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...
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Veröffentlicht in: | Analytica chimica acta 2022-04, Vol.1201, p.339616-339616, Article 339616 |
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Sprache: | eng |
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Zusammenfassung: | 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 α-lactalbumin, β-lactoglobulin and β-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.
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•Automated untargeted method to analyse the peptide composition of food hydrolysates.•Guidelines to evaluate the completeness and reproducibility of peptide annotations.•Absolute and label-free peptide quantification with UV absorbance.•Amino acid sequence coverages for single and mixed hydrolysates were 99–100%.•Concentration based sequence coverage only decreased on average 4% after mixing. |
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ISSN: | 0003-2670 1873-4324 |
DOI: | 10.1016/j.aca.2022.339616 |