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Genetic Determinants of Intrinsic Antibiotic Tolerance in Mycobacterium avium.

William M MaternHarley T HarrisCarina DanchikLeah HooverJoel S BaderPetros C Karakousis
Published in: Microbiology spectrum (2021)
The Mycobacterium avium complex (MAC) is one of the most prevalent causes of nontuberculous mycobacteria pulmonary infection in the United States, and yet it remains understudied. Current MAC treatment requires more than a year of intermittent to daily combination antibiotic therapy, depending on disease severity. In order to shorten and simplify curative regimens, it is important to identify the innate bacterial factors contributing to reduced antibiotic susceptibility, namely, antibiotic tolerance genes. In this study, we performed a genome-wide transposon screen to elucidate M. avium genes that play a role in the bacterium's tolerance to first- and second-line antibiotics. We identified a total of 193 unique M. avium mutants with significantly altered susceptibility to at least one of the four clinically used antibiotics we tested, including two mutants (in DFS55_00905 and DFS55_12730) with panhypersusceptibility. The products of the antibiotic tolerance genes we have identified may represent novel targets for future drug development studies aimed at shortening the duration of therapy for MAC infections. IMPORTANCE The prolonged treatment required to eradicate Mycobacterium avium complex (MAC) infection is likely due to the presence of subpopulations of antibiotic-tolerant bacteria with reduced susceptibility to currently available drugs. However, little is known about the genes and pathways responsible for antibiotic tolerance in MAC. In this study, we performed a forward genetic screen to identify M. avium antibiotic tolerance genes, whose products may represent attractive targets for the development of novel adjunctive drugs capable of shortening the curative treatment for MAC infections.
Keyphrases
  • genome wide
  • dna methylation
  • mycobacterium tuberculosis
  • immune response
  • copy number
  • bioinformatics analysis
  • genome wide identification
  • mesenchymal stem cells
  • pulmonary hypertension