Contamination of ecosystems by xenobiotic substances has led to significant negative impacts on the ecologies and on the health and economic livelihood of the human populations in affected environments. Bioremediation, particularly microbial bioremediation, has proven to be a safe, low-cost and environmentally friendly method for remediation of such areas. However, a lack of complete understanding of the metabolic, enzymatic and cellular processes involved has made it difficult to model and predict outcomes of field processes. The ability of researchers to make critical decisions capable of influencing the direction and outcomes of these processes is also hampered. This study outlines the results of a survey and describes the electronic Microbial BioRemediation (eMBR) web portal, designed to improve collaboration in the bioremediation research community. It describes the structure, algorithms and output of three bioinformatics resources developed and deployed via the portal. eMBRLitMine addresses the problem of identifying which microorganisms would be suitable for remediating sites contaminated by named compounds. It combines named-entity recognition algorithms, a mySQL database, graph rendering technologies and Perl scripts to create, from the vast information available within published literature, a statistical co-occurrence matrix which it uses to infer possible associations between microorganisms and particular contaminants. This provides valuable insights into possible bacteria/contaminant relationships and highlights bacterial species that could be used in remediation of specified contaminants. eMBRCatalogue is a moderated and searchable database cataloguing bioremediation case studies. Implemented as an eXtensible Markup Language (XML) database employing a user-generated-content framework, it provides background knowledge necessary for planning and execution of bioremediation activities. Developed following the construction of a comprehensive metabolic biodegradation network, eMBRHelper enables the delineation of possible biodegradation pathways for named contaminants. By integrating relevant chemical, enzymatic and genomics information, it attempts to model the interplay between contaminants, enzymes, microorganisms and degradation pathway, enabling researchers to make informed decisions for improved outcomes, particularly for remediation exercises involving bioaugmentation. The study also analysed usage of the portal and resources, made recommendations for future developments and highlights avenues for further informatics support for the bioremediation research sector.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:595818 |
| Date | January 2012 |
| Creators | Elekwachi, Chijioke Obioma |
| Publisher | University of Nottingham |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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