Bromilow Sophie N L, Gethings Lee A, Langridge James I, Shewry Peter R, Buckley Michael, Bromley Michael J, Mills E N Clare
Faculty of Biology, Medicine and Health, Infection, Immunity and Respiratory Medicine, Manchester Academic Health Sciences Centre, Manchester Institute of Biotechnology, University of Manchester Manchester, UK.
Waters Corporation Wilmslow, UK.
Front Plant Sci. 2017 Jan 10;7:2020. doi: 10.3389/fpls.2016.02020. eCollection 2016.
Wheat is the most important food crop in the world, the unique physiochemical properties of wheat gluten enabling a diverse range of food products to be manufactured. However, genetic and environmental factors affect the technological properties of gluten in unpredictable ways. Although newer proteomic methods have the potential to offer much greater levels of information, it is the older gel-based methods that remain most commonly used to identify compositional differences responsible for the variation in gluten functionality, in part due to the nature of their primary sequences. A combination of platforms were investigated for comprehensive gluten profiling: a QTOF with a data independent schema, which incorporated ion mobility (DIA-IM-MS) and a data dependent acquisition (DDA) workflow using a linear ion trap quadrupole (LTQ) instrument. In conjunction with a manually curated gluten sequence database a total of 2736 gluten peptides were identified with only 157 peptides identified by both platforms. These data showed 127 and 63 gluten protein accessions to be inferred with a minimum of one and three unique peptides respectively. Of the 63 rigorously identified proteins, 26 were gliadin species (4 ω-, 14 α-, and 8 γ-gliadins) and 37 glutenins (including 29 LMW glutenin and 8 HMW glutenins). Of the HMW glutenins, three were 1Dx type and five were 1Bx type illustrating the challenge of unambiguous identification of highly polymorphic proteins without cultivar specific gene sequences. The capacity of the platforms to sequence longer peptides was crucial to achieving the number of identifications, the combination of QTOF-LTQ technology being more important than extraction method to obtain a comprehensive profile. Widespread glutamine deamidation, a post-translational modification, was observed adding complexity to an already highly polymorphic mixture of proteins, with numerous insertions, deletions and substitutions. The data shown is the most comprehensive and detailed proteomic profile of gluten to date.
小麦是世界上最重要的粮食作物,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,遗传和环境因素以不可预测的方式影响面筋的技术特性。尽管更新的蛋白质组学方法有可能提供更多信息,但基于凝胶的较老方法仍然是最常用的,用于识别导致面筋功能变化的组成差异,部分原因是其一级序列的性质。研究了多种平台组合用于全面的面筋分析:一种具有数据独立模式的四极杆飞行时间质谱仪(QTOF),它结合了离子淌度(DIA-IM-MS)以及使用线性离子阱四极杆(LTQ)仪器的数据依赖采集(DDA)工作流程。结合一个人工整理的面筋序列数据库,共鉴定出2736个面筋肽段,两个平台共同鉴定出的只有157个肽段。这些数据显示分别有127个和63个面筋蛋白登录号可通过至少一个和三个独特肽段推断出来。在这63个经过严格鉴定的蛋白质中,26个是醇溶蛋白种类(4个ω-醇溶蛋白、14个α-醇溶蛋白和8个γ-醇溶蛋白),37个是谷蛋白(包括29个低分子量谷蛋白和8个高分子量谷蛋白)。在高分子量谷蛋白中,3个是1Dx型,5个是1Bx型,这说明了在没有品种特异性基因序列的情况下明确鉴定高度多态性蛋白质的挑战。平台对较长肽段进行测序的能力对于实现鉴定数量至关重要,QTOF-LTQ技术的组合比提取方法对于获得全面的分析更为重要。观察到广泛存在的谷氨酰胺脱酰胺化这种翻译后修饰,这给本就高度多态的蛋白质混合物增加了复杂性,其中存在大量插入、缺失和替换。所示数据是迄今为止最全面、最详细的面筋蛋白质组分析。