Functional Cooperativity Between the Trigger Factor Chaperone and the ClpXP Degradation System
Bibliographic record
Abstract
Comprehensive bioinformatic analyses demonstrated the conservation of the close proximity of the tig gene coding for the ribosome‐associated chaperone trigger factor (TF) chaperone and the genes coding for the ClpXP proteolytic complex suggesting the possible functional association between the protein folding and the protein degradation systems. Genome‐wide genetic interaction studies further supported such an observation. The effect of TF on ClpXP‐dependent degradation varied depending on the nature of the substrate. For some substrates, TF slowed down their degradation by ClpXP, while for others it had no effect. Surprisingly, for a third class of substrates, TF increased the degradation rate. The ClpXP‐dependent degradation of the λ phage replication protein λO was significantly enhanced by TF in vitro and in vivo . TF was found to interact with both ClpX and λO with similar affinities and to enhance the ClpXP‐mediated degradation of ribosome‐stalled λO nascent chains. Experiments suggest that TF transfers λO to ClpX for eventual degradation by the ClpP serine protease and that this could occur cotranslationally. Globally, it is estimated that TF enhances the degradation of about 2% of newly synthesized E. coli proteins. This reveals a new role for TF in facilitating the degradation of newly translated proteins and the potential presence of cotranslational degradation in bacteria. Support or Funding Information Canadian Institutes of Health Research
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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 | 0.001 |
| 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 | 0.001 |
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".