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Metabolic Engineering and Systems Biotechnology. Ka-Yiu San. Departments of Bioengineering Departments of Chemical Engineering Rice University Houston, Texas. Recombined plasmid. Restriction cleavage. mRNA. Gene of interest. Translation. Restriction sites. Ligation.

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slide1

Metabolic Engineering

and

Systems Biotechnology

Ka-Yiu San

Departments of Bioengineering

Departments of Chemical Engineering

Rice University

Houston, Texas

slide3

Recombined

plasmid

Restriction

cleavage

mRNA

Gene of interest

Translation

Restriction sites

Ligation

Transcription

Protein

Restriction

cleavage

Transformation

Cloning vector

Host cell

Cloning for rProtein production

slide4

Recombinant proteins by microorganisms

Some early products

Year Products Disease Company

1982 Humulin Type 1 diabetes Genetech, Inc.

(synthetic insulin)

1985 Protropin Growth hormone Genetech, Inc.

Deficiency

slide5

Examples of a few biopharmaceutical products in 1994

Source: Biotechnology Industry Organization, Pharmaceutical Research and Manufacturers of America, company results, analyst reports

slide6

What is metabolic engineering?

Metabolic engineering is referred to as the directed improvement of cellular properties through the modification of specific biochemical reactions or the introduction of new ones, with the use of recombinant DNA technology

slide7

Protein/

enzyme

Gene

mRNA

transcription

Modern biology – central dogma

translation

slide8

Protein/

enzyme

Gene

mRNA

transcription

translation

  • Current metabolic engineering approaches
    • Amplification of enzyme levels
    • Use enzymes with different properties
    • Addition of new enzymatic pathway
    • Deletion of existing enzymatic pathway

Genetic manipulation

slide9

NADH

(Reduced)

NAD+

(Oxidized)

Current projects

  • Cofactor engineering of Escherichia coli
    • Manipulation of NADH availability
    • Manipulation of CoA/acetyl-CoA
  • Plant metabolic engineering
  • 3. Quantitative systems biotechnology
    • A. Rational pathway design and optimization
    • Metabolic flux analysis based on dynamic genomic information
    • Design and modeling of artificial genetic networks
    • Metabolite profiling
  • Genetic networks – architectures and physiology
motivations and hypothesis
Motivations and hypothesis
  • Motivations
    • Existing metabolic engineering methodologies include
      • pathway deletion
      • pathway addition
      • pathway modification: amplification, modulation or use of isozymes (or enzyme from directed evolution study) with different enzymatic properties
    • Cofactors play an essential role in a large number of biochemical reactions

Hypothesis

Cofactor manipulation can be used as an additional tool to achieve desired metabolic engineering goals

slide14

Cofactor engineering

  • NAD+/NADH
  • CoA/acetyl-CoA
nadh nad cofactor pair

NADH (Reduced)

NAD+

(Oxidized)

NADH/NAD+ Cofactor Pair
  • Important in metabolism
    • Cofactor in > 300 red-ox reactions
    • Regulates genes and enzymes
  • Donor or acceptor of reducing equivalents
  • Reversible transformation
  • Recycle of cofactors necessary for cell growth
slide16

Coenzyme A (CoA)

    • Essential intermediates in many biosynthetic and energy yielding metabolic pathways
    • CoA is a carrier of acyl group
    • Important role in enzymatic production of industrially useful compounds like esters, biopolymers, polyketides etc.
slide17

Acetyl-CoA

  • Entry point to Energy yielding TCA cycle
  • Important component in fatty acid metabolism
  • Precursor of malonyl-CoA, acetoacetyl-CoA
  • Allosteric activator of certain enzymes
slide18

Lactic acid

Polylactic acid(PLA)

LDH

Pyruvate

Lactate

NAD+

NADH

Example: Lactic acid formation

slide19

Biopolymer production

Poly(3-hydroxybutyrate- co-3-hydroxyvalerate)

(PHB/PHV block copolymer)

Glycerol Propionate

Acetyl-CoA Propionyl-CoA

Acetyl-CoA

3-Ketothiolase (PhaA)

