Systems Metabolic Engineering
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The first step in the process is to identify a desired goal to achieve through the improvement or modification of an organism's metabolism. Reference books and online databases are used to research reactions and metabolic pathways that are able to produce this product or result. These databases contain copious genomic and chemical information including pathways for metabolism and other cellular processes.
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Using this research, an organism is chosen that will be used to create the desired product or result. Considerations that are taken into account when making this decision are how close the organism's metabolic pathway is to the desired pathway, the maintenance costs associated with the organism, and how easy it is to modify the pathway of the organism. The completed metabolic pathway is modeled mathematically to find the theoretical yield of the product or the reaction fluxes in the cell.
A flux is the rate at which a given reaction in the network occurs. Simple metabolic pathway analysis can be done by hand, but most require the use of software to perform the computations. To solve a network using the equation for determined systems shown below, one must input the necessary information about the relevant reactions and their fluxes.
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Information about the reaction such as the reactants and stoichiometry are contained in the matrices G x and G m. Matrices V m and V x contain the fluxes of the relevant reactions. When solved, the equation yields the values of all the unknown fluxes contained in V x. After solving for the fluxes of reactions in the network, it is necessary to determine which reactions may be altered in order to maximize the yield of the desired product. To determine what specific genetic manipulations to perform, it is necessary to use computational algorithms, such as OptGene or OptFlux.
Metabolic engineering
For example, if a given reaction has particularly low flux and is limiting the amount of product, the software may recommend that the enzyme catalyzing this reaction should be overexpressed in the cell to increase the reaction flux. The necessary genetic manipulations can be performed using standard molecular biology techniques.
Genes may be overexpressed or knocked out from an organism, depending on their effect on the pathway and the ultimate goal. In order to create a solvable model, it is often necessary to have certain fluxes already known or experimentally measured. In addition, in order to verify the effect of genetic manipulations on the metabolic network to ensure they align with the model , it is necessary to experimentally measure the fluxes in the network.
To measure reaction fluxes, carbon flux measurements are made using carbon isotopic labeling.
Systems Metabolic Engineering Turns Microbes into Factories - Scientific American
After these molecules are used in the network, downstream metabolites also become labeled with carbon, as they incorporate those atoms in their structures. The specific labeling pattern of the various metabolites is determined by the reaction fluxes in the network.
IntechOpen The Carnitine System. Microbes arguably offer even more potential, in the long term, to make inexpensive materials in the incredible variety of properties that we now take for granted. Publish with us Peer Review Quality We are passionate about quality of research. This may take some time to load. You do not have JavaScript enabled. This article is part of a special report on the Top 10 Emerging Technologies of produced by the World Economic Forum.
Labeling patterns may be measured using techniques such as gas chromatography-mass spectrometry GC-MS along with computational algorithms to determine reaction fluxes. From Wikipedia, the free encyclopedia. Biological Art of Producing Useful Chemicals.
1. Introduction
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Systems metabolic engineering, which incorporates the concepts and techniques of systems biology, synthetic biology and evolutionary. Systems Metabolic Engineering is changing the way microbial cell factories are designed and optimized for industrial production. Integrating systems biology.
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