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      Deciphering the complexities of the wheat flour proteome using quantitative two-dimensional electrophoresis, three proteases and tandem mass spectrometry

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          Abstract

          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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          Most cited references70

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          Wheat.

          P. Shewry (2009)
          Wheat is the dominant crop in temperate countries being used for human food and livestock feed. Its success depends partly on its adaptability and high yield potential but also on the gluten protein fraction which confers the viscoelastic properties that allow dough to be processed into bread, pasta, noodles, and other food products. Wheat also contributes essential amino acids, minerals, and vitamins, and beneficial phytochemicals and dietary fibre components to the human diet, and these are particularly enriched in whole-grain products. However, wheat products are also known or suggested to be responsible for a number of adverse reactions in humans, including intolerances (notably coeliac disease) and allergies (respiratory and food). Current and future concerns include sustaining wheat production and quality with reduced inputs of agrochemicals and developing lines with enhanced quality for specific end-uses, notably for biofuels and human nutrition.
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            Alpha-gliadin genes from the A, B, and D genomes of wheat contain different sets of celiac disease epitopes

            Background Bread wheat (Triticum aestivum) is an important staple food. However, wheat gluten proteins cause celiac disease (CD) in 0.5 to 1% of the general population. Among these proteins, the α-gliadins contain several peptides that are associated to the disease. Results We obtained 230 distinct α-gliadin gene sequences from severaldiploid wheat species representing the ancestral A, B, and D genomes of the hexaploid bread wheat. The large majority of these sequences (87%) contained an internal stop codon. All α-gliadin sequences could be distinguished according to the genome of origin on the basis of sequence similarity, of the average length of the polyglutamine repeats, and of the differences in the presence of four peptides that have been identified as T cell stimulatory epitopes in CD patients through binding to HLA-DQ2/8. By sequence similarity, α-gliadins from the public database of hexaploid T. aestivum could be assigned directly to chromosome 6A, 6B, or 6D. T. monococcum (A genome) sequences, as well as those from chromosome 6A of bread wheat, almost invariably contained epitope glia-α9 and glia-α20, but never the intact epitopes glia-α and glia-α2. A number of sequences from T. speltoides, as well as a number of sequences fromchromosome 6B of bread wheat, did not contain any of the four T cell epitopes screened for. The sequences from T. tauschii (D genome), as well as those from chromosome 6D of bread wheat, were found to contain all of these T cell epitopes in variable combinations per gene. The differences in epitope composition resulted mainly from point mutations. These substitutions appeared to be genome specific. Conclusion Our analysis shows that α-gliadin sequences from the three genomes of bread wheat form distinct groups. The four known T cell stimulatory epitopes are distributed non-randomly across the sequences, indicating that the three genomes contribute differently to epitope content. A systematic analysis of all known epitopes in gliadins and glutenins will lead to better understanding of the differences in toxicity among wheat varieties. On the basis of such insight, breeding strategies can be designed to generate less toxic varieties of wheat which may be tolerated by at least part of the CD patient population.
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              A method for reducing the time required to match protein sequences with tandem mass spectra.

              An algorithm for reducing the time necessary to match a large set of peptide tandem mass spectra with a list of protein sequences is described. This algorithm breaks the process into multiple steps. A rapid survey step identifies all protein sequences that are reasonable candidates for a match with a set of tandem mass spectra. These candidates are then used as models, which are refined by detailed analysis of the set of tandem mass spectra for evidence of incomplete enzymatic hydrolysis, non-specific hydrolysis and chemical modifications of amino acid residues resulting from either post-translational modifications or sample handling. Compared with current one-step methods for matching proteins to mass spectra, this multiple-step method can decrease the time required for the calculation by several orders of magnitude. Copyright 2003 John Wiley & Sons, Ltd.
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                Author and article information

                Journal
                Proteome Sci
                Proteome Science
                BioMed Central
                1477-5956
                2011
                11 February 2011
                : 9
                : 10
                Affiliations
                [1 ]USDA Agricultural Research Service, Western Regional Research Center, Albany CA 94710, USA
                Article
                1477-5956-9-10
                10.1186/1477-5956-9-10
                3238214
                21314956
                34fa4edf-f2cb-4949-a3ac-8f635b47e859
                Copyright ©2011 Dupont et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 16 November 2010
                : 11 February 2011
                Categories
                Research

                Molecular biology
                Molecular biology

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