Systems Metabolic Engineering

Systems Metabolic Engineering

Sang Yup Lee Dept. of Chemical & Biomolecular Engineering Metabolic Engineering National Research Laboratory BioInformatics Research Center BioProcess Engineering Research Center Center for Systems and Synthetic Biotechnology Institute for the BioCentury

Metabolic engineering g g ((J. Baileyy @ Caltech/ETH)) Purposeful modification of metabolic and other cellular networks to achieve desired phenotypes

1. Th 1 There should h ld b be objective(s) bj ti ( ) 2. Desired phenotypes should do something good for h human ((and d our environment) i t) 3. Many different tools, chemical, biological and computational, t ti l can b be combinatorially bi t i ll employed l d

Metabolic Engineering Purposeful modification of metabolic network to achieve… 1. Enhanced production of metabolites and other biologicals that are already produced by host organism 2. Production of modified or new metabolites and other biologicals that are new to the host organism 3. Broadening the substrate utilization range 4. Designing improved or new metabolic pathways for degradation of various ario s chemicals chemicals, especiall especially xenobiotics enobiotics 5. Modification of cell properties that facilitate bioprocessing (fermentation and product recovery) Lee, S.Y. and Papoutsakis, E.T.(1999) Metabolic Engineering, Marcel Dekker Stephanopoulos, G., Aristidou, A., Nielsen, J. (1998) Metabolic Engineering, Academic Press

Strain improvement 0th generation: Random mutagenesis and selection 1st generation metabolic engineering : introduction/amplification of a handful of genes : metabolic flux analysis and rational engineering of metabolic network : limited li it d regulatory l t engineering i i

2nd g generation metabolic engineering g g : integration of omics and genome-scale analysis for metabolic engineering : combination of rational, random, and rational-random approaches : consideration of upstream to midstream to downstream processes all together ÎSystems Metabolic Engineering

3rd generation metabolic engineering: to be seen

Figure by Dr. Nicholson

Omics Revolution Lee, S.Y. et al. Trends in Biotechnol. 23: 349-358 349 358 (2005)

Applications To Strain Development?

Metabolic engineering based on large amounts of data and information

Enhanced production of poly(3-hydroxybutyrate): proteome Enhanced production of succinic acid: transcriptome and proteome Enhanced production of lycopene: transcriptome Enhanced production of IGF-I: transcriptome Enhanced production of leptin and other serine rich proteins: proteome E h Enhanced d production d ti off L-threonine: L th i proteome t … and more … by engineering E. coli

1.5 1 5th generation i metabolic b li engineering i i

“Local Local metabolic engineering based on local information selected from global omics information”

Moving towards nd the 2 generation metabolic engineering Systems metabolic engineering

Integrating g genome-scale flux analysis + regulatory eng Lee et al. (2005) TIBTECH

Systems biotechnology (coined by Systems biology) by Sang Yup Lee (from the lecture "Microbial Genomics and Proteomics", International BRC Sympo., Yonsei Univ, Seoul, Korea, Aug 25, 2000)

Definition (my definition based on OECD definition of Biotechnology

Systems biotechnology is "The application of science and technology at systems level to living organisms as well as parts, products and models thereof, for the production of knowledge goods and services" knowledge, services . Lee, Lee S.Y., S Y Lee, Lee D.-Y., D -Y and Kim Kim, T T.Y., Y "Systems Systems biotechnology for strain improvement", Trends Biotechnol., 23(7): 349-358 (2005)

Prospects : Systems biotechnology is the way biotechnology should be developed and practiced from now on. Up-stream (strain, cell and organism development), mid-stream (fermentation and other unit operations), operations) and down-stream processes of biotechnology will benefit significantly by taking systems biotechnological approaches. In the cases of mid- to down-stream bioprocesses, it resembles systems engineering approach that has been successfully applied in chemical industries (core subject of chemical engineering). Now, it is time to take systems biotechnological approaches in developing up-stream processes such as strain development, which will ultimately lead to successful f l biotechnology bi h l development d l when h combined bi d with i h systems engineering i i off mid- to down-stream processes. As a whole, this is Systems Biotechnology !!!

