ArticleVeterinary research2025
M. caprae in northern Italy: a comprehensive analysis through whole-genome sequencing on the genetic variability in bovine herds.
Article in Veterinary research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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13 authors.
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Abstract
Mycobacterium (M.) bovis and M. caprae are the causative agents of bovine tuberculosis (bTB), which is still a concern due to its health implications and economic impact. Although M. caprae is less prevalent than M. bovis among bovine tuberculosis cases, it has a significant impact on animal health especially in Europe, where it has been isolated from a range of hosts. Starting from spoligotyping and the MIRU-VNTR profile specifically associated with the Lechtal subgroup we decided to process a selection of Italian M. caprae isolates using whole genome sequencing (WGS) to define the phylogenetic relationships between isolates and deepen the understanding of this public health issue. In this study, 20 outbreaks of bovine tuberculosis caused by M. caprae in northern Italy were retrospectively investigated by interpreting and validating WGS results with available epidemiological information. Genomes of 34 Italian strains, with a known and traditionally typed genotype, isolated between 2001 and 2022 from 21 bovine farms, with 12 isolates from Austria, were analyzed focusing on single nucleotide polymorphisms (SNP) to derive evolutionary relationships, pairing with the tracing of infections, suggested by the epidemiological contacts. The results outline possible connections between outbreaks, which caused the spread of the infection, obtaining two clusters differing by 6-16 SNP pairwise, overlapping with the territory distribution of the herds between two different Italian regions. Epidemiological information and phylogeny revealed that M. caprae was probably introduced in northern Italy from Austria and/or Germany, through separate and independent events for the two Italian clusters. The complex approach of integrating WGS data with epidemiological information proved to be useful in delineating likely transmission chains and identifying the possible sources of infection, showing how NGS is a powerful tool to support epidemiological investigations.
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