Development and application of an in silico metabolic model of Geobacillus thermoglucosidasius
Development and application of an in silico metabolic model of Geobacillus thermoglucosidasius
批准号:
BB/I015841/2
负责人:
金额:
$9.1万
依托单位:
依托单位国家:
英国
项目类别:
Training Grant
财政年份:
2013
资助国家:
英国
项目状态:
已结题
起止时间:
2013 至 --
中文摘要
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英文摘要
TMO Renewables Ltd, the CASE collaborating company, has developed an ethanol fermentation process capable of using sugars derived from lignocellulosic substrates, based on engineering the fermentation pathways of Geobacillus thermoglucosidasius. As part of the work they have contracted to obtain the genome sequence of this organism, which is almost complete. In the initial stages, the annotation of a genome sequence is usually done automatically, based on the search for open reading frames (orfs) and bio-informatic homology searches. This means that initial annotations often contain errors and unclassified orfs. In this project the student will start to build a genomic scale metabolic model of this organism, using the initial genome sequence as a starting point. The ultimate goal is to build an in silico model of the metabolic capabilities of this organism based on Palsson's flux balance analysis approach (Palsson BO (2006) Systems Biology. Properties of Reconstructed Networks. Cambridge University Press, New York, USA). However, because Geobacillus spp are not extensively described at a biochemical and physiological level, this will require a considerable amount of experimental validation to eg confirm the gene assignments and fill in missing metabolic links. Once constructed, an in silico metabolic model can have predictive capabilities. Initially, these can be used to authenticate the quality of the model, which invariably includes an number of assumptions/estimates. However, in the long term, these may be used to predict the optimal route for metabolic engineering for a defined objective, which is one of the future aims of the company. In the interim, however, the logical iterative experimental and in silico construction of the model should generate new insights into the physiology and biochemistry of this increasingly important group of thermophiles. The combined experimental and modelling aspects of this programme will form an excellent training programme for a postgraduate student with a biological background, exposing them to one of the more accessible avenues of systems biology.
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