General strategy gy for Systems biotechnology (systems metabolic engineering)

Park et al. 2008. Trends Biotechnol 26: 404-412 Sang Yup Lee

Strategies for strain design combined systems metabolic eng, random, and rational random approaches

Host selection – does not necessarily have to be E. coli Control of gene expression – plasmid/chromosome Amplification, Knock-outs, Knock-ins, Knock-downs… Regulatory engineering – TFs, promoter/rbs, RNA structure… Feedback from midstream and downstream processes Protein/enzyme engineering – new or improved traits Ad ti evolution Adaptive l ti off proteins, t i pathways, th and d cellll Use the tools of systems biology and synthetic biology …

Versatility of amino acids

Val, Leu, Ile : effective in hepatic failure Glu : antiulcer drug Arg : immune-enhancing effect

Val,, Leu,, Ile : Muscle building, g, increase of stamina, recovery from fatigue

Medical care

Sports

Food & animal feed

Beauty care

Health care

Amino acid

Platform chemicals The skin moisturizing effect Collagen composition Care of damaged cuticles Efficient burning of body fat

L valine L-valine

essential amino acid hydrophobic branched chain amino acid hydrophobic, needed for muscle metabolism, tissue repair used as an energy source by muscle tissue used as cosmetics and pharmaceutical source, animal food additives

ilvGMEDA x acetohydroxy acid synthase I II, I, II III

acetohydroxy acid isomeroreductase

dihydroxy acid dehydratase

branched chain amino acid aminotransferase

Jin Hwan Park

Ptac

ilvGMEDA

thr dehydratase

ΔlacI Ptac

…later…(manuscript submitted) 598th GATGACTTC 41th GÆ A 50th CÆ T 2-isopropylmalate synthase

X 3-methyl-2-oxobutanoate hydroxymethyltransferase

Auxotrophic 2 mM Leu 2 mM Ile 1 5 μM 1.5 M pantoth t th

Base strain

X

X

ÆVal {W3110(attilvG::ptac, attilvB::ptac, ilvHA41G, C50T, ∆lacI, ∆ilvA, ∆leuA, ∆panB)} harboring pKKilvBN

Fermentation & Transcriptome analysis Val : W3110(attilvG::ptac, attilvB::ptac, ilvHA41G, C50T, ΔlacI, ΔilvA, ΔleuA, ΔpanB), pKKilvBN Control : W3110 (ΔlacI, pKK223-3) Medium

NM1, Glucose (20 g/L), L-leucine (2mM), L-isoleucine (2mM), D-pantothenate (1.5μM)

30

3.0

25

2.5

20

2.0

15

1.5

100

1.0 .0

5

0.5

0

0.0 0

5

10

Time (hr)

15

20

▶ 1.31 g/L L L-valine valine L-vvaline (g//liter)

Cell growth ((OD600)

Condition 31°C, pH 6.0

by batch fermentation

Jin Hwan Park

Overexpression of upregulated biosynthetic pathway genes

Relative expression level of L-valine biosynthetic pathway genes gene

enzyme

chip data

ilvB

acetohydroxy acid synthase isoenzyme I

54.46

ilvN

acetohydroxy acid synthase isoenzyme I

32.50

ilvC

acetohydroxy acid isomeroreductase

3.74

ilvD

dihydroxy acid dehydratase

4.28

ilvE

branched chain amino acid aminotransferase

1.32 Co-amplification of the ilvCED genes in pKKilvBN 4

Increased L-valine p production (1.31 ( Æ3.43 g g/L))

L-valline (g/L)

3

2

1

0 Val+pKKilvBN

Val+pKKilvBNCED

Reducing the cellular burden caused by plasmid-multigene expression The origin of replication of pKKilvBNCED was replaced with that of a medium copy number plasmid pBR322 to make pKBRilvBNCED.

