Rapid, culture-free detection of carbapenem-resistant Klebsiella pneumoniae in a case of bloodstream infection using genomics.

Timely diagnosis and treatment of sepsis is a major challenge faced by critical care specialists around the world. The traditional blood culture methods have a significant turnaround time which delays targeted therapy leading to poor prognosis. In the current study, we highlight the clinical utility of a genomics solution for diagnosis and management of bloodstream infections by combining the real-time DNA sequencing of Oxford Nanopore Technology with an automated genomic data analysis software. We identify a carbapenem-resistant Klebsiella pneumoniae directly from a blood sample in <24 hours and thereby prove the effectiveness of the test in early diagnosis of sepsis.

An integrated method for targeted Oxford Nanopore sequencing and automated bioinformatics for the simultaneous detection of bacteria, fungi, and ARG.

AIMS: The use of metagenomics for pathogen identification in clinical practice has been limited. Here we describe a workflow to encourage the clinical utility and potential of NGS for the screening of bacteria, fungi, and antimicrobial resistance genes (ARGs). METHODS AND RESULTS: The method includes target enrichment, long-read sequencing, and automated bioinformatics. Evaluation of several tools and databases was undertaken across standard organisms (n = 12), clinical isolates (n = 114), and blood samples from patients with suspected bloodstream infections (n = 33). The strategy used could offset the presence of host background DNA, error rates of long-read sequencing, and provide accurate and reproducible detection of pathogens. Eleven targets could be successfully tested in a single assay. Organisms could be confidently identified considering ≥60% of best hits of a BLAST-based threshold of e-value 0.001 and a percent identity of >80%. For ARGs, reads with percent identity of >90% and >60% overlap of the complete gene could be confidently annotated. A kappa of 0.83 was observed compared to standard diagnostic methods. Thus, a workflow for the direct-from-sample, on-site sequencing combined with automated genomics was demonstrated to be reproducible. CONCLUSION: NGS-based technologies overcome several limitations of current day diagnostics. Highly sensitive and comprehensive methods of pathogen screening are the need of the hour. We developed a framework for reliable, on-site, screening of pathogens.