Abstract
Mathematical models are playing an important part in the current developments in engineering, science and biotechnology. Within this field the most fashionable and representative organisms are the ones who are genetically and physiologically tractable. Since the fission yeast Schizosaccharomyces pombe plays a role model among them and its behaviour has medical, genetic and industrial links (related to cancer research, metabolic pathways and beer production), this makes it a particularly interesting organism for study. This dissertation presents the first physiological model ever developed for the yeast S. pombe. The model allows for the simulation and prediction of batch and repeated batch experiments which are an important engineering tool in terms of optimization of industrial processes improving yield in bioreactors by predicting precise values of harvest fraction (HF) and dilution cycle times (DCT). The model has been developed within the generic modelling framework of CelCyMUS (Cell Cycle Model University of Surrey). As part of the research being carried out CelCyMUS has been up-dated by introducing the new Fortran 95 features and utilities in order to exploit its powerful new features and to keep the generic model in pace with technological software advancements. The model is a one-dimensional age-based population balance for the fission yeast S. pombe. It includes the four typical phases (S, G2, M and G1) with the G2 phase divided into two phases (G2A, G2B) and two checkpoints that govern the movement of cells between G1 and S, and G2B and M phases. The transitions (movement of cells between phases) are determined by a probability function related to the consumption of glucose. The G2B-M transition is also dependent on cell size, but since individual growth of cells is related to the consumption of the carbon source (in this case glucose), cell size is dependent upon the amount of glucose consumed per cell. The model also includes a phase for cells facing starvation before going into a meiotic cycle, with some chance of coming back to the mitotic cycle, and a death phase that accounts for cells dying with no chance of recovering at all. Parameters in the S. pombe model have been gathered from experimental data in batch culture reported in literature. Data generated from this specific model have been compared with data from experiments (Fotuhi, 2002) in batch and repeated batch cultures of S. pombe following the behaviour of population balance, consumption of nutrients, and production of metabolites. The new code was tested by successftilly reproducing data from mm-321 hybridoma cell line, the first specific model of a cell line developed in CelCyMUS. As a new feature a model of mass transfer has been incorporated in the generic framework. This mass transfer module accounts for interactions of metabolites (oxygen and carbon dioxide) in the gas and liquid phase of bioreactors. The new S. pombe model was fitted to the experiments of Creanor (1992) on synchronised cultures where the consumption of oxygen was being measured. Such experiments identify two points (G2B and G1) where the rate of oxygen uptake increased in the cycle, doubling the consumption at the end of every cycle. With the model fitted to experimental results in synchronised cultures of S. pombe the model was then used to simulate desynchronised cultures. S. pombe was successfully tested when reproducing experimental data generated by Fotuhi (2002) in S.pombe for batch and repeated batch bioreactors. The S. pombe model was able to simulate cell number, oxygen and glucose consumption. Carbon dioxide and ATP production were predicted by the model however there was no experimental data to compare with. Now that the S. pombe model has been tested against experimental data it will be applied in a model-based observer strategy for the online control of bioreactors.