A genome-scale metabolic model for deciphering the host metabolic perturbations during Mycobacterium tuberculosis infection

ABSTRACT: Conventional tuberculosis (TB) research predominantly relies on forward-designed experiments, such as studying host responses to Mycobacterium tuberculosis (Mtb) gene knockouts. While informative, these approaches offer only a partial view of host-pathogen interactions and often overlook the broader alterations in the host microenvironment during infection. To address this limitation, we adopted a back tracing strategy to retrospectively identify host metabolic modulators and link them to specific Mtb virulence factors. Using RNA-seq data from Mtb-infected mouse lung tissue, we integrated transcriptomic profiles into a genome-scale metabolic model to predict host metabolic genes essential for Mtb survival. This analysis identified 18 host proteins as putative modulators. We then constructed a host-pathogen protein interaction network, which connected these host factors to 9 Mtb proteins. Experimental validation using Mtb knockdown strains confirmed that three genes Rv1970, Rv0243, and Rv2234 play key roles in manipulating host responses rather than supporting intrinsic bacterial viability. Further, we employed targeted proteomics and untargeted metabolomics analyses on THP-1 macrophages infected with these KD strains to dissect the host-pathogen interaction mechanisms in greater detail. These findings introduce a novel framework for decoding host-pathogen interactions and lay the groundwork for future host-directed therapy (HDT) strategies targeting Mtb-induced host vulnerabilities.

INSTRUMENT(S):

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Macrophage

DISEASE(S): Tuberculosis

SUBMITTER: Samrat Chatterjee  

LAB HEAD: Dr. Samrat Chatterjee

PROVIDER: PXD067154 | Pride | 2026-10-09

REPOSITORIES: Pride