Abstract

Human Immunodeficiency Virus (HIV) infection of humans represents a complex biological system and a great challenge to public health. Novel approaches for the analysis and prediction of the infection dynamics based on a multi-scale integration of virus ontogeny and immune reactions are needed to deal with the systems’ complexity. The aim of our study is: (1) to formulate a multi-scale mathematical model of HIV infection; (2) to implement the model computationally following a hybrid approach; and (3) to calibrate the model by estimating the parameter values enabling one to reproduce the “standard” observed dynamics of HIV infection in blood during the acute phase of primary infection. The modeling approach integrates the processes of infection spread and immune responses in Lymph Nodes (LN) to that observed in blood. The spatio-temporal population dynamics of T lymphocytes in LN in response to HIV infection is governed by equations linking an intracellular regulation of the lymphocyte fate by intercellular cytokine fields. We describe the balance of proliferation, differentiation and death at a single cell level as a consequence of gene activation via multiple signaling pathways activated by IL-2, IFNa and FasL. Distinct activation thresholds are used in the model to relate different modes of cellular responses to the hierarchy of the relative levels of the cytokines. We specify a reference set of model parameter values for the fundamental processes in lymph nodes that ensures a reasonable agreement with viral load and CD4+ T cell dynamics in blood.

Highlights

  • Human Immunodeficiency Virus (HIV) type 1 infection represents a complex biological system [1,2,3,4]and a great challenge for cure strategies [5,6]

  • The maximal number of HIV-specific T cells in the computational domain is assumed to be ∼3 × 102. This corresponds to ∼10% of the lymph node space that can be occupied by T cells

  • The numerical code implementing the model is available upon request to the first author or can be directly assessed at https://github.com/MPS7/MultiScale-HIV

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Summary

Introduction

Human Immunodeficiency Virus (HIV) type 1 infection represents a complex biological system [1,2,3,4]and a great challenge for cure strategies [5,6]. Novel approaches for the analysis and prediction of the infection dynamics based on a multi-scale integration of virus ontogeny and immune reactions are needed to deal with the systems’ complexity [7,8,9,10] Such approaches have not yet been developed in the HIV modeling field [11,12,13]. The term “multi-scale models” is used with different meanings in different sciences In mathematics, it implies the presence of one or several small parameters, homogenization and averaging techniques. It implies the presence of one or several small parameters, homogenization and averaging techniques In physics, it is understood in the sense of microscopic-macroscopic scales (e.g., molecular dynamics versus continuum mechanics).

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