Comparative study of raw and thermally treated peanut major allergen post- translational modifications (PTMs)
Bibliographic record
Abstract
Introduction. Peanut allergy affects a large portion of world population causing reactions rangingfrom mild to severe. Major peanut allergen IgE epitopes are well characterized but little is knownabout their post-translational modifications (PTM) and how they are affected by thermaltreatment. PTM profile may differ between raw and thermally treated peanut, which could affectits allergic potential depending on type, size and position of modifications.Objective. Our aim was to analyse and compare PTM profiles of 4 major peanut allergens - Ara h 1,Ara h 2, Ara h 3 and Ara h 6, as well as their amounts in raw and roasted samples using bottom-upproteomics methods.Methodology. Full peanut protein extracts (both thermally treated and non-treated) were digestedin gel and in solution, and analysed by a Top10 nLC-MS/MS method by LTQ Orbitrap XL (ThermoFisher Scientific Inc., Germany). Within the extracts major allergens - Ara h 1, Ara h 2, Ara h 3 andAra h 6 were identified, label free quantified (LFQ) and searched for PTMs by Peaks X software(Bioinformatics solutions Inc.I, Canada). Epitope sequences were acquired from the ImmuneEpitope Database (IEDB www.iedb.org).Main findings. LFQ results show that there is no significant change in the amountsof any of thestudied allergens between raw and roasted extracts.Out of the 4 allergens Ara h 6 is modified in thehighest portion, with respect to the protein size: 15% and 12% of its positions are modified in rawand roasted sample, respectively. Total of 21 modifications were quantified between the twopreparations, with oxidation (M), methylation (K,R) and dethiomethylation affecting the largestnumber of peptides.Conclusions. Peanut allergen epitopes are indeed carriers of PTMs that differ in pattern andquantity between treated and non-treated extracts. The in silico discovered PTMs could affectprotein digestibility and allergenicity. Further investigation is necessary in order to fully understandthe impact protein modifications could have on their allergenic potential.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.002 | 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".