The adaptive immune response is initiated by the interaction of the T cell antigen receptor/CD3 complex (TCR) with a cognate peptide bound to a MHC molecule. This interaction, along with the activity of co-stimulatory molecules and cytokines in the microenvironment, enables cells to proliferate and produce soluble factors that stimulate other branches of the immune response for inactivation of infectious agents. The intracellular activation signals are reinforced, amplified and diversified by a complex network of biochemical interactions, and includes the activity of molecules that modulate the activation process and stimulate the metabolic changes necessary for fulfilling the cell energy demands. We present an approach to the analysis of the main early signaling events of T cell activation by proposing a concise 46-node hybrid Boolean model of the main steps of TCR and CD28 downstream signaling, encompassing the activity of the anergy factor Ndrg1, modulation of activation by CTLA-4, and the activity of the nutrient sensor AMPK as intrinsic players of the activation process. The model generates stable states that reflect the overcoming of activation signals and induction of anergy by the expression of Ndrg1 in the absence of co-stimulation. The model also includes the induction of CTLA-4 upon activation and its competition with CD28 for binding to the co-stimulatory CD80/86 molecules, leading to stable states that reflect the activation arrest. Furthermore, the model integrates the activity of AMPK to the general pathways driving differentiation to functional cell subsets (Th1, Th2, Th17, and Treg). Thus, the network topology incorporates basic mechanism associated to activation, regulation and induction of effector cell phenotypes. The model puts forth a conceptual framework for the integration of functionally relevant processes in the analysis of the T CD4 cell function.

No abstract

T CD4+ cells are central to the adaptive immune response against pathogens. Their activation is induced by the engagement of the T-cell receptor by antigens, and of co-stimulatory receptors by molecules also expressed on antigen presenting cells. Then, a complex network of intracellular events reinforce, diversify and regulate the initial signals, including dynamic metabolic processes that strongly influence both the activation state and the differentiation to effector cell phenotypes. The regulation of cell metabolism is controlled by the nutrient sensor adenosine monophosphate-activated protein kinase (AMPK), which drives the balance between oxidative phosphorylation (OXPHOS) and glycolysis. Herein, we put forward a 51-node continuous mathematical model that describes the temporal evolution of the early events of activation, integrating a circuit of metabolic regulation into the main routes of signaling. The model simulates the induction of anergy due to defective co-stimulation, the CTLA-4 checkpoint blockade, and the differentiation to effector phenotypes induced by external cytokines. It also describes the adjustment of the OXPHOS-glycolysis equilibrium by the action of AMPK as the effector function of the T cell develops. The development of a transient phase of increased OXPHOS before induction of a sustained glycolytic phase during differentiation to the Th1, Th2 and Th17 phenotypes is shown. In contrast, during Treg differentiation, glycolysis is subsequently reduced as cell metabolism is predominantly polarized towards OXPHOS. These observations are in agreement with experimental data suggesting that OXPHOS produces an ATP reservoir before glycolysis boosts the production of metabolites needed for protein synthesis, cell function, and growth.

Upon antigen stimulation and co-stimulation, CD4+ T lymphocytes produce soluble factors that promote the activity of other immune cells against pathogens or modified tissues; this task must be performed in presence of a variety of environmental cytokines, nutrient, and oxygen conditions, which necessarily impact T cell function. The complexity of the early intracellular processes taking place upon lymphocyte stimulation is addressed by means of a mathematical model based on a network that integrates variable microenvironmental conditions with intracellular activating, regulatory, and metabolic signals. Besides the phenotype subsets considered in previous works (Th1, Th2, Th17, and Treg) the model includes the main early events in differentiation to the TFH phenotype. The model describes how cytokines, nutrients and oxygen availability regulate the differentiation of naïve CD4+ T cells into distinct subsets. Particularly, it shows that elevated amounts of an all-type mixture of effector cytokines under optimal nutrient and oxygen availability conduces the system towards a highly-polarized Th1 or Th2 state, while reduced cytokine levels allow the expression of the Th17, Treg or TFH subsets, or even hybrid phenotypes. On the other hand, optimal levels of an all-type cytokine mixture in combination with glutamine or tryptophan restriction implies a shift from Th1 to Th2 expression, while decreased levels of the Th2-inducing cytokine IL-4 leads to the rupture of the Th1-Th2 axis, allowing the manifestation of different (or hybrid) subsets. Modeling proposes that, even under reduced levels of pro-inflammatory cytokines, the sole action of hypoxia boost Th17 expression.