Multi-omic analyses in immune cell development with lessons learned from T cell development
Frontiers in Cell and Developmental Biology, vol. 11, pp. 1163529
Abstract
Traditionally, flow cytometry has been the preferred method to characterize immune cells at the single-cell level. Flow cytometry is used in immunology mostly to measure the expression of identifying markers on the cell surface, but-with good antibodies-can also be used to assess the expression of intracellular proteins. The advent of single-cell RNA-sequencing has paved the road to study immune development at an unprecedented resolution. Single-cell RNA-sequencing studies have not only allowed us to efficiently chart the make-up of heterogeneous tissues, including their most rare cell populations, it also increasingly contributes to our understanding how different omics modalities interplay at a single cell resolution. Particularly for investigating the immune system, this means that these single-cell techniques can be integrated to combine and correlate RNA and protein data at the single-cell level. While RNA data usually reveals a large heterogeneity of a given population identified solely by a combination of surface protein markers, the integration of different omics modalities at a single cell resolution is expected to greatly contribute to our understanding of the immune system.
Authors 5
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Martijn Cordes Aachen Department of Biomedical Data Sciences Department of Immunology, Leiden University Medical Center
Leiden University Medical Center
Affiliation as printed
Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands
Department of Immunology, Leiden University Medical Center, Leiden, Netherlands
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Leiden University Medical Center
Affiliation as printed
Department of Immunology, Leiden University Medical Center, Leiden, Netherlands
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Erik B. van den Akker Aachen Department of Biomedical Data Sciences Department of Immunology, Leiden University Medical Center Novo Nordisk Foundation Center for Stem Cell Medicine (reNEW)
Leiden University Medical Center · Novo Nordisk Foundation Center for Stem Cell Medicine · Delft University of Technology
Affiliation as printed
Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands
Department of Immunology, Leiden University Medical Center, Leiden, Netherlands
Novo Nordisk Foundation Center for Stem Cell Medicine (reNEW), Leiden University Medical Center, Leiden, Netherlands
Pattern Recognition and Bioinformatics, Delft University of Technology, Delft, Netherlands
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Frank J. T. Staal corresponding Aachen Department of Immunology, Leiden University Medical Center Department of Pediatrics, Leiden University Medical Center Novo Nordisk Foundation Center for Stem Cell Medicine (reNEW)
Leiden University Medical Center · Novo Nordisk Foundation Center for Stem Cell Medicine
Affiliation as printed
Department of Immunology, Leiden University Medical Center, Leiden, Netherlands
Department of Pediatrics, Leiden University Medical Center, Leiden, Netherlands
Novo Nordisk Foundation Center for Stem Cell Medicine (reNEW), Leiden University Medical Center, Leiden, Netherlands
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Kirsten Canté-Barrett Aachen Department of Immunology, Leiden University Medical Center Novo Nordisk Foundation Center for Stem Cell Medicine (reNEW)
Leiden University Medical Center · Novo Nordisk Foundation Center for Stem Cell Medicine
Affiliation as printed
Department of Immunology, Leiden University Medical Center, Leiden, Netherlands
Novo Nordisk Foundation Center for Stem Cell Medicine (reNEW), Leiden University Medical Center, Leiden, Netherlands
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