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March 10, 2026Scientific Reports0 citationsOpen Access

Evaluating long-read metagenomics for bloodstream infection diagnostics: a pilot study from a Thai Tertiary Hospital

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TYThunchanok YaikhanTWThidathip WongsurawatPJPiroon Jenjaroenpan

Key Points

  • The central aim is to evaluate the effectiveness of long-read metagenomics for diagnosing bloodstream infections using rapid sequencing techniques.
  • Applied Oxford Nanopore Technology to analyze positive blood cultures.
  • Used long-read sequencing for species identification and antimicrobial resistance detection.
  • Conducted genomic profiling for virulence factors and plasmid types.
  • Identified diverse Gram-negative and Gram-positive pathogens, including ESBL-producing E. coli.
  • Detected complex resistance mechanisms and multiple virulence factors associated with infection.
  • Achieved species identification and AMR detection within 6–8 hours, significantly faster than conventional methods.

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.

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Cite This Study

Yaikhan et al. (2026) studied this question.

synapsesocial.com/papers/69af95b470916d39fea4d7f3https://doi.org/10.1038/s41598-026-41247-2
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