纳米孔测序
基因组
DNA测序
计算生物学
生物
工作流程
基因组学
病菌
基因组
基因
生物信息学
遗传学
计算机科学
数据库
作者
Sanjana Kuruwa,Amrutraj Zade,Sanchi Shah,Rameez Moidu,Shailesh B. Lad,Chhaya Chande,Ameeta Joshi,Nilma Hirani,Chaitali Nikam,Sanjay Bhattacharya,Aruna Poojary,Mohit Kapoor,Kiran Kondabagil,Anirvan Chatterjee
标识
DOI:10.1093/jambio/lxae037
摘要
Abstract 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.
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