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      Characterization and Relative Quantitation of Wheat, Rye, and Barley Gluten Protein Types by Liquid Chromatography–Tandem Mass Spectrometry

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          Abstract

          The consumption of wheat, rye, and barley may cause adverse reactions to wheat such as celiac disease, non-celiac gluten/wheat sensitivity, or wheat allergy. The storage proteins (gluten) are known as major triggers, but also other functional protein groups such as α-amylase/trypsin-inhibitors or enzymes are possibly harmful for people suffering of adverse reactions to wheat. Gluten is widely used as a collective term for the complex protein mixture of wheat, rye or barley and can be subdivided into the following gluten protein types (GPTs): α-gliadins, γ-gliadins, ω5-gliadins, ω1,2-gliadins, high- and low-molecular-weight glutenin subunits of wheat, ω-secalins, high-molecular-weight secalins, γ-75k-secalins and γ-40k-secalins of rye, and C-hordeins, γ-hordeins, B-hordeins, and D-hordeins of barley. GPTs isolated from the flours are useful as reference materials for clinical studies, diagnostics or in food analyses and to elucidate disease mechanisms. A combined strategy of protein separation according to solubility followed by preparative reversed-phase high-performance liquid chromatography was employed to purify the GPTs according to hydrophobicity. Due to the heterogeneity of gluten proteins and their partly polymeric nature, it is a challenge to obtain highly purified GPTs with only one protein group. Therefore, it is essential to characterize and identify the proteins and their proportions in each GPT. In this study, the complexity of gluten from wheat, rye, and barley was demonstrated by identification of the individual proteins employing an undirected proteomics strategy involving liquid chromatography–tandem mass spectrometry of tryptic and chymotryptic hydrolysates of the GPTs. Different protein groups were obtained and the relative composition of the GPTs was revealed. Multiple reaction monitoring liquid chromatography–tandem mass spectrometry was used for the relative quantitation of the most abundant gluten proteins. These analyses also allowed the identification of known wheat allergens and celiac disease-active peptides. Combined with functional assays, these findings may shed light on the mechanisms of gluten/wheat-related disorders and may be useful to characterize reference materials for analytical or diagnostic assays more precisely.

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          The Paragon Algorithm, a next generation search engine that uses sequence temperature values and feature probabilities to identify peptides from tandem mass spectra.

          The Paragon Algorithm, a novel database search engine for the identification of peptides from tandem mass spectrometry data, is presented. Sequence Temperature Values are computed using a sequence tag algorithm, allowing the degree of implication by an MS/MS spectrum of each region of a database to be determined on a continuum. Counter to conventional approaches, features such as modifications, substitutions, and cleavage events are modeled with probabilities rather than by discrete user-controlled settings to consider or not consider a feature. The use of feature probabilities in conjunction with Sequence Temperature Values allows for a very large increase in the effective search space with only a very small increase in the actual number of hypotheses that must be scored. The algorithm has a new kind of user interface that removes the user expertise requirement, presenting control settings in the language of the laboratory that are translated to optimal algorithmic settings. To validate this new algorithm, a comparison with Mascot is presented for a series of analogous searches to explore the relative impact of increasing search space probed with Mascot by relaxing the tryptic digestion conformance requirements from trypsin to semitrypsin to no enzyme and with the Paragon Algorithm using its Rapid mode and Thorough mode with and without tryptic specificity. Although they performed similarly for small search space, dramatic differences were observed in large search space. With the Paragon Algorithm, hundreds of biological and artifact modifications, all possible substitutions, and all levels of conformance to the expected digestion pattern can be searched in a single search step, yet the typical cost in search time is only 2-5 times that of conventional small search space. Despite this large increase in effective search space, there is no drastic loss of discrimination that typically accompanies the exploration of large search space.
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            The Overlapping Area of Non-Celiac Gluten Sensitivity (NCGS) and Wheat-Sensitive Irritable Bowel Syndrome (IBS): An Update

            Gluten-related disorders have recently been reclassified with an emerging scientific literature supporting the concept of non-celiac gluten sensitivity (NCGS). New research has specifically addressed prevalence, immune mechanisms, the recognition of non-immunoglobulin E (non-IgE) wheat allergy and overlap of NCGS with irritable bowel syndrome (IBS)-type symptoms. This review article will provide clinicians with an update that directly impacts on the management of a subgroup of their IBS patients whose symptoms are triggered by wheat ingestion.
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              Deciphering the complexities of the wheat flour proteome using quantitative two-dimensional electrophoresis, three proteases and tandem mass spectrometry

