Biomedical subjects

Andreas Ruepp

Publications and source records attributed to Andreas Ruepp.

9 recordsLinked to original sources

PubMed2006

Cloning and characterization of Enterobacter sakazakii pigment genes and in situ spectroscopic analysis of the pigment.

Enterobacter sakazakii is considered an opportunistic foodborne pathogen that is characterized by formation of yellow-pigmented colonies. Because of the lack of basic knowledge about Enterobacter sakazakii genetics, the BAC approach and the heterologous expression of the pigment in Escherichia coli were used to elucidate the molecular structure of the genes responsible for pigment production in Enterobacter sakazakii strain ES5. Sequencing and annotation of a 33.025 bp fragment revealed seven ORFs that could be assigned to the carotenoid biosynthesis pathway. The gene cluster had the organization crtE-idi-XYIBZ, with the crtE-idi-XYIB genes putatively transcribed as an operon and the crtZ gene transcribed in the opposite orientation. The carotenogenic nature of the pigment of Enterobacter sakazakii wt was ascertained by in situ analysis using visible microspectroscopy and resonance Raman microspectroscopy.

Carotenoids↗

PubMed2006

Molecular characterization of the alpha-glucosidase activity in Enterobacter sakazakii reveals the presence of a putative gene cluster for palatinose metabolism.

Enterobacter sakazakii is considered an opportunistic pathogen for premature infants and neonates. Although E. sakazakii has been isolated from various types of food, recontaminated dried infant formula has been epidemiologically identified as the major source of infection. Amongst others, alpha-glucosidase activity is one of the most important biochemical features, which differentiates E. sakazakii from other species in the family Enterobacteriaceae and has therefore been used as a selective marker in the development of differential media. However, it has been shown, that methods based on this biochemical feature are prone to producing false-positive results for presumptive E. sakazakii colonies due to the presence of this enzymatic activity in other species of the Enterobacteriaceae. Therefore, elucidation of the molecular basis responsible for the biochemical feature in E. sakazakii would provide novel targets suitable for the development of more specific and direct identification systems for this organism. By applying the bacterial artificial chromosome (BAC) approach, along with heterologous gene expression in Escherichia coli, the molecular basis of the alpha-glucosidase activity in E. sakazakii was characterized. Here we report the identification of two different alpha-glucosidase encoding genes. Homology searches of the deduced amino acid sequences revealed that the proteins belong to a cluster of gene products putatively responsible for the metabolism of isomaltulose (palatinose; 6-O-alpha-d-glucopyranosyl-d-fructose). The glycosyl-hydrolyzing activity of each protein was demonstrated by subcloning the respective open reading frames and screening of E. coli transformants for their ability to hydrolyze 4-methyl-umbelliferyl-alpha-d-glucoside. Analysis at the protein level revealed that both enzymes belong to the intracellular fraction of cell proteins. The presence of the postulated palatinose metabolism was proven by growth experiments using this sugar as a sole carbon source.

Bacterial Proteins↗

PubMed2006

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 http://mips.gsf.de/genre/proj/mpact.

Databases, Protein↗

PubMed2006

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

MfunGD (http://mips.gsf.de/genre/proj/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.

Animals↗

PubMed2006

Resources and tools for investigating biomolecular networks in mammals.

Molecular databases serve as primary information resources for the analysis of biological networks providing an essential and invaluable treasure for information exploration. Tools for projecting experimental data sets onto known functional information are a major need to support the analysis of samples produced in clinical research. A new concept is the notation of functional modules, i.e. the characterisation of sets of proteins that perform a defined biological function in cooperation. The determination and analysis of functional modules overcome the limitations of the analysis of individual genes and their properties. Although functional modules are not suitable to fully capture systems properties, they have the potential to unify the information generated by different types of experiments. We describe advances related to the problem of integrating heterogeneous data sets into functional modules for mouse and/or human cellular networks based on publicly available data resources, including advances in the design of ontologies for functional classification, problems of automatic protein functional annotation and integration of microarray data.

Algorithms↗

PubMed2005

Super paramagnetic clustering of protein sequences.

BACKGROUND: Detection of sequence homologues represents a challenging task that is important for the discovery of protein families and the reliable application of automatic annotation methods. The presence of domains in protein families of diverse function, inhomogeneity and different sizes of protein families create considerable difficulties for the application of published clustering methods. RESULTS: Our work analyses the Super Paramagnetic Clustering (SPC) and its extension, global SPC (gSPC) algorithm. These algorithms cluster input data based on a method that is analogous to the treatment of an inhomogeneous ferromagnet in physics. For the SwissProt and SCOP databases we show that the gSPC improves the specificity and sensitivity of clustering over the original SPC and Markov Cluster algorithm (TRIBE-MCL) up to 30%. The three algorithms provided similar results for the MIPS FunCat 1.3 annotation of four bacterial genomes, Bacillus subtilis, Helicobacter pylori, Listeria innocua and Listeria monocytogenes. However, the gSPC covered about 12% more sequences compared to the other methods. The SPC algorithm was programmed in house using C++ and it is available at http://mips.gsf.de/proj/spc. The FunCat annotation is available at http://mips.gsf.de. CONCLUSION: The gSPC calculated to a higher accuracy or covered a larger number of sequences than the TRIBE-MCL algorithm. Thus it is a useful approach for automatic detection of protein families and unsupervised annotation of full genomes.

Algorithms↗

PubMed2005

MIPS bacterial genomes functional annotation benchmark dataset.

MOTIVATION: Any development of new methods for automatic functional annotation of proteins according to their sequences requires high-quality data (as benchmark) as well as tedious preparatory work to generate sequence parameters required as input data for the machine learning methods. Different program settings and incompatible protocols make a comparison of the analyzed methods difficult. RESULTS: The MIPS Bacterial Functional Annotation Benchmark dataset (MIPS-BFAB) is a new, high-quality resource comprising four bacterial genomes manually annotated according to the MIPS functional catalogue (FunCat). These resources include precalculated sequence parameters, such as sequence similarity scores, InterPro domain composition and other parameters that could be used to develop and benchmark methods for functional annotation of bacterial protein sequences. These data are provided in XML format and can be used by scientists who are not necessarily experts in genome annotation. AVAILABILITY: BFAB is available at http://mips.gsf.de/proj/bfab

Bacterial Proteins↗

PubMed2004

The MIPS mammalian protein-protein interaction database.

SUMMARY: The MIPS mammalian protein-protein interaction database (MPPI) is a new resource of high-quality experimental protein interaction data in mammals. The content is based on published experimental evidence that has been processed by human expert curators. We provide the full dataset for download and a flexible and powerful web interface for users with various requirements.

Animals↗

PubMed2004

The FunCat, a functional annotation scheme for systematic classification of proteins from whole genomes.

In this paper, we present the Functional Catalogue (FunCat), a hierarchically structured, organism-independent, flexible and scalable controlled classification system enabling the functional description of proteins from any organism. FunCat has been applied for the manual annotation of prokaryotes, fungi, plants and animals. We describe how FunCat is implemented as a highly efficient and robust tool for the manual and automatic annotation of genomic sequences. Owing to its hierarchical architecture, FunCat has also proved to be useful for many subsequent downstream bioinformatic applications. This is illustrated by the analysis of large-scale experiments from various investigations in transcriptomics and proteomics, where FunCat was used to project experimental data into functional units, as 'gold standard' for functional classification methods, and also served to compare the significance of different experimental methods. Over the last decade, the FunCat has been established as a robust and stable annotation scheme that offers both, meaningful and manageable functional classification as well as ease of perception.

Abstracting and Indexing↗