The Effect of Mutation and Selection on Codon Adaptation in<i>Escherichia coli</i>Bacteriophage
Bibliographic record
Abstract
Studying phage codon adaptation is important not only for understanding the process of translation elongation, but also for reengineering phages for medical and industrial purposes. To evaluate the effect of mutation and selection on phage codon usage, we developed an index to measure selection imposed by host translation machinery, based on the difference in codon usage between all host genes and highly expressed host genes. We developed linear and nonlinear models to estimate the C→T mutation bias in different phage lineages and to evaluate the relative effect of mutation and host selection on phage codon usage. C→T-biased mutations occur more frequently in single-stranded DNA (ssDNA) phages than in double-stranded DNA (dsDNA) phages and affect not only synonymous codon usage, but also nonsynonymous substitutions at second codon positions, especially in ssDNA phages. The host translation machinery affects codon adaptation in both dsDNA and ssDNA phages, with a stronger effect on dsDNA phages than on ssDNA phages. Strand asymmetry with the associated local variation in mutation bias can significantly interfere with codon adaptation in both dsDNA and ssDNA phages.
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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 | 0.001 | 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".