Single-cell analysis of CD4+ T-cell differentiation reveals three major cell states and progressive acceleration of proliferation
Year: 2016
Type: article
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.
Source: Genome biology
Authors: Valentina Proserpio, Andrea Piccolo, Liora Haim-Vilmovsky, Gozde Kar, Tapio Lönnberg, Valentine Svensson, Jhuma Pramanik, Kedar Nath Natarajan, Weichao Zhai, Xiuwei Zhang, Giacomo Donati, Melis Kayikci, Jurij Kotar, Andrew N. J. McKenzie, Ruddy Montandon, Oliver Billker, Steven Woodhouse, Pietro Cicuta, Mario Nicodemi, Sarah A. Teichmann
Institutions: European Bioinformatics Institute, Wellcome Sanger Institute, Istituto Nazionale di Fisica Nucleare, Istituto Nazionale di Fisica Nucleare, Sezione di Napoli, University of Naples Federico II, University of Cambridge, King's College London, MRC Laboratory of Molecular Biology, Wellcome/MRC Cambridge Stem Cell Institute, Wellcome Trust
Language: English
Topic: T-cell and B-cell Immunology
Subfield: Immunology
Field: Immunology and Microbiology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $5,490
Funders: National Science Foundation, Microsoft Research, Wellcome Trust, European Bioinformatics Institute, Lister Institute of Preventive Medicine, Agency for Science, Technology and Research, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, National Institutes of Health, Directorate-General for Research and Innovation, Medical Research Council, European Research Council, National Institute of Diabetes and Digestive and Kidney Diseases
Awards: G2117226865, G2285996095, Innate lymphoid cells in immunity and disease., G3752093831, An evolutionary approach to understanding and predicting protein structures using contact networks, G458884304, G4612446324, Innate lymphoid cells in immunity and disease., G6409071814, G6949437775, G8483203165, G9000215225
OpenAlex ID: W2371748820
