Identifying mechanisms driving formation of granuloma-associated fibrosis during Mycobacterium tuberculosis infection

Authored by Denise E Kirschner, Jennifer J Linderman, JoAnne L Flynn, Hayley C Warsinske, Robert M DiFazio

Date Published: 2017

DOI: 10.1016/j.jtbi.2017.06.017

Sponsors: United States National Institutes of Health (NIH) United States Department of Energy (DOE) United States National Science Foundation (NSF)

Platforms: No platforms listed

Model Documentation: Other Narrative

Model Code URLs: Model code not found

Abstract

Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis (TB), is a pulmonary pathogen of major global concern. A key feature of Mtb infection in primates is the formation of granulomas, dense cellular structures surrounding infected lung tissue. These structures serve as the main site of host pathogen interaction in TB, and thus to effectively treat TB we must clarify mechanisms of granuloma formation and their function in disease. Fibrotic granulomas are associated with both good and bad disease outcomes. Fibrosis can serve to isolate infected tissue from healthy tissue, but it can also cause difficulty breathing as it leaves scars. Little is known about fibrosis in TB, and data from non -human primates is just beginning to clarify the picture. This work focuses on constructing a hybrid multi-scale model of fibrotic granuloma formation, in order to identify mechanisms driving development of fibrosis in Mtb infected lungs. We combine dynamics of molecular, cellular, and tissue scale models from previously published studies to characterize the formation of two common sub-types of fibrotic granulomas: peripherally fibrotic, with a cuff of collagen surrounding granulomas, and centrally fibrotic, with collagen throughout granulomas. Uncertainty and sensitivity analysis, along with large simulation sets, enable us to identify mechanisms differentiating centrally versus peripherally fibrotic granulomas. These findings suggest that heterogeneous cytokine environments exist within granulomas and may be responsible for driving tissue scale morphologies. Using this model we are primed to better understand the complex structure of granulomas, a necessity for developing successful treatments for TB. (C) 2017 Elsevier Ltd. All rights reserved.

Tags

Agent-based model Immune-response Necrosis-factor-alpha Growth-factor-beta Tgf-beta Myofibroblast differentiation Idiopathic pulmonary-fibrosis Transforming growth-factor-beta-1 Collagen formation Biological tissue