4

L-valinee (g/L)

3

2

1

0 Val+pKKilvBNCED Val+pKBRilvBNCED

Better cell growth & slight increase in L-valine production (3.43 Æ 3.73 g/L)

Leucine responsive protein: Lrp Î Downregulated (ratio: 0.52) Enhanced production of L-valine L valine by overexpression of lrp CM(R)

P15A ORI

4

5S

lrp

pKB BRilvBNCE ED

1

pTrc

rrnBT1T2

Val (Δlrp)+

2

V Val+pKBRilv vBNCED+ pTrc184lrp

3

V Val+pKBRilv vBNCED+ pT Trc184

pTrc184lrp

Val+pKBRilv V vBNCED

L-valine cconcentratiion (g/L)

5

0

21.6% increase (3.57Æ4.34 g/L) in L-valine production with lrp overexpression 36.2% decrease (3.73Æ2.38 g/L) in L-valine production with lrp deletion ÆLrp plays an important role in L-valine production

Identification of the E. coli gene homologous to Corynebacterium glutamicum brnF

Exporter Engineering

YgaZH: hypothetical protein Downregulated to 0.61-0.75 during Val production

L-valine exporter in E. coli ?

Synergistic effect of ygaZH and lrp on L-valine production 113% (3.57Æ7.61 g/L)

8

47 1% 47.1%

0

CM(R)

RilvBNCED+ + Val+pKBR pTrc184ygaZHlrp

2

Val+pKBR RilvBNCED+ + pTrc184lrp p

4

Val+pKBR RilvBNCED+ + pTrc184ygaZH

21.6%

Val+pKBR RilvBN CED+pTrcc184

L-valin ne (g/L)

6

CM(R)

CM(R)

P15A ORI P15A ORI

pTrc184lrp

pTrc184ygaZH

pTrc

rrnBT1T2 5S

lrp

P15A ORI

pTrc184ygaZHlrp

Ptrc

rrnBT1T2 5S

Ptrc

rrnBT1T2 5S

ygaZH

lrp

ygaZH

Metabolic engineering of E. coli for L-Valine production… (flask culture for 48 h @ 31C; 50 g/L glucose) -Removed R d feedback f db k iinhibition hibiti -Removed transcriptional attenuation control -Removed major competing metabolic pathways -Stepwise improvement based on transcriptome analysis

Amplification of Global regulator L-valine production engineering pathways GLC

GLC

ptsG

G6P

ptsG zwf

6PGL

pgl

6PGC

gnd

rpiA

X5P

F6P

S7P

GAP

E4P

GAP

F6P

DHAP

Leu

PEP

Ptac

ACL

ilvC

DHV

ilvD

ilvGM

rpiA

R5P

S7P

tktAB

GAP talAB

fba tpiA

E4P

GAP

ilvE

Val

avtA

pgk

Ala

F6P Leu

PYR

aceEF

ACA

pta

ACP

ackA

Ace

eno

Pan

PEP

gltA

OAA

CIT

aceA

GLO

ICIT icdA

FUM

AKG SUC

sucCD

sucAB

SUCOA

ACL

Val+pKKilvBN Val pKKilvBN

1.31 g/L

ilvC

DHV

ilvD

ilvGM

41th G A 50th C T

PYR

aceEF

ACA

pta

ACP

gltA

OAA aceB

aceA

GLO

fumA

ICIT icdA

FUM sdhACD

ilvE

AKG SUC

ackA

Val

avtA

Ala

Ace

Pan

Val+pKBRilvBNCED+pTrc184ygaZHlrp

CIT

mdh

MAL

KIV

ilvIH

Ptac

pykAF

ppc

aceB

fumA

Ptac

ilvBN gpmA

41th G A 50th C T

mdh

sdhACD

KIV

ilvIH

Ptac

pykAF

ppc

MAL

RL5P

X5P

GBP ilvBN

eno

gnd

rpe

gapA

GBP gpmA

6PGC

tktAB

FBP

gapA

pgk

pgl

pfkA

talAB

fba tpiA

6PGL

F6P

tktAB tktAB

zwf

pgi

R5P

pfkA

DHAP

G6P

RL5P

rpe

pgi

FBP

Exporter engineering

sucCD

sucAB

SUCOA

7 61 g/L 7.61

Any more targets to engineer?

