2021
DOI: 10.1038/s41598-021-95036-0
|View full text |Cite
|
Sign up to set email alerts
|

The post-translational modification landscape of commercial beers

Abstract: Beer is one of the most popular beverages worldwide. As a product of variable agricultural ingredients and processes, beer has high molecular complexity. We used DIA/SWATH-MS to investigate the proteomic complexity and diversity of 23 commercial Australian beers. While the overall complexity of the beer proteome was modest, with contributions from barley and yeast proteins, we uncovered a very high diversity of post-translational modifications (PTMs), especially proteolysis, glycation, and glycosylation. Prote… Show more

Help me understand this report
View preprint versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2
1

Citation Types

0
21
0

Year Published

2022
2022
2024
2024

Publication Types

Select...
6
1

Relationship

1
6

Authors

Journals

citations
Cited by 15 publications
(21 citation statements)
references
References 42 publications
(47 reference statements)
0
21
0
Order By: Relevance
“…Sorghum samples were searched against all predicted proteins from S. bicolor v3. 1 analyses was performed as previously described (33), protein abundances were re-calculated using a strict 1% FDR cut-off of (21). Normalisation was performed to either the total protein abundance in each sample or to the abundance of trypsin self-digest peptides, as previously described (29).…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…Sorghum samples were searched against all predicted proteins from S. bicolor v3. 1 analyses was performed as previously described (33), protein abundances were re-calculated using a strict 1% FDR cut-off of (21). Normalisation was performed to either the total protein abundance in each sample or to the abundance of trypsin self-digest peptides, as previously described (29).…”
Section: Discussionmentioning
confidence: 99%
“…The abundance of peptide fragments, peptides, and proteins was determined using PeakView 2.2 (SCIEX) with settings: shared peptides, allowed; peptide confidence threshold, 99%; false 6 discovery rate, 1%; XIC extraction window, 6 min; XIC width, 75 ppm. Protein-centric analyses was performed as previously described (33), protein abundances were re-calculated using a strict 1% FDR cut-off of (21). Normalisation was performed to either the total protein abundance in each sample or to the abundance of trypsin self-digest peptides, as previously described (29).…”
Section: Discussionmentioning
confidence: 99%
“…The analysis of the multiple regression equation for non-alcoholic beer (1) showed that the most significant relationship exists between the original extract data (the amount of grain raw materials) and the concentration of nitrogenous compounds: with an increase in the amount of raw materials used, the content of soluble nitrogenous compounds are reduced, which can be explained by coagulation processes on the part of the beer matrix and high-molecular protein compounds, unstable due to molecular weight, as well as a decrease in nitrogenous compounds in the process of alcohol removal in non-alcoholic beer technology [38][39][40][41].…”
Section: The Determination and Mathimatical Analysis Of Beer's Sample Compositionmentioning
confidence: 99%
“…The beer's quality as a colloidal system is determined by the organic compounds that form its structure. The grain (malted and unmalted cultures), the plant raw material (hops and hop products), and the yeast strain ultimately determine the sensory profile of the finished beer [1]. It is confirmed that, on the one hand, the overall complexity of the beer proteome is narrow and is caused by the protein molecules of Hordeum vulgare (barley) as a primary source, and yeast, but, on the other hand, there is a large variety of posttranslational modifications (PTMs) created as a result of hydrolytic cleavage (proteolysis), glycation, and glycosylation during malting, mashing, and other technological stages of brewing.…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation