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Lao HY, Wong LLY, Hui Y, Ng TTL, Chan CTM, Lo HWH, Yau MCY, Leung ECM, Wong RCW, Ho AYM, Yip KT, Lam JYW, Chow VCY, Luk KS, Que TL, Chow FWN, Siu GKH. The clinical utility of Nanopore 16S rRNA gene sequencing for direct bacterial identification in normally sterile body fluids. Front Microbiol 2024; 14:1324494. [PMID: 38264489 PMCID: PMC10803466 DOI: 10.3389/fmicb.2023.1324494] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 12/19/2023] [Indexed: 01/25/2024] Open
Abstract
The prolonged incubation period of traditional culture methods leads to a delay in diagnosing invasive infections. Nanopore 16S rRNA gene sequencing (Nanopore 16S) offers a potential rapid diagnostic approach for directly identifying bacteria in infected body fluids. To evaluate the clinical utility of Nanopore 16S, we conducted a study involving the collection and sequencing of 128 monomicrobial samples, 65 polymicrobial samples, and 20 culture-negative body fluids. To minimize classification bias, taxonomic classification was performed using 3 analysis pipelines: Epi2me, Emu, and NanoCLUST. The result was compared to the culture references. The limit of detection of Nanopore 16S was also determined using simulated bacteremic blood samples. Among the three classifiers, Emu demonstrated the highest concordance with the culture results. It correctly identified the taxon of 125 (97.7%) of the 128 monomicrobial samples, compared to 109 (85.2%) for Epi2me and 102 (79.7%) for NanoCLUST. For the 230 cultured species in the 65 polymicrobial samples, Emu correctly identified 188 (81.7%) cultured species, compared to 174 (75.7%) for Epi2me and 125 (54.3%) for NanoCLUST. Through ROC analysis on the monomicrobial samples, we determined a threshold of relative abundance at 0.058 for distinguishing potential pathogens from background in Nanopore 16S. Applying this threshold resulted in the identification of 107 (83.6%), 117 (91.4%), and 114 (91.2%) correctly detected samples for Epi2me, Emu, and NanoCLUST, respectively, in the monomicrobial samples. Nanopore 16S coupled with Epi2me could provide preliminary results within 6 h. However, the ROC analysis of polymicrobial samples exhibited a random-like performance, making it difficult to establish a threshold. The overall limit of detection for Nanopore 16S was found to be about 90 CFU/ml.
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Affiliation(s)
- Hiu-Yin Lao
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China
| | - Lily Lok-Yee Wong
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China
| | - Yan Hui
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China
| | - Timothy Ting-Leung Ng
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China
| | - Chloe Toi-Mei Chan
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China
| | - Hazel Wing-Hei Lo
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China
| | - Miranda Chong-Yee Yau
- Department of Clinical Pathology, Pamela Youde Nethersole Eastern Hospital, Chai Wan, Hong Kong SAR, China
| | - Eddie Chi-Man Leung
- Department of Clinical Pathology, Pamela Youde Nethersole Eastern Hospital, Chai Wan, Hong Kong SAR, China
| | - River Chun-Wai Wong
- Department of Microbiology, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - Alex Yat-Man Ho
- Department of Pathology, Princess Margaret Hospital, Kowloon, Hong Kong SAR, China
| | - Kam-Tong Yip
- Department of Clinical Pathology, Tuen Mun Hospital, Tuen Mun, Hong Kong SAR, China
| | - Jimmy Yiu-Wing Lam
- Department of Clinical Pathology, Pamela Youde Nethersole Eastern Hospital, Chai Wan, Hong Kong SAR, China
| | - Viola Chi-Ying Chow
- Department of Microbiology, Prince of Wales Hospital, Shatin, Hong Kong SAR, China
| | - Kristine Shik Luk
- Department of Pathology, Princess Margaret Hospital, Kowloon, Hong Kong SAR, China
| | - Tak-Lun Que
- Department of Clinical Pathology, Tuen Mun Hospital, Tuen Mun, Hong Kong SAR, China
| | - Franklin Wang Ngai Chow
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China
| | - Gilman Kit-Hang Siu
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China
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