Characterization of DicB by partially masking its potent inhibitory activity of cell division
Bibliographic record
Abstract
DicB, a protein encoded by the Kim (Qin) prophage in Escherichia coli, inhibits cell division through interaction with MinC. Thus far, characterization of DicB has been severely hampered owing to its potent activity which ceases cell division and leads to cell death. In this work, through fusing maltose-binding protein to the N-terminus of DicB (MBP-DicB), we successfully expressed and purified recombinant DicB that enabled in vitro analysis for the first time. More importantly, taking advantage of the reduced inhibitory activity of MBP-DicB, we were able to study its effects on cell growth and morphology. Inhibition of cell growth by MBP-DicB was systematically evaluated using various DicB constructs, and their corresponding effects on cell morphology were also investigated. Our results revealed that the N-terminal segment of DicB plays an essential functional role, in contrast to its C-terminal tail. The N-terminus of DicB is of critical importance as even the first amino acid (following the initial Met) could not be removed, although it could be mutated. This study provides the first glimpse of the molecular determinants underlying DicB's function.
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".