Abstract
Introduction: Tuberculosis (TB) caused by Mycobacterium tuberculosis (MTB) remains a global health concern because of the development of drug resistance. The adaptability of MTB in response to a variety of environmental stresses is a crucial strategy that supports their survival and evades host defense mechanisms. Stress regulates gene expression, particularly virulence genes, leading to the development of drug tolerance. Mannose-capped lipoarabinomannan (ManLAM) is a critical component of the cell wall, functions as a virulence factor and influences host defense mechanisms. Purpose: This study focuses on the effect of isoniazid (INH) stress on the regulation of ManLAM-related genes, to improve our understanding of virulence and drug resistance development in MTB. Materials and Methods: MTB with distinct drug resistance profiles were used for gene expression analysis. Multiplex-real time PCR assay was performed to monitor stress-related genes (hspX, tgs1, and sigE). The expression levels of ManLAM-related genes (pimB, mptA, mptC, dprE1, dprE2, and embC) were quantified by qRT-PCR. Sequence analysis of drug resistance-associated genes (inhA, katG, and rpoB) and ManLAM-related genes were performed to establish a correlation between genetic variation and gene expression. Results: INH treatment activates the stress response mechanism in MTB, resulting in a distinct gene expression pattern between drug resistance and drug-sensitive TB. In response to INH, hspX was up-regulated in RIF-R and MDR. tgs1 was strongly up-regulated in MDR, whereas sigE was dramatically up-regulated in the drug-sensitive TB. Interestingly, ManLAM-related genes were most up regulated in drug resistance, notably MDR (pimB, mptA, dprE1, and embC), implying a role for drug resistance and adaptability of MTB via ManLAM modulation. Conclusion: This study establishes a relationship between the antibiotic stress response mechanism and the expression of ManLAMrelated genes in MTB samples with diverse drug resistance profiles. The novel gene expression pattern in this work is valuable knowledge that can be applied for TB monitoring and treatment in the future.
