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Single-cell analysis of CD4+ T-cell differentiation reveals three major cell states and progressive acceleration of proliferation.

Published version
Peer-reviewed

Type

Article

Change log

Authors

Proserpio, Valentina 
Piccolo, Andrea 
Haim-Vilmovsky, Liora 
Kar, Gozde 
Lönnberg, Tapio 

Abstract

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.

Description

Keywords

Adaptive immunity, CD4+ T cells, Cell cycle, Differentiation, Live imaging, Single-cell RNA-seq, Animals, CD4-Positive T-Lymphocytes, Cell Differentiation, Cell Proliferation, Cells, Cultured, Cytokines, Female, Gene Expression Profiling, Malaria, Mice, Mice, Inbred C57BL, Models, Biological, Sequence Analysis, RNA, Single-Cell Analysis, Transcriptome

Journal Title

Genome Biol

Conference Name

Journal ISSN

1474-7596
1474-760X

Volume Title

17

Publisher

Springer Science and Business Media LLC