KR20090109072A - Genome­scale Metabolic Network Model in Butanol­producing Microorganism and Method for Analyzing Metabolic Feature and for Screening Knock­out Targets in Butanol­producing Microorganism Using the Same - Google Patents

Abstract

PURPOSE: A network model of microorganism metabolism, metabolic property of butanol-producing microorganism or a method for screening deletion target is provided to predict genetic deletion target in a short time. CONSTITUTION: An analysis of metabolism of microorganism which produces buthanol using metabolism network model or a method for screening deletion target comprises a step of collecting genome information or information relating to each gene and a step of arranging enzyme reaction formulation in C. acetobutylicum and GPR relation. The enzyme relating to enzyme reaction is alcohol dehydrogenase, butanol dehydratase, butyryl coenzyme A dehydratase, acetylcoenzyme-A transacetylase, 3-hydroxybutyril coenzyme A dehydratase, and hydrogenase.

Description

Genomescale Metabolic Network Model in Butanolproducing Microorganism and Method for Analyzing Metabolic Feature and for Screening Knockout Targets in Butanolproducing Microorganism Using the Same}

The present invention relates to a metabolic network model for metabolic characterization of butanol producing microorganisms and a method for screening metabolic characterization and deletion of butanol producing microorganisms using the same.

Due to the recent rise in oil prices, interest in alternative energy such as biofuel is increasing, and interest in butanol, which has better physical properties as a substitute for gasoline than ethanol, is increasing. As a result, the clot which generates a solvent such as butanol as a metabolite Interest in the strain of genus Clostridium is also increasing.

Microorganisms in the genus Clostridium are Gram-positive, fully anaerobic and endogenous spores, most of which are known to produce acetic and butyric acid as fermentation products. Some of these strains cause acetone-butanol-ethanol fermentation (hereinafter, ABE fermentation) to produce acetone, butanol, and ethanol in addition to the above organic acids.

In fact, in the early 20th century, one of these strains, Clostridium acetobutylicum, was used to produce acetone and butanol in large quantities. The mass production lasted until the 1960s and 1970s, but with the development of chemical processes, Due to the low cost of chemical synthesis and the difficulty of supplying and receiving substrates, the company has died except in some countries.

To date, the production of bio butanol using Clostridium spp. Includes the following problems. First, there is a problem that both yield and productivity are significantly reduced compared to yeast-based bioethanol. Second, Clostridium The genus strain produces by-products such as acetone, acetic acid, butyric acid, in addition to high butanol as a biofuel, which has the disadvantage of increasing the separation cost.

In the case of Clostridium spp., Which produces a solvent, in the exponential growth phase, organic acids are produced in the exponential growth phase as in the fermentation of ordinary microorganisms. This is called the acidogenic phase. As it enters the plateau phase, the metabolism of the cells is converted into a solventogenic phase that resorbs organic acids and produces solvents of acetone (or isopropanol), butanol and ethanol. This can be interpreted as follows. As it enters the ballast phase, the pH is lowered, thereby increasing the concentration of undissociated organic acids. Among these, undissociated butyric acid is highly toxic to cells, and by reabsorption of these organic acids and conversion to solvents, cells are given time to form endospores that can survive long-term in harsh environments. will be.

Recently, efforts have been made to create improved strains using metabolic engineering approaches that manipulate metabolic pathways as desired by humans based on genetic engineering knowledge and tools.

However, it is known that strains of the genus Clostridium are not easily genetically deleted by homologous recombination. Several cases have been reported in which DNA strands are inserted between genes by single crossover to inactivate the function of genes.However, such single cross gene deletion causes two homologous sequences near the insertion site. This in turn causes homologous recombination, leading to instability of escape of the inserted DNA portion. Cases of gene deletion due to double crossover have only been reported for the pathogen C. perfringens (Awad et al., Mol. Microbiol ., 16: 535-51, 1995). This problem of gene deletion was solved to some extent by the recent development of a methodology for site-specific insertion using group II introns in Lactococcus lactis (Heap et al., J. Microbiol). Methods., 70: 452-64, 2007).

In addition, expression of genes involved in solvent production is associated with the formation of endogenous spores. For example, in the case of deletion of the spo0A gene associated with signaling of endogenous spore formation in C. acetobutylicum or C. beijerinckii , the production of solvents has been reported to be significantly reduced (Harris et al., J. bacteriol). ., 184: 3586-97, 2002; Ravagnani et al, Mol Microbiol, 37:... 1172-85, 2000). Clostridium is relatively lacking in genetic studies compared to Bacillus , another genus that forms endogenous spores, which is a disadvantage in strain improvement.

Thus, attempts were made to produce butanol by cloning and expressing butanol production-related genes in strains with a well-developed genetic tool such as Escherichia coli , without using Clostridium. There was a problem that it was significantly lower than tridium (Atsumi et al., Metab. Eng. , In press, 2007; Inui et al., Appl. Microbiol. Biotechnol. , 77: 1305-16, 2008).

Even if the above problems are solved, it is difficult to find a gene deletion target only through solvent production-related pathways, and it is difficult to find a gene deletion target by insight into the entire metabolic pathway through human intuition. It is also financially and temporally impossible to identify traits by experimentally deleting hundreds to thousands of genes. In addition, since this metabolic flow is not caused by a single gene but by interactions between complex cellular components, it is difficult to obtain an improved strain that is satisfactory only by a single gene deletion. For example, if there are 4,000 genes of the strain we want to improve, we need to perform 4,000 experiments to identify all the traits of a single gene deletion strain, and if we want to identify the traits of double gene deletions, it is 4,000 × 3,999 ≒ (4,000) ² = 16,000,000 experiments should be performed.

Therefore, it is very important to understand cell mechanisms and interactions between microbial cell components in order to develop strains that efficiently produce specific metabolites such as butanol. Therefore, the construction of metabolites and metabolic networks through the development of genomic information and functional genomics provides an effective fruitful target for understanding the interactions between genes and proteins to compose cellular components and forming metabolic networks to increase metabolite production. It adds importance to screening.

In fact, after constructing the metabolic network information using genomic information, the metabolic flow of wild-type strains and gene deletion strains can be simulated, and only the genes showing good results can be used to actually perform the experiment. If you confirm, you can save a lot of time and money compared to the method that you check through every case.

Analytical and predictive techniques through metabolic networks have shown promise with rapidly growing genomic information. In particular, the metabolic network models of each microorganism are combined with mathematical models and optimization techniques, making it possible to predict the response of the metabolic network after removal or addition of genes (Lee et al., Trends Biotechnol ., 23: 349 , 2005). . In addition, metabolic flow analysis techniques using metabolic networks show the ideal metabolic flow of cells even when dynamic information is not required, and it is known that they can accurately simulate and predict cell behavior (Papin, J. et al., Nat. Rev. Mol. Cell Biol. , 6:99, 2005).

Metabolic flow analysis uses the mass balance and cell composition information of biochemical reaction equations to obtain the ideal metabolic flow space that cells can reach, and aims to maximize or minimize specific objective functions through optimization methods (maximization of cell growth rate or specific perturbation). Minimization of metabolic regulation by In addition, metabolic flow analysis can generally be used to confirm the lethality of specific genes of a desired metabolite through strain improvement, and use this to grasp the metabolic network characteristics within the strain. In addition, various studies have been reported applying metabolic flow analysis methods to predict the flow changes in metabolic networks caused by the removal or addition of genes. Indeed, in the development of high yield amino acid strains, this metabolic flow analysis has been used to find gene deletion targets (Park et al., Proc. Natl. Acad. Sci. , 104: 7797-802., 2007; Lee et al. , Mol. Syst. Biol., 3: 149, 2007).

Therefore, the present inventors have intensively tried to develop a metabolic network for analyzing metabolic characteristics of butanol-producing microorganisms for developing strains that efficiently produce specific metabolites. We confirmed that the network model is useful for analyzing metabolic properties of butanol-producing microorganisms, and theoretically found that metabolic flow analysis can be used to screen deletion target genes to create ideal deletion combinations that can improve butanol-producing ability of butanol-producing microorganisms. The present invention has been completed.

It is an object of the present invention to provide a metabolic network model for analyzing metabolic properties of butanol producing microorganisms.

Another object of the present invention is to provide a method for analyzing metabolic properties in butanol producing microorganisms and screening for deletion target enzymes or genes thereof to increase the production of specific metabolites based on the established metabolic network model of butanol producing microorganisms. There is.

In order to achieve the above object, the present invention provides a metabolic network model for metabolic characterization of butanol-producing microorganisms, comprising an enzyme reaction involving the following enzymes:

Alcohol dehydrogenase, butanol dehydrogenase, butyryl coenzyme A dehydrogenase, butyryl-CoA dehydrogenase, crotonase, acetyl coenzyme A acetyltransferase ), 3-hydroxybutyryl coenzyme A dehydrogenase (3-hydroxybutyryl-CoA dehydrogenase) and hydrogenase.

The present invention also provides a method for analyzing metabolic properties of butanol-producing microorganisms, characterized by using the metabolic network model.

The present invention also provides a method for analyzing the topology of the metabolic network model.

The present invention also applies a linear programming method by blocking one or more enzyme reactions in the metabolic network model, but when the ability to produce a specific metabolite increases, the enzyme of the blocked enzyme reaction is selected as a deletion target enzyme, or Provided are a deletion target enzyme or a method for screening the gene for increasing the production of a specific metabolite of a butanol producing microorganism characterized by selecting a gene to be encoded as a deletion target gene.

The present invention also provides a method for producing a mutant microorganism having an increased ability to produce a specific metabolite, wherein the butanol producing microorganism deletes the deletion target gene screened by the above method.

The present invention also provides a mutant microorganism having an increased ability to produce a specific metabolite prepared by the method for preparing the mutant microorganism.

The present invention also comprises the steps of culturing the prepared microorganisms; And it provides a method for producing a specific metabolite comprising recovering a specific metabolite from the culture.

The present invention also provides a method for predicting metabolic flow of butanol-producing microorganisms using the metabolic network model.

The present invention has the effect of providing a metabolic network model for analyzing the metabolic properties of butanol producing microorganisms. The metabolic network model according to the present invention is useful for analyzing metabolic properties such as butanol producing microorganisms and screening for deletion target enzymes or genes thereof to increase the production of specific metabolites, and the metabolic network of butanol producing microorganisms according to the present invention. Model-based screening of deletion targets, unlike human intuition and inference searching for deletion genes, allows for rapid prediction of gene deletion targets at the system level. In addition, by deleting the deletion target gene screened according to the above method in the butanol producing strain, it is useful because it saves time and cost and obtains a mutant microorganism capable of producing a specific metabolite such as butanol with high efficiency.

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. In general, the nomenclature used herein is well known and commonly used in the art.

In one aspect, the present invention relates to a metabolic network model for analyzing metabolic properties of a butanol-producing microorganism comprising an enzyme reaction scheme.

First, a metabolic network model for analyzing metabolic characteristics of butanol-producing microorganisms is constructed as follows. In an embodiment of the present invention were using a Claus tree Clostridium (Clostridium) in microorganisms of butanol-producing microorganisms, Clostridium genome sequencing is completed Genomic information of acetobutylicum ATCC 824 was used. The following describes the case where a metabolic network model of C. acetobutylicum was constructed.

(1) First, genomic information and information about each gene annotation are collected, and then, based on genomic sequence information, the enzyme reactions present in C. acetobutylicum are summarized, and an enzyme catalyzing the enzyme reaction, and Clean up the relationship between the genes you code, or GPR. In this case, rather than directly analyzing the collected gene annotation information, it is preferable to use the information of the metabolic related database that analyzes and organizes the metabolic pathway-related information, and then use the collected information as a reference used in the calibration process.

As used herein, the term "GPR relationship" refers to a Gene-Protein-Reaction Relationship, and refers to a relationship between a gene and its product and the enzyme reaction catalyzed by the product.

