Literature DB >> 27297043

A Proteomics Approach to the Protein Normalization Problem: Selection of Unvarying Proteins for MS-Based Proteomics and Western Blotting.

Jacek R Wiśniewski1, Matthias Mann1.   

Abstract

Proteomics and other protein-based analysis methods such as Western blotting all face the challenge of discriminating changes in the levels of proteins of interest from inadvertent changes in the amount loaded for analysis. Mass-spectrometry-based proteomics can now estimate the relative and absolute amounts of thousands of proteins across diverse biological systems. We reasoned that this new technology could prove useful for selection of very stably expressed proteins that could serve as better loading controls than those traditionally employed. Large-scale proteomic analyses of SDS lysates of cultured cells and tissues revealed deglycase DJ-1 as the protein with the lowest variability in abundance among different cell types in human, mouse, and amphibian cells. The protein constitutes 0.069 ± 0.017% of total cellular protein and occurs at a specific concentration of 34.6 ± 8.7 pmol/mg of total protein. Since DJ-1 is ubiquitous and therefore easily detectable with several peptides, it can be helpful in normalization of proteomic data sets. In addition, DJ-1 appears to be an advantageous loading control for Western blot that is superior to those used commonly used, allowing comparisons between tissues and cells originating from evolutionarily distant vertebrate species. Notably, this is not possible by the detection and quantitation of housekeeping proteins, which are often used in the Western blot technique. The approach introduced here can be applied to select the most appropriate loading controls for MS-based proteomics or Western blotting in any biological system.

Entities:  

Keywords:  DJ-1; PARK7; Western blot; Xenopus; loading control; proteomic data normalization; quantitative proteomics; “Total Protein Approach”

Mesh:

Substances:

Year:  2016        PMID: 27297043     DOI: 10.1021/acs.jproteome.6b00403

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  17 in total

1.  Activation of CD44/PAK1/AKT signaling promotes resistance to FGFR1 inhibition in squamous-cell lung cancer.

Authors:  Omar Elakad; Björn Häupl; Vera Labitzky; Sha Yao; Stefan Küffer; Alexander von Hammerstein-Equord; Bernhard C Danner; Manfred Jücker; Henning Urlaub; Tobias Lange; Philipp Ströbel; Thomas Oellerich; Hanibal Bohnenberger
Journal:  NPJ Precis Oncol       Date:  2022-07-19

2.  Sample Preparation by Easy Extraction and Digestion (SPEED) - A Universal, Rapid, and Detergent-free Protocol for Proteomics Based on Acid Extraction.

Authors:  Joerg Doellinger; Andy Schneider; Marcell Hoeller; Peter Lasch
Journal:  Mol Cell Proteomics       Date:  2019-11-21       Impact factor: 5.911

3.  A selected reaction monitoring mass spectrometric assessment of biomarker candidates diagnosing large-cell neuroendocrine lung carcinoma by the scaling method using endogenous references.

Authors:  Tetsuya Fukuda; Masaharu Nomura; Yasufumi Kato; Hiromasa Tojo; Kiyonaga Fujii; Toshitaka Nagao; Yasuhiko Bando; Thomas E Fehniger; György Marko-Varga; Haruhiko Nakamura; Harubumi Kato; Toshihide Nishimura
Journal:  PLoS One       Date:  2017-04-27       Impact factor: 3.240

4.  The ER membrane protein complex interacts cotranslationally to enable biogenesis of multipass membrane proteins.

Authors:  Matthew J Shurtleff; Daniel N Itzhak; Jeffrey A Hussmann; Nicole T Schirle Oakdale; Elizabeth A Costa; Martin Jonikas; Jimena Weibezahn; Katerina D Popova; Calvin H Jan; Pavel Sinitcyn; Shruthi S Vembar; Hilda Hernandez; Jürgen Cox; Alma L Burlingame; Jeffrey L Brodsky; Adam Frost; Georg Hh Borner; Jonathan S Weissman
Journal:  Elife       Date:  2018-05-29       Impact factor: 8.140

5.  Proteomic analysis in lupus mice identifies Coronin-1A as a potential biomarker for lupus nephritis.

Authors:  Orthodoxia Nicolaou; Kleitos Sokratous; Zuzanna Makowska; María Morell; Aurélie De Groof; Pauline Montigny; Andreas Hadjisavvas; Kyriaki Michailidou; Anastasis Oulas; George M Spyrou; Christiana Demetriou; Marta E Alarcón-Riquelme; Savvas Psarellis; Andreas Kousios; Bernard Lauwerys; Kyriacos Kyriacou
Journal:  Arthritis Res Ther       Date:  2020-06-18       Impact factor: 5.156

Review 6.  Bioinformatics Methods for Mass Spectrometry-Based Proteomics Data Analysis.

Authors:  Chen Chen; Jie Hou; John J Tanner; Jianlin Cheng
Journal:  Int J Mol Sci       Date:  2020-04-20       Impact factor: 5.923

7.  Global identification of phospho-dependent SCF substrates reveals a FBXO22 phosphodegron and an ERK-FBXO22-BAG3 axis in tumorigenesis.

Authors:  Ping Liu; Xiaoji Cong; Shengjie Liao; Xinglong Jia; Xiaomin Wang; Wei Dai; Linhui Zhai; Lei Zhao; Jing Ji; Duan Ni; Zhiwei Liu; Yulu Chen; Lulu Pan; Wei Liu; Jian Zhang; Min Huang; Bin Liu; Minjia Tan
Journal:  Cell Death Differ       Date:  2021-07-02       Impact factor: 15.828

Review 8.  Bioinformatic Analysis of Temporal and Spatial Proteome Alternations During Infections.

Authors:  Matineh Rahmatbakhsh; Alla Gagarinova; Mohan Babu
Journal:  Front Genet       Date:  2021-07-02       Impact factor: 4.599

9.  Distinct brain regional proteome changes in the rTg-DI rat model of cerebral amyloid angiopathy.

Authors:  Joseph M Schrader; Feng Xu; William E Van Nostrand
Journal:  J Neurochem       Date:  2021-08-17       Impact factor: 5.546

10.  One carbon metabolism in human lung cancer.

Authors:  Sha Yao; Luogen Peng; Omar Elakad; Stefan Küffer; Marc Hinterthaner; Bernhard C Danner; Alexander von Hammerstein-Equord; Philipp Ströbel; Hanibal Bohnenberger
Journal:  Transl Lung Cancer Res       Date:  2021-06
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.