Greg Butler

Snapshot of the Eukaryotic Gene Expression in Muskoxen Rumen—A Metatranscriptomic Approach

Background Herbivores rely on digestive tract lignocellulolytic microorganisms, including bacteria, fungi and protozoa, to derive energy and carbon from plant cell wall polysaccharides. Culture independent metagenomic studies have been used to reveal the genetic content of the bacterial species within gut microbiomes. However, the nature of the genes encoded by eukaryotic protozoa and fungi within these environments has not been explored using metagenomic or metatranscriptomic approaches. Methodology/Principal Findings In this study, a metatranscriptomic approach was used to investigate the functional diversity of the eukaryotic microorganisms within the rumen of muskoxen (Ovibos moschatus), with a focus on plant cell wall degrading enzymes. Polyadenylated RNA (mRNA) was sequenced on the Illumina Genome Analyzer II system and 2.8 gigabases of sequences were obtained and 59129 contigs assembled. Plant cell wall degrading enzyme modules including glycoside hydrolases, carbohydrate esterases and polysaccharide lyases were identified from over 2500 contigs. These included a number of glycoside hydrolase family 6 (GH6), GH48 and swollenin modules, which have rarely been described in previous gut metagenomic studies. Conclusions/Significance The muskoxen rumen metatranscriptome demonstrates a much higher percentage of cellulase enzyme discovery and an 8.7x higher rate of total carbohydrate active enzyme discovery per gigabase of sequence than previous rumen metagenomes. This study provides a snapshot of eukaryotic gene expression in the muskoxen rumen, and identifies a number of candidate genes coding for potentially valuable lignocellulolytic enzymes.

Curation of characterized glycoside hydrolases of fungal origin.

Fungi produce a wide range of extracellular enzymes to break down plant cell walls, which are composed mainly of cellulose, lignin and hemicellulose. Among them are the glycoside hydrolases (GH), the largest and most diverse family of enzymes active on these substrates. To facilitate research and development of enzymes for the conversion of cell-wall polysaccharides into fermentable sugars, we have manually curated a comprehensive set of characterized fungal glycoside hydrolases. Characterized glycoside hydrolases were retrieved from protein and enzyme databases, as well as literature repositories. A total of 453 characterized glycoside hydrolases have been cataloged. They come from 131 different fungal species, most of which belong to the phylum Ascomycota. These enzymes represent 46 different GH activities and cover 44 of the 115 CAZy GH families. In addition to enzyme source and enzyme family, available biochemical properties such as temperature and pH optima, specific activity, kinetic parameters and substrate specificities were recorded. To simplify comparative studies, enzyme and species abbreviations have been standardized, Gene Ontology terms assigned and reference to supporting evidence provided. The annotated genes have been organized in a searchable, online database called mycoCLAP (Characterized Lignocellulose-Active Proteins of fungal origin). It is anticipated that this manually curated collection of biochemically characterized fungal proteins will be used to enhance functional annotation of novel GH genes. Database URL: http://mycoCLAP.fungalgenomics.ca/

Generation, annotation, and analysis of an extensive Aspergillus niger EST collection

BackgroundAspergillus niger, a saprophyte commonly found on decaying vegetation, is widely used and studied for industrial purposes. Despite its place as one of the most important organisms for commercial applications, the lack of available information about its genetic makeup limits research with this filamentous fungus.ResultsWe present here the analysis of 12,820 expressed sequence tags (ESTs) generated from A. niger cultured under seven different growth conditions. These ESTs identify about 5,108 genes of which 44.5% code for proteins sharing similarity (E ≤ 1e -5) with GenBank entries of known function, 38% code for proteins that only share similarity with GenBank entries of unknown function and 17.5% encode proteins that do not have a GenBank homolog. Using the Gene Ontology hierarchy, we present a first classification of the A. niger proteins encoded by these genes and compare its protein repertoire with other well-studied fungal species. We have established a searchable web-based database that includes the EST and derived contig sequences and their annotation. Details about this project and access to the annotated A. niger database are available.ConclusionThis EST collection and its annotation provide a significant resource for fundamental and applied research with A. niger. The gene set identified in this manuscript will be highly useful in the annotation of the genome sequence of A. niger, the genes described in the manuscript, especially those encoding hydrolytic enzymes will provide a valuable source for researchers interested in enzyme properties and applications.

Semantic web infrastructure for fungal enzyme biotechnologists

The FungalWeb Ontology seeks to support various data integration needs of enzyme biotechnology from inception to product roll. Serving as a knowledgebase for decision support, the conceptualization seeks to link fungal species with enzymes, enzyme substrates, enzyme classifications, enzyme modifications, enzyme related intellectual property, enzyme retail and applications. The ontology, developed in the OWL language, is the result of the integration of numerous biological database schemas, web accessible text resources and components of existing ontologies. We assess the quantity of implicit knowledge in the FungalWeb Ontology by analyzing the range of tags in the OWL files and along with other description logic (DL) computable metrics of the ontology, contrast it with other publicly available bio-ontologies. Thereafter, we demonstrate how the FungalWeb Ontology supports its broad remit required in fungal biotechnology by (i) presenting application scenarios (ii) presenting the conceptualizations of the ontological frame able to support these scenarios and (iii) suggesting semantic queries typical of a fungal enzymologist involved in product development. Recognizing the complexity of the ontology query process for the non-technical manager we introduce a simplified query tool, Ontoligent Interactive Query (OntoIQ) that allows the user to browse and build queries from a selection of query patterns and ontology content. The OntoIQ interface supports users not familiar with writing DL syntax allowing them access to the ontology with expressive description logic reasoning tools. Finally we discuss the challenges encountered during the development of semantic infrastructure for fungal enzyme biotechnologists.

