MPact: the MIPS protein interaction resource on yeast

In recent years, the Munich Information Center for Protein Sequences (MIPS) yeast protein–protein interaction (PPI) dataset has been used in numerous analyses of protein networks and has been called a gold standard because of its quality and comprehensiveness [H. Yu, N. M. Luscombe, H. X. Lu, X. Zhu, Y. Xia, J. D. Han, N. Bertin, S. Chung, M. Vidal and M. Gerstein (2004) Genome Res., 14, 1107–1118]. MPact and the yeast protein localization catalog provide information related to the proximity of proteins in yeast. Beside the integration of high-throughput data, information about experimental evidence for PPIs in the literature was compiled by experts adding up to 4300 distinct PPIs connecting 1500 proteins in yeast. As the interaction data is a complementary part of CYGD, interactive mapping of data on other integrated data types such as the functional classification catalog [A. Ruepp, A. Zollner, D. Maier, K. Albermann, J. Hani, M. Mokrejs, I. Tetko, U. Güldener, G. Mannhaupt, M. Münsterkötter and H. W. Mewes (2004) Nucleic Acids Res., 32, 5539–5545] is possible. A survey of signaling proteins and comparison with pathway data from KEGG demonstrates that based on these manually annotated data only an extensive overview of the complexity of this functional network can be obtained in yeast. The implementation of a web-based PPI-analysis tool allows analysis and visualization of protein interaction networks and facilitates integration of our curated data with high-throughput datasets. The complete dataset as well as user-defined sub-networks can be retrieved easily in the standardized PSI-MI format. The resource can be accessed through

FGDB: a comprehensive fungal genome resource on the plant pathogen Fusarium graminearum

The MIPS Fusarium graminearum Genome Database (FGDB) is a comprehensive genome database on one of the most devastating fungal plant pathogens of wheat and barley. FGDB provides information on two gene sets independently derived by automated annotation of the F.graminearum genome sequence. A complete manually revised gene set will be completed within the near future. The initial results of systematic manual correction of gene calls are already part of the current gene set. The database can be accessed to retrieve information from bioinformatics analyses and functional classifications of the proteins. The data are also organized in the well established MIPS catalogs and novel query techniques are available to search the data. The comprehensive set of gene calls was also used for the design of an Affymetrix GeneChip. The resource is accessible on

An evolutionary and structural characterization of mammalian protein complex organization

Background: We have recently released a comprehensive, manually curated database of mammalian protein complexes called CORUM. Combining CORUM with other resources, we assembled a dataset of over 2700 mammalian complexes. The availability of a rich information resource allows us to search for organizational properties concerning these complexes. Results: As the complexity of a protein complex in terms of the number of unique subunits increases, we observed that the number of such complexes and the mean non-synonymous to synonymous substitution ratio of associated genes tend to decrease. Similarly, as the number of different complexes a given protein participates in increases, the number of such proteins and the substitution ratio of the associated gene also tend to decrease. These observations provide evidence relating natural selection and the organization of mammalian complexes. We also observed greater homogeneity in terms of predicted protein isoelectric points, secondary structure and substitution ratio in annotated versus randomly generated complexes. A large proportion of the protein content and interactions in the complexes could be predicted from known binary protein-protein and domain-domain interactions. In particular, we found that large proteins interact preferentially with much smaller proteins. Conclusions: We observed similar trends in yeast and other data. Our results support the existence of conserved relations associated with the mammalian protein complexes

The Mouse Functional Genome Database (MfunGD): functional annotation of proteins in the light of their cellular context

MfunGD () provides a resource for annotated mouse proteins and their occurrence in protein networks. Manual annotation concentrates on proteins which are found to interact physically with other proteins. Accordingly, manually curated information from a protein–protein interaction database (MPPI) and a database of mammalian protein complexes is interconnected with MfunGD. Protein function annotation is performed using the Functional Catalogue (FunCat) annotation scheme which is widely used for the analysis of protein networks. The dataset is also supplemented with information about the literature that was used in the annotation process as well as links to the SIMAP Fasta database, the Pedant protein analysis system and cross-references to external resources. Proteins that so far were not manually inspected are annotated automatically by a graphical probabilistic model and/or superparamagnetic clustering. The database is continuously expanding to include the rapidly growing amount of functional information about gene products from mouse. MfunGD is implemented in GenRE, a J2EE-based component-oriented multi-tier architecture following the separation of concern principle

Broadening the horizon – level 2.5 of the HUPO-PSI format for molecular interactions

