No genetically identical cell displays the same behavior and appearance. This suggest that the behavior of a cell cannot merely be attributed to its genetic background and the external inputs it receives. Such cell-to-cell variability is partly caused by the inherent probabilistic character of biochemical reactions but also variability in cellular states. These differences in cellular state enable the regulatory system to modulate for the uncertainty of future events. This heterogeneity can be observed when the cell is exposed to new environmental conditions. Cells which are exposed to a switch in carbon source availability display a change in gene expression machinery. Previous work of our group has shown that the magnitude of the change variates from cell to cell . Here, we want to understand which cell dynamics introduce fluctuations in cellular states and how these provide an evolutionary benefit to the overall population.
Dynamic imaging of single cells through fluorescent microscopy enables to study the stochastic nature of biological processes. Therefore, we will work in this project with a large dataset of yeast cells with a fluorescent reporter for gene expression which have been observed over time through microscopy after a switch in carbon source. In the first part, this project will utilize image analysis to categorize the individual cell in groups for age, size, cell cycle, etc. In the next part we will use a system biology approach and design a simple model of ordinary differential equations (ODEs) which describes the expression of the fluorescent reporters. Next, parameter estimation will be done for the different categories of cells. Through simulation of these parameters with the ODE-model we will be able to compare the variability between the different cell categories. This will give us an insight in how cellular ageing and cell cycle introduce cellular heterogeneity, and how this effects the response to environmental changes.
References:  Niek Welkenhuysen, Johannes Borgqvist, Mattias Backman, Loubna Bendrioua, Mattias Goksör, Caroline B. Adiels, Marija Cvijovic, Stefan Hohmann. Single‐cell study links metabolism with nutrient signalling and reveals sources of variability. BMC Systems Biology. 2017, 11:59
Gruppstorlek 3-4 studenter
Målgrupp GU- och Chalmersstudenter. För GU-studenter räknas projektet som ett projekt i Tillämpad matematik (MMG900/MMG920).
Projektspecifika förkunskapskrav Introductory course(s) or strong interest in cellular and molecular biology. Introductory course in programming in Matlab.
Se respektive kursplan för allmänna förkunskapskrav. Utöver de allmänna förkunskapskraven i MVEX01 ska Chalmersstudenter ha avklarat kurser i en- och flervariabelanalys, linjär algebra och matematisk statistik.