Comparative shotgun proteomics using spectral count data and quasi-likelihood modeling.
Comparative shotgun proteomics using spectral count data and quasi-likelihood modeling.
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DOI：
10.1021/pr100527g
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发表时间：
2010-08-06
影响因子：
4.4
通讯作者：
Slebos RJ
中科院分区：
文献类型：
--
作者：
Li M;Gray W;Zhang H;Chung CH;Billheimer D;Yarbrough WG;Liebler DC;Shyr Y;Slebos RJ
Shotgun蛋白质组学为使用液相色谱-串联质谱（LC-MS/MS）的复杂蛋白质组的全球库存提供了最强大的分析平台，并允许对蛋白质变化进行全球分析。然而，复杂的蛋白质组采样目前鸟枪蛋白质组学平台是不完整的，这有助于通过光谱计数方法的肽和蛋白质库存的评估的变化。因此，鸟枪法蛋白质组学数据在比较来自不同生物状态的蛋白质组方面提出了挑战。我们开发了一种分析策略，使用准似然广义线性模型（GLM），包括在一个图形界面软件包（QuasiTel），读取标准输出的蛋白质组装创建的IDPicker，基于HTML的用户界面查询鸟枪蛋白质组数据集。这种方法进行了比较，其他四个统计分析策略：学生t检验，Wilcoxon秩检验，Fisher精确检验，泊松为基础的GLM。我们分析了这些测试的性能，以基于鸟枪数据集中的光谱计数来识别蛋白质水平的差异，其中将等摩尔量的48种人类蛋白质以不同水平掺入到全酵母裂解物中。GLM方法和Fisher精确检验均表现良好，但各有其独特的局限性。随后，我们使用这种方法比较了正常扁桃体上皮和HNSCC的蛋白质组，并在正常扁桃体上皮和HNSCC之间鉴定了86种具有差异光谱计数的蛋白质。我们从该比较中选择了18种蛋白质，用于使用液相色谱-多反应监测质谱法（LC-MRM-MS）验证个体正常组织和肿瘤组织之间的蛋白质水平。该分析证实了所有6种蛋白质中蛋白质表达差异的幅度和方向，可以获得可靠的数据。我们的分析表明，来自不同组织表型的鸟枪蛋白质组数据集具有足够丰富的定量信息，蛋白质光谱计数的统计学显著差异反映了样品的潜在生物学特性。鸟枪蛋白质组学为复杂蛋白质组的全球库存提供了最强大的分析平台，但不完整的采样对光谱计数方法比较蛋白质库存提出了挑战。我们开发了一种基于准似然建模的统计方法，并证明它比其他统计检验。通过MRM证实了统计学显著性光谱计数差异，表明观察到的蛋白质水平差异反映了样品的潜在生物学。
Shotgun proteomics provides the most powerful analytical platform for global inventory of complex proteomes using liquid chromatography−tandem mass spectrometry (LC−MS/MS) and allows a global analysis of protein changes. Nevertheless, sampling of complex proteomes by current shotgun proteomics platforms is incomplete, and this contributes to variability in assessment of peptide and protein inventories by spectral counting approaches. Thus, shotgun proteomics data pose challenges in comparing proteomes from different biological states. We developed an analysis strategy using quasi-likelihood Generalized Linear Modeling (GLM), included in a graphical interface software package (QuasiTel) that reads standard output from protein assemblies created by IDPicker, an HTML-based user interface to query shotgun proteomic data sets. This approach was compared to four other statistical analysis strategies: Student t test, Wilcoxon rank test, Fisher’s Exact test, and Poisson-based GLM. We analyzed the performance of these tests to identify differences in protein levels based on spectral counts in a shotgun data set in which equimolar amounts of 48 human proteins were spiked at different levels into whole yeast lysates. Both GLM approaches and the Fisher Exact test performed adequately, each with their unique limitations. We subsequently compared the proteomes of normal tonsil epithelium and HNSCC using this approach and identified 86 proteins with differential spectral counts between normal tonsil epithelium and HNSCC. We selected 18 proteins from this comparison for verification of protein levels between the individual normal and tumor tissues using liquid chromatography−multiple reaction monitoring mass spectrometry (LC−MRM-MS). This analysis confirmed the magnitude and direction of the protein expression differences in all 6 proteins for which reliable data could be obtained. Our analysis demonstrates that shotgun proteomic data sets from different tissue phenotypes are sufficiently rich in quantitative information and that statistically significant differences in proteins spectral counts reflect the underlying biology of the samples. Shotgun proteomics provides the most powerful analytical platform for global inventory of complex proteomes but incomplete sampling poses challenges in comparing protein inventories by spectral counting approaches. We developed a statistical method based on quasi-likelihood modeling and demonstrate that it compares favorably to other statistical tests. Statistically significant spectral count differences were confirmed by MRM demonstrating that the observed protein level differences reflect the underlying biology of the samples.
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影响因子：
3.4
作者：
Melle, Christian;Ernst, Guenther;von Eggeling, Ferdinand
通讯作者：
von Eggeling, Ferdinand
影响因子：
4.4
作者：
Fu, Xiaoyun;Gharib, Sina A.;Heinecke, Jay W.
通讯作者：
Heinecke, Jay W.
影响因子：
5.8
作者：
Beissbarth, Tim;Hyde, Lavinia;Speed, Terence P.
通讯作者：
Speed, Terence P.
DOI：
10.1111/j.2517-6161.1995.tb02031.x
发表时间：
1995-01-01
影响因子：
5.8
作者：
BENJAMINI, Y;HOCHBERG, Y
通讯作者：
HOCHBERG, Y
影响因子：
7.4
作者：
Licklider, LJ;Thoreen, CC;Gygi, SP
通讯作者：
Gygi, SP