Development of a strategy for the reconstruction of in silico genome-scale metabolic model g

Kim et al. Biotech. Bioeng. 97:657 (July 2007)

In silico single gene knock-out

Tae Yong Kim

In silico double gene knock-out

Tae Yong Kim

In silico triple gene knock-out

Tae Yong Kim

Flux redirection by triple knock-out Î 37.75 g L-valine from 100 g glucose From ED and PPP pathway

Acetyl-CoA

From malate through malic enzyme

aceF/E/lpdA

pyruvate dehydrogenase

pfkA/B

phosphofructokinase

mdh

malate dehydrogenase

Selection of genes g for triple knock-out mutation Park et al., PNAS 104: 7797-7802 (2007)

L-valine path a pathway

Systems metabolic engineering of E. coli for the production of L-valine Park et al., PNAS 104: 7797-7802 (2007)

Replacement of attenuator with tac promoter

E. coli W3110

CM(R)

CM(R)

P15A ORI

P15A ORI

L-Threonine

pTrc184ygaZH

ilvA

pTrc184lrp

Pyruvate

Pyruvate

Ketobutyrate 5S

ilvBN, ilvGM, ilvIH

ilvC

ilvC

+

Dihydroxyiso valerate

ilvE

panE panC

tyrB

L-Leucine

L-valine overproducer

panB

ilvE

L-Valine

lrp

5S

il E ilvE L-Isoleucine

leuCD

pTrc

rrnBT1T2

ilvD

ilvD Ketoiso valerate leuA

ygaZH

Transcriptome analysis

Acetohydroxy butyrate

Acetolactate

leuB

Ptrc

rrnBT1T2

ilvBN ilvGM ilvIH

Pantothenate

Lrp

+

_

In silico knock-out simulation Glucose

Base strain

ptsG pgl

zwf

G6P

D6PGL

gnd

D6PGC

RL5P

rpe

pgi

rpiA

R5P

X5P

F6P

tktAB pfkAB

F16P tpiA

S7P

tktAB

talAB

fba

DHAP

GAP

E4P

F6P

Leu

G3P

leuA gapA

Aclac

PGA

Dhival

ilvD

pykAF

PYR

pta

ACA

OAA

Ace

CIT

mdh

acnAB aceB aceA

FUM

sdhABCD

ICIT icdA

GLO

fumA

AKG

sucCD

SUC

Val

ackA

Ace-P

gltA

ppc

ilvE

panB

aceEF

PEP

MAL

Kival

ilvBN, ilvGM, ilvIH

eno

Removal of feedback inhibition

ilvC

sucAB SUCOAS

aceK

Pan

Metabolic engineering strategy for constructing L-threonine producing E. coli strain Lee et al. Molecular Systems Biology, 3:149 (Dec 2007)

byproduct

Kwang Ho Lee

regulation branched pathway

Tae Yong Kim

central carbon flux

biosynthetic pathway

degradation threonine efflux

250

9 3 fold ↑ 9.3 200

150 100

32.0

50

0

6

18 16 14 12 10 8

5.3

6 4

2.2 1.7

2

5 4 3 2

10 2.0

0

1 0

0

1.5 6 1.0 0.5

2 0 5

10

Time (h)

4

6

8

10

12

0.0 14

0.19g/ g 0.0 l15 20

7 6 5 4 3 2 1 0

10 2.0

Glucos se (g/l)

8

4

2

Time (h)

Biomas ss (g/l)

2.0

0

1.46g/l1.0 0.5

0

L-thrreonine, org ganic acids ((g/l)

2

10

Glucos se (g/l)

Biomas ss (g/l)

3

4

1.5

TH07 (pBRThrABC, pACYC-ppc) (ppc amplified strain)

7

4

6

0

TH11C (pBRThrABC, pACYC177) (ppc deleted strain)

5

glucose Biomass L-Thr pyruvate t acetate succinate

2

1

control control ppc ppc ppc ppc -amplified -deleted -amplified -deleted

6

8

8

1.21g/l

6

1.5 1.0

4

0.5

2 0 0

2

4

6

8

Time (h)

10

12

0.0 14

L-threonine, org ganic acids (g/l)

298.4

Glucos se (g/l)

300

7

20

Biomas ss (g/l)

specific activity of P s PPC (U/mg protein)

350

ICL specific activity of IICL (U/mg protein)

PPC

L-thrreonine, org ganic acids ((g/l)

TH07 (pBRThrABC, pACYC177) (control strain)

Enzyme assay

in silico flux response analysis The changes of the L-threonine production rate were examined under PPC flux perturbation.

