Diverse continuum of CD4+ T-cell states is determined by hierarchical additive integration of cytokine signals

Inbal Eizenberg-Magar, Jacob Rimer, Irina Zaretsky, David Lara-Astiaso, Shlomit Reich-Zeliger, Nir Friedman*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

42 Scopus citations

Abstract

During cell differentiation, progenitor cells integrate signals from their environment that guide their development into specialized phenotypes. The ways by which cells respond to complex signal combinations remain difficult to analyze and model. To gain additional insight into signal integration, we systematically mapped the response of CD4+ T cells to a large number of input cytokine combinations that drive their differentiation. We find that, in response to varied input combinations, cells differentiate into a continuum of cell fates as opposed to a limited number of discrete phenotypes. Input cytokines hierarchically influence the cell population, with TGFβ being most dominant followed by IL-6 and IL-4. Mathematical modeling explains these results using additive signal integration within hierarchical groups of input cytokine combinations and correctly predicts cell population response to new input conditions. These findings suggest that complex cellular responses can be effectively described using a segmented linear approach, providing a framework for prediction of cellular responses to new cytokine combinations and doses, with implications to fine-tuned immunotherapies.

Original languageAmerican English
Pages (from-to)E6447-E6456
JournalProceedings of the National Academy of Sciences of the United States of America
Volume114
Issue number31
DOIs
StatePublished - 1 Aug 2017
Externally publishedYes

Bibliographical note

Funding Information:
We thank members of the laboratory of N.F. for helpful comments and discussions. This research was supported by Israel Science Foundation Grant 1184/15 and the David and Fela Shapell Family Foundation Israel National Center for Personalized Medicine Fund for Preclinical Studies.

Publisher Copyright:
© 2017, National Academy of Sciences. All rights reserved.

Keywords

  • CD4 T-cell lineages
  • Cell differentiation
  • Mathematical modeling
  • Systems immunology
  • T cells

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