Purpose: The objective of this study was to evaluate the correlation between resistance phenotype and genotype using in vitro antimicrobial susceptibility testing (AST) and WGS.
Methods: Seventy-four Campylobacter isolates recovered from the National Antimicrobial Resistance Monitoring System were selected in this study. Standard broth micro dilution was used to determine antimicrobial susceptibility profiles of nine antimicrobials, including ciprofloxacin (CIP), erythromycin (ERY), gentamicin (GEN), tetracycline (TET), azithromycin (AZI), clindamycin (CLI), florfenicol (FFN), nalidixic acid (NAL) and telithromycin (TEL). Resistance breakpoints of EUCAST epidemiological cut-off values were used to interpret the AST data. Genomic DNA was sequenced as paired-end reads using Illumina MiSeq. Genome sequences were assembled by using CLC genomics workbench 6.0.2. Previously reported antibiotic resistance genes were downloaded from GenBank to an in-house database. Resistance genotypes were determined using assembled WGS data through BLAST analysis.
Results: Eleven resistance genes, including tetO, blaOXA-61, aph(3')-IIIa, aph(2'')-Ic, aph(3')-Ic, aadE, Sat4, ant(6'), aad9, aph(2'')-Ig, aph(2')-If plus mutations in three house-keeping genes (GyrA at position 86, 23S rRNA at position 2074 and 2075) were identified by WGS. Overall, between resistant /susceptible phenotypes and genotype correlated well, with 100% for TET, CIP/NAL and ERY. A few discrepancies were observed for GEN, AZI, CLI and TEL and the correlation between phenotype and genotype for these drugs ranges from 95.9% to 98.6%. All isolates were susceptible to FFN and no genes associated with FFN resistance were detected.
Significance: WGS can provide comprehensive resistance genotypes, and is capable of accurately predicting resistance phenotypes, suggesting that WGS has the potential to be used as a routine method for antimicrobial resistance surveillance programs.