Synergy between suppressor of Hairless and Notch in regulation of Enhancer of split m gamma and m delta expression.

The Notch signaling pathway is known to regulate cell fate decisions in a variety of organisms from worms to humans. Although several components of the pathway have been characterized, the actual mechanism and molecular results of signaling remain elusive. We have examined the role of the Notch signaling pathway in the transcriptional regulation of two Drosophila Enhancer of split [E(spl)] genes, whose gene products have been shown to be downstream players in the pathway. Using a reporter assay system in Drosophila tissue culture cells, we have observed a significant induction of E(spl) m gamma and m delta expression after cotransfection with activated Notch. Characterization of the 5' regulatory regions of these two genes led to the identification of a number of target sites for the Suppressor of Hairless [Su(H)] protein, a transcription factor activated by Notch signaling. We show that Notch-inducible expression of E(spl) m gamma and m delta both in cultured cells and in vivo is dependent on functional Su(H). Although overexpression of Su(H) augments the level of induction of the reporter genes by activated Notch, Su(H) alone is insufficient to produce high levels of transcriptional activation. Despite the synergy observed between activated Notch and Su(H), the former affects neither the nuclear localization nor the DNA binding activity of the latter.

The Human Brain Project: neuroinformatics tools for integrating, searching and modeling multidisciplinary neuroscience data.

What is neuroinformatics? What is the Human Brain Project? Why should you care? Supported by a consortium of US funding agencies, the Human Brain Project aims to bring to the analysis of brain function the same advantages of Internet-accessible databases and database tools that have been crucial to the development of molecular biology and the Human Genome Project. The much greater complexity of neural data, however, makes this a far more challenging task. As a pilot project in this new initiative, we review some of the progress that has been made and indicate some of the problems, challenges and opportunities that lie ahead.

Regulation of expression of the chicken ovalbumin gene: interactions between steroid hormones and second messenger systems.

The chicken ovalbumin gene is subject to multihormonal regulation. Maximal expression of it requires not only the synergistic effects of estrogen and corticosterone, but also the permissive effects of insulin. In addition to effects on transcription, the stability of its message is greatly enhanced by estrogen. Furthermore, two signal transduction pathways involving protein kinases have been implicated in the regulation of the ovalbumin gene. To better define the role of second messengers on expression of the ovalbumin gene, the effects of the protein kinase-C (PKC) and the cAMP-dependent protein kinase (PKA) pathways on the endogenous levels of ovalbumin mRNA and the transcription of an ovalbumin fusion gene were investigated. Primary cultures of oviduct cells were treated with phorbol 12-myristilate 13-acetate (an activator of PKC) or with forskolin and 3-isobutyl-1-methylxanthine (an activator of PKA) alone, activators plus estrogen and corticosterone, or activators plus both steroids and insulin. The results indicate that phorbol 12-myristilate 13-acetate causes a dramatic destabilization of ovalbumin message, resulting in a reduction in ovalbumin mRNA levels. In contrast, the activators of the PKA system can substitute for insulin and, thereby, increase expression of the ovalbumin gene synergistically with the steroids. The effect of the activators of the PKA system is at the level of transcription. Thus, in chicken oviduct cell cultures, the PKA and PKC signal transduction pathways act in opposing ways to modulate the steroid-induced expression of the ovalbumin gene.

Organization of heterogeneous scientific data using the EAV/CR representation.

Entity-attribute-value (EAV) representation is a means of organizing highly heterogeneous data using a relatively simple physical database schema. EAV representation is widely used in the medical domain, most notably in the storage of data related to clinical patient records. Its potential strengths suggest its use in other biomedical areas, in particular research databases whose schemas are complex as well as constantly changing to reflect evolving knowledge in rapidly advancing scientific domains. When deployed for such purposes, the basic EAV representation needs to be augmented significantly to handle the modeling of complex objects (classes) as well as to manage interobject relationships. The authors refer to their modification of the basic EAV paradigm as EAV/CR (EAV with classes and relationships). They describe EAV/CR representation with examples from two biomedical databases that use it.

Conserved sequence motifs of olfactory receptor-like proteins may participate in upstream and downstream signal transduction.