Construct a draft model based on the GPR relationships summarized above. In general, metabolic databases include the synthesis of DNA replication, transcription, translation, and other elements that make up cells (such as the phospholipids that make up the cell membrane, the cell wall, the amino acid content of all proteins in the cell, and the cell-wide polymer composition). Expression and growth of the whole cell are not organized. However, these expressions are essential for building models to simulate cell growth, and in order to make these expressions, the composition ratio of each component of the cell must be known. This can be found by obtaining a reference or analyzing a sample obtained through actual fermentation.

At this time, the fermentation conditions are preferably the same as the conditions of the fermentation used in the actual calibration process.

Review the initial model constructed above and perform the correction. Metabolism-related database is a database of gene annotation information analyzed by computer program through bioinformatics techniques. Therefore, such a database is very likely to contain incomplete or incorrect metabolic information due to the following causes.

First, there is a possibility that the gene annotation information itself is incomplete. This is because most gene annotations are performed on the basis of homology by comparing the sequence of genes and the amino acid sequences of enzymes to be analyzed with statistical techniques. If there are genes that have not been identified in a strain, the function of these genes will be difficult to clarify using only bioinformatics techniques.

Second, there is a possibility that errors may occur in the process of automatically interpreting this gene annotation information and making a database by metabolic pathway. For example, when an amino acid sequence of one of the genes of a strain is analyzed for homology through BLAST analysis, there is a case where the homology with the protein of the other strain is high but the database is designated as having no function. .

Therefore, in this step, corrections are performed based on strain-related literature, biochemistry textbooks and literature, and traits identified through actual fermentation, rather than information obtained through bioinformatics techniques.

This process mainly focuses on the following areas.

1) errors in metabolite counting in enzymatic reactions

2) The metabolic pathways that make up the cell components analyzed above are broken

3) Maintenance energy used for life sustaining activity and growth of cells

4) Other various typos

The retention energy of 3) is obtained through continuous chemostat culture. In continuous anti-component culture, the concentration of the cells can be kept constant, and the growth of the cells can be artificially controlled by controlling the dilution rate. In this case, the specific growth rate coincides with the dilution rate, and by adjusting the dilution rate, the dilution rate and the substrate absorption rate per dry weight of the cell at that time can be obtained. Based on this, growth-associated maintenance energy used by cells for growth and non-growth-associated maintenance energy used for life-sustaining phenomena regardless of growth can be obtained. .

If such continuous culture is inevitable, information of other strains may be used. However, since the magnitude of the maintenance energy may vary depending on the strain, it is preferable to use a strain having a close flexible relationship. Otherwise, actual results and metabolic flow analysis are likely to be inaccurate.

In the present invention, the constructed metabolic network model for analyzing the metabolism of butanol-producing microorganisms is characterized by including an enzyme reaction involving the following enzymes:

Alcohol dehydrogenase, butanol dehydrogenase, butyryl coenzyme A dehydrogenase, butyryl-CoA dehydrogenase, crotonase, acetyl coenzyme A acetyltransferase ), 3-hydroxybutyryl coenzyme A dehydrogenase (3-hydroxybutyryl-CoA dehydrogenase) and hydrogenase.

In the present invention, the metabolic network model for analyzing the metabolic properties of the butanol-producing microorganism may be characterized by including an enzyme reaction involving the following enzymes, but several to tens of enzyme reactions may be added or subtracted for metabolic analysis. Can be obvious to one of ordinary skill in the art:

D-3-phosphoglycerate dehydrogenase, aspartate-semialdehyde dehydrogenase, deoxycytidine triphosphate deaminase, orotate phosphoribosyltransferase, phosphatidylserine decarboxylase, D-3-phosphoglycerate dehydrogenase, ketol-acid reductoisomerase, ferredoxin-nitrite reductase, O-thidenkinylrinesasease , sulfate adenylyltransferase subunit 2, adenylylsulfate kinase / sulfate adenylyltransferase subunit 1, PTS system, mannitol-specific IIBC component (gene MtlA), PTS system, mannitol-specific IIA domain (Ntr-type) (gene MltF), mannitol-1-phosphate 5-dehydrogenase, glucosamine--fructose-6-phosphate aminotransferase (isomerizing), glucosamine-6-phosphate isomerase (glucosamine-6-phosphate), N-acetylglucosamine-6-phosphate deacetylase (gene nagA), prephenate dehydrotase (pheA), 1-phosphofructokinase (fructoso 1-phosphate kinase), nitrogenase iron protein (nitrogenase component II) gene nifH, nitrogenase molybdenum-iron protein, alpha chain (nitrogenase componen t I) gene nifD, nitrogenase molibdenum-iron protein, beta chain, gene nifK, phosphoserine phosphatase related protein, L-lactate dehydrogenase, 2-isopropylmalate synthase, aspartate ammonia-lyase (aspartase) gene ansB (aspA), aspartate kinase, cytosine / guanine deaminase related protein, ornithine carbomoyltransferase, PTS cellobiose-specific component IIA, PTS system, cellobiose-specific component BII, beta-glucosidase, PTS cellobiose-specific component IIC, cystathionine gamma-synthase, cystathionine beta-lyase, dedol phosphogluconate al kdgA), 2-keto-3-deoxygluconate kinase (gene kdgK), fusion: PTS system, beta-glucosides specific IIABC component, Fructokinase, sucrase-6-phosphate hydrolase (gene sacA), oxygen-sensitive ribonucleoside-triphosphate reductase nrdD, Phosphomannomutase, alanine racemase, UDP-N-acetylenolpyruvoylglucosamine reductase (murB), 6-phosphofructokinase, pyruvate kinase (pykA), Dihydroorotase, PTS system, maltose-specific enzyme IIBC component, malt ose-6'-phosphate glucosidase (glvA), phosphoenolpyruvate synthase (gene pps), malate dehydrogenase, aspartate semialdehyde dehydrogenase (gene asd), PTS system, glucose-specific IIABC component, cobalamine-dependent methionine synthase I (methyltransferase and cobalamine-binding domain ), diaminohydroxyphosphoribosylaminopyrimidine deaminase / 5-amino-6- (5-phosphoribosylamino) uracil reductase, riboflavin synthase alpha chain, riboflavin biosynthes protein RIBA (GTPcyclohydrolase / 3,4-dihydroxy-2-butanone 4-phosphate synthase), riboflavin synthase beta chain , diaminopimelate decarboxilase (lisA), L-serine dehydratase, beta chain, L-serine dehydratase, alpha chain, phosphatidylserine synthase, ammonium transporter (membrane protein nrgA), serine acetyltransferase, glyceraldehyde 3-phosphate dehydrogenase, gene gapC, phosphoglycerate phosphate isomerase (TIM), 2,3-bisphosphoglycerate-independent phosphoglycerate mutase gene, Enolase, ribose 5-phosphate isomerase RpiB, NADP-spe cific glutamate dehydrogenase, NADPH-dependent glutamate synthase beta chain, glycerol uptake facilitator protein (permease), phosphatidylserine synthase, nucleoside-diphosphate-sugar epimerase (UDP-glucose 4-epimerase), phosphatidylserine decarboxylase, 3-oxoacylyl-ac protein] synthase III, phosphoribosylpyrophosphate synthetase, fructose-bisphosphate aldolase, glucan phosphorylase, thioredoxine reductase, adenine deaminase, phospho-2-dehydro-3-deoxyheptonate aldolase, prephenate dehydrogenase, 3-dehydroquinate synthetase, 5-enolpyruatelshikimate chorismate synthase, fusion: chorismate mutase and shikimate 5-dehydrogenase, shikimate kinase, 3-dehydroquinate dehydratase II, cystathionine gamma-synthase, cysteine synthase, ATP phosphoribosyltransferase, histidinol dehydrogenase, imidazoleglycerol-phosphate dehydratylformamide, hydrochloride ribonucleotide (ProFAR) isomerase, imidazoleglycerol-phos phate synthase cyclase, phosphoribosyl-AMP cyclohydrolase, phosphoribosyl-ATP pyrophosphohydrolase, Transketolase, aconitase A, isocitrate dehydrogenase, argininosuccinate synthase, argininosuccinate lyase, pyruvate-formate lyase, 1-acyl-sylserinefergenase synthase, aspartate aminotransferase, nicotinic acid phosphoribosyltransferase, superfamily I DNA helicase (rep-like helicase), P-loop kinase (uridine kinase family), nicotinate-nucleotide pyrophosphorylase, aspartate oxidase, quinolinate synthase, pyruvate kinase, ribonucleotide reductase dependent, NH (3) -dependent NAD (+) synthetase, Arginase, beta-glucosidase family protein, beta-glucosidase family protein, GlpX-like protein (Fructose-1,6-bisphosphatase related protein), 5-formyltetrahydrofolate cyclo-ligase , anaerobic ribonucleotide reductase, deoxyuridine 5'triphosphate nucleotidohydrolase (DUPTase), chorismate mutase PheB of B.subtilis ortholog, homoserine kinase (thrB), predicted nucleotidyltransferases of NarD / TagD family (N-term. domain) (yqeJ ortholog), diacylglycerol kinase (dgkA) fused to phosphatase B domain (pgpB), glycerol uptake facilitator protein (GLPF), glycerol kinase (GLPK), ribulose-5-phosphate 4-epimerase family protein, L-arabinose isomerase , sugar kinase, possible xylulose kinase, L-arabinose isomerase, Transaldolase, Transketolase (TKT), aldose-1-epimerase, phosphotransferase system IIC component (possibly N-acetylglucosamine-specific), PTS system (N-acetylglucosamine-specific IIA component, putative), histidinol-phosphate aminotransferase, cobalamin biosynthesis enzyme CobT, phosphoribosylcarboxyaminoimidazole (NCAIR) mutase, phosphoribosylaminoimidazolesuccinocarboxamide (SAICAR) synthase, glutamine phosphoribosylpyrophosphate amidotransferase, phosphoribosylaminolythe- diasease phosphorase ligase, beta-glucosidase, UDP-glucose 4-epimerase, ribose 5-phosphate iso merase, PTS system, fructose (mannose) -specific IIA component, PTS system, fructose (mannose) -specific IIB, PTS system, fructose (mannose) -specific IIC, PTS system, fructose (mannose) -specific IID, branched-chain -amino-acid transaminase (ilvE), Fructokinase, fructose-1,6-bisphosphatase, malic enzyme, malate dehydrogenase (oxaloacetate-decarboxylating), phosphoserine phosphatase family enzyme, bifunctional enzyme phosphoribosylformylglycinamidine (FGAM) synthase (synthetase amidotransase domain / glutamine domain / glutamine domain , aspartate ammonia-lyase, glycogen phosphorylase, large subunit of NADH-dependent glutamate synthase, small subunit of NADPH-dependent glutamate synthase, periplasmic phosphate-binding protein, phosphate permease, permease component of ATP-dependent phosphate uptake system, ATPase component of ABC -type phosphate transport system, glycerol 3-phosphate dehydrogenase, L-asparaginase, guanylate kinase, YLOD B.subtilis ortholog, flavoprotein involved in panthothenate metabolism, YLO I B.subtilis ortholog, pentose-5-phosphate-3-epimerase, phosphopantetheine adenylyltransferase, phosphate acetyltransferase, acetate kinase, nicotinic acid phosphoribosyltransferase, NH (3) -dependent NAD (+) synthase (nadE) fused to amidohydrolasedomain, uridylate kinase CDP-diglyceride synthetase, riboflavin kinase / FAD synthase, Aspartokinase, phosphatidylglycerophosphate synthase, aspartate aminotransferase, phosphocarrier protein (Hpr), adenylosuccinate lyase, homoserine trans-succinylase, cytidylate kinase, 3-acoxyylase- nucleoside phosphorylase, Phosphopentomutase, predicted kinase, tetrahydrofolate dehydrogenase / cyclohydrolase (FolD), nucleoside phosphorylase, cation transport P-type ATPase, phosphoserine phosphatase family enzyme, pyruvate: ferredoxin oxidoreductase, cysteine synthase / cystacosease A pyrophosphorylase, ADP-glucose pyrophosphorylase, glycogen synthase (glgA), N-terminal domain of asparagine synt hase, UDP-glucose pyrophosphorylase, glycine hydroxymethyltransferase, adenine phosphoribosyltransferase (Apt), UDP-glucose 4-epimerase, UTP-glucose-1-phosphate uridylyltransferase, dihydrodipicolinate synthase, dihydrodipicolinate reductase, PLP-dependent aminotransferolinate acetylornithine aminotransferase, acetylglutamate kinase, N-acetyl-gamma-glutamyl-phosphate reductase, amino-acid N-acetyltransferase / glutamate N-acetyltransferase, folylpolyglutamate synthase, 2-oxoacid ferredoxin oxidoreductase beta subunit, 2-oxoacid ferredoxin subunitase xunitase , transcriptional regulators of NagC / XylR family, beta-phosphoglucomutase, diaminopimelate epimerase, possible 3-ketoacyl-acyl carrier protein reductase, carbamoylphosphate synthase large subunit, carbamoylphosphate synthase small subunit, dihydroorotate dehydrogenase, orotidine-5'-phosphate decarboxybase, subunit, asp artate carbamoyltransferase catalytic subunit, glutamine synthetase type III, pyruvate carboxylase (PYKA), glucose-6-phosphate isomerase, sugar kinase, ribokinase family, trehalose / maltose hydrolase (phosphorylase), GMP synthase, IMP dehydrogenase, 3-hydroxybutyryl-CoA dehydro electron transfer flavoprotein alpha-subunit, electron transfer flavoprotein beta-subunit, butyryl-CoA dehydrogenase, 3-hydroxybutyryl-CoA dehydratase, deacethylase / dipeptidase / desuccinylase family of Zn-dependenthydrolases, putative histidinol-phosphatase, O-acetylhomoserine (thiol) -lyase , Acylphosphatases (ACYP), PLP-dependent aminotransferase, glycerate kinase, galactose-1-phosphate uridylyltransferase, S-adenosylmethionine synthetase, UDP-N-acetylglucosamine 1-carboxyvinyltransferase, acetyl-CoA acetyltransferase, deoxycytidylate deaminate isomerase 5-Ripase ), fusion of alpha-glucosidase (family 31 glycosyl hydrolase), CTP synthase (UTP-ammonia lyase), D-alanine-D-alanine ligase, ke topantoate hydroxymethyltransferase, pantoate--beta-alanine ligase, aspartate 1-decarboxylase, mannose-6 phospate isomerase, dihydropteroate synthase, dihydroneopterin aldolase fused to 7,8-dihydro-6-hydroxymethylpterin-pyrophosphokinase, ketopantoate reductase, PanE / Apb conprotein fron YGAG family, predictedmetal-dependent enzyme, 3-phosphoserine aminotransferase (Possible phosphoglycerate dehydrogenase), tagatose-6-phosphate kinase, galactose-6-phosphate isomerase, galactose-6-phosphate isomerase, PTS system galactitol-specific IIC component, PTS system galactitol-specific IIB component, PTS system galactitol-specific IIA component putative, Galactokinase, UDP-galactose 4-epimerase, 6-phospho-beta-D-galactosidase, PTS system lactose-specific enzyme IIBC, PTS system lactose-specific enzyme IIA, alpha-acetolactate decarboxylase, 2-keto-3-deoxy-6-phosphogluconate aldolase (eda / kdgA), PTS system (Glucose-specific) component IIA, thymidylate synthase, dihydrofolat e reductase, adenosine deaminase, amino-acid N-acetyltransferase / glutamate N-acetyltransferase, histidinol-phosphate aminotransferase, butyrate kinase (BUK), phosphate butyryltransferase, phosphoenolpyruvate-protein kinase (PTS system enzyme I), fumarate hydratase -terminal domain of FumA E.coli), fumarate hydratase, subunit A (N-terminal domain of FumA E.coli), adenylate kinase, tryptophan synthase alpha chain, tryptophan synthase beta chain, phosphoribosylanthranilate isomerase, indole-3-glycerol phosphate synthase , anthranilate phosphoribosyltransferase, putative anthranilate synthase component II, para-aminobenzoate synthase component I, acetolactate synthase large subunit, dihydroxyacid dehydratase, isopropylmalate dehydrogenase, 3-isopropylmalate dehydratase, small subunit, 3-isopropylmalate dehydratase, large subtolacate, 2-isopropylmalate synthase small subunit, predicted transcriptional regulator, homolog of Bvg accessory factor, formate--t etrahydrofolate ligase, hypoxanthine-guanine phosphoribosyltransferase, phosphoribosylpyrophosphate synthetase, glucosamine-1-phosphate N-acetyltransferase, possible glutamate racemase, pyrroline-5-carboxylate reductase, glutamate 5-kinase, gamma-glutamyl phosphate reductase, tanucleotide subductase alphaduct subunit, NADH-dependent butanol dehydrogenase B (BDH II), NADH-dependent butanol dehydrogenase A (BDH I), possible cardiolipin synthase (phospholipase D family), alanine racemase, possible homocysteine S-methyltransferase, alcohol dehydrogenase, low specificity L-threonine aldolase, PTS system, (possibly glucose-specific) IIBC component, 6-phospho-alpha-glucosidase, PTS system, (possibly glucose-specific) IIA component, 3-oxoacyl-acyl carrier protein reductase, GMP reductase, UDP-N- acetylglucosamine enolpyruvyl transferase, lactate dehydrogenase, acetyl-CoA carboxylase alpha subunit, acetyl-CoA carboxylase beta subunit, biotin carboxyl ase, hydroxymyristoyl- (acyl carrier protein) dehydratase, biotin carboxyl carrier protein of acetyl-CoA carboxylase, 3-oxoacyl- (acyl-carrier-protein) synthase I, 3-ketoacyl-acyl carrier protein reductase, malonyl CoA-acyl carrier protein transacylase, trans-2-enoyl-ACP reductase II, 3-oxoacyl- [acyl-carrier-protein] synthase III, adenylosuccinate synthase, phosphatidylglycerophosphate synthase, dihydrodipicolinate synthase, dihydroxy-acid dehydratase, GTP cyclohydrolase I, acetolactate bethta subunit -glucosidase, pyruvate decarboxylase, alcohol dehydrogenase / acetaldehyde dehydrogenase, fructose-bisphosphate aldolase class I, mannose-specific phosphotransferase system component IIAB, mannose / fructose-specific phosphotransferase system component IIC, mannose-specific phosphotransferase coacetylase acetyl thiolase), 3-oxoacyl-acyl-carrier protein synthase, alcohol dehydrogenase / acetaldehyde dehydrogenase, butyrate-acetoacetat e CoA-transferase subunit A, butyrate-acetoacetate CoA-transferase subunit B and acetoacetate decarboxylase.

In the present invention, the metabolic network model for metabolism analysis of the butanol-producing microorganism may be characterized by including the Gene-Protein-Reaction (GPR) relationship of Table 1 below:

Table 1 GPR Relationships Used in Constructed Metabolic Networks

In another aspect, the present invention relates to a method for analyzing metabolic characteristics of a butanol-producing microorganism, characterized in that the metabolic network model is used. The butanol producing microorganism may be characterized as belonging to the genus Clostridium. The metabolic properties may be characterized as metabolic flow, wherein the metabolic flow may include the following steps:

(a) calibrating the transport scheme for available carbon and nitrogen sources in the metabolic network model; And

(b) metabolic flow analysis using the carbon and nitrogen sources.

In another aspect, the present invention relates to a method for analyzing the topology of the metabolic network model.

As used herein, topology analysis of a metabolic network refers to a metabolic network represented by a node, a metabolite as a node, and an enzyme reaction that mediates two metabolites as an edge, and used in topology theory. This method is used to find out the characteristics of the metabolic network. Edges and nodes are terms used in graph theory, where nodes represent a series of points that make up a network, and edges represent lines connecting two nodes.

The following information can be obtained through topology analysis of the metabolic network according to the present invention.

Connectivity: The number of nodes connected by edges with other nodes. The larger this value means that this metabolite is used more frequently in the metabolic network. Can be used as useful information when operating.

Network diameter: Represents the maximum value of the number of edges used to connect two arbitrary nodes and is information indicating the size of the metabolic network.

Average path length: The number of edges used to get from one node to another can vary, so pick two out of the nodes in the metabolic network. You can find a path with fewer edges. In this case, the average path length means that these values are calculated and averaged at any two nodes. The larger this value is, the more steps in converting one metabolite to another metabolite. That means you have to go through.

In the present invention, the analysis of the topology may be characterized by using the following clotor coefficient Cn :

Cn = N / M

N : Number of connected lines between nth node and neighboring nodes

M : the maximum number of possible lines between nth node and neighboring nodes

Alternatively, the following Cluster coefficient Cn can be used.

Cn = 2en / (kn (kn-1)) (for unidirectional networks)

Cn = en / (kn (kn-1)) (for bidirectional networks)

kn : number of contiguous connected nodes in nth node

en : The number of connected pairs among all neighbors of the nth node.

In another aspect, the present invention relates to a method for screening a deletion target enzyme or a gene thereof for increasing the production of a specific metabolite of a butanol producing microorganism characterized by using the metabolic network model. In one embodiment of the present invention, a metabolic network model of C. acetobutylicum , a microorganism of the genus Clostridium , was used as a butanol-producing microorganism. A schematic process is shown in FIG. 1 and the detailed description of each step is as follows.

In the established metabolic network model of C. acetobutylicum , one or more enzyme reactions are blocked and a linear scheme is applied. When the ability to produce a specific metabolite increases, the enzyme of the blocked enzyme reaction is selected as a deletion target enzyme, or The coding gene is selected as the deletion target gene. At this time, the specific metabolite may be selected from the group consisting of butanol, acetic acid, butyrate (butyrate), ethanol and acetic acid, but the following will be described as a case for increasing the butanol production capacity. The present invention may include the following steps in detail.

(1) Set the initial conditions such that the reaction rate or metabolic flow rate of the cell growth reaction equation is positive with respect to the enzyme reaction equations constituting the corrected metabolic network, and configure one or more combinations of the enzyme reaction equations one by one. Blocked enzymatic reactions with increased butanol production when blocking and linear programming were applied were selected as deletion target enzyme candidates (I).

In this case, in order to mathematically express the constructed metabolic network, all metabolites constituting the constructed metabolic network model, metabolic pathways of the metabolites and stoichiometric matrix S (stoichiometric matrix) in the metabolic pathways ( Sij, Using the stoichiometric coefficient of the i- th metabolite over time in the j- th reaction, the metabolic flow vector ( νj , the metabolic flow of the j- th metabolic reaction) can be calculated.

Here, the change in the metabolite concentration X over time can be expressed as the sum of the flows of all metabolic reactions. Assuming that there is no change in concentration of X over time, that is, under the assumption of quasi-steady state, the change in metabolite concentration over time can be defined by Equation 1 below.

Where Sν : Change in X over time, X : concentration of metabolite, t: time)

In the constructed stoichiometric matrix, the reaction equation to be optimized, ie maximized or minimized, is set as the objective function and the metabolic flow in the cell is predicted using linear programming (Kim et al., Mol Biosyst. 4 (2)). : 113, 2008). In one embodiment of the present invention, the cell growth rate was optimized by setting the enzyme reaction equation representing the cell constituents in the matrix S as the objective function.

In addition, in applying the linear programming method for metabolic flow analysis, it should be carried out on the assumption that only nutrients actually used in fermentation of this strain are supplied. In general, the complex medium used is very difficult to quantitatively identify each component thereof, and in the present invention, the present invention was fermented using a synthetic medium optimized for the present invention. Used for verification.

In the present invention, the enzyme reaction blocking simulation in the constructed metabolic network model aims at the cell growth rate in a state in which the metabolic flow of the enzyme reaction to be blocked in the metabolic flow vector ν is fixed at 0 (= ν j ). Set up as a function and run linear programming to maximize it.

(2) Solvent generation by fixing the metabolic rate or metabolic flow rate of the cell growth reaction formula to 0 with respect to the enzyme reactions constituting the C. acetobutylicum metabolism network and blocking the enzyme reactions by constructing one or several combinations When applying the linear programming method to maximize the flow value of the equation, the blocked enzyme reactions for increasing butanol production capacity are selected as secondary deletion target enzyme candidates (II) when not blocked. This is to reflect the existing experimental results that the generation of solvent is active in the ballast to the model.

(3) comparing the deletion target candidates (I) and secondary deletion target enzymes (II), which are the results obtained in the above steps (1) and (2), to select overlapping deletion target enzyme candidates as final deletion target enzyme groups, or The gene encoding this is selected as the deletion target gene. In this step, metabolic flow analysis examines the overall metabolic flow of acid and solvent generators to incorporate the best candidate deletion targets for butanol production. However, it is also possible to obtain a deletion target by performing only step (1) above.

In another aspect, the present invention relates to a method for producing a mutant microorganism having an increased ability to produce a specific metabolite, wherein the deletion target gene screened by the method is deleted in a butanol producing microorganism and a mutant microorganism produced thereby. .

The deletion of the deleted target gene may be characterized by being performed by homologous recombination, and the homologous recombination may be performed using a gene exchange vector comprising the deleted target gene. have.

In another aspect, the present invention relates to a method for producing a specific metabolite using the mutant microorganism. This comprises culturing the mutant microorganism; And recovering a specific metabolite from the culture solution.

On the other hand, in one embodiment of the present invention, the metabolic flow of the gene deletion strain using the constructed metabolic network model, as a result, appeared almost close to the actual experimental value, the metabolic network model according to the present invention is butanol It was found to be useful for predicting metabolic flow of the produced microorganisms.

Accordingly, the present invention relates to a method for predicting metabolic flow of butanol-producing microorganisms using the metabolic network model. In this case, it is preferable to use the prior planning method or the secondary planning method with the absorption rate of the substrate as a prior input value.

In addition, when predicting the metabolic flow of the solvent generator of the butanol producing microorganism using the metabolic network model, the following scheme II can be used:

Scheme II

Restrictions:

S ν = 0, ν _min ≤ ν ≤ ν _max

는 용매 생성기에서 조효소 A 전달 효소에 의한 부티르산의 흡수 속도이고;

는 용매 생성기에서 조효소 A 전달 효소에 의한 아세트산의 흡수 속도이고;

는 산 생성기에서 부티르산의 생성 속도이고;

는 산 생성기에서 아세트산의 생성 속도임.Where ν _acid is the metabolic flow vector at the acid generator; ν _sol is a metabolic flow vector in the solvent generator;

Is the rate of uptake of butyric acid by the coenzyme A transfer enzyme in the solvent generator;

Is the rate of absorption of acetic acid by the coenzyme A transfer enzyme in the solvent generator;

Is the rate of production of butyric acid in the acid generator;

Is the rate of acetic acid production in the acid generator.

Hereinafter, the present invention will be described in more detail with reference to Examples. These examples are only for illustrating the present invention, it will be apparent to those skilled in the art that the scope of the present invention is not to be construed as being limited by these examples.

In particular, the following examples are only illustrated for the method using C. acetobutylicum as a model system, it will be apparent to those skilled in the art from the disclosure herein that it is also applied to butanol producing microorganisms other than C. acetobutylicum .

Example 1: C. acetobutylicum Cell composition analysis

The information of various documents and parts without the literature information constituted cell growth essential for metabolic networks by directly analyzing samples obtained by actual fermentation or using information obtained from references with close strains.

First, the macromolecular composition of the cells borrowed the composition of B. subtilis from Bacillus sp . Microorganisms that are similar in appearance and similar to Clostridium genus (Oh et al., J. Biol. Chem. , 282: 28791-9, 2007). It is assumed here that the cells are divided into proteins, RNA, DNA, phospholipids, lipoteichoic acid, cell walls (peptidoglycan and polysaccharides), and other trace components.

The amino acid composition analysis of protein was actually obtained by fermenting C. acetobutylicum to proteomics team.

Analyzing the composition of the nucleotides that make up DNA is relatively easy because the base sequence has already been completed. However, in addition to chromosomal DNA, C. acetobutylicum has a large plasmid (megaplasmid), and the copy number is not constant. In practice, however, the effects of large plasmid numbers on DNA composition are negligible. Therefore, the composition of the DNA was calculated based on one chromosomal DNA + giant plasmid.

RNA assumes that the ratio of mRNA, tRNA, rRNA is the ratio indicated in the literature. It is assumed that the nucleotide composition of mRNA is the same as that of DNA, and tRNA and rRNA were averaged by analyzing the nucleotide sequence of the gene.

The fatty acid composition of phospholipids and the composition of polar groups are referred to in the literature (Durre, Taylor & Francis , 2005). Unlike other microorganisms, C. acetobutylicum contains lipids that have alk-1-enyl bonds with fatty aldehydes called plasmalogen. Its biosynthesis is well known in higher organisms, but it is not known in bacteria, so we only consider the number of carbons and the number of double bonds, and assume that the rest is the same as normal phospholipids.

The composition of the cell wall was obtained by direct fermentation of samples obtained by DSMZ, and other components were borrowed from other strains because they did not have a significant effect on the metabolic network.

The following cell composition was obtained from the information obtained through the above method.

TABLE 2

Macromolecule Composition Component Rate (% g / g) protein 52.84 RNA 6.55 DNA 2.6 Phospholipids 7.6 Teikosan 3.04 Cell wall 22.42 Trace ingredients 4.04

TABLE 3

DNA (chromosomal + pSOL) Nucleotide Composition (mol / mol DNA) Molecular Weight (g / mol) mmol / gDNA A 0.345 313.2 1.118 G 0.155 329.2 0.501 T 0.345 304.2 1.118 C 0.155 289.2 0.501

TABLE 4

RNA composition Nucleotide rRNA tRNA mRNA Weighted average Molecular Weight (g / mol) mmol / gRNA 75% 20% 5% A 0.284 0.205 0.345 0.271 329.2 1.050 G 0.295 0.302 0.155 0.290 345.2 1.124 T 0.212 0.244 0.345 0.225 305.2 0.873 C 0.209 0.249 0.155 0.214 306.2 0.832

TABLE 5

Total fatty acid composition in phospholipids (mol / total fatty acid or aldehyde) in phospholipids C14 0.073 C16 0.521 C16: 1 0.065 C18 0.036 C18: 1 0.102 C17: cyc 0.022 C19: cyc 0.182

TABLE 6

Amino acid composition amino acid mmol / g protein gly 1.078 ala 0.775 val 1.172 leu 0.429 ile 0.436 met 0.783 pro 0.457 phe 0.185 tyr 0.801 trp 0.043 ser 0.427 thr 0.410 asn 0.156 asp 0.156 gln 0.127 glu 0.127 cys 1.216 lys 0.336 arg 0.133 his 0.146

TABLE 7

Cell wall composition Composition mmol / g peptidoglycan N-acetylmuramate 1.152 N-acetylglucosamine 1.152 alanine 1.727 diaminopimelic acid 1.152 glutamate 1.152

TABLE 8

Teicoic acid component Composition mmol / g teichoic acid Polyglycerophosphate chain 0.518 Lysine 0.129 N-acetylglucosamine 0.129

TABLE 9

Carbohydrate Composition in Cell Walls Composition mmol / g carbohydrate Glucose 2.058 Galactose 4.115

Based on the composition, the following growth-related equations were made.

DNA: 1.118 dATP + 0.501 dCTP + 1.118 dTTP + 0.501 dGTP + 4.403 ATP-> 4.403 ADP + 4.403 Pi + 3.236 PPi + DNA

RNA: 1.05 ATP + 1.124 CTP + 0.873 UTP + 0.832 GTP-> 1.554 ADP + 1.554 Pi + 3.879 PPi + RNA

PROTEIN: 0.775 LALA + 0.133 LARG + 0.156 LASN + 0.156 LASP + 1.216 LCYS + 0.127 LGLN + 0.127 LGLU + 1.078 GLY + 0.146 LHIS + 0.436 LILE + 0.429 LLEU + 0.336 LLYS + 0.783 LMET + 0.185 LPHE + 0.457 LPRO + 0.427 LSER + 0.41 LTHR + 0.043 LTRP + 0.801 LTYR + 1.172 LVAL + 37.195 ATP-> 37.195 ADP + 37.195 Pi + PROTEIN

Phospholipids (PHOSPHOLIPID): 0.8 PE + 0.397 PG + 0.109 CDL-> PHOSPHOLIPID

Teicoic Acid (TEICHOIC ACID): 0.518 POLYGP + 0.129 LLYS + 0.129 UACGAM + 0.129 ATP-> TEICH + 0.129 UDP + 0.129 ADP + 0.129 Pi

TRACE: 0.215 NAD + 0.192 NADP + 0.199 COA + 0.321 THF + 0.313 FMN + 0.182 FAD-> TRACE

PEPTIDOGLYCAN: 1.064 UAMR + 1.064 UACGAM + 1.106 LALA + 1.106 LGLU + 1.106 DALADALA + 1.106 26DAP-M + 4.425 ATP-> PEPTIDOGLYCAN + 1.106 DALA + 1.106 UDP + 1.106 UMP + 4.425 ADP + 4.425 Pi

CARBOHYDRATE: 2.058 UDPGLC + 4.115 UDPGAL-> 6.173 UDP + CARBOHYDRATE

In addition, the cell growth scheme obtained from the composition is as follows, which was applied to the screening method according to the present invention.

BIOMASS: 0.5284 protein (PROTEIN) + 0.0655 RNA + 0.026 DNA + 0.076 phospholipid (PHOSPHOLIPID) + 0.1009 peptidoglycan (PEPTIDOGLYCAN) + 0.08 teicosane (0.0ICH) + 0.0432 CARBOHYDRATE + 0.0494 traces (TRACE) ) + 85 ATP-> BIOMASS + 85 ADP + 85 Pi

Example 2: C. acetobutylicum Metabolic network and metabolic flow analysis

In order to predict the deletion target of C. acetobutylicum for enhancing metabolite production using a computer, a genome-level metabolic network was constructed using various databases and experimental results.

KEGG (Kanehisa et al .. Nucleic Acids Res , 34: D354, 2006), TransportDB (Ren et al., PLoS Comput. Biol. , 1: e27, 2005), MetaCyc (Caspi et al. Nucleic Acids Res. , 36 (D623, 2008), an early version of the metabolic network was established, and genomic information was used to clarify the orientation of the enzyme reaction and the correlation of genes and proteins.

It has been found in the above that the contents of this database may be incomplete. This also occurs in the case of C. acetobutylicum , some examples of which will be explained.

First, the metabolism database is not able to metabolize a specific substance, but in the literature it is a normal metabolism of this substance as a substrate, such as the case of xylose. As shown in FIG. 2, when examining the sucrose metabolism pathway of C. acetobutylicum in KEGG, xylose intake is not considered. However, it has been experimentally shown that C. acetobutylicum can use xylose as a carbon source (Ounine et al., Biotechnol. Lett. , 5: 605-610, 1983). Therefore, in this case, we added a reaction to the metabolic network that we thought would be necessary for the metabolism of xylose, even if the GPR relationship was not clear.

Secondly, the GPR relationship does not exist, but from the results of our own experiments, it is too clear that the reaction or similar scheme exists. Many such cases are found in the amino acid biosynthetic pathway. The medium used for fermentation is a previously published optimized synthetic medium (Monot et al., Appl. Environ. Microbiol. , 44: 1318-1324, 1982), which uses only ammonium ions as the nitrogen source, Growth occurs normally. Therefore, it can be seen that the production of all amino acids from ammonium, and added the reaction schemes lacking the amino acid biosynthesis pathway.

The metabolic network of C. acetobutylicum consists of 502 biochemical equations and 479 metabolites. Information on the metabolic network contains the following 432 gene information. GPR relationships of the established metabolic network are shown in Table 1 above. The following predicted deletion targets were selected from these genes.

In addition, the reaction formula used as the objective function is as follows.

