Literature DB >> 20828166

Visual indicator for surfactant abundance in MS-based membrane and general proteomics applications.

Chao-Jung Chen1, Mei-Chun Tseng, Han-Jia Lin, Ting-Wei Lin, Yet-Ran Chen.   

Abstract

The existence of surfactants in proteomics samples can severely reduce enzymatic digestion efficiency, liquid chromatography (LC) separation efficiency, column lifetime, and mass spectrometry (MS) sensitivity. Although various techniques are able to remove surfactants, surfactants may occasionally be retained in samples due to variations in sample preparation method or personal skill. Evaluation of surfactant residue in a sample, however, usually requires an additional instrument and is time-consuming. In this study, a simple and rapid visual indicator for surfactant abundance (VISA) was developed. With the detection of a visible surfactant pellet in the solution, this assay was able to detect surfactant residue in aqueous solutions within 5 min. Without the need of additional equipment such as a mass spectrometer, every user can perform a quick test on their bench before sending the sample to the MS facility. The detection limit for the commonly used surfactants, Triton X-114 and SDS, was about 0.0005% and 0.0002%, respectively. The VISA was successfully applied to evaluate the efficiency of removal of surfactants in Triton X-114 extracted membrane proteins using tube-gel. With the combination of Triton X-114 extraction and tube-gel protocol, a study of spermatozoa membrane proteome identified about 252 proteins of which about 67.5% were classified as membrane proteins. The coexistence of protein and surfactant did not affect the VISA sensitivity, suggesting that this indicator is suitable for proteomics applications. The VISA also has potential for the detection of other surfactants and can be applied to other surfactant removing protocols.

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Year:  2010        PMID: 20828166     DOI: 10.1021/ac1017937

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  5 in total

1.  Identification and characterization of an extracellular alkaline phosphatase in the marine diatom Phaeodactylum tricornutum.

Authors:  Hung-Yun Lin; Chi-Yu Shih; Hung-Chun Liu; Jeng Chang; Ying-Lan Chen; Yet-Ran Chen; Han-Tso Lin; Yu-Yung Chang; Chun-Hua Hsu; Han-Jia Lin
Journal:  Mar Biotechnol (NY)       Date:  2013-01-29       Impact factor: 3.619

2.  Integration of Different "-omics" Technologies Identifies Inhibition of the IGF1R-Akt-mTOR Signaling Cascade Involved in the Cytotoxic Effect of Shikonin against Leukemia Cells.

Authors:  Benjamin Wiench; Yet-Ran Chen; Malte Paulsen; Rebecca Hamm; Sven Schröder; Ning-Sun Yang; Thomas Efferth
Journal:  Evid Based Complement Alternat Med       Date:  2013-06-19       Impact factor: 2.629

3.  Streamlined Membrane Proteome Preparation for Shotgun Proteomics Analysis with Triton X-100 Cloud Point Extraction and Nanodiamond Solid Phase Extraction.

Authors:  Minh D Pham; Ting-Chun Wen; Hung-Cheng Li; Pei-Hsuan Hsieh; Yet-Ran Chen; Huan-Cheng Chang; Chau-Chung Han
Journal:  Materials (Basel)       Date:  2016-05-18       Impact factor: 3.623

4.  MSRB7 reverses oxidation of GSTF2/3 to confer tolerance of Arabidopsis thaliana to oxidative stress.

Authors:  Shu-Hong Lee; Chia-Wen Li; Kah Wee Koh; Hsin-Yu Chuang; Yet-Ran Chen; Choun-Sea Lin; Ming-Tsair Chan
Journal:  J Exp Bot       Date:  2014-06-24       Impact factor: 6.992

5.  Multiplex Brain Proteomic Analysis Revealed the Molecular Therapeutic Effects of Buyang Huanwu Decoction on Cerebral Ischemic Stroke Mice.

Authors:  Hong-Jhang Chen; Yuh-Chiang Shen; Young-Ji Shiao; Kuo-Tong Liou; Wei-Hsiang Hsu; Pei-Hsuan Hsieh; Chi-Ying Lee; Yet-Ran Chen; Yun-Lian Lin
Journal:  PLoS One       Date:  2015-10-22       Impact factor: 3.240

  5 in total

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