Publications by authors named "Matthias Bujara"

Cell-free extract (CFX)-derived biocatalytic systems are usually embedded in a complex metabolic network, which makes chemical insulation of the production system necessary by removing enzymatic connections. While insulation can be performed by different methods, the identification of potentially disturbing reactions can become a rather lengthy undertaking requiring extensive experimental analysis and literature review. Therefore, a tool for network topology analysis in cell-free systems was developed based on genome scale metabolic models.

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Recruiting complex metabolic reaction networks for chemical synthesis has attracted considerable attention but frequently requires optimization of network composition and dynamics to reach sufficient productivity. As a design framework to predict optimal levels for all enzymes in the network is currently not available, state-of-the-art pathway optimization relies on high-throughput phenotype screening. We present here the development and application of a new in vitro real-time analysis method for the comprehensive investigation and rational programming of enzyme networks for synthetic tasks.

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The implementation of the engineering design cycle of measure, model, manipulate would drastically enhance the success rate of biotechnological designs. Recent progress for the three elements suggests that the scope of the traditional engineering paradigm in biotechnology is expanding. Substantial advances were made in dynamic in vivo analysis of metabolism, which is essential for the accurate prediction of metabolic pathway behavior.

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The orchestration of a multitude of enzyme catalysts allows cells to carry out complex and thermodynamically unfavorable chemical conversions. In an effort to recruit these advantages for in vitro biotransformations, we have assembled a 10-step catalytic system-a system of biotransformations (SBT)-for the synthesis of unnatural monosaccharides based on the versatile building block dihydroxyacetone phosphate (DHAP). To facilitate the assembly of such a network, we have insulated a production pathway from Escherichia coli's central carbon metabolism.

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Pathogens, which alternate between environmental reservoirs and a mammalian host, frequently use thermal sensing devices to adjust virulence gene expression. Here, we identify the Yersinia virulence regulator RovA as a protein thermometer. Thermal shifts encountered upon host entry lead to a reversible conformational change of the autoactivator, which reduces its DNA-binding functions and renders it more susceptible for proteolysis.

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