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Antimicrob Agents Chemother. 2019 Mar 27;63(4). pii: e02462-18. doi: 10.1128/AAC.02462-18. Print 2019 Apr.

Predicting Antibiotic Resistance in Gram-Negative Bacilli from Resistance Genes.

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OpGen, Inc., Gaithersburg, Maryland, USA
OpGen, Inc., Gaithersburg, Maryland, USA.
Intermountain Medical Center, Murray, Utah, USA.
University of Utah, Salt Lake City, Utah, USA.
Merck & Co., Inc., Whitehouse Station, New Jersey, USA.
IHMA, Inc., Schaumburg, Illinois, USA.


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.


PCR; antibiotic resistance; resistance genes

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