Flux redistribution by gene perturbation

biomass

Genome-scale G l metabolic t b li model d l E. coli MBEL979

the e flux u o of PPC C is sp presented ese ed in the e < 4 mmol/gDCW/h o /g C / in ae aerobic ob c condition (Fisher et al., Anal. Chem.(2004))

118 4 118.4

5 4 3 2

10 2.0 8 1.5

1.46g/l

6

1.0

4

0.5

2

1 0

0 0

2

4

6

8

10

12

0.0 14

plasmid l id -borne overexpression

7 6 5 4 3 2 1 0

10 2.0 8

1.0

4

0.5

2 0 0

Time (h)

1.5

1.21g/l

6

2

4

6

8

10

12

0.0 14

Time (h)

promoter replacement

L-Thr conc. 28.8 % ↑

TH19C (pBRThrABC, pACYC177) (ppc amplified strain) 7

5 4 3 2 1 0

Glucos se (g/l)

Biomas ss (g/l)

6

10

1.88g/l 2.0

8

glucose Biomass L-Thr pyruvate acetate succinate

6 4

1.5 1.0 0.5

2 0 0

2

4

6

8

Time (h)

10

12

0.0 14

L-thrreonine, org ganic acids ((g/l)

Pppc control ppc ÆPtrc -amplified

L threonine concentration L-threonine was increased about 28.8% (1.88g/l vs. 1.46g/l) Volumetric L-Thr productivity was enhanced more than 54% (0 191g/l/h vs (0.191g/l/h vs. 0 0.124g/l/h) 124g/l/h)

L-threonine, organic acids (g g/l)

Bio omass (g/l)

3.7 fold

6

Glu ucose (g/l)

60.1% ↓

L-Thr conc. 17.1 % ↓

Glu ucose (g/l)

7

TH07 (pBRThrABC, pACYC-ppc)

Biom mass (g/l)

298.4

L-threonine,, organic acids (g/l))

TH07 (pBRThrABC, pACYC177) (control strain)

Fed-batch fermentation base strain: TH07C (pBRThrABC)

strain: TH27C (pBRThrE) (# pBRThrE : pBRThrABC-rhtC-rhtA-rhtB)

Glucose,, L-threonine (g/l), ce ell growth ((OD600)

90

77.1 g/l 80

(1.37g/l/h)

70

70.8g/l (1.87g/l/h)

60

50

7.85 g g/l

40

30

20

10

0 0

10

20

30

Time (h)

40

50

60

In silico perturbation analysis for reduced acetate production To determine the most effective flux change for reducing the acetate excretion rate

TH27C (pBRThrE) ( BRTh E)

Genome-scale metabolic model E. coli MBEL979

Min

Max

deletion target pta-ack, poxB

amplification target

acs, ppc, ppc aceBA Min

Max

Reducing the fluxes involved in pta-ack pta ack or poxB will retard growth or increase pyruvate excretion (Causey et al., 2004; Diaziricca, 1991).

ACS overexpression for acetate reduction TH28C (pBRThrE)

TH27C (pBRThrE)

77.1 g/l L-Thr (1.37g/l/h)

7.85g/l

acs mRNA level (real time RT-PCR analysis) 4.81-fold (OD600 32.5) 3.20-fold (OD600 71.2)

L-Thr L Thr productivity (g/l/h) Æ 20.4 % increased acetate excretion Æ 70.1 % decreased

82.4 g/l L-Thr (1.65g/l/h)

2.35g/l

Systems metabolic engineering of E. coli for the production of L-threonine Lee et al. Molecular Systems Biology, 3:149 (Dec 2007) Replacement of attenuator with tac promoter

