Non-tuberculous mycobacteria isolates from patients with chronic pulmonary disease and no epidemiological relationship show sequence clusters through whole-genome sequencing

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Objectives This study aimed to investigate the genomic epidemiology of slow-growing mycobacteria (SGM) isolates from patients with bronchiectasis through whole-genome sequencing (WGS) and assess various bioinformatic tools to establish relationships between the isolates. Methods A total of 46 SGM isolates from 37 patients with underlying chronic pulmonary disease, previously identified as Mycobacterium avium, Mycobacterium intracellulare, or Mycobacterium chimaera through polymerase chain reaction, were analyzed using WGS and three different clustering methods, namely rPinecone, Split K-mer analysis (SKA), and custom single nucleotide variant threshold calculation. Results The three analyses revealed one cluster of M. intracellulare subsp. intracellulare isolates and one cluster of M. intracellulare subsp. chimaera isolates from different patients. The analyses did not indicate any clusters formed by M. avium subsp. avium isolates from different patients. Conclusion M. intracellulare subsp. chimaera and M. intracellulare subsp. intracellulare form clusters of very closely related isolates from patients with no epidemiological relationship. This absence of an epidemiological relationship indicated that the infections were likely acquired from common sources rather than through direct transmission between patients. The use of three methodologies is an adequate strategy for an in-depth study of the relationship between isolates of very closely related species and subspecies.

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