Data integration issues in the reconstruction of the genome-scale metabolic model of Zymomonas mobillis

Genome-scale model reconstruction represents a major tool in the field of Metabolic Engineering .This paper reports on a study about data integration issues in the process of genome- scale reconstruction of the metabolic model of the bacterium Zymomonas mobilis, a promising organism for bioethanol production. Data is retrieved from the Entrez Gene, KEGG, BioCyc and Brenda databases, and the several processes involved in data integration from these sources are described, as well as the data quality issues.Fundação para a Ciência e a Tecnologia (FCT) - POCI/BIO/60139/2004, PhD grant ref. SFRH/BD/41763/200

Concept-based query expansion for retrieving gene related publications from MEDLINE

<p>Abstract</p> <p>Background</p> <p>Advances in biotechnology and in high-throughput methods for gene analysis have contributed to an exponential increase in the number of scientific publications in these fields of study. While much of the data and results described in these articles are entered and annotated in the various existing biomedical databases, the scientific literature is still the major source of information. There is, therefore, a growing need for text mining and information retrieval tools to help researchers find the relevant articles for their study. To tackle this, several tools have been proposed to provide alternative solutions for specific user requests.</p> <p>Results</p> <p>This paper presents QuExT, a new PubMed-based document retrieval and prioritization tool that, from a given list of genes, searches for the most relevant results from the literature. QuExT follows a concept-oriented query expansion methodology to find documents containing concepts related to the genes in the user input, such as protein and pathway names. The retrieved documents are ranked according to user-definable weights assigned to each concept class. By changing these weights, users can modify the ranking of the results in order to focus on documents dealing with a specific concept. The method's performance was evaluated using data from the 2004 TREC genomics track, producing a mean average precision of 0.425, with an average of 4.8 and 31.3 relevant documents within the top 10 and 100 retrieved abstracts, respectively.</p> <p>Conclusions</p> <p>QuExT implements a concept-based query expansion scheme that leverages gene-related information available on a variety of biological resources. The main advantage of the system is to give the user control over the ranking of the results by means of a simple weighting scheme. Using this approach, researchers can effortlessly explore the literature regarding a group of genes and focus on the different aspects relating to these genes.</p

Semantic annotation of biological concepts interplaying microbial cellular responses

<p>Abstract</p> <p>Background</p> <p>Automated extraction systems have become a time saving necessity in Systems Biology. Considerable human effort is needed to model, analyse and simulate biological networks. Thus, one of the challenges posed to Biomedical Text Mining tools is that of learning to recognise a wide variety of biological concepts with different functional roles to assist in these processes.</p> <p>Results</p> <p>Here, we present a novel corpus concerning the integrated cellular responses to nutrient starvation in the model-organism <it>Escherichia coli</it>. Our corpus is a unique resource in that it annotates biomedical concepts that play a functional role in expression, regulation and metabolism. Namely, it includes annotations for genetic information carriers (genes and DNA, RNA molecules), proteins (transcription factors, enzymes and transporters), small metabolites, physiological states and laboratory techniques. The corpus consists of 130 full-text papers with a total of 59043 annotations for 3649 different biomedical concepts; the two dominant classes are <it>genes </it>(highest number of unique concepts) and <it>compounds </it>(most frequently annotated concepts), whereas other important cellular concepts such as <it>proteins </it>account for no more than 10% of the annotated concepts.</p> <p>Conclusions</p> <p>To the best of our knowledge, a corpus that details such a wide range of biological concepts has never been presented to the text mining community. The inter-annotator agreement statistics provide evidence of the importance of a consolidated background when dealing with such complex descriptions, the ambiguities naturally arising from the terminology and their impact for modelling purposes.</p> <p>Availability is granted for the full-text corpora of 130 freely accessible documents, the annotation scheme and the annotation guidelines. Also, we include a corpus of 340 abstracts.</p

The genome-scale metabolic network analysis of Zymomonas mobilis ZM4 explains physiological features and suggests ethanol and succinic acid production strategies

<p>Abstract</p> <p>Background</p> <p><it>Zymomonas mobilis </it>ZM4 is a Gram-negative bacterium that can efficiently produce ethanol from various carbon substrates, including glucose, fructose, and sucrose, <it>via </it>the Entner-Doudoroff pathway. However, systems metabolic engineering is required to further enhance its metabolic performance for industrial application. As an important step towards this goal, the genome-scale metabolic model of <it>Z. mobilis </it>is required to systematically analyze <it>in silico </it>the metabolic characteristics of this bacterium under a wide range of genotypic and environmental conditions.</p> <p>Results</p> <p>The genome-scale metabolic model of <it>Z. mobilis </it>ZM4, ZmoMBEL601, was reconstructed based on its annotated genes, literature, physiological and biochemical databases. The metabolic model comprises 579 metabolites and 601 metabolic reactions (571 biochemical conversion and 30 transport reactions), built upon extensive search of existing knowledge. Physiological features of <it>Z. mobilis </it>were then examined using constraints-based flux analysis in detail as follows. First, the physiological changes of <it>Z. mobilis </it>as it shifts from anaerobic to aerobic environments (i.e. aerobic shift) were investigated. Then the intensities of flux-sum, which is the cluster of either all ingoing or outgoing fluxes through a metabolite, and the maximum <it>in silico </it>yields of ethanol for <it>Z. mobilis </it>and <it>Escherichia coli </it>were compared and analyzed. Furthermore, the substrate utilization range of <it>Z. mobilis </it>was expanded to include pentose sugar metabolism by introducing metabolic pathways to allow <it>Z. mobilis </it>to utilize pentose sugars. Finally, double gene knock-out simulations were performed to design a strategy for efficiently producing succinic acid as another example of application of the genome-scale metabolic model of <it>Z. mobilis</it>.</p> <p>Conclusion</p> <p>The genome-scale metabolic model reconstructed in this study was able to successfully represent the metabolic characteristics of <it>Z. mobilis </it>under various conditions as validated by experiments and literature information. This reconstructed metabolic model will allow better understanding of <it>Z. mobilis </it>metabolism and consequently designing metabolic engineering strategies for various biotechnological applications.</p

Modeling a Reversed β-oxidation Cycle Into the Genome Scale Model of Zymomonas mobilis

This study proposes simulations which present optimized methods for producing fatty acids, fatty alcohols and alkanes using Zymomonas mobilis bacterium by the energy efficient β-oxidation reversal pathway, an eco-friendly alternative to the present petro