NinR- and Red-Mediated Phage-Prophage Marker Rescue Recombination in <i>Escherichia coli</i>
Bibliographic record
Abstract
We examined the requirement of lambda recombination functions for marker rescue of cryptic prophage genes within the Escherichia coli chromosome. We infected lysogenic host cells with lambdaimm434 phages and selected for recombinant immlambda phages that had exchanged the imm434 region of the infecting phage for the heterologous 2.6-kb immlambda region from the prophage. Phage-encoded activity, provided by either Red or NinR functions, was required for the substitution. Red(-) phages with DeltaNinR, internal NinR deletions of rap-ninH, or orf-ninC were 117-, 12-, and 5-fold reduced for immlambda rescue in a Rec(+) host, suggesting the participation of several NinR activities. RecA was essential for NinR-dependent immlambda rescue, but had slight influence on Red-dependent rescue. The host recombination activities RecBCD, RecJ, and RecQ participated in NinR-dependent recombination while they served to inhibit Red-mediated immlambda rescue. The opposite effects of several host functions toward NinR- and Red-dependent immlambda rescue explains why the independent pathways were not additive in a Rec(+) host and why the NinR-dependent pathway appeared dominant. We measured the influence of the host recombination functions and DnaB on the appearance of orilambda-dependent replication initiation and whether orilambda replication initiation was required for immlambda marker rescue.
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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) | 0.001 | 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 | 0.001 |
| 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".