRNA-seq, impacting data quality and cell representation. We show that a low-salinity phosphate buffer supplemented with D-mannitol (PBS-M) enables higher-quality scRNA-seq of blood cells from the tunicate Ciona robusta. Using PBS-M reduces cell death and ambient mRNA, revealing cell states not otherwise detected. This simple protocol modification could enable or improve scRNA-seq for the majority of marine organisms.
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Affiliation(s)
- Tal Scully
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
| | - Allon Klein
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
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18
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Hudson WH, Wieland A. Technology meets TILs: Deciphering T cell function in the -omics era. Cancer Cell 2023; 41:41-57. [PMID: 36206755 PMCID: PMC9839604 DOI: 10.1016/j.ccell.2022.09.011] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 08/15/2022] [Accepted: 09/15/2022] [Indexed: 01/17/2023]
Abstract
T cells are at the center of cancer immunology because of their ability to recognize mutations in tumor cells and directly mediate cancer cell killing. Immunotherapies to rejuvenate exhausted T cell responses have transformed the clinical management of several malignancies. In parallel, the development of novel multidimensional analysis platforms, such as single-cell RNA sequencing and high-dimensional flow cytometry, has yielded unprecedented insights into immune cell biology. This convergence has revealed substantial heterogeneity of tumor-infiltrating immune cells in single tumors, across tumor types, and among individuals with cancer. Here we discuss the opportunities and challenges of studying the complex tumor microenvironment with -omics technologies that generate vast amounts of data, highlighting the opportunities and limitations of these technologies with a particular focus on interpreting high-dimensional studies of CD8+ T cells in the tumor microenvironment.
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Affiliation(s)
- William H Hudson
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX 77030, USA; Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA; Center for Cell and Gene Therapy, Baylor College of Medicine, Houston, TX 77030, USA.
| | - Andreas Wieland
- Department of Otolaryngology, The Ohio State University, Columbus, OH 43210, USA; Department of Microbial Infection and Immunity, The Ohio State University, Columbus, OH 43210, USA; Pelotonia Institute for Immuno-Oncology, The Ohio State University, Columbus, OH 43210, USA.
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19
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Rossi T, Angeli D, Martinelli G, Fabbri F, Gallerani G. From phenotypical investigation to RNA-sequencing for gene expression analysis: A workflow for single and pooled rare cells. Front Genet 2022; 13:1012191. [PMID: 36452152 PMCID: PMC9703136 DOI: 10.3389/fgene.2022.1012191] [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: 08/05/2022] [Accepted: 10/28/2022] [Indexed: 08/30/2023] Open
Abstract
Combining phenotypical and molecular characterization of rare cells is challenging due to their scarcity and difficult handling. In oncology, circulating tumor cells (CTCs) are considered among the most important rare cell populations. Their phenotypic and molecular characterization is necessary to define the molecular mechanisms underlying their metastatic potential. Several approaches that require cell fixation make difficult downstream molecular investigations on RNA. Conversely, the DEPArray technology allows phenotypic analysis and handling of both fixed and unfixed cells, enabling a wider range of applications. Here, we describe an experimental workflow that allows the transcriptomic investigation of single and pooled OE33 cells undergone to DEPArray analysis and recovery. In addition, cells were tested at different conditions (unfixed, CellSearch fixative (CSF)- and ethanol (EtOH)-fixed cells). In a forward-looking perspective, this workflow will pave the way for novel strategies to characterize gene expression profiles of rare cells, both single-cell and low-resolution input.
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Affiliation(s)
- Tania Rossi
- Biosciences Laboratory, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) “Dino Amadori”, Meldola, Italy
| | - Davide Angeli
- Unit of Biostatistics and Clinical Trials, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) “Dino Amadori”, Meldola, Italy
| | - Giovanni Martinelli
- Scientific Directorate, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) “Dino Amadori”, Meldola, Italy
| | - Francesco Fabbri
- Biosciences Laboratory, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) “Dino Amadori”, Meldola, Italy
| | - Giulia Gallerani
- Biosciences Laboratory, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) “Dino Amadori”, Meldola, Italy
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20
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Detecting signatures of selection on gene expression. Nat Ecol Evol 2022; 6:1035-1045. [PMID: 35551249 DOI: 10.1038/s41559-022-01761-8] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Accepted: 04/01/2022] [Indexed: 12/15/2022]
Abstract
A substantial amount of phenotypic diversity results from changes in gene expression levels and patterns. Understanding how the transcriptome evolves is therefore a key priority in identifying mechanisms of adaptive change. However, in contrast to powerful models of sequence evolution, we lack a consensus model of gene expression evolution. Furthermore, recent work has shown that many of the comparative approaches used to study gene expression are subject to biases that can lead to false signatures of selection. Here we first outline the main approaches for describing expression evolution and their inherent biases. Next, we bridge the gap between the fields of phylogenetic comparative methods and transcriptomics to reinforce the main pitfalls of inferring selection on expression patterns and use simulation studies to show that shifts in tissue composition can heavily bias inferences of selection. We close by highlighting the multi-dimensional nature of transcriptional variation and identifying major unanswered questions in disentangling how selection acts on the transcriptome.
