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Species Determination and Quantitation in Mixtures Using MRM Mass Spectrometry of Peptides Applied to Meat Authentication
Published on: September 20, 2016
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An Integrative Glycomic Approach for Quantitative Meat Species Profiling.
Sean Chia1, Gavin Teo1, Shi Jie Tay1
1Bioprocessing Technology Institute, Agency for Science Technology and Research (A*STAR), Singapore 138668, Singapore.
Foods (Basel, Switzerland)
|July 9, 2022
Summary
Food fraud is costly, necessitating accurate meat profiling. A novel glycomic approach analyzing O- and N-glycans successfully distinguished chicken, pork, and beef, offering a robust method for species authentication.
Area of Science:
- Food Science
- Analytical Chemistry
- Biotechnology
Background:
- Food fraud, including mislabeling of meat species, poses a significant economic threat to the global food industry, estimated at USD 6.2 to USD 40 billion annually.
- Accurate and robust methods are crucial for characterizing and profiling meat samples to combat food fraud and ensure product authenticity.
Purpose of the Study:
- To develop and validate a novel glycomic approach for the accurate profiling and authentication of meat from different species.
- To investigate the distinct glycan profiles of chicken, pork, and beef meat samples.
Main Methods:
- Utilized O-glycan analysis via liquid chromatography-mass spectrometry with time-of-flight detection (LC-MS qTOF).
- Employed high-resolution, non-targeted ultra-performance liquid chromatography-fluorescence-mass spectrometry (UPLC-FLR-MS) for N-glycan analysis.
- Applied principal component analysis (PCA) to multi-attribute glycan data for species discrimination.
Main Results:
- The integrated glycomic approach revealed significantly distinct glycan profiles between chicken, pork, and beef.
- Key glycosylation attributes, including fucosylation, sialylation, galactosylation, high mannose, α-galactose, Neu5Gc, and Neu5Ac, showed significant inter-species differences.
- Principal component analysis effectively separated meat samples from different species based on their multi-attribute glycan data.
Conclusions:
- A glycomics-based workflow utilizing O- and N-glycan analysis provides a robust method for meat profiling and species authentication.
- This glycoanalytical methodology demonstrates potential for application in other high-value biotechnology industries requiring product authentication.
