<scp>CRISPR</scp>1 analysis of naturalized surface water and fecal <i>Escherichia coli</i> suggests common origin
Bibliographic record
Abstract
Clustered regularly interspaced short palindromic repeats (CRISPRs) are part of an acquired bacterial immune system that functions as a barrier to exogenous genetic elements. Since naturalized Escherichia coli are likely to encounter different genetic elements in aquatic environments compared to enteric strains, we hypothesized that such differences would be reflected within the hypervariable CRISPR alleles of these two populations. Comparison of CRISPR1 alleles from naturalized and fecal phylogroup B1 E. coli strains revealed that the alleles could be categorized into four major distinct groups (designated G6-G9), and all four allele groups were found among naturalized strains and fecal strains. The distribution of CRIPSR G6 and G8 alleles was similar among strains of both ecotypes, while naturalized strains tended to have CRISPR G7 alleles rather than G9 alleles. Since CRISPR G7 alleles were not specific to naturalized strains, they, however, would not be useful as a marker for identifying naturalized strains. Notably, CRISPR alleles from naturalized and fecal strains also had similar spacer repertoires. This indicates a shared history of encounter with mobile genetic elements and suggests that the two populations were derived from common ancestors.
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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) | 0.001 | 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".