PXD029137-1

PXD029137 is an original dataset announced via ProteomeXchange.

Title	Quantification of Soy-Derived Ingredients in Model Bread and Frankfurter Matrices with an Optimized LC-MS/MS External Standard Calibration Workflow
Description	The detection and quantification of soy protein is important for food allergen management and identifying the presence of undeclared soy proteins. Heat processing and matrix interactions can affect the accuracy of allergen detection methods. The sensitivity of ELISA methods can be compromised if protein epitopes are modified during processing. Therefore, an MS-based method was evaluated for the recovery of total soy protein in incurred matrices. MS-based quantification of total soy protein was assessed using a combination of external and internal standards. The reproducibility of the standard curves was investigated by comparing within-day and among among-day variation. Incurred samples were prepared using bread and frankfurters as model food matrices. Several soy-derived ingredients were used to prepare the matrices with varying levels of soy protein (1, 10, 50, or 100 ppm total soy protein). A pooled standard curve was used to estimate the total soy protein concentration of the incurred food matrices and the percent total protein recovery. The variation of replicate standard curves between days and among all days was not significant. The differences in slopes obtained from replicate standards run on different days were minimal. The most influential factor on the quantitative protein recovery in incurred samples was the effect of the physical matrix structure on protein extraction. The lowest percent protein recoveries, less than 50%, were calculated for uncooked matrices. The cooked matrices had percent recoveries between 50-150% for all total soy protein levels. Other factors, such as type of ingredient, were determined to be not as impactful on recovery. The MS method described in this study was able to provide sensitive detection and accurate quantification of total soy protein from various soy-derived ingredients present in processed food matrices.
HostingRepository	PanoramaPublic
AnnounceDate	2021-11-12
AnnouncementXML	Submission_2021-11-12_08:40:53.870.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Supported dataset by repository
PrimarySubmitter	Melanie Downs
SpeciesList	scientific name: Glycine max; NCBI TaxID: 3847;
ModificationList	Label:13C(6)15N(2); Label:13C(6)15N(4)
Instrument	Q Exactive Plus

Revision	Datetime	Status	ChangeLog Entry
0	2021-10-14 12:10:06	ID requested
⏵ 1	2021-11-12 08:40:54	announced

Krager J, Baumert JL, Downs ML, Quantification of Soy-Derived Ingredients in Model Bread and Frankfurter Matrices with an Optimized Liquid Chromatography-Tandem Mass Spectrometry External Standard Calibration Workflow. J Food Prot, 85(2):311-322(2022) [pubmed]

submitter keyword: Food Allergen, Soybean Allergy, Parallel Reaction Monitoring, Incurred Food Matrices, Mass Spectrometry

Melanie Downs
contact affiliation	Food Allergy Research and Resource Program, Department of Food Science and Technology, University of Nebraska-Lincoln
contact email	mdowns2@unl.edu
lab head
Melanie Downs
contact affiliation	Food Allergy Research and Resource Program, Department of Food Science and Technology, University of Nebraska-Lincoln
contact email	mdowns2@unl.edu
dataset submitter

Panorama Public dataset URI