Multiplex Detection of Antimicrobial Resistance Genes for Rapid Antibiotic Guidance of Urinary Tract Infections

Abstract

Identification of antimicrobial resistance markers in urinary tract infections could provide a more targeted approach in the diagnosis and treatment of UTIs while reducing overall public health burdens. We describe a molecular assay as a diagnostic tool for antibiotic resistance characterization to promote faster diagnosis of antibiotic regimens compared to standard microbiology techniques. Targeted antibiotic usage for pathogenic infections remains a main goal for effective antibiotic treatment protocols and reducing the overall public health burden. Rapid identification of the pathogen(s) causing the infection and harboring the antibiotic resistance gene is also a main area of exploration for antibiotic appropriation and stewardship. Urinary tract infections are a common clinical disease and reservoir for pathogenic infection and the development of antibiotic resistance, especially in hospital- and community-acquired settings. Standard methods require urine culture, which is time consuming and relies on phenotypic characterization. A genetic diagnostic method is warranted for the rapid molecular characterization of antibiotic resistance genes to reduce inappropriate exposure to antibiotics while improving the overall treatment model for urinary tract infections. The purpose of this study is to demonstrate logical viability for real-time molecular diagnostics for early identification, active surveillance and overall targeted antibiotic stratification that is proposed as an in vitro rapid and comprehensive tool for assessing proper antibiotic stewardship in UTIs. Here, we describe a multiplex real-time fluorescence polymerase chain reaction (PCR) for probe-based detection of the top 24 antibiotic resistance genes with targeted relationships to target molecular drug classes and administered antibiotics. Multiplexed analysis based on molecular features enables rapid testing while shifting the diagnostic detection paradigm from monocentric infections towards polymicrobial infections. We utilized 366 samples from the FDA-CDC Antimicrobial Resistance Isolate Bank to test the efficacy of the assay and propose a model to infer the identity of bacterial isolates. We found that, in addition to a high level of accuracy in predicting bacterial genus classification, the assay was mostly in agreement with CDC-tested genotypic and phenotypic results. This study provides evidence for using genetic diagnostic methods, such as multiplex qPCR, in the rapid identification of antibiotic resistance (ABR) genes for the characterization and treatment of urinary tract infections.

Keywords

• antibiotic resistance
• urinary tract infections
• multiplex PCR
• pathogen detection
• molecular diagnostics
• antibiotic stewardship