mGene.web: a web service for accurate computational gene finding

We describe mGene.web, a web service for the genome-wide prediction of protein coding genes from eukaryotic DNA sequences. It offers pre-trained models for the recognition of gene structures including untranslated regions in an increasing number of organisms. With mGene.web, users have the additional possibility to train the system with their own data for other organisms on the push of a button, a functionality that will greatly accelerate the annotation of newly sequenced genomes. The system is built in a highly modular way, such that individual components of the framework, like the promoter prediction tool or the splice site predictor, can be used autonomously. The underlying gene finding system mGene is based on discriminative machine learning techniques and its high accuracy has been demonstrated in an international competition on nematode genomes. mGene.web is available at http://www.mgene.org/web, it is free of charge and can be used for eukaryotic genomes of small to moderate size (several hundred Mbp)

mGene.web: a web service for accurate computational gene finding

We describe mGene.web, a web service for the genome-wide prediction of protein coding genes from eukaryotic DNA sequences. It offers pre-trained models for the recognition of gene structures including untranslated regions in an increasing number of organisms. With mGene.web, users have the additional possibility to train the system with their own data for other organisms on the push of a button, a functionality that will greatly accelerate the annotation of newly sequenced genomes. The system is built in a highly modular way, such that individual components of the framework, like the promoter prediction tool or the splice site predictor, can be used autonomously. The underlying gene finding system mGene is based on discriminative machine learning techniques and its high accuracy has been demonstrated in an international competition on nematode genomes. mGene.web is available at http://www.mgene.org/web, it is free of charge and can be used for eukaryotic genomes of small to moderate size (several hundred Mbp)

The Mystery of Two Straight Lines in Bacterial Genome Statistics. Release 2007

In special coordinates (codon position--specific nucleotide frequencies) bacterial genomes form two straight lines in 9-dimensional space: one line for eubacterial genomes, another for archaeal genomes. All the 348 distinct bacterial genomes available in Genbank in April 2007, belong to these lines with high accuracy. The main challenge now is to explain the observed high accuracy. The new phenomenon of complementary symmetry for codon position--specific nucleotide frequencies is observed. The results of analysis of several codon usage models are presented. We demonstrate that the mean--field approximation, which is also known as context--free, or complete independence model, or Segre variety, can serve as a reasonable approximation to the real codon usage. The first two principal components of codon usage correlate strongly with genomic G+C content and the optimal growth temperature respectively. The variation of codon usage along the third component is related to the curvature of the mean-field approximation. First three eigenvalues in codon usage PCA explain 59.1%, 7.8% and 4.7% of variation. The eubacterial and archaeal genomes codon usage is clearly distributed along two third order curves with genomic G+C content as a parameter.Comment: Significantly extended version with new data for all the 348 distinct bacterial genomes available in Genbank in April 200

Universal architecture of bacterial chemoreceptor arrays

Chemoreceptors are key components of the high-performance signal transduction system that controls bacterial chemotaxis. Chemoreceptors are typically localized in a cluster at the cell pole, where interactions among the receptors in the cluster are thought to contribute to the high sensitivity, wide dynamic range, and precise adaptation of the signaling system. Previous structural and genomic studies have produced conflicting models, however, for the arrangement of the chemoreceptors in the clusters. Using whole-cell electron cryo-tomography, here we show that chemoreceptors of different classes and in many different species representing several major bacterial phyla are all arranged into a highly conserved, 12-nm hexagonal array consistent with the proposed “trimer of dimers” organization. The various observed lengths of the receptors confirm current models for the methylation, flexible bundle, signaling, and linker sub-domains in vivo. Our results suggest that the basic mechanism and function of receptor clustering is universal among bacterial species and was thus conserved during evolution

Biophysical controls on cluster dynamics and architectural differentiation of microbial biofilms in contrasting flow environments

