Whole Genome Sequencing for Surveillance of Antimicrobial Resistance in Actinobacillus pleuropneumoniae

Abstract

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.

Genetic diversity and toxin gene distribution among serovars of Actinobacillus pleuropneumoniae from Australian pigs

“…Other elements that can be transposed are antibiotic resistance genes, and integrative conjugative elements, such as the 56‐kb ICE Apl1 , have been found in the genome of A. pleuropneumoniae , conferring resistance to tetracycline . Furthermore, analysis has also found the tetracycline resistance ( tet (B)) gene as part of the Tn7 insertion and in some isolates it is the only resistance gene in the genome . Hence, insertion of resistance genes could be a possible explanation of the variance found in the ERIC‐PCR patterns and/or the failure of the toxin PCRs to give the expected profiles.…”

“…24 Furthermore, analysis has also found the tetracycline resistance (tet(B)) gene as part of the Tn7 insertion and in some isolates it is the only resistance gene in the genome. 25 Hence, insertion of resistance genes could be a possible explanation of the variance found in the ERIC-PCR patterns and/or the failure of the toxin PCRs to give the expected profiles.…”

Update onActinobacillus pleuropneumoniae-knowledge, gaps and challenges

“…In a Spanish retrospective study from 1994 to 2009, a high or an increasing trend for resistance against beta‐lactam antibiotics, tetracyclines and tilmicosin was recorded, while most isolates were susceptible to amphenicols, fluoroquinolones and ceftiofur (Vanni et al., ). In a recent study, only 33% of UK App isolates were negative for resistance genes, while 57% of the isolates were resistant (as adjudged by MICs) to tetracycline, 48% to sulfisoxazole, 20% to ampicillin, 17% to trimethoprim and 6% to enrofloxacin (Bossé, Li, Rogers, et al., ).…”

“…Recently, plasmids conferring resistance to florfenicol and chloramphenicol were isolated from App clinical isolates from Greece and Brazil (Bossé et al., ; Cunha da Silva et al., ), and enrofloxacin‐resistant strains have been reported in Taiwan and the UK (Bossé, Li, Rogers, et al., ; Wang et al., ). It has been demonstrated that whole‐genome sequencing can be used as predictor for App resistance to antimicrobial substances (Bossé, Li, Rogers, et al., ). In general, variation in levels of antimicrobial resistance of App isolates within the same herd can be high (Dayao et al., ), and there is not always an association between in vitro test results and success after treatment of disease.…”

Evaluation of Machine Learning Models for Predicting Antimicrobial Resistance of Actinobacillus pleuropneumoniae From Whole Genome Sequences

“…Typically, the determination of antimicrobial susceptibility is done either by disk diffusion or minimum inhibitory concentration (MIC) assays. Identification of resistance-specific markers by PCR or microarray hybridization not only corroborates phenotypic results but is also useful for epidemiological purposes, as there are often multiple different genes that can confer resistance to a given antimicrobial agent (Bossé et al, 2017). With the increasing throughput and decreasing cost of DNA sequencing, whole genome sequencing (WGS) may be an alternative for routine surveillance of resistance profiles and for identification of emerging resistances (Mahé and Tournoud, 2018).…”