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Borrelli C, Gurtner A, Arnold IC, Moor AE. Stress-free single-cell transcriptomic profiling and functional genomics of murine eosinophils. Nat Protoc 2024; 19:1679-1709. [PMID: 38504138 DOI: 10.1038/s41596-024-00967-3] [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: 04/17/2023] [Accepted: 12/20/2023] [Indexed: 03/21/2024]
Abstract
Eosinophils are a class of granulocytes with pleiotropic functions in homeostasis and various human diseases. Nevertheless, they are absent from conventional single-cell RNA sequencing atlases owing to technical difficulties preventing their transcriptomic interrogation. Consequently, eosinophil heterogeneity and the gene regulatory networks underpinning their diverse functions remain poorly understood. We have developed a stress-free protocol for single-cell RNA capture from murine tissue-resident eosinophils, which revealed distinct intestinal subsets and their roles in colitis. Here we describe in detail how to enrich eosinophils from multiple tissues of residence and how to capture high-quality single-cell transcriptomes by preventing transcript degradation. By combining magnetic eosinophil enrichment with microwell-based single-cell RNA capture (BD Rhapsody), our approach minimizes shear stress and processing time. Moreover, we report how to perform genome-wide CRISPR pooled genetic screening in ex vivo-conditioned bone marrow-derived eosinophils to functionally probe pathways required for their differentiation and intestinal maturation. These protocols can be performed by any researcher with basic skills in molecular biology and flow cytometry, and can be adapted to investigate other granulocytes, such as neutrophils and mast cells, thereby offering potential insights into their roles in both homeostasis and disease pathogenesis. Single-cell transcriptomics of eosinophils can be performed in 2-3 d, while functional genomics assays may require up to 1 month.
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Affiliation(s)
- Costanza Borrelli
- Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland
| | - Alessandra Gurtner
- Institute of Experimental Immunology, University of Zürich, Zürich, Switzerland
| | - Isabelle C Arnold
- Institute of Experimental Immunology, University of Zürich, Zürich, Switzerland.
| | - Andreas E Moor
- Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland.
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Ramirez Flores RO, Schäfer PSL, Küchenhoff L, Saez-Rodriguez J. Complementing Cell Taxonomies with a Multicellular Analysis of Tissues. Physiology (Bethesda) 2024; 39:0. [PMID: 38319138 DOI: 10.1152/physiol.00001.2024] [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: 01/03/2024] [Accepted: 01/31/2024] [Indexed: 02/07/2024] Open
Abstract
The application of single-cell molecular profiling coupled with spatial technologies has enabled charting of cellular heterogeneity in reference tissues and in disease. This new wave of molecular data has highlighted the expected diversity of single-cell dynamics upon shared external queues and spatial organizations. However, little is known about the relationship between single-cell heterogeneity and the emergence and maintenance of robust multicellular processes in developed tissues and its role in (patho)physiology. Here, we present emerging computational modeling strategies that use increasingly available large-scale cross-condition single-cell and spatial datasets to study multicellular organization in tissues and complement cell taxonomies. This perspective should enable us to better understand how cells within tissues collectively process information and adapt synchronized responses in disease contexts and to bridge the gap between structural changes and functions in tissues.
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Affiliation(s)
- Ricardo Omar Ramirez Flores
- Faculty of Medicine, Heidelberg University and Institute for Computational Biomedicine, Heidelberg University Hospital, Heidelberg, Germany
| | - Philipp Sven Lars Schäfer
- Faculty of Medicine, Heidelberg University and Institute for Computational Biomedicine, Heidelberg University Hospital, Heidelberg, Germany
| | - Leonie Küchenhoff
- Faculty of Medicine, Heidelberg University and Institute for Computational Biomedicine, Heidelberg University Hospital, Heidelberg, Germany
| | - Julio Saez-Rodriguez
- Faculty of Medicine, Heidelberg University and Institute for Computational Biomedicine, Heidelberg University Hospital, Heidelberg, Germany
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Fujiwara N, Kimura G, Nakagawa H. Emerging Roles of Spatial Transcriptomics in Liver Research. Semin Liver Dis 2024. [PMID: 38574750 DOI: 10.1055/a-2299-7880] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/06/2024]
Abstract
Spatial transcriptomics, leveraging sequencing- and imaging-based techniques, has emerged as a groundbreaking technology for mapping gene expression within the complex architectures of tissues. This approach provides an in-depth understanding of cellular and molecular dynamics across various states of healthy and diseased livers. Through the integration of sophisticated bioinformatics strategies, it enables detailed exploration of cellular heterogeneity, transitions in cell states, and intricate cell-cell interactions with remarkable precision. In liver research, spatial transcriptomics has been particularly revelatory, identifying distinct zonated functions of hepatocytes that are crucial for understanding the metabolic and detoxification processes of the liver. Moreover, this technology has unveiled new insights into the pathogenesis of liver diseases, such as the role of lipid-associated macrophages in steatosis and endothelial cell signals in liver regeneration and repair. In the domain of liver cancer, spatial transcriptomics has proven instrumental in delineating intratumor heterogeneity, identifying supportive microenvironmental niches and revealing the complex interplay between tumor cells and the immune system as well as susceptibility to immune checkpoint inhibitors. In conclusion, spatial transcriptomics represents a significant advance in hepatology, promising to enhance our understanding and treatment of liver diseases.
