Emulsifying peptides from potato protein predicted by bioinformatics: Stabilization of fish oil-in-water emulsions

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Standard

Emulsifying peptides from potato protein predicted by bioinformatics : Stabilization of fish oil-in-water emulsions. / García Moreno, Pedro Jesús; Jacobsen, Charlotte; Marcatili, Paolo; Gregersen, Simon; Overgaard, Michael T.; Andersen, Mogens L.; Sørensen, Ann-Dorit Moltke; Hansen, Egon B.

I: Food Hydrocolloids, Bind 101, 105529, 2020.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Harvard

García Moreno, PJ, Jacobsen, C, Marcatili, P, Gregersen, S, Overgaard, MT, Andersen, ML, Sørensen, A-DM & Hansen, EB 2020, 'Emulsifying peptides from potato protein predicted by bioinformatics: Stabilization of fish oil-in-water emulsions', Food Hydrocolloids, bind 101, 105529. https://doi.org/10.1016/j.foodhyd.2019.105529

APA

García Moreno, P. J., Jacobsen, C., Marcatili, P., Gregersen, S., Overgaard, M. T., Andersen, M. L., Sørensen, A-D. M., & Hansen, E. B. (2020). Emulsifying peptides from potato protein predicted by bioinformatics: Stabilization of fish oil-in-water emulsions. Food Hydrocolloids, 101, [105529]. https://doi.org/10.1016/j.foodhyd.2019.105529

Vancouver

García Moreno PJ, Jacobsen C, Marcatili P, Gregersen S, Overgaard MT, Andersen ML o.a. Emulsifying peptides from potato protein predicted by bioinformatics: Stabilization of fish oil-in-water emulsions. Food Hydrocolloids. 2020;101. 105529. https://doi.org/10.1016/j.foodhyd.2019.105529

Author

García Moreno, Pedro Jesús ; Jacobsen, Charlotte ; Marcatili, Paolo ; Gregersen, Simon ; Overgaard, Michael T. ; Andersen, Mogens L. ; Sørensen, Ann-Dorit Moltke ; Hansen, Egon B. / Emulsifying peptides from potato protein predicted by bioinformatics : Stabilization of fish oil-in-water emulsions. I: Food Hydrocolloids. 2020 ; Bind 101.

Bibtex

@article{86dbb005864a4ae5ad878d275d58d0f0,
title = "Emulsifying peptides from potato protein predicted by bioinformatics: Stabilization of fish oil-in-water emulsions",
abstract = "This work investigated the use of bioinformatics to predict emulsifying peptides embedded in patatin proteins from potato (Solanum tuberosum). Six peptides (23–29 amino acids) with potentially different predominant structure at the oil/water interface (e.g. α-helix, β-strand or unordered) were identified within patatin sequences. The interfacial tension between peptides solutions and fish oil as well as the physical and oxidative stability of 5 wt% fish oil-in-water emulsions (pH 7) stabilized with synthetic predicted peptides were evaluated. The peptides predicted to have lower amphiphilic score (α1 and α2) led to emulsions with creaming after production and with low oxidative stability. On the other hand, a half hydrophobic and half hydrophilic peptide (γ1), which was predicted to have the highest amphiphilic score, showed a superior ability to reduce interfacial tension (even when compared to casein). γ1-Stabilized emulsion was physically stable during storage (48 h at 50 °C) and presented the lowest droplet size (D4,3 = 0.518 ± 0.011 μm). Electron spin resonance (ESR) and Oxygraph results indicated that the type of synthetic peptide used also affected the oxidative stability of fish oil-in-water emulsions differently. Therefore, this study shows the potential of using bioinformatics to predict emulsifying peptides, reducing time and cost of extensive screening hydrolysis processes.",
keywords = "Electron spin resonance, Interfacial tension, Omega-3, Oxidative stability, Oxygraph, Physical stability",
author = "{Garc{\'i}a Moreno}, {Pedro Jes{\'u}s} and Charlotte Jacobsen and Paolo Marcatili and Simon Gregersen and Overgaard, {Michael T.} and Andersen, {Mogens L.} and S{\o}rensen, {Ann-Dorit Moltke} and Hansen, {Egon B.}",
year = "2020",
doi = "10.1016/j.foodhyd.2019.105529",
language = "English",
volume = "101",
journal = "Food Hydrocolloids",
issn = "0268-005X",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Emulsifying peptides from potato protein predicted by bioinformatics

