Microwave-assisted acid hydrolysis of proteins combined with liquid chromatography MALDI MS/MS for protein identification
Bibliographic record
Abstract
Simple and efficient digestion of proteins, particularly hydrophobic membrane proteins, is of significance for comprehensive proteome analysis using the bottom-up approach. We report a microwave-assisted acid hydrolysis (MAAH) method for rapid protein degradation for peptide mass mapping and tandem mass spectrometric analysis of peptides for protein identification. It uses 25% trifluoroacetic acid (TFA) aqueous solution to dissolve or suspend proteins, followed by microwave irradiation for 10 min. This detergent-free method generates peptide mixtures that can be directly analyzed by liquid chromatography (LC) matrix-assisted laser desorption ionization (MALDI) mass spectrometry (MS) without the need of extensive sample cleanup. LC-MALDI MS/MS analysis of the hydrolysate from 5 microg of a model transmembrane protein, bacteriorhodopsin, resulted in almost complete sequence coverage by the peptides detected, including the identification of two posttranslational modification sites. Cleavage of peptide bonds inside all seven transmembrane domains took place, generating peptides of sizes amenable to MS/MS to determine possible sequence errors or modifications within these domains. Cleavage specificity, such as glycine residue cleavage, was observed. Terminal peptides were found to be present in relatively high abundance in the hydrolysate, particularly when low concentrations of proteins were used for MAAH. It was shown that these peptides could still be detected from MAAH of bacteriorhodopsin at a protein concentration of 1 ng/microl or 37 fmol/microl. To evaluate the general applicability of this method, it was applied to identify proteins from a membrane protein enriched fraction of cell lysates of human breast cancer cell line MCF7. With one-dimensional LC-MALDI MS/MS, a total of 119 proteins, including 41 membrane-associated or membrane proteins containing one to 12 transmembrane domains, were identified by MS/MS database searching based on matches of at least two peptides to a protein.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".