Diverse Taxonomies for Diverse Chemistries: Enhanced Representation of Natural Product Metabolism in UniProtKB.

The UniProt Knowledgebase UniProtKB is a comprehensive, high-quality, and freely accessible resource of protein sequences and functional annotation that covers genomes and proteomes from tens of thousands of taxa, including a broad range of plants and microorganisms producing natural products of medical, nutritional, and agronomical interest. Here we describe work that enhances the utility of UniProtKB as a support for both the study of natural products and for their discovery. The foundation of this work is an improved representation of natural product metabolism in UniProtKB using Rhea, an expert-curated knowledgebase of biochemical reactions, that is built on the ChEBI (Chemical Entities of Biological Interest) ontology of small molecules. Knowledge of natural products and precursors is captured in ChEBI, enzyme-catalyzed reactions in Rhea, and enzymes in UniProtKB/Swiss-Prot, thereby linking chemical structure data directly to protein knowledge. We provide a practical demonstration of how users can search UniProtKB for protein knowledge relevant to natural products through interactive or programmatic queries using metabolite names and synonyms, chemical identifiers, chemical classes, and chemical structures and show how to federate UniProtKB with other data and knowledge resources and tools using semantic web technologies such as RDF and SPARQL. All UniProtKB data are freely available for download in a broad range of formats for users to further mine or exploit as an annotation source, to enrich other natural product datasets and databases.

Enzyme annotation in UniProtKB using Rhea.

MOTIVATION: To provide high quality computationally tractable enzyme annotation in UniProtKB using Rhea, a comprehensive expert-curated knowledgebase of biochemical reactions which describes reaction participants using the ChEBI (Chemical Entities of Biological Interest) ontology. RESULTS: We replaced existing textual descriptions of biochemical reactions in UniProtKB with their equivalents from Rhea, which is now the standard for annotation of enzymatic reactions in UniProtKB. We developed improved search and query facilities for the UniProt website, REST API and SPARQL endpoint that leverage the chemical structure data, nomenclature and classification that Rhea and ChEBI provide. AVAILABILITY AND IMPLEMENTATION: UniProtKB at https://www.uniprot.org; UniProt REST API at https://www.uniprot.org/help/api; UniProt SPARQL endpoint at https://sparql.uniprot.org/; Rhea at https://www.rhea-db.org.

Updates in Rhea: SPARQLing biochemical reaction data.

Rhea (http://www.rhea-db.org) is a comprehensive and non-redundant resource of over 11 000 expert-curated biochemical reactions that uses chemical entities from the ChEBI ontology to represent reaction participants. Originally designed as an annotation vocabulary for the UniProt Knowledgebase (UniProtKB), Rhea also provides reaction data for a range of other core knowledgebases and data repositories including ChEBI and MetaboLights. Here we describe recent developments in Rhea, focusing on a new resource description framework representation of Rhea reaction data and an SPARQL endpoint (https://sparql.rhea-db.org/sparql) that provides access to it. We demonstrate how federated queries that combine the Rhea SPARQL endpoint and other SPARQL endpoints such as that of UniProt can provide improved metabolite annotation and support integrative analyses that link the metabolome through the proteome to the transcriptome and genome. These developments will significantly boost the utility of Rhea as a means to link chemistry and biology for a more holistic understanding of biological systems and their function in health and disease.

Updates in Rhea - an expert curated resource of biochemical reactions.

Rhea (http://www.rhea-db.org) is a comprehensive and non-redundant resource of expert-curated biochemical reactions designed for the functional annotation of enzymes and the description of metabolic networks. Rhea describes enzyme-catalyzed reactions covering the IUBMB Enzyme Nomenclature list as well as additional reactions, including spontaneously occurring reactions, using entities from the ChEBI (Chemical Entities of Biological Interest) ontology of small molecules. Here we describe developments in Rhea since our last report in the database issue of Nucleic Acids Research. These include the first implementation of a simple hierarchical classification of reactions, improved coverage of the IUBMB Enzyme Nomenclature list and additional reactions through continuing expert curation, and the development of a new website to serve this improved dataset.

Updates in Rhea--a manually curated resource of biochemical reactions.

