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Protein-protein crosslinking in food: proteomic characterisation methods, consequences and applications

journal contribution
posted on 2023-05-03, 10:29 authored by Hannah McKerchar, Stefan ClerensStefan Clerens, Renwick Dobson, Jolon Dyer, Evelyne MaesEvelyne Maes, Juliet Gerrard
Background Although formation of protein-protein crosslinks during food processing is known to influence food properties, a detailed molecular view of this crosslinking is still lacking. Even in the case of enzymatic crosslinking, such as with transglutaminase, which is commonly used in the food industry to induce crosslinking in food proteins, questions remain. Understanding the mechanisms of protein crosslinking is crucial to understanding how inherent beneficial characteristics of food can be preserved and enhanced, and therefore how quality, safety and function can be improved. Scope and Approach This work reviews recent developments in the study of crosslinking in food proteins. The advantages and limitations of varying proteomic techniques for evaluating protein-protein crosslinking in foods are discussed and areas of future study suggested. Key Findings and Conclusions The advent of mass spectrometry-based approaches for identifying chemically induced crosslinks in proteins has introduced a welcome set of tools to elucidate protein structure. However, despite this progress, crosslinks that occur naturally in food or form during processing, continue to present unique challenges that have yet to be wholly overcome in studying complex food systems.

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Rights statement

© 2019 Elsevier Ltd. All rights reserved.

Language

  • English

Does this contain Māori information or data?

  • No

Publisher

Elsevier

Journal title

Trends in Food Science and Technology

ISSN

0924-2244

Citation

McKerchar, H. J., Clerens, S., Dobson, R. C. J., Dyer, J. M., Maes, E., & Gerrard, J. A. (2019). Protein-protein crosslinking in food: proteomic characterisation methods, consequences and applications. Trends in Food Science and Technology, 86, 217–229. doi:10.1016/j.tifs.2019.02.005

Job code

152100x02

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