Quantitative Proteomics of the E. coli Membranome

被引:11
|
作者
Tsolis, K. C. [1 ]
Economou, A. [1 ]
机构
[1] Katholieke Univ Leuven, Rega Inst Med Res, Lab Mol Bacteriol, Leuven, Belgium
来源
关键词
LABEL-FREE; MASS-SPECTROMETRY; STATISTICAL-MODEL; PROTEIN; GENE; QUANTIFICATION; ABUNDANCE; DATABASE; INNER; IDENTIFICATION;
D O I
10.1016/bs.mie.2016.09.026
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Due to their physicochemical properties, membrane protein proteomics analyses often require extensive sample preparation protocols resulting in sample loss and introducing technical variation. Several methods for membrane proteomics have been described, designed to meet the needs of specific sample types and experimental designs. Here, we present a complete membrane proteomics pipeline starting from the membrane sample preparation to the protein identification/quantification and also discuss about annotation of proteomics data. The protocol has been developed using Escherichia coli samples but is directly adaptable to other bacteria including pathogens. We describe a method for the preparation of E. coli inner membrane vesicles (IMVs) central to our pipeline. IMVs are functional membrane vesicles that can also be used for biochemical studies. Next, we propose methods for membrane protein digestion and describe alternative experimental approaches that have been previously tested in our lab. We highlight a surface proteolysis protocol for the identification of inner membrane and membrane-bound proteins. This is a simple, fast, and reproducible method for the membrane sample characterization that has been previously used for the E. coli inner membrane proteome characterization (Papanastasiou et al., 2013) and the experimental validation of E. coli membrane proteome (Orfanoudaki & Economou, 2014). It provides a reduced load on MS-time and allows for multiple repeats. Then we discuss membrane protein quantification approaches and tools that can be used for the functional annotation of identified proteins. Overall, membrane proteome quantification can be fast, simplified, and reproducible; however, optimization steps should be performed for a given sample type.
引用
收藏
页码:15 / 36
页数:22
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