HSCoA

Acetoacetyl-CoA 3-Ketovaleryl-CoA

NADPH

Acetoacetyl-CoA

Reductase (PhaB)

NADP+

3-Hydroxybutyryl-CoA 3-Hydroxyvalery-CoA

PHA Synthase (PhaC)

HSCoA

HSCoA

P(HB-co-HV)

slide20

Polyketide production

  • Complex natural products
  • > 10,000 polyketides identified
  • Broad range of therapeutic applications
    • Cancer (adriamycin)
    • Infection disease (tetracyclines, erythromycin)
    • Cardiovascular (mevacor, lovastatin)
    • Immunosuppression (rapamycin, tacrolimus)

6-deoxyerythronolide B

slide21

Polyketide production

Precursor supply - example

Ref: Precursor Supply for Polyketide Biosynthesis: The Role of Crotonyl-CoA Reductase, Metabolic Engineering 3, 40-48 (2001)

slide22

Approach

Systematic manipulation of cofactor levels by genetic engineering means

Model systems

Simple model systems, such as biosynthesis of succinate and ester, to illustrate the concept

Results

  • increased NADH availability to the cell
  • increased levels of CoA and acetyl CoA
  • significantly change metabolite redistribution
fermentation pathway of e coli

Glucose

NAD+

Succinate

2NADH

Pyruvate

Lactate

NADH

Acetyl-CoA

Formate

2NADH

Acetate

Ethanol

2NAD+

NAD+

NADH

2NAD+

Fermentation Pathway of E. coli
slide25

Pyruvate

NAD+

NADH

PFL

Formate

CO2

FDH1

Acetyl-CoA

FDHF

CO2

original NAD independent pathway

(FDHF: formate dehydrogenase, NAD independent)

Newly added NAD+ dependent pathway

(FDH1: NAD+ dependent formate dehydrogenase

FDH1 encoded by fdh1from Candida boidinii)

H

2

NADH Regeneration

slide26

Construction of pSBF2 Overexpressing FDH

pFDH1

PCR

fdh

fdh

pSBF2

XbaI

pSBF2

fdh

fdh

EcoRI/XbaI

pUC18

pUCFDH

XbaI

pDHK30

pDHK30

assay of fdh activity

Strain

FDH activity (units/mg protein)

GJT001(pSBF2)

0.42

BS1(pSBF2)

0.28

GJT001(pDHK29)

Not detected

BS1(pDHK30)

Not detected

Assay of FDH activity
slide28

XbaI

lacZ'

KmR

lacZ

fdh

MCS

pSBF2

pDHK29

KmR

Ori

Ori

Characterization of NADH-dependent FDH

NADH-dependent FDH

NADH-dependent FDH

PanK

PanK

GJT (pDHK29)

(Control strain)

GJT (pSBF2)

(New strain)

anaerobic tubes experimental method
Anaerobic Tubes :Experimental Method
  • Strains : Escherichia coli (MC4100 derivative)
    • GJT001 (pDHK29): wild type (control plasmid)
    • GJT001 (pSBF2): wild type (new FDH plasmid)
  • Media:
    • LB + 1g/L NaHCO3
    • 100mg/L Kanamycin
    • 20g/L Glucose
  • Temperature: 37 ºC
  • Agitation: 250 rpm
  • Samples: 72 hrs after inoculation
  • HPLC
effect of increasing nadh availability

NADH

2NAD+

NAD+

2NAD+

Effect of Increasing NADH Availability

% of Increase/Decrease for GJT001 (pSBF2) relative to GJT001 (pDHK29)

Glucose

Consumed

NAD+

3-fold

Succinate

55%

2NADH

Lactate

Pyruvate

91%

NADH

Formate Converted

Acetyl-CoA

2NADH

Acetate

8-fold

43%

NADH

NAD+

CO2

Formate

Ethanol

O.D.600nm: 59%

Et/Ac: 27-fold

FDH1

FDHF

15-fold

CO2

H

2

slide31

NADH Availability

5.0

4.0

mol NADH/mol glucose

3.0

2.0

1.0

0.0

GJT(pDHK29)

