AUTHOR=Puniya Bhanwar Lal , Todd Robert G. , Mohammed Akram , Brown Deborah M. , Barberis Matteo , Helikar Tomáš 

TITLE=A Mechanistic Computational Model Reveals That Plasticity of CD4+ T Cell Differentiation Is a Function of Cytokine Composition and Dosage

JOURNAL=Frontiers in Physiology

VOLUME=Volume 9 - 2018

YEAR=2018

URL=https://www.frontiersin.org/journals/physiology/articles/10.3389/fphys.2018.00878

DOI=10.3389/fphys.2018.00878

ISSN=1664-042X

ABSTRACT=CD4+ T cells provide cell mediated-immunity in response to various antigens.  During an immune response, naïve CD4+ T cells differentiate into specialized effector T helper (Th1, Th2, and Th17) cells and induced regulatory (iTreg) cells based on a cytokine milieu. In recent studies, complex phenotypes resembling more than one classical T cell lineage have been observed experimentally. Herein, we sought to characterize the capacity of T cell differentiation in response to the complex extracellular environment. We constructed a comprehensive Boolean (logic-based) computational model of the signal transduction that regulates T cell differentiation. The model’s dynamics were characterized and analyzed under 511 possible environmental conditions, under which the model predicted both the classical and previously reported T cell phenotypes as well as novel complex (mixed) phenotypes such as Th1-Th2-Treg, Th1-Th17-Treg, and Th1-Th2-Th17-Treg. The complex phenotypes can co-express transcription factors (TFs) related to multiple differentiated T cell lineages. Analyses of the model suggest that lineage decision is regulated by both compositions and dosage of signals that constitute the extracellular environment. In this regard, we first characterized specific patterns of extracellular environments that result in novel T cell phenotypes.  Next, we predicted inputs that can regulate the transition between canonical and complex T cell phenotypes in a dose-dependent manner. Finally, we predicted optimal levels of inputs that can simultaneously maximize the activity of multiple lineage-specifying TFs and that can drive a phenotype towards one of the co-expressed TFs. For example, our results suggest that low activities of T-cell receptor (TCR) ligand, IFN- γ, IL-27, and high activities of IL-18 and IL-4 favor the complex Th1-Th2 phenotype. We also predicted that IL-18 might have a dominant role over IL-4 in regulating Tbet (T-box expressed in T cells)/GATA3 (GATA binding protein 3) balance within the complex Th1-Th2 phenotype. In conclusion, our study provides new insights into the plasticity of CD4+ T cell differentiation, as well as a tool to design testable hypotheses for the generation of complex T cell phenotypes by various input combinations and dosage.