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DataSet Summary

  • HostingRepository: PanoramaPublic
  • AnnounceDate: 2019-02-14
  • AnnouncementXML: Submission_2019-02-14_09:19:16.xml
  • DigitalObjectIdentifier:
  • ReviewLevel: Peer-reviewed dataset
  • DatasetOrigin: Original data
  • RepositorySupport: Supported dataset by repository
  • PrimarySubmitter: Shimin Chen
  • Title: Detection of Six Commercially Processed Soy ingredients in an Incurred Food Matrix Using Parallel Reaction Monitoring
  • Description: Soybean is one of the major allergenic foods in the United States, European Union, and many other countries. Soybean is commonly processed into different types of soy ingredients to achieve desired properties. The processing, however, may affect the protein profiles and protein structure, thus affecting the detection of soy proteins. Mass spectrometry is a potential alternative to the traditional immunoassays for the detection of soy-derived ingredients in foods. This study aims to develop an LC-MS/MS method that uniformly detects different types of soy-derived ingredients. Target peptides applicable to the detection of six commercial soy ingredients were identified based on the results of MS label-free quantification and a set of selection criteria. The results indicated that soy ingredient processing can result in different protein profiles, mostly affecting the content of minor seed storage proteins. Six soy ingredients were then individually incurred into cookie matrices at different levels. Sample preparation methods were optimized, and a distinct improvement in peptide performance was observed after optimization. Cookies and dough incurred with different soy ingredients at 100 ppm total soy protein showed a similar level of peptide recovery, demonstrating the advantage of the MS method in detecting processed soy ingredients in comparison with antibody-based methods.
  • SpeciesList: scientific name: Glycine max; NCBI TaxID: 3847;
  • ModificationList: Carbamidomethyl; Oxidation
  • Instrument: Q Exactive Plus

Dataset History

VersionDatetimeStatusChangeLog Entry
02018-08-22 14:14:48ID requested
12019-02-14 09:10:22announced
22019-02-14 09:19:18announcedUpdated keywords

Publication List

  1. Chen S, Yang CT, Downs ML, Detection of Six Commercially Processed Soy Ingredients in an Incurred Food Matrix Using Parallel Reaction Monitoring. J Proteome Res, 18(3):995-1005(2019) [pubmed]

Keyword List

  1. submitter keyword: Soybean, food allergen, parallel reaction monitoring

Contact List

    Melanie Downs
    • contact affiliation: Department of Food Science and Technology, University of Nebraska-Lincoln
    • contact email: mdowns2@unl.edu
    • lab head:
    Shimin Chen
    • contact affiliation: Department of Food Science and Technology, University of Nebraska-Lincoln
    • contact email: shimin@huskers.unl.edu
    • dataset submitter:

Full Dataset Link List

  1. Panorama Public dataset URI

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