Lönnberg, T., Svensson, V., James, K.R. et al. (20 more authors) (2017) Single-cell RNA-seq and computational analysis using temporal mixture modeling resolves TH1/TFH fate bifurcation in malaria. Science Immunology, 2 (9). eaal2192. ISSN 2470-9468
Abstract
Differentiation of naïve CD4+ T cells into functionally distinct T helper (TH) subsets is crucial for the orchestration of immune responses. Because of extensive heterogeneity and multiple overlapping transcriptional programs in differentiating T cell populations, this process has remained a challenge for systematic dissection in vivo. By using single-cell transcriptomics and computational analysis with a temporal mixtures of Gaussian processes model, termed GPfates, we reconstructed the developmental trajectories of TH1 and TFH (T follicular helper) cells during blood-stage Plasmodium infection in mice. By tracking clonality using endogenous T cell receptor sequences, we first demonstrated that TH1/TFH bifurcation had occurred at both population and single-clone levels. Next, we identified genes whose expression was associated with TH1 or TFH fates and demonstrated a T cell–intrinsic role for Galectin-1 in supporting TH1 differentiation. We also revealed the close molecular relationship between TH1 and interleukin-10–producing Tr1 cells in this infection. TH1 and TFH fates emerged from a highly proliferative precursor that up-regulated aerobic glycolysis and accelerated cell cycling as cytokine expression began. Dynamic gene expression of chemokine receptors around bifurcation predicted roles for cell-cell interaction in driving TH1/TFH fates. In particular, we found that precursor TH cells were coached toward a TH1 but not a TFH fate by inflammatory monocytes. Thus, by integrating genomic and computational approaches, our study has provided two unique resources: a database, www.PlasmoTH.org, which facilitates discovery of novel factors controlling TH1/TFH fate commitment, and, more generally, GPfates, a modeling framework for characterizing cell differentiation toward multiple fates.
Metadata
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Copyright, Publisher and Additional Information: | © 2017, American Association for the Advancement of Science. This is an author-produced version of a paper subsequently published in Science Immunology. Uploaded in accordance with the publisher's self-archiving policy. | ||||
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Institution: | The University of Sheffield | ||||
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) | ||||
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Depositing User: | Symplectic Sheffield | ||||
Date Deposited: | 12 Dec 2019 16:28 | ||||
Last Modified: | 12 Dec 2019 16:34 | ||||
Status: | Published | ||||
Publisher: | American Association for the Advancement of Science | ||||
Refereed: | Yes | ||||
Identification Number: | https://doi.org/10.1126/sciimmunol.aal2192 |