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Shotgun Proteomics and Protein-Based Bioinformatics for the Characterization of Food-Derived Bioactive Peptides

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Shotgun Proteomics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2259))

Abstract

A workflow for the characterization of food-derived bioactive peptides is described in this chapter. The workflow integrates two consecutive steps: a discovery phase and a protein-based bioinformatic phase. In the first step (discovery phase), a shotgun bottom-up proteomics approach is used to create a reference data set for a selected food proteome. Afterward, in a second step (bioinformatic phase), the reference proteome is subjected to several in silico protein-based bioinformatic analyses to predict and characterize potential bioactive peptides after an in silico human gastrointestinal digestion. Using this workflow, bioactive collagen peptides, antihypertensive, antimicrobial, and antitumor peptides were predicted as potential valuable bioactive peptides from seafood and marine by-products. It is concluded that the combination of the global shotgun proteomic analysis and the analysis by protein-based bioinformatics can provide a rapid strategy for the characterization of new potential food-derived bioactive peptides.

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References

  1. Vermeirssen V, Van Camp J, Verstraete W (2004) Bioavailability of angiotensin I converting enzyme inhibitory peptides. Br J Nutr 92:357–366

    Article  CAS  Google Scholar 

  2. Sánchez A, Vazquez A (2017) Bioactive peptides: a review. Food Qual Saf 1:29–46

    Article  Google Scholar 

  3. Yamamoto N (1997) Antihypertensive peptides derived from food proteins. Biopolymers 43:129–134

    Article  CAS  Google Scholar 

  4. Guang C, Phillips RD (2009) Plant food-derived angiotensin I converting enzyme inhibitory peptides. J Agric Food Chem 57:5113–5120

    Article  CAS  Google Scholar 

  5. Suarez-Jimenez GM, Burgos-Hernandez A, Ezquerra-Brauer JM (2012) Bioactive peptides and depsipeptides with anticancer potential: sources from marine animals. Mar Drugs 10:963–986

    Article  CAS  Google Scholar 

  6. Ryan JT, Ross RP, Bolton D, Fitzgerald GF, Stanton C (2011) Bioactive peptides from muscle sources: meat and fish. Nutrients 3:765–791

    Article  CAS  Google Scholar 

  7. Cunsolo V, Saletti R, Muccilli V, Gallina S, Di Francesco A, Foti S (2017) Proteins and bioactive peptides from donkey milk: the molecular basis for its reduced allergenic properties. Food Res Int 99:41–57

    Article  CAS  Google Scholar 

  8. Moller NP, Scholz-Ahrens KE, Roos N, Schrezenmeir J (2008) Bioactive peptides and proteins from foods: indication for health effects. Eur J Nutr 47:171–182

    Article  CAS  Google Scholar 

  9. Amado IR, Vázquez JA, González P, Esteban-Fernández D, Carrera M, Piñeiro C (2014) Identification of the major ACE-inhibitory peptides produced by enzymatic hydrolysis of a protein concentrate from cuttlefish wastewater. Mar Drugs 12:1390–1405

    Article  CAS  Google Scholar 

  10. Mora L, Gallego M, Toldrá F (2018) ACEI-inhibitory peptides naturally generated in meat and meat products and their health relevance. Nutrients 10:1259

    Article  Google Scholar 

  11. Carrera M, Cañas B, Gallardo JM (2013) The sarcoplasmic fish proteome: pathways, metabolic networks and potential bioactive peptides for nutritional inferences. J Proteome 78:211–220

    Article  CAS  Google Scholar 

  12. Agyei D, Tsopmo A, Udenigwe CC (2018) Bioinformatics and peptidomics approaches to the discovery and analysis of food-derived bioactive peptides. Anal Bioanal Chem 410:3463–3472

    Article  CAS  Google Scholar 

  13. Anekthanakul K, Apiradee Hongsthong A, Jittisak Senachak J, Ruengjitchatchawalya M (2018) SpirPep: an in silico digestion-based platform to assist bioactive peptides discovery from a genome-wide database. BMC Bioinformatics 19:149

    Article  Google Scholar 

  14. Arena S, Renzone G, Scaloni A (2020) A multi-approach peptidomic analysis of hen egg white reveals novel putative bioactive molecules. J Proteome 215:103646

    Article  CAS  Google Scholar 

  15. Carrera M, Ezquerra-Brauer JM, Aubourg SP (2020) Characterization of the jumbo squid (Dosidicus gigas) skin by-product by shotgun proteomics and protein-based bioinformatics. Mar Drugs 18:31

    Article  CAS  Google Scholar 

  16. Gallardo JM, Carrera M, Ortea I (2013) Proteomics in food science. In: Cifuentes A (ed) Foodomics: advanced mass spectrometry in modern food science and nutrition. John Wiley & Sons Inc., Hoboken, NJ, USA, pp 125–165

    Chapter  Google Scholar 

  17. Carrera M, González-Fernández A, Magadán S, Mateos J, Pedrós L, Medina I, Gallardo JM (2019) Molecular characterization of B-cell epitopes for the major fish allergen, parvalbumin, by shotgun proteomics, protein-based bioinformatics and IgE-reactive approaches. J Proteome 200:123–133

    Article  CAS  Google Scholar 

  18. Perkins DN, Pappin DJC, Creasy DM, Cottrell JS (1999) Probability-based protein identification by searching sequence databases using mass spectrometry data. Electrophoresis 20:3551–3567

