The recombination-cold region as an epidemiological marker of recombinogenic opportunistic pathogen Mycobacterium avium

Abstract

Abstract Background The rapid identification of lineage remains a challenge in the genotyping of clinical isolates of recombinogenic pathogens. The chromosome of Mycobacterium avium subsp. hominissuis (MAH), an agent of Mycobacterium avium complex (MAC) lung disease, is often mosaic and is composed of chromosomal segments originating from different lineages. This makes it difficult to infer the MAH lineage in a simple experimental set-up. To overcome this difficulty, we sought to identify chromosomal marker genes containing lineage-specific alleles by genome data mining. Results We conducted genetic population structure analysis, phylogenetic analysis, and a survey of historical recombination using data from 125 global MAH isolates. Six MAH lineages (EA1, EA2, SC1, SC2, SC3, and SC4) were identified in the current dataset. One P-450 gene (locus_tag MAH_0788/MAV_0940) in the recombination-cold region was found to have multiple alleles that could discriminate five lineages. By combining the information about allele type from one additional gene, the six MAH lineages as well as other M. avium subspecies were distinguishable. A recombination-cold region of 116 kb contains an insertion hotspot and is flanked by a mammalian cell-entry protein operon where allelic variants have previously been reported to occur. Hence, we speculate that the acquisition of lineage- or strain-specific insertions has introduced homology breaks in the chromosome, thereby reducing the chance of interlineage recombination. Conclusions The allele types of the newly identified marker genes can be used to predict major lineages of M. avium. The single nucleotide polymorphism typing approach targeting multiallelic loci in recombination-cold regions will facilitate the epidemiological study of MAC, and may also be useful for equivalent studies of other nontuberculous mycobacteria potentially carrying mosaic genomes.

Keywords

• MAC
• NTM
• VNTR
• MLVA
• Genotyping
• SNP