Identification and Relative Quantification of Native and Proteolytically Generated Protein C-Termini from Complex Proteomes: C-Terminome Analysis
Bibliographic record
Abstract
Proteome-wide analysis of protein C-termini has long been inaccessible, but is now enabled by a newly developed negative selection strategy we term C-terminomics. In this procedure, amine- and carboxyl groups of full-length proteins are chemically protected. After trypsin digestion, N-terminal and internal tryptic peptides - but not C-terminal peptides - posses newly formed, unprotected C-termini that are removed by coupling to the high-molecular-weight polymer poly-allylamine. Ultrafiltration separates the uncoupled, blocked C-terminal peptides that are subsequently analyzed by liquid chromatography-tandem mass spectrometry. On a proteome-wide scale, this strategy profiles native protein C-termini together with neo C-termini generated by endoproteolytic cleavage or processive C-terminal truncations ("ragging"). In bacterial proteomes, hundreds of protein C-termini were identified. Stable isotope labeling enables -quantitative comparison of protein C-termini and C-terminal processing in different samples. Using formaldehyde-based chemical labeling, this quantitative approach termed "carboxy-terminal amine-based isotope labeling of substrates (C-TAILS)" identified >100 cleavage sites of exogenously applied GluC protease in an Escherichia coli proteome. C-TAILS complements recently developed N-terminomic techniques for endoprotease substrate discovery and is essential for the characterization of carboxyprotease processing.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".