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一个经过整理的麸质蛋白序列数据库,以支持用于测定无麸质食品中麸质的蛋白质组学方法的开发。

A curated gluten protein sequence database to support development of proteomics methods for determination of gluten in gluten-free foods.

作者信息

Bromilow Sophie, Gethings Lee A, Buckley Mike, Bromley Mike, Shewry Peter R, Langridge James I, Clare Mills E N

机构信息

School of Biological Sciences, Manchester Institute of Biotechnology, Manchester Academic Health Sciences Centre, University of Manchester, M17DN, UK.

Waters Corporation, Stamford Avenue, Altrincham Road, Wilmslow SK9 4AX, UK.

出版信息

J Proteomics. 2017 Jun 23;163:67-75. doi: 10.1016/j.jprot.2017.03.026. Epub 2017 Apr 4.

Abstract

UNLABELLED

The unique physiochemical properties of wheat gluten enable a diverse range of food products to be manufactured. However, gluten triggers coeliac disease, a condition which is treated using a gluten-free diet. Analytical methods are required to confirm if foods are gluten-free, but current immunoassay-based methods can unreliable and proteomic methods offer an alternative but require comprehensive and well annotated sequence databases which are lacking for gluten. A manually a curated database (GluPro V1.0) of gluten proteins, comprising 630 discrete unique full length protein sequences has been compiled. It is representative of the different types of gliadin and glutenin components found in gluten. An in silico comparison of their coeliac toxicity was undertaken by analysing the distribution of coeliac toxic motifs. This demonstrated that whilst the α-gliadin proteins contained more toxic motifs, these were distributed across all gluten protein sub-types. Comparison of annotations observed using a discovery proteomics dataset acquired using ion mobility MS/MS showed that more reliable identifications were obtained using the GluPro V1.0 database compared to the complete reviewed Viridiplantae database. This highlights the value of a curated sequence database specifically designed to support the proteomic workflows and the development of methods to detect and quantify gluten.

SIGNIFICANCE

We have constructed the first manually curated open-source wheat gluten protein sequence database (GluPro V1.0) in a FASTA format to support the application of proteomic methods for gluten protein detection and quantification. We have also analysed the manually verified sequences to give the first comprehensive overview of the distribution of sequences able to elicit a reaction in coeliac disease, the prevalent form of gluten intolerance. Provision of this database will improve the reliability of gluten protein identification by proteomic analysis, and aid the development of targeted mass spectrometry methods in line with Codex Alimentarius Commission requirements for foods designed to meet the needs of gluten intolerant individuals.

摘要

未标注

小麦面筋独特的物理化学性质使得能够制造出各种各样的食品。然而,面筋会引发乳糜泻,这种疾病需采用无麸质饮食进行治疗。需要分析方法来确认食品是否无麸质,但目前基于免疫分析的方法可能不可靠,蛋白质组学方法提供了一种替代方案,但需要全面且注释良好的序列数据库,而麸质缺乏这样的数据库。现已汇编了一个手动整理的麸质蛋白数据库(GluPro V1.0),其中包含630个离散的独特全长蛋白序列。它代表了麸质中发现的不同类型的醇溶蛋白和谷蛋白成分。通过分析乳糜泻毒性基序的分布,对它们的乳糜泻毒性进行了计算机模拟比较。这表明,虽然α-醇溶蛋白含有更多毒性基序,但这些基序分布在所有麸质蛋白亚型中。使用离子淌度MS/MS获得的发现蛋白质组学数据集观察到的注释比较表明,与完整的经过审核的绿藻植物数据库相比,使用GluPro V1.0数据库可获得更可靠的鉴定结果。这突出了专门设计用于支持蛋白质组学工作流程以及检测和定量麸质方法开发的整理序列数据库的价值。

意义

我们构建了第一个以FASTA格式的手动整理的开源小麦麸质蛋白序列数据库(GluPro V1.0),以支持蛋白质组学方法在麸质蛋白检测和定量中的应用。我们还对手动验证的序列进行了分析,首次全面概述了能够在乳糜泻(麸质不耐受的常见形式)中引发反应的序列分布。提供这个数据库将提高蛋白质组学分析鉴定麸质蛋白的可靠性,并有助于根据食品法典委员会对旨在满足麸质不耐受个体需求的食品的要求开发靶向质谱方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4f89/5479479/0c3f1fc7be5e/fx1.jpg

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