Antimicrobial resistance (AMR) is an emerging public health problem and methods for surveillance are needed. We designed 85 sequence-specific PCR reactions to detect 79 genes or mutations associated with resistance across 10 major antimicrobial classes, with a focus on E . coli . The 85 qPCR assays demonstrated >99.9% concordance with sequencing. We evaluated the correlation between genotypic resistance markers and phenotypic susceptibility results on 239 E . coli isolates. Both sensitivity and specificity exceeded 90% for ampicillin, ceftriaxone, cefepime, imipenem, ciprofloxacin, azithromycin, gentamicin, amikacin, trimethoprim/sulfamethoxazole, tetracycline, and chloramphenicol phenotypic susceptibility results. We then evaluated the assays on direct stool specimens and observed a sensitivity of 97% ± 5 but, as expected, a lower specificity of 75% ± 31 versus the genotype of the E . coli cultured from stool. Finally, the assays were incorporated into a convenient TaqMan Array Card (TAC) format. These assays may be useful for tracking AMR in E . coli isolates or directly in stool for targeted testing of the fecal antibiotic resistome.
Antimicrobial use in agricultural animals is known to be associated with increases in antimicrobial resistance. Most prior studies have utilized culture and susceptibility testing of select organisms to document these phenomena. In this study we aimed to detect 66 antimicrobial resistance (AMR) genes for 10 antimicrobial agent classes directly in swine fecal samples using our previously developed antimicrobial resistance TaqMan array card (AMR-TAC) across three different swine farm management systems. This included 38 extensive antimicrobial use (both in treatment and feed), 30 limited antimicrobial use (treatment only), and 30 no antimicrobial use farms. The number of resistance genes detected in extensive antimicrobial use farms was higher than in limited and no antimicrobial use farms (28.2 genes ± 4.2 vs. 24.0 genes ± 4.1 and 22.8 genes ± 3.6, respectively, p < 0.05). A principal component analysis and hierarchical clustering of the AMR gene data showed the extensive use farm samples were disparate from the limited and no antimicrobial use farms. The prevalence of resistance genes in extensive use farms was significantly higher than the other farm categories for 18 resistance genes including bla SHV , bla CTX−M1 group, bla CTX−M9 group, bla VEB , bla CMY2−LAT, aac(6)-lb-cr, qnrB1, gyrA83L-E. coli, armA, rmtB, aac(3)-IIa, mphA, 23S rRNA 2075G-Campylobacter spp., mcr-1, catA1, floR, dfrA5-14, and dfrA17. These genotypic findings were supported by phenotypic susceptibility results on fecal E. coli isolates. To examine the timing of AMR gene abundance in swine farms, we also performed a longitudinal study in pigs. The results showed that AMR prevalence occurred both early, presumably from mothers, as well as after weaning, presumably from the environment. In summary, detection of AMR genes directly in fecal samples can be used to qualitatively and quantitatively monitor AMR in swine farms.
In our view, the TAC, the MYCOTB plate, and the conventional phenotypic method have similar performance for second-line drugs; however, the former methods offer speed, throughput, and quantitative DST information.
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