GJT(pSBF2)

summary of results
Summary of results

Effect of NADH regeneration (overexpressing NAD+-dependent FDH):

  • Increases intracellular NADH availability
  • Provide a more reduced environment
  • Increase reduced product (such as ethanol and succinate) productivity significantly
slide36

Projects

  • Metabolic flux analysis based on dynamic genomic information
  • Rational pathway design and optimization
    • feasible and realizable new network design
  • Design and modeling of artificial genetic networks
slide37

Motivations

Observations

  • Traditional reductionist approach
    • Knowledge at the basic and fundamental level
        • – but mostly isolated
  • Information overflow
    • Genome database, gene expression database (functional genomic), proteomic, metabolomics, metabolic pathway database
  • Most of the existing data base – static
    • Genome database, metabolic pathway database
slide38

Motivations and objectives:

How can one utilize the static genomic and metabolic databases (especially when genetic/regulatory network structures are available) to describe and predict cellular functions, such as metabolic patterns?

slide39

Genome

Database

Pathway

Database

FBA

Metabolic

Pattern

Metabolic

Network

A priori

Knowledge

Traditional flux balance analysis (FBA)

slide40

Metabolic Network

(From http://www.genome.ad.jp/kegg/pathway/map/map00020.html)

slide41

Metabolic Pattern (Illustration)

1.0

0.8

0.2

0.8: Metabolic rates

(From http://www.genome.ad.jp/kegg/pathway/map/map00020.html)

slide42

genotype

phenotype

environmental

genetic

perturbations

perturbations

(mutant strains)

Cellular

Responses

Transcription

Translation

Metabolic Flux Analysis

OR

Metabolite

Patterns

Protein/

enzyme

Gene

mRNA

Stimuli

traditional metabolic engineering study

slide43

?

Genome

Database

Pathway

Database

Genetic

Structure

Expression

Patterns

Genetic

Network

A priori

Knowledge

FBA

Metabolic

Network

Metabolic

Patterns

Gene Regulation

Knowledge

Gene Chip (Array) Data

Proposed New Approach

Environmental

Conditions

slide44

Model System

  • Oxygen and redox sensing/regulation system
  • Sugar utilization regulatory network
slide45

Simplified schematic of E. coli central metabolic pathways

Glucose

PEP

Pyruvate

Lactate

ldhA

[1.1.1.28]

NAD+,CoA

ppc

[4.1.1.31]

NADH, CO2

pdh

[1.2.4.1]

CoA

pfl

[2.3.1.54]

H2 + CO2

Formate

CO2

Acetyl- CoA

Ethanol

gltA

[4.1.3.7]

Acetate

Citrate

Oxaloacetate

aspC

[2.6.1.1]

NADH

acnB

[4.2.1.3]

mdh

[1.1.1.37]

NADH

NAD+

NAD+

Isocitrate

Aspartate

Malate

aspA

[4.3.1.1]

fumB

[4.2.1.2]

fumA

[4.2.1.2]

icd

[1.2.4.2]

NADP+

NADPH

Fumarate

sdhCDAB

[1.3.99.1]

CO2

NADH

frdABCD

[1.3.1.6]

2-ketoglutarate

NAD+

sucAB

[1.2.4.2]

Succinate

sucCD

[6.2.1.5]

NAD+

NADH

Succinyl-CoA

CO2

Simplified schematic of E. coli central metabolic pathways

slide46

e- transport

Cytoplasmic

membrane

ArcB

P

FNR

FNR

Redox,

metabolites

Aer

Redox?

