Antimicrobial Susceptibility of Bacteria That Cause Bovine Respiratory Disease Complex in Alberta, Canada - Anholt, R. Michele; Klima, Cassidy; Allan, Nick; Matheson-Bird, Heather; Schatz, Crystal; Ajitkumar, Praseeda; Otto, Simon JG; Peters, Delores; Schmid, Karin; Olson, Merle; McAllister, Tim; Ralston, Brenda (Frontiers in Veterinary Science, 2017)
Bovine respiratory disease (BRD) is the most important illness of feedlot cattle. Disease management targets the associated bacterial pathogens, Mannheimia haemolytica, Mycoplasma bovis, Pasteurella multocida, Histophilus somni, and Trueperella pyogenes. We conducted a cross-sectional study to measure the frequencies of antimicrobial-resistant BRD pathogens using a collaborative network of veterinarians, industry, government, and a diagnostic laboratory. Seven private veterinary practices in southern Alberta collected samples from both living and dead BRD-affected animals at commercial feedlots. Susceptibility testing of 745 isolates showed that 100% of the M. haemolytica, M. bovis, P. multocida, and T. pyogenes isolates and 66.7% of the H. somni isolates were resistant to at least one antimicrobial class. Resistance to macrolide antimicrobials (90.2% of all isolates) was notable for their importance to beef production and human medicine. Multidrug resistance (MDR) was high in all target pathogens with 47.2% of the isolates resistant to four or five antimicrobial classes and 24.0% resistance to six to nine classes. We compared the MDR profiles of isolates from two feedlots serviced by different veterinary practices. Differences in the average number of resistant classes were found for M. haemolytica (p < 0.001) and P. multocida (p = 0.002). Compared to previous studies, this study suggests an increasing trend of resistance in BRD pathogens against the antimicrobials used to manage the disease in Alberta. For the veterinary clinician, the results emphasize the importance of ongoing susceptibility testing of BRD pathogens to inform treatment protocols. Surveillance studies that collect additional epidemiological information and manage sampling bias will be necessary to develop strategies to limit the spread of resistance.