Temporal mixture modelling of single-cell RNA-seq data resolves a CD4 + T cell fate bifurcation
Temporal mixture modelling of single-cell RNA-seq data resolves a CD4 + T cell fate bifurcation
Abstract Differentiation of na?ve CD4+ T cells into functionally distinct T helper subsets is crucial for the orchestration of immune responses. Due to multiple levels of 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 RNA transcriptomics and computational modelling of temporal mixtures, we reconstructed the developmental trajectories of Th1 and Tfh cell populations during Plasmodium infection in mice at single-cell resolution. These cell fates emerged from a common, highly proliferative and metabolically active precursor. Moreover, by tracking clonality from T cell receptor sequences, we infer that ancestors derived from the same na?ve CD4+ T cell can concurrently populate both Th1 and Tfh subsets. We further found that precursor T cells were coached towards a Th1 but not a Tfh fate by monocytes/macrophages. The integrated genomic and computational approach we describe is applicable for analysis of any cellular system characterized by differentiation towards multiple fates. One Sentence SummaryUsing single-cell RNA sequencing and a novel unsupervised computational approach, we resolve the developmental trajectories of two CD4+ T cell fates in vivo, and show that uncommitted T cells are externally influenced towards one fate by inflammatory monocytes.
Billker Oliver、Zwiessele Max、Teichmann Sarah A.、Fogg Lily G、Stegle Oliver、Fernandez-Ruiz Daniel、Sebina Ismail、Montandon Ruddy、Soon Megan S. F.、Stubbington Michael J. T.、Lawrence Neil、L?nnberg Tapio、Souza-Fonseca-Guimaraes Fernando、Heath William R.、Haque Ashraful、James Kylie R、Otzen Bagger Frederik、Svensson Valentine
Wellcome Trust Sanger InstituteDepartment of Computer Science, University of SheffieldEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI)||Wellcome Trust Sanger InstituteQIMR Berghofer Medical Research InstituteEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI)Department of Microbiology and Immunology, The Peter Doherty Institute, University of MelbourneQIMR Berghofer Medical Research InstituteWellcome Trust Sanger InstituteQIMR Berghofer Medical Research InstituteEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI)||Wellcome Trust Sanger InstituteDepartment of Computer Science, University of SheffieldEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI)||Wellcome Trust Sanger InstituteQIMR Berghofer Medical Research InstituteDepartment of Microbiology and Immunology, The Peter Doherty Institute, University of Melbourne||The Australian Research Council Centre of Excellence in Advanced Molecular Imaging, The University of MelbourneQIMR Berghofer Medical Research InstituteQIMR Berghofer Medical Research InstituteEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI)||Wellcome Trust Sanger Institute||Department of Haematology, University of Cambridge||National Health Service (NHS) Blood and TransplantEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI)
基础医学细胞生物学分子生物学
Billker Oliver,Zwiessele Max,Teichmann Sarah A.,Fogg Lily G,Stegle Oliver,Fernandez-Ruiz Daniel,Sebina Ismail,Montandon Ruddy,Soon Megan S. F.,Stubbington Michael J. T.,Lawrence Neil,L?nnberg Tapio,Souza-Fonseca-Guimaraes Fernando,Heath William R.,Haque Ashraful,James Kylie R,Otzen Bagger Frederik,Svensson Valentine.Temporal mixture modelling of single-cell RNA-seq data resolves a CD4 + T cell fate bifurcation[EB/OL].(2025-03-28)[2025-08-02].https://www.biorxiv.org/content/10.1101/074971.点此复制
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