Tryptic digestion of ubiquitin standards reveals an improved strategy for identifying ubiquitinated proteins by mass spectrometry
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Ubiquitination plays an essential role in maintaining cellular homeostasis by regulating a multitude of essential processes. The ability to identify ubiquitinated proteins by MS currently relies on a strategy in which ubiquitinated peptides are identified by a 114.1 Da diglycine (GG) tag on lysine residues, which is derived from the C-terminus of ubiquitin, following trypsin digestion. In the following study, we report a more comprehensive approach for mapping ubiquitination sites by trypsin digestion and MS/MS analysis. We demonstrate that ubiquitination sites can be identified by signature peptides containing a GG-tag (114.1 Da) and an LRGG-tag (383.2 Da) on internal lysine residues as well as a GG-tag found on the C-terminus of ubiquitinated peptides. Application of this MS-based approach enabled the identification of 96 ubiquitination sites from proteins purified from human MCF-7 breast cancer cells, representing a 2.4-fold increase in the number of ubiquitination sites that could be identified over standard methods. Our improved MS-based strategy will aid future studies which aim to identify and/or characterize ubiquitinated proteins in human cells.
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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 | 0.002 | 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 it