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An Ionic Liquid-Based Sample Preparation Method for Next-Stage Aggregate Proteomic Analysis

delete2019-10-16
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PRE
AI
M
Masato Taoka
K
Koji Horita
T
Takahiro Takekiyo
T
Takamasa Uekita
Y
Yukihiro Yoshimura
T
Tohru Ichimura *
DOI:10.1021/acs.analchem.9b02555delete
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摘要

摘要

En 中文
A wide variety of proteomic methods have been applied for protein profiling of insoluble aggregates or inclusion bodies deposited in various cells or tissues. However, these are essentially optimized or modified classical protein chemistry techniques using conventional denaturing agents such as formic acid, urea, and sodium dodecyl sulfate (SDS). The use of these denaturants has several shortcomings, including limited solubilization, contamination, and restrictions on absolute sample quantity and throughput. Here, we describe an alternative proteomic sample preparation platform for widespread aggregation analysis. This approach combines two techniques, (1) the use of ionic liquid for protein solubilization and (2) the recently published microbead-based and organic-media-assisted proteolysis strategy (BOPs), into a single-tube workflow. We demonstrate that the combined approach (iBOPs) enabled the successful solubilization of heat-aggregated hen egg whites within 10 min and supported sensitive mass spectrometry (MS) analysis. The performance of the iBOPs system surpassed those of conventional detergents and chaotropes. Moreover, this technology enabled ultrasensitive proteomic characterization of protein aggregates deposited in individual Caenorhabditis elegans nematodes. We identified ubiquitin and other molecules as candidate stochastic factors whose accumulation levels varied among aging nematode individuals. The sensitivity and applicability of the present iBOPs make it especially attractive for next-stage aggregate proteomic analysis of various biological processes.
Keyword:
EGG-WHITE LYSOZYME
DISSOLUTION
FIBRIL
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期刊

Analytical Chemistry 封面图
Analytical Chemistry
IF:
6.7
论文数:
4.7W
被引数:
15.9W

机构

N
national defense academy - japan
学者数:
595
论文数: 620
被引数: 0
T
Tokyo Metropolitan University
学者数:
4.1K
论文数: 3.8K
被引数: 5.9K
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