Tracheal Aspirate Metagenomics Reveals Association of Antibiotic Resistance with Nonpulmonary Sepsis Mortality
Bibliographic record
Abstract
Abstract Background Previous metabarcoding studies based on 16S rRNA sequencing in patients with extrapulmonary sepsis have found early pulmonary dysbiosis associated with a poor prognosis. To further discern this association, here we aimed to better characterize the pulmonary bacterial communities in these patients by leveraging metagenomics and to evaluate if the presence of antibiotic resistance genes (ARGs) could explain the higher mortality of the patients. Material and methods Metagenomic sequencing was performed using the Nextera XT Library Prep Kit and HiSeq 4000 (Illumina Inc.) on tracheal aspirate samples that were obtained within 24 h from diagnosis from patients with extrapulmonary sepsis admitted to the Intensive Care Unit (ICU). Analysis involved MetaSpades for contig assembly, Kraken2 and Metaphlan4 for taxonomic classification, and CARD and GTDB-tk for ARGs annotation and assignment to the bacterial species. The relationship between the presence of antibiotic resistance and ICU mortality was evaluated using the Wilcoxon test and logistic regression models adjusting for clinical and demographic variables. Results In total, 127 different ARGs were detected circumscribed only to seven patients. The most common ARGs found were from the antibiotic groups of aminoglycosides and beta-lactams, both present in most of the patients. These ARGs were found, almost entirely linked to Klebsiella pneumoniae, Escherichia coli , and Pseudomonas aeruginosa . The results also show a significant enrichment of ARGs among patients who died while admitted in the ICU (57%, 95% confidence interval [CI]: 18-90%) compared to surviving patients (20%, 95% CI: 7-40%) ( p =0.022). Analyses adjusting for clinical and demographic variables did not alter this result. Conclusion Metagenomic sequencing has allowed an unprecedented characterization of the sepsis lung microbiome showing that antibiotic resistance is common among these patients. The results also suggest a relationship between the early accumulation of ARGs in the lung of patients with extrapulmonary sepsis who die while admitted in the ICU. Studies in independent samples will be needed to validate our findings.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".