Mapping the protein interaction network in methicillin-resistant Staphylococcus aureus.

Mortality attributable to infection with methicillin-resistant Staphylococcus aureus (MRSA) has now overtaken the death rate for AIDS in the United States, and advances in research are urgently needed to address this challenge. We report the results of the systematic identification of protein-protein interactions for the hospital-acquired strain MRSA-252. Using a high-throughput pull-down strategy combined with quantitative proteomics to distinguish specific from nonspecific interactors, we identified 13,219 interactions involving 608 MRSA proteins. Consecutive analyses revealed that this protein interaction network (PIN) exhibits scale-free organization with the characteristic presence of highly connected hub proteins. When clinical and experimental antimicrobial targets were queried in the network, they were generally found to occupy peripheral positions in the PIN with relatively few interacting partners. In contrast, the hub proteins identified in this MRSA PIN that are essential for network integrity and stability have largely been overlooked as drug targets. Thus, this empirical MRSA-252 PIN provides a rich source for identifying critical proteins essential for network stability, many of which can be considered as prospective antimicrobial drug targets.

[1]  P. Uetz,et al.  The Binary Protein Interactome of Treponema pallidum – The Syphilis Spirochete , 2008, PloS one.

[2]  David S. Wishart,et al.  DrugBank: a knowledgebase for drugs, drug actions and drug targets , 2007, Nucleic Acids Res..

[3]  Aleksey A. Porollo,et al.  Combining prediction of secondary structure and solvent accessibility in proteins , 2005, Proteins.

[4]  Artem Cherkasov,et al.  Predicting highly-connected hubs in protein interaction networks by QSAR and biological data descriptors , 2009, Bioinformation.

[5]  J. Barker Antibacterial drug discovery and structure-based design. , 2006, Drug discovery today.

[6]  M. Mann,et al.  MSQuant, an open source platform for mass spectrometry-based quantitative proteomics. , 2010, Journal of proteome research.

[7]  A. Barabasi,et al.  Lethality and centrality in protein networks , 2001, Nature.

[8]  E. Koonin,et al.  The structure of the protein universe and genome evolution , 2002, Nature.

[9]  A. E. Hirsh,et al.  Evolutionary Rate in the Protein Interaction Network , 2002, Science.

[10]  P. Legrain,et al.  A genomic approach of the hepatitis C virus generates a protein interaction map. , 2000, Gene.

[11]  Leonard J Foster,et al.  Changes in protein expression during honey bee larval development , 2008, Genome Biology.

[12]  Mark Gerstein,et al.  The Importance of Bottlenecks in Protein Networks: Correlation with Gene Essentiality and Expression Dynamics , 2007, PLoS Comput. Biol..

[13]  Julie A. Hines,et al.  A proteome-wide protein interaction map for Campylobacter jejuni , 2007, Genome Biology.

[14]  Joel S. Bader,et al.  Where Have All the Interactions Gone? Estimating the Coverage of Two-Hybrid Protein Interaction Maps , 2007, PLoS Comput. Biol..

[15]  Tatiana Tatusova,et al.  NCBI Reference Sequence (RefSeq): a curated non-redundant sequence database of genomes, transcripts and proteins , 2004, Nucleic Acids Res..

[16]  Bernardo A Mangiola,et al.  A Drosophila protein-interaction map centered on cell-cycle regulators , 2004, Genome Biology.

[17]  Artem Cherkasov,et al.  The use of Gene Ontology terms for predicting highly-connected 'hub' nodes in protein-protein interaction networks , 2008, BMC Systems Biology.

[18]  J. García-Lara,et al.  Staphylococcus aureus: the search for novel targets. , 2005, Drug discovery today.

[19]  S. L. Wong,et al.  Towards a proteome-scale map of the human protein–protein interaction network , 2005, Nature.

[20]  M. Gerstein,et al.  The dominance of the population by a selected few: power-law behaviour applies to a wide variety of genomic properties , 2002, Genome Biology.

[21]  P. Bork,et al.  Proteome survey reveals modularity of the yeast cell machinery , 2006, Nature.

[22]  A. Lambowitz,et al.  Use of targetrons to disrupt essential and nonessential genes in Staphylococcus aureus reveals temperature sensitivity of Ll.LtrB group II intron splicing. , 2006, RNA.

[23]  D. Payne,et al.  Finding the gems using genomic discovery: antibacterial drug discovery strategies – the successes and the challenges , 2004 .

[24]  Martin Vingron,et al.  IntAct: an open source molecular interaction database , 2004, Nucleic Acids Res..

[25]  Artem Cherkasov,et al.  The Use of Sequence‐Derived QSPR Descriptors for Predicting Highly Connected Proteins (Hubs) in Protein–Protein Interactions , 2009 .

[26]  Douglas B. Kell,et al.  Comparative Genomic Assessment of Novel Broad-Spectrum Targets for Antibacterial Drugs , 2004, Comparative and functional genomics.