Growth Scheme: 0.5284 PROTEIN + 0.0655 RNA + 0.026 DNA + 0.076 PHOSPHOLIPID + 0.1009 PEPTIDOGLYCAN + 0.08 TEICH + 0.0432 CARBOHYDRATE + 0.0494 TRACE + 85 ATP-> BIOMASS + 85 ADP + 85 Pi

Solvent Formula: 2.379568182 ACTAC + 3.729151017 BUAL + ACAL + 4.729151016 NADH-> 2.379568182 ACETONE + 2.379568182 CO2 + 3.729151017 BUOH + ETOH + 4.729151016 NAD (except for individual acetone, butanol and ethanol formulas)

On the other hand, the abbreviation of the metabolite used in the metabolic network of the present invention and its formal name are summarized in Table 10 below.

Table 10 Summary of Abbreviations of Metabolites Used in Metabolic Networks

Abbreviation Official name 10FTHF 10-Formyltetrahydrofolate 12DAG 1,2-diacylglycerol 13DPG 1,3-Bisphospho-D-glycerate 1APROH (R) -1-Aminopropan-2-ol 1MAG3P 1-acylglycerol-3-phosphate 1PYR5C 1-Pyrroline-5-carboxylate 23DHDP L-2,3-Dihydrodipicolinate 23DHMB (R) -2,3-Dihydroxy-3-methylbutanoate 23DHMP (R) -2,3-Dihydroxy-3-methylpentanoate 25DRAPP 2,5-Diamino-6- (5'-phosphoribosylamino) -4-pyrimidineone 26DAP-LL LL-2,6-Diaminoheptanedioate 26DAP-M meso-2,6-Diaminoheptanedioate 2AHBUT (S) -2-Aceto-2-hydroxybutanoate 2CPR5P 1- (2-Carboxyphenylamino) -1'-deoxy-D-ribulose 5'-phosphate 2DDA7P 2-Dehydro-3-deoxy-D-arabino-heptonate 7-phosphate 2DDG6P 2-Dehydro-3-deoxy-6-phospho-D-gluconate 2DDGLCN 2-Dehydro-3-deoxy-D-gluconate 2DHP 2-Dehydropantoate 2DR1P 2-Deoxy-D-ribose 1-phosphate 2HBUT 2-Hydroxybutyrate 2IPPM 2-Isopropylmaleate 2IPPMAL (2S) -2-Isopropylmalate 2IPSUCC (2S) -2-Isopropyl-3-oxosuccinate 2OBUT 2-Oxobutanoate 2PG 2-Phospho-D-glycerate 34HPP 3- (4-Hydroxyphenyl) pyruvate 3DHQ 3-Dehydroquinate 3DHSK 3-Dehydroshikimate 3H3MOB 3-Hydroxy-3-methyl-2-oxobutanoate 3H3MOP (R) -3-Hydroxy-3-methyl-2-oxopentanoate 3HBCOA 3-Hydroxybutanoyl-CoA 3IG3P Indoleglycerol phosphate 3IPPMAL (2R, 3S) -3-Isopropylmalate 3MOB 3-Methyl-2-oxobutanoate 3MOP 3-Methyl-2-oxopentanoate 3PG 3-Phospho-D-glycerate 3PHP 3-Phosphonooxypyruvate 3PSME 5-O- (1-Carboxyvinyl) -3-phosphoshikimate 4ABUT 4-Aminobutyrate 4H2KPM 4-Hydroxy-2-ketopimelate 4MOP 4-Methyl-2-oxopentanoate 4PASP 4-Phospho-L-aspartate 4PCYS N-((R) -Pantothenoyl) -L-cysteine 4PPAN D-4'-Phosphopantothenate 4PPCYS (R) -4'-Phosphopantothenoyl-L-cysteine 4R5AU 4- (1-D-Ribitylamino) -5-aminouracil 5AOP 5-Aminolevulinate 5APRBU 5-Amino-6- (5'-phosphoribosylamino) uracil 5 APRU 5-Amino-6- (5'-phosphoribitylamino) uracil 5FTHF 5-Formyltetrahydrofolate 5METRIB 5-Methylthio-D-ribose 5MTHF 5-methyltetrahydrofolate 5PRDMBZ N1- (5-Phospho-alpha-D-ribosyl) -5,6-dimethylbenzimidazole AC Acetate  AC (Ext) Acetate (Extracellular) ACACP Acetyl- [acyl-carrier protein] ACAL Acetaldehyde ACBA Adenosyl cobinamide ACBAP Adenosyl cobinamide phosphate ACBRNDA Adenosyl cobyrinate a, c diamide ACBRNHA Adenosyl cobyrinate hexaamide ACCOA Acetyl-CoA ACETOIN Acetoin ACETOIN (Ext) Acetoin (Extracellular) ACETONE Acetone ACETONE (Ext) Acetone (Extracellular) ACGAM (Ext) N-Acetyl-D-glucosamine (Extracellular) ACGAM1P N-Acetyl-D-glucosamine 1-phosphate ACGAM6P N-Acetyl-D-glucosamine 6-phosphate ACGLU N-Acetyl-L-glutamate ACGLU5P N-Acetyl-L-glutamate 5-phosphate ACGLU5SA N-Acetyl-L-glutamate 5-semialdehyde ACHMS O-Acetyl-L-homoserine ACLAC 2-Acetolactate ACORN N-Acetylornithine ACP Acyl-carrier protein ACSER O-Acetyl-L-serine ACTAC Acetoacetate ACTACCOA Acetoacetyl-CoA ACTP Acetyl phosphate ADE Adenine ADHHP Amino-7,8-dihydro-4-hydroxy-6- (diphosphooxymethyl) pteridine ADN Adenosine ADP Adenosine 5'-diphosphate ADPGLC ADP-glucose AGDPCBA Adenosine-GDP-cobinamide AHCYS S-Adenosyl-L-homocysteine AHHMDHP 2-Amino-4-hydroxy-6-hydroxymethyl-7,8-dihydropteridine AHTHDH 2-Amino-4-hydroxy-6- (erythro-1,2,3-trihydroxypropyl) dihydropteridine triphosphate AICAR 1- (5'-Phosphoribosyl) -5-amino-4-imidazolecarboxamide AIR Aminoimidazole ribotide AKG 2-Oxoglutarate AMET S-adenosyl-L-methionine AMETA S-Adenosylmethioninamine AMP Adenosine 5'-monophosphate ANTH Anthranilate APROHP D-1-Aminopropan-2-ol O-phosphate APS Adenylyl sulfate ARBZL N1- (alpha-D-ribosyl) -5,6-dimethylbenzimidazole ARBZL5P N1- (5-Phospho-alpha-D-ribosyl) -5,6-dimethylbenzimidazole ARGSUC N- (L-Arginino) succinate ASPSA L-Aspartate 4-semialdehyde ATP Adenosine 5'-triphosphate bALA beta-Alanine bDG1P beta-D-Glucose 1-phosphate bDG6P beta-D-Glucose 6-phosphate bDGLC beta-D-Glucose bDGLC (Ext) beta-D-Glucose (Extracellular)  BIOMASS Biomass BU Butyrate BU (Ext) Butyrate (Extracellular) BUAL Butyraldehyde BUCOA Butyryl-coa BUOH 1-Butanol BUOH (Ext) 1-Butanol (Extracellular) BUP Butyryl phosphate C140-ACP C14: 0- [acyl-carrier protein] C160-ACP C16: 0- [acyl-carrier protein] C161-ACP C16: 1- [acyl-carrier protein] C17CYC-ACP C17: cyclic- [acyl-carrier protein] C180-ACP C18: 0- [acyl-carrier protein] C181-ACP C18: 1- [acyl-carrier protein] C19CYC-ACP C19: cyclic- [acyl-carrier protein] CACO Cobamide coenzyme CARBO Carbohydrate CBASP N-Carbamoyl-L-aspartate CBP Carbamoyl phosphate CBRN Cobyrinate CBRNDA Cob (II) yrinate a, c diamide CDHPRCR6 Cobalt-precorrin 6B CDL Cardiolipin CDP Cytidine 5'-diphosphate CDP-DAG CDP-Diacylglycerol CDPMERY2P 2-Phospho-4- (cytidine 5'-diphospho) -2-C-methyl-D-erythritol CDPMERYTH 4- (Cytidine 5'-diphospho) -2-C-methyl-D-erythritol CDV Cadverine CHOR Chorismate CIT Citrate CLB (Ext) Cellobiose (Extracellular) CMP Cytidine-5'-monophosphate CO2 Carbon dioxide CO2 (Ext) Carbon dioxide (extracellular) COA Coenzyme a COBALT Cobalt ion CORR Corrinoid CPPPG3 Coproporphyrinogen III CPRCR2 Cobalt-precorrin 2 CPRCR3 Cobalt-precorrin 3 CPRCR4 Cobalt-precorrin 4 CPRCR5A Cobalt-precorrin 5A CPRCR5B Cobalt-precorrin 5B CPRCR6 Cobalt-precorrin 6 CPRCR7 Cobalt-precorrin 7 CPRCR8 Cobalt-precorrin 8 CRTCOA Crotonoyl-coa CTP Cytidine 5'-triphosphate CYST Cystathionine dADN Deoxyadenosine dADP 2'-Deoxyadenosine 5'-diphosphate DALA D-Alanine DALADALA D-Alanyl-D-Alanine dAMP 2'-Deoxyadenosine 5'-phosphate DAPTP 2,5-Diaminopyrimidine nucleoside triphosphate  DATHAO 2,5-Diamino-6- (5'-triphosphoryl-3 ', 4'-trihydroxy-2'-oxopentyl) -amino-4-oxopyrimidine dATP 2'-Deoxyadenosine 5'-triphosphate DB4P 3,4-Dihydroxy-2-butanone 4-phosphate DCAMP N6- (1,2-Dicarboxyethyl) -AMP dCDP 2'-Deoxycytidine 5'-diphosphate dCMP 2'-Deoxycytidine 5'-monophosphate dCTP 2'-Deoxycytidine 5'-triphosphate dGDP 2'-Deoxyguanosine 5'-diphosphate DGLU D-Glutamate dGTP 2'-Deoxyguanosine 5'-triphosphate DHAP Dihydroxyacetone phosphate DHF Dihydrofolate DHNP 2-Amino-4-hydroxy-6- (D-erythro-1,2,3-trihydroxypropyl) -7,8-dihydropteridine DHNPP Dihydroneopterin phosphate DHOR-S (S) -Dihydroorotate DHPT Dihydropteroate dINS Deoxyinosine DMBZID Dimethylbenzimidazole DMLZ 6,7-Dimethyl-8- (1-D-ribityl) lumazine DMMOHCOA 2,6-Dimethyl-5-methylene-3-oxo-heptanoyl-CoA DMPP Dimethylallyl diphosphate DNA DNA DNAD Deamino-NAD + DPCOA Dephospho-CoA DPHE D-Phenylalanine DRIB D-Ribose DRU5P D-Ribulose 5-phosphate dTDP Deoxythymidine 5'-diphosphate dTMP Deoxythymidine 5'-phosphate dTTP Deoxythymidine 5'-triphosphate dUDP 2'-Deoxyuridine 5'-diphosphate dUMP 2'-Deoxyuridine 5'-phosphate dUTP 2'-Deoxycytidine 5'-triphosphate DXU5P D-Xylulose 5-phosphate DXYL D-Xylose DXYL (Ext) D-Xylose (Extracellular) DXYLU D-Xylulose dXYLU5P 1-Deoxy-D-xylulose 5-phosphate E4P D-Erythrose 4-phosphate EIG3P D-erythro-1- (Imidazol-4-yl) glycerol 3-phosphate ETOH Ethanol ETOH (Ext) Ethanol (Extracellular) F1P D-Fructose 1-phosphate F6P beta-D-Fructose 6-phosphate FAD Flavin adenine dinucleotide FAPTP Formamidopyrimidine nucleoside triphosphate