All cell types endure changes to their environments, and thus, have evolved remarkable ways to react to complex stimuli. Importantly, separate cell functions may combine directly or indirectly to handle such environmental perturbations. Accurate prediction of cellular behavior requires knowing how these functions are coordinated by gene regulation. Moreover, understanding how dynamic cross-talk affects these responses will provide important insights into the causes and appropriate treatments for adverse disease and drug side effects. The ways to do so vary greatly based on scales of interest. In small systems of few genes, models are typically formal chemical equations that offer great dynamical accuracy. Alternately, statistical approaches are more feasible to predict larger, more complex, global networks due to limited parameter data, high dimensionality, and nonlinearity. Hence, quantitative dynamic predictions are typically unavailable at the large scale, creating uncertainty in how small changes to underlying components affect global dynamics. I will address this issue using a multiscale approach that integrates a dynamic model of a small regulatory subcircuit into a statistically inferred, predictive, model of global gene regulation. I will study the copper (Cu) efflux pathway in H. salinarum NRC-1. Based on its regulatory architecture, the subcircuit is potentially bistable in expression of the Cu specific efflux pump yvgX. Yet, such bistability is not readily observed. Notably, H. salinarum NRC-1 also uses a multispecific efflux pump, zntA, to export Cu, which may explain the lack of bistability. I hypothesize that zntA regulation uses many of the same control-points (transcription factors, metallochaperone complexes, etc.) as yvgX and such regulatory sharing offers robust/rapid expression dynamics, but at the cost of regulatory cross-talk. Specifically, additional feedback from zntA forces transient yvgX expression to a high """"""""ON"""""""" state in high Cu concentrations and a low """"""""OFF"""""""" state in low/homeostatic amounts, avoiding bistability which is detrimental to the cell. However, cross-talk from zntA's sensitivity to other metal ions, namely zinc (Zn), disrupts Cu homeostasis, forcing the system closer to bistability. Moreover, by combining small and large scale modeling techniques, I should be able to predict system wide gene expression perturbations as a result of this cross-talk.
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