| Summary: | Cellulosic biomass is one of the most abundant materials on earth, making it an attractive prospect for bioprocessing to produce fuels and chemicals as an alternative to fossil fuels. Traditional processes that convert cellulose to products do so via an inefficient multistep process, involving sequential reactors that first hydrolyse the cellulose through the addition of exogenous enzymes and then pass the hydrolysate to the next reactor for the liberated sugars to be fermented. Consolidated bioprocessing (CBP) combines this two-step process into one, offering improvements in costing, by removing the need for extra reactors, and efficiency, by having organisms utilise sugars as they are produced reducing end product inhibition of the cellulases. This thesis is aims to model the CBP process by developing separate hydrolysis and fermentation models and then integrating them together. Then by using the model the optimal conditions for ethanol production will be found and the limiting steps of the process identified. A model depicting the breakdown of cellulose by cellulases and a dynamic metabolic flux analysis (DMFA) model describing the fermentation of glucose and cellobiose by the thermophilic organism G. thermoglucosidasius was developed. These models were fitted to experimental data of the cells growing on cellobiose and literature data of cellulose hydrolysis. The effects of the timing of the anaerobic switch, adding either glucose or cellobiose to the system and enzyme composition were analysed. It was found that by adding 5 mmol/L of cellobiose at the start of the reaction, the ethanol production increased by 35% (mol/mol). The timing of the switch from aerobic to anaerobic conditions was found to be an important factor. The later the switch occurred, the less ethanol was produced. The longer the cells lived in aerobic conditions the more of the glucose and cellobiose was used for cell growth, leaving less for ethanol production once the switch was made. The ratio of endo/exoglucanses to β-glucosidase affected the rate at which cellulose was broken down. This effect then passed on to the cell growth curves and ethanol production. A ratio of 0.95 exo/endoglucanases to 0.05 β-glucosidases was found to produce the most ethanol. A combination of 1-hour anaerobic switch time, 0.95/0.05 enzyme split and 5 mmol/L initial cellobiose were found to be optimal, producing 115 mmol/L of ethanol. Global sensitivity analysis (GSA) was carried out on each of the models, with the key parameters affecting the outputs identified. There was a lack of detailed CBP for these cells growing on cellulose to assess the accuracy and validate the model. Therefore, there are areas of the model that require further investigation, in particular how the model predicts cell growth. Despite this the model does show that the ability to test changes to the process through simulations can be very powerful. Modelling the CBP process opens areas for more research in the future, such as online optimisation and control. Accurate control of co-cultures of microorganisms will be key in the future to produce exact levels of enzyme production and cell growth that maximise the production of products.
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