ArticleMicrobial genomics2021
Metagenomic evidence for a polymicrobial signature of sepsis.
Article in Microbial genomics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 19 citations in OpenAlex.
- Comparative Evaluation of Sequencing Technologies for Detecting Antimicrobial Resistance in Bloodstream Infections.Antibiotics (Basel, Switzerland) · 2025Review
- Hyphal growth determines spatial organization and coexistence in a pathogenic polymicrobial community in a spatially structured environment.The ISME journal · 2025Article
- Analysis of metagenomic data.Nature reviews. Methods primers · 2025Article
- Multiplexed longitudinal analysis of the cellular and microbial dynamics of acute polymicrobial sepsis in mice.Frontiers in immunology · 2025Article
- Interpretable machine learning decodes soil microbiome's response to drought stress.Environmental microbiome · 2024Article
- Divergent bacterial landscapes: unraveling geographically driven microbiomes in Atlantic cod.Scientific reports · 2024Article
- No microbial community in the blood of healthy individuals.Nature microbiology · 2023Article
- No evidence for a common blood microbiome based on a population study of 9,770 healthy humans.Nature microbiology · 2023Article
- Polymicrobial Infections and Biofilms: Clinical Significance and Eradication Strategies.Antibiotics (Basel, Switzerland) · 2022Review
- Molecular Methodologies for Improved Polymicrobial Sepsis Diagnosis.International journal of molecular sciences · 2022Review
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Our understanding of the host component of sepsis has made significant progress. However, detailed study of the microorganisms causing sepsis, either as single pathogens or microbial assemblages, has received far less attention. Metagenomic data offer opportunities to characterize the microbial communities found in septic and healthy individuals. In this study we apply gradient-boosted tree classifiers and a novel computational decontamination technique built upon SHapley Additive exPlanations (SHAP) to identify microbial hallmarks which discriminate blood metagenomic samples of septic patients from that of healthy individuals. Classifiers had high performance when using the read assignments to microbial genera [area under the receiver operating characteristic (AUROC=0.995)], including after removal of species 'culture-confirmed' as the cause of sepsis through clinical testing (AUROC=0.915). Models trained on single genera were inferior to those employing a polymicrobial model and we identified multiple co-occurring bacterial genera absent from healthy controls. While prevailing diagnostic paradigms seek to identify single pathogens, our results point to the involvement of a polymicrobial community in sepsis. We demonstrate the importance of the microbial component in characterising sepsis, which may offer new biological insights into the aetiology of sepsis, and ultimately support the development of clinical diagnostic or even prognostic tools.
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Registered trials
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