Time series proteome profiling to study endoplasmic reticulum stress response
Time series proteome profiling to study endoplasmic reticulum stress response
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DOI：
10.1021/pr700842m
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发表时间：
2008-06-01
影响因子：
4.4
通讯作者：
Hathout, Yetrib
中科院分区：
文献类型：
--
作者：
Mintz, Michelle;Vanderver, Adeline;Hathout, Yetrib
时间序列分析是获得蛋白质表达动态和主要生化途径信息的有力方法。到目前为止，这些信息只能在mRNA水平上使用成熟和高度平行的技术，如微阵列基因表达谱。由于缺乏稳健和高度可重复的方法，蛋白质水平的时间序列数据的生成已经滞后。使用SILAC策略，SDS-PAGE和LC-MS/MS的组合，我们证明了当暴露于ER应激诱导剂衣霉素和毒胡萝卜素时，在人原代成纤维细胞的ER隔室内的不同时间点成功监测相同蛋白质组的表达水平。使用GeneSpring GX分析平台促进数据可视化，所述分析平台被设计用于处理Affytron微阵列数据。该软件还促进了重要参数的生成，例如数据归一化、统计值的计算以提取蛋白质表达的显著变化以及数据集的交叉比较。
Time series profiling is a powerful approach for obtaining information on protein expression dynamics and prevailing biochemical pathways. To date, such information could only be obtained at the mRNA level using mature and highly parallel technologies such as microarray gene expression profiling. The generation of time series data at the protein level has lagged due to the lack of robust and highly reproducible methodologies. Using a combination of SILAC strategy, SDS-PAGE and LC-MS/MS, we demonstrate successful monitoring of expression levels of the same set of proteins across different time points within the ER compartment of human primary fibroblast cells when exposed to ER stress inducers tunicamycin and thapsigargin. Data visualization was facilitated using GeneSpring GX analysis platform that was designed to process Affymetrix microarray data. This software also facilitated the generation of important parameters such as data normalization, calculation of statistical values to extract significant changes in protein expression, and the cross comparison of data sets.