Comparing the Genomes of Multidrug and Vancomycin-Resistant <em>Enterococcus faecium</em> from a Florida Wastewater Treatment Plant
Bibliographic record
Abstract
Vancomycin-resistant Enterococcus (VRE) are a serious health threat, causing 50,000 infections and 5,000 deaths each year in the United States (CDC, 2019). Multidrug-resistant VRE are becoming more prevalent, and treatment options for infections caused by these organisms are limited (Arias et al., 2010; CDC, 2019). Multidrug resistant VRE have been previously isolated from wastewater in Brazil, Canada, and Portugal (Araújo et al., 2010; de_Farias et al., 2022; Sanderson et al., 2019). Thirteen vancomycin-resistant Enterococcus faecium isolated from three stages of a Florida wastewater treatment plant were fully resistant to the following antibiotics: vancomycin, ampicillin, ciprofloxacin, erythromycin, tetracycline, and nitrofurantoin, and sensitive to linezolid, fosfomycin, and quinupristin-dalfopristin. The genomes of the thirteen VRE strains were sequenced via 50 paired-end sequencing on an Illumina NovaSeq and analyzed to determine relationships among the genomes and mobile genetic elements. All strains belonged to clonal complex 17, and three sequence types were identified (ST18, ST412, and ST584). Each strain contained a mean of 18 antimicrobial resistance genes and 22 virulence genes, and multiple putative plasmids and genomic islands (clusters of genes that are transferable between organisms) were identified. All strains shared Tn1546, which carries the vanA operon, as well as four putative genomic islands. The strains had 99.5% percent genomic identity and were more closely related to other wastewater and clinical VRE strains than to vancomycin-resistant E. faecium strains isolated from environmental habits, or vancomycin-susceptible E. faecium. The similarity among the strains as well as to clinical strains suggests an origin from hospital sewage.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".