Back to Search Start Over

Application of Four Genotyping Methods to Mycoplasma bovis Isolates Derived from Western Canadian Feedlot Cattle

Authors :
Andrea Kinnear
Tim A. McAllister
Rahat Zaheer
Matthew Waldner
Karen B. Register
Murray D. Jelinski
Source :
Journal of Clinical Microbiology
Publication Year :
2021

Abstract

Mycoplasma bovis is a significant pathogen of feedlot cattle, responsible for chronic pneumonia and polyarthritis syndrome (CPPS). M. bovis isolates (n = 129) were used to compare four methods of phylogenetic analysis and to determine if the isolates’ genotypes were associated with phenotypes. Metadata included the health status of the animal from which an isolate was derived (healthy, diseased, or dead), anatomical location (nasopharynx, lung, or joint), feedlot, and production year (2006 to 2018). Four in silico phylogenetic typing methods were used: multilocus sequence typing (MLST), core genome MLST (cgMLST), core genome single nucleotide variant (cgSNV) analysis, and whole-genome SNV (wgSNV) analysis. Using Simpson’s diversity index (D) as a proxy for resolution, MLST had the lowest resolution (D = 0.932); cgSNV (D = 0.984) and cgMLST (D = 0.987) generated comparable results; and wgSNV (D = 1.000) provided the highest resolution. Visual inspection of the minimum spanning trees found that the memberships of the clonal complexes and clades had similar structural appearances. Although MLST had the lowest resolution, this methodology was intuitive and easy to apply, and the PubMLST database facilitates the comparison of sequence types across studies. The cg methods had higher resolution than MLST, and the graphical interface software was user-friendly for nonbioinformaticians, but the proprietary software is relatively expensive. The wgSNV approach was the most robust for processing poor-quality sequence data while offering the highest resolution; however, application of its software requires specialized training. None of the four methods could associate genotypes with phenotypes.

Details

ISSN :
1098660X
Volume :
59
Issue :
7
Database :
OpenAIRE
Journal :
Journal of clinical microbiology
Accession number :
edsair.doi.dedup.....1630134a403b006d64db74a005a8373b