Dataset Information

Bacterial Virus Ontology; Coordinating across Databases.

ABSTRACT: Bacterial viruses, also called bacteriophages, display a great genetic diversity and utilize unique processes for infecting and reproducing within a host cell. All these processes were investigated and indexed in the ViralZone knowledge base. To facilitate standardizing data, a simple ontology of viral life-cycle terms was developed to provide a common vocabulary for annotating data sets. New terminology was developed to address unique viral replication cycle processes, and existing terminology was modified and adapted. Classically, the viral life-cycle is described by schematic pictures. Using this ontology, it can be represented by a combination of successive events: entry, latency, transcription/replication, host-virus interactions and virus release. Each of these parts is broken down into discrete steps. For example enterobacteria phage lambda entry is broken down in: viral attachment to host adhesion receptor, viral attachment to host entry receptor, viral genome ejection and viral genome circularization. To demonstrate the utility of a standard ontology for virus biology, this work was completed by annotating virus data in the ViralZone, UniProtKB and Gene Ontology databases.

SUBMITTER: Hulo C

PROVIDER: S-EPMC5490803 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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Publications

Bacterial Virus Ontology; Coordinating across Databases.

Hulo Chantal C Masson Patrick P Toussaint Ariane A Osumi-Sutherland David D de Castro Edouard E Auchincloss Andrea H AH Poux Sylvain S Bougueleret Lydie L Xenarios Ioannis I Le Mercier Philippe P

Viruses 20170523 6

Bacterial viruses, also called bacteriophages, display a great genetic diversity and utilize unique processes for infecting and reproducing within a host cell. All these processes were investigated and indexed in the ViralZone knowledge base. To facilitate standardizing data, a simple ontology of viral life-cycle terms was developed to provide a common vocabulary for annotating data sets. New terminology was developed to address unique viral replication cycle processes, and existing terminology ...[more]

PMID: 28545254

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Project description:The ability to query many independent biological databases using a common ontology-based semantic model would facilitate deeper integration and more effective utilization of these diverse and rapidly growing resources. Despite ongoing work moving toward shared data formats and linked identifiers, significant problems persist in semantic data integration in order to establish shared identity and shared meaning across heterogeneous biomedical data sources.We present five processes for semantic data integration that, when applied collectively, solve seven key problems. These processes include making explicit the differences between biomedical concepts and database records, aggregating sets of identifiers denoting the same biomedical concepts across data sources, and using declaratively represented forward-chaining rules to take information that is variably represented in source databases and integrating it into a consistent biomedical representation. We demonstrate these processes and solutions by presenting KaBOB (the Knowledge Base Of Biomedicine), a knowledge base of semantically integrated data from 18 prominent biomedical databases using common representations grounded in Open Biomedical Ontologies. An instance of KaBOB with data about humans and seven major model organisms can be built using on the order of 500 million RDF triples. All source code for building KaBOB is available under an open-source license.KaBOB is an integrated knowledge base of biomedical data representationally based in prominent, actively maintained Open Biomedical Ontologies, thus enabling queries of the underlying data in terms of biomedical concepts (e.g., genes and gene products, interactions and processes) rather than features of source-specific data schemas or file formats. KaBOB resolves many of the issues that routinely plague biomedical researchers intending to work with data from multiple data sources and provides a platform for ongoing data integration and development and for formal reasoning over a wealth of integrated biomedical data.

