Science Immunology

Supplementary Materials

Supplementary Material for:

Single-cell RNA-seq and computational analysis using temporal mixture modeling resolves TH1/TFH fate bifurcation in malaria

Tapio Lönnberg, Valentine Svensson, Kylie R. James, Daniel Fernandez-Ruiz, Ismail Sebina, Ruddy Montandon, Megan S. F. Soon, Lily G. Fogg, Arya Sheela Nair, Urijah N. Liligeto, Michael J. T. Stubbington, Lam-Ha Ly, Frederik Otzen Bagger, Max Zwiessele, Neil D. Lawrence, Fernando Souza-Fonseca-Guimaraes, Patrick T. Bunn, Christian R. Engwerda, William R. Heath, Oliver Billker, Oliver Stegle,* Ashraful Haque,* Sarah A. Teichmann*

*Corresponding author. Email: st9{at} (S.A.T.); ashraful.haque{at} (A.H.); stegle{at} (O.S.)

Published 3 March 2017, Sci. Immunol. 2, eaal2192 (2017)
DOI: 10.1126/sciimmunol.aal2192

This PDF file includes:

  • Materials and Methods
  • Fig. S1. Enrichment of PbTII cells for adoptive transfer.
  • Fig. S2. Sorting strategy for PbTII cells.
  • Fig. S3. Flow cytometric assessment of TH1/TFH responses during PcAS infection.
  • Fig. S4. Expression of subset-specific marker genes in PbTII cells.
  • Fig. S5. Heterogeneity of activated PbTII cells and variability associated with cell size and differentiation.
  • Fig. S6. Heterogeneity of TH1/TFH signature gene expression in activated PbTII cells.
  • Fig. S7. Heterogeneity of the entire PbTII time series and the contribution of TH1 and TFH signature genes to the overall variability.
  • Fig. S8. The relationship of pseudotime with time points and with the TH1 assignment probability.
  • Fig. S9. Correlation of GPfates trends with TH1 and TFH signature genes.
  • Fig. S10. Expression of transgenic and endogenous TCRs.
  • Fig. S11. Expression of endogenous TCRs does not influence PbTII cell TH1/TFH differentiation.
  • Fig. S12. Robustness of top bifurcating genes across experiments.
  • Fig. S13. Flow cytometric validation of CXCR6 expression in PbTII cells before and after bifurcation.
  • Fig. S14. T cell–intrinsic Galectin-1 supports TH1 fate commitment.
  • Fig. S15. IL-10– and IFNγ-coproducing Tr1 cells derive from TH1 cells.
  • Fig. S16. Proliferative burst of activated PbTII cells.
  • Fig. S17. Kinetics of chemokine receptor expression during PcAS infection according to the GPfates model.
  • Fig. S18. Coexpression of chemokine receptors at single-cell level during PcAS infection.
  • Fig. S19. B cells are essential for TFH responses in PbTII cells during PcAS infection.
  • Fig. S20. Sorting strategy for myeloid cells.
  • Fig. S21. PCA of cDCs from naïve and infected mice.
  • Fig. S22. Differential gene expression between single splenic CD8α+ and CD8α cDCs.
  • Fig. S23. Differentially expressed genes between single naïve and day 3 PcASinfected cDCs.
  • Fig. S24. PCA of Ly6Chi monocytes from naïve and infected mice.
  • Fig. S25. Differentially expressed genes between single Ly6Chi monocytes from na?ve and day 3 PcAS-infected mice.
  • Fig. S26. Expression of immune signaling genes by cDCs and monocytes.
  • Fig. S27. Myeloid cell depletion in LysMCre × iDTR mice.
  • Legends for tables S1 to S4
  • References (49–64)

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Other Supplementary Material for this manuscript includes the following:

  • Table S1 (Microsoft Excel format). The expression data from day 7 after infection with functional annotations for genes (15, 37, 44?46).
  • Table S2 (Microsoft Excel format). TraCeR detection statistics for the original data set.
  • Table S3 (Microsoft Excel format). TraCeR detection statistics for the replicate data set.
  • Table S4 (Microsoft Excel format). Annotation of receptors, cytokines, and transcription factors.
  • Supplementary Computational Methods—The GPfates model (.pdf format).

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