Dynamisk modellering av signalvägar som reglerar kol- och kvävemetabolismen i bagerijäst
Typ
Examensarbete för kandidatexamen
Program
Publicerad
2022
Författare
Andrekson, Leo
Hellberg, Rakel
Johansson, Emma
Olsson, Jesper
Modellbyggare
Tidskriftstitel
ISSN
Volymtitel
Utgivare
Sammanfattning
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. [1]. 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. [1]. 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.