Temporal mixture modelling of single-cell RNA-seq data resolves a CD4+ T cell fate bifurcation

Autor: Oliver Stegle, Kylie R. James, Ashraful Haque, William R. Heath, Tapio Lönnberg, Ruddy Montandon, Daniel Fernandez-Ruiz, Otzen Bagger F, Max Zwiessele, Stubbington Mjt, Svensson, Soon Msf, Oliver Billker, Lily Fogg, Sarah A. Teichmann, Fernando Souza-Fonseca-Guimaraes, Ismail Sebina, Neil D. Lawrence
Rok vydání: 2016
Předmět:
Popis: 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.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.
Databáze: OpenAIRE