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Whole-genome sequencing (WGS) has changed our understanding of bacterial pathogens, aiding outbreak investigations and advancing our knowledge of their genetic features. However, there has been limited use of genomics to understand antimicrobial resistance of veterinary pathogens, which would help identify emerging resistance mechanisms and track their spread. The objectives of this study were to evaluate the correlation between resistance genotypes and phenotypes for Staphylococcus pseudintermedius, a major pathogen of companion animals, by comparing broth microdilution antimicrobial susceptibility testing and WGS. From 2017-2019, we conducted antimicrobial susceptibility testing and WGS on S. pseudintermedius isolates collected from dogs in the United States as a part of the Veterinary Laboratory Investigation and Response Network (Vet-LIRN) antimicrobial resistance monitoring program. Across thirteen antimicrobials in nine classes, resistance genotypes correlated with clinical resistance phenotypes 98.4 % of the time among a collection of 592 isolates. Our findings represent isolates from diverse lineages based on phylogenetic analyses, and these strong correlations are comparable to those from studies of several human pathogens such as Staphylococcus aureus and Salmonella enterica. We uncovered some important findings, including that 32.3 % of isolates had the mecA gene, which correlated with oxacillin resistance 97.0 % of the time. We also identified a novel rpoB mutation likely encoding rifampin resistance. These results show the value in using WGS to assess antimicrobial resistance in veterinary pathogens and to reveal putative new mechanisms of resistance., (Published by Elsevier B.V.)

Health problems can be thought of as phenotypic expressions of the complex relationships between genes, environments, and phenomes as a whole. Detailed evaluations of phenotypic expressions of illness are required to characterize important biological outcomes. We hypothesized that classifying dairy calf mortality phenotypes via a systematic postmortem analysis would identify different cause-of-death diagnoses than those derived from treatments alone. This cross-sectional study was carried out on a dairy calf ranch in the northwestern United States from June to September 2017 and focused on calves ≤90 d of age. Comparisons were made between causes of death based on 3 levels of information: on-farm treatment records alone, necropsy-based postmortem analyses in addition to treatment records, and Washington Animal Disease Diagnostic Laboratory (WADDL) results in addition to all other information. A total of 210 dairy calves were necropsied during this study, of which 122 cases were submitted to WADDL. Necropsy- and WADDL-derived mortality phenotypes were in almost perfect agreement (Cohen's κ = 0.86) when broadly categorized as diarrhea, respiratory, diarrhea and respiratory combined, or other causes. The level of agreement between on-farm treatment records and postmortem-derived results was low and varied by the level of diagnostic detail provided. There was just fair agreement (κ = 0.22) between treatment-based and necropsy-based phenotypes without WADDL input and only slight agreement (κ = 0.13) between treatment-based and corresponding necropsy-based phenotypes with WADDL input. Even for those cases in which causes of death aligned along a comparable pathologic spectrum, the lack of detail inherent to standard treatment-based causes of death failed to identify meaningful target areas for intervention. This was especially apparent for numerous cases of necrotizing enteritis and typhlitis (cecal inflammation) that were variously categorized as diarrhea and pneumonia by treatment-based diagnoses. The specificity of these lesions stood in stark contrast to the otherwise generic cause of death diagnoses derived from treatments. The findings from this study supported the hypothesis and highlighted the value of on-farm necropsies and laboratory-based diagnostics to (1) detect antemortem disease misclassifications, (2) provide detail regarding disease processes and mortality phenotypes, and (3) direct disease mitigation strategies., (Copyright © 2019 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)