Evidence of horizontal gene transfer between human and animal commensal<i>Escherichia coli</i>strains identified by microarray
Bibliographic record
Abstract
Bacteria exchange genetic material by horizontal gene transfer (HGT). To evaluate the impact of HGT on Escherichia coli genome plasticity, 19 commensal strains collected from the intestinal floras of humans and animals were analyzed by microarrays. Strains were hybridized against an oligoarray containing 2700 E. coli K12 chromosomal genes. A core (genes shared among compared genomes) and a flexible gene pool (genes unique for each genome) have been identified. Analysis of hybridization signals evidenced 1015 divergent genes among the 19 strains and each strain showed a specific genomic variability pattern. Four hundred and fifty-eight genes were characterized by higher rates of interstrain variation and were considered hyperdivergent. These genes are not randomly distributed onto the chromosome but are clustered in precise regions. Hyperdivergent genes belong to the flexible gene pool and show a specific GC content, differing from that of the chromosome, indicating acquisition by HGT. Among these genes, those involved in defense mechanisms and cell motility as well as intracellular trafficking and secretion were far more represented than others. The observed genome plasticity contributes to the maintenance of genetic diversity and may therefore be a source of evolutionary adaptation and survival.
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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 | 0.000 | 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) | 0.001 | 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".