Time series proteome profiling to study endoplasmic reticulum stress response.

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.

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