    Article  CAS  Google Scholar 

  19. Eng JK, McCormack AL, Yates JR III (1994) An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database. J Am Soc Mass Spectrom 5:976–989

    Article  CAS  Google Scholar 

  20. Kall L, Canterbury JD, Weston J, Noble WS, MacCoss MJ (2007) Semi-supervised learning for peptide identification from shotgun proteomics datasets. Nat Methods 4:923–925

    Article  Google Scholar 

  21. Keller A, Nesvizhskii AI, Kolker E, Aebersold R (2002) Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search. Anal Chem 74:5383–5392

    Article  CAS  Google Scholar 

  22. Capriotti AL, Cavaliere C, Foglia P, Piovesana S, Samperi R, Zenezini Chiozzi R, Laganà A (2015) Development of an analytical strategy for the identification of potential bioactive peptides generated by in vitro tryptic digestion of fish muscle proteins. Anal Bioanal Chem 407:845–854

    Article  CAS  Google Scholar 

  23. Amorim FG, Coitinho LB, Dias AT, Friques AGF, Monteiro BL, Rezende LCD, Pereira TMC, Campagnaro BP, De Pauw E, Vasquez EC, Quinton L (2019) Identification of new bioactive peptides from kefir milk through proteopeptidomics: bioprospection of antihypertensive molecules. Food Chem 282:109–119

    Article  CAS  Google Scholar 

  24. Wang G, Li X, Wang Z (2016) APD3: the antimicrobial peptide database as a tool for research and education. Nucleic Acids Res 4:D1087–D1093

    Article  Google Scholar 

  25. Jimsheena VK, Gowda LR (2010) Arachin derived peptides as selective angiotensin I-converting enzyme (ACE) inhibitors: structure-activity relationship. Peptides 31:1165–1176

    Article  CAS  Google Scholar 

  26. Minkiewicz P, Iwaniak A, Darewicz M (2019) BIOPEP-UWM database of bioactive peptides: current opportunities. Int J Mol Sci 20:5978

    Article  CAS  Google Scholar 

  27. Shi L, Zhang Q, Rui W, Lu M, Jing X, Shang T, Tang J (2004) BioPD: a web-based information center for bioactive peptides. Regul Pept 120:1–3

    Article  CAS  Google Scholar 

  28. Li Q, Zhang C, Chen H, Xue J, Guo X, Liang M, Chen M (2018) BioPepDB: an integrated data platform for food-derived bioactive peptides. Int J Food Sci Nutr 69:963–968

    Article  CAS  Google Scholar 

  29. Thomas S, Karnik S, Barai RS, Jayaraman VK, Idicula-Thomas S (2010) CAMP: a useful resource for research on antimicrobial peptides. Nucleic Acids Res 38:D774–D780

    Article  CAS  Google Scholar 

  30. Panyayai T, Ngamphiw C, Tongsima S, Mhuantong W, Limsripraphan W, Choowongkomon K, Sawatdichaikul O (2019) FeptideDB: a web application for new bioactive peptides from protein. Heliyon 5:e02076

    Article  Google Scholar 

  31. Rong M, Zhou B, Zhou R, Liao Q, Zeng Y, Xu S, Liu Z (2019) PPIP: automated software for identification of bioactive endogenous peptides. J Proteome Res 18:721–727

    Article  CAS  Google Scholar 

  32. Wang J, Yin T, Xiao X, He D, Xue Z, Jiang X, Wang Y (2018) StraPep: a structure database of bioactive peptides. Database (Oxford) 2018:bay038

    Google Scholar 

  33. Aguilera-Mendoza L, Marrero-Ponce Y, Beltran JA, Tellez Ibarra R, Guillen-Ramirez HA, Brizuela CA (2019) Graph-based data integration from bioactive peptide databases of pharmaceutical interest: towards an organized collection enabling visual network analysis. Bioinformatics 35:4739–4747

    Article  CAS  Google Scholar 

  34. Mooney C, Haslam NJ, Pollastri DC (2012) Towards the improved discovery and design of functional peptides: common features of diverse classes permit generalized prediction of bioactivity. PLoS One 7:e45012

    Article  CAS  Google Scholar 

  35. Gasteiger E, Hoogland C, Gattiker A, Duvaud S, Wilkins MR, Appel RD, Bairoch A (2005) Protein identification and analysis tools on the ExPASy server. In: Walker JM (ed) The proteomics protocols handbook. Humana Press, Totowa, NJ, pp 571–607

    Chapter  Google Scholar 

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Acknowledgments

The authors wish to express their gratitude to Lorena Barros for her excellent technical assistance in this study. This work was supported by the GAIN-Xunta de Galicia Project (IN607D 2017/01) and the Spanish AEI/EU-FEDER (PID2019-103845RB-C21) project. Dr. Mónica Carrera is supported by the Ramón y Cajal contract (Ministry of Science and Innovation of Spain).

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Correspondence to Mónica Carrera .

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Carrera, M., Pazos, M., Aubourg, S.P., Gallardo, J.M. (2021). Shotgun Proteomics and Protein-Based Bioinformatics for the Characterization of Food-Derived Bioactive Peptides. In: Carrera, M., Mateos, J. (eds) Shotgun Proteomics. Methods in Molecular Biology, vol 2259. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1178-4_14

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  • DOI: https://doi.org/10.1007/978-1-0716-1178-4_14

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-1177-7

  • Online ISBN: 978-1-0716-1178-4

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