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REVIEW ARTICLE
Gel Electrophoresis and Mass Spectrometry Supported by Bioinformatics for the Detection of Food Allergens – Opportunities to Advance the State of the Art – A Review
1
Department of Food Biochemistry, University of Warmia and Mazury in Olsztyn, Plac Cieszyński 1, 10-26 Olsztyn, Poland
Submission date: 2026-04-15
Acceptance date: 2026-10-26
Corresponding author
Piotr Minkiewicz
Department of Food Biochemistry, University of Warmia and Mazury in Olsztyn, Plac Cieszyński 1, 10-26 Olsztyn, Poland
Department of Food Biochemistry, University of Warmia and Mazury in Olsztyn, Plac Cieszyński 1, 10-26 Olsztyn, Poland
KEYWORDS
TOPICS
ABSTRACT
The aim of the present review was to discuss the current state of the art and to highlight opportunities for the development of selected methods deployed for allergen identification, namely gel electrophoresis and mass spectrometry. The review presents possibilities of implementing solutions aimed at improving the reproducibility of gel electrophoresis and supporting mass spectrometry through the use of existing, publicly available bioinformatics tools. In the case of electrophoresis, the automated matching of gel images may improve reproducibility and traceability. This approach can be applied to compare electrophoregrams obtained from various experiments. Automated matching using computer programs may also be employed to optimize protocols involving gel electrophoresis and immunoblotting. These protocols may further be developed using dedicated software for processing images of two-dimensional gels. Identification of allergenic proteins by mass spectrometry is based on the sequencing of peptides being fragments of proteins of interest. Such peptides are increasingly often not attributable to a single protein, but rather to a family of homologous proteins according to the principles of comparative proteomics. A conventional statistical criterion, namely over 95% probability that a protein precursor of a peptide is synthesized by an organism belonging to a given taxon or a set of taxa, may be proposed for the systematic classification of identified proteins. The structural classification of allergens, particularly the newly identified ones, should be supported by deep integration of various bioinformatics tools used for the description of protein families, spatial structures, sequences, and epitopes.
FUNDING
This work was supported by Minister of Science under “the Regional Initiative of Excellence Program”.
CONFLICT OF INTEREST
Authors declare no conflict of interests.
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