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Published July 2013 | Supplemental Material + Published
Journal Article Open

Mapping Differentiation under Mixed Culture Conditions Reveals a Tunable Continuum of T Cell Fates

Abstract

Cell differentiation is typically directed by external signals that drive opposing regulatory pathways. Studying differentiation under polarizing conditions, with only one input signal provided, is limited in its ability to resolve the logic of interactions between opposing pathways. Dissection of this logic can be facilitated by mapping the system's response to mixtures of input signals, which are expected to occur in vivo, where cells are simultaneously exposed to various signals with potentially opposing effects. Here, we systematically map the response of naïve T cells to mixtures of signals driving differentiation into the Th1 and Th2 lineages. We characterize cell state at the single cell level by measuring levels of the two lineage-specific transcription factors (T-bet and GATA3) and two lineage characteristic cytokines (IFN-γ and IL-4) that are driven by these transcription regulators. We find a continuum of mixed phenotypes in which individual cells co-express the two lineage-specific master regulators at levels that gradually depend on levels of the two input signals. Using mathematical modeling we show that such tunable mixed phenotype arises if autoregulatory positive feedback loops in the gene network regulating this process are gradual and dominant over cross-pathway inhibition. We also find that expression of the lineage-specific cytokines follows two independent stochastic processes that are biased by expression levels of the master regulators. Thus, cytokine expression is highly heterogeneous under mixed conditions, with subpopulations of cells expressing only IFN-γ, only IL-4, both cytokines, or neither. The fraction of cells in each of these subpopulations changes gradually with input conditions, reproducing the continuous internal state at the cell population level. These results suggest a differentiation scheme in which cells reflect uncertainty through a continuously tuneable mixed phenotype combined with a biased stochastic decision rather than a binary phenotype with a deterministic decision.

Additional Information

© 2013 Antebi et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Received: September 25, 2012; Accepted: June 14, 2013; Published: July 30, 2013. This research was supported by grants from the International Human Frontier Science Program Organization, and the Israel Science Foundation (grant no. 812/08 and 1254/11). NF is incumbent of the Pauline Recanati Career Development Chair of Immunology. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. We thank Ziv Porat for technical help with ImageStream use and data analysis. We thank Naama Barkai, Benjamin Chain, Pierre Neveu, and Smita Krishnaswamy for comments on the manuscript and members of the Friedman lab for helpful discussions.

Attached Files

Published - journal.pbio.1001616.pdf

Supplemental Material - journal.pbio.1001616.s001.pdf

Supplemental Material - journal.pbio.1001616.s002.pdf

Supplemental Material - journal.pbio.1001616.s003.pdf

Supplemental Material - journal.pbio.1001616.s004.pdf

Supplemental Material - journal.pbio.1001616.s005.pdf

Supplemental Material - journal.pbio.1001616.s006.pdf

Supplemental Material - journal.pbio.1001616.s007.pdf

Supplemental Material - journal.pbio.1001616.s008.pdf

Supplemental Material - journal.pbio.1001616.s009.pdf

Supplemental Material - journal.pbio.1001616.s010.pdf

Supplemental Material - journal.pbio.1001616.s011.pdf

Supplemental Material - journal.pbio.1001616.s012.pdf

Supplemental Material - journal.pbio.1001616.s013.pdf

Supplemental Material - journal.pbio.1001616.s014.pdf

Supplemental Material - journal.pbio.1001616.s015.pdf

Supplemental Material - journal.pbio.1001616.s016.pdf

Supplemental Material - journal.pbio.1001616.s017.pdf

Supplemental Material - journal.pbio.1001616.s018.pdf

Supplemental Material - journal.pbio.1001616.s019.pdf

Supplemental Material - journal.pbio.1001616.s020.pdf

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Additional details

Created:
August 19, 2023
Modified:
October 24, 2023