A reaction-diffusion model for Mycobacterium tuberculosis infection

TL;DR

This paper develops a reaction-diffusion model for Mycobacterium tuberculosis infection, analyzing how chemotaxis influences immune cell aggregation and granuloma formation through stability analysis, pattern formation, and numerical simulations.

Contribution

It introduces a novel reaction-diffusion model incorporating chemotaxis for Mtb infection and investigates pattern formation mechanisms relevant to granuloma development.

Findings

Chemotaxis can destabilize endemic equilibria leading to pattern formation.

Turing patterns correspond to granuloma structures in tuberculosis.

Numerical simulations confirm pattern emergence under certain conditions.

Abstract

This paper aims to investigate a reaction-diffusion model which describes in-host infection for Mycobacterium tuberculosis (Mtb) allowing random motion (i.e. linear diffusion) and chemotaxis (i.e. non-linear diffusion) of macrophages and bacteria populations. In particular, chemotaxis-driven aggregation of macrophages plays a fundamental role in the development of the Mtb infection and the production of chemokine - located in the infection site - represents an attractant for the uninfected macrophages, therefore we consider chemotaxis between infected macrophages and uninfected macrophages. The linear stability of the endemic equilibria is investigated. In particular, by looking for conditions guaranteeing that an equilibrium, stable in the absence of diffusion, becomes unstable when diffusion is allowed, the formation of Turing patterns - that biologically represent the formation of granuloma initiated by the immune cells - is investigated. The weakly nonlinear analysis is performed to deeply explore the patterns amplitude. Furthermore, via numerical simulations, the formation of Turing patterns is analysed.