ArticleMolecular biology of the cell2022
Emergent dynamics of a three-node regulatory network explain phenotypic switching and heterogeneity: a case study of Th1/Th2/Th17 cell differentiation.
Article in Molecular biology of the cell, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
8 citing papers in PubMed, 15 citations in OpenAlex.
- The Immunogenetic Landscape of Allergic Rhinitis: from Cellular Effectors to Gene Regulation and Targeted Therapies.International journal of biological sciences · 2026Review
- Article
- Emergent dynamics of cellular decision making in multi-node mutually repressive regulatory networks.Journal of the Royal Society, Interface · 2025Article
- The interaction between gut microbiota and host DNA methylation in the pathogenesis and therapy of inflammatory bowel disease.Frontiers in microbiology · 2025Review
- Multistability and predominant hybrid phenotypes in a four node mutually repressive network of Th1/Th2/Th17/Treg differentiation.NPJ systems biology and applications · 2024Article
- Network topology and interaction logic determine states it supports.NPJ systems biology and applications · 2024Review
- Global quantitative understanding of non-equilibrium cell fate decision-making in response to pheromone.iScience · 2023Article
- T-helper cells flexibility: the possibility of reprogramming T cells fate.Frontiers in immunology · 2023Review
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Naïve helper (CD4+) T-cells can differentiate into distinct functional subsets including Th1, Th2, and Th17 phenotypes. Each of these phenotypes has a "master regulator"-T-bet (Th1), GATA3 (Th2), and RORγT (Th17)-that inhibits the other two master regulators. Such mutual repression among them at a transcriptional level can enable multistability, giving rise to six experimentally observed phenotype, Th1, Th2, Th17, hybrid Th/Th2, hybrid Th2/Th17, and hybrid Th1/Th17. However, the dynamics of switching among these phenotypes, particularly in the case of epigenetic influence, remain unclear. Here through mathematical modeling, we investigated the coupled transcription-epigenetic dynamics in a three-node mutually repressing network to elucidate how epigenetic changes mediated by any master regulator can influence the transition rates among different cellular phenotypes. We show that the degree of plasticity exhibited by one phenotype depends on relative strength and duration of mutual epigenetic repression mediated among the master regulators in a three-node network. Further, our model predictions can offer putative mechanisms underlying relatively higher plasticity of Th17 phenotype as observed in vitro and in vivo. Together, our modeling framework characterizes phenotypic plasticity and heterogeneity as an outcome of emergent dynamics of a three-node regulatory network, such as the one mediated by T-bet/GATA3/RORγT.
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