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Elucidating Tissue- and Plasma-Specific Proteomic Alterations in Health and Disease

作者
Lily S. Neff,James C. DeMar,Nicholas C. Gary,Mital Y. Patel,Burook Misganaw,Aarti Gautam,Rasha Hammamieh
出处
期刊:Journal of Visualized Experiments [MyJOVE]
卷期号: (223)
标识
DOI:10.3791/67240
摘要

Proteomics is the large-scale study of expressed proteins, focusing on their structure, function, interactions, abundance, and post-translational modifications within a biological system. For example, phosphoproteomics, a vital subset of total proteomics, is the study of phosphorylation patterns and alterations on proteins. The methodology described herein illustrates a total proteomics approach to elucidate alterations in overall protein expression profiles, including phosphorylation patterns, in the plasma, brain, lung, spleen, and liver tissues collected from research animal models (i.e., ferrets and mice). This technique is applicable for other tissue types, as well as almost any bio-sample containing proteins (e.g., cultured cells). Following dissection, tissues of interest were flash frozen and stored at -80 °C. Tissues were then homogenized using a mortar and pestle with liquid nitrogen to preserve protein integrity and phosphorylation changes. Total protein was extracted from the tissue homogenates using a lysis buffer with a universal nuclease and protease/phosphatase inhibitors. Proteins extracted from tissue and equivalent plasma were converted to total peptides by controlled protease digestion using a commercial mass spectrometer sample preparation kit. Peptides were directly analyzed using ultra-high performance liquid chromatography/Orbitrap-tribrid tandem mass spectrometry. Identities of constituent proteins were reconstructed from the peptide mass spectral data, using proteomics bioinformatics software, as matched to a species-specific amino acid sequence library. Following this, the analysis should include strict cutoff criteria, especially using only high-confidence protein identifications. Statistically significant proteomic differences (>2-fold change; p < 0.05) can be determined between control and experimental groups.
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