The Molecular Biology Database Collection: an updated compilation of biological database resources

The Molecular Biology Database Collection is an online resource listing key databases of value to the biological community. This Collection is intended to bring fellow scientists’ attention to high-quality databases that are available throughout the world, rather than just be a lengthy listing of all available databases. As such, this up-to-date listing is intended to serve as the initial point from which to find specialized databases that may be of use in biological research. The databases included in this Collection provide new value to the underlying data by virtue of curation, new data connections or other innovative approaches. Short, searchable summaries of each of the databases included in the Collection are available through the Nucleic Acids Research Web site, at http://www.nar.oupjournals.org.

Detecting inconsistency in biological molecular databases using ontologies

The rapid growth of life science databases demands the fusion of knowledge from heterogeneous databases to answer complex biological questions. The discrepancies in nomenclature, various schemas and incompatible formats of biological databases, however, result in a significant lack of interoperability among databases. Therefore, data preparation is a key prerequisite for biological database mining. Integrating diverse biological molecular databases is an essential action to cope with the heterogeneity of biological databases and guarantee efficient data mining. However, the inconsistency in biological databases is a key issue for data integration. This paper proposes a framework to detect the inconsistency in biological databases using ontologies. A numeric estimate is provided to measure the inconsistency and identify those biological databases that are appropriate for further mining applications. This aids in enhancing the quality of databases and guaranteeing accurate and efficient mining of biological databases.

GOBASE: the organelle genome database

GOBASE (http://megasun.bch.umontreal.ca/gobase/) is a network-accessible biological database, which is unique in bringing together diverse biological data on organelles with taxonomically broad coverage, and in furnishing data that have been exhaustively verified and completed by experts. So far, we have focused on mitochondrial data: GOBASE contains all published nucleotide and protein sequences encoded by mitochondrial genomes, selected RNA secondary structures of mitochondria-encoded molecules, genetic maps of completely sequenced genomes, taxonomic information for all species whose sequences are present in the database and organismal descriptions of key protistan eukaryotes. All of these data have been integrated and organized in a formal database structure to allow sophisticated biological queries using terms that are inherent in biological concepts. Most importantly, data have been validated, completed, corrected and standardized, a prerequisite of meaningful analysis. In addition, where critical data are lacking, such as genetic maps and RNA secondary structures, they are generated by the GOBASE team and collaborators, and added to the database. The database is implemented in a relational database management system, but features an object-oriented view of the biological data through a Web/Genera-generated World Wide Web interface. Finally, we have developed software for database curation (i.e. data updates, validation and correction), which will be described in some detail in this paper.

Identification de nouveaux substrats des kinases Erk1/2 par une approche bio-informatique, pharmacologique et phosphoprotéomique