Olfactory receptor-like proteins (ORLs) are seven transmembrane domain G protein-coupled receptors. We hypothesize that, in contrast with the hypervariable regions that may interact with a variety of odor ligands, the external and internal segments of the ORLs contain conserved regions that may interact with conserved olfactory binding proteins or direct axon guidance, and with G proteins, respectively. To test this hypothesis, a comprehensive analysis using the multiple expectation maximization for motif elicitation discovery tool was performed in all the full-length ORL clones deposited in the public section of the olfactory receptor database. Ten motifs have been identified that are present in all the olfactory receptors, in the same order, and are not present in other G protein-coupled receptors. These motifs are concentrated either in the extracellular-most or the intracellular-most parts of the receptors. The generality of these motifs was verified by their existence in the partial ORLs and 28 newly identified human receptors. The existence and localization of these motifs, suggest that they may be involved in the interactions of the receptors with their upstream and downstream signaling partners. In addition, the motifs present an additional to overall homology criterion for ORL family definition.

Olfactory receptor database: a sensory chemoreceptor resource.

The Olfactory Receptor Database (ORDB) is a WWW-accessible database that has been expanded from an olfactory receptor resource to a chemoreceptor resource. It stores data on six classes of G-protein-coupled sensory chemoreceptors: (i) olfactory receptor-like proteins, (ii) vomeronasal receptors, (iii) insect olfactory receptors, (iv) worm chemo-receptors, (v) taste papilla receptors and (vi) fungal pheromone receptors. A complementary database of the ligands of these receptors (OdorDB) has been constructed and is publicly available in a pilot mode. The database schema of ORDB has been changed from traditional relational to EAV/CR (Entity-Attribute-Value with Classes and Relationships), which allows the interoperability of ORDB with other related databases as well as the creation of intra-database associations among objects. This inter-operability facilitates users to follow information from odor molecule binding to its putative receptor, to the properties of the neuron expressing the receptor, to a computational model of activity of olfactory bulb neurons. In addition, tools and resources have been added allowing users to access interactive phylogenetic trees and alignments of sensory chemoreceptors. ORDB is available via the WWW at http://ycmi.med. yale.edu/senselab/ordb/

Neuronal database integration: the Senselab EAV data model.

We discuss an approach towards integrating heterogeneous nervous system data using an augmented Entity-Attribute-Value (EAV) schema design. This approach, widely used in implementing electronic patient record systems (EPRSs), allows the physical schema of the database to be relatively immune to changes in domain knowledge. This is because new kinds of facts are added as data (or as metadata) rather than hard-coded as the names of newly created tables or columns. Because the domain knowledge is stored as metadata, a framework developed in one scientific domain can be ported to another with only modest revision. We describe our progress in creating a code framework that handles browsing and hyperlinking of the different kinds of data.

Olfactory Receptor Database: a database of the largest eukaryotic gene family.

The Olfactory Receptor Database (ORDB) is a WWW-accessible database that stores data on Olfactory Receptor-like molecules (ORs) and has been open to the public since June 1996. It contains a public and a private area. The public area includes published DNA and protein sequence data for ORs, links to OR models and data on their expression, chromosomal localization and source organism, as well as (i) links to bibliography through PubMed and (ii) interactive WWW-based tools, such as BLAST homology searching. The private area functions as a service to laboratories that are actively cloning receptors. Source laboratories enter the sequences of the receptor clones they have characterized to the private database and can search for identical or near identical OR sequences in both public and private databases. If another laboratory has cloned and deposited an identical or closely matching sequence there are means for communication between the laboratories to help avoid duplication of work. ORDB is available via the WWW at http://crepe.med.yale.edu/ORDB/HTML

Olfactory receptor database (ORDB): a resource for sharing and analyzing published and unpublished data.

An olfactory receptor database (ORDB) is being developed to facilitate analysis of this large gene family. ORDB currently contains over 400 olfactory receptor sequences and related information, and is available via the World Wide Web. We plan to incorporate functional data, structural models, spatial localization and other categories of information, toward an integrated model of olfactory receptor function.