↓ Skip to main content

PLOS

Identification of Novel Protein-Protein Interactions of Yersinia pestis Type III Secretion System by Yeast Two Hybrid System

Overview of attention for article published in PLOS ONE, January 2013
Altmetric Badge

Mentioned by

facebook
1 Facebook page

Citations

dimensions_citation
16 Dimensions

Readers on

mendeley
45 Mendeley
Title
Identification of Novel Protein-Protein Interactions of Yersinia pestis Type III Secretion System by Yeast Two Hybrid System
Published in
PLOS ONE, January 2013
DOI 10.1371/journal.pone.0054121
Pubmed ID
Authors

Huiying Yang, Yafang Tan, Tingting Zhang, Liujun Tang, Jian Wang, Yuehua Ke, Zhaobiao Guo, Xiaoming Yang, Ruifu Yang, Zongmin Du

Abstract

Type III secretion system (T3SS) of the plague bacterium Y. pestis encodes a syringe-like structure consisting of more than 20 proteins, which can inject virulence effectors into host cells to modulate the cellular functions. Here in this report, interactions among the possible components in T3SS of Yersinia pestis were identified using yeast mating technique. A total of 57 genes, including all the pCD1-encoded genes except those involved in plasmid replication and partition, pseudogenes, and the putative transposase genes, were subjected to yeast mating analysis. 21 pairs of interaction proteins were identified, among which 9 pairs had been previously reported and 12 novel pairs were identified in this study. Six of them were tested by GST pull down assay, and interaction pairs of YscG-SycD, YscG-TyeA, YscI-YscF, and YopN-YpCD1.09c were successfully validated, suggesting that these interactions might play potential roles in function of Yersinia T3SS. Several potential new interactions among T3SS components could help to understand the assembly and regulation of Yersinia T3SS.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
Madagascar 1 2%
Unknown 43 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 27%
Researcher 8 18%
Student > Master 6 13%
Student > Doctoral Student 5 11%
Student > Bachelor 5 11%
Other 6 13%
Unknown 3 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 20 44%
Biochemistry, Genetics and Molecular Biology 12 27%
Immunology and Microbiology 2 4%
Unspecified 1 2%
Computer Science 1 2%
Other 4 9%
Unknown 5 11%