Mutational Analysis of the Antitoxin in the Lactococcal Type III Toxin-Antitoxin System AbiQ
Bibliographic record
Abstract
The lactococcal abortive phage infection mechanism AbiQ recently was classified as a type III toxin-antitoxin system in which the toxic protein (ABIQ) is regulated following cleavage of its repeated noncoding RNA antitoxin (antiQ). In this study, we investigated the role of the antitoxin in antiphage activity. The cleavage of antiQ by ABIQ was characterized using 5' rapid amplification of cDNA ends PCR and was located in an adenine-rich region of antiQ. We next generated a series of derivatives with point mutations within antiQ or with various numbers of antiQ repetitions. These modifications were analyzed for their effect on the antiphage activity (efficiency of plaquing) and on the endoribonuclease activity (Northern hybridization). We observed that increasing or reducing the number of antiQ repeats significantly decreased the antiphage activity of the system. Several point mutations had a similar effect on the antiphage activity and were associated with changes in the digestion profile of antiQ. Interestingly, a point mutation in the putative pseudoknot structure of antiQ mutants led to an increased AbiQ antiphage activity, thereby offering a novel way to increase the activity of an abortive infection mechanism.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".