# Genomic analysis of the 2017 Aotearoa New Zealand outbreak of Mycoplasma bovis and its position within the global population structure

## TL;DR

This study analyzed the 2017 Mycoplasma bovis outbreak in New Zealand and compared it to global strains, finding unique genetic variants and highlighting the importance of genomic tools for tracking disease spread.

## Contribution

The study identifies novel genetic variants unique to the New Zealand outbreak and emphasizes the value of whole genome sequencing alongside MLST for outbreak management.

## Key findings

- The New Zealand outbreak strain (ST21) showed clonal expansion and unique alleles in six genes.
- Two international genomes showed extensive unique recombination, suggesting diverse genetic origins.
- A global population structure with 11 clusters was identified, highlighting mixed genetic relationships between countries.

## Abstract

In 2017 an outbreak of Mycoplasma bovis (M. bovis), an infectious agent of cattle, was identified in Aotearoa New Zealand. This study characterizes the genomic population structure of the outbreak in New Zealand and compares it with the known global population structure using multilocus sequence typing (MLST) and genomic analysis. The New Zealand outbreak strain was MLST genotyped as ST21. A comprehensive collection of 840 genomes from the New Zealand outbreak showed a pattern of clonal expansion when characterized by MLST, core genome MLST (cgMLST) and whole genome MLST (wgMLST). A lineage of genomes was found with no in silico identifiable pta2 locus, a housekeeping gene used in the MLST scheme. We compared a sample set of 40 New Zealand genomes to 47 genomes from other countries. This group had 79 ST21 genomes and eight genomes that were single nucleotide polymorphism (SNP) variants within the MLST loci of ST21. Two of the 47 international genomes showed signs of extensive unique recombination. Unique alleles in six genes were identified as present only in the New Zealand genomes. These novel variants were in the genes; haeIIIM encoding for cytosine-specific methyltransferase, cysC encoding for cysteinyl tRNA synthetase, era encoding for GTPase Era, metK encoding for S-adenosylmethionine synthase, parE encoding for DNA topoisomerase, and hisS encoding for histidine-tRNA ligase. This finding could be due to a population bottleneck, genetic drift, or positive selection. The same sample set of 40 New Zealand genomes were compared using MLST to 404 genomes from 15 other countries and 11 genomes without a known country. A FastBAPS analysis of 455 genomes showed a global population structure with 11 clusters. Some countries, such as Canada, Denmark and Australia contained both internally closely related genomes and some genomes that were more closely related to genomes found in other countries. Our results support the need for Whole Genome Sequencing (WGS) as well as MLST genotyping in M. bovis outbreaks. They also support the importance of understanding the national and international movement patterns of cattle and their genetic material, as possible routes of transmission, when managing the spread of M. bovis.