Abstract
Binary protein interactions form the basic building blocks of molecular networks and dynamic assemblies that control all cellular functions of bacteria. Although these protein interactions are a potential source of targets for the development of new antibiotics, few high-confidence data sets are available for the large proteomes of most pathogenic bacteria. We used a library of recombinant proteins from the plague bacterium Yersinia pestis to probe planar microarrays of immobilized proteins that represented ∼85% (3552 proteins) of the bacterial proteome, resulting in >77,000 experimentally determined binary interactions. Moderate (KD ∼μM) to high-affinity (KD ∼nM) interactions were characterized for >1600 binary complexes by surface plasmon resonance imaging of microarrayed proteins. Core binary interactions that were in common with other gram-negative bacteria were identified from the results of both microarray methods. Clustering of proteins within the interaction network by function revealed statistically enriched complexes and pathways involved in replication, biosynthesis, virulence, metabolism, and other diverse biological processes. The interaction pathways included many proteins with no previously known function. Further, a large assembly of proteins linked to transcription and translation were contained within highly interconnected subregions of the network. The two-tiered microarray approach used here is an innovative method for detecting binary interactions, and the resulting data will serve as a critical resource for the analysis of protein interaction networks that function within an important human pathogen.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 3220-3232 |
| Number of pages | 13 |
| Journal | Molecular and Cellular Proteomics |
| Volume | 15 |
| Issue number | 10 |
| DOIs | |
| State | Published - Oct 1 2016 |
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ASJC Scopus subject areas
- Analytical Chemistry
- Biochemistry
- Molecular Biology
Cite this
Cell-free determination of binary complexes that comprise extended protein-protein interaction networks of Yersinia pestis. / Keasey, Sarah L.; Natesan, Mohan; Pugh, Christine; Kamata, Teddy; Wuchty, Stefan; Ulrich, Robert G.
In: Molecular and Cellular Proteomics, Vol. 15, No. 10, 01.10.2016, p. 3220-3232.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Cell-free determination of binary complexes that comprise extended protein-protein interaction networks of Yersinia pestis
AU - Keasey, Sarah L.
AU - Natesan, Mohan
AU - Pugh, Christine
AU - Kamata, Teddy
AU - Wuchty, Stefan
AU - Ulrich, Robert G.
PY - 2016/10/1
Y1 - 2016/10/1
N2 - Binary protein interactions form the basic building blocks of molecular networks and dynamic assemblies that control all cellular functions of bacteria. Although these protein interactions are a potential source of targets for the development of new antibiotics, few high-confidence data sets are available for the large proteomes of most pathogenic bacteria. We used a library of recombinant proteins from the plague bacterium Yersinia pestis to probe planar microarrays of immobilized proteins that represented ∼85% (3552 proteins) of the bacterial proteome, resulting in >77,000 experimentally determined binary interactions. Moderate (KD ∼μM) to high-affinity (KD ∼nM) interactions were characterized for >1600 binary complexes by surface plasmon resonance imaging of microarrayed proteins. Core binary interactions that were in common with other gram-negative bacteria were identified from the results of both microarray methods. Clustering of proteins within the interaction network by function revealed statistically enriched complexes and pathways involved in replication, biosynthesis, virulence, metabolism, and other diverse biological processes. The interaction pathways included many proteins with no previously known function. Further, a large assembly of proteins linked to transcription and translation were contained within highly interconnected subregions of the network. The two-tiered microarray approach used here is an innovative method for detecting binary interactions, and the resulting data will serve as a critical resource for the analysis of protein interaction networks that function within an important human pathogen.
AB - Binary protein interactions form the basic building blocks of molecular networks and dynamic assemblies that control all cellular functions of bacteria. Although these protein interactions are a potential source of targets for the development of new antibiotics, few high-confidence data sets are available for the large proteomes of most pathogenic bacteria. We used a library of recombinant proteins from the plague bacterium Yersinia pestis to probe planar microarrays of immobilized proteins that represented ∼85% (3552 proteins) of the bacterial proteome, resulting in >77,000 experimentally determined binary interactions. Moderate (KD ∼μM) to high-affinity (KD ∼nM) interactions were characterized for >1600 binary complexes by surface plasmon resonance imaging of microarrayed proteins. Core binary interactions that were in common with other gram-negative bacteria were identified from the results of both microarray methods. Clustering of proteins within the interaction network by function revealed statistically enriched complexes and pathways involved in replication, biosynthesis, virulence, metabolism, and other diverse biological processes. The interaction pathways included many proteins with no previously known function. Further, a large assembly of proteins linked to transcription and translation were contained within highly interconnected subregions of the network. The two-tiered microarray approach used here is an innovative method for detecting binary interactions, and the resulting data will serve as a critical resource for the analysis of protein interaction networks that function within an important human pathogen.
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U2 - 10.1074/mcp.M116.059337
DO - 10.1074/mcp.M116.059337
M3 - Article
C2 - 27489291
AN - SCOPUS:84992088918
VL - 15
SP - 3220
EP - 3232
JO - Molecular and Cellular Proteomics
JF - Molecular and Cellular Proteomics
SN - 1535-9476
IS - 10
ER -