Editing Metabolic engineering (section)

==Metabolic flux analysis==
An analysis of metabolic flux can be found at ''[[Flux balance analysis]]''

===Setting up a metabolic pathway for analysis===
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.  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.  ''Escherichia coli'' (''E. coli'') is widely used in metabolic engineering to synthesize a wide variety of products such as amino acids because it is relatively easy to maintain and modify.<ref>University of California - Los Angeles (2008, December 18). "Genetic Modification Turns E. Coli Bacteria Into High Density Biofuel". ''ScienceDaily.'' Retrieved December 7, 2011, from https://www.sciencedaily.com/releases/2008/12/081218151652.htm</ref>  If the organism does not contain the complete pathway for the desired product or result, then genes that produce the missing enzymes must be incorporated into the organism.

===Analyzing a metabolic pathway===
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.<ref>Schellenberger, J., Que, R., Fleming, R., et al. (2011). "Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0". ''Nature Protocols.'' 6(9):1290-1307</ref>  These programs use complex linear algebra algorithms to solve these models. 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. Information about the reaction (such as the reactants and stoichiometry) are contained in the matrices G<sub>x</sub> and G<sub>m</sub>. Matrices V<sub>m</sub> and V<sub>x</sub> contain the fluxes of the relevant reactions.  When solved, the equation yields the values of all the unknown fluxes (contained in V<sub>x</sub>).

:<math>V_x=-(G_x)^{-1}*(G_m * V_m)</math>

===Determining the optimal genetic manipulations===
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.<ref>Rocha, I., Maia, P., Evangelista, P., et al. (2010). "OptFlux: an open-source software platform for in silico metabolic engineering". BMC Sys Biol. 45(4)</ref> They provide recommendations for which genes should be overexpressed, knocked out, or introduced in a cell to allow increased production of the desired product. 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.<ref>Work, T.S., Hinton, R., Work, E., Dobrota, M., Chard, T. (1980). "Laboratory Techniques in Biochemistry and Molecular Biology". v.8</ref>

===Experimental measurements===
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 [[isotopic labeling|carbon-13 isotopic labeling]].<ref>Wiechert, W. and de Graaf, A.A. (2000). "Bidirectional Reaction Steps in Metabolic Networks: Modeling and Simulation of Carbon Isotope Labeling Experiments". ''Biotechnol. Bioeng.'' 55(1):101-117</ref> The organism is fed a mixture that contains molecules where specific carbons are engineered to be carbon-13 atoms, instead of carbon-12. After these molecules are used in the network, downstream metabolites also become labeled with carbon-13, 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. Labeling patterns may be measured using techniques such as [[gas chromatography-mass spectrometry]] (GC-MS) along with computational algorithms to determine reaction fluxes.