RNA markers for ultra-rapid molecular antimicrobial susceptibility testing in fluoroquinolone-treated Klebsiella pneumoniae. (19th March 2020)

• Record Type: Journal Article
• Authors: Yang, Xi; Hashemi, Marjan M; Andini, Nadya; Li, Michelle M; Kuang, Shuzhen; Carroll, Karen C; Wang, Tza-Huei; Yang, Samuel
• Is Part Of: Journal of antimicrobial chemotherapy. Volume 75:Number 7(2020)
• Page Start: 1747
• Page End: 1755
• Publication Date: 2020-03-19
• Subjects: Anti-infective agents -- Periodicals; Chemotherapy -- Periodicals; 615.58
• DOI: 10.1093/jac/dkaa078
• Languages: English
• ISSNs: 0305-7453

Abstract

Abstract: Objectives: Traditional antimicrobial susceptibility testing (AST) is growth dependent and time-consuming. With rising rates of drug-resistant infections, a novel diagnostic method is critically needed that can rapidly reveal a pathogen's antimicrobial susceptibility to guide appropriate treatment. Recently, RNA sequencing has been identified as a powerful diagnostic tool to explore transcriptional gene expression and improve AST. Methods: RNA sequencing was used to investigate the potential of RNA markers for rapid molecular AST using Klebsiella pneumoniae and ciprofloxacin as a model. Downstream bioinformatic analysis was applied for optimal marker selection. Further validation on 11 more isolates of K. pneumoniae was performed using quantitative real-time PCR. Results: From RNA sequencing, we identified RNA signatures that were induced or suppressed following exposure to ciprofloxacin. Significant shifts at the transcript level were observed as early as 10 min after antibiotic exposure. Lastly, we confirmed marker expression profiles with concordant MIC results from traditional culture-based AST and validated across 11 K. pneumoniae isolates . recA, coaA and metN transcripts harbour the most sensitive susceptibility information and were selected as our top markers. Conclusions: Our results suggest that RNA signature is a promising approach to AST development, resulting in faster clinical diagnosis and treatment of infectious disease. This approach is potentially applicable in other models including other pathogens exposed to different classes of antibiotics.