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

Metagenomics of clinical samples and microbiomes have enabled a better understanding of the role of pathogens. However, the use of metagenomics in clinical practice has been limited due to non-standardized methods of sample processing and need of expertise for the bioinformatic analysis of next generation sequencing (NGS) data. 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). 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 % identity of > 80%. For ARGs, reads with % 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. 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.