La phosphorylation est une modification post-traductionnelle omniprésente des protéines Cette modification est ajoutée et enlevée par l’activité enzymatique respective des protéines kinases et phosphatases. Les kinases Erk1/2 sont au cœur d’une voie de signalisation importante qui régule l’activité de protéines impliquées dans la traduction, le cycle cellulaire, le réarrangement du cytosquelette et la transcription. Ces kinases sont aussi impliquées dans le développement de l’organisme, le métabolisme du glucose, la réponse immunitaire et la mémoire. Différentes pathologies humaines comme le diabète, les maladies cardiovasculaires et principalement le cancer, sont associées à une perturbation de la phosphorylation sur les différents acteurs de cette voie. Considérant l’importance biologique et clinique de ces deux kinases, connaître l’étendue de leur activité enzymatique pourrait mener au développement de nouvelles thérapies pharmacologiques. Dans ce contexte, l’objectif principal de cette thèse était de mesurer l’influence de cette voie sur le phosphoprotéome et de découvrir de nouveaux substrats des kinases Erk1/2. Une étude phosphoprotéomique de cinétique d’inhibition pharmacologique de la voie de signalisation Erk1/2 a alors été entreprise. Le succès de cette étude était basé sur trois technologies clés, soit l’enrichissement des phosphopeptides avec le dioxyde de titane, la spectrométrie de masse haut débit et haute résolution, et le développement d’une plateforme bio-informatique nommée ProteoConnections. Cette plateforme permet d’organiser les données de protéomique, évaluer leur qualité, indiquer les changements d’abondance et accélérer l’interprétation des données. Une fonctionnalité distinctive de ProteoConnections est l’annotation des sites phosphorylés identifiés (kinases, domaines, structures, conservation, interactions protéiques phospho-dépendantes). Ces informations ont été essentielles à l’analyse des 9615 sites phosphorylés sur les 2108 protéines identifiées dans cette étude, soit le plus large ensemble rapporté chez le rat jusqu’à ce jour. L’analyse des domaines protéiques a révélé que les domaines impliqués dans les interactions avec les protéines, les acides nucléiques et les autres molécules sont les plus fréquemment phosphorylés et que les sites sont stratégiquement localisés pour affecter les interactions. Un algorithme a été implémenté pour trouver les substrats potentiels des kinases Erk1/2 à partir des sites identifiés selon leur motif de phosphorylation, leur cinétique de stimulation au sérum et l’inhibition pharmacologique de Mek1/2. Une liste de 157 substrats potentiels des kinases Erk1/2 a ainsi été obtenue. Parmi les substrats identifiés, douze ont déjà été rapportés et plusieurs autres ont des fonctions associées aux substrats déjà connus. Six substrats (Ddx47, Hmg20a, Junb, Map2k2, Numa1, Rras2) ont été confirmés par un essai kinase in vitro avec Erk1. Nos expériences d’immunofluorescence ont démontré que la phosphorylation de Hmg20a sur la sérine 105 par Erk1/2 affecte la localisation nucléocytoplasmique de cette protéine. Finalement, les phosphopeptides isomériques positionnels, soit des peptides avec la même séquence d’acides aminés mais phosphorylés à différentes positions, ont été étudiés avec deux nouveaux algorithmes. Cette étude a permis de déterminer leur fréquence dans un extrait enrichi en phosphopeptides et d’évaluer leur séparation par chromatographie liquide en phase inverse. Une stratégie analytique employant un des algorithmes a été développée pour réaliser une analyse de spectrométrie de masse ciblée afin de découvrir les isomères ayant été manqués par la méthode d’analyse conventionnelle.

Baseline comorbidities in a population-bases cohort of rheumatoid arthritis patients receiving biological therapy: data from the Australian Rheumatology Association database

Aims: To describe the baseline characteristics of an Australian population-based cohort of rheumatoid arthritis (RA) patients commencing biological therapy.

Methods: Descriptive analysis from the Australian Rheumatology Association Database (ARAD).

Results: Up to October 2006, there were 681 RA patients taking biologics enrolled in ARAD. Baseline data were available for 624 (72% female, mean (SD) age 57.0 (12.5) years). Of these, 59.5% reported at least one comorbid condition, most commonly hypertension (35.7%) and osteoporosis (30.4%); 61 (9.8%) had a history of malignancy (35 nonmelanoma skin, 5 breast, 4 bowel, 5 cervix, 3 melanoma, 3 prostate and 1 each of lip, lung, myeloma, testis, uterus, vagina). Self-reported infections within the previous 6 months were common (71.5%).

Conclusions: History of comorbidities, including recent infections, is common among Australian RA patients commencing biologics, and 10% have a history of malignancy. This may impact future evaluations of health outcomes among this population, including attribution of adverse events of biologic therapy.

