Post-translational hydroxylation by 2OG/Fe(II)-dependent oxygenases as a novel regulatory mechanism in bacteria
Bibliographic record
Abstract
Protein hydroxylation has been well-studied in eukaryotic systems. The structural importance of hydroxylation of specific proline and lysine residues during collagen biosynthesis is well established. Recently, key roles for post-translational hydroxylation in signaling and degradation pathways have been discovered. The function of hydroxylation in signaling is highlighted by its role in the hypoxic response of eukaryotic cells, where oxygen dependent hydroxylation of the hypoxia inducible transcription factor both targets it for degradation and blocks its activation. In contrast, the role of protein hydroxylation has been largely understudied in prokaryotes. Recently, an evolutionarily conserved class of ribosomal oxygenases (ROX) that catalyze the hydroxylation of specific residues in the ribosome has been identified in bacteria. ROX activity has been linked to cell growth, and has been found to have a direct impact on bulk protein translation. This discovery of ribosomal protein hydroxylation in bacteria could lead to new therapeutic targets for regulating bacterial growth, as well as, shed light on new prokaryotic hydroxylation signaling pathways. In this review, recent structural and functional studies will be highlighted and discussed, underscoring the regulatory potential of post-translational hydroxylation in bacteria.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 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 teacher head, 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".