A sequence-specific RNA acetylation catalyst
Bibliographic record
Abstract
N4-acetylcytidine (ac4C) is a ubiquitous RNA modification incorporated by cytidine acetyltransferase enzymes. Here, we report the biochemical characterization of Thermococcus kodakarensis Nat10 (TkNat10), an RNA acetyltransferase involved in archaeal thermotolerance. We demonstrate that TkNat10's catalytic activity is critical for T. kodakarensis fitness at elevated temperatures. Unlike eukaryotic homologs, TkNat10 exhibits robust stand-alone activity, modifying diverse RNA substrates in a temperature, ATP, and acetyl-CoA-dependent manner. Transcriptome-wide analysis reveals TkNat10 preferentially modifies unstructured RNAs containing a 5'-CCG-3' consensus sequence. Using a high-throughput mutagenesis approach, we define sequence and structural determinants of TkNat10 substrate recognition. We find TkNat10 can be engineered to facilitate use of propionyl-CoA, providing insight into its cofactor specificity. Finally, we demonstrate TkNat10's utility for site-specific acetylation of RNA oligonucleotides, enabling analysis of ac4C-dependent RNA-protein interactions. Our findings establish a framework for understanding archaeal RNA acetylation and a new tool for studying the functional consequences of ac4C in diverse RNA contexts.
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 | 0.001 |
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".