Martin Mokrejs

Bio: Martin Mokrejs is an academic researcher from Charles University in Prague. The author has contributed to research in topics: Genome & Internal ribosome entry site. The author has an hindex of 9, co-authored 12 publications receiving 3458 citations. Previous affiliations of Martin Mokrejs include Max Planck Society & Academy of Sciences of the Czech Republic.

MIPS: a database for genomes and protein sequences

Abstract: The Munich Information Center for Protein Sequences (MIPS-GSF, Neuherberg, Germany) continues to provide genome-related information in a systematic way. MIPS supports both national and European sequencing and functional analysis projects, develops and maintains automatically generated and manually annotated genome-specific databases, develops systematic classification schemes for the functional annotation of protein sequences, and provides tools for the comprehensive analysis of protein sequences. This report updates the information on the yeast genome (CYGD), the Neurospora crassa genome (MNCDB), the databases for the comprehensive set of genomes (PEDANT genomes), the database of annotated human EST clusters (HIB), the database of complete cDNAs from the DHGP (German Human Genome Project), as well as the project specific databases for the GABI (Genome Analysis in Plants) and HNB (Helmholtz-Netzwerk Bioinformatik) networks. The Arabidospsis thaliana database (MATDB), the database of mitochondrial proteins (MITOP) and our contribution to the PIR International Protein Sequence Database have been described elsewhere [Schoof et al. (2002) Nucleic Acids Res., 30, 91-93; Scharfe et al. (2000) Nucleic Acids Res., 28, 155-158; Barker et al. (2001) Nucleic Acids Res., 29, 29-32]. All databases described, the protein analysis tools provided and the detailed descriptions of our projects can be accessed through the MIPS World Wide Web server (http://mips.gsf.de).

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

Abstract: 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.

Genome, transcriptome, and secretome analysis of wood decay fungus Postia placenta supports unique mechanisms of lignocellulose conversion

Abstract: Brown-rot fungi such as Postia placenta are common inhabitants of forest ecosystems and are also largely responsible for the destructive decay of wooden structures. Rapid depolymerization of cellulose is a distinguishing feature of brown-rot, but the biochemical mechanisms and underlying genetics are poorly understood. Systematic examination of the P. placenta genome, transcriptome, and secretome revealed unique extracellular enzyme systems, including an unusual repertoire of extracellular glycoside hydrolases. Genes encoding exocellobiohydrolases and cellulose-binding domains, typical of cellulolytic microbes, are absent in this efficient cellulose-degrading fungus. When P. placenta was grown in medium containing cellulose as sole carbon source, transcripts corresponding to many hemicellulases and to a single putative β-1–4 endoglucanase were expressed at high levels relative to glucose-grown cultures. These transcript profiles were confirmed by direct identification of peptides by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Also up-regulated during growth on cellulose medium were putative iron reductases, quinone reductase, and structurally divergent oxidases potentially involved in extracellular generation of Fe(II) and H2O2. These observations are consistent with a biodegradative role for Fenton chemistry in which Fe(II) and H2O2 react to form hydroxyl radicals, highly reactive oxidants capable of depolymerizing cellulose. The P. placenta genome resources provide unparalleled opportunities for investigating such unusual mechanisms of cellulose conversion. More broadly, the genome offers insight into the diversification of lignocellulose degrading mechanisms in fungi. Comparisons with the closely related white-rot fungus Phanerochaete chrysosporium support an evolutionary shift from white-rot to brown-rot during which the capacity for efficient depolymerization of lignin was lost.

The PEDANT genome database

Abstract: The PEDANT genome database (http://pedant.gsf.de) provides exhaustive automatic analysis of genomic sequences by a large variety of established bioinfor- matics tools through a comprehensive Web-based user interface. One hundred and seventy seven completely sequenced and unfinished genomes have been processed so far, including large eukar- yotic genomes (mouse, human) published recently. In this contribution, we describe the current status of the PEDANT database and novel analytical features added to the PEDANT server in 2002. Those include: (i) integration with the BioRS TM data retrieval system which allows fast text queries, (ii) pre-computed sequence clusters in each complete genome, (iii) a comprehensive set of tools for genome comparison, including genome comparison tables and protein function prediction based on genomic context, and (iv) computation and visualization of protein- protein interaction (PPI) networks based on experi- mental data. The availability of functional and structural predictions for 650 000 genomic proteins in well organized form makes PEDANT a useful resource for both functional and structural genomics.

