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Single-cell analysis of CD4+ T-cell differentiation reveals three major cell states and progressive acceleration of proliferation
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2016 (English)In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 17, article id 103Article in journal (Refereed) Published
Abstract [en]

BACKGROUND: Differentiation of lymphocytes is frequently accompanied by cell cycle changes, interplay that is of central importance for immunity but is still incompletely understood. Here, we interrogate and quantitatively model how proliferation is linked to differentiation in CD4+ T cells.

RESULTS: We perform ex vivo single-cell RNA-sequencing of CD4+ T cells during a mouse model of infection that elicits a type 2 immune response and infer that the differentiated, cytokine-producing cells cycle faster than early activated precursor cells. To dissect this phenomenon quantitatively, we determine expression profiles across consecutive generations of differentiated and undifferentiated cells during Th2 polarization in vitro. We predict three discrete cell states, which we verify by single-cell quantitative PCR. Based on these three states, we extract rates of death, division and differentiation with a branching state Markov model to describe the cell population dynamics. From this multi-scale modelling, we infer a significant acceleration in proliferation from the intermediate activated cell state to the mature cytokine-secreting effector state. We confirm this acceleration both by live imaging of single Th2 cells and in an ex vivo Th1 malaria model by single-cell RNA-sequencing.

CONCLUSION: The link between cytokine secretion and proliferation rate holds both in Th1 and Th2 cells in vivo and in vitro, indicating that this is likely a general phenomenon in adaptive immunity.

Place, publisher, year, edition, pages
BioMed Central, 2016. Vol. 17, article id 103
Keywords [en]
CD4+ T cells, Adaptive immunity, Single-cell RNA-seq, Cell cycle, Differentiation, Live imaging
National Category
Cell and Molecular Biology
Identifiers
URN: urn:nbn:se:umu:diva-165847DOI: 10.1186/s13059-016-0957-5ISI: 000375963300001PubMedID: 27176874OAI: oai:DiVA.org:umu-165847DiVA, id: diva2:1379085
Funder
Wellcome trust, 100963Wellcome trust, WT098051NIH (National Institute of Health), ID 1U54DK107977-01Available from: 2019-12-16 Created: 2019-12-16 Last updated: 2019-12-18Bibliographically approved

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