Ecology, with a traditional focus on plants and animals, seeks to understand the mechanisms underlying structure and dynamics of communities. In microbial ecology, the focus is changing from planktonic communities to attached biofilms that dominate microbial life in numerous systems. Therefore, interest in the structure and function of biofilms is on the rise. Biofilms can form reproducible physical structures (i.e. architecture) at the millimetre-scale, which are central to their functioning. However, the spatial dynamics of the clusters conferring physical structure to biofilms remains often elusive. By experimenting with complex microbial communities forming biofilms in contrasting hydrodynamic microenvironments in stream mesocosms, we show that morphogenesis results in 'ripple-like' and 'star-like' architectures - as they have also been reported from monospecies bacterial biofilms, for instance. To explore the potential contribution of demographic processes to these architectures, we propose a size-structured population model to simulate the dynamics of biofilm growth and cluster size distribution. Our findings establish that basic physical and demographic processes are key forces that shape apparently universal biofilm architectures as they occur in diverse microbial but also in single-species bacterial biofilm

Coupling virtual watersheds with ecosystem services assessment: A 21st century platform to support river research and management

The demand for freshwater is projected to increase worldwide over the coming decades, resulting in severe water stress and threats to riverine biodiversity, ecosystem functioning and services. A major societal challenge is to determine where environmental changes will have the greatest impacts on riverine ecosystem services and where resilience can be incorporated into adaptive resource planning. Both water managers and scientists need new integrative tools to guide them towards the best solutions that meet the demands of a growing human population but also ensure riverine biodiversity and ecosystem integrity. Resource planners and scientists could better address a growing set of riverine management and risk mitigation issues by (1) using a “Virtual Watersheds” approach based on improved digital river networks and better connections to terrestrial systems; (2) integrating Virtual Watersheds with ecosystem services technology (ARtificial Intelligence for Ecosystem Services: ARIES), and (3) incorporating the role of riverine biotic interactions in shaping ecological responses. This integrative platform can support both interdisciplinary scientific analyses of pressing societal issues and effective dissemination of findings across river research and management communities. It should also provide new integrative tools to identify the best solutions and trade-offs to ensure the conservation of riverine biodiversity and ecosystem services

Draft Genome Sequence of the Marine Streptomyces sp. Strain PP-C42, Isolated from the Baltic Sea

Streptomyces, a branch of aerobic Gram-positive bacteria represents the largest genus of actinobacteria. The streptomycetes are characterized by a complex secondary metabolism and produce over two-thirds of the clinically used natural antibiotics today. Here we report the draft genome sequence of a Streptomyces strain PP-C42 isolated from the marine environment. A subset of unique genes and gene clusters for diverse secondary metabolites as well as antimicrobial peptides (AMPs) could be identified from the genome, showing great promise as a source for novel bioactive compound

Draft Genome Sequence of the Marine Streptomyces sp. Strain PP-C42, Isolated from the Baltic Sea

Streptomyces, a branch of aerobic Gram-positive bacteria represents the largest genus of actinobacteria. The streptomycetes are characterized by a complex secondary metabolism and produce over two-thirds of the clinically used natural antibiotics today. Here we report the draft genome sequence of a Streptomyces strain PP-C42 isolated from the marine environment. A subset of unique genes and gene clusters for diverse secondary metabolites as well as antimicrobial peptides (AMPs) could be identified from the genome, showing great promise as a source for novel bioactive compound

Comparative analysis of an experimental subcellular protein localization assay and in silico prediction methods

The subcellular localization of a protein can provide important information about its function within the cell. As eukaryotic cells and particularly mammalian cells are characterized by a high degree of compartmentalization, most protein activities can be assigned to particular cellular compartments. The categorization of proteins by their subcellular localization is therefore one of the essential goals of the functional annotation of the human genome. We previously performed a subcellular localization screen of 52 proteins encoded on human chromosome 21. In the current study, we compared the experimental localization data to the in silico results generated by nine leading software packages with different prediction resolutions. The comparison revealed striking differences between the programs in the accuracy of their subcellular protein localization predictions. Our results strongly suggest that the recently developed predictors utilizing multiple prediction methods tend to provide significantly better performance over purely sequence-based or homology-based predictions

Ergatis: a web interface and scalable software system for bioinformatics workflows

Motivation: The growth of sequence data has been accompanied by an increasing need to analyze data on distributed computer clusters. The use of these systems for routine analysis requires scalable and robust software for data management of large datasets. Software is also needed to simplify data management and make large-scale bioinformatics analysis accessible and reproducible to a wide class of target users