Regulatory network operations in the Pathway Tools software

BMC Bioinformatics Regulatory network operations in the Pathway Tools software Suzanne M Paley 0 Mario Latendresse 0 Peter D Karp 0 0 Bioinformatics Research Group, SRI International 333 Ravenswood Ave , Menlo Park, CA 94025 Background: Biologists are elucidating complex collections of genetic regulatory data for multiple organisms. Software is needed for such regulatory network data. Results: The Pathway Tools software supports storage and manipulation of regulatory information through a variety of strategies. The Pathway Tools regulation ontology captures transcriptional and translational regulation, substrate-level regulation of enzyme activity, post-translational modifications, and regulatory pathways. Regulatory visualizations include a novel diagram that summarizes all regulatory influences on a gene; a transcription-unit diagram, and an interactive visualization of a full transcriptional regulatory network that can be painted with gene expression data to probe correlations between gene expression and regulatory mechanisms. We introduce a novel type of enrichment analysis that asks whether a gene-expression dataset is over-represented for known regulators. We present algorithms for ranking the degree of regulatory influence of genes, and for computing the net positive and negative regulatory influences on a gene. Conclusions: Pathway Tools provides a comprehensive environment for manipulating molecular regulatory interactions that integrates regulatory data with an organism's genome and metabolic network. Curated collections of regulatory data authored using Pathway Tools are available for Escherichia coli, Bacillus subtilis, and Shewanella oneidensis. Regulatory networks; Regulatory interactions; Regulation ontology; Bioinformatics - Background Cells have evolved multiple molecular regulatory modalities. For example, in addition to having its activity regulated directly by a ligand, an enzyme can be regulated at the point of transcription, translation or degradation. It can be sequestered or covalently modified. And all of these processes can themselves be subject to regulation. Here we report our progress in developing a comprehensive environment for capturing, interrogating, visualizing, and computing with individual regulatory interactions, and with regulatory networks. Currently this environment emphasizes prokaryotic rather than eukaryotic regulatory mechanisms. At the core of our efforts is a regulation ontology for capturing regulatory interactions in a declarative, computable fashion. A set of interactive editing tools allows curation of regulatory interactions and the molecules they regulate. We have also developed computational tools for interrogating and displaying individual regulatory interactions, and genome-scale regulatory networks. These tools have been implemented in the Pathway Tools software [1], which is a comprehensive systemsbiology software environment for management, analysis, and visualization of integrated collections of genome, pathway, and regulatory data. It supports creation, curation, dissemination and Web-publishing of organismspecific databases, called Pathway/Genome Databases (PGDBs), that integrate many types of data. It performs computational inferences, including prediction of metabolic pathways, prediction of metabolic pathway hole fillers, and prediction of operons. The software also supports the development of metabolic-flux models using flux-balance analysis [2]. All of the software and data features described in this paper are available in version 16.0 of the Pathway Tools software, with the exception of the tool described in Section Inferring regulatory influences on a gene, which currently exists as a research prototype only. Because this paper attempts to summarize all the regulation-related features in Pathway Tools, it includes some components that have been part of the software for some time. Table 1 highlights those features that are new since [1]. In addition, the amount of regulatory data represented in EcoCyc, BsubCyc and other PGDBs has increased substantially. An ontology of regulatory interactions The Pathway Tools schema (ontology) organizes biological information in a structured fashion, so that data can be made readily accessible for computational analysis. The ontology is designed to enable high-fidelity representation of regulatory relationships. It is also designed to represent incomplete information (e.g., we might know that a given transcription factor controls all the genes within an operon without knowing the location of the promoter for that operon). Currently, the ontology is qualitative: it does not capture quantitative information about regulation. The Pathway Tools schema is organized into a class hierarchy. Each class has a set of slots that define the attributes and relationships of instances of those classes. Classes inherit slots from their parent classes. Most forms of regulation are collected under the class Regulation, which represents a single molecular regulatory interaction. The Regulation class is a root class in the ontology, that is, it has no parents. Figure 1 shows the tree of subclasses under the Regulation class. The Regulation class defines several relationship slots that are inherited by all of its subclasses and Table 1 Major new features Regulation-related features or capabilities described in this paper that are new in Pathway Tools since the last major Pathway Tools paper [1]. instances. The slot Regulator specifies the regulator object in the regulatory interaction (such as a protein or a small molecule). The slot Regulated-Entity specifies the object whose activity is being regulated (such as a gene, a transcription unit (TU) a, a reaction, or a catalysis object). The slot Mode indicates whether the regulation is positive (activating), negative (inhibitory) or unknown. Subclasses of the Regulation class define additional slots specific to those types of regulatory interactions. A few of the major subclasses are described below. Regulation of Enzymatic Activity: This class defines substrate-level modulation of an enzyme. Its Mechanism slot indicates whether regulation is allosteric, competitive, etc. Because many purely in vitro activators and inhibitors are reported in the literature, an additional slot indicates whether or not the regulation is physiologically relevant in vivo. Transcription Factor Binding: This class represents the binding of a regulator to a DNA binding site in order to regulate the binding of RNA polymerase to a promoter and subsequent transcription. The regulator is the transcription factor when the ligand that activates or deactivates the transcription factor is known, that information is indicated by specifying as the regulator the database object representing the appropriate chemically modified form of the transcription factor. An additional slot, Associated-Binding-Site, provides a link to the binding site. The regulated e (...truncated)