Dynamisk modellering av signalvägar som reglerar kol- och kvävemetabolismen i bagerijäst
Examensarbete för kandidatexamen
Understanding how signaling functions within and between cells is relevant to get a better grasp of several diseases. A central signaling process in organisms ranging from everyday baker’s yeast to humans is the nutrient signaling network, which is responsible for sensing availability of nutrients, such as carbon and nitrogen. The TORC1, SNF1 and cAMP-PKA signaling pathways are central components of the nutrient signaling network in baker’s yeast, which regulates the metabolism based on nutrient levels. In this project, we investigated these pathways by implementing and analyzing an ODE model of said pathways from Jalihal et al. . As a first step, the model was implemented and some results from Jalihal et al. were recreated in order to confirm the implementation. Furthermore, the model consists of several unknown parameters that have to be estimated. This was done using a quasi-Newton algorithm. Two parameter vectors were obtained which give a better description of data than the parameter vector reported by Jalihal et al. The conclusion drawn from the identifiability and sensitivity analysis is that the majority of the parameters have low sensitivity. Qualitative data was used to examine the model’s validity for scenarios where no quantitative data is available. This was done for the parameter vectors obtained from the parameter estimation and Jalihal et al. . Most of the scenarios analyzed were consistent with qualitative data, except for a few cases. For these cases, experiments were proposed that could improve and expand the model. Despite the shortcomings of the model, it is still useful as a basis for further development. Measures such as extending the model, combined with new parameter estimations, may in the long run lead to a well-describing model of the nutrient signaling pathways in baker’s yeast.