Strain-dependent variability in growth and survival of Escherichia coli in agricultural soil
Bibliographic record
Abstract
Abstract This study investigated strain-dependent variability in Escherichia coli survival in soil, and strain-dependent responses to variations in some soil conditions. Collections of E. coli were isolated from swine manure slurry, and from manured soil following 6 days of incubation in the laboratory. The bacteria were fingerprinted by enterobacterial repetitive intergenic consensus-polymerase chain reaction (ERIC-PCR). During the course of the incubation the composition of the E. coli community changed dramatically suggesting that E. coli phylotypes, distinguishable by ERIC-PCR fingerprinting, varied significantly in their ability to survive in soil under these conditions. A representative isolate from one ERIC group which increased in abundance in soil (designated strain C279) and one which decreased (designated strain C278) were chosen for comparison. These strains persisted comparatively when inoculated into loam soil. However, when added into a loam soil or a sandy soil supplemented with 10% (v/v) swine manure slurry, strain C279 increased in abundance 10-fold, whereas strain C278 did not. At 4 degrees C, or in a clay loam soil, manure slurry did not support the growth of strain C279. These results indicate that the community composition of E. coli populations in manured soils can be very dynamic, and that strains able to proliferate in manured soils can have a selective advantage.
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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 | 0.002 |
| 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 | 0.000 |
| 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".