Phenotypic Diversity Caused by Differential RpoS Activity among Environmental Escherichia coli Isolates
Bibliographic record
Abstract
Enteric bacteria deposited into the environment by animal hosts are subject to diverse selective pressures. These pressures may act on phenotypic differences in bacterial populations and select adaptive mutations for survival in stress. As a model to study phenotypic diversity in environmental bacteria, we examined mutations of the stress response sigma factor, RpoS, in environmental Escherichia coli isolates. A total of 2,040 isolates from urban beaches and nearby fecal pollution sources on Lake Ontario (Canada) were screened for RpoS function by examining growth on succinate and catalase activity, two RpoS-dependent phenotypes. The rpoS sequence was determined for 45 isolates, including all candidate RpoS mutants, and of these, six isolates were confirmed as mutants with the complete loss of RpoS function. Similarly to laboratory strains, the RpoS expression of these environmental isolates was stationary phase dependent. However, the expression of RpoS regulon members KatE and AppA had differing levels of expression in several environmental isolates compared to those in laboratory strains. Furthermore, after plating rpoS+ isolates on succinate, RpoS mutants could be readily selected from environmental E. coli. Naturally isolated and succinate-selected RpoS mutants had lower generation times on poor carbon sources and lower stress resistance than their rpoS+ isogenic parental strains. These results show that RpoS mutants are present in the environment (with a frequency of 0.003 among isolates) and that, similarly to laboratory and pathogenic strains, growth on poor carbon sources selects for rpoS mutations in environmental E. coli. RpoS selection may be an important determinant of phenotypic diversification and, hence, the survival of E. coli in the environment.
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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 | 0.000 | 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) | 0.000 | 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".