A method to identify and quantify the complete peptide composition in protein hydrolysates

Automated approaches from proteomics are used to characterise peptides for food applications and in protein digests. Peptide annotations and confidence in these annotations are then based on the fragment spectra. Low reproducibility in repeat analyses has been reported even for annotations with high confidence. When analysing protein hydrolysates (in food) it is important to determine criteria that yield highly reproducible annotations. This study provides a structured approach to determine these criteria. Tryptic hydrolysates of alpha-lactalbumin, beta-lactoglobulin and beta-casein were analysed manually and automatically, using an UPLC-PDA-MS method for untargeted identification and absolute label-free quantification of peptides. A lock mass with two components was introduced resulting in an average mass error of 1 ppm. Processing filters were set to ensure reliable annotations based on MS/MS fragmentation, while maintaining maximum amount of information. Peptides in the individual hydrolysates with an MS intensity above the limit of annotation represented 99% of total MS intensity and were 100% consistently annotated between four replicates. Amino acid and peptide sequence coverages for the individual protein hydrolysates were 99-100% and 89-95%, respectively. Mixing the hydrolysates resulted in a loss of 11% of the peptide annotations above the LOA and lower reproducibility (97%) for the remaining annotations, as well as more co-eluting peptides. Calculated concentrations of co-eluting peptides in mixed hydrolysates varied 37 +/- 21% from the value for single hydrolysates. The proposed approach allows complete description of peptide composition with highly repeatable annotations and quantification of peptides even in mixed hydrolysates. (c) 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Automated summary

Automated approaches from proteomics are used to characterize peptides for food applications and in protein digests. This study provides a structured approach to determine criteria that yield highly reproducible annotations. The researchers found that setting appropriate filters can ensure reliable annotations while maintaining maximum amount of information when analyzing protein hydrolysates.