Dynamics of gene expression and signal transduction in single cells

Abstract

Each individual cell is a highly dynamic and complex system. Characterizing dynamics of gene expression and signal transduction is essential to understand what underlie the behavior of the cell and has stimulated much interest in systems biology. However, traditional techniques based on population averages 'wash out' crucial dynamics that are either out of phase among cells or are driven by stochastic cellular components[34]. In this work, we combined time-lapse microscopy, quantitative image analysis and fluorescent protein reporters, which allowed us to directly observe multiple cellular components over time in individual cells. In conjunction with mathematical models, we have investigated three dynamical systems, two of which are based on a long-term genealogical tracking method. First, we found that stochastic switching between different gene expression states in budding yeast is heritable[29]. This striking behavior only became evident using genealogical information from growing colonies. Our model based on burst induced correlation can explain the bulk of our results. In the next system investigated, we explored the interaction between biological oscillators. Especially, we used an abstract model to describe and predict the synchronization of cell cycles by the circadian clock. Simultaneous measurement of both circadian dynamics and cell cycle dynamics in individual cyanobacteria cells revealed the direct relationships between these two biological clocks and thus provided a clear evidence of 'circadian gating', in which circadian rhythms regulate the timing of cell divisions. Lastly, we studied the robustness of the network dynamics to the sequence changes and the changes of gene expression levels of embedding proteins by characterizing dynamic response of the well-conserved mitogen-activated protein kinase (MAPK) cascade to osmotic shock, combining experimental measurements and theoretical models.