Predicting antibiotic resistance in gram-negative bacilli from resistance genes

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Abstract

We developed a rapid high-throughput PCR test and evaluated highly antibiotic-resistant clinical isolates of Escherichia coli (n 2,919), Klebsiella pneumoniae (n 1,974), Proteus mirabilis (n 1,150), and Pseudomonas aeruginosa (n 1,484) for several antibiotic resistance genes for comparison with phenotypic resistance across penicillins, cephalosporins, carbapenems, aminoglycosides, trimethoprim-sulfamethoxazole, fluoroquinolones, and macrolides. The isolates originated from hospitals in North America (34%), Europe (23%), Asia (13%), South America (12%), Africa (7%), or Oceania (1%) or were of unknown origin (9%). We developed statistical methods to predict phenotypic resistance from resistance genes for 49 antibiotic-organism combinations, including gentamicin, tobramycin, ciprofloxacin, levofloxacin, trimethoprim-sulfamethoxazole, ertapenem, imipenem, cefazolin, cefepime, cefotaxime, ceftazidime, ceftriaxone, ampicillin, and aztreonam. Average positive predictive values for genotypic prediction of phenotypic resistance were 91% for E. coli, 93% for K. pneumoniae, 87% for P. mirabilis, and 92% for P. aeruginosa across the various antibiotics for this highly resistant cohort of bacterial isolates.

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Terrance Walker, G., Quan, J., Higgins, S. G., Toraskar, N., Chang, W., Saeed, A., … Sahm, D. (2019). Predicting antibiotic resistance in gram-negative bacilli from resistance genes. Antimicrobial Agents and Chemotherapy, 63(4). https://doi.org/10.1128/AAC.02462-18

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