Towards the establishment of a comprehensive food inspection system: An approach to utilize de novo peptide sequencing from MS/MS spectra

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.