Statistical analysis of the experimental variation in the proteomic characterization of human plasma by two-dimensional difference gel electrophoresis
Statistical analysis of the experimental variation in the proteomic characterization of human plasma by two-dimensional difference gel electrophoresis
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DOI：
10.1021/pr060100p
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发表时间：
2006-10-06
影响因子：
4.4
通讯作者：
McCutchen-Maloney, Sandra L.
中科院分区：
文献类型：
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作者：
Corzett, Todd H.;Fodor, Imola K.;McCutchen-Maloney, Sandra L.
人血浆的复杂性对响应于疾病的差异表达的高效和可重复的蛋白质组学分析提出了许多挑战。在可以从人血浆中鉴定个体变异和疾病特异性蛋白质生物标志物之前，必须量化蛋白质分离和检测技术中固有的实验变异性。我们报告中发现的变化，在二维差异凝胶电泳（2-D DIGE）分析人血浆。对8份等份人血浆样品进行前6种最高丰度蛋白质消除，随后在12个凝胶上对总共24份DIGE样品进行一式三份分析。逐点标准差估计值表明，在人血浆的简单ANOVA实验中，可通过可管理的重复次数检测到大于2的倍数变化。混合效应统计建模量化了染料的影响，并将逐点方差分离为样品制备、凝胶间差异和随机误差的组分。发现凝胶-凝胶组分是最大的变异来源，其次是样品制备步骤。一个改进的协议，建议的前6个高丰度蛋白质的耗尽，这沿着使用的统计建模和未来的改进，在凝胶质量和图像处理，可以进一步减少的变化和提高效率的2-D DIGE蛋白质组学分析的人血浆。
The complexity of human plasma presents a number of challenges to the efficient and reproducible proteomic analysis of differential expression in response to disease. Before individual variation and disease-specific protein biomarkers can be identified from human plasma, the experimental variability inherent in the protein separation and detection techniques must be quantified. We report on the variation found in two-dimensional difference gel electrophoresis (2-D DIGE) analysis of human plasma. Eight aliquots of a human plasma sample were subjected to top-6 highest abundant protein depletion and were subsequently analyzed in triplicate for a total of 24 DIGE samples on 12 gels. Spot-wise standard deviation estimates indicated that fold changes greater than 2 can be detected with a manageable number of replicates in simple ANOVA experiments with human plasma. Mixed-effects statistical modeling quantified the effect of the dyes, and segregated the spot-wise variance into components of sample preparation, gel-to-gel differences, and random error. The gel-to-gel component was found to be the largest source of variation, followed by the sample preparation step. An improved protocol for the depletion of the top-6 high-abundance proteins is suggested, which, along with the use of statistical modeling and future improvements in gel quality and image processing, can further reduce the variation and increase the efficiency of 2-D DIGE proteomic analysis of human plasma.