B Base strain t i 1034th

Ptac

GLC

Ptrc

ptsG

G6P

∆lacI

CÆT

Transcriptome analysis & in silico flux response analysis zwf

6PGL

pgl

6PGC

gnd

RL5P

rpe

pgi

rpiA

X5P

F6P

R5P tktAB

pfkA

FBP

Removall off ffeedback R db k inhibition

DHAP

S7P

tktAB

GAP talAB

fba tpiA

E4P

GAP

F6P

gapA

GBP

acs

pgk

1055th CÆT

gpmA eno

PEP

ppc

pykAF

PYR

aceEF

ACA

pta

ACP

gltA

ppc

OAA

CIT

mdh

MAL

aceB

ICIT

aceA

fumA

GLO

icdA

sucCD

sucAB

FUM sdhACD

AKG SUC

SUCOA

_ 290thCÆT

isoleucine glycine

iclR

ilvA aceBA tdcC tdh rhtABC

Thr

acs

ackA

Ace

Putrescine (1,4-diaminobutane) used for various materials Including nylon nylon-4,6 46 1,3-diaminopropane 1 5 di i 1,5-diaminopentane t

Z. Qian

Construction of a putrescine overproducing strain

Z. Qian

X.X. Xia

Qian et al. (2009) Biotech. Bioeng. 104: 651-662

KmR

Putrescine (1 4-diaminobutane) (1,4 diaminobutane) used for various materials Including nylon-4,6

Identifying genes to be deleted in silico: ÎC ÎCan b be d done as we can sett th those fl fluxes tto ZERO ! Identifying genes to be amplified in silico: ÎVery difficult because mRNA level, protein level, enzyme activity & flux do not necessarily y correlate one another Then, how do we find target genes to be amplified?

Flux Scanning based on Enforced Objective Flux

Flux Scanning based on Enforced Objective Flux Choi et al. al (2010) Appl. Appl Environ Environ. Microbiol. Microbiol In press

Max. product formation rate

Prroduct fo ormation n rate

Identify those fluxes that are also increased

Current actual product formation rate

Biomass formation rate

H.S. Choi H.M. Woo

Creating a cell versus Modifying/Optimizing a cell

Synthetic biology

November 23, 2009

Can we produce PLA and its copolymers by y direct microbial fermentation?

L project j t (2004~) a series of patents pending

Biosynthesis of P(3HB-co-LA) through direct condensation of lactate and 3 3-hydroxybutyrate hydroxybutyrate

3-Hydroxybutyrate

Lactate

Acetyl-CoA y

A t t Acetate Yang et al., (2010) Biotechnol. Bioeng. 105: 150-160 Jung et al., (2010) Biotechnol. Bioeng., 105: 161- 171

Pct + PHA synthase construct Glucose

3HB

Lactate

3HB Propionate CoA-transferase (Pct)

Lactyl-CoA 3HB-CoA PHA synthase

P(3HB-co-LA)

PLA

Pct+PHA synthase+Re-phaAB construct Glucose

Acetyl-CoA + Acetyl-CoA

Lactate

CnPhaA

Lactyl-CoA Propionate CoA-transferase (Pct)

Acetoacetyl-CoA CnPhaB

PHA synthase

3HB-CoA 3HB CoA

PLA P(3HB-co-LA)

Yang et al., (2010) Biotechnol. Bioeng. 105: 150-160 Jung et al., (2010) Biotechnol. Bioeng., 105: 161- 171

Synthetic metabolic network for one-step production of PLA polymers

Y.K. Jung

Yang et al., (2010) Biotechnol. Bioeng. 105: 150-160 Jung et al., (2010) Biotechnol. Bioeng., 105: 161- 171

One-step microbial production of PLA and its copolymers Renewable resources (glucose, (glucose sucrose, sucrose xylose, xylose lactose, lactose fatty acids, acids …))

Dextrose Microbial fermentation

Systems metabolic engineering towards genome-scale genome scale synthetic biology

+ Bioprocess engineering

= Systems biotechnology

S.Y. Lee and B. Palsson

2009 book 20 chapters by world-leaders which cover: Genome Omics G Genome-scale l modeling d li Static & dynamic simulation Plasmids Promoters and network Central metabolic network Protein machinery y engineering g g Metabolic engineering Adaptive evolution Synthetic biology Systems biotechnology Database and bioinformatics ...

Financial supports

Ministry of Education, Science & Technol. Ministry of Knowledge Economy Korean Systems Biology Research Grant Genome to Integrated g Bioprocess p Research Grant BK21 Program World Class Univ Program

LG Chem GSCaltex Bi F lCh BioFuelChem IBM Microsoft

Thank yyou !

http://mbel.kaist.ac.kr