Fd (Ox) Oxidized ferredoxin Fd (Red) Reduced ferredoxin FDP beta-D-Fructose 1,6-bisphosphate Fe2 Ferrous ion FGAM 2- (Formamido) -N1- (5'-phosphoribosyl) acetamidine FGAR 5'-Phosphoribosyl-N-formylglycinamide FMN Flavin mononucleotide  FOL Folate FORM Formate FORM (Ext) Formate (Extracellular) FPRICA 1- (5'-Phosphoribosyl) -5-formamido-4-imidazolecarboxamide FRDP trans, trans-Farnesyl diphosphate FRU D-Fructose FRU (Ext) D-Fructose (Extracellular) FUM Fumarate G1P alpha-D-Glucose 1-phosphate G6P alpha-D-Glucose 6-phosphate GA3P D-Glyceraldehyde 3-phosphate GAL D-Galactose GAL (Ext) D-Galactose (Extracellular) GAL1P alpha-D-Galactose 1-phosphate GAL6P D-Galactose6-phosphate GAM1P D-Glucosamine 1-phosphate GAM6P D-Glucosamine 6-phosphate GAR 5'-Phosphoribosylglycinamide GDP Guanosine 5'-diphosphate GDPoRHAM GDP-4-dehydro-6-deoxy-L-mannose GDPRHAM GDP-6-deoxy-L-mannose GGRDP Geranylgeranyl diphosphate GLC Alpha-D-glucose GLC (Ext) Alpha-D-glucose (Extracellular) GLU1SA L-Glutamate 1-semialdehyde GLU5P L-Glutamyl 5-phosphate GLU5SA L-Glutamate 5-semialdehyde GLY Glycine GLY (Ext) Glycine (Extracellular) GLYALD D-Glyceraldehyde GLYC Glycerol GLYC (Ext) Glycerol (Extracellular) GLYC3P sn-Glycerol 3-phosphate GLYCAC D-Glycerate GLYCALD Glycolaldehyde GLYCALD (Ext) Glycolaldehyde (Extracellular) Glycogen Glycogen GMP Guanosine 5'-phosphate GRDP Geranyl diphosphate GTH (Ox) Glutathione disulfide GTH (Red) Glutathione GTP Guanosine 5'-triphosphate GUA Guanine H2 Hydrogen H2 (Ext) Hydrogen (Extracellular) H2O2 Hydrogen Peroxide H2O2 (Ext) Hydrogen Peroxide (Extracellular) HCO3 Bicarbonate HDMHCOA 3-Hydroxy-2,6-dimethyl-5-methylene-heptanoyl-CoA HETHMPP 2- (alpha-Hydroxyethyl) thiamine diphosphate HGBRN Hydrogenobyrinate HIPCOA 2-Hydroxy-4-isopropenylcyclohexane-1-carboxyl-CoA HISP L-Histidinol phosphate HISTD L-Histidinol HISTDAL L-Histidinal  HMB4DP 1-Hydroxy-2-methyl-2-butenyl 4-diphosphate HMBIL Hydroxymethylbilane HOR Hordenine HPYR Hydroxypyruvate HXAN Hypoxanthine ICIT Isocitrate IMACP 3- (Imidazol-4-yl) -2-oxopropyl phosphate IMP Inosine 5'-monophosphate INDOLE Indole INS Inosine IPCHCCOA 4-Isopropenyl-2-oxy-cyclohexanecarboxyl-CoA IPDP Isopentenyl diphosphate LAC (S) -Lactate LAC (Ext) (S) -Lactate (Extracellular) LALA L-Alanine LALA (Ext) L-Alanine LARAB L-Arabinose LARAB (Ext) L-Arabinose (Extracellular) LARG L-Arginine LARG (Ext) L-Arginine (Extracellular) LASN L-Asparagine LASN (Ext) L-Asparagine (Extracellular) LASP L-Aspartate LASP (Ext) L-Aspartate (Extracellular) LCITR L-Citrulline LCTS (Ext) Lactose (Extracellular) LCTS6P Lactose 6-phosphate LCYS L-Cysteine LCYS (Ext) L-Cysteine (Extracellular) LGLN L-Glutamine LGLN (Ext) L-Glutamine (Extracellular) LGLU L-Glutamate LGLU (Ext) L-Glutamate (Extracellular) LHCYS L-Homocysteine LHIS L-Histidine LHIS (Ext) L-Histidine (Extracellular) LHMS L-Homoserine LILE L-Isoleucine LILE (Ext) L-Isoleucine (Extracellular) LLEU L-Leucine LLEU (Ext) L-Leucine (Extracellular) LLYS L-Lysine LLYS (Ext) L-Lysine (Extracellular) LMET L-Methionine LMET (Ext) L-Methionine (Extracellular) LORN L-Ornithine LPHE L-Phenylalanine LPHE (Ext) L-Phenylalanine (Extracellular) LPRO L-Proline LPRO (Ext) L-Proline (Extracellular) LPSER O-Phospho-L-serine LRBL L-Ribulose LRU5P L-Ribulose 5-phosphate LSER L-Serine LSER (Ext) L-Serine (Extracellular)  LTHR L-Threonine LTHR (Ext) L-Threonin (Extracellular) LTRP L-Tryptophan LTRP (Ext) L-Tryptophan (Extracellular) LTYR L-Tyrosine LTYR (Ext) L-Tyrosine (Extracellular) LVAL L-Valine LVAL (Ext) L-Valine (Extracellular) MAL (S) -Malate MAL (Ext) (S) -Malate (Extracelllular) MALACP Malonyl- [acyl-carrier protein] MALCOA Malonyl-CoA MALT Maltose MALT (Ext) Maltose (Extracellular) MALT6P Maltose 6'-phosphate MAN (Ext) D-Mannose (Extracellular) MAN6P D-Mannose 6-phosphate MECORR Methylcorrinoid MERYcDP 2-C-Methyl-D-erythritol 2,4-cyclodiphosphate MERYTH4P 2-C-Methyl-D-erythritol 4-phosphate METADN 5'-Methylthioadenosine METHF 5,10-Methenyltetrahydrofolate MLHIS N (pi) -Methyl-L-histidine MLTHF 5,10-Methylenetetrahydrofolate MNL (Ext) Mannitol MNL1P D-Mannitol 1-phosphate MTNAL Myrtenal MTNOL Myrtenol MTYRAM N-Methyltyramine N2 Nitrogen N2 (Ext) Nitrogen (Extracellular) NA Nicotinic acid NA (Ext) Nicotinic acid (Extracellular) NAD NAD + NADH NADH NADP NADP + NADPH NADPH NAMN Nicotinate D-ribonucleotide NAMNs Nicotinate D-ribonucleoside NH3 Ammonium ion NH3 (Ext) Ammonium ion (Extracellular) NMN Nicotinamide D-ribonucleotide NO2 Nitrite NO2 (Ext) Nitrite (Extracellular) O2 Oxygen OAA Oxaloacetate OROT Orrotate OROT5P Orotidine 5'-phosphate PA Phosphatidate PABA 4-Aminobenzoate PABA (Ext) 4-Aminobenzoate (Extracellular) PAN Pantetheine PAN4P Pantetheine 4'-phosphate PANT (R) -Pantoate PAP Adenosine 3 ', 5'-bisphosphate  PAPS 3'-Phosphoadenylyl sulfate PE Phosphatidylethanolamine PEP Phosphoenolpyruvate PEPTIDO Peptidoglycan PG Phosphatidylglycerol PGP Phosphatidylglycerophosphate PHOM O-Phospho-L-homoserine PHPYR Phenylpyruvate Pi Inorganic phosphate Pi (Ext) Inorganic phosphate (Extracellular) PLIPID Phospholipid PNTO Pantothenate POLYGP Polyglycerol phosphate PPBNG Porphobilinogen PPHN Prephenate PPi Pyrophosphate PPPG9 Protoporphyrinogen IX PRAIC 1- (5-Phospho-D-ribosyl) -5-amino-4-imidazolecarboxylate PRAM 5-Phosphoribosylamine PRAN N- (5-Phospho-D-ribosyl) anthranilate PRBAMP Phosphoribosyl-AMP PRBATP Phosphoribosyl-ATP PRCR2 Precorrin 2 PRCR3B Precorrin 3B PRCR4 Precorrin 4 PRCR5 Precorrin 5 PRCR6A Precorrin 6A PRCR6B Precorrin 6B PRCR8 Precorrin 8 PRFP 5- (5-Phospho-D-ribosylaminoformimino) -1- (5-phosphoribosyl) -imidazole-4-carboxamide PRLP N- (5'-Phospho-D-1'-ribulosylformimino) -5-amino-1- (5 ''-phospho-D-ribosyl) -4-imidazolecarboxamide PROCOA Propionyl-coa ProDS Protein disulfide ProDTH Protein dithiol PROP Propionate PROP (Ext) Propionate (Extracellular) PROPP Propionyl phosphate PROTEIN Protein PRPP 5-Phospho-alpha-D-ribose 1-diphosphate PS Phosphatidylserine PTRC Putrecine PYR Pyruvate PYR (Ext) Pyruvate (Extracellular) QULN Pyridine-2,3-dicarboxylate R1P D-Ribose 1-phosphate R5P D-Ribose 5-phosphate RHCYS S- (5-deoxy-D-ribos-5-yl) -L-homocysteine RIBFLA Riboflavin RNA RNA S Sulfide S7P D-Sedoheptulose 7-phosphate SAICAR 1- (5'-Phosphoribosyl) -5-amino-4- (N-succinocarboxamide) -imidazole  SHCL Sirohydrochlorin SHEME Siroheme SKM Shikimate SKM3P Shikimate 3-phosphate SL26DA N-Succinyl-LL-2,6-diaminoheptanedioate SL2A6O N-Succinyl-2-L-amino-6-oxoheptanedioate SO3 Sulfite SO4 Sulfate SO4 (Ext) Sulfate (Extracellular) SPERMD Spermidine SUC6P Sucrose 6-phosphate SUCC Succinate SUCCOA Succinyl-CoA SUCCSA Succinate semialdehyde SUCHMS O-Succinyl-L-homoserine SUCR (Ext) Sucrose (Extracellular) TAG6P D-Tagatose 6-phosphate TAGDP D-Tagatose 1,6-bisphosphate TDPDHdGLC dTDP-4-dehydro-6-deoxy-alpha-D-glucose TDPGAL dTDP-galactose TDPGLC dTDP-glucose TDPoRHAM dTDP-4-dehydro-6-deoxy-L-mannose TDPRHAM dTDP-6-deoxy-L-mannose TEICH Teichoic acid THDP 2,3,4,5-Tetrahydrodipicolinate THF Tetrahydrofolate THMPP Thiamin pyrophosphate TRACE Trace components TRD (Ox) Oxidized thioredoxin TRD (Red) Reduced thioredoxin UACCG UDP-N-acetyl-3- (1-carboxyvinyl) -D-glucosamine UACGAM UDP-N-acetyl-D-glucosamine UAMR UDP-N-acetylmuramate UDCPDP Undecaprenyl diphosphate UDP Uridine 5'-diphosphate UDPGAL UDP-D-galactose UDPGLC UDP-D-glucose UMP Uridine 5'-monophosphate UPPG3 Uroporphyrinogen III UREA Urea UREA (Ext) Urea (Ext) UTP Uridine 5'-triphosphate XAN Xanthine XANT Xanthosine XMP Xanthosine 5'-phosphate XOL Xylitol

