Journal
FRONTIERS IN MICROBIOLOGY
Volume 13, Issue -, Pages -Publisher
FRONTIERS MEDIA SA
DOI: 10.3389/fmicb.2022.1065159
Keywords
pathogen detection; nanopore sequencing; respiratory system; species; resistance genes
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This study found that targeted nanopore sequencing (TNPseq) can effectively identify pathogens in patients with lower respiratory tract infections (LRTIs), helping physicians to provide timely and precise treatment. Compared to traditional culture methods, TNPseq has higher sensitivity and detection rate, can identify more bacterial infections and mixed infections, and can also detect antimicrobial resistance (AMR) genes, aiding in the appropriate use of antibiotics.
ObjectivesLower respiratory tract infections (LRTIs) are one of the causes of mortality among infectious diseases. Microbial cultures commonly used in clinical practice are time-consuming, have poor sensitivity to unculturable and polymicrobial patterns, and are inadequate to guide timely and accurate antibiotic therapy. We investigated the feasibility of targeted nanopore sequencing (TNPseq) for the identification of pathogen and antimicrobial resistance (AMR) genes across suspected patients with LRTIs. TNPseq is a novel approach, which was improved based on nanopore sequencing for the identification of bacterial and fungal infections of clinical relevance. MethodsThis prospective study recruited 146 patients suspected of having LRTIs and with a median age of 61 years. The potential pathogens in these patients were detected by both TNPseq and the traditional culture workups. We compared the performance between the two methods among 146 LRTIs-related specimens. AMR genes were also detected by TNPseq to prompt the proper utilization of antibiotics. ResultsAt least one pathogen was detected in 133 (91.1%) samples by TNPseq, but only 37 (25.3%) samples contained positive isolates among 146 cultured specimens. TNPseq possessed higher sensitivity than the conventional culture method (91.1 vs. 25.3%, P < 0.001) in identifying pathogens. It detected more samples with bacterial infections (P < 0.001) and mixed infections (P < 0.001) compared with the clinical culture tests. The most frequent AMR gene identified by TNPseq was bla(TEM) (n = 29), followed by bla(SHV) (n = 4), bla(KPC) (n = 2), bla(CTX-M) (n = 2), and mecA (n = 2). Furthermore, TNPseq discovered five possible multi-drug resistance specimens. ConclusionTNPseq is efficient to identify pathogens early, thus assisting physicians to conduct timely and precise treatment for patients with suspected LRTIs.
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