Whole Genome Sequencing for Surveillance of Antimicrobial Resistance in Actinobacillus pleuropneumoniae - Bossé, Janine T.; Li, Yanwen; Rogers, Jon; Fernandez Crespo, Roberto; Li, Yinghui; Chaudhuri, Roy R.; Holden, Matthew T. G.; Maskell, Duncan J.; Tucker, Alexander W.; Wren, Brendan W.; Rycroft, Andrew N.; Langford, Paul R. (Frontiers in Microbiology, 2017)
The aim of this study was to evaluate the correlation between antimicrobial resistance (AMR) profiles of 96 clinical isolates of Actinobacillus pleuropneumoniae, an important porcine respiratory pathogen, and the identification of AMR genes in whole genome sequence (wgs) data. Susceptibility of the isolates to nine antimicrobial agents (ampicillin, enrofloxacin, erythromycin, florfenicol, sulfisoxazole, tetracycline, tilmicosin, trimethoprim, and tylosin) was determined by agar dilution susceptibility test. Except for the macrolides tested, elevated MICs were highly correlated to the presence of AMR genes identified in wgs data using ResFinder or BLASTn. Of the isolates tested, 57% were resistant to tetracycline [MIC ≥ 4 mg/L; 94.8% with either tet(B) or tet(H)]; 48% to sulfisoxazole (MIC ≥ 256 mg/L or DD = 6; 100% with sul2), 20% to ampicillin (MIC ≥ 4 mg/L; 100% with blaROB-1), 17% to trimethoprim (MIC ≥ 32 mg/L; 100% with dfrA14), and 6% to enrofloxacin (MIC ≥ 0.25 mg/L; 100% with GyrAS83F). Only 33% of the isolates did not have detectable AMR genes, and were sensitive by MICs for the antimicrobial agents tested. Although 23 isolates had MIC ≥ 32 mg/L for tylosin, all isolates had MIC ≤ 16 mg/L for both erythromycin and tilmicosin, and no macrolide resistance genes or known point mutations were detected. Other than the GyrAS83F mutation, the AMR genes detected were mapped to potential plasmids. In addition to presence on plasmid(s), the tet(B) gene was also found chromosomally either as part of a 56 kb integrative conjugative element (ICEApl1) in 21, or as part of a Tn7 insertion in 15 isolates. Our results indicate that, with the exception of macrolides, wgs data can be used to accurately predict resistance of A. pleuropneumoniae to the tested antimicrobial agents and provides added value for routine surveillance.