The ability of cells and organisms to generate heritable alternative strategies through genetic or epigenetic variations is not well understood and is a central issue in evolution and disease control. The contribution of network complexity to evolvability of new cellular mechanisms is directly relevant to a variety of medical concerns. For example, cancer cells have incredible abilities to escape treatments that are intended to block their growth. Pathogens are known to use epigenetic and genetic modifications to rapidly switch expression of cell-surface proteins to escape detection by the immune system. An important task for quantitative genomic medicine is to characterize the adaptive response of cells to perturbations by drugs or mutation, then to quantify them with models and predict the patterns of adaptation. A systems approach will be adopted to characterize the complex genetic or epigenetic changes in budding yeast cells in response to perturbations of the mitotic exit network. The mitotic exit network (MEN) is a complicated regulatory network that interacts with several other important pathways to control the timing of mitotic exit and cytokinesis. The fundamental goal is to determine if characteristic patterns and organizational principles are exhibited in suppressors when key genes are deleted from the MEN pathway. Genetic crosses, live cell imaging, and microarray expression measurements will be used to characterize adaptations. Then data from recent publications will be integrated with corroborating data from several sources to build computational models of the MEN and adaptations, which will be analyzed and compared quantitatively to discover patterns. This may provide insights into how network complexity contributes to the activation of new cellular mechanisms and may have practical applications for predicting the possible response of cells to targeted drug treatments.
| Bosl, William J; Li, Rong (2010) The role of noise and positive feedback in the onset of autosomal dominant diseases. BMC Syst Biol 4:93 |
| Kriete, Andres; Bosl, William J; Booker, Glenn (2010) Rule-based cell systems model of aging using feedback loop motifs mediated by stress responses. PLoS Comput Biol 6:e1000820 |
| Bosl, William J (2007) Systems biology by the rules: hybrid intelligent systems for pathway modeling and discovery. BMC Syst Biol 1:13 |
