Investigation of in vitro histone H3 glycosylation using H3 tail peptides
Bibliographic record
Abstract
Posttranslational modifications (PTMs) on histone tails regulate eukaryotic gene expression by impacting the chromatin structure and by modulating interactions with other cellular proteins. One such PTM has been identified as serine and threonine glycosylation, the introduction of the ß-N-acetylglucosamine (GlcNAc) moiety on histone H3 tail at position Ser10 and Thr32. The addition of the ß-O-GlcNAc moiety on serine or threonine residues is facilitated by the O-GlcNAc transferase (OGT), and can be removed by the action of O-GlcNAcase (OGA). Conflicting reports on histone tail GlcNAc modification in vivo prompted us to investigate whether synthetic histone H3 tail peptides in conjunction with other PTMs are substrates for OGT and OGA in vitro. Our enzymatic assays with recombinantly expressed human OGT revealed that the unmodified and PTM-modified histone H3 tails are not substrates for OGT at both sites, Ser10 and Thr32. In addition, full length histone H3 was not a substrate for OGT. Conversely, our work demonstrates that synthetic peptides containing the GlcNAc functionality at Ser10 are substrates for recombinantly expressed human OGA, yielding deglycosylated histone H3 peptides. We also show that the catalytic domains of human histone lysine methyltransferases G9a, GLP and SETD7 and histone lysine acetyltransferases PCAF and GCN5 do somewhat tolerate glycosylated H3Ser10 close to lysine residues that undergo methylation and acetylation reactions, respectively. Overall, this work indicates that GlcNAcylation of histone H3 tail peptide in the presence of OGT does not occur in vitro.
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) | 0.000 | 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".