Whole Genome Sequencing Analysis Accurately Predicts Antimicrobial Resistance Phenotypes in Campylobacter.

Zhao S1, Tyson GH2, Chen Y2, Li C2, Mukherjee S2, Young S2, Lam C2, Folster JP3, Whichard JM3, McDermott PF2.

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Abstract

OBJECTIVES:

The objectives of this study were to identify antimicrobial resistance genotypes for Campylobacter and to evaluate the correlation between resistance phenotypes and genotypes using in vitro antimicrobial susceptibility testing and whole-genome sequencing (WGS).

METHODS:

One hundred-fourteen Campylobacter sp. (82 C. coli and 32 C. jejuni) isolated from 2000-2013 from ill humans, retails meats and cecal samples from food production animals in the United States as part of the National Antimicrobial Resistance Monitoring System were selected for study. Resistance phenotypes were determined using broth micro-dilution of nine antimicrobials. Genomic DNA was sequenced using the Illumina MiSeq platform, and resistance genotypes were identified using assembled WGS sequences through BLASTx analysis.

RESULTS:

Eighteen resistance genes, including tetO, blaOXA-61, catA, lnuC, aph(2' ')-Ib, aph(2' ')-Ic, aph(2')-If, aph(2' ')-Ig, aph(2' ')-Ih, aac(6')-Ie/aph(2' ')-Ia, aac(6')-Ie/aph(2' ')-If, aac(6')-Im, aadE, sat4, ant(6'), aad9, aph(3')-Ic, aph(3')-IIIa, and mutations in two house-keeping genes (gyrA and 23S rRNA) were identified. There was a high degree of correlation between phenotypic resistance to a given drug and the presence of one or more corresponding resistance genes. Phenotypic and genotypic correlation was 100% for tetracycline, ciprofloxacin/nalidixic acid, and erythromycin and ranged from 95.4% to 98.7% for gentamicin, azithromycin, clindamycin, and telithromycin. All isolates were susceptible to florfenicol, and no genes associated with florfenicol resistance were detected.

CONCLUSIONS:

There was a strong correlation (99.2%) between resistance genotypes and phenotypes, suggesting that WGS is a reliable indicator of resistance to the nine antimicrobial agents assayed in this study. WGS has the potential to be a powerful tool for antimicrobial resistance surveillance programs.