Bioinformatics tools assist in the screening of potential porcine-specific peptide biomarkers of gelatin and collagen for halal authentication - Abdul Shukor, Muhd Syarafuddin; Abdullah, Mohd Faiz Foong; Zainal Abidin, Siti Aimi Sarah; Yuswan, Mohd Hafis; Mohd Ismail, Azilawati (Malaysian Society of Applied Biology, 2024)
Gelatin and collagen are two animal-derived ingredients that are widely used in various industries. Both have distinctive physico-chemical characteristic that made them ingredients of interest for many industrial players to be applied as there are vast arrays of usage in the food, cosmetic and biomedical fields. However, the origin of gelatin and collagen poses ethical and religious concerns, especially for Muslims and Jews who have restrictions on food consumption. Porcine by-products are of concern for religious and health reasons, and there is a demand for precise and reliable detection techniques. The limitation of DNA detection is due to extreme environment in food processing which results in low extractability of DNA. Therefore, peptide-based detection using mass spectrometry is required. However, identify the suitable marker is like searching needle in haystacks. Hence, combination of bioinformatics and mass spectrometry is proposed. This study aims to identify the specific peptide biomarkers by employing bioinformatics technique which can be applied to identify gelatin and collagen sources with the aid of mass spectrometry. In these approach, combination of Petunia Trans-Proteomic Pipeline (TPP, version 5.2.0) and sequence alignment ClustalW were applied to facilitate the MS data (LC-QTOF-MS) and peptide identification. As a result, 69 fasta file of protein sequence from both UniProtKB and NCBInr have been collected, 81 collagen peptides sequence and 118 gelatine peptides has been attainable that have the potential to distinguish different species. In conclusion, in silico protein sequence approaches helps to enable rapid screening of proteotypic peptides that can serve as species biomarkers proficiently. © 2024 Malaysian Society of Applied Biology.