Food Science and Technology Department
First Advisor
Melanie Downs
Second Advisor
Phillip Johnson
Date of this Version
12-2023
Document Type
Article
Citation
A thesis presented to the faculty of the Graduate College at the University of Nebraska in partial fulfillment of requirements for the degree of Master of Science
Major: Food Science and Technology
Under the supervision of Professors Melanie Downs and Phillip Johnson
Lincoln, Nebraska, December 2023
Abstract
The authentication of products with claims regarding protein sources or compositions is a challenge for traditional analytical methods, which generally lack the required specificity whole protein analysis can provide. For example, the establishment of milk as “A2” is achieved through genetic testing of cows before milk production, with no methods to authenticate milk products themselves. Establishment of A2 milk is completed through genetic testing of the cows before milk production, but with no methods to authenticate the milk products themselves. Intact protein mass spectrometry (MS) has the potential to directly authenticate protein products, including specific proteoform claims. The development of an intact MS method to detect and differentiate major bovine milk proteins (αS1-, αS2-, β-, K-caseins, β-lactoglobulins, and α-lactalbumins) and their proteoforms is needed for protein profile claims and can be an effective tool to analyze milk products for protein authentication.
This was attained through three major phases: generation of a predicted mass database, optimization of sample preparation and instrument parameters conducive with intact bovine milk proteins, and the selection of deconvolution software for protein identification with a mass error tolerance (10 ppm). Fifteen powdered and HTST liquid milk products with an equal distribution of marked A2 and normal commercial products were selected. Each sample was diluted to 1 mg protein/mL in 50 mM ammonium bicarbonate and then defatted through centrifugation of 15 minutes at 3,000 x g. The samples were then cleaned up, desalted through 3 kDa spin column filters, and then separated and analyzed by liquid chromatography mass spectrometry (LC-MS). Data was deconvoluted using BioPharma Finder sliding windows algorithm that were compared to the predicted database and mass were identified. A mean of 85.27% (± 6.68%, n = 57) of the total signal of powdered and liquid HTST milk could be assigned to the predicted database proteoforms using the finalized method. The average ratio of selected normal commercial products was 25.86% A1 and 0.74.14% A2.
Advisors: Melanie Downs and Phillip Johnson
Included in
Food Biotechnology Commons, Food Chemistry Commons, Food Microbiology Commons, Food Processing Commons, Other Food Science Commons
Comments
Copyright 2023, Emily F. Harley-Dowell