Dos

ArcA

O2

O2

CheW,A,Y

ArcA-P

Transcription

unknown

Energy taxis

Transcription

Schematic showing selected oxygen and redox sensing pathways in E. coli (adopted from Sawers, 1999)

slide47

Some example of available pathway information

FNR active in the absence of oxygen; ArcA is activated in the absence of oxygen

 Ref 1: “Reg of gene expression in fermentative and respiratory systems in Escherichia coli and related bacteria”, E.C.E. Lin and S. Iuchi, . Annual Rev. Genet, 1991, 25:361-87Ref 2:

Ref 2 “O2-Sensing and o2 dependent gene regulation in facultatively anaerobic bacteria”, G. Unden, S. Becker, J. Bongaerts, G.Holighaus, J. Schirawski, and S. Six, Arch Microbi. (1995) 164:81-90

Ref 3: “Regualtion of gene expression in E. coli” E.C.C. Lin and A.S. Lynch eds. (1996) Chapman & Hall, New York (p370)

Ref 4: “Regualtion of gene expression in E. coli” E.C.C. Lin and A.S. Lynch eds. (1996) Chapman & Hall, New York (p322)

slide48

ldhA

aspA

fumB

frdABCD

pfl

cyd

cyo

ArcB

aceB

mqo

ArcA

FNR

fumC

aceEF

acnB

sdhCDAB

fumA

mdh

gltA

icd

sucAB

sucCD

We have 3 sensing/regulatory components whose activity evolves according to the Boolean mapping coded in the figure. Here red denotes repress and green denotes activate. When two components regulate a third we suppose their action to be an “and”. These regulatory components determine the state of 19 structural genes via the specified Boolean net.

slide49

O2

ArcA

FNR

pfl

aceEF

PDH

PFL

CO2

CoA

NADH

Acetyl-CoA

NAD+

pyruvate

Stimulus

Sensors/regulators

genes

enzymes

formate

Metabolites

activation

repression

slide50

Work in progress

To develop a model that can provide dynamic and automatic adaptation of pathway map to environmental conditions

slide51

Biosystems

  • Systems biology is the study of living organisms at the systems level rather than simply their individual components
  • High-throughput, quantitative technologies are essential to provide the necessary data to understand the interactions among the components
  • Computation tools are also required to handle and interpret the volumes of data necessary to understand complex biological systems
slide52

genotype

phenotype

environmental

genetic

perturbations

perturbations

(mutant strains)

Cellular

Responses

OR

Metabolite

Patterns

Protein/

enzyme

Gene

mRNA

Stimuli

Functional Genomics

Metabolomics

Proteomics

Genomics

slide54

Proteinomics

  • 2D gel electrophoresis
  • Mass spectrometry
  • Bioinformatics
  • Protein "chips"
slide56

Protein Chips

  • The basic construction of such protein chips has some similarities to DNA chips, such as the use of a glass or plastic surface dotted with an array of molecules.
  • Known proteins are analyzed using functional assays that are on the chip. For example, chip surfaces can contain enzymes, receptor proteins, or antibodies that enable researchers to conduct protein-protein interaction studies, ligand binding studies, or immunoassays
  • High-end quadruple TOF tandem mass spectrometers enable high-performance protein identification, epitope and phosphorylation mapping, and protein-interaction analyses.
slide57

Metabolomics

  • Metabolomics is a relatively new discipline and techniques for high-throughput metabolic profiling are still under development.
  • No single technique is suitable for the analysis of all different types of molecule, so a mixture of techniques is used.
  • Methods such as gas chromatography, high-pressure liquid chromatography and capillary electrophoresis are used to separate metabolites according to various chemical and physical properties. The molecules are then identified using methods such as mass spectrometry.
slide60

Collaborators

Dr. George N. Bennett

Department of Biochemistry and Cell Biology

Rice University

Dr. Steve Cox

Department of Computational & Applied Math

Dr. Nikos Mantzaris

Department of Chemical Engineering

Dr. Kyriacos Zygourakis

Department of Chemical Engineering

Dr. Jacqueline V. Shanks

Department of Chemical Engineering

Dr. Ramon Gonzalez

Department of Chemical Engineering

Dr. Sue Gibson

Department of Plant Biology

slide63

(ksan@rice.edu)

Office:

GRB E200K

Lab:

GRB E201, E202, E210, E128

Metabolic Engineering and

Systems Biotechnology Laboratory

Ka-Yiu San

slide64

???

Questions ?