Project description:BackgroundHigh-throughput molecular biology provides new data at an incredible rate, so that the increase in the size of biological databanks is enormous and very rapid. This scenario generates severe problems not only at indexing time, where suitable algorithmic techniques for data indexing and retrieval are required, but also at query time, since a user query may produce such a large set of results that their browsing and "understanding" becomes humanly impractical. This problem is well known to the Web community, where a new generation of Web search engines is being developed, like Vivisimo. These tools organize on-the-fly the results of a user query in a hierarchy of labeled folders that ease their browsing and knowledge extraction. We investigate this approach on biological data, and propose the so called The BioPrompt-boxsoftware system which deploys ontology-driven clustering strategies for making the searching process of biologists more efficient and effective.ResultsThe BioPrompt-box (Bpb) defines a document as a biological sequence plus its associated meta-data taken from the underneath databank--like references to ontologies or to external databanks, and plain texts as comments of researchers and (title, abstracts or even body of) papers. Bpboffers several tools to customize the search and the clustering process over its indexed documents. The user can search a set of keywords within a specific field of the document schema, or can execute Blastto find documents relative to homologue sequences. In both cases the search task returns a set of documents (hits) which constitute the answer to the user query. Since the number of hits may be large, Bpbclusters them into groups of homogenous content, organized as a hierarchy of labeled clusters. The user can actually choose among several ontology-based hierarchical clustering strategies, each offering a different "view" of the returned hits. Bpbcomputes these views by exploiting the meta-data present within the retrieved documents such as the references to Gene Ontology, the taxonomy lineage, the organism and the keywords. Of course, the approach is flexible enough to leave room for future additions of other meta-information. The ultimate goal of the clustering process is to provide the user with several different readings of the (maybe numerous) query results and show possible hidden correlations among them, thus improving their browsing and understanding.ConclusionBpb is a powerful search engine that makes it very easy to perform complex queries over the indexed databanks (currently only UNIPROT is considered). The ontology-based clustering approach is efficient and effective, and could thus be applied successfully to larger databanks, like GenBank or EMBL.

Project description:UnlabelledCell division in bacteria is driven by a cytoskeletal ring structure, the Z ring, composed of polymers of the tubulin-like protein FtsZ. Z-ring formation must be tightly regulated to ensure faithful cell division, and several mechanisms that influence the positioning and timing of Z-ring assembly have been described. Another important but as yet poorly understood aspect of cell division regulation is the need to coordinate division with cell growth and nutrient availability. In this study, we demonstrated for the first time that cell division is intimately linked to central carbon metabolism in the model Gram-positive bacterium Bacillus subtilis. We showed that a deletion of the gene encoding pyruvate kinase (pyk), which produces pyruvate in the final reaction of glycolysis, rescues the assembly defect of a temperature-sensitive ftsZ mutant and has significant effects on Z-ring formation in wild-type B. subtilis cells. Addition of exogenous pyruvate restores normal division in the absence of the pyruvate kinase enzyme, implicating pyruvate as a key metabolite in the coordination of bacterial growth and division. Our results support a model in which pyruvate levels are coupled to Z-ring assembly via an enzyme that actually metabolizes pyruvate, the E1? subunit of pyruvate dehydrogenase. We have shown that this protein localizes over the nucleoid in a pyruvate-dependent manner and may stimulate more efficient Z-ring formation at the cell center under nutrient-rich conditions, when cells must divide more frequently.ImportanceHow bacteria coordinate cell cycle processes with nutrient availability and growth is a fundamental yet unresolved question in microbiology. Recent breakthroughs have revealed that nutritional information can be transmitted directly from metabolic pathways to the cell cycle machinery and that this can serve as a mechanism for fine-tuning cell cycle processes in response to changes in environmental conditions. Here we identified a novel link between glycolysis and cell division in Bacillus subtilis. We showed that pyruvate, the final product of glycolysis, plays an important role in maintaining normal division. Nutrient-dependent changes in pyruvate levels affect the function of the cell division protein FtsZ, most likely by modifying the activity of an enzyme that metabolizes pyruvate, namely, pyruvate dehydrogenase E1?. Ultimately this system may help to coordinate bacterial division with nutritional conditions to ensure the survival of newborn cells.

Dataset Information

Bacterial Virus Ontology; Coordinating across Databases.

Publications

Bacterial Virus Ontology; Coordinating across Databases.

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