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  • Title: Assessing biological variation and protein processing in primary human leukocytes by automated multiplex stable isotope labeling coupled to 2 dimensional peptide separation.
    Author: Raijmakers R, Heck AJ, Mohammed S.
    Journal: Mol Biosyst; 2009 Sep; 5(9):992-1003. PubMed ID: 19668865.
    Abstract:
    Determining the relative abundances of proteins in biological systems is an important aspect of proteomics. Quantitation provides the possibility to unravel the often subtle molecular differences that regulate biological processes in cells and organisms. A common method to analyze differences in protein expression in complex samples is differential stable isotopic labeling combined with 2D-LC-MS separation. In such experiments, proteins or peptides from different samples are labeled with different stable isotopes and their relative amounts are determined from the peptide ion intensities using mass spectrometry. When human tissue samples are investigated, chemical stable isotope labeling strategies instead of metabolic labeling strategies are required. However, biological variation in protein expression between individuals is a key concern.Here we describe a method that allows for fully automated quantitative proteome analysis; involving desalting, triplex stable isotopic dimethyl labeling and multi-dimensional strong cation exchange/reversed phase separation of peptides prior to mass spectrometric analysis that can be applied to complex samples such as human tissue lysates. We highlight the usability of the method by characterizing the extent of biological variation between the proteomes of primary human leukocytes from three healthy donors. Using our method we were able to quantify 967 proteins with a minimum of 2 peptides, revealing very limited biological variation between the donors. The discovery is noteworthy considering the presence of significant endogenous protease activity, originating primarily from the enzyme neutrophil elastase. This dataset represents the largest quantitative dataset for human leukocytes proteins, which was made possible by the use of an automated labeling strategy.
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