Semantic text mining support for lignocellulose research

BackgroundBiofuels produced from biomass are considered to be promising sustainable alternatives to fossil fuels. The conversion of lignocellulose into fermentable sugars for biofuels production requires the use of enzyme cocktails that can efficiently and economically hydrolyze lignocellulosic biomass. As many fungi naturally break down lignocellulose, the identification and characterization of the enzymes involved is a key challenge in the research and development of biomass-derived products and fuels. One approach to meeting this challenge is to mine the rapidly-expanding repertoire of microbial genomes for enzymes with the appropriate catalytic properties.ResultsSemantic technologies, including natural language processing, ontologies, semantic Web services and Web-based collaboration tools, promise to support users in handling complex data, thereby facilitating knowledge-intensive tasks. An ongoing challenge is to select the appropriate technologies and combine them in a coherent system that brings measurable improvements to the users. We present our ongoing development of a semantic infrastructure in support of genomics-based lignocellulose research. Part of this effort is the automated curation of knowledge from information on fungal enzymes that is available in the literature and genome resources.ConclusionsWorking closely with fungal biology researchers who manually curate the existing literature, we developed ontological natural language processing pipelines integrated in a Web-based interface to assist them in two main tasks: mining the literature for relevant knowledge, and at the same time providing rich and semantically linked information.

Refactoring use case models on episodes

Use case models are widely used to capture functional requirements of a system. However, to obtain well-organized use case models is not easy. Refactoring is an approach to reorganize the internal structure of models in order to improve them or extend them in some way. This work looks at refactoring of use case models based on the information captured in episode models. We introduce 10 refactoring rules for use case refactoring in detail, including their verification of the behavior-preserving property. We also present a case study based on the automated teller machine.

The fungalweb ontology: semantic web challenges in bioinformatics and genomics

Bioinformatics and genomics cover a wide range of different data formats (i.e. annotations, pathways, structures, sequences) derived from experimental and in-silico biological analysis which are stored, used, and manipulated by scientists and machines. The volume of this data is huge and usually distributed in different locations, and often frequently being updated. FungalWeb is the first project of its kind in Canada to focus on bringing semantic web technology to genomics. It aimed to bring together available expertise in ontologies, multi-agent systems, machine learning and natural language processing to build a tailored knowledgebase and semantic systems of direct use to the scientific discovery process in the domain of fungal genomics [1].

An approach to controlling user models and personalization effects in recommender systems

Personalization nowadays is a commodity in a broad spectrum of computer systems. Examples range from online shops recommending products identified based on the users previous purchases to web search engines sorting search hits based on the user browsing history. The aim of such adaptive behavior is to help users to find relevant content easier and faster. However, there are a number of negative aspects of this behavior. Adaptive systems have been criticized for violating the usability principles of direct manipulation systems, namely controllability, predictability, transparency, and unobtrusiveness. In this paper, we propose an approach to controlling adaptive behavior in recommender systems. It allows users to get an overview of personalization effects, view the user profile that is used for personalization, and adjust the profile and personalization effects to their needs and preferences. We present this approach using an example of a personalized portal for biochemical literature, whose users are biochemists, biologists and genomicists. Also, we report on a user study evaluating the impacts of controllable personalization on the usefulness, usability, user satisfaction, transparency, and trustworthiness of personalized systems.

New Results on Deriving SDL Specifications from MSCs

We have developed an approach for the derivation of SDL specifications from MSCs. The architecture of the target system is given with the MSCs as input to the derivation algorithm. In this paper, we report on new results on this derivation and the MSC2SDL tool, which has been interfaced with a commercial tool. We report on new issues related to multiple instances of a process, multiple instances of a message from different processes, SDL process identifiers, addressing schemes as well as the MSCs implementability issue and its implementation.

Ontoligent Interactive Query Tool

Recognizing the complexity of the Description Logic-based query of 0WL-DL ontologies for the non-specialist, we introduce a query tool called Ontoligent Interactive Query (OntoIQ). This tool provides a well-organized user interface for a variety of users, from the beginner to the professional. Users can browse ontologies and build queries using query patterns and ontology content. OntoIQ translates queries automatically into the new RACER Query language (nRQL) syntax and presents them to description logic automated reasoner RACER which returns the query results. The tool includes import and export functions so that queries can be stored, shared, and re-imported by other users. Users are not required to learn the nRQL syntax. OntoIQ software is available for download at The FungalWeb website.