Degron-mediated proteolysis of CrhR-like DEAD-box RNA helicases in cyanobacteria
Bibliographic record
Abstract
Conditional proteolytic degradation is an irreversible and highly regulated process that fulfills crucial regulatory functions in all organisms. As proteolytic targets tend to be critical metabolic or regulatory proteins, substrates are targeted for degradation only under appropriate conditions through the recognition of an amino acid sequence referred to as a "degron". DEAD-box RNA helicases mediate all aspects of RNA metabolism, contributing to cellular fitness. However, the mechanism by which abiotic-stress modulation of protein stability regulates bacterial helicase abundance has not been extensively characterized. Here, we provide in vivo evidence that proteolytic degradation of the cyanobacterial DEAD-box RNA helicase CrhR is conditional, being initiated by a temperature upshift from 20 to 30 °C in the model cyanobacterium, Synechocystis sp. PCC 6803. We show degradation requires a unique, highly conserved, inherently bipartite degron located in the C-terminal extension found only in CrhR-related RNA helicases in the phylum Cyanobacteria. However, although necessary, the degron is not sufficient for proteolysis, as disruption of RNA helicase activity and/or translation inhibits degradation. These results suggest a positive feedback mechanism involving a role for CrhR in expression of a crucial factor required for degradation. Furthermore, AlphaFold structural prediction indicated the C-terminal extension is a homodimerization domain with homology to other bacterial RNA helicases, and mass photometry data confirmed that CrhR exists as a dimer in solution at 22 °C. These structural data suggest a model wherein the CrhR degron is occluded at the dimerization interface but could be exposed if dimerization was disrupted by nonpermissive conditions.
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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) | 0.000 | 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".