A comprehensive model of a complete biological system will enable prediction of phenotypic outcomes in face of novel genetic and environmental perturbations. Such predictive power for cellular systems, such as DMA repair, will have tremendous impacts on early detection and diagnosis of genetic disorders and, ultimately in designing preventive and/or curative treatments. However, the full understanding of eukaryotic DMA repair systems presents a daunting challenge due to their enormous complexity, especially given that systems approaches are not yet sufficiently mature to mathematically model such complex processes. At a molecular level, eukaryotic genetic information processing is mirrored in a simplified manner by their evolutionary ancestors, the archaea. In Halobacterium NRC-1 we have a simple yet powerful model system of -2400 genes in which the underlying generalized principles of a systems approach can be delineated. This halophilic archaeon routinely mitigates damage from high salinity, UV radiation and desiccation-rehydration cycles. We will use this model system to address the hypothesis that the decision making process governing cell fate after exposure to DMA damaging events such as UV irradiation is mediated by robust gene regulatory networks that simultaneously process information on spectral characteristics of the impinging radiation, the nature and extent of DMA damage and the potential preparative role of cellular entrainment to diurnal cycles. This hypothesis is motivated by two main observations: a. in systems analysis of UV response, although extraordinarily resistant, not all expected repair genes in this microbe responded to irradiation or damage;b. many of these damage-unresponsive repair genes did, however, respond to day-night entrainment. At a fundamental level this suggested that the resident state of the cell at time of irradiation may influence the type of response elicited. A systems approach is ideally suited to delinate the networks underlying this decision making process. Specifically, we will measure dynamic global changes (degree of damage, mRNA /protein levels, protein-protein and protein-DNA interactions) in wild type and mutant strains (defective in sensors, signal transducers, regulators and repair proteins) subjected to combinatorial changes in incident radiation, type of damage inflicted and resident state of the cell at the time of radiation. Through an integrated analysis of these diverse systems level data we will statistically learn perturbation-induced rewiring of a gene regulatory network that processes environmental perturbations (input) into phenotype (output), i.e. a predictive model for regulatory mechanisms for repair. This basic model will serve as a template for designing systems approaches to model higher complexities of eukaryotic repair processes.
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