Rhea (http://www.ebi.ac.uk/rhea) is a comprehensive and non-redundant resource of expert-curated biochemical reactions described using species from the ChEBI (Chemical Entities of Biological Interest) ontology of small molecules. Rhea has been designed for the functional annotation of enzymes and the description of genome-scale metabolic networks, providing stoichiometrically balanced enzyme-catalyzed reactions (covering the IUBMB Enzyme Nomenclature list and additional reactions), transport reactions and spontaneously occurring reactions. Rhea reactions are extensively curated with links to source literature and are mapped to other publicly available enzyme and pathway databases such as Reactome, BioCyc, KEGG and UniPathway, through manual curation and computational methods. Here we describe developments in Rhea since our last report in the 2012 database issue of Nucleic Acids Research. These include significant growth in the number of Rhea reactions and the inclusion of reactions involving complex macromolecules such as proteins, nucleic acids and other polymers that lie outside the scope of ChEBI. Together these developments will significantly increase the utility of Rhea as a tool for the description, analysis and reconciliation of genome-scale metabolic models.

MetaMine--a tool to detect and analyse gene patterns in their environmental context.

BACKGROUND: Modern sequencing technologies allow rapid sequencing and bioinformatic analysis of genomes and metagenomes. With every new sequencing project a vast number of new proteins become available with many genes remaining functionally unclassified based on evidences from sequence similarities alone. Extending similarity searches with gene pattern approaches, defined as genes sharing a distinct genomic neighbourhood, have shown to significantly improve the number of functional assignments. Further functional evidences can be gained by correlating these gene patterns with prevailing environmental parameters. MetaMine was developed to approach the large pool of unclassified proteins by searching for recurrent gene patterns across habitats based on key genes. RESULTS: MetaMine is an interactive data mining tool which enables the detection of gene patterns in an environmental context. The gene pattern search starts with a user defined environmentally interesting key gene. With this gene a BLAST search is carried out against the Microbial Ecological Genomics DataBase (MEGDB) containing marine genomic and metagenomic sequences. This is followed by the determination of all neighbouring genes within a given distance and a search for functionally equivalent genes. In the final step a set of common genes present in a defined number of distinct genomes is determined. The gene patterns found are associated with their individual pattern instances describing gene order and directions. They are presented together with information about the sample and the habitat. MetaMine is implemented in Java and provided as a client/server application with a user-friendly graphical user interface. The system was evaluated with environmentally relevant genes related to the methane-cycle and carbon monoxide oxidation. CONCLUSION: MetaMine offers a targeted, semi-automatic search for gene patterns based on expert input. The graphical user interface of MetaMine provides a user-friendly overview of the computed gene patterns for further inspection in an ecological context. Prevailing biological processes associated with a key gene can be used to infer new annotations and shape hypotheses to guide further analyses. The use-cases demonstrate that meaningful gene patterns can be quickly detected using MetaMine.MetaMine is freely available for academic use from http://www.megx.net/metamine.

A standard MIGS/MIMS compliant XML Schema: toward the development of the Genomic Contextual Data Markup Language (GCDML).

The Genomic Contextual Data Markup Language (GCDML) is a core project of the Genomic Standards Consortium (GSC) that implements the "Minimum Information about a Genome Sequence" (MIGS) specification and its extension, the "Minimum Information about a Metagenome Sequence" (MIMS). GCDML is an XML Schema for generating MIGS/MIMS compliant reports for data entry, exchange, and storage. When mature, this sample-centric, strongly-typed schema will provide a diverse set of descriptors for describing the exact origin and processing of a biological sample, from sampling to sequencing, and subsequent analysis. Here we describe the need for such a project, outline design principles required to support the project, and make an open call for participation in defining the future content of GCDML. GCDML is freely available, and can be downloaded, along with documentation, from the GSC Web site (http://gensc.org).

JCoast - a biologist-centric software tool for data mining and comparison of prokaryotic (meta)genomes.

