Journal article
Single-cell RNA-seq and computational analysis using temporal mixture modeling resolves TH1/TFH fate bifurcation in malaria
T Lönnberg, V Svensson, KR James, D Fernandez-Ruiz, I Sebina, R Montandon, MSF Soon, LG Fogg, AS Nair, UN Liligeto, MJT Stubbington, LH Ly, FO Bagger, M Zwiessele, ND Lawrence, F Souza-Fonseca-Guimaraes, PT Bunn, CR Engwerda, WR Heath, O Billker Show all
Science Immunology | Published : 2017
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 ..
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Awarded by Australian Biosecurity Cooperative Research Centre for Emerging Infectious Diseases
Funding Acknowledgements
This work was supported by Wellcome Trust (no. WT098051), European Research Council grant ThSWITCH (no. 260507), Australian National Health and Medical Research Council Project grant (number 1028641), and Career Development Fellowship (no. 1028643), University of Queensland; Australian Infectious Diseases Research Centre grants; and the Lister Institute for Preventive Medicine. K.R.J. was supported by grants from European Molecular Biology Laboratory Australia and OzEMalaR. F.O.B. was supported by the Lundbeck Foundation. M.Z. was supported by the Marie Curie Initial Training Networks grant "Machine Learning for Personalized Medicine" (EU FP7-PEOPLE Project Ref 316861, MLPM2012).