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Affiliation(s)
- Naoto Fujiwara
- Department of Gastroenterology and Hepatology, Graduate School of Medicine, Mie University, Mie, Japan
| | - Genki Kimura
- Department of Gastroenterology and Hepatology, Graduate School of Medicine, Mie University, Mie, Japan
| | - Hayato Nakagawa
- Department of Gastroenterology and Hepatology, Graduate School of Medicine, Mie University, Mie, Japan
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Lafzi A, Borrelli C, Baghai Sain S, Bach K, Kretz JA, Handler K, Regan-Komito D, Ficht X, Frei A, Moor A. Identifying Spatial Co-occurrence in Healthy and InflAmed tissues (ISCHIA). Mol Syst Biol 2024; 20:98-119. [PMID: 38225383 PMCID: PMC10897385 DOI: 10.1038/s44320-023-00006-5] [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: 09/27/2023] [Revised: 11/28/2023] [Accepted: 12/08/2023] [Indexed: 01/17/2024] Open
Abstract
Sequencing-based spatial transcriptomics (ST) methods allow unbiased capturing of RNA molecules at barcoded spots, charting the distribution and localization of cell types and transcripts across a tissue. While the coarse resolution of these techniques is considered a disadvantage, we argue that the inherent proximity of transcriptomes captured on spots can be leveraged to reconstruct cellular networks. To this end, we developed ISCHIA (Identifying Spatial Co-occurrence in Healthy and InflAmed tissues), a computational framework to analyze the spatial co-occurrence of cell types and transcript species within spots. Co-occurrence analysis is complementary to differential gene expression, as it does not depend on the abundance of a given cell type or on the transcript expression levels, but rather on their spatial association in the tissue. We applied ISCHIA to analyze co-occurrence of cell types, ligands and receptors in a Visium dataset of human ulcerative colitis patients, and validated our findings at single-cell resolution on matched hybridization-based data. We uncover inflammation-induced cellular networks involving M cell and fibroblasts, as well as ligand-receptor interactions enriched in the inflamed human colon, and their associated gene signatures. Our results highlight the hypothesis-generating power and broad applicability of co-occurrence analysis on spatial transcriptomics data.
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Affiliation(s)
- Atefeh Lafzi
- Roche Pharma Research and Early Development, Immunology Infectious Diseases and Ophthalmology Discovery and Translational Area, Grenzacherstrasse 124, 4070, Basel, Switzerland
- Department of Biosystems Science and Engineering, ETH Zürich, Mattenstrasse 26, 4058, Basel, Switzerland
| | - Costanza Borrelli
- Department of Biosystems Science and Engineering, ETH Zürich, Mattenstrasse 26, 4058, Basel, Switzerland
| | - Simona Baghai Sain
- Department of Biosystems Science and Engineering, ETH Zürich, Mattenstrasse 26, 4058, Basel, Switzerland
| | - Karsten Bach
- Department of Biosystems Science and Engineering, ETH Zürich, Mattenstrasse 26, 4058, Basel, Switzerland
| | - Jonas A Kretz
- Department of Biosystems Science and Engineering, ETH Zürich, Mattenstrasse 26, 4058, Basel, Switzerland
| | - Kristina Handler
- Department of Biosystems Science and Engineering, ETH Zürich, Mattenstrasse 26, 4058, Basel, Switzerland
| | - Daniel Regan-Komito
- Roche Pharma Research and Early Development, Immunology Infectious Diseases and Ophthalmology Discovery and Translational Area, Grenzacherstrasse 124, 4070, Basel, Switzerland
| | - Xenia Ficht
- Department of Biosystems Science and Engineering, ETH Zürich, Mattenstrasse 26, 4058, Basel, Switzerland
| | - Andreas Frei
- Roche Pharma Research and Early Development, Immunology Infectious Diseases and Ophthalmology Discovery and Translational Area, Grenzacherstrasse 124, 4070, Basel, Switzerland
| | - Andreas Moor
- Department of Biosystems Science and Engineering, ETH Zürich, Mattenstrasse 26, 4058, Basel, Switzerland.
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