BACKGROUND: Current sequencing technologies give access to sequence information for genomes and metagenomes at a tremendous speed. Subsequent data processing is mainly performed by automatic pipelines provided by the sequencing centers. Although, standardised workflows are desirable and useful in many respects, rational data mining, comparative genomics, and especially the interpretation of the sequence information in the biological context, demands for intuitive, flexible, and extendable solutions. RESULTS: The JCoast software tool was primarily designed to analyse and compare (meta)genome sequences of prokaryotes. Based on a pre-computed GenDB database project, JCoast offers a flexible graphical user interface (GUI), as well as an application programming interface (API) that facilitates back-end data access. JCoast offers individual, cross genome-, and metagenome analysis, and assists the biologist in exploration of large and complex datasets. CONCLUSION: JCoast combines all functions required for the mining, annotation, and interpretation of (meta)genomic data. The lightweight software solution allows the user to easily take advantage of advanced back-end database structures by providing a programming and graphical user interface to answer biological questions. JCoast is available at the project homepage.

Detailed proteome analysis of growing cells of the planctomycete Rhodopirellula baltica SH1T.

Rhodopirellula baltica SH1(T), which was isolated from the water column of the Kieler Bight, a bay in the southwestern Baltic Sea, is a marine aerobic, heterotrophic representative of the ubiquitous bacterial phylum Planctomycetes. We analyzed the R. baltica proteome by applying different preanalytical protein as well as peptide separation techniques (1-D and 2-DE, HPLC separation) prior to MS. That way, we could identify a total of 1115 nonredundant proteins from the intracellular proteome and from different cell wall protein fractions. With the contribution of 709 novel proteins resulting from this study, the current comprehensive R. baltica proteomic dataset consists of 1267 unique proteins (accounting for 17.3% of the total putative protein-coding ORFs), including 261 proteins with a predicted signal peptide. The identified proteins were functionally categorized using Clusters of Orthologous Groups (COGs), and their potential cellular locations were predicted by bioinformatic tools. A unique protein family that contains several YTV domains and is rich in cysteine and proline was found to be a component of the R. baltica proteinaceous cell wall. Based on this comprehensive proteome analysis a global schema of the major metabolic pathways of growing R. baltica cells was deduced.

MetaLook: a 3D visualisation software for marine ecological genomics.

BACKGROUND: Marine ecological genomics can be defined as the application of genomic sciences to understand the structure and function of marine ecosystems. In this field of research, the analysis of genomes and metagenomes of environmental relevance must take into account the corresponding habitat (contextual) data, e.g. water depth, physical and chemical parameters. The creation of specialised software tools and databases is requisite to allow this new kind of integrated analysis. RESULTS: We implemented the MetaLook software for visualisation and analysis of marine ecological genomic and metagenomic data with respect to habitat parameters. MetaLook offers a three-dimensional user interface to interactively visualise DNA sequences on a world map, based on a centralised georeferenced database. The user can define environmental containers to organise the sequences according to different habitat criteria. To find similar sequences, the containers can be queried with either genes from the georeferenced database or user-imported sequences, using the BLAST algorithm. This allows an interactive assessment of the distribution of gene functions in the environment. CONCLUSION: MetaLook allows scientists to investigate sequence data in their environmental context and to explore correlations between genes and habitat parameters. This software is a step towards the creation of specialised tools to study constrained distributions and habitat specificity of genes correlated with specific processes. MetaLook is available at: http://www.megx.net/metalook.

Comparative genome analysis of four magnetotactic bacteria reveals a complex set of group-specific genes implicated in magnetosome biomineralization and function.

Magnetotactic bacteria (MTB) are a heterogeneous group of aquatic prokaryotes with a unique intracellular organelle, the magnetosome, which orients the cell along magnetic field lines. Magnetotaxis is a complex phenotype, which depends on the coordinate synthesis of magnetosomes and the ability to swim and orient along the direction caused by the interaction with the Earth's magnetic field. Although a number of putative magnetotaxis genes were recently identified within a conserved genomic magnetosome island (MAI) of several MTB, their functions have remained mostly unknown, and it was speculated that additional genes located outside the MAI might be involved in magnetosome formation and magnetotaxis. In order to identify genes specifically associated with the magnetotactic phenotype, we conducted comparisons between four sequenced magnetotactic Alphaproteobacteria including the nearly complete genome of Magnetospirillum gryphiswaldense strain MSR-1, the complete genome of Magnetospirillum magneticum strain AMB-1, the complete genome of the magnetic coccus MC-1, and the comparative-ready preliminary genome assembly of Magnetospirillum magnetotacticum strain MS-1 against an in-house database comprising 426 complete bacterial and archaeal genome sequences. A magnetobacterial core genome of about 891 genes was found shared by all four MTB. In addition to a set of approximately 152 genus-specific genes shared by the three Magnetospirillum strains, we identified 28 genes as group specific, i.e., which occur in all four analyzed MTB but exhibit no (MTB-specific genes) or only remote (MTB-related genes) similarity to any genes from nonmagnetotactic organisms and which besides various novel genes include nearly all mam and mms genes previously shown to control magnetosome formation. The MTB-specific and MTB-related genes to a large extent display synteny, partially encode previously unrecognized magnetosome membrane proteins, and are either located within (18 genes) or outside (10 genes) the MAI of M. gryphiswaldense. These genes, which represent less than 1% of the 4,268 open reading frames of the MSR-1 genome, as yet are mostly of unknown functions but are likely to be specifically involved in magnetotaxis and, thus, represent prime targets for future experimental analysis.