In the metabolic network constructed above, metabolic flow analysis was performed on 479 metabolites of C. acetobutylicum using MetaFluxNet (Lee et al., Bioinformatics , 19: 2144, 2003) and GAMS.

Metabolic flow analysis of the major metabolic pathways of C. acetobutylicum is shown in FIG.

Example 3 Overall Characterization of the Constructed Metabolic Network

The constructed metabolic network was analyzed using NetworkAnalyzer, a network characterization tool. By analyzing these metabolic characteristics, it is possible to determine whether there are other parts in addition to the deletion target candidate group found by metabolic flow analysis. Various analyzes are possible by using this tool. In this embodiment, a single parameter analysis result will be described. The results are shown in FIG. 4, and a description of clustering coefficients is as follows.

Cluster Coefficient: For a network configured in a single direction, the cluster coefficient Cn for the nth node is defined as follows.

Cn  = 2 en / ( kn ( kn -One))

kn : number of contiguous connected nodes in nth node

en : the number of connected pairs among all neighbors of the nth node

Here, the node is a metabolite included in the metabolic network. In FIG. 4, a metabolic network composed of only a carbon source and a nitrogen source necessary for simulation is analyzed, and the number is smaller than that of the metabolic network of the second embodiment.

For a bidirectional network, use the following definition:

Cn = en / ( kn ( kn -1))

For both cases, the cluster coefficient can be expressed as

N / M

N : Number of connected lines between nth node and neighboring nodes

M : the maximum number of possible lines between nth node and neighboring nodes

Therefore, the cluster coefficient always has a value greater than or equal to 0 and less than or equal to 1.

Example  4: Gene deletion strain using genome-level metabolic network Metabolic flow  prediction

Using the constructed metabolic network, the metabolic flow of the wild-type strain and the metabolic flow of the PJC4BK strain, which is a strain that deletes butyrate kinase, were simulated and compared with actual experimental values.

In order to more accurately simulate the distinction between the acid generator and the solvent generator, the characteristics of the solvent-generating strains, a modification of the previously announced minimaation of metabolic adjustment (MOMA) was introduced. The metabolic flow of the acid generator was calculated by maximizing cell growth using the conventional linear programming method. The metabolic flow of the solvent generator was assumed to be the same as the gene deletion strain of the acid generator cell and modified MOMA. (Segre et al. Proc. Nat.l Acad. Sci . 99: 15112-15117. 2002) Since the growth of the cells occurs little in the solvent generator, the growth rate of the cells is assumed to be zero. do.

In addition, in the solvent generator, organic acids generated in the acid generator are reabsorbed by coenzyme A transferase (Ctf) to be used for solvent production. A term was introduced to more accurately simulate the absorption rate of acetic acid and butyric acid. (Desai et al. Metab . Eng . 1: 206-213. 1999). The overall process is expressed as follows.

minimization:

Restrictions:

S ν = 0, ν _min ≤ ν ≤ ν _max

The definition of each term is as follows.

ν _acid : metabolic flow vector in acid generator

ν _sol : metabolic flow vector in the solvent generator

: 용매 생성기에서 조효소 A 전달 효소에 의한 부티르산의 흡수 속도

: Absorption Rate of Butyric Acid by Coenzyme A Transfer Enzyme in Solvent Generator

: 용매 생성기에서 조효소 A 전달 효소에 의한 아세트산의 흡수 속도

: Absorption Rate of Acetic Acid by Coenzyme A Transfer Enzyme in Solvent Generator

: 산 생성기에서 부티르산의 생성 속도

: Rate of butyric acid production in acid generator

: 산 생성기에서 아세트산의 생성 속도

: Rate of Formation of Acetic Acid in Acid Generator

Using the metabolic network model of the present invention to simulate the metabolic flow of wild-type strains and the metabolic flow of PJC4BK strain, which is a strain that deletes butyrate kinase, and compared with the actual experimental value, as shown in Figure 5, The results predicted using the metabolic network model according to the present invention were found to be close to the actual experimental values. That is, the metabolic network model according to the present invention was found to be useful for predicting metabolic flow of butanol-producing microorganisms.

As described above in detail a specific part of the content of the present invention, for those skilled in the art, such a specific description is only a preferred embodiment, which is not limited by the scope of the present invention Will be obvious. Thus, the substantial scope of the present invention will be defined by the appended claims and their equivalents.

FIG. 1 is a schematic diagram illustrating a process of constructing a metabolic network from a genomic information of a strain to perform metabolic flow analysis based on genomic information and searching for a deletion target gene or a deletion target enzyme through gene deletion simulation.

2 is a schematic showing that xylose isomerase is not present in C. acetobutylicum on KEGG for xylose metabolism.

3 is a diagram showing the reaction rate of the major metabolic pathways given the uptake rate of glucose as a result of metabolic flow analysis using the established metabolic network.

4 shows single parameter values obtained by analyzing the constructed metabolic network.

5 is a result of predicting the metabolic flow of the solvent generator and the acid generator using the constructed metabolic network.

Claims (21)

Metabolic network model for metabolic characterization of butanol producing microorganisms, including enzymatic reaction involving the following enzymes: Alcohol dehydrogenase, butanol dehydrogenase, butyryl coenzyme A dehydrogenase, butyryl-CoA dehydrogenase, crotonase, acetyl coenzyme A acetyltransferase ), 3-hydroxybutyryl coenzyme A dehydrogenase (3-hydroxybutyryl-CoA dehydrogenase) and hydrogenase. The metabolic network model for metabolic characterization of butanol-producing microorganisms according to claim 1, comprising an enzyme reaction involving the following enzymes: D-3-phosphoglycerate dehydrogenase, aspartate-semialdehyde dehydrogenase, deoxycytidine triphosphate deaminase, orotate phosphoribosyltransferase, phosphatidylserine decarboxylase, D-3-phosphoglycerate dehydrogenase, ketol-acid reductoisomerase, ferredoxin-nitrite reductase, O-thidenkinylrinesasease , sulfate adenylyltransferase subunit 2, adenylylsulfate kinase / sulfate adenylyltransferase subunit 1, PTS system, mannitol-specific IIBC component (gene MtlA), PTS system, mannitol-specific IIA domain (Ntr-type) (gene MltF), mannitol-1-phosphate 5-dehydrogenase, glucosamine--fructose-6-phosphate aminotransferase (isomerizing), glucosamine-6-phosphate isomerase (glucosamine-6-phosphate), N-acetylglucosamine-6-phosphate deacetylase (gene nagA), prephenate dehydrotase (pheA), 1-phosphofructokinase (fructoso 1-phosphate kinase), nitrogenase iron protein (nitrogenase component II) gene nifH, nitrogenase molybdenum-iron protein, alpha chain (nitrogenase componen t I) gene nifD, nitrogenase molibdenum-iron protein, beta chain, gene nifK, phosphoserine phosphatase related protein, L-lactate dehydrogenase, 2-isopropylmalate synthase, aspartate ammonia-lyase (aspartase) gene ansB (aspA), aspartate kinase, cytosine / guanine deaminase related protein, ornithine carbomoyltransferase, PTS cellobiose-specific component IIA, PTS system, cellobiose-specific component BII, beta-glucosidase, PTS cellobiose-specific component IIC, cystathionine gamma-synthase, cystathionine beta-lyase, dedol phosphogluconate al kdgA), 2-keto-3-deoxygluconate kinase (gene kdgK), fusion: PTS system, beta-glucosides specific IIABC component, Fructokinase, sucrase-6-phosphate hydrolase (gene sacA), oxygen-sensitive ribonucleoside-triphosphate reductase nrdD, Phosphomannomutase, alanine racemase, UDP-N-acetylenolpyruvoylglucosamine reductase (murB), 6-phosphofructokinase, pyruvate kinase (pykA), Dihydroorotase, PTS system, maltose-specific enzyme IIBC component, malt ose-6'-phosphate glucosidase (glvA), phosphoenolpyruvate synthase (gene pps), malate dehydrogenase, aspartate semialdehyde dehydrogenase (gene asd), PTS system, glucose-specific IIABC component, cobalamine-dependent methionine synthase I (methyltransferase and cobalamine-binding domain ), diaminohydroxyphosphoribosylaminopyrimidine deaminase / 5-amino-6- (5-phosphoribosylamino) uracil reductase, riboflavin synthase alpha chain, riboflavin biosynthes protein RIBA (GTPcyclohydrolase / 3,4-dihydroxy-2-butanone 4-phosphate synthase), riboflavin synthase beta chain , diaminopimelate decarboxilase (lisA), L-serine dehydratase, beta chain, L-serine dehydratase, alpha chain, phosphatidylserine synthase, ammonium transporter (membrane protein nrgA), serine acetyltransferase, glyceraldehyde 3-phosphate dehydrogenase, gene gapC, phosphoglycerate phosphate isomerase (TIM), 2,3-bisphosphoglycerate-independent phosphoglycerate mutase gene, Enolase, ribose 5-phosphate isomerase RpiB, NADP-spe cific glutamate dehydrogenase, NADPH-dependent glutamate synthase beta chain, glycerol uptake facilitator protein (permease), phosphatidylserine synthase, nucleoside-diphosphate-sugar epimerase (UDP-glucose 4-epimerase), phosphatidylserine decarboxylase, 3-oxoacylyl-ac protein] synthase III, phosphoribosylpyrophosphate synthetase, fructose-bisphosphate aldolase, glucan phosphorylase, thioredoxine reductase, adenine deaminase, phospho-2-dehydro-3-deoxyheptonate aldolase, prephenate dehydrogenase, 3-dehydroquinate synthetase, 5-enolpyruatelshikimate chorismate synthase, fusion: chorismate mutase and shikimate 5-dehydrogenase, shikimate kinase, 3-dehydroquinate dehydratase II, cystathionine gamma-synthase, cysteine synthase, ATP phosphoribosyltransferase, histidinol dehydrogenase, imidazoleglycerol-phosphate dehydratylformamide, hydrochloride ribonucleotide (ProFAR) isomerase, imidazoleglycerol-phos phate synthase cyclase, phosphoribosyl-AMP cyclohydrolase, phosphoribosyl-ATP pyrophosphohydrolase, Transketolase, aconitase A, isocitrate dehydrogenase, argininosuccinate synthase, argininosuccinate lyase, pyruvate-formate lyase, 1-acyl-sylserinefergenase synthase, aspartate aminotransferase, nicotinic acid phosphoribosyltransferase, superfamily I DNA helicase (rep-like helicase), P-loop kinase (uridine kinase family), nicotinate-nucleotide pyrophosphorylase, aspartate oxidase, quinolinate synthase, pyruvate kinase, ribonucleotide reductase dependent, NH (3) -dependent NAD (+) synthetase, Arginase, beta-glucosidase family protein, beta-glucosidase family protein, GlpX-like protein (Fructose-1,6-bisphosphatase related protein), 5-formyltetrahydrofolate cyclo-ligase , anaerobic ribonucleotide reductase, deoxyuridine 5'triphosphate nucleotidohydrolase (DUPTase), chorismate mutase PheB of B.subtilis ortholog, homoserine kinase (thrB), predicted nucleotidyltransferases of NarD / TagD family (N-term. domain) (yqeJ ortholog), diacylglycerol kinase (dgkA) fused to phosphatase B domain (pgpB), glycerol uptake facilitator protein (GLPF), glycerol kinase (GLPK), ribulose-5-phosphate 4-epimerase family protein, L-arabinose isomerase , sugar kinase, possible xylulose kinase, L-arabinose isomerase, Transaldolase, Transketolase (TKT), aldose-1-epimerase, phosphotransferase system IIC component (possibly N-acetylglucosamine-specific), PTS system (N-acetylglucosamine-specific IIA component, putative), histidinol-phosphate aminotransferase, cobalamin biosynthesis enzyme CobT, phosphoribosylcarboxyaminoimidazole (NCAIR) mutase, phosphoribosylaminoimidazolesuccinocarboxamide (SAICAR) synthase, glutamine phosphoribosylpyrophosphate amidotransferase, phosphoribosylaminolythe- diasease phosphorase ligase, beta-glucosidase, UDP-glucose 4-epimerase, ribose 5-phosphate iso merase, PTS system, fructose (mannose) -specific IIA component, PTS system, fructose (mannose) -specific IIB, PTS system, fructose (mannose) -specific IIC, PTS system, fructose (mannose)-specific IID, branched-chain -amino-acid transaminase (ilvE), Fructokinase, fructose-1,6-bisphosphatase, malic enzyme, malate dehydrogenase (oxaloacetate-decarboxylating), phosphoserine phosphatase family enzyme, bifunctional enzyme phosphoribosylformylglycinamidine (FGAM) synthase (synthetase amidotransase domain / glutamine domain / glutamine domain , aspartate ammonia-lyase, glycogen phosphorylase, large subunit of NADH-dependent glutamate synthase, small subunit of NADPH-dependent glutamate synthase, periplasmic phosphate-binding protein, phosphate permease, permease component of ATP-dependent phosphate uptake system, ATPase component of ABC -type phosphate transport system, glycerol 3-phosphate dehydrogenase, L-asparaginase, guanylate kinase, YLOD B.subtilis ortholog, flavoprotein involved in panthothenate metabolism, YLO I B.subtilis ortholog, pentose-5-phosphate-3-epimerase, phosphopantetheine adenylyltransferase, phosphate acetyltransferase, acetate kinase, nicotinic acid phosphoribosyltransferase, NH (3) -dependent NAD (+) synthase (nadE) fused to amidohydrolasedomain, uridylate kinase CDP-diglyceride synthetase, riboflavin kinase / FAD synthase, Aspartokinase, phosphatidylglycerophosphate synthase, aspartate aminotransferase, phosphocarrier protein (Hpr), adenylosuccinate lyase, homoserine trans-succinylase, cytidylate kinase, 3-acoxyylase- nucleoside phosphorylase, Phosphopentomutase, predicted kinase, tetrahydrofolate dehydrogenase / cyclohydrolase (FolD), nucleoside phosphorylase, cation transport P-type ATPase, phosphoserine phosphatase family enzyme, pyruvate: ferredoxin oxidoreductase, cysteine synthase / cystacosease A pyrophosphorylase, ADP-glucose pyrophosphorylase, glycogen synthase (glgA), N-terminal domain of asparagine synt hase, UDP-glucose pyrophosphorylase, glycine hydroxymethyltransferase, adenine phosphoribosyltransferase (Apt), UDP-glucose 4-epimerase, UTP-glucose-1-phosphate uridylyltransferase, dihydrodipicolinate synthase, dihydrodipicolinate reductase, PLP-dependent aminotransferolinate acetylornithine aminotransferase, acetylglutamate kinase, N-acetyl-gamma-glutamyl-phosphate reductase, amino-acid N-acetyltransferase / glutamate N-acetyltransferase, folylpolyglutamate synthase, 2-oxoacid ferredoxin oxidoreductase beta subunit, 2-oxoacid ferredoxin subunitase xunitase , transcriptional regulators of NagC / XylR family, beta-phosphoglucomutase, diaminopimelate epimerase, possible 3-ketoacyl-acyl carrier protein reductase, carbamoylphosphate synthase large subunit, carbamoylphosphate synthase small subunit, dihydroorotate dehydrogenase, orotidine-5'-phosphate decarboxybase, subunit, asp artate carbamoyltransferase catalytic subunit, glutamine synthetase type III, pyruvate carboxylase (PYKA), glucose-6-phosphate isomerase, sugar kinase, ribokinase family, trehalose / maltose hydrolase (phosphorylase), GMP synthase, IMP dehydrogenase, 3-hydroxybutyryl-CoA dehydrogen electron transfer flavoprotein alpha-subunit, electron transfer flavoprotein beta-subunit, butyryl-CoA dehydrogenase, 3-hydroxybutyryl-CoA dehydratase, deacethylase / dipeptidase / desuccinylase family of Zn-dependenthydrolases, putative histidinol-phosphatase, O-acetylhomoserine (thiol) -lyase , Acylphosphatases (ACYP), PLP-dependent aminotransferase, glycerate kinase, galactose-1-phosphate uridylyltransferase, S-adenosylmethionine synthetase, UDP-N-acetylglucosamine 1-carboxyvinyltransferase, acetyl-CoA acetyltransferase, deoxycytidylate deaminate isomerase 5-Ripase ), fusion of alpha-glucosidase (family 31 glycosyl hydrolase), CTP synthase (UTP-ammonia lyase), D-alanine-D-alanine ligase, ke topantoate hydroxymethyltransferase, pantoate--beta-alanine ligase, aspartate 1-decarboxylase, mannose-6 phospate isomerase, dihydropteroate synthase, dihydroneopterin aldolase fused to 7,8-dihydro-6-hydroxymethylpterin-pyrophosphokinase, ketopantoate reductase, PanE / Apb conprotein fron YGAG family, predictedmetal-dependent enzyme, 3-phosphoserine aminotransferase (Possible phosphoglycerate dehydrogenase), tagatose-6-phosphate kinase, galactose-6-phosphate isomerase, galactose-6-phosphate isomerase, PTS system galactitol-specific IIC component, PTS system galactitol-specific IIB component, PTS system galactitol-specific IIA component putative, Galactokinase, UDP-galactose 4-epimerase, 6-phospho-beta-D-galactosidase, PTS system lactose-specific enzyme IIBC, PTS system lactose-specific enzyme IIA, alpha-acetolactate decarboxylase, 2-keto-3-deoxy-6-phosphogluconate aldolase (eda / kdgA), PTS system (Glucose-specific) component IIA, thymidylate synthase, dihydrofolat e reductase, adenosine deaminase, amino-acid N-acetyltransferase / glutamate N-acetyltransferase, histidinol-phosphate aminotransferase, butyrate kinase (BUK), phosphate butyryltransferase, phosphoenolpyruvate-protein kinase (PTS system enzyme I), fumarate hydratase -terminal domain of FumA E.coli), fumarate hydratase, subunit A (N-terminal domain of FumA E.coli), adenylate kinase, tryptophan synthase alpha chain, tryptophan synthase beta chain, phosphoribosylanthranilate isomerase, indole-3-glycerol phosphate synthase , anthranilate phosphoribosyltransferase, putative anthranilate synthase component II, para-aminobenzoate synthase component I, acetolactate synthase large subunit, dihydroxyacid dehydratase, isopropylmalate dehydrogenase, 3-isopropylmalate dehydratase, small subunit, 3-isopropylmalate dehydratase, large subtolacate, 2-isopropylmalate synthase small subunit, predicted transcriptional regulator, homolog of Bvg accessory factor, formate-- tetrahydrofolate ligase, hypoxanthine-guanine phosphoribosyltransferase, phosphoribosylpyrophosphate synthetase, glucosamine-1-phosphate N-acetyltransferase, possible glutamate racemase, pyrroline-5-carboxylate reductase, glutamate 5-kinase, gamma-glutamyl phosphate reductase, ribonucleotideunitducto betanucleotide subunit, NADH-dependent butanol dehydrogenase B (BDH II), NADH-dependent butanol dehydrogenase A (BDH I), possible cardiolipin synthase (phospholipase D family), alanine racemase, possible homocysteine S-methyltransferase, alcohol dehydrogenase, low specificity L-threonine aldolase, PTS system, (possibly glucose-specific) IIBC component, 6-phospho-alpha-glucosidase, PTS system, (possibly glucose-specific) IIA component, 3-oxoacyl-acyl carrier protein reductase, GMP reductase, UDP-N- acetylglucosamine enolpyruvyl transferase, lactate dehydrogenase, acetyl-CoA carboxylase alpha subunit, acetyl-CoA carboxylase beta subunit, biotin carboxyl ase, hydroxymyristoyl- (acyl carrier protein) dehydratase, biotin carboxyl carrier protein of acetyl-CoA carboxylase, 3-oxoacyl- (acyl-carrier-protein) synthase I, 3-ketoacyl-acyl carrier protein reductase, malonyl CoA-acyl carrier protein transacylase, trans-2-enoyl-ACP reductase II, 3-oxoacyl- [acyl-carrier-protein] synthase III, adenylosuccinate synthase, phosphatidylglycerophosphate synthase, dihydrodipicolinate synthase, dihydroxy-acid dehydratase, GTP cyclohydrolase I, acetolactate bethta subunit -glucosidase, pyruvate decarboxylase, alcohol dehydrogenase / acetaldehyde dehydrogenase, fructose-bisphosphate aldolase class I, mannose-specific phosphotransferase system component IIAB, mannose / fructose-specific phosphotransferase system component IIC, mannose-specific phosphotransferase coacetylase acetyl thiolase), 3-oxoacyl-acyl-carrier protein synthase, alcohol dehydrogenase / acetaldehyde dehydrogenase, butyrate-acetoacetat e CoA-transferase subunit A, butyrate-acetoacetate CoA-transferase subunit B and acetoacetate decarboxylase. According to claim 1, wherein the metabolic network model for metabolism analysis of the butanol-producing microorganism metabolism for metabolic characterization characterized in that the gene-protein-reaction (GPR) relationship of Table 1 below Network model: TABLE 1

