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DNA-based PCR test accurately predicts antibiotic resistance
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A rapid high-throughput PCR test developed by OpGen “accurately and reliably” predicted antibiotic resistance in common bacteria at a rate of 90% or higher, researchers reported.
According to a study published in Antimicrobial Agents and Chemotherapy, the researchers evaluated more than 7,500 highly antibiotic-resistant clinical isolates of Escherichia coli, Klebsiella pneumoniae, Proteus mirabilis and Pseudomonas aeruginosa for antibiotic-resistance genes and compared them with phenotypic resistance across penicillins, cephalosporins, carbapenems, aminoglycosides, trimethoprim-sulfamethoxazole, fluoroquinolones and macrolides.
“In the most comprehensive study of its kind, OpGen’s informatics technology (Acuitas Lighthouse) rapidly predicted antibiotic resistance to 15 antibiotics accurately and reliably, with an average positive predictive value of 90%,” G. Terrance Walker, PhD, senior vice president of research and development at OpGen, told Infectious Disease News. “On a larger scale, the paper supports a potential breakthrough in the global effort to speed up the rapid detection of antimicrobial resistance.
“Today, phenotypic methods based on bacterial growth are the standard of care. It can take days to provide results to patients. However, DNA testing can be completed in just hours and represents an attractive potential solution. Showing that DNA testing can be used to accurately predict antibiotic resistance has been a critical challenge that scientists have been working on for many years. This paper demonstrates that a well-defined set of DNA markers can potentially be used to perform rapid, accurate antibiotic resistance detection in key pathogens.”
Walker and colleagues reported testing 2,919 E. coli isolates, 1,974 K. pneumoniae isolates, 1,150 P. mirabilis isolates and 1,484 P. aeruginosa isolates, of which 34% originated in hospitals in North America, 23% in Europe, 13% in Asia, 12% in South America, 7% in Africa and 1% in Oceania, according to the study. Another 9% of tested isolates were of unknown origin.
According to the study, they “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.”
The findings revealed that the test’s average positive predictive value for genotypic prediction of phenotypic resistance was 91% for E. coli, 93% for K. pneumoniae, 87% for P. mirabilis and 92% for P. aeruginosa, according to the study.
OpGen expects the first FDA clearances for the test this year, Walker noted.
“In high-risk patients needing urgent care and patients with complicated urinary tract infections, the faster determination of appropriate antibiotic therapy translates to improved health outcomes, lower hospital costs and better antibiotic stewardship,” Walker said. “OpGen’s technology is the application of precision medicine to infectious disease management, which has become more complex with the proliferation of antimicrobial resistance.” – by Marley Ghizzone
Disclosure: Walker is employed by OpGen.
Perspective
Back to TopSheetal Kandiah, MD
Gram-negative antibiotic resistance has become a public health crisis because of the increased mortality rate associated with infections and the limited availability of treatment options. The microbiology laboratory plays a significant role in patient care by providing bacterial identification and antibiotic susceptibility testing, which can take up to 48 hours. Early identification of genes associated with specific antibiotic resistance using a PCR-based method could reduce unnecessary antibiotic exposure by predicting which antibiotics are likely resistant within hours. This test also has the potential to impact hospital-based transmission of antibiotic-resistant organisms by allowing for timely implementation of appropriate precautions when an organism is predicted to have a resistance gene. Although this technology may make an impact on patient care, further studies are necessary to assess the utility in the patient care setting. A cost-benefit analysis would be beneficial based on facility needs and resources, taking into account the prevalence of resistant organisms. Adequate manpower in the laboratory setting is also necessary to optimize the use of this test. Collaboration with antimicrobial stewardship programs and/or clinicians to develop plans for test implementation and interpretation in the clinical setting should also be required for optimization, which may be challenging in the resource-limited setting.
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