Source:http://linkedlifedata.com/resource/pubmed/id/20973567
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| Predicate | Object |
|---|---|
| rdf:type | |
| lifeskim:mentions | |
| pubmed:issue |
12
|
| pubmed:dateCreated |
2010-12-3
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| pubmed:abstractText |
Analysis of the protein-protein interaction network of a pathogen is a powerful approach for dissecting gene function, potential signal transduction, and virulence pathways. This study looks at the construction of a global protein-protein interaction (PPI) network for the human pathogen Mycobacterium tuberculosis H37Rv, based on a high-throughput bacterial two-hybrid method. Almost the entire ORFeome was cloned, and more than 8000 novel interactions were identified. The overall quality of the PPI network was validated through two independent methods, and a high success rate of more than 60% was obtained. The parameters of PPI networks were calculated. The average shortest path length was 4.31. The topological coefficient of the M. tuberculosis B2H network perfectly followed a power law distribution (correlation = 0.999; R-squared = 0.999) and represented the best fit in all currently available PPI networks. A cross-species PPI network comparison revealed 94 conserved subnetworks between M. tuberculosis and several prokaryotic organism PPI networks. The global network was linked to the protein secretion pathway. Two WhiB-like regulators were found to be highly connected proteins in the global network. This is the first systematic noncomputational PPI data for the human pathogen, and it provides a useful resource for studies of infection mechanisms, new signaling pathways, and novel antituberculosis drug development.
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| pubmed:language |
eng
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| pubmed:journal | |
| pubmed:citationSubset |
IM
|
| pubmed:chemical | |
| pubmed:status |
MEDLINE
|
| pubmed:month |
Dec
|
| pubmed:issn |
1535-3907
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| pubmed:author |
pubmed-author:ChenHuanchunH,
pubmed-author:GaoChunhuiC,
pubmed-author:HeYangY,
pubmed-author:HeZheng-GuoZG,
pubmed-author:HuangChengC,
pubmed-author:HuangFengF,
pubmed-author:HuangYuanxiaY,
pubmed-author:LiWeihuiW,
pubmed-author:LiYuqingY,
pubmed-author:TianYuxiY,
pubmed-author:WangYiY,
pubmed-author:WosJ DJD,
pubmed-author:YangMinM,
pubmed-author:YangQiongQ,
pubmed-author:ZengJumeiJ,
pubmed-author:ZhangCongC,
pubmed-author:ZhangHuaH,
pubmed-author:ZhangLeiL,
pubmed-author:ZhaoChunchaoC
|
| pubmed:issnType |
Electronic
|
| pubmed:day |
3
|
| pubmed:volume |
9
|
| pubmed:owner |
NLM
|
| pubmed:authorsComplete |
Y
|
| pubmed:pagination |
6665-77
|
| pubmed:meshHeading |
pubmed-meshheading:20973567-Bacterial Proteins,
pubmed-meshheading:20973567-Humans,
pubmed-meshheading:20973567-Models, Biological,
pubmed-meshheading:20973567-Mycobacterium tuberculosis,
pubmed-meshheading:20973567-Protein Binding,
pubmed-meshheading:20973567-Protein Interaction Mapping,
pubmed-meshheading:20973567-Proteomics,
pubmed-meshheading:20973567-Signal Transduction,
pubmed-meshheading:20973567-Tuberculosis,
pubmed-meshheading:20973567-Two-Hybrid System Techniques
|
| pubmed:year |
2010
|
| pubmed:articleTitle |
Global protein-protein interaction network in the human pathogen Mycobacterium tuberculosis H37Rv.
|
| pubmed:affiliation |
National Key Laboratory of Agricultural Microbiology, Center for Proteomics Research, College of Life Science and Technology, Huazhong Agricultural University, Wuhan 430070, China.
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| pubmed:publicationType |
Journal Article,
Research Support, Non-U.S. Gov't
|