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21
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Bourlard L, Manigart Y, Donner C, Smits G, Désir J, Migeotte I, Pichon B. Rarity of fetal cells in exocervical samples for noninvasive prenatal diagnosis. J Perinat Med 2022; 50:476-485. [PMID: 34973051 DOI: 10.1515/jpm-2021-0291] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/05/2021] [Accepted: 12/04/2021] [Indexed: 11/15/2022]
Abstract
OBJECTIVES The possibility to isolate fetal cells from pregnant women cervical samples has been discussed for five decades but is not currently applied in clinical practice. This study aimed at offering prenatal genetic diagnosis from fetal cells obtained through noninvasive exocervical sampling and immuno-sorted based on expression of HLA-G. METHODS We first developed and validated robust protocols for cell detection and isolation on control cell lines expressing (JEG-3) or not (JAR) the HLA-G antigen, a specific marker for extravillous trophoblasts. We then applied these protocols to noninvasive exocervical samples collected from pregnant women between 6 and 14 weeks of gestational age. Sampling was performed through insertion and rotation of a brush at the ectocervix close to the external os of the endocervical canal. Finally, we attempted to detect and quantify trophoblasts in exocervical samples from pregnant women by ddPCR targeting the male SRY locus. RESULTS For immunohistochemistry, a strong specific signal for HLA-G was observed in the positive control cell line and for rare cells in exocervical samples, but only in non-fixative conditions. HLA-G positive cells diluted in HLA-G negative cells were isolated by flow cytometry or magnetic cell sorting. However, no HLA-G positive cells could be recovered from exocervical samples. SRY gene was detected by ddPCR in exocervical samples from male (50%) but also female (27%) pregnancies. CONCLUSIONS Our data suggest that trophoblasts are too rarely and inconstantly present in noninvasive exocervical samples to be reliably retrieved by standard immunoisolation techniques and therefore cannot replace the current practice for prenatal screening and diagnosis.
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Affiliation(s)
- Laura Bourlard
- Department of Medical Genetics, Erasme University Hospital, Bruxelles, Belgium.,Center of Human Genetics, Université Libre de Bruxelles - Erasme Hospital, Route de Lennik 808, 1070 Brussels, Belgium
| | - Yannick Manigart
- Department of Obstetrics and Gynecology, Saint-Pierre University Hospital, Bruxelles, Belgium
| | - Catherine Donner
- Department of Obstetrics and Gynecology, Erasme University Hospital, Bruxelles, Belgium
| | - Guillaume Smits
- Department of Medical Genetics, Erasme University Hospital, Bruxelles, Belgium.,Center of Human Genetics, Université Libre de Bruxelles - Erasme Hospital, Route de Lennik 808, 1070 Brussels, Belgium
| | - Julie Désir
- Department of Genetics, Institute of Pathology and Genetics (IPG), Gosselies, Belgium
| | - Isabelle Migeotte
- Department of Medical Genetics, Erasme University Hospital, Bruxelles, Belgium.,Center of Human Genetics, Université Libre de Bruxelles - Erasme Hospital, Route de Lennik 808, 1070 Brussels, Belgium
| | - Bruno Pichon
- Center of Human Genetics, Université Libre de Bruxelles - Erasme Hospital, Route de Lennik 808, 1070 Brussels, Belgium
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22
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Han L, Jara CP, Wang O, Shi Y, Wu X, Thibivilliers S, Wóycicki RK, Carlson MA, Velander WH, Araújo EP, Libault M, Zhang C, Lei Y. Isolating and cryopreserving pig skin cells for single-cell RNA sequencing study. PLoS One 2022; 17:e0263869. [PMID: 35176067 PMCID: PMC8853494 DOI: 10.1371/journal.pone.0263869] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Accepted: 01/29/2022] [Indexed: 11/27/2022] Open
Abstract
The pig skin architecture and physiology are similar to those of humans. Thus, the pig model is very valuable for studying skin biology and testing therapeutics. The single-cell RNA sequencing (scRNA-seq) technology allows quantitatively analyzing cell types, compositions, states, signaling, and receptor-ligand interactome at single-cell resolution and at high throughput. scRNA-seq has been used to study mouse and human skins. However, studying pig skin with scRNA-seq is still rare. A critical step for successful scRNA-seq is to obtain high-quality single cells from the pig skin tissue. Here we report a robust method for isolating and cryopreserving pig skin single cells for scRNA-seq. We showed that pig skin could be efficiently dissociated into single cells with high cell viability using the Miltenyi Human Whole Skin Dissociation kit and the Miltenyi gentleMACS Dissociator. Furthermore, the obtained single cells could be cryopreserved using 90% FBS + 10% DMSO without causing additional cell death, cell aggregation, or changes in gene expression profiles. Using the developed protocol, we were able to identify all the major skin cell types. The protocol and results from this study are valuable for the skin research scientific community.
