Evaluating long-read metagenomics for bloodstream infection diagnostics: a pilot study from a Thai Tertiary Hospital
Issued Date
2026-12-01
Resource Type
eISSN
20452322
Scopus ID
2-s2.0-105033823647
Journal Title
Scientific Reports
Volume
16
Issue
1
Rights Holder(s)
SCOPUS
Bibliographic Citation
Scientific Reports Vol.16 No.1 (2026)
Suggested Citation
Yaikhan T., Wongsurawat T., Jenjaroenpan P., Thaipisuttikul I., Chayakulkeeree M., Tribhuddarat C., Nitayanon P., Peizner M.T., Tansirichaiya S., Kamolvit W., Surachat K. Evaluating long-read metagenomics for bloodstream infection diagnostics: a pilot study from a Thai Tertiary Hospital. Scientific Reports Vol.16 No.1 (2026). doi:10.1038/s41598-026-41247-2 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/115974
Title
Evaluating long-read metagenomics for bloodstream infection diagnostics: a pilot study from a Thai Tertiary Hospital
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Corresponding Author(s)
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Abstract
Bloodstream infections (BSIs) are life-threatening and require rapid, accurate pathogen characterization to guide antimicrobial therapy. Conventional culture-based diagnostics offer limited insight into the genetic basis of antimicrobial resistance (AMR) and virulence. In this study, we applied Oxford Nanopore Technology (ONT) metagenomic sequencing directly to 40 positive blood culture bottles collected at Siriraj Hospital, Thailand (2022 and 2025). Long-read data enabled species identification, AMR marker detection, virulence profiling, and plasmid replicon analysis. Diverse Gram-negative and Gram-positive pathogens were identified, including ESBL-producing Escherichia coli, carbapenem-resistant Klebsiella pneumoniae, Enterococcus spp., and Staphylococcus spp. Comprehensive genomic profiling revealed complex resistance mechanisms, multiple virulence factors related to adhesion, biofilm formation, and toxin production, and diverse plasmid types associated with horizontal gene transfer (HGT). This study demonstrates the value of ONT-based metagenomics as a faster workflow that is blood culture-dependent but subculture-independent, enabling species identification and AMR gene detection within 6–8 h, compared with 5–7 days for conventional methods, while supporting integrated genomic characterization for diagnostics, infection control, and regional AMR surveillance.