Proteome-Based Analysis of Colloidal Instability Enables the Detection of Haze-Active Proteins in Beer
Schulte F, Flaschel E, Niehaus K (2016)
Journal of Agricultural and Food Chemistry 64(35): 6752-6761.
Zeitschriftenaufsatz
| Veröffentlicht | Englisch
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Einrichtung
Abstract / Bemerkung
Colloidal haze is a serious quality defect of bright beers that considerably reduces their shelf life and is thought to be triggered by hordeins, a class of proline-rich barley proteins. In this work, the proteomes of fresh and old beers were investigated in bottled pilsners and compared to the protein inventory of haze to identify specific haze-active proteins. Haze isolates dissolved in rehydration buffer contained high concentrations of proteins and sugars but provided protein gels with weak spot signals. Consequently, a treatment for the chemical deglycation with trifluoromethanesulfonic acid was applied, which resulted in the identification of protein Z4, LTP1, CMb, CMe, pUP13, 3a, and Bwiph as constituents of the haze proteome. Because only one hordein was detectable and the proline content in haze hydrolysates was lower than those of barley prolamins, our results suggest that this class of proteins is of minor importance for haze development.
Stichworte
beer proteome;
beer haze;
colloidal instability;
barley;
yeast;
hordeins;
Hordeum vulgare;
Saccharomyces cerevisiae
Erscheinungsjahr
2016
Zeitschriftentitel
Journal of Agricultural and Food Chemistry
Band
64
Ausgabe
35
Seite(n)
6752-6761
ISSN
0021-8561
eISSN
1520-5118
Page URI
https://pub.uni-bielefeld.de/record/2906183
Zitieren
Schulte F, Flaschel E, Niehaus K. Proteome-Based Analysis of Colloidal Instability Enables the Detection of Haze-Active Proteins in Beer. Journal of Agricultural and Food Chemistry. 2016;64(35):6752-6761.
Schulte, F., Flaschel, E., & Niehaus, K. (2016). Proteome-Based Analysis of Colloidal Instability Enables the Detection of Haze-Active Proteins in Beer. Journal of Agricultural and Food Chemistry, 64(35), 6752-6761. doi:10.1021/acs.jafc.6b02467
Schulte, Fabian, Flaschel, Erwin, and Niehaus, Karsten. 2016. “Proteome-Based Analysis of Colloidal Instability Enables the Detection of Haze-Active Proteins in Beer”. Journal of Agricultural and Food Chemistry 64 (35): 6752-6761.
Schulte, F., Flaschel, E., and Niehaus, K. (2016). Proteome-Based Analysis of Colloidal Instability Enables the Detection of Haze-Active Proteins in Beer. Journal of Agricultural and Food Chemistry 64, 6752-6761.
Schulte, F., Flaschel, E., & Niehaus, K., 2016. Proteome-Based Analysis of Colloidal Instability Enables the Detection of Haze-Active Proteins in Beer. Journal of Agricultural and Food Chemistry, 64(35), p 6752-6761.
F. Schulte, E. Flaschel, and K. Niehaus, “Proteome-Based Analysis of Colloidal Instability Enables the Detection of Haze-Active Proteins in Beer”, Journal of Agricultural and Food Chemistry, vol. 64, 2016, pp. 6752-6761.
Schulte, F., Flaschel, E., Niehaus, K.: Proteome-Based Analysis of Colloidal Instability Enables the Detection of Haze-Active Proteins in Beer. Journal of Agricultural and Food Chemistry. 64, 6752-6761 (2016).
Schulte, Fabian, Flaschel, Erwin, and Niehaus, Karsten. “Proteome-Based Analysis of Colloidal Instability Enables the Detection of Haze-Active Proteins in Beer”. Journal of Agricultural and Food Chemistry 64.35 (2016): 6752-6761.
Daten bereitgestellt von European Bioinformatics Institute (EBI)
2 Zitationen in Europe PMC
Daten bereitgestellt von Europe PubMed Central.
Development of engineered yeast for biosorption of beer haze-active polyphenols.
Cejnar R, Hložková K, Jelínek L, Kotrba P, Dostálek P., Appl Microbiol Biotechnol 101(4), 2017
PMID: 27770176
Cejnar R, Hložková K, Jelínek L, Kotrba P, Dostálek P., Appl Microbiol Biotechnol 101(4), 2017
PMID: 27770176
Deep coverage of the beer proteome.
Grochalová M, Konečná H, Stejskal K, Potěšil D, Fridrichová D, Srbová E, Ornerová K, Zdráhal Z., J Proteomics 162(), 2017
PMID: 28478308
Grochalová M, Konečná H, Stejskal K, Potěšil D, Fridrichová D, Srbová E, Ornerová K, Zdráhal Z., J Proteomics 162(), 2017
PMID: 28478308
References
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