Concurrent Automated Sequencing of the Glycan and Peptide Portions of <i>O</i>-Linked Glycopeptide Anions by Ultraviolet Photodissociation Mass Spectrometry
Bibliographic record
Abstract
O-Glycopeptides are often acidic owing to the frequent occurrence of acidic saccharides in the glycan, rendering traditional proteomic workflows that rely on positive mode tandem mass spectrometry (MS/MS) less effective. In this report, we demonstrate the utility of negative mode ultraviolet photodissociation (UVPD) MS for the characterization of acidic O-linked glycopeptide anions. This method was evaluated for a series of singly and multiply deprotonated glycopeptides from the model glycoprotein kappa casein, resulting in production of both peptide and glycan product ions that afforded 100% sequence coverage of the peptide and glycan moieties from a single MS/MS event. The most abundant and frequent peptide sequence ions were a/x-type products which, importantly, were found to retain the labile glycan modifications. The glycan-specific ions mainly arose from glycosidic bond cleavages (B, Y, C, and Z ions) in addition to some less common cross-ring cleavages. On the basis of the UVPD fragmentation patterns, an automated database searching strategy (based on the MassMatrix algorithm) was designed that is specific for the analysis of glycopeptide anions by UVPD. This algorithm was used to identify glycopeptides from mixtures of glycosylated and nonglycosylated peptides, sequence both glycan and peptide moieties simultaneously, and pinpoint the correct site(s) of glycosylation. This methodology was applied to uncover novel site-specificity of the O-linked glycosylated OmpA/MotB from the "superbug" A. baumannii to help aid in the elucidation of the functional role that protein glycosylation plays in pathogenesis.
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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 | 0.000 | 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 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".