T2 - Stabilization of fish oil-in-water emulsions

AU - García Moreno, Pedro Jesús

AU - Jacobsen, Charlotte

AU - Marcatili, Paolo

AU - Gregersen, Simon

AU - Overgaard, Michael T.

AU - Andersen, Mogens L.

AU - Sørensen, Ann-Dorit Moltke

AU - Hansen, Egon B.

PY - 2020

Y1 - 2020

N2 - This work investigated the use of bioinformatics to predict emulsifying peptides embedded in patatin proteins from potato (Solanum tuberosum). Six peptides (23–29 amino acids) with potentially different predominant structure at the oil/water interface (e.g. α-helix, β-strand or unordered) were identified within patatin sequences. The interfacial tension between peptides solutions and fish oil as well as the physical and oxidative stability of 5 wt% fish oil-in-water emulsions (pH 7) stabilized with synthetic predicted peptides were evaluated. The peptides predicted to have lower amphiphilic score (α1 and α2) led to emulsions with creaming after production and with low oxidative stability. On the other hand, a half hydrophobic and half hydrophilic peptide (γ1), which was predicted to have the highest amphiphilic score, showed a superior ability to reduce interfacial tension (even when compared to casein). γ1-Stabilized emulsion was physically stable during storage (48 h at 50 °C) and presented the lowest droplet size (D4,3 = 0.518 ± 0.011 μm). Electron spin resonance (ESR) and Oxygraph results indicated that the type of synthetic peptide used also affected the oxidative stability of fish oil-in-water emulsions differently. Therefore, this study shows the potential of using bioinformatics to predict emulsifying peptides, reducing time and cost of extensive screening hydrolysis processes.

AB - This work investigated the use of bioinformatics to predict emulsifying peptides embedded in patatin proteins from potato (Solanum tuberosum). Six peptides (23–29 amino acids) with potentially different predominant structure at the oil/water interface (e.g. α-helix, β-strand or unordered) were identified within patatin sequences. The interfacial tension between peptides solutions and fish oil as well as the physical and oxidative stability of 5 wt% fish oil-in-water emulsions (pH 7) stabilized with synthetic predicted peptides were evaluated. The peptides predicted to have lower amphiphilic score (α1 and α2) led to emulsions with creaming after production and with low oxidative stability. On the other hand, a half hydrophobic and half hydrophilic peptide (γ1), which was predicted to have the highest amphiphilic score, showed a superior ability to reduce interfacial tension (even when compared to casein). γ1-Stabilized emulsion was physically stable during storage (48 h at 50 °C) and presented the lowest droplet size (D4,3 = 0.518 ± 0.011 μm). Electron spin resonance (ESR) and Oxygraph results indicated that the type of synthetic peptide used also affected the oxidative stability of fish oil-in-water emulsions differently. Therefore, this study shows the potential of using bioinformatics to predict emulsifying peptides, reducing time and cost of extensive screening hydrolysis processes.

KW - Electron spin resonance

KW - Interfacial tension

KW - Omega-3

KW - Oxidative stability

KW - Oxygraph

KW - Physical stability

U2 - 10.1016/j.foodhyd.2019.105529

DO - 10.1016/j.foodhyd.2019.105529

M3 - Journal article

AN - SCOPUS:85075265809

VL - 101

JO - Food Hydrocolloids

JF - Food Hydrocolloids

SN - 0268-005X

M1 - 105529

ER -

ID: 235855538