Rapid diagnosis of common, undetected, and uncultivable bloodstream infections from positive blood cultures using Oxford Nanopore sequencing: a metagenomic pipeline analysis

@article{govender2026rapid,
  title = {{Rapid diagnosis of common, undetected, and uncultivable bloodstream infections from positive blood cultures using Oxford Nanopore sequencing: a metagenomic pipeline analysis}},
  author = {Kumeren N. Govender and Teresa L. Street and Nicholas D. Sanderson and Laura Leach and Marcus Morgan and David W. Eyre},
  journal = {The Lancet Microbe},
  year = {2026},
  month = may,
  doi = {10.1016/j.lanmic.2025.101333},
  url = {https://doi.org/10.1016/j.lanmic.2025.101333},
  note = {CC BY},
}

TY  - JOUR
TI  - Rapid diagnosis of common, undetected, and uncultivable bloodstream infections from positive blood cultures using Oxford Nanopore sequencing: a metagenomic pipeline analysis
AU  - Kumeren N. Govender
AU  - Teresa L. Street
AU  - Nicholas D. Sanderson
AU  - Laura Leach
AU  - Marcus Morgan
AU  - David W. Eyre
PY  - 2026
DA  - 2026/05/15
JO  - The Lancet Microbe
DO  - 10.1016/j.lanmic.2025.101333
UR  - https://doi.org/10.1016/j.lanmic.2025.101333
AB  - Background Metagenomic sequencing has the potential to transform clinical microbiology by enabling rapid pathogen identification and antimicrobial resistance (AMR) prediction in critically ill patients with bloodstream infections (BSIs). However, its clinical implementation has been hindered by challenges in speed, accuracy, and technical feasibility. We present a direct from positive blood culture workflow using Oxford Nanopore sequencing that overcomes these limitations, delivering results rapidly and accurately. Methods We developed and evaluated a direct-from-blood culture metagenomic sequencing method for rapid pathogen and AMR prediction using Oxford Nanopore Sequencing. Species prediction was performed using Kraken2 with a comprehensive standard database, employing heuristic and random forest classification models. Additionally, we benchmarked AMR classification tools and databases, including ResFinder, CARD, and NCBI AMRFinderPlus. We processed 273 randomly selected blood cultures (211 positive, 62 negative) from hospitalised patients in real time, comparing species identification, AMR detection and time-to-result against standard culture-based diagnostics performed by the routine microbiology laboratory. Findings Our method achieved 97% sensitivity and 94% specificity (both improving to 100% after accounting for plausible additional infections) for species identification compared to established diagnostic methods. We detected 18 additional infections—13 polymicrobial and 5 previously unidentifiable—and delivered findings in 3.5 hours, nearly a third of time taken by routine methods. For the top ten pathogens, our method produced AMR results 20 hours faster than current antimicrobial susceptibility testing, with 88% sensitivity and 93% specificity. For Staphylococcus aureus and Escherichia coli , AMR prediction sensitivity was 100% and 91%, and specificity 99% and 94% respectively. Interpretation These findings highlight the potential of metagenomic sequencing to improve BSI diagnosis by providing rapid and comprehensive pathogen and AMR detection. Integrating this approach into routine clinical workflows could bridge critical diagnostic gaps in sepsis care, reduce empirical antibiotic use, and inform targeted treatment within hours rather than days. Funding National Institute for Health Research (NIHR) Biomedical Research Centre, Oxford. Research in Context Evidence before this study Bloodstream infections (BSIs) remain a critical global health burden, affecting over 30 million people annually with mortality rates reaching up to 30%. The urgency of early diagnosis is well-established -delays in appropriate antimicrobial therapy, even by one hour, can significantly reduce survival in severe cases. Conventional blood culture, the current diagnostic standard, is hampered by long turnaround times (24–72 hours), reduced sensitivity in patients already on antibiotics, and its inability to detect fastidious, slow-growing, or unculturable organisms. To explore current advancements in the field, we conducted a search on PubMed and Google Scholar on 6th April 2025 using a combination of relevant medical subject heading terms: “infection,” “diagnosis,” “metagenomic,” and “bloodstream.” This search yielded 59 results, from which we excluded pilot studies, those with fewer than 50 samples and studies focused on diagnosing specific pathogens. After applying these exclusions, we found four that contributed valuable insights into the application of metagenomics in BSIs. Blauwkamp and colleagues demonstrated strong concordance between cell-free DNA sequencing and blood culture, although the technique showed limited utility in predicting antimicrobial resistance. Similarly, Rossoff and colleagues used a cell-free DNA assay at a CLIA-certified laboratory demonstrating performance with >90% with turnaround times within 48 hours. Anson and colleagues developed a method to extract bacterial DNA from positive blood cultures for whole-genome sequencing, successfully identifying Staphylococcus and Gram-negative species, though antimicrobial resistance prediction was limited with Illumina data alone. A more recent study by Harris and colleagues demonstrated that direct-from-blood culture methods can accurately identify causative pathogens at the species level in ICU patients, particularly in monomicrobial infections, approximately 9-17 hours after a positive blood culture result. To date, no study, to our knowledge, at scale has systematically evaluated the diagnostic yield, speed, and practical clinical utility of metagenomic sequencing applied directly to randomised routine blood culture samples. Added value of this study This study presents the first clinical implementation of metagenomic sequencing using Oxford Nanopore technology directly on routine blood cultures at scale, with a focus on real-time diagnosis of bloodstream infections. It uniquely assesses the ability of metagenomics to detect not only common but polymicrobial, uncultivable, or previously undetected pathogens, and to predict antimicrobial resistance within clinically actionable timeframes. The study advances the field by demonstrating how accurate and rapid pathogen identification and resistance profiling can be integrated into existing diagnostic workflows, thereby reducing diagnostic delay and enabling early, targeted antimicrobial therapy. Implications of all the available evidence The collective evidence indicates that clinical metagenomics has reached a stage of maturity where we now see workflows ready for implementation in clinical settings. This study adds to the growing recognition that, when applied to positive blood cultures, metagenomic sequencing can bridge critical diagnostic gaps in sepsis care, reduce empirical antibiotic use, and inform precision treatment within hours rather than days. Nonetheless, widespread clinical adoption will require further standardisation of laboratory protocols, development of robust…
SN  - 2666-5247
ER  -