              Background Wheat flour is one of the world's major food ingredients, in part because of the unique end-use qualities conferred by the abundant glutamine- and proline-rich gluten proteins. Many wheat flour proteins also present dietary problems for consumers with celiac disease or wheat allergies. Despite the importance of these proteins it has been particularly challenging to use MS/MS to distinguish the many proteins in a flour sample and relate them to gene sequences. Results Grain from the extensively characterized spring wheat cultivar Triticum aestivum 'Butte 86' was milled to white flour from which proteins were extracted, then separated and quantified by 2-DE. Protein spots were identified by separate digestions with three proteases, followed by tandem mass spectrometry analysis of the peptides. The spectra were used to interrogate an improved protein sequence database and results were integrated using the Scaffold program. Inclusion of cultivar specific sequences in the database greatly improved the results, and 233 spots were identified, accounting for 93.1% of normalized spot volume. Identified proteins were assigned to 157 wheat sequences, many for proteins unique to wheat and nearly 40% from Butte 86. Alpha-gliadins accounted for 20.4% of flour protein, low molecular weight glutenin subunits 18.0%, high molecular weight glutenin subunits 17.1%, gamma-gliadins 12.2%, omega-gliadins 10.5%, amylase/protease inhibitors 4.1%, triticins 1.6%, serpins 1.6%, purinins 0.9%, farinins 0.8%, beta-amylase 0.5%, globulins 0.4%, other enzymes and factors 1.9%, and all other 3%. Conclusions This is the first successful effort to identify the majority of abundant flour proteins for a single wheat cultivar, relate them to individual gene sequences and estimate their relative levels. Many genes for wheat flour proteins are not expressed, so this study represents further progress in describing the expressed wheat genome. Use of cultivar-specific contigs helped to overcome the difficulties of matching peptides to gene sequences for members of highly similar, rapidly evolving storage protein families. Prospects for simplifying this process for routine analyses are discussed. The ability to measure expression levels for individual flour protein genes complements information gained from efforts to sequence the wheat genome and is essential for studies of effects of environment on gene expression.
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                Author and article information

                Contributors
                URI : https://loop.frontiersin.org/people/301342
                URI : https://loop.frontiersin.org/people/597424
                Journal
                Front Plant Sci
                Front Plant Sci
                Front. Plant Sci.
                Frontiers in Plant Science
                Frontiers Media S.A.
                1664-462X
                13 December 2019
                2019
                : 10
                : 1530
                Affiliations
                [1] 1Leibniz-Institute for Food Systems Biology at the Technical University of Munich , Freising, Germany
                [2] 2CSIRO Agriculture and Food , St Lucia, QLD, Australia
                [3] 3School of Science, Edith Cowan University , Joondalup, WA, Australia
                [4] 4Department of Bioactive and Functional Food Chemistry, Institute of Applied Biosciences, Karlsruhe Institute of Technology (KIT) , Karlsruhe, Germany
                Author notes

                Edited by: Nicolas L. Taylor, University of Western Australia, Australia

                Reviewed by: Robert Winkler, Center for Research and Advanced Studies (CINVESTAV), Mexico; Barbara Prandi, University of Parma, Italy

                *Correspondence: Katharina A. Scherf, k.scherf.leibniz-lsb@ 123456tum.de

                This article was submitted to Plant Proteomics, a section of the journal Frontiers in Plant Science

                Article
                10.3389/fpls.2019.01530
                6923249
                31921226
                8c79522b-57bf-41ba-beba-6d371e7accf7
                Copyright © 2019 Lexhaller, Colgrave and Scherf

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 02 August 2019
                : 01 November 2019
                Page count
                Figures: 2, Tables: 6, Equations: 0, References: 62, Pages: 16, Words: 10070
                Categories
                Plant Science
                Original Research

                Plant science & Botany
                allergy,amylase/trypsin-inhibitor,celiac disease,gliadin,gluten,mass spectrometry,non-celiac gluten sensitivity,proteomics

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