A reaction-diffusion model to understand granulomas formation inside secondary lobule during tuberculosis infection

PLoS One. 2020 Sep 16;15(9):e0239289. doi: 10.1371/journal.pone.0239289. eCollection 2020.

Abstract

Mycobacterium tuberculosis (Mtb) is the causative agent for tuberculosis, the most extended infectious disease around the world. When Mtb enters inside the pulmonary alveolus it is rapidly phagocytosed by the alveolar macrophage. Although this controls the majority of inhaled microorganisms, in this case, Mtb survives inside the macrophage and multiplies. A posterior chemokine and cytokine cascade generated by the irruption of monocytes, neutrophils and posteriorly, by T-cells, does not necessarily stop the growth of the granuloma. Interestingly, the encapsulation process built by fibroblasts is able to surround the lesion and stop its growing. The success of this last process determines if the host enters in an asymptomatic latent state or continues into a life-threatening and infective active tuberculosis disease (TB). Understanding such dichotomic process is challenging, and computational modeling can bring new ideas. Thus, we have modeled the different stages of the infection, first in a single alveolus (a sac with a radius of 0.15 millimeters) and, second, inside a secondary lobule (a compartment of the lungs of around 3 cm3). We have employed stochastic reaction-diffusion equations to model the interactions among the cells and the diffusive transport to neighboring alveolus. The whole set of equations have successfully described the encapsulation process and determine that the size of the lesions depends on its position on the secondary lobule. We conclude that size and shape of the secondary lobule are the relevant variables to control the lesions, and, therefore, to avoid the evolution towards TB development. As lesions appear near to interlobular connective tissue they are easily controlled and their growth is drastically stopped, in this sense secondary lobules with a more flattened shape could control better the lesion.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Chemokines / immunology
  • Computer Simulation*
  • Cytokines / immunology
  • Cytokines / metabolism
  • Diffusion
  • Granuloma / immunology
  • Granuloma / microbiology
  • Granuloma / pathology*
  • Humans
  • Latent Tuberculosis / immunology
  • Latent Tuberculosis / microbiology
  • Latent Tuberculosis / pathology
  • Lung / immunology
  • Lung / metabolism
  • Macrophages, Alveolar / enzymology
  • Macrophages, Alveolar / metabolism
  • Macrophages, Alveolar / pathology
  • Mycobacterium tuberculosis / immunology
  • Mycobacterium tuberculosis / pathogenicity*
  • Neutrophils / immunology
  • Neutrophils / metabolism
  • Phagocytosis / immunology
  • T-Lymphocytes / immunology
  • T-Lymphocytes / pathology
  • Tuberculosis / immunology*
  • Tuberculosis / microbiology
  • Tuberculosis, Pulmonary / immunology
  • Tuberculosis, Pulmonary / microbiology
  • Tuberculosis, Pulmonary / pathology

Substances

  • Chemokines
  • Cytokines

Grants and funding

CP, PJC and MC received funding from La Caixa Foundation (ID 100010434), under agreement LCF/PR/GN17/50300003; PJC received funding from Agència de Gesto d’Ajuts Universitaris i de Recerca AGAUR), Grup Unitat de Tuberculosi Experimental, 2017-SGR-500; CP, DL, SA, MC received funding from Ministerio de Ciencia, Innovación y Universidades and FEDER, with the project PGC2018-095456-B-I00.