Se-Pair Search for Deciphering Selenium-Encoded Peptide and a Pyrolysis-Thermolysis Dietary Model for Minimizing Loss of "KKSe(M)R" during Processing.
Xin WangWei JiaPublished in: Journal of agricultural and food chemistry (2024)
Dietary deficiency of selenium is a global health hazard. Supplementation of organic selenopeptides via food crops is a relatively safe approach. Selenopeptides with heterogeneous selenium-encoded isotopes or a poorly fragmented peptide backbone remain unidentified in site-specific selenoproteomic analysis. Herein, we developed the Se-Pair Search , a UniProtKB -FASTA-independent peptide-matching strategy, exploiting the fragmentation patterns of shared peptide backbones in selenopeptides to optimize spectral interpretation, along with developing new selenosite assignment schemes (steps 1-3) to standardize selenium-localization data reporting for the selenoproteome community and thereby facilitating the discovery of unexpected selenopeptides. Using selenium-biofortified rice under cooking, fermentation, and high-temperature and high-pressure processing conditions as a pyrolysis-thermolysis dietary model, we probed the single-molecule-level kinetic evolution of the novel selenopeptide "KKSe(M)R" with qual-quantitative information on graph-theory-oriented localization calculations, abundance patterns, activation energy, and rate constants at a selenoproteome-wide scale. We ground-truth-annotated thirteen pyrolysis-thermolysis products and inferred four pyrolysis-thermolysis pathways to characterize the formation reactivity of the main intermediate variables of KKSe(M)R and constructed an advanced probe-type ultrasound technique prior to pyrolysis-thermolysis conditions for minimizing loss of KKSe(M)R during processing. Importantly, we reveal the unappreciated pyro-excitation diversion of KKSe(M)R at pyrolysis-thermolysis time and temperature matrices. These findings provide pioneering theoretical guidance for controlling dietary selenium supplementation within the safety thresholds.
Keyphrases
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- global health
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- heavy metals
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- high temperature
- magnetic resonance imaging
- molecular dynamics simulations
- emergency department
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- deep learning
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- quantum dots
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- mass spectrometry
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