East Asian Mycobacterium avium subsp. paratuberculosis: molecular typing and population structure

The global molecular epidemiology of Mycobacterium avium subsp. paratuberculosis (MAP) has been well documented in North America and Europe, but the population-genetic framework of the East Asian lineages is underrepresented, hindering a complete understanding of the global genotype distribution and transmission dynamics.

This study aimed to establish a regional molecular-typing framework for MAP in East Asia and investigate its genetic relatedness with global lineages to explore potential intercontinental connections associated with international livestock movements.

The study integrated 12 newly characterized MAP isolates from South Korean ruminant herds (cattle and black goats, 2021-2024) with 34 global isolates across six continents. Genotypic characterization was performed using mycobacterial interspersed repetitive unit-variable number tandem repeat (MIRU-VNTR) and multilocus short sequence repeat (MLSSR) approaches to evaluate the allelic diversity and subtyping resolution.

All South Korean isolates were identified as "cattle-type" (Type II) and predominantly belonged to the INRA Nouzilly MIRU-VNTR (INMV) genotype. Age-associated differences in MAP prevalence were observed among Korean ruminant herds (Fisher's exact test, p < 0.05), with distinct age-related patterns in beef and dairy cattle The integrated MIRU-VNTR and MLSSR approaches identified 14 and 31 distinct subtypes, respectively, with MLSSR showing superior discriminatory power (discriminatory index = 0.973 vs. 0.630 for MIRU-VNTR). This high allelic diversity in the global MLSSR dataset provided finer resolution than MIRU-VNTR for distinguishing the MAP subtypes across continents.

This study provides a reference point for understanding the global diversity and distribution of MAP by bridging the genomic information gap in Asia. These findings underscore the potential of high-resolution, MLSSR-integrated surveillance as a practical tool for monitoring MAP across diverse geographical scales and for prioritizing isolates for future whole genome sequencing-based studies.