GlycoSuiteDB: a new curated relational database of glycoprotein glycan structures and their biological sources

GlycoSuiteDB is a relational database that curates information from the scientific literature on glyco­protein derived glycan structures, their biological sources, the references in which the glycan was described and the methods used to determine the glycan structure. To date, the database includes most published O-linked oligosaccharides from the last 50 years and most N-linked oligosaccharides that were published in the 1990s. For each structure, information is available concerning the glycan type, linkage and anomeric configuration, mass and composition. Detailed information is also provided on native and recombinant sources, including tissue and/or cell type, cell line, strain and disease state. Where known, the proteins to which the glycan structures are attached are reported, and cross-references to the SWISS-PROT/TrEMBL protein sequence databases are given if applicable. The GlycoSuiteDB annotations include literature references which are linked to PubMed, and detailed information on the methods used to determine each glycan structure are noted to help the user assess the quality of the structural assignment. GlycoSuiteDB has a user-friendly web interface which allows the researcher to query the database using mono­isotopic or average mass, monosaccharide composition, glycosylation linkages (e.g. N- or O-linked), reducing terminal sugar, attached protein, taxonomy, tissue or cell type and GlycoSuiteDB accession number. Advanced queries using combinations of these parameters are also possible. GlycoSuiteDB can be accessed on the web at http://www.glycosuite.com.

A new database compilation of whole-rock chemical and geochronological data of igneous rocks in Queensland : a new resource for HDR geothermal resource exploration

The Geothermal industry in Australia and Queensland is in its infancy and for hot dry rock (HDR) geothermal energy, it is very much in the target identification and resource definition stages. As a key effort to assist the geothermal industry and exploration for HDR in Queensland, we are developing a comprehensive and new integrated geochemical and geochronological database on igneous rocks. To date, around 18,000 igneous rocks have been analysed across Queensland for chemical and/or age information. However, these data currently reside in a number of disparate datasets (e.g., Ozchron, Champion et al., 2007, Geological Survey of Queensland, journal publications, and unpublished university theses). The goal of this project is to collate and integrate these data on Queensland igneous rocks to improve our understanding of high heat producing granites in Queensland, in terms of their distribution (particularly in the subsurface), dimensions, ages, and controlling factors in their genesis.

The fossil calibration database - A new resource for divergence dating

Fossils provide the principal basis for temporal calibrations, which are critical to the accuracy of divergence dating analyses. Translating fossil data into minimum and maximum bounds for calibrations is the most important, and often least appreciated, step of divergence dating. Properly justified calibrations require the synthesis of phylogenetic, paleontological, and geological evidence and can be difficult for non-specialists to formulate. The dynamic nature of the fossil record (e.g., new discoveries, taxonomic revisions, updates of global or local stratigraphy) requires that calibration data be updated continually lest they become obsolete. Here, we announce the Fossil Calibration Database (http://fossilcalibrations.org), a new open-access resource providing vetted fossil calibrations to the scientific community. Calibrations accessioned into this database are based on individual fossil specimens and follow best practices for phylogenetic justification and geochronological constraint. The associated Fossil Calibration Series, a calibration-themed publication series at Palaeontologia Electronica, will serve as one key pipeline for peer-reviewed calibrations to enter the database.

Development of a New Zealand database of plant virus and virus-like organisms.

The recent 8th Australasian plant virology workshop in Rotorua, New Zealand, discussed the development of a New Zealand database of plant virus and virus-like organisms. Key points of discussion included: (i) the purpose of such a database; (ii) who would benefit from the information in a database; (iii) the scope of a database and its associated collections; (iv) database information and format; and (v) potential funding of such a database. From the workshop and further research, we conclude that the preservation and verification of specimens within the collections and the development of a New Zealand database of plant virus and virus-like organisms is essential. Such a collection will help to fulfil statutory requirements in New Zealand and assist in fulfilling international obligations under the International Plant Protection Convention. Sustaining such a database will assist New Zealand virologists and statutory bodies to undertake scientifically sound research. Establishing reliable records and an interactive database will help to ensure accurate and timely diagnoses of diseases caused by plant viruses and virus-like organisms. Detection of new incursions and their diagnosis will be further enhanced by the use of such reference collections and their associated database. Connecting and associating this information to similar overseas databases would assist international collaborations and allow access to the latest taxonomic and diagnostic resources. Associated scientists working in the areas of plant breeding, export phytosanitary assurance and in the area of the conservation estate would also benefit from access to verified specimens of plant viruses and virus-like organisms. We conclude that funding of a New Zealand database of virus and virus-like organisms and its associated collections should be based partly on Crown funds, as it is a nationally significant biological resource.

