Spatial Lymphocyte Dynamics in Lymph Nodes Predicts the Cytotoxic T Cell Frequency Needed for HIV Infection Control

Dmitry Grebennikov,Nikolay Bessonov,Gennady Bocharov,Anass Bouchnita,Vitaly Volpert,Andreas Meyerhans

doi:10.3389/fimmu.2019.01213

Abstract

The surveillance of host body tissues by immune cells is central for mediating their defense function. In vivo imaging technologies have been used to quantitatively characterize target cell scanning and migration of lymphocytes within lymph nodes (LNs). The translation of these quantitative insights into a predictive understanding of immune system functioning in response to various perturbations critically depends on computational tools linking the individual immune cell properties with the emergent behavior of the immune system. By choosing the Newtonian second law for the governing equations, we developed a broadly applicable mathematical model linking individual and coordinated T-cell behaviors. The spatial cell dynamics is described by a superposition of autonomous locomotion, intercellular interaction, and viscous damping processes. The model is calibrated using in vivo data on T-cell motility metrics in LNs such as the translational speeds, turning angle speeds, and meandering indices. The model is applied to predict the impact of T-cell motility on protection against HIV infection, i.e., to estimate the threshold frequency of HIV-specific cytotoxic T cells (CTLs) that is required to detect productively infected cells before the release of viral particles starts. With this, it provides guidance for HIV vaccine studies allowing for the migration of cells in fibrotic LNs.

Highlights

The surveillance of host body tissues by cells of the immune system is central for mediating defense functions against invading pathogens and tumor cells [1, 2]
physical models (PMs) of lymphocyte migration dynamics derived from the Newtonian second law offer the possibility to define cell motions in terms of the forces generated by the environment and the cell itself
Multicellular systems dynamics can be accurately described by biophysical models as reviewed recently [14, 25]

Summary

Introduction

The surveillance of host body tissues by cells of the immune system is central for mediating defense functions against invading pathogens and tumor cells [1, 2]. In vivo imaging technologies have been used to quantitatively characterize target cell scanning and migration dynamics of lymphocytes within LNs [4, 5]. The translation of these quantitative insights into a predictive understanding of immune system functioning in response to various perturbations critically depends on the availability of computational tools linking the individual immune cell properties with the systems response as a whole [6]. CAMs incorporate experimentally defined characteristics of cell motion and, simulate cell dynamics based on actual data, they lack quantifiable links to the underlying biophysical interactions between cells in multicellular environments and to intrinsic cell motility parameters [12]. PMs of individual cells and coordinated cell migration represent a general and generic way to describe and predict the multicellular system dynamics for a broad range of cell numbers and external conditions [13, 14]

Methods

Results

Conclusion