4.5 Article

Peptidome characterization and bioactivity analysis of donkey milk

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JOURNAL OF PROTEOMICS
卷 119, 期 -, 页码 21-29

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ELSEVIER
DOI: 10.1016/j.jprot.2015.01.020

关键词

Peptidomics; Donkey milk; Peptide purification; Protein precipitation

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Donkey milk is an interesting commercial product for its nutritional values, which make it the most suitable mammalian milk for human consumption, and for the bioactivity associated with it and derivative products. To further mine the characterization of donkey milk, an extensive peptidomic study was performed. Two peptide purification strategies were compared to remove native proteins and lipids and enrich the peptide fraction. In one case the whole protein content was precipitated by organic solvent using cold acetone. In the other one the precipitation of the most abundant milk proteins, caseins, was performed under acidic conditions by acetic acid at pH 4.6, instead. The procedures were compared and proved to be partially complementary. Considered together they provided 1330 peptide identifications for donkey milk, mainly coming from the most abundant proteins in milk. The bioactivity of the isolated peptides was also investigated, both by angiotensinconverting-enzyme inhibitory and antioxidant activity assays and by bioinformatics, proving that the isolated peptides did have the tested biological activities. Biological significance The rationale behind this study is that peptides in food matrices often play an important biological role and, despite the extensive study of the protein composition of different samples, they remain poorly characterized. In fact, in a typical shotgun proteomics study endogenous peptides are not properly characterized. In proteomics workflows one limiting point is the isolation process: if it is specific for the purification of proteins, it often comprises a precipitation step which aims at isolating pure protein pellets and remove unwonted interferent compounds. In this way endogenous peptides, which are not effectively precipitated as well as proteins, are removed too and not analyzed at the end of the process. Moreover, endogenous peptides do often originate from precursor proteins, but in phenomena which are independent of the shotgun digestion protocol, thus they can be obtained from cleavage specificities other than ttypsin's, which is the main proteolytic enzyme employed in proteomic experiments. For this reason, in the end, database search will not be effective for identification of these peptides, thus the need to provide different workflows for peptide analysis. In the work presented in this paper this issue is considered for the first time for the analysis of the peptides isolated in donkey milk samples, which have been chosen for its nutritional interest. This study provides additional knowledge on this milk, already characterized by traditional proteomics studies and peptidomic studies after simulated digestion. This type of study is not just a description of the naturally occurring peptidome of a sample, but also represents a starting point to discover and characterize those naturally occurring peptides responsible for the observed bioactivities of biological samples, as in the case of donkey milk, which would remain uncharacterized by other approaches. In this paper an analytical protocol was described for the efficient isolation and purification of peptides in donkey milk, assessing the effect of the purification protocol on the final identifications. Purified peptide samples were also checked to empirically elucidate any ACE inhibitory or antioxidant activity. Finally, the peptidomic results were also further mined by a bioinformatic-driven approach for bioactive peptide identification in the donkey milk samples. In our opinion, the main strengths of this study are related to the improved analytical workflow (either as purification protocol comparison or analytical platform development) which provides a high number of identified peptides, for which the biological significance as potential bioactive peptides has also been investigated. (C) 2015 Elsevier B.V. All rights reserved.

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