Systems Modeling of Molecular Mechanisms Controlling Cytokine-driven CD4+ T Cell Differentiation and Phenotype Plasticity

Abstract

Differentiation of CD4+ T cells into effector or regulatory phenotypes is tightly controlled by the cytokine milieu, complex intracellular signaling networks and numerous transcriptional regulators. We combined experimental approaches and computational modeling to investigate the mechanisms controlling differentiation and plasticity of CD4+ T cells in the gut of mice. Our computational model encompasses the major intracellular pathways involved in CD4+ T cell differentiation into T helper 1 (Th1), Th2, Th17 and induced regulatory T cells (iTreg). Our modeling efforts predicted a critical role for peroxisome proliferator-activated receptor gamma (PPARγ) in modulating plasticity between Th17 and iTreg cells. PPARγ regulates differentiation, activation and cytokine production, thereby controlling the induction of effector and regulatory responses, and is a promising therapeutic target for dysregulated immune responses and inflammation. Our modeling efforts predict that following PPARγ activation, Th17 cells undergo phenotype switch and become iTreg cells. This prediction was validated by results of adoptive transfer studies showing an increase of colonic iTreg and a decrease of Th17 cells in the gut mucosa of mice with colitis following pharmacological activation of PPARγ. Deletion of PPARγ in CD4+ T cells impaired mucosal iTreg and enhanced colitogenic Th17 responses in mice with CD4+ T cell-induced colitis. Thus, for the first time we provide novel molecular evidence in vivo demonstrating that PPARγ in addition to regulating CD4+ T cell differentiation also plays a major role controlling Th17 and iTreg plasticity in the gut mucosa.

The CD4+ T cell regulatory network mediates inflammatory responses during acute hyperinsulinemia: a simulation study

“…For the construction of the network, the Boolean functions were defined based on available CD4+ T differentiation models [11][12][13] and experimental data for the reported interactions among a network of more than 90 nodes [Additional file 1: As part of the simplification we assumed that the signal produced by the TCR and its co-factors was active and enough to induce activation and ignored weak interactions as well as input and output nodes.…”

“…Paradoxically, it has been reported that the reduction of adipose tissue Treg cells seems to both, improve and worsen insulin resistance [37][38][39][40]. This kind of behavior could be linked to an underlying multi-stable dynamic mechanism such as that recently proposed to study CD4+ T cell differentiation and plasticity [11][12][13]. On the other hand, the general metabolic state of an individual also affects CD4+ T cells.…”

“…These probably play important roles in the onset of inflammatory responses, and their systemic impact remains unresolved. A starting point, involves understanding: (i) the complex regulatory network involved in the cell fate attainment of CD4+ T cell types [11][12][13], (ii) how such network responds to extracellular metabolic and microenvironmental conditions [14,15], and (iii) how the resulting system dynamically modulates the inflammatory and immune responses [1][2][3][4].…”

“…Furthermore, CD4+ T cells can plastically alter their expression patterns in response to environmental conditions [26][27][28][29]. Such complex and dynamic plastic behaviors have started to be explained at the system level using multi-stable network models [11][12][13].…”

(Compl)Ex-Th17–Tregcell inter-relationship

“…25 A recent report by Carbo et al demonstrates that PPARg activation promotes a phenotype switch from Th17-to-T reg cells and can thereby alleviate colitis. 26 Th17-to-T reg conversion only occurs in lean fat tissue and allows for insulin sensitivity and homeostasis, while Th17 accumulation in adipose tissue is associated with increased insulin resistance. 27 Factors with Dual T reg -and Th17-Promoting Functions…”