Comprehensive expression profiling and trace-level identification of unlabeled peptides ions in 2DLC-MS proteomics experiments using integrated detection and clustering software.

摘要

Subtle protein expression changes are often the hallmark of important cellular events and remain intrinsically difficult to detect in bottom up proteomics experiments due to the overwhelming sample complexity and variability associated with cell extracts. Efficient detection programs and data mining tools are required to obtain a comprehensive survey of the diverse peptide ion population generated from large-scale LC-MS experiments [1-3]. In order to profile low abundance expression changes across cell extracts, we have developed MassSense, a software that provide global peptide detection and segmentation analyses from data files of different MS platforms. The performance of this software was assessed with protein digest mixtures spiked at different levels in a complex extract of J774 macrophage cells. We also evaluated the ability of MassSense to profile protein expression changes in U937 cell line upon exposure to PMA across salt fractions in replicate 2D-LC-MS analyses.