Microbiology & Immunology - Research Publications

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    Temporal mixture modelling of single-cell RNA-seq data resolves a CD4+ T cell fate bifurcation
    Lönnberg, T ; Svensson, V ; James, K ; Fernandez-Ruiz, D ; Sebina, I ; Montandon, R ; Soon, M ; Fogg, L ; Stubbington, M ; Otzen Bagger, F ; Zwiessele, M ; Lawrence, N ; Souza-Fonseca-Guimaraes, F ; Heath, W ; Billker, O ; Stegle, O ; Haque, A ; Teichmann, S ( 2016)
    Differentiation of naïve 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 naïve 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.

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    Using 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.