Mycobacterium abscessus soft tissue infections associated with subcutaneous injection of lipolytic agents: An outbreak report and novel molecular epidemiology analysis approach.

BACKGROUND

Management of Mycobacterium abscessus (M. abscessus) skin and soft tissue infections outbreaks require collaboration between clinicians, public health authorities and reference laboratories providing bacterial molecular identification and genotyping.

OBJECTIVE

This study reports on a M. abscessus skin and soft tissue outbreak linked to mesotherapy treatments in Montréal, Canada. We present an innovative approach combining Nanopore long read and Illumina short read whole-genome sequencing data with a novel open access bioinformatic molecular epidemiology pipeline to support public health investigations by identifying genomically related isolates.

METHODS

Public health investigations and physician questionnaires were used for outbreak identification and investigation. The complete genomes of six isolates from four individuals were sequenced. Nanopore and Illumina data were combined to assemble genomes de novo using a hybrid approach. Single nucleotide polymorphisms (SNPs) were identified within each genome by mapping the short reads to a reference genome. Single nucleotide polymorphisms distances among isolates, and between isolates and the reference genome were used alongside core SNP alignment analyses to evaluate genetic similarity between isolates and other contemporary M. abscessus genomes.

RESULTS

Identified individuals had received mesotherapy injections from the same esthetician within a one-month period. Outbreak isolates were genomically nearly identical, differing by only 0-2 SNPs when using the earliest collected isolate as a reference. A phylogenetic tree revealed genetic distinctness between outbreak isolates and other contemporary M. abscessus isolates from Montréal.

CONCLUSION

Genomic sequencing and the presented bioinformatic approach can identify M. abscessus genomic relatedness suggestive of clinical outbreaks. This approach can support public health investigations, particularly when epidemiological links are uncertain.