Evidence of Naturalized Stress-Tolerant Strains of Escherichia coli in Municipal Wastewater Treatment Plants
Bibliographic record
Abstract
UNLABELLED: Escherichia coli has been proposed to have two habitats-the intestines of mammals/birds and the nonhost environment. Our goal was to assess whether certain strains of E. coli have evolved toward adaptation and survival in wastewater. Raw sewage samples from different treatment plants were subjected to chlorine stress, and ∼59% of the surviving E. coli strains were found to contain a genetic insertion element (IS30) located within the uspC-flhDC intergenic region. The positional location of the IS30 element was not observed across a library of 845 E. coli isolates collected from various animal hosts or within GenBank or whole-genome reference databases for human and animal E. coli isolates (n = 1,177). Phylogenetics clustered the IS30 element-containing wastewater E. coli isolates into a distinct clade, and biomarker analysis revealed that these wastewater isolates contained a single nucleotide polymorphism (SNP) biomarker pattern that was specific for wastewater. These isolates belonged to phylogroup A, possessed generalized stress response (RpoS) activity, and carried the locus of heat resistance, features likely relevant to nonhost environmental survival. Isolates were screened for 28 virulence genes but carried only the fimH marker. Our data suggest that wastewater contains a naturalized resident population of E. coli We developed an endpoint PCR targeting the IS30 element within the uspC-flhDC intergenic region, and all raw sewage samples (n = 21) were positive for this marker. Conversely, the prevalence of this marker in E. coli-positive surface and groundwater samples was low (≤5%). This simple PCR assay may represent a convenient microbial source-tracking tool for identification of water samples affected by municipal wastewater. IMPORTANCE: The results of this study demonstrate that some strains of E. coli appear to have evolved to become naturalized populations in the wastewater environment and possess a number of stress-related genetic elements likely important for survival in this nonhost environment. The presence of non-host-adapted strains in wastewater challenges our understanding of using E. coli as a microbial indicator of wastewater treatment performance, suggesting that the E. coli strains present in human and animal feces may be very different from those found in treated wastewater.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".