Molecular Characterization and Computational Analysis of Drug-Resistant Strains of Mycobacterium Tuberculosis
Tuberculosis (TB) is one of the leading health problem caused by Mycobacterium tuberculosis (MTB). The standard new therapy of TB includes a six-month treatment of four recommended first-line drugs, isoniazid, rifampicin, pyrazinamide and ethambutol. However, the misuse of these drugs has led to the emergence of drug resistance MTB. Pyrazinamide (PZA) is an important component of firstline drugs because of its distinctive capability to kill subpopulations of persistent MTB under latent stage, where other drugs fail to work. The drug in initial stage requires a conversion into pyrazinoic acid (POA), an active form of PZA, by the activity of pncA encoded pyrazinamidase (PZase) enzyme. POA targets the ribosomal proteins S1 (RpsA) and aspartate decarboxylase (PanD). Mutations in pncA have been considered as the most common and primary cause of PZA-resistance. However, in minor cases, mutations in rpsA and panD have also been accounted in resistance. The major aims of this study was, to explore the prevalence of PZAresistance in a geographically distinct region, Khyber Pakhtunkhwa province of Pakistan, molecular characterization, mechanisms of PZA-resistance behind mutations, and network analysis under latent stage. Samples have been taken and cultured from TB suspects, followed by PZA drug susceptibility testing on MTB positive samples. Genomic DNA was extracted and PCR products of pncA, rpsA, and panD was sequenced for mutations. To find the mechanism of PZA-resistance, the mutants and wild type proteins activities were analyzed through computational molecular dynamic simulations (MD simulation) at different time periods. Among 4518 TB samples, 754 (16.7%) subjects were detected as MTB positive. Out of total positive, 69 (14.8%) isolates were detected as PZA-resistance. The resistance isolate along with PZA-sensitive and one of each, H37Rv and Mycobacterium bovis as controls, were sequenced to analyze the mutations in the coding regions of pncA, rpsA, and panD. Thirty-six different mutation were identified in pncA of 51 PZA-resistant isolates. The sequences have been submitted to GeneBank (GeneBank Accession No. MH461111). Out of 36, fifteen mutations, including two deletion, 194-203delCCTCGTCGTG and 317-318-del-TC, have not been reported earlier. While, 18 resistance isolates lacked mutation in pncA (pncAWT). Mutations have not been detected in PZA sensitive isolates except, a single synonymous mutation at position C195T (Ser65Ser). Among 18 pncAWT isolates, 11 have mutation in rpsA while seven were found as pncAWT and rpsAWT PZAresistant. We identified 14 non-synonymous and one synonymous mutations in the coding region of rpsA gene. The remaining seven PZA-resistant isolates did not reveal any mutation. The sensitivity and specificity of the pncA sequencing method were 79.31% (95% CI, 69.29% to 87.25%) and 86.67% (95% CI, 69.28% to 96.24%). MD simulations analysis showed a significant variation in structures and activity between wild type and mutant PZase and RpsA proteins. Stability, flexibility, total energy, and drug binding pocket of these proteins also have been altered. Regulatory pathway analysis revealed that SigH and RshA are the major regulators under latent stage, receiving signals from PknB that might be an alternative drug target in PZA-resistance cases. In conclusion, mutation in the pncA is a major mechanism of PZA-resistance among circulating isolates. Molecular methods of investigating PZA-resistance are better to expose the cause of PZA resistant. In PZA-resistance, mutations in pncA and rpsA have been detected, altering the overall activity, causing a weak interactions with PZA and POA. Exploring alternative drug targets through investigation of regulatory pathways might be useful for alternative drug target identification and designing new drugs under latent stage of MTB. This study offers valuable information for better management of TB and drug resistance.