Literature DB >> 21478485

Statistical analysis of features associated with protein expression/solubility in an in vivo Escherichia coli expression system and a wheat germ cell-free expression system.

Shuichi Hirose1, Yoshifumi Kawamura, Kiyonobu Yokota, Toshihiro Kuroita, Tohru Natsume, Kazuo Komiya, Takeshi Tsutsumi, Yorimasa Suwa, Takao Isogai, Naoki Goshima, Tamotsu Noguchi.   

Abstract

Recombinant protein technology is an important tool in many industrial and pharmacological applications. Although the success rate of obtaining soluble proteins is relatively low, knowledge of protein expression/solubility under 'standard' conditions may increase the efficiency and reduce the cost of proteomics studies. In this study, we conducted a genome-scale experiment to assess the overexpression and the solubility of human full-length cDNA in an in vivo Escherichia coli expression system and a wheat germ cell-free expression system. We evaluated the influences of sequence and structural features on protein expression/solubility in each system and estimated a minimal set of features associated with them. A comparison of the feature sets related to protein expression/solubility in the in vivo Escherichia coli expression system revealed that the structural information was strongly associated with protein expression, rather than protein solubility. Moreover, a significant difference was found in the number of features associated with protein solubility in the two expression systems.

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Year:  2011        PMID: 21478485     DOI: 10.1093/jb/mvr042

Source DB:  PubMed          Journal:  J Biochem        ISSN: 0021-924X            Impact factor:   3.387


  3 in total

1.  Enhancing solubility of deoxyxylulose phosphate pathway enzymes for microbial isoprenoid production.

Authors:  Kang Zhou; Ruiyang Zou; Gregory Stephanopoulos; Heng-Phon Too
Journal:  Microb Cell Fact       Date:  2012-11-14       Impact factor: 5.328

2.  Electrostatic mis-interactions cause overexpression toxicity of proteins in E. coli.

Authors:  Gajinder Pal Singh; Debasis Dash
Journal:  PLoS One       Date:  2013-05-29       Impact factor: 3.240

3.  A review of machine learning methods to predict the solubility of overexpressed recombinant proteins in Escherichia coli.

Authors:  Narjeskhatoon Habibi; Siti Z Mohd Hashim; Alireza Norouzi; Mohammed Razip Samian
Journal:  BMC Bioinformatics       Date:  2014-05-08       Impact factor: 3.169

  3 in total

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