(567bi) Regulation of the Cellulosomal Operon in Clostridium Acetobutylicum | AIChE

(567bi) Regulation of the Cellulosomal Operon in Clostridium Acetobutylicum

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Developing cellulosic biofuels economically is a major challenge facing chemical and biological engineers today. Organisms exist that can convert cellulose and hemicellulose to potential biofuel solvents, but so far none have shown the ability to do it with high yields. The bacterium Clostridium acetobutylicum ATCC 824 is an industrial organism that undergoes acetone, biobutanol, and ethanol (ABE) fermentation. While C. acetobutylicum is able to produce biobutanol from both hexose and pentose sugars, it is unable to consume large amounts of cellulose. Microorganisms capable of cellulose utilization often contain an extracellular multi-enzyme complex called a ?cellulosome.? C. acetobutylicum contains genes that encode for a potentially potent cellulosome, but for unknown reasons, this cellulosomal operon is not transcriptionally expressed, even in the presence of cellulose as the sole carbon source. Transcriptional expression of the cellulosomal operon is controlled by a promoter region preceding the gene for the cellulosomal scaffolding protein (CAC0910). Previous computational predictions have identified two sigma factor binding sites in this promoter region. We have applied a previously validated computational method based on ?relative occurrences? of random genomic sequences for predicting DNA regulatory elements in bacteria. This method uncovered two additional potential sigma factor binding sites and several possible regulatory sequences. In this research, we seek to understand why the cellulosome is not highly expressed in C. acetobutylicum by analyzing specific elements of the promoter region using a gene reporter system. The results of this research have provided extensive insight into the regulatory mechanisms responsible for suppressing the cellulosome in this highly solventogenic industrial bacterium. The results presented here are currently being used to design effective metabolic engineering strategies.