IRESite—a tool for the examination of viral and cellular internal ribosome entry sites

Abstract: The IRESite (http://www.iresite.org) presents carefully curated experimental evidence of many eukaryotic viral and cellular internal ribosome entry site (IRES) regions. At the time of submission, IRESite stored >600 records. The IRESite gradually evolved into a robust tool providing (i) biologically meaningful information regarding the IRESs and their experimental background (including annotation of IRES secondary structures and IRES trans-acting factors) as well as (ii) thorough concluding remarks to stored database entries and regularly updated evaluation of the reported IRES function. A substantial portion of the IRESite data results purely from in-house bioinformatic analyses of currently available sequences, in silico attempts to repeat published cloning experiments, DNA sequencing and restriction endonuclease verification of received plasmid DNA. We also present a newly implemented tool for displaying RNA secondary structures and for searching through the structures currently stored in the database. The supplementary material contains an updated list of reported IRESs.

Gene Ontology: tool for the unification of biology

Abstract: Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.

Large-scale analysis of the yeast proteome by multidimensional protein identification technology.

Abstract: We describe a largely unbiased method for rapid and large-scale proteome analysis by multidimensional liquid chromatography, tandem mass spectrometry, and database searching by the SEQUEST algorithm, named multidimensional protein identification technology (MudPIT). MudPIT was applied to the proteome of the Saccharomyces cerevisiae strain BJ5460 grown to mid-log phase and yielded the largest proteome analysis to date. A total of 1,484 proteins were detected and identified. Categorization of these hits demonstrated the ability of this technology to detect and identify proteins rarely seen in proteome analysis, including low-abundance proteins like transcription factors and protein kinases. Furthermore, we identified 131 proteins with three or more predicted transmembrane domains, which allowed us to map the soluble domains of many of the integral membrane proteins. MudPIT is useful for proteome analysis and may be specifically applied to integral membrane proteins to obtain detailed biochemical information on this unwieldy class of proteins.

An automated method for finding molecular complexes in large protein interaction networks.

Abstract: Recent advances in proteomics technologies such as two-hybrid, phage display and mass spectrometry have enabled us to create a detailed map of biomolecular interaction networks. Initial mapping efforts have already produced a wealth of data. As the size of the interaction set increases, databases and computational methods will be required to store, visualize and analyze the information in order to effectively aid in knowledge discovery. This paper describes a novel graph theoretic clustering algorithm, "Molecular Complex Detection" (MCODE), that detects densely connected regions in large protein-protein interaction networks that may represent molecular complexes. The method is based on vertex weighting by local neighborhood density and outward traversal from a locally dense seed protein to isolate the dense regions according to given parameters. The algorithm has the advantage over other graph clustering methods of having a directed mode that allows fine-tuning of clusters of interest without considering the rest of the network and allows examination of cluster interconnectivity, which is relevant for protein networks. Protein interaction and complex information from the yeast Saccharomyces cerevisiae was used for evaluation. Dense regions of protein interaction networks can be found, based solely on connectivity data, many of which correspond to known protein complexes. The algorithm is not affected by a known high rate of false positives in data from high-throughput interaction techniques. The program is available from ftp://ftp.mshri.on.ca/pub/BIND/Tools/MCODE .

Functional profiling of the Saccharomyces cerevisiae genome.

Abstract: Determining the effect of gene deletion is a fundamental approach to understanding gene function. Conventional genetic screens exhibit biases, and genes contributing to a phenotype are often missed. We systematically constructed a nearly complete collection of gene-deletion mutants (96% of annotated open reading frames, or ORFs) of the yeast Saccharomyces cerevisiae. DNA sequences dubbed 'molecular bar codes' uniquely identify each strain, enabling their growth to be analysed in parallel and the fitness contribution of each gene to be quantitatively assessed by hybridization to high-density oligonucleotide arrays. We show that previously known and new genes are necessary for optimal growth under six well-studied conditions: high salt, sorbitol, galactose, pH 8, minimal medium and nystatin treatment. Less than 7% of genes that exhibit a significant increase in messenger RNA expression are also required for optimal growth in four of the tested conditions. Our results validate the yeast gene-deletion collection as a valuable resource for functional genomics.