A Multiplexed Quantitative Strategy for Membrane Proteomics: Opportunities for Mining Therapeutic Targets for Autosomal Dominant Polycystic Kidney Disease

Abstract

Toward multiplexed, comprehensive, and robust quantitation of the membrane proteome, we report a strategy combining gel-assisted digestion, iTRAQ (isobaric tags for relative and absolute quantitation) labeling, and LC-MS/MS. Quantitation of four independently purified membrane fractions from HeLa cells gave high accuracy (<8% error) and precision (<12% relative S.D.), demonstrating a high degree of consistency and reproducibility of this quantitation platform. Under stringent identification criteria (false discovery rate = 0%), the strategy efficiently quantified membrane proteins; as many as 520 proteins (91%) were membrane proteins, each quantified based on an average of 14.1 peptides per integral membrane protein. In addition to significant improvements in signal intensity for most quantified proteins, most remarkably, topological analysis revealed that the biggest improvement was achieved in detection of transmembrane peptides from integral membrane proteins with up to 19 transmembrane helices. To the best of our knowledge, this level of coverage exceeds that achieved previously using MS and provides superior quantitation accuracy compared with other methods. We applied this approach to the first proteomics delineation of phenotypic expression in a mouse model of autosomal dominant polycystic kidney disease (ADPKD). By characterizing kidney cell plasma membrane from wild-type versus PKD1 knock-out mice, 791 proteins were quantified, and 67 and 37 proteins showed > or =2-fold up-regulation and down-regulation, respectively. Some of these differentially expressed membrane proteins are involved in the mechanisms underlying major abnormalities in ADPKD, including epithelial cell proliferation and apoptosis, cell-cell and cell-matrix interactions, ion and fluid secretion, and membrane protein polarity. Among these proteins, targeting therapeutics to certain transporters/receptors, such as epidermal growth factor receptor, has proven effective in preclinical studies of ADPKD; others are known drug targets in various diseases. Our method demonstrates how comparative membrane proteomics can provide insight into the molecular mechanisms underlying ADPKD and the identification of potential drug targets, which may lead to new therapeutic opportunities to prevent or retard the disease.