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蛋白质组学技术在评估蛋白质表达方面的效用。

Utility of proteomics techniques for assessing protein expression.

作者信息

Natarajan Savithiry S, Xu Chenping, Cregan Perry, Caperna Thomas J, Garrett Wesley M, Luthria Devanand

机构信息

USDA-ARS, Soybean Genomics and Improvement Laboratory, PSI, Beltsville, MD 20705, USA.

出版信息

Regul Toxicol Pharmacol. 2009 Aug;54(3 Suppl):S32-6. doi: 10.1016/j.yrtph.2008.12.003. Epub 2008 Dec 24.

Abstract

Proteomic technologies are currently used as an effective analytical tool for examining modifications in protein profiles. Understanding the natural variation of soybean seed proteins is necessary to evaluate potential unintended (collateral) effects due to transgenic modifications in genetically modified (GMO) soybeans. We used two-dimensional polyacrylamide gel electrophoresis (2D-PAGE), matrix-assisted laser desorption/ionization time of flight (MALDI-TOF) mass spectrometry, and liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) to separate, identify and quantify the different classes of soybean seed proteins. Sixteen soybean genotypes, including four wild and twelve cultivated genotypes, belonging to four different subgroups were used as models for protein profile evaluation. Significant variations of allergen and anti-nutritional protein profiles were observed between two different groups, cultivated and wild soybean genotypes. However, only minor variations in protein profiles were observed within the soybean samples from the same group (cultivated or wild). These results may be useful to scientists needing to compare GMO and non-GMO soybeans once additional data are generated on additional soybean varieties and the same varieties grown at different geographical locations.

摘要

蛋白质组学技术目前被用作一种有效的分析工具,用于检测蛋白质谱的变化。了解大豆种子蛋白质的自然变异对于评估转基因大豆中转基因修饰可能产生的非预期(附带)效应是必要的。我们使用二维聚丙烯酰胺凝胶电泳(2D-PAGE)、基质辅助激光解吸/电离飞行时间(MALDI-TOF)质谱以及液相色谱-串联质谱(LC-MS/MS)来分离、鉴定和定量不同类别的大豆种子蛋白质。16个大豆基因型,包括4个野生型和12个栽培型,分属于4个不同的亚组,被用作蛋白质谱评估的模型。在栽培型和野生型大豆基因型这两个不同组之间观察到了过敏原和抗营养蛋白谱的显著差异。然而,在来自同一组(栽培型或野生型)的大豆样品中仅观察到了蛋白质谱的微小差异。一旦针对更多大豆品种以及在不同地理位置种植的相同品种生成了更多数据,这些结果可能会对需要比较转基因大豆和非转基因大豆的科学家有用。

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