Towards the establishment of a comprehensive food inspection system: An approach to utilize de novo peptide sequencing from MS/MS spectra
peer-reviewed · Food and Humanity · 2026
| Date | 2026-07-16 |
| Type | peer-reviewed |
| Venue | Food and Humanity |
| Publisher | Elsevier BV |
| Contribution | downstream-application |
| DOI | 10.1016/j.foohum.2026.101356 |
| Citations (OpenAlex) | 0 |
| Venue 2-year citedness | 3.15 |
Preprint version: Towards the establishment of a comprehensive food inspection system: an approach to utilise de novo peptide sequencing from MS/MS spectra (2026-02-13, SSRN Electronic Journal)
Abstract
Ensuring food safety and preventing food fraud require analytical methods capable of identifying unknown and unexpected contaminants in foods. This study developed a proteomics-based strategy centered on de novo sequencing, in which peptide sequences are directly determined from MS/MS spectra without reliance on protein databases. To obtain high-confidence peptide sequences, mass spectrometry conditions were optimized using tryptic digests of K562 cells. Among the tested platforms, ZenoTOF 7600 operated with a Zeno trap accumulation time of 25 ms and 80 MS/MS events yielded the highest number of peptide sequences, averaging 1,057 peptides with an Average Local Confidence score of ≥99. The resulting peptide sequences were used for species identification and quantitative analysis, with database searching applied as a complementary step. Application of this strategy to oyster extract-supplemented soy sauce enabled identification of species associated with added ingredients and the manufacturing process, demonstrating its potential for detecting unknown adulteration and unexpected contamination.
Methods and tools
- Food inspection de novo peptide screening: Database-free food inspection workflow: de novo sequencing of MS/MS spectra on a ZenoTOF 7600 for species identification and quantitation in food extracts, with database search as a complementary step, aimed at unknown contaminants and food fraud.
Methods it uses
- PEAKS: Commercial DP-based de novo