Genome and proteome characterization of the psychrophilic Flavobacterium bacteriophage 11b.

Virion DNA of bacteriophage 11b (Phi11b), which infects a psychrophilic Flavobacterium isolate from Arctic sea-ice, was determined to consist of 36,012 bp. With 30.6% its GC content corresponds to that of host-genus species and is the lowest of all phages of Gram-negative bacteria sequenced so far. Similarities of several of 65 predicted ORFs, genome organization and phylogeny suggest an affiliation to 'mesophilic' nonmarine siphoviruses, e.g. to bacteriophages SPP1 and HK97. Early genes presumably encode an essential recombination factor (ERF), a single strand binding (SSB) protein, an endonuclease, and a DNA methylase. The late gene segment is likely to contain a terminase, portal, minor head, protease and a major capsid gene. Five ORFs exhibited similarities to Bacteroidetes species and seem to reflect the host specificity of the phage. Among PAGE-separated virion proteins that were identified by MALDI-ToF mass spectrometry are the portal, the major capsid, and a putative conserved tail protein. The Phi11b genome is the first to be described of a cultivated virus infecting a psychrophilic host as well as a Bacteroidetes bacterium.

Whole genome analysis of the marine Bacteroidetes'Gramella forsetii' reveals adaptations to degradation of polymeric organic matter.

Members of the Bacteroidetes, formerly known as the Cytophaga-Flavobacteria-Bacteroides (CFB) phylum, are among the major taxa of marine heterotrophic bacterioplankton frequently found on macroscopic organic matter particles (marine snow). In addition, they have been shown to also represent a significant part of free-living microbial assemblages in nutrient-rich microenvironments. Their abundance and distribution pattern in combination with enzymatic activity studies has led to the notion that organisms of this group are specialists for degradation of high molecular weight compounds in both the dissolved and particulate fraction of the marine organic matter pool, implying a major role of Bacteroidetes in the marine carbon cycle. Despite their ecological importance, comprehensive molecular data on organisms of this group have been scarce so far. Here we report on the first whole genome analysis of a marine Bacteroidetes representative, 'Gramella forsetii' KT0803. Functional analysis of the predicted proteome disclosed several traits which in joint consideration suggest a clear adaptation of this marine Bacteroidetes representative to the degradation of high molecular weight organic matter, such as a substantial suite of genes encoding hydrolytic enzymes, a predicted preference for polymeric carbon sources and a distinct capability for surface adhesion.

Megx.net--database resources for marine ecological genomics.

Marine microbial genomics and metagenomics is an emerging field in environmental research. Since the completion of the first marine bacterial genome in 2003, the number of fully sequenced marine bacteria has grown rapidly. Concurrently, marine metagenomics studies are performed on a regular basis, and the resulting number of sequences is growing exponentially. To address environmentally relevant questions like organismal adaptations to oceanic provinces and regional differences in the microbial cycling of nutrients, it is necessary to couple sequence data with geographical information and supplement them with contextual information like physical, chemical and biological data. Therefore, new specialized databases are needed to organize and standardize data storage as well as centralize data access and interpretation. We introduce Megx.net, a set of databases and tools that handle genomic and metagenomic sequences in their environmental contexts. Megx.net includes (i) a geographic information system to systematically store and analyse marine genomic and metagenomic data in conjunction with contextual information; (ii) an environmental genome browser with fast search functionalities; (iii) a database with precomputed analyses for selected complete genomes; and (iv) a database and tool to classify metagenomic fragments based on oligonucleotide signatures. These integrative databases and webserver will help researchers to generate a better understanding of the functioning of marine ecosystems. All resources are freely accessible at http://www.megx.net.

