Xi Yang1, Marjan M Hashemi1, Nadya Andini1, Michelle M Li2, Shuzhen Kuang3, Karen C Carroll4, Tza-Huei Wang5, Samuel Yang1. 1. Department of Emergency Medicine, Stanford University, Stanford, CA, USA. 2. Department of Mathematical and Computational Science, Stanford University, Stanford, CA, USA. 3. Department of Biological Sciences, Clemson University, Clemson, SC, USA. 4. Department of Pathology, Johns Hopkins University, Baltimore, MD, USA. 5. Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, USA.
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.
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.
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