Qualitative and Quantitative Analysis of Ejiao-Related Animal Gelatins through Peptide Markers Using LC-QTOF-MS/MS and Scheduled Multiple Reaction Monitoring (MRM) by LC-QQQ-MS/MS

Wen Jie Wu, Li Feng Li, Hau Yee Fung, Hui Yuan Cheng, Hau Yee Kong, Tin Long Wong, Quan Wei Zhang, Man Liu, Wan Rong Bao, Chu Ying Huo, Shangwei Guo, Haibin Liu, Xiangshan Zhou*, Deng Feng Gao, Quan Bin Han*

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

5 Citations (Scopus)

Abstract

Donkey-hide gelatin, also called Ejiao (colla corii asini), is commonly used as a food health supplement and valuable Chinese medicine. Its growing popular demand and short supply make it a target for fraud, and many other animal gelatins can be found as adulterants. Authentication remains a quality concern. Peptide markers were developed by searching the protein database. However, donkeys and horses share the same database, and there is no specific marker for donkeys. Here, solutions are sought following a database-independent strategy. The peptide profiles of authentic samples of different animal gelatins were compared using LC-QTOF-MS/MS. Fourteen specific markers, including four donkey-specific, one horse-specific, three cattle-specific, and six pig-specific peptides, were successfully found. As these donkey-specific peptides are not included in the current proteomics database, their sequences were determined by de novo sequencing. A quantitative LC-QQQ multiple reaction monitoring (MRM) method was further developed to achieve highly sensitive and selective analysis. The specificity and applicability of these markers were confirmed by testing multiple authentic samples and 110 batches of commercial Ejiao products, 57 of which were found to be unqualified. These results suggest that these markers are specific and accurate for authentication purposes.

Original languageEnglish
Article number4643
Number of pages15
JournalMolecules
Volume27
Issue number14
DOIs
Publication statusPublished - 2 Jul 2022

Scopus Subject Areas

  • Drug Discovery
  • Analytical Chemistry
  • Chemistry (miscellaneous)
  • Molecular Medicine
  • Physical and Theoretical Chemistry
  • Pharmaceutical Science
  • Organic Chemistry

User-Defined Keywords

  • authentication
  • database-independent strategy
  • de novo sequencing
  • Ejiao
  • gelatin
  • peptide marker

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