Sources and Consequences of noise in cell cycle regulation

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DESCRIPTION (provided by applicant): Single-cell variation (noise) in the operation of genetic networks is an inevitable consequence of the small size of cellular systems, leading to small numbers of molecules (genes, mRNAs, proteins) that may cause fluctuations in the function of important genetic control circuits. Where such noise is deleterious, it is likely that noise suppression mechanisms have evolved; noise could also be beneficial in some cases, by allowing breakout from dynamical dead-ends or by diversifying a population to meet a changing environment. Despite the significance of this topic, empirical results on noise have so far been largely restricted to simple synthetic gene circuits. We propose analysis of single-cell variation in a much more complex and physiologically relevant situation: the robustness of cell cycle traversal and duration of cell cycle intervals in the eukaryote S. cerevisiae. We have developed a quantitative fully automated time- lapse fluorescent microscopy setup allowing semi-automated analysis of cell-cycle-regulated gene expression and relocation of cell cycle regulators, throughout the generation of complete multi-cell cycle pedigrees. This capability can be integrated with the enormous amount of information available about the regulation of the budding yeast cell cycle, the availability of genetic reagents to systematically perturb the cell cycle, and useful deterministic mathematical models of the cell cycle engine. We will test the hypothesis that variability in G1 length is due to bistability at cell cycle Start. We will generate quantitative single-cell data on the relationship of cell and nuclear size to cell cycle transition times, in wild-type and mutants, to provide constraints for models on nucleo-cytoplasmic size coupling. We will attack the question of what promoter architectures may lead to different levels of single-cell variability in gene expression, using a synthetic promoter strategy combined with single-cell imaging. We have obtained direct evidence for stochastic molecular variation in cell cycle Start; we will pursue this finding genetically and with stochastic modeling. To pursue these ideas in more dynamic depth, we have developed microfluidic methods that allow periodic pulses of gene expression in individual monitored cells as they proliferate from single cells into microcolonies. With this technology we will test the response of the cell cycle engine to brief forced expression of regulators, and looking for mode-locking and other informative dynamic behaviors. We will extend these analytical tools to mitotic regulation, testing the hypothesis that the complex design of the mitotic oscillator functions to suppress noise. The results should shed light on fundamental questions of robustness and dynamics of the cell cycle engine at single-cell resolution, and on the advantages and disadvantages of variability in the operation of a fundamental complex genetic circuit.