Insights into the genomes of archaea mediating the anaerobic oxidation of methane.

The anaerobic oxidation of methane is a globally significant process which is mediated by consortia of yet uncultivated methanotrophic archaea (ANME) and sulfate-reducing bacteria. In order to gain deeper insights into genome characteristics of the different ANME groups, large-insert genomic libraries were constructed using DNA extracted from a methanotrophic microbial mat growing in the anoxic part of the Black Sea, and from sediments above gas hydrates at the Hydrate Ridge off the coast of Oregon. Analysis of these fosmid libraries with respect to archaeal 16S rRNA gene diversity revealed a single ANME-1b ribotype for the Black Sea libraries, whereas the sequences derived from the Hydrate Ridge library phylogenetically affiliated with the ANME-2a, ANME-2c and ANME-3 group. Genome walking for ANME-1b resulted in a contiguous 155 kb composite genome fragment. The comparison of a set of four genomic fragments belonging to the different ANME groups revealed differences in the rRNA operon structure and the average G+C content, with the ANME-2c contig showing the highest divergence within the set. A detailed analysis of the ANME contigs with respect to genes putatively involved in the anaerobic oxidation of methane led to the identification of: (i) a putative N5,N10-methenyltetrahydromethanopterin cyclohydrolase gene, (ii) a gene cluster supposedly encoding a novel type of heterodisulfide reductase/dehydrogenase complex and (iii) a gene cluster putatively encoding a new type of CO dehydrogenase/acetyl-CoA synthase enzyme complex.

Clustered genes related to sulfate respiration in uncultured prokaryotes support the theory of their concomitant horizontal transfer.

The dissimilatory reduction of sulfate is an ancient metabolic process central to today's biogeochemical cycling of sulfur and carbon in marine sediments. Until now its polyphyletic distribution was most parsimoniously explained by multiple horizontal transfers of single genes rather than by a not-yet-identified "metabolic island." Here we provide evidence that the horizontal transfer of a gene cluster may indeed be responsible for the patchy distribution of sulfate-reducing prokaryotes (SRP) in the phylogenetic tree. We isolated three DNA fragments (32 to 41 kb) from uncultured, closely related SRP from DNA directly extracted from two distinct marine sediments. Fosmid ws39f7, and partially also fosmids ws7f8 and hr42c9, harbored a core set of essential genes for the dissimilatory reduction of sulfate, including enzymes for the reduction of sulfur intermediates and synthesis of the prosthetic group of the dissimilatory sulfite reductase. Genome comparisons suggest that encoded membrane proteins universally present among SRP are critical for electron transfer to cytoplasmic enzymes. In addition, novel, conserved hypothetical proteins that are likely involved in dissimilatory sulfate reduction were identified. Based on comparative genomics and previously published experimental evidence, a more comprehensive model of dissimilatory sulfate reduction is presented. The observed clustering of genes involved in dissimilatory sulfate reduction has not been previously found. These findings strongly support the hypothesis that genes responsible for dissimilatory sulfate reduction were concomitantly transferred in a single event among prokaryotes. The acquisition of an optimized gene set would enormously facilitate a successful implementation of a novel pathway.

Towards the proteome of the marine bacterium Rhodopirellula baltica: mapping the soluble proteins.

