Differential analysis of membrane proteins in mouse fore- and hindbrain using a label-free approach

Le Bihan, Thierry, Goh, Theo, Stewart, Ian I., Salter, Anne Marie, Bukhman, Yury V., Dharsee, Moyez, Ewing, Rob and Wiśniewski, Jacek R. (2006) Differential analysis of membrane proteins in mouse fore- and hindbrain using a label-free approach. Journal of Proteome Research, 5 (10), 2701-2710. (doi:10.1021/pr060190y). (PMID:17022641)

Abstract

The ability to quantitatively compare protein levels across different regions of the brain to identify disease mechanisms remains a fundamental research challenge. It requires both a robust method to efficiently isolate proteins from small amounts of tissue and a differential technique that provides a sensitive and comprehensive analysis of these proteins. Here, we describe a proteomic approach for the quantitative mapping of membrane proteins between mouse fore- and hindbrain regions. The approach focuses primarily on a recently developed method for the fractionation of membranes and on-membrane protein digestion, but incorporates off-line SCX-fractionation of the peptide mixture and nano-LC-MS/MS analysis using an LTQ-FT-ICR instrument as part of the analytical method. Comparison of mass spectral peak intensities between samples, mapping of peaks to peptides and protein sequences, and statistical analysis were performed using in-house differential analysis software (DAS). In total, 1213 proteins were identified and 967 were quantified; 81% of the identified proteins were known membrane proteins and 38% of the protein sequences were predicted to contain transmembrane helices. Although this paper focuses primarily on characterizing the efficiency of this purification method from a typical sample set, for many of the quantified proteins such as glutamate receptors, GABA receptors, calcium channel subunits, and ATPases, the observed ratios of protein abundance were in good agreement with the known mRNA expression levels and/or intensities of immunostaining in rostral and caudal regions of murine brain. This suggests that the approach would be well-suited for incorporation in more rigorous, larger scale quantitative analysis designed to achieve biological significance.

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Contributors

Author: Rob Ewing

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