Multi-Approach and Multi-Scale Model of CD4+ T Cells Predicts Switch-Like and Oscillatory Emergent Behaviors in Inflammatory Response to Infection

Abstract

Immune responses rely on a complex adaptive system in which the body and infections interact at multiple scales and in different compartments. We developed a modular model of CD4+ T cells which uses four modeling approaches to integrate processes taking place at three spatial scales in different tissues. In each cell, signal transduction and gene regulation are described by a logical model, metabolism by constraint-based models. Cell population dynamics are described by an agent-based model and systemic cytokine concentrations by ordinary differential equations. A Monte Carlo simulation algorithm allows information to flow efficiently between the four modules by separating the time scales. Such modularity improves computational performance and versatility, and facilitates data integration. Our technology helps capture emergent behaviors that arise from nonlinear dynamics interwoven across three scales. Multi-scale insights added to single-scale studies allowed us to identify switch-like and oscillatory behaviors of CD4+ T cells at the population level, which are both novel and immunologically important. We envision our model and the generic framework encompassing it to become the foundation of a more comprehensive model of the human immune system. Immune responses mediated by CD4+ T cells involve complex interactions among immune cells and molecules.Resting CD4+ T cells are activated by antigen-presenting cells and cytokines, further differentiate, and secrete cytokines to act against pathogens and abnormal cells. They also recruit other immune cells to the sites of infection. Depending on the cytokine milieu, activated CD4+ T cells may differentiate into various phenotypes including T helper type 1 (Th1), T helper type 2 (Th2), T helper type 17 (Th17), and induced T regulatory cells (Tregs) [1]. To produce the energy and molecular precursors required to achieve a specific mixture of phenotypes, activated CD4+ T cells utilize certain signaling and metabolic pathways such as aerobic glycolysis [1,2]. To fully understand these complex interactions underlying the dynamics of CD4+ T cell immune response, we must integrate events taking place at various spatial, temporal, and organizational scales, such as immune cell proliferation, development, and migration; cell-cell and cell-molecule interactions; intracellular signaling; and intracellular metabolism.Multi-scale modeling aims to integrate spatial, temporal, and organizational scales of biological systems. This strategy has been used extensively in immunology. For instance, multi-scale models have been developed to study infections and inflammatory processes [3], and the immune response to the Helicobacter pylori infection [4]. Such integration could be achieved by combining different modeling approaches, such as ordinary differential equations (ODEs) and partial differential equations (PDEs) for the chemical kinetics and transport of molecular species (in terms of concentrations) in and across different cells, organs or tissues; agent-based modeling (ABM) for cell...

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