The marine bacterium Rhodopirellula baltica, a member of the phylum Planctomycetes, has distinct morphological properties and contributes to remineralization of biomass in the natural environment. On the basis of its recently determined complete genome we investigated its proteome by 2-DE and established a reference 2-DE gel for the soluble protein fraction. Approximately 1000 protein spots were excised from a colloidal Coomassie-stained gel (pH 4-7), analyzed by MALDI-MS and identified by PMF. The non-redundant data set contained 626 distinct protein spots, corresponding to 558 different genes. The identified proteins were classified into role categories according to their predicted functions. The experimentally determined and the theoretically predicted proteomes were compared. Proteins, which were most abundant in 2-DE gels and the coding genes of which were also predicted to be highly expressed, could be linked mainly to housekeeping functions in glycolysis, tricarboxic acid cycle, amino acid biosynthesis, protein quality control and translation. Absence of predictable signal peptides indicated a localization of these proteins in the intracellular compartment, the pirellulosome. Among the identified proteins, 146 contained a predicted signal peptide suggesting their translocation. Some proteins were detected in more than one spot on the gel, indicating post-translational modification. In addition to identifying proteins present in the published sequence database for R. baltica, an alternative approach was used, in which the mass spectrometric data was searched against a maximal ORF set, allowing the identification of four previously unpredicted ORFs. The 2-DE reference map presented here will serve as framework for further experiments to study differential gene expression of R. baltica in response to external stimuli or cellular development and compartmentalization.

The transcriptional regulator pool of the marine bacterium Rhodopirellula baltica SH 1T as revealed by whole genome comparisons.

Rhodopirellula baltica (strain SH 1T) is a free-living marine representative of the phylogenetically independent and environmentally relevant phylum Planctomycetes. Little is known about the regulatory strategies of free-living bacteria with large (7.15 Mb) genomes. Therefore, a consistent, quantitative and qualitative description was produced by comparing R. baltica's transcriptional regulator pool with that of 123 publicly available bacterial genomes. The overall results are congruous with earlier observations that in Bacteria, the proportion of genes encoding transcriptional regulators generally increases with genome size. However, R. baltica distinctly stands out from this trend with only 2.4% (174) of all genes predicted to encode transcriptional regulators. The qualitative investigation of R. baltica's transcriptional regulators revealed a clear shift towards high numbers of two-component systems (66) as well as high numbers of sigma factors (49), with more than 76% (37) belonging to the extra-cytoplasmic function subfamily of sigma-70. Only one predicted sigma factor showed a relatively close phylogenetic relationship to that of another bacterium, the sigma factor SigZ of Bacillus subtilis. In summary, analysis of the R. baltica genome revealed disparate regulatory mechanisms and a clear bias towards direct environmental sensing. This strategy might provide a selective advantage for organisms living in habitats with frequently changing environmental conditions.

TETRA: a web-service and a stand-alone program for the analysis and comparison of tetranucleotide usage patterns in DNA sequences.

BACKGROUND: In the emerging field of environmental genomics, direct cloning and sequencing of genomic fragments from complex microbial communities has proven to be a valuable source of new enzymes, expanding the knowledge of basic biological processes. The central problem of this so called metagenome-approach is that the cloned fragments often lack suitable phylogenetic marker genes, rendering the identification of clones that are likely to originate from the same genome difficult or impossible. In such cases, the analysis of intrinsic DNA-signatures like tetranucleotide frequencies can provide valuable hints on fragment affiliation. With this application in mind, the TETRA web-service and the TETRA stand-alone program have been developed, both of which automate the task of comparative tetranucleotide frequency analysis. AVAILABILITY: http://www.megx.net/tetra. RESULTS: TETRA provides a statistical analysis of tetranucleotide usage patterns in genomic fragments, either via a web-service or a stand-alone program. With respect to discriminatory power, such an analysis outperforms the assignment of genomic fragments based on the (G+C)-content, which is a widely-used sequence-based measure for assessing fragment relatedness. While the web-service is restricted to the calculation of correlation coefficients between tetranucleotide usage patterns of submitted DNA sequences, the stand-alone program generates a much more detailed output, comprising all raw data and graphical plots. The stand-alone program is controlled via a graphical user interface and can batch-process a multitude of sequences. Furthermore, it comes with pre-computed tetranucleotide usage patterns for 166 prokaryote chromosomes, providing a useful reference dataset and source for data-mining. CONCLUSIONS: Up to now, the analysis of skewed oligonucleotide distributions within DNA sequences is not a commonly used tool within metagenomics. With the TETRA web-service and stand-alone program, the method is now accessible in an easy to use manner for a broad audience. This will hopefully facilitate the interrelation of genomic fragments from metagenome libraries, ultimately leading to new insights into the genetic potentials of yet uncultured microorganisms.