Single-cell RNA-seq and computational analysis using temporal mixture modeling resolves T _H 1/T _FH fate bifurcation in malaria

Abstract

Differentiation of naïve CD4 + T cells into functionally distinct T helper subsets is crucial for the orchestration of immune responses. Due to extensive heterogeneity and multiple overlapping transcriptional programs in differentiating T cell populations, this process has remained a * Correspondence to: st9@sanger.ac.uk, Ashraful.Haque@qimrberghofer.edu.au or stegle@ebi.ac.uk. # denotes equal contribution † denotes equal contribution Author contributions TL and KRJ performed the single-cell RNA-seq experiments. VS developed the GPfates model in collaboration with MZ, NDL, OS and SAT. DFR and WRH generated the PbTII mouse model. KRJ, RM, IS, MSFS, LGF, ASN, UL, FSFG, PTB and CRE performed the mouse experiments. TL, VS, KRJ, LHL and FOB analysed the data and interpreted the results MJTS performed the TCR clonality analysis. TL, KRJ, RM, OB, AH and SAT designed the experiments. OS, AH and SAT cosupervised the study. TL, VS, KRJ, OS, AH and SAT wrote the manuscript. All authors have read and approved the manuscript. Competing interestsThe authors declare no competing interests. Data and materials availabilityThe data presented in this paper is publically available in the ArrayExpress database with accession number E-MTAB-4388. Europe PMC Funders Group Europe PMC Funders Author ManuscriptsEurope PMC Funders Author Manuscripts challenge for systematic dissection in vivo. By using single-cell transcriptomics and computational analysis using a temporal mixtures of Gaussian processes model, termed GPfates, we reconstructed the developmental trajectories of Th1 and Tfh cells during blood-stage Plasmodium infection in mice. By tracking clonality using endogenous TCR 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 a Th1 differentiation. We also revealed the close molecular relationship between Th1 and IL-10-producing Tr1 cells in this infection. Th1 and Tfh fates emerged from a highly proliferative precursor that upregulated aerobic glycolysis and accelerated cell cycling as cytokine expression began. Dynamic gene expression of chemokine receptors around bifurcation predicted roles for cell-cell in driving Th1/Tfh fates. In particular, we found that precursor Th cells were coached towards 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 modelling framework for characterizing cell differentiation towards multiple fates.

SpatialDE - Identification of spatially variable genes

“…First used in geostatistics 31 , GP models have been applied to test for differential gene expression over time 32 , including the analysis of bifurcation points 26 , and general tests for temporal variability 25,[33][34][35] .…”

“…Fig. 8), an application of SpatialDE for which previous methods exist [24][25][26] , but previous methods are likely less computationally efficient than SpatialDE. In principle, SpatialDE can also be applied to 3-dimensional data, e.g., from serial sections of 2-dimensional data, or from in situ sequencing when such technologies mature 11,12 .…”

STREAM: Single-cell Trajectories Reconstruction, Exploration And Mapping of omics data

“…In fact, more than 50 methods have been proposed for this task making a systematic comparison unfeasible for the scope of this manuscript. For this reason, we compared STREAM with 10 state-of-the-art methods well recognized and commonly used by the single-cell community: Monocle2, scTDA, Wishbone, TSCAN, SLICER, DPT, GPFates, Mpath, SCUBA and PHATE 12,[16][17][18][19][20][21][22][23][24] .…”

Dynamic phenotypes: illustrating a single-cell odyssey

“…For example, the development and heterogeneity and molecular trajectories of T helper (Th) subsets Th1 and Tfh cells during infection with P. chabaudi chabaudi AS, a rodent-infective strains of malaria, were monitored with a computational modeling strategy (a mixture of Gaussian processes models) with scRNA-seq (Lönnberg et al 2017). Those important findings demonstrated that splenic monocytes/macrophages, dendritic cells, and other myeloid cells could support the Th1 fate by influencing bifurcation during infection.…”