Antimicrobial resistance among Streptococcus equi subspecies zooepidemicus and Rhodococcus equi isolated from equine specimens submitted to a diagnostic laboratory in Kentucky, USA

Abstract

Background Surveillance of antimicrobial resistance (AMR) among veterinary pathogens is necessary to identify clinically relevant patterns of AMR and to inform antimicrobial use practices. Streptococcus equi subsp. zooepidemicus and Rhodococcus equi are bacterial pathogens of major clinical importance in horses and are frequently implicated in respiratory tract infections. The objectives of this study were to describe antimicrobial resistance patterns and identify predictors of AMR and multidrug resistance (MDR) (resistance to three or more antimicrobial classes) among equine S. zooepidemicus and R. equi isolates. Methods Antimicrobial susceptibility data from equine specimens submitted to the University of Kentucky Veterinary Diagnostic Laboratory between 2012 and 2017 were used in the study. Temporal trends in AMR and MDR were assessed using the Cochran-Armitage test. Logistic regression was used to identify associations between patient characteristics and the following outcomes: (a) MDR among S. zooepidemicus isolates, and (b) resistance to macrolides and ansamycins (rifampin) among R. equi isolates. Logistic regression was also used to investigate whether resistance of S. zooepidemicus and R. equi isolates to an antimicrobial class could be predicted by resistance to other drug classes. Results The vast majority of S. zooepidemicus (99.6%) and R. equi isolates (83%) were resistant to at least one antimicrobial agent, but no significant temporal trends in AMR were observed. Approximately half (53.3%) of the S. zooepidemicus isolates were multidrug-resistant, and there was a significant (p < 0.001) increasing temporal trend of MDR among S. zooepidemicus isolates. Resistance to penicillin, which is typically recommended for treatment of suspected S. zooepidemicus infections, also increased during the study period, from 3.3% to 9.5%. Among R. equi isolates, 19.2% were resistant to one or more macrolide antibiotics, 24% were resistant to rifampin, and 15.6% were resistant to both macrolide(s) and rifampin. For both organisms, resistance to an antimicrobial class could be predicted based on resistance profiles to other drug classes. For instance, significant (p < 0.01) predictors of β-lactam resistance among S. zooepidemicus isolates included resistance to macrolides (Odds Ratio (OR) = 14.7) and ansamycins (OR = 9.3). Resistance to phenicols (OR = 3.7) and ansamycins (OR = 19.9) were associated with higher odds of macrolide resistance among R. equi isolates. Conclusions The increase in MDR among S. zooepidemicus isolates is concerning. The observed levels of resistance to macrolides and rifampin among R. equi are also worrisome given the limited number of antimicrobials available for treatment of this organism. The findings of this study highlight the importance of ongoing surveillance of AMR to guide treatment decisions and directions for future research.