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共 21 共 1共 NTHU Modeling and Simulating the Modeling and Simulating the Biological Pathway Biological Pathway - case study - - case study - 第第第 Systems Biology Presentation

Modeling and Simulating the Biological Pathway - case study -

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Systems Biology Presentation. Modeling and Simulating the Biological Pathway - case study -. 第六組. Outline. Information gathering KEGG web service Ontology-based knowledge extraction Modeling environment Stoichiometric matrix Simulating environment Kinetics model Results and discussion. - PowerPoint PPT Presentation

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Page 1: Modeling and Simulating the Biological Pathway - case study -

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Modeling and Simulating the Modeling and Simulating the Biological PathwayBiological Pathway

- case study -- case study -

第六組

Systems Biology Presentation

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OutlineOutline

• Information gathering – KEGG web service– Ontology-based knowledge extraction

• Modeling environment– Stoichiometric matrix

• Simulating environment– Kinetics model

• Results and discussion

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Global agent ArchitectureGlobal agent Architecture

Database (KEGG, NCBI, Micro-array)、 Bioinformatics Toolkit

Web service Matchmaker (Broker Agent)

Information wrapper Agent

Connect the service

Information Gathering

Bio-ontology& thesauri

Pathway modeling agent

Literature extraction agent

Quantitative Simulation agent

Workflow Planning agent

Model the pathway according to

the promoter and

molecular interactions

Extract the

molecularinteractions

and Chemical

coefficients

According tothe

Quality of Serviceand use’s goal

to make theBiological plan

Measure the chemical valuesby calculating the coefficients

and pathway

structure

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ArchitectureArchitecture

Pathwaydatabase

Kineticsdatabase

chemicaldatabase

Biologicaldatabase

Stoichiometric model

Dynamic model

Get the kinetics coefficient from the experiments

or literature

Get the gene name,chemical compound and its physical information

Get the chemical reaction

Get the biological pathway

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BenefitBenefit

• Relational database system for managing kinetic data, chemical structure, pathway, chemical reaction

• Provide stoichiometric information and parameters for kinetics equations to the model

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Web service-KEGGWeb service-KEGG

KEGG API provides valuable means for accessing the KEGG system, such as for searching and computing biochemical pathways in cellular processes or analyzing the universe of genes in the completely sequenced genomes. get_genes_by_pathway,get_enzymes_by_pathway,get_compounds_by_pathway,get_reactions_by_pathway….etcThe users can access the KEGG API server by the SOAP technology over the HTTP protocol. The SOAP server also comes with the WSDL, which makes it easy to build a client library for a specific computer language.

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Ontology-based knowledge extractionOntology-based knowledge extraction

• Concentration (mM), Volume (m),Flux (mM/s),PH,…etc

• C-mol/min*L-cytosol – where C-mol is a mol of carbon and L-cytosol i

s a litre of cytosolic water

• Sentence: – The pyruvate concentration that is required to

accommodate a flux of 0.48 C-mol/min*L-cytosol, is 8 mM.

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GlycolysisGlycolysis

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Enzyme KineticsEnzyme Kinetics

One substrate, one product reversible Michaelis-Menten kinetics was used to describe the enzymes PGI, PGM and ENO:

where a and p represent the concentrations of the corresponding substrate and product, respectively. G is the mass-action ratio, p/a, Keq is the equilibrium constant, peq/aeq. Ka and Kp are the Michaelis-Menten constants for a and p.Reversible Michaelis-Menten kinetics for two noncompeting substrate-product couples was used for HK, GraPDH, PGK and PYK:

where a and b represent the concentrations of the substrates andp and q the concentrations of the products.

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ExampleExample

DEMO

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ResultsResults

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Results (II)Results (II)

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Future workFuture work

• The combination of flux based static modeling with dynamic modeling based on kinetic equations

• The model can be initiated as a stoichiometric model that is gradually converted into a dynamic model by adding dynamic equations.

• Flux distribution analysis as a method for calculating each flux in stoichiometric models.

• Substances at the boundary between dynamic models and stoichiometric model are influenced by both flux.

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Biosynthesis of EthanolBiosynthesis of Ethanolby by E.coliE.coli

Systems Biology Presentation

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GlycolysisGlycolysis

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ProblemProblem

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Pyruvate DecarboxylasePyruvate Decarboxylase

• Reference– Saccharomyces cerevisiae pyruvate decarb

oxylase PDC1 has been isolated and fused to the indicator gene Escherichia coli lacZ.

– T7 RNA polymerase promoter phi 10, that a cloned Saccharomyces cerevisiae pyruvate decarboxylase gene ( pdc1) can be expressed in Escherichia coli.

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Alcohol DehydrogenaseAlcohol Dehydrogenase

• Only strain K-12 definitely have alcohol dehydrogenase (adhP)

• alcohol dehydrogenase (EC 1.1.1.1)

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Escherichia coli strain KO11Escherichia coli strain KO11

• E. coli KO11 and three ethanol-resistant mutants of this strain (LY01-LY03).

• Strain KO11 is an ethanol-producing recombinant in which the – Z. mobilis genes for ethanol production (pdc, a

dhB) – and the cat gene (acetyltransferase) have bee

n integrated into the E. coli B chromosom.

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Two strain used for this!Two strain used for this!

1. Strain K-12• definitely have alcohol dehydrogenase (adh

P)• Saccharomyces cerevisiae pyruvate decarb

oxylase (pdc1) recombinant

2. Escherichia coli strain KO11• Z. mobilis genes for ethanol production (pdc,

adhB) recombinant

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ReferenceReference

• Karp, P.D.; Riley, M.; Saier, M.; Paulsen, I.T.; Collado-Vides, J.; Paley, S.; Pellegrini-Toole, A.; Bonavides, C.; Gama-Castro, S. The Ecocyc database. Nucleic Acids Res. 2002, 30,56-58

• Yomano, L.P.; York, S.W.; Ingram, L.O. Journal of Industrial Microbiology & Biotechnology. Isolation and characterization of ethanol-tolerant mutants of Escherichia coli KO11 for fuel ethanol production. 1998, 20, 132-138