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

Valentina Proserpio(European Bioinformatics Institute), Andrea Piccolo(Istituto Nazionale di Fisica Nucleare), Liora Haim-Vilmovsky(Wellcome Sanger Institute), Gozde Kar(European Bioinformatics Institute), Tapio Lönnberg(European Bioinformatics Institute), Valentine Svensson(European Bioinformatics Institute), Jhuma Pramanik(Wellcome Sanger Institute), Kedar Nath Natarajan(European Bioinformatics Institute), Weichao Zhai(University of Cambridge), Xiuwei Zhang(European Bioinformatics Institute), Giacomo Donati(King's College London), Melis Kayikci(MRC Laboratory of Molecular Biology), Jurij Kotar(University of Cambridge), Andrew N. J. McKenzie(MRC Laboratory of Molecular Biology), Ruddy Montandon(Wellcome Sanger Institute), Oliver Billker(Wellcome Sanger Institute), Steven Woodhouse(Medical Research Council), Pietro Cicuta(University of Cambridge), Mario Nicodemi(University of Naples Federico II), Sarah A. Teichmann(Wellcome Sanger Institute)
Genome biology
May 12, 2016
Cited by 70Open Access
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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.


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