[27]  Dianne P. O'Leary,et al.  Why Do Hubs in the Yeast Protein Interaction Network Tend To Be Essential: Reexamining the Connection between the Network Topology and Essentiality , 2008, PLoS Comput. Biol..

[28]  A. Wilkinson,et al.  Structure and non-essential function of glycerol kinase in Plasmodium falciparum blood stages , 2009, Molecular microbiology.

[29]  B. Snel,et al.  Comparative assessment of large-scale data sets of protein–protein interactions , 2002, Nature.

[30]  S. L. Wong,et al.  A Map of the Interactome Network of the Metazoan C. elegans , 2004, Science.

[31]  L. Foster,et al.  Sequestosome-1/p62 Is the Key Intracellular Target of Innate Defense Regulator Peptide* , 2009, The Journal of Biological Chemistry.

[32]  James R. Knight,et al.  A Protein Interaction Map of Drosophila melanogaster , 2003, Science.

[33]  L. Foster,et al.  Proteomics of Photoreceptor Outer Segments Identifies a Subset of SNARE and Rab Proteins Implicated in Membrane Vesicle Trafficking and Fusion *S , 2008, Molecular & Cellular Proteomics.

[34]  S. Eriksson,et al.  Structural and functional investigations of Ureaplasma parvum UMP kinase – a potential antibacterial drug target , 2007, The FEBS journal.

[35]  L. Foster,et al.  Identification of cognate host targets and specific ubiquitylation sites on the Salmonella SPI-1 effector SopB/SigD. , 2008, Journal of proteomics.

[36]  Andrey Rzhetsky,et al.  Birth of scale-free molecular networks and the number of distinct DNA and protein domains per genome , 2001, Bioinform..

[37]  A. Barabasi,et al.  Network biology: understanding the cell's functional organization , 2004, Nature Reviews Genetics.

[38]  M. Mann,et al.  Unbiased quantitative proteomics of lipid rafts reveals high specificity for signaling factors , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[39]  M. Mulvey,et al.  The evolution of methicillin-resistant Staphylococcus aureus in Canadian hospitals: 5 years of national surveillance. , 2001, CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne.

[40]  Yan Lin,et al.  DEG 5.0, a database of essential genes in both prokaryotes and eukaryotes , 2008, Nucleic Acids Res..

[41]  Albert J R Heck,et al.  Triplex protein quantification based on stable isotope labeling by peptide dimethylation applied to cell and tissue lysates , 2008, Proteomics.

[42]  B. Schönfisch,et al.  Ring vaccination , 2000, Journal of mathematical biology.

[43]  J. Reifman,et al.  Influence of Protein Abundance on High-Throughput Protein-Protein Interaction Detection , 2009, PloS one.

[44]  S. Kanaya,et al.  Large-scale identification of protein-protein interaction of Escherichia coli K-12. , 2006, Genome research.

[45]  H. Lehrach,et al.  A Human Protein-Protein Interaction Network: A Resource for Annotating the Proteome , 2005, Cell.

[46]  Ian Collins,et al.  An Inhibitor of FtsZ with Potent and Selective Anti-Staphylococcal Activity , 2008, Science.

[47]  S. Fields,et al.  Genome-wide analysis of vaccinia virus protein-protein interactions. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[48]  A. Emili,et al.  Interaction network containing conserved and essential protein complexes in Escherichia coli , 2005, Nature.

[49]  P. Shannon,et al.  Cytoscape: a software environment for integrated models of biomolecular interaction networks. , 2003, Genome research.

[50]  M. Kretzschmar,et al.  Modeling prevention strategies for gonorrhea and Chlamydia using stochastic network simulations. , 1996, American journal of epidemiology.

[51]  Huanye Sheng,et al.  Understanding gene essentiality by finely characterizing hubs in the yeast protein interaction network. , 2010, Biochemical and biophysical research communications.

[52]  Keunwan Park,et al.  Localized network centrality and essentiality in the yeast–protein interaction network , 2009, Proteomics.

[53]  M. Gerstein,et al.  Protein family and fold occurrence in genomes: power-law behaviour and evolutionary model. , 2001, Journal of molecular biology.

[54]  D. Pompliano,et al.  Drugs for bad bugs: confronting the challenges of antibacterial discovery , 2007, Nature Reviews Drug Discovery.

[55]  L. Foster,et al.  Mapping the integrin-linked kinase interactome using SILAC. , 2008, Journal of proteome research.

[56]  D. Rice,et al.  Antibiotic Activity and Characterization of BB-3497, a Novel Peptide Deformylase Inhibitor , 2001, Antimicrobial Agents and Chemotherapy.

[57]  J. Wojcik,et al.  The protein–protein interaction map of Helicobacter pylori , 2001, Nature.

[58]  C. DeLisi,et al.  Predictions of gene family distributions in microbial genomes: evolution by gene duplication and modification. , 2000, Physical review letters.