Control-Theoretic Approaches in Systems Biology: sensitivity conservations as performance constraints

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The proposed research addresses the 'design principles' of life. In the past, comparisons have often been made between engineered automatic feedback systems and living organisms. Recent advances in experimental techniques allow the rigorous testing of these comparisons, through the comprehensive observation of the most fundamental of biological feedback systems: biochemical and gene-regulatory networks. The proposed research addresses a particular aspect of the theory of automatic feedback systems: conservation of sensitivity. Generally, improving robustness means reducing system sensitivity -- insulating a system from unforeseen perturbations. The control engineering community has identified that in many cases, system structure imposes a conservation of sensitivity, so sensitivity reduction cannot be achieved. When this constraint is in place, the system engineer is limited to designing feedback that will redistribute sensitivity to improve system behaviour, for instance by shifting sensitivity away from components to which perturbations are dangerous. Because sensitivity in conserved, this will necessarily introduce additional sensitivity in other components. Sensitivity constraints apply in the biomolecular 'design space' as well. They have been applied to metabolic pathways in order to better understand their regulation. Recent work by myself and others indicates that these constraints are in place in a range of biochemical and genetic networks. The proposed research aims to explore where these constraints occur, and what forms they take, as well as to experimentally verify their consequences. This will result in a better understanding of cellular regulation, and thus enhance strategies that aim to alter cellular behaviour, either chemically (e.g. with drugs), or genetically (e.g. genetic engineering). These types of manipulations are key to current efforts in a range of biotechnological directions, including human health and disease, biomanufacturing, agriculture, and environmental bioremediation.