The metabolic network model for metabolic characterization as claimed in claim 1, wherein the butanol-producing microorganism is Clostridium microorganism. Method for analyzing metabolic properties of butanol-producing microorganisms using the metabolic network model of any one of claims 1 and 4. 6. The method of claim 5, wherein said metabolic property is metabolic flow. The method of claim 6 comprising the following steps: (a) calibrating the transport scheme for available carbon and nitrogen sources in the metabolic network model; And (b) metabolic flow analysis using the carbon and nitrogen sources. Method for analyzing the topology of the metabolic network model of claim 1. 10. The method of claim 8, wherein the analysis of the topology uses the following clouter coefficient Cn : Cn  = N / M N : Number of connected lines between nth node and neighboring nodes M : the maximum number of possible lines between nth node and neighboring nodes Wherein the node represents a metabolite of the metabolic network and the line connecting the two nodes is an enzymatic reaction mediating two metabolites. 10. The method of claim 8, wherein the analysis of the topology uses the following clouter coefficient Cn : n = 2 en / ( kn ( kn -1)) (for unidirectional networks) Cn = en / ( kn ( kn -1)) (for bidirectional networks) kn : number of contiguous connected nodes in nth node en : the number of connected pairs among all neighbors of the nth node Wherein the node represents a metabolite of the metabolic network and the line connecting the two nodes is an enzymatic reaction mediating two metabolites. In the metabolic network model of any one of claims 1 or 4, one or two or more enzyme reactions are blocked and a linear programming is applied, but when the ability to produce a specific metabolite increases, the enzyme of the blocked enzyme reaction is deleted. Or a method of screening for a deletion target enzyme or a gene for increasing the production of a specific metabolite of a butanol producing microorganism, characterized in that it is selected as a deletion target gene. 12. The method according to claim 11, wherein the enzyme of the blocked enzyme reaction is selected as a deletion target enzyme or the gene encoding the enzyme is deleted when the growth rate or the metabolic flow value is positive, and the production capacity of the specific metabolite is increased. Method for selecting a gene. 13. The method of claim 12, further comprising applying a linear programming method by blocking one or more enzyme reactions in a metabolic network model of a butanol producing microorganism, wherein the growth rate or the rate of metabolic flow is zero. When the enzyme of the blocked enzyme reaction is selected as a candidate candidate for secondary deletion target enzyme in case of increasing the ability of a specific metabolite, the deletion is performed only when the reaction rate or metabolic flow value of the growth scheme overlaps with a target enzyme that is positive. A method for selecting a target enzyme or selecting a gene encoding the same as a deletion target gene. The method of claim 12, wherein said growth scheme is Scheme I: Scheme I 0.5284 PROTEIN + 0.0655 RNA + 0.026 DNA + 0.076 PHOSPHOLIPID + 0.1009 PEPTIDOGLYCAN + 0.08 TEICH + 0.0432 CARBOHYDRATE + 0.0494 TRACE + 85 ATP-> BIOMASS + 85 ADP + 85 Pi 12. The method of claim 11, wherein the specific metabolite is selected from the group consisting of butanol, acetic acid, butyrate, ethanol and acetic acid. A method for producing a mutant microorganism having increased production ability of a specific metabolite, wherein the deletion target gene screened by the method of claim 11 is deleted in the butanol producing microorganism. Mutant microorganisms with increased production capacity of certain metabolites prepared by the method of claim 16. Culturing the mutant microorganism of claim 17; And recovering a specific metabolite from the culture solution. A method for predicting metabolic flow of butanol-producing microorganisms using the metabolic network model of claim 1. 20. The method for predicting metabolic flow of butanol-producing microorganisms according to claim 19, characterized by using a prior art planing method or a second planing method in which the absorption rate of the substrate is a prior input value. The method of claim 20, wherein the following Scheme II is used: Scheme II

Restrictions: S ν = 0, ν _min ≤ ν ≤ ν _max Where ν _acid is the metabolic flow vector at the acid generator; ν _sol is a metabolic flow vector in the solvent generator;

Is the rate of uptake of butyric acid by the coenzyme A transfer enzyme in the solvent generator;

Is the rate of absorption of acetic acid by the coenzyme A transfer enzyme in the solvent generator;

Is the rate of production of butyric acid in the acid generator;

Is the rate of acetic acid production in the acid generator.

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