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In silico aided metaoblic engineering of Saccharomyces cerevisiae for improved bioethanol production...

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In silico aided metaoblic engine ering of Saccharomyces cerevisiae for improved bioethanol production Christoffer Bro et al. 2005
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Page 1: In silico aided metaoblic engineering of Saccharomyces cerevisiae for improved bioethanol production Christoffer Bro et al. 2005.

In silico aided metaoblic engineering of Saccharomyces cerevisiae for improved bio

ethanol productionChristoffer Bro et al. 2005

Page 2: In silico aided metaoblic engineering of Saccharomyces cerevisiae for improved bioethanol production Christoffer Bro et al. 2005.

The problem• Under anaerobic conditions, S. cerev

isiae produces only four major products from glucose:• CO2, ethanol, biomass and glycerol

• To increase the ethanol yield, the flow of carbon going to biomass or glycerol should be redirected towards ethanol.

Page 3: In silico aided metaoblic engineering of Saccharomyces cerevisiae for improved bioethanol production Christoffer Bro et al. 2005.

Overview of main fluxes

Page 4: In silico aided metaoblic engineering of Saccharomyces cerevisiae for improved bioethanol production Christoffer Bro et al. 2005.

Previous work• Some of the carbon flowing to biomass ca

n be redirected towards ethanol by increasing the consumption of ATP for biomass production or reducing the amount of ATP formed in association with ethanol production. (Nissen et al. 2000)

• Deletion of the structural genes in glycerol biosynthesis is not a successful strategy.• The maximum specific growth rate is severely l

owered in such strains• Formation of glycerol is necessary for maintai

ning the redox balance by oxidizing NADH

Page 5: In silico aided metaoblic engineering of Saccharomyces cerevisiae for improved bioethanol production Christoffer Bro et al. 2005.

Strategy #1• Substitution of NADPH-oxidizing

reactions in biomass formation with NADH-oxidizing reactions

Page 6: In silico aided metaoblic engineering of Saccharomyces cerevisiae for improved bioethanol production Christoffer Bro et al. 2005.

Strategy #2• Substitution of NAD+-reducing

reactions in biomass formation by NADP+-reducing reactions.

Page 7: In silico aided metaoblic engineering of Saccharomyces cerevisiae for improved bioethanol production Christoffer Bro et al. 2005.

Strategy #3• Introduction of a reaction which

either directly or via a cycle converts NADH into NADPH.

Page 8: In silico aided metaoblic engineering of Saccharomyces cerevisiae for improved bioethanol production Christoffer Bro et al. 2005.

Strategy #4• Substitution of the glycerol production

with production of ethanol, which has a net oxidation of NADH.

Page 9: In silico aided metaoblic engineering of Saccharomyces cerevisiae for improved bioethanol production Christoffer Bro et al. 2005.

In silico model• iFF708 (Forster et al., 2003)

• 708 genes• 584 metabolites• 1175 reactions

Page 10: In silico aided metaoblic engineering of Saccharomyces cerevisiae for improved bioethanol production Christoffer Bro et al. 2005.

Method• A database of 3800 biochemical reactions is deriv

ed from the LIGAND database of KEGG. • Each gene (corresponding to a specific biochemi

cal reaction) was inserted one at a time into the genome-scale metabolic model, and the performance of the engineered strain was evaluated.

• Two other engineered strains:• Heterologous expression of a non-phosphorylating, NA

DP+-dependent D-GAPN• Deletion of GDH1 combined with simultaneous overexpr

ession of GDH2 or GLN1 and GLT1.• GDH1: AKG + NH3 + NADPH -> GLU + NADP• GDH2: GLU + NAD -> AKG + NH3 + NADH• GLN1: GLU + NH3 + ATP -> GLN + ADP + PI• GLT1: AKG + GLN + NADH -> NAD + 2 GLU

Page 11: In silico aided metaoblic engineering of Saccharomyces cerevisiae for improved bioethanol production Christoffer Bro et al. 2005.

Eight best strains predicted

Page 12: In silico aided metaoblic engineering of Saccharomyces cerevisiae for improved bioethanol production Christoffer Bro et al. 2005.

The best strategy

Page 13: In silico aided metaoblic engineering of Saccharomyces cerevisiae for improved bioethanol production Christoffer Bro et al. 2005.

In vivo testing of the best strategy• Ethanol production increased by 3%

• Reasons for disagreement between experiment and model: • Limited GAPN activity in vivo• Low intracellular NADP+ concentrations

compared with NADPH

Page 14: In silico aided metaoblic engineering of Saccharomyces cerevisiae for improved bioethanol production Christoffer Bro et al. 2005.

Discussion• “The success of the strategies is due

to the tight linking of the different parts of the metabolic network through the common usage of co-factors like NADH, NADPH and ATP, and the genome-scale metabolic model represents a valuable tool for studying how these co-factors link the different parts of the metabolism in a quantitative fashion.”

Page 15: In silico aided metaoblic engineering of Saccharomyces cerevisiae for improved bioethanol production Christoffer Bro et al. 2005.

Efficiency of amino acid production in Escherichia coli

Anthony Burgard & Costas Maranas, 2001

Page 16: In silico aided metaoblic engineering of Saccharomyces cerevisiae for improved bioethanol production Christoffer Bro et al. 2005.

208.260915.6818.6279.450111.32211.8126.1227.87287.42197.57.85125.79515.491310.0742012.6014.49075.688610

iJR904

Page 17: In silico aided metaoblic engineering of Saccharomyces cerevisiae for improved bioethanol production Christoffer Bro et al. 2005.

Universal model• The universal model is constructed b

y incorporating 3400 cellular reactions from the KEGG into the modified Keasling stoichiometric model.

Page 18: In silico aided metaoblic engineering of Saccharomyces cerevisiae for improved bioethanol production Christoffer Bro et al. 2005.

Arginine production


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