Reproducible microwave-assisted acid hydrolysis of proteins using a household microwave oven and its combination with LC-ESI MS/MS for mapping protein sequences and modifications
Bibliographic record
Abstract
A new set-up for microwave-assisted acid hydrolysis (MAAH) with high efficiency and reproducibility to degrade proteins into peptides for mass spectrometry analysis is described. It is based on the use of an inexpensive domestic microwave oven and can be used for low volume protein solution digestion. This set-up has been combined with liquid chromatography electrospray ionization quadrupole time-of-flight mass spectrometry (LC-ESI QTOF MS) for mapping protein sequences and characterizing phosphoproteins. It is demonstrated that for bovine serum albumin (BSA), with a molecular mass of about 67,000 Da, 1292 peptides (669 unique sequences) can be detected from a 2 microg hydrolysate generated by trifluoroacetic acid (TFA) MAAH. These peptides cover the entire protein sequence, allowing the identification of an amino acid substitution in a natural variant of BSA. It is shown that for a simple phosphoprotein containing one phosphoform, beta-casein, direct analysis of the hydrolysate generates a comprehensive peptide map that can be used to identify all five known phosphorylation sites. For characterizing a complex phosphoprotein consisting of different phosphoforms with varying numbers of phosphate groups and/or phosphorylation sites, such as bovine alpha(S1)-casein, immobilized metal-ion affinity chromatography (IMAC) is used to enrich the phosphopeptides from the hydrolysate, followed by LC-ESI MS analysis. The MS/MS data generated from the initial hydrolysate and the phosphopeptide-enriched fraction, in combination with MS analysis of the intact protein sample, allow us to reveal the presence of three different phosphoforms of bovine alpha(S1)-casein and assign the phosphorylation sites to each phosphoform with high confidence.
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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 | 0.001 | 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".