A multi-approach and multi-scale platform to model CD4+ T cells responding to infections

Immune responses rely on a complex adaptive system in which the body and infections interact at multiple scales different compartments. We developed modular model of CD4+ T cells, uses four modeling approaches to integrate processes three spatial tissues. In each cell, signal transduction gene regulation are described by logical model, metabolism constraint-based models. Cell population dynamics an agent-based systemic cytokine concentrations ordinary differential equations. A Monte Carlo simulation algorithm allows information flow efficiently between modules separating time scales. Such modularity improves computational performance versatility facilitates data integration. validated our technology reproducing known experimental results, including differentiation patterns cells triggered combinations cytokines, metabolic IL2 these their response influenza infection. doing so, we added multi-scale insights single-scale studies demonstrated its predictive power discovering switch-like oscillatory behaviors that arise from nonlinear interwoven across identified inflamed lymph node’s ability retain naive as key mechanism generating emergent behaviors. envision generic framework encompassing it serve tool for understanding cellular molecular immunological problems through lens systems immunology.