Whole-Genome Sequencing and Drug-Susceptibility Analysis of Serial Mycobacterium abscessus Isolates from Thai Patients - Orawee Kaewprasert; Ditthawat Nonghanphithak; Ploenchan Chetchotisakd; Wises Namwat; Rick Twee-Hee Ong; Kiatichai Faksri (Biology, 2022)
Mycobacterium abscessus is an important pathogen that can cause serious human diseases and is difficult to treat due to antibiotic resistance. In this study, we analyzed, using whole-genome sequence (WGS) data, M. abscessus strains serially isolated from patients at various time intervals. We undertook genetic diversity analysis between subspecies, mutation-rate estimation and identification of drug-resistant mutations with minimum inhibitory concentration (MIC) analysis. Clonal isolates of M. abscessus:—subsp. abscessus (MAB) and subsp. massiliense (MMAS)—causing persistent infection through time, differed by 0–7 and 0–14 SNPs, respectively, despite being isolated 1 to 659 days apart. Two cases caused by MMAS differed by ≥102 SNPs at 350 days apart and were regarded as examples of reinfection. Isolates collected ≤7 days apart exhibited a high mutation rate (133.83 ± 0.00 SNPs/genome (5 Mb)/year for MMAS and 127.75 SNPs/genome (5 Mb)/year for MAB). Mutation rates declined in a time-dependent manner in both subspecies. Based on isolates collected > 180 days apart, MMAS had a significantly higher average mutation rate than MAB (2.89 ± 1.02 versus 0.82 ± 0.83 SNPs/genome (5 Mb)/year, (p = 0.01), respectively). All well-known drug-resistance mutations were found to be strongly associated with high MIC levels for clarithromycin and ciprofloxacin. No known mutations were identified for strains resistant to linezolid and amikacin. MAB strains in the study were susceptible to amikacin, while most MMAS strains were susceptible to clarithromycin, amikacin and linezolid. No hetero-resistance was found in the strains analyzed. Our study reports the genetic diversity and mutation rate of M. abscessus between the two major subspecies and confirms the drug resistance-associated mutations. Information about drug-resistance and associated mutations can be applied in diagnosis and patient management.