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Method for analyzing metabolites flux using converging ratio determinant and split ratio determinant

A metabolism and throughput technology, applied in the fields of botany equipment and methods, biochemical equipment and methods, analytical materials, etc., can solve problems such as user inconvenience, long calculation time, and inability to obtain actual values

Inactive Publication Date: 2009-06-17
KOREA ADVANCED INST OF SCI & TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Constraint-based flux analysis based on linear programming has ease of availability and simple calculation steps, but has the problem that some of the available constraints are small, making it impossible to obtain real values
However, this technique has the disadvantage that, since it is based on a non-linear programming method, it uses a very complex calculation process, which causes inconvenience to the user and requires a long calculation time, and due to its complexity and the range of constraints and number of limitations, it is only calculated in small-scale models, including glycolysis, pentose phosphate pathway, TCA, replenishment pathway and some amino acid synthesis pathways (Biotechnol.Bioeng.66:86, 1999; K.Shimizu , Biotechnol. Bioprocess Eng. 7: 237, 2002)

Method used

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  • Method for analyzing metabolites flux using converging ratio determinant and split ratio determinant
  • Method for analyzing metabolites flux using converging ratio determinant and split ratio determinant
  • Method for analyzing metabolites flux using converging ratio determinant and split ratio determinant

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0114]Example 1: Application of CRD and SRD in Exemplary Model

[0115] As an exemplary model for metabolic flux analysis, the image 3 system shown in . An exemplary model including 5 reaction equations, 3 metabolites and 1 uptake (uptake, R1 ) and maximum v6 as objective functions for metabolic flux analysis was set up. Stimulation was performed using MetaFluxNet 1.6, which can be downloaded at http: / / mbel.kaist.ac.kr / (Lee et al., Bioinformatics, 19:2144, 2003).

[0116] For comparison, a metabolic flux analysis excluding CRD and SRD was initially performed. When a quasi-steady state is assumed, the stoichiometric matrix for the exemplary model is as follows:

[0117] S · v = 1 - 1 0 - 1 ...

Embodiment 2

[0150] Example 2: Example of CRD applied to E.coli. metabolic network model

[0151] In the case of E. coli., a new metabolic network consisting of 979 biochemical reactions and 814 metabolites was taken as the metabolic network. Such a system including all E. coli biochemical reactions and most of the biomass composition for forming E. coli to be used as the objective function using the biomass formation equation is as follows (Neidhardt et al., Cellular and Molecular Biology, 1996): 55% protein, 20.5% RNA, 3.1% DNA, 9.1% lipid, 3.4% lipopolysaccharide, 2.5% peptidoglycan, 2.5% glycogen, 0.4% polyamine and 3.5% other metabolites, cofactors and ion.

[0152] In general, E. coli. seem to grow using a maximal cell fraction, which is expressed as a specific growth rate. Therefore, metabolic flux analysis was performed according to linear programming using a specific growth rate as the objective function.

[0153] First, in E. coli., experimental values ​​for definable correlat...

Embodiment 3

[0178] Example 3: Genetic Screening and Organism Improvement Using the Present Invention to Increase the Yield of Useful Substances

[0179] In order to increase the yield of useful substances, the genes to be amplified that increase the yield of useful substances were screened using the optimal value of the total metabolic flux and the spectrum obtained according to Examples 1 and 2. The screening of the gene to be amplified was performed according to the method described in Korean Patent Document Publication No. 10-2005-0086119.

[0180] Also, the gene to be amplified screened according to the method in Korean Patent Publication No. 10-2005-0086119 may be introduced into or amplified in a related organism to construct a mutant of the related organism.

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Abstract

The present invention relates to a method for analyzing metabolic flux using CRD and SRD. Specifically, the method comprising: selecting a specific target organism, constructing the metabolic network model of the selected organism, identifying the correlations between specific metabolic fluxes in the metabolic network model, defining the correlation ratios as CRD and SRD, determining the correlation ratios of the metabolic fluxes through the experiment for measuring metabolic flux ratios, modifying a stoichiometric matrix with the determined CRD, SRD and correlation ratios, and applying the modified stoichiometric matrix of the metabolic network model for linear programming. According to the inventice method, the correlation between influent / effluent metabolic fluxes with respect to specific metabolites in target organisms (including E. coli), the genome-scale metabolic network model of which was constructed, can be determined as relative ratio using useful information obtained from various experiments, including a growth experiment using a radioactive isotope-labeled carbon source and an assay for measuring enzymatic reaction. Thus, limit values from various experiments can be effectively applied, so that internal metabolic flux can be quantified and analyzed in a more accurate and rapid manner.

Description

technical field [0001] The present invention relates to a method for analyzing intracellular metabolic flux using CRD (converging ratio determinant) and SRD (split ratio determinant), in particular to a method for analyzing metabolic flux, which comprises: Select a specific target organism, construct a metabolic network model of the selected organism based on biochemical reactions, determine the correlation between specific metabolic fluxes in the metabolic network model, define the correlation as CRD and SRD, and pass 13 C labeling experiments determine the flux ratios of specific biochemical reactions in the metabolic network model, modify the stoichiometric matrix with the determined CRD, SRD, and artificial metabolites, and apply the revised stoichiometric matrix to the metabolic network model for linear programming. Background technique [0002] By introducing new biochemical reactions or removing, amplifying or modifying existing metabolic pathways using molecular biol...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N33/50C12N1/15C12N1/19C12N1/21C12N15/00C12Q1/00G06F19/00G06F19/12
CPCG01N33/5088G01N2333/245G01N33/48G01N33/50
Inventor 李相烨崔亨奭金兑勇
Owner KOREA ADVANCED INST OF SCI & TECH
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