Utilization of dried and long-term stored polyacrylamide gels for the advanced proteomic profiling of mitochondrial contact sites from rat liver

利用干燥和长期储存的聚丙烯酰胺凝胶对大鼠肝脏线粒体接触位点进行高级蛋白质组学分析

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作者:Sandra Murphy, Michael Henry, Paula Meleady, Kay Ohlendieck

Abstract

Following subcellular fractionation, the complexity of proteins derived from a particular cellular compartment is often evaluated by gel electrophoretic analysis. For the proteomic cataloguing of these distinct protein populations and their biochemical characterization, gel electrophoretic protein separation can be conveniently combined with liquid chromatography mass spectrometry. Here we describe a gel-enhanced liquid chromatography mass spectrometry (GeLC-MS)/MS approach with a new bioanalytical focus on the proteomic profiling of mitochondrial contact sites from rat liver using the highly sensitive Orbitrap Fusion Tribrid mass spectrometer for optimum protein identification following extraction from dried and long-term stored gels. Mass spectrometric analysis identified 964 protein species in the mitochondrial contact site fraction, whereby 459 proteins were identified by ≥3 unique peptides. This included mitochondrial components of the supramolecular complexes that form the ATP synthase, the respiratory chain, ribosomal subunits and the cytochrome P450 system, as well as crucial components of the translocase complexes translocase of the inner membrane (TIM) and translocase of the outer membrane (TOM) of the two mitochondrial membranes. Proteomics also identified contact site markers, such as glutathione transferase, monoamine oxidase and the pore protein voltage dependent anion channel (VDAC)-1. Hence, this report demonstrates that the GeLC-MS/MS method can be used to study complex mixtures of proteins that have been embedded and stored in dried polyacrylamide gels for a long period of time. Careful re-swelling and standard in-gel digestion is suitable to produce peptide profiles from old gels that can be used to extract sophisticated proteomic maps and enable the subsequent bioinformatics analysis of the distribution of protein function and the determination of potential protein clustering within the contact site system.

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