A whole-genome sequencing (WGS) approach was conducted in order to identify the molecular determinants associated with antimicrobial resistance in 12 multidrug-resistant Campylobacter jejuni and Campylobacter coli isolates, with a focus… Click to show full abstract
A whole-genome sequencing (WGS) approach was conducted in order to identify the molecular determinants associated with antimicrobial resistance in 12 multidrug-resistant Campylobacter jejuni and Campylobacter coli isolates, with a focus on aminoglycoside resistance determinants. Two variants of a new aminoglycoside phosphotransferase gene [aph(2″)-Ii1 and aph(2″)-Ii2] putatively associated with gentamicin resistance were found. ABSTRACT A whole-genome sequencing (WGS) approach was conducted in order to identify the molecular determinants associated with antimicrobial resistance in 12 multidrug-resistant Campylobacter jejuni and Campylobacter coli isolates, with a focus on aminoglycoside resistance determinants. Two variants of a new aminoglycoside phosphotransferase gene [aph(2″)-Ii1 and aph(2″)-Ii2] putatively associated with gentamicin resistance were found. In addition, the following new genes were identified for the first time in Campylobacter: a lincosamide nucleotidyltransferase gene [lnu(G)], likely associated with lincomycin resistance, and two resistance enzyme genes (spw and apmA) similar to those found in Staphylococcus aureus, which may confer spectinomycin and gentamicin resistance, respectively. A C1192T mutation of the 16S rRNA gene that may be involved in spectinomycin resistance was also found in a C. coli isolate. Genes identified in the present study were located either on the bacterial chromosome or on plasmids that could be transferred naturally. Their role in aminoglycoside resistance remains to be supported by genetic studies. Regarding the other antimicrobial agents studied, i.e., ampicillin, ciprofloxacin, erythromycin, and tetracycline, a perfect correlation between antimicrobial phenotypes and genotypes was found. Overall, our data suggest that WGS analysis is a powerful tool for identifying resistance determinants in Campylobacter and can disclose the full genetic elements associated with resistance, including antimicrobial compounds not tested routinely in antimicrobial susceptibility testing.
               
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