Abstract
During an adaptive immune response from pathogen invasion, multiple cytokines are produced by various immune cells interacting jointly at the cellular level to mediate several processes. For example, studies have shown that regulation of interleukin-4 (IL-4) correlates with interleukin-2 (IL-2) induced lymphocyte proliferation. This motivates the need to better understand and model the mechanisms driving the dynamic interplay of proliferation of lymphocytes with the complex interaction effects of cytokines during an immune response. To address this challenge, we adopt a hybrid computational approach comprising of continuous, discrete and stochastic non-linear model formulations to predict a system-level immune response as a function of multiple dependent signals and interacting agents including cytokines and targeted immune cells. We propose a hybrid ordinary differential equation-based (ODE) multicellular model system with a stochastic component of antigen microscopic states denoted as Multiscale Multicellular Quantitative Evaluator (MMQE) implemented using MATLAB. MMQE combines well-defined immune response network-based rules and ODE models to capture the complex dynamic interactions between the proliferation levels of different types of communicating lymphocyte agents mediated by joint regulation of IL-2 and IL-4 to predict the emergent global behavior of the system during an immune response. We model the activation of the immune system in terms of different activation protocols of helper T cells by the interplay of independent biological agents of classic antigen-presenting cells (APCs) and their joint activation which is confounded by the exposure time to external pathogens. MMQE quantifies the dynamics of lymphocyte proliferation during pathogen invasion as bivariate distributions of IL-2 and IL-4 concentration levels. Specifically, by varying activation agents such as dendritic cells (DC), B cells and their joint mechanism of activation, we quantify how lymphocyte activation and differentiation protocols boost the immune response against pathogen invasion mediated by a joint downregulation of IL-4 and upregulation of IL-2. We further compare our in-silico results to in-vivo and in-vitro experimental studies for validation. In general, MMQE combines intracellular and extracellular effects from multiple interacting systems into simpler dynamic behaviors for better interpretability. It can be used to aid engineering of anti-infection drugs or optimizing drug combination therapies against several diseases.
Highlights
The immune system is composed of a large variety of cells and mediators that interact in a complex and dynamic network to protect the host against foreign pathogens and to simultaneously maintain tolerance towards self-antigens
We motivate the key players during an adaptive immune response and propose a hybrid ODE model with a stochastic component framework denoted as Multiscale Multicellular Quantitative Evaluator (MMQE) which combines network-based rules and ordinary differential equations-based (ODE) models to study the dynamic proliferation structure of different types of communicating lymphocytes mediated by the joint signaling of key cytokines
We investigate the joint effects of IL-2 and IL-4 stimulation and the heterogeneous lymphocyte proliferation changes during an immune response using a hybrid ODE model with a stochastic component framework describing the microscopic state of antigen invasion
Summary
The immune system is composed of a large variety of cells and mediators that interact in a complex and dynamic network to protect the host against foreign pathogens and to simultaneously maintain tolerance towards self-antigens. This system is categorized into innate and adaptive immunity, both of which are key biological systems in generating acute and chronic inflammatory responses (Belardelli and Ferrantini, 2002). Most mechanistic models applied to study immune response are population driven models They include specific mechanisms/ processes in a very simplified compartmental manner and do not account for joint extracellular and intracellular interactions at multiscale and multicellular levels (Handel et al, 2020). We motivate the key players during an adaptive immune response and propose a hybrid ODE model with a stochastic component framework denoted as Multiscale Multicellular Quantitative Evaluator (MMQE) which combines network-based rules and ordinary differential equations-based (ODE) models to study the dynamic proliferation structure of different types of communicating lymphocytes mediated by the joint signaling of key cytokines
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