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Affiliation(s)
- Li Han
- School of Biological Science, University of Nebraska, Lincoln, Nebraska, United States of America
- Department of Chemical and Biomolecular Engineering, University of Nebraska, Lincoln, Nebraska, United States of America
- Department of Biomedical Engineering, Pennsylvania State University, University Park, Pennsylvania, United States of America
- Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania, United States of America
| | - Carlos P. Jara
- Nursing School, University of Campinas, Campinas SP, Brazil
- Laboratory of Cell Signaling, University of Campinas, Campinas SP, Brazil
| | - Ou Wang
- Department of Chemical and Biomolecular Engineering, University of Nebraska, Lincoln, Nebraska, United States of America
| | - Yu Shi
- School of Biological Science, University of Nebraska, Lincoln, Nebraska, United States of America
| | - Xinran Wu
- Department of Biomedical Engineering, Pennsylvania State University, University Park, Pennsylvania, United States of America
- Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania, United States of America
| | - Sandra Thibivilliers
- Department of Agronomy and Horticulture, Center for Plant Science Innovation, University of Nebraska, Lincoln, Nebraska, United States of America
| | - Rafał K. Wóycicki
- Department of Agronomy and Horticulture, Center for Plant Science Innovation, University of Nebraska, Lincoln, Nebraska, United States of America
| | - Mark A. Carlson
- Mary and Dick Holland Regenerative Medicine Program, University of Nebraska Medical Center, Omaha, Nebraska, United States of America
- Department of Surgery, University of Nebraska Medical Center and the VA Nebraska-Western Iowa Health Care System, Omaha, Nebraska, United States of America
| | - William H. Velander
- Department of Chemical and Biomolecular Engineering, University of Nebraska, Lincoln, Nebraska, United States of America
| | - Eliana P. Araújo
- Nursing School, University of Campinas, Campinas SP, Brazil
- Laboratory of Cell Signaling, University of Campinas, Campinas SP, Brazil
| | - Marc Libault
- Department of Agronomy and Horticulture, Center for Plant Science Innovation, University of Nebraska, Lincoln, Nebraska, United States of America
| | - Chi Zhang
- School of Biological Science, University of Nebraska, Lincoln, Nebraska, United States of America
| | - Yuguo Lei
- Department of Chemical and Biomolecular Engineering, University of Nebraska, Lincoln, Nebraska, United States of America
- Department of Biomedical Engineering, Pennsylvania State University, University Park, Pennsylvania, United States of America
- Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania, United States of America
- Mary and Dick Holland Regenerative Medicine Program, University of Nebraska Medical Center, Omaha, Nebraska, United States of America
- Department of Surgery, University of Nebraska Medical Center and the VA Nebraska-Western Iowa Health Care System, Omaha, Nebraska, United States of America
- Sartorius Mammalian Cell Culture Facility, Pennsylvania State University, University Park, Pennsylvania, United States of America
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23
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Wang X, Yu L, Wu AR. Correction to: The effect of methanol fixation on single-cell RNA sequencing data. BMC Genomics 2021; 22:554. [PMID: 34281520 PMCID: PMC8290621 DOI: 10.1186/s12864-021-07806-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Affiliation(s)
- Xinlei Wang
- Division of Life Science, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong SAR, China
| | - Lei Yu
- Division of Life Science, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong SAR, China
| | - Angela Ruohao Wu
- Division of Life Science, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong SAR, China. .,Department of Chemical and Biological Engineering, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong SAR, China. .,Hong Kong Branch of Guangdong Southern Marine Science and Engineering Laboratory (Guangzhou), Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong SAR, China.
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