BACKGROUND: Molecular interaction Information is a key resource in modern biomedical research. Publicly available data have previously been provided in a broad array of diverse formats, making access to this very difficult. The publication and wide implementation of the Human Proteome Organisation Proteomics Standards Initiative Molecular Interactions (HUPO PSI-MI) format in 2004 was a major step towards the establishment of a single, unified format by which molecular interactions should be presented, but focused purely on protein-protein interactions. RESULTS: The HUPO-PSI has further developed the PSI-MI XML schema to enable the description of interactions between a wider range of molecular types, for example nucleic acids, chemical entities, and molecular complexes. Extensive details about each supported molecular interaction can now be captured, including the biological role of each molecule within that interaction, detailed description of interacting domains, and the kinetic parameters of the interaction. The format is supported by data management and analysis tools and has been adopted by major interaction data providers. Additionally, a simpler, tab-delimited format MITAB2.5 has been developed for the benefit of users who require only minimal information in an easy to access configuration. CONCLUSION: The PSI-MI XML2.5 and MITAB2.5 formats have been jointly developed by interaction data producers and providers from both the academic and commercial sector, and are already widely implemented and well supported by an active development community. PSI-MI XML2.5 enables the description of highly detailed molecular interaction data and facilitates data exchange between databases and users without loss of information. MITAB2.5 is a simpler format appropriate for fast Perl parsing or loading into Microsoft Excel

Insights from the genome of the biotrophic fungal plant pathogen Ustilago maydis

Ustilago maydis is a ubiquitous pathogen of maize and a well-established model organism for the study of plant-microbe interactions. This basidiomycete fungus does not use aggressive virulence strategies to kill its host. U. maydis belongs to the group of biotrophic parasites (the smuts) that depend on living tissue for proliferation and development. Here we report the genome sequence for a member of this economically important group of biotrophic fungi. The 20.5-million-base U. maydis genome assembly contains 6,902 predicted protein-encoding genes and lacks pathogenicity signatures found in the genomes of aggressive pathogenic fungi, for example a battery of cell-wall-degrading enzymes. However, we detected unexpected genomic features responsible for the pathogenicity of this organism. Specifically, we found 12 clusters of genes encoding small secreted proteins with unknown function. A significant fraction of these genes exists in small gene families. Expression analysis showed that most of the genes contained in these clusters are regulated together and induced in infected tissue. Deletion of individual clusters altered the virulence of U. maydis in five cases, ranging from a complete lack of symptoms to hypervirulence. Despite years of research into the mechanism of pathogenicity in U. maydis, no 'true' virulence factors had been previously identified. Thus, the discovery of the secreted protein gene clusters and the functional demonstration of their decisive role in the infection process illuminate previously unknown mechanisms of pathogenicity operating in biotrophic fungi. Genomic analysis is, similarly, likely to open up new avenues for the discovery of virulence determinants in other pathogens. ©2006 Nature Publishing Group.J.K., M. B. and R.K. thank G. Sawers and U. Kämper for critical reading of the manuscript. The genome sequencing of Ustilago maydis strain 521 is part of the fungal genome initiative and was funded by National Human Genome Research Institute (USA) and BayerCropScience AG (Germany). F.B. was supported by a grant from the National Institutes of Health (USA). J.K. and R.K. thank the German Ministry of Education and Science (BMBF) for financing the DNA array setup and the Max Planck Society for their support of the manual genome annotation. F.B. was supported by a grant from the National Institutes of Health, B.J.S. was supported by the Natural Sciences and Engineering Research Council of Canada and the Canada Foundation for Innovation, J.W.K. received funding from the Natural Sciences and Engineering Research Council of Canada, J.R.-H. received funding from CONACYT, México, A.M.-M. was supported by a fellowship from the Humboldt Foundation, and L.M. was supported by an EU grant. Author Contributions All authors were involved in planning and executing the genome sequencing project. B.W.B., J.G., L.-J.M., E.W.M., D.D., C.M.W., J.B., S.Y., D.B.J., S.C., C.N., E.K., G.F., P.H.S., I.H.-H., M. Vaupel, H.V., T.S., J.M., D.P., C.S., A.G., F.C. and V. Vysotskaia contributed to the three independent sequencing projects; M.M., G.M., U.G., D.H., M.O. and H.-W.M. were responsible for gene model refinement, database design and database maintenance; G.M., J. Kämper, R.K., G.S., M. Feldbrügge, J.S., C.W.B., U.F., M.B., B.S., B.J.S., M.J.C., E.C.H.H., S.M., F.B., J.W.K., K.J.B., J. Klose, S.E.G., S.J.K., M.H.P., H.A.B.W., R.deV., H.J.D., J.R.-H., C.G.R.-P., L.O.-C., M.McC., K.S., J.P.-M., J.I.I., W.H., P.G., P.S.-A., M. Farman, J.E.S., R.S., J.M.G.-P., J.C.K., W.L. and D.H. were involved in functional annotation and interpretation; T.B., O.M., L.M., A.M.-M., D.G., K.M., N.R., V. Vincon, M. VraneŠ, M.S. and O.L. performed experiments. J. Kämper, R.K. and M.B. wrote and edited the paper with input from L.-J.M., J.G., F.B., J.W.K., B.J.S. and S.E.G. Individual contributions of authors can be found as Supplementary Notes

Analysis of integrated biomolecular networks using a generic network analysis suite

network analysis suit