DoSA: Database of Structural Alignments

Protein structure alignment is a crucial step in protein structure-function analysis. Despite the advances in protein structure alignment algorithms, some of the local conformationally similar regions are mislabeled as structurally variable regions (SVRs). These regions are not well superimposed because of differences in their spatial orientations. The Database of Structural Alignments (DoSA) addresses this gap in identification of local structural similarities obscured in global protein structural alignments by realigning SVRs using an algorithm based on protein blocks. A set of protein blocks is a structural alphabet that abstracts protein structures into 16 unique local structural motifs. DoSA provides unique information about 159 780 conformationally similar and 56 140 conformationally dissimilar SVRs in 74 705 pairwise structural alignments of homologous proteins. The information provided on conformationally similar and dissimilar SVRs can be helpful to model loop regions. It is also conceivable that conformationally similar SVRs with conserved residues could potentially contribute toward functional integrity of homologues, and hence identifying such SVRs could be helpful in understanding the structural basis of protein function.

Overview of FEED, the feeding experiments end-user database.

The Feeding Experiments End-user Database (FEED) is a research tool developed by the Mammalian Feeding Working Group at the National Evolutionary Synthesis Center that permits synthetic, evolutionary analyses of the physiology of mammalian feeding. The tasks of the Working Group are to compile physiologic data sets into a uniform digital format stored at a central source, develop a standardized terminology for describing and organizing the data, and carry out a set of novel analyses using FEED. FEED contains raw physiologic data linked to extensive metadata. It serves as an archive for a large number of existing data sets and a repository for future data sets. The metadata are stored as text and images that describe experimental protocols, research subjects, and anatomical information. The metadata incorporate controlled vocabularies to allow consistent use of the terms used to describe and organize the physiologic data. The planned analyses address long-standing questions concerning the phylogenetic distribution of phenotypes involving muscle anatomy and feeding physiology among mammals, the presence and nature of motor pattern conservation in the mammalian feeding muscles, and the extent to which suckling constrains the evolution of feeding behavior in adult mammals. We expect FEED to be a growing digital archive that will facilitate new research into understanding the evolution of feeding anatomy.

Statistical analysis of crystallization database links protein physico-chemical features with crystallization mechanisms.

X-ray crystallography is the predominant method for obtaining atomic-scale information about biological macromolecules. Despite the success of the technique, obtaining well diffracting crystals still critically limits going from protein to structure. In practice, the crystallization process proceeds through knowledge-informed empiricism. Better physico-chemical understanding remains elusive because of the large number of variables involved, hence little guidance is available to systematically identify solution conditions that promote crystallization. To help determine relationships between macromolecular properties and their crystallization propensity, we have trained statistical models on samples for 182 proteins supplied by the Northeast Structural Genomics consortium. Gaussian processes, which capture trends beyond the reach of linear statistical models, distinguish between two main physico-chemical mechanisms driving crystallization. One is characterized by low levels of side chain entropy and has been extensively reported in the literature. The other identifies specific electrostatic interactions not previously described in the crystallization context. Because evidence for two distinct mechanisms can be gleaned both from crystal contacts and from solution conditions leading to successful crystallization, the model offers future avenues for optimizing crystallization screens based on partial structural information. The availability of crystallization data coupled with structural outcomes analyzed through state-of-the-art statistical models may thus guide macromolecular crystallization toward a more rational basis.