Our group combines metabolomics and computational modeling to investigate how bacteria control their metabolic networks dynamically. We ask which mechanisms for dynamic control evolved naturally, and which synthetic control circuits could improve production strains in biotechnology. In nature, bacteria produce metabolites with the objective to grow, and regulatory mechanisms assure that supply and demand of metabolites is balanced. In biotechnological applications, in contrast, bacteria should overproduce a desired metabolite, and regulatory mechanisms often conflict with this objective. The common practice in metabolic engineering is partial disruption of regulation and strong overexpression of enzymes in the production pathway. However, with these modifications the cell cannot respond to disturbances of cellular fitness that require lower activity of the production pathway. Our long-term goal is the design of strains that integrate overproduction of a chemical with cellular fitness and thus autonomously optimize yield.
Although a large part of the metabolic network is mapped, the dynamic nature of metabolism remains elusive. Fundamental questions are still unsolved: How do cells maintain metabolite homeostasis, and which regulatory mechanisms control metabolic flux? The mission of our group is to systematically tackle such questions using a synthetic biology approach. We engineer regulatory interactions and examine their function in metabolic networks of microbes like Escherichia coli. The methods we use are based on metabolomics and integration of these data with computational models. Our long-term goal is to develop enzymes that improve biotechnological processes by coupling overproduction to the metabolic state of the host.
Although engineering of allosteric enzymes is possible at large-scale, methods to analyze their function are lacking behind. For instance, making mutations in allosteric proteins or swapping domains are possible for large mutant libraries, but assessing their function in metabolic networks at the same scale is not possible. We develop such methods based on mass spectrometry and metabolomics to systematically assess the effect of mutations in allosteric enzymes at large-scale. In combination with new cultivation and sample preparation techniques we bridge the gap between construction of enzyme variants and functional characterization.
Coupling activity of an arbitrary enzyme to an arbitrary ligand is one of the great challenges of synthetic biology and has great potential for biotechnological applications. However, the common practice in metabolic engineering is merely disruption of regulatory mechanisms, which is problematic when an individual cell finds itself in suboptimal conditions that would require lower synthesis and redistribution of chemical precursors. With our methods for enzyme design we try to change the sensitivity of an allosteric enzyme to its ligand and to create new specificities. The goal is to construct enzymes with new regulatory mechanisms, which couple overproduction to the metabolic state of the host.
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