ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
ITE 25th Birthday Celebration
Heraklion, Crete, 8 November, 2008
Reflections from the explorations of an engineer in the space of
life sciences
Gregory StephanopoulosMIT
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
Mixed cultures
ProductTank
Feed TankWith glucose
Aqueous medium with cells
F (L/h) F (L/h)
Scale
Parameters:
• Dilution Rate, D=F/ V• Substrate feed, Sf
M1+
B1
S
B2 P(Glucose)
+
+ M2
-
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
• Take advantage of an enriched pool of genes by sustaining more than one species in the same system
Mixed Cultures(progenitor of Metabolic Engineering)
Science, 213, pp. 972-979 (1981)
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
Following the recombinant revolution
• Instead of sustaining a mixed culture, transfer relevant pathways into a single cell
(genesis of)
Metabolic EngineeringScience, 252, pp. 1675-1681 (1991)
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
M1
+
B1
S
B2 P(Glucose)
+
+ M2
-
From mixed cultures …
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
Asp
Lysine
CO2
Glt
Gln
AspartaticsemialdehydeHomoserine
Threonine
Methionine
Trehalose
PYR
H4D
meso-DAPSuc
OAA
GLC6P
FRU6P
GAP
Acetate
ALA, VAL, LAC
Ribu5P
Sed7PE4PFru1,6bP
G3P
GLC
PYR
PEP
AcCoA
Isocit
aKG
Mal
Fum
To metabolic pathways …
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
To complex models of multi-level regulation and metabolism
1 23
4
Stephanopoulos, et al., “Exploiting biological complexity for strain improvement through systems biology,” Nature Biotechnology, 22: 1261-1267 (2004)
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
Lessons from the explorations of an
engineer in the space of life sciences
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
The Engineering ethosIntegration
Making sense of large systems and a lot of dataData-driven hypotheses
QuantificationModelsStructure of interactions Patterns of characteristic phenotypes
RelevanceDoing things for a reason
Lesson 1:Define the line between engineering
and life sciences
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
Asp
Lysine
CO2
Glt
Gln
AspartaticsemialdehydeHomoserine
Threonine
Methionine
Trehalose
PYR
H4D
meso-DAPSuc
OAA
GLC6P
FRU6P
GAP
Acetate
ALA, VAL, LAC
Ribu5P
Sed7PE4PFru1,6bP
G3P
GLC
PYR
PEP
AcCoA
Isocit
aKG
Mal
Fum
Back to metabolic engineering …
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
Metabolic Engineering as a new Organic Chemistry
Metabolic Engineering: Making improved biocatalysts (or engineering microbes) capable of :
Enhanced production of a native product to a microorganism
Formation of a product that is new to the microorganism
Synthesizing novel products
Science, 252:1675-1681 (1991)
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
Asp
Lysine
CO2
Glt
Gln
AspartaticsemialdehydeHomoserine
Threonine
Methionine
Trehalose
PYR
H4D
meso-DAPSuc
OAA
GLC6P
FRU6P
GAP
Acetate
ALA, VAL, LAC
Ribu5P
Sed7PE4PFru1,6bP
G3P
GLC
PYR
PEP
AcCoA
Isocit
aKG
Mal
Fum
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
Probing cellular function
DNA microarrays
Environment
DNA
mRNAFluxes
Proteins
Proteomics Metabolic Flux Analysis
Signal Transduction
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
Lesson 2
Biology, at the molecular level, is a
Chemical ScienceChemical engineering is the natural
engineering discipline to explore the applied aspects of biology at the cellular and molecular levels
Stephanopoulos G., “Chemical and Biological Engineering,”Chemical Engineering Science, 58: 3291-3293 and 58: 4931-4933
(2003).
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
ths
ASP
ASA
DAP
Lys
Hom
Meth
Thr
Ile
hdh
hkdapA
Science, 252: 1675 (1991)Biotech. & Bioeng. 41 633 (1993),Biotech. Progress, 10: 320 (1994)Biotech. & Bioeng. 58: 149 (1998)Science: 292:p.2024 (2001)
Example 1: Engineering the aspartate aminoacid pathways
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
Lesson 3
There are many biologies besides
molecular biology
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
Schematic pathway of aminoacid biosynthesis in C. glutamicum
Asp
Lysine
CO2
Glt
Gln
AspartaticsemialdehydeHomoserine
Threonine
Methionine
Trehalose
PYR
H4D
meso-DAPSuc
OAA
GLC6P
FRU6P
GAP
Acetate
ALA, VAL, LAC
Ribu5P
Sed7PE4PFru1,6bP
G3P
GLC
PYR
PEP
AcCoA
Isocit
aKG
Mal
Fum
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
Probing metabolic pathways using isotopic tracers
Can help in:
• Reconstructing metabolic networks
• Calculating pathway fluxes
• Identifying rate-controlling steps
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
Schematic pathway of aminoacid biosynthesis in C. glutamicum
Asp
Lysine
CO2
Glt
Gln
AspartaticsemialdehydeHomoserine
Threonine
Methionine
Trehalose
PYR
H4D
meso-DAPSuc
OAA
GLC6P
FRU6P
GAP
Acetate
ALA, VAL, LAC
Ribu5P
Sed7PE4PFru1,6bP
G3P
GLC
PYR
PEP
AcCoA
Isocit
aKG
Mal
Fum
Simultaneous amplification of pyc and ask increased lysine qpby 100-300%Park et al.,Biotech. & Bioeng., 55: 864 (1997)
Koffas et al., Metabolic Eng., 5:32-41, (2003)
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
Lesson 4
Metabolic engineering is far more powerful in constructing
optimal biocatalysts than chemical catalysis
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
Example 2: Indene biocatalysis for the synthesis of Crixivan precursor
• Crixivan™: Merck’s HIV protease inhibitor
N
N
NHN
OH
O NHC(CH3)3O
OH·H2SO4
Aminoindanol
• Chemical synthesis of aminoindanol requires the use of expensive catalyst and gives low yields.
• Increased production is desired to meet patient needs (1 kg/patient/year).
• Bioconversion can potentially result in 100% yield.• Project focus on production of 2R-indandiol.
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
Indene Bioconversion by RhodococcusStafford et al., PNAS, 99:1801-1806, (2002);
European J. of Biochemistry, 278: 1450-1460 (2001)
Indene
OH
1-Indenol
1-indanone
O
OH
OH
trans-(1R,2R)-indandiol
OH
OH
cis-(1S,2R)-indandiol
O
indene oxide
OH
O
1-keto-2-hydroxy-indan
OH
OH
cis-(1R,2S)-indandiol
Proposed NetworkDecoupled from primary metabolism
IndeneOH
1-Indenol
1-indanone
O
OH
OH
trans-(1R,2R)-indandiol
OH
OH
cis-(1S,2R)-indandiol
O
indene oxide
OH
OH
cis-(1R,2S)-indandiol
OxygenaseActivities
OH
O
1-keto-2-hydroxy-indan
DehydrogenaseActivities
Extracellular medium
Strain I24Cell
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
Rational pathway design
indene
OH
OH
1,2-indenediol
O
indene oxide
1-indenol OH
1-indanoneO
OH
O
1-keto-2-hydroxy-indan
OH
OH
cis-(1S,2R)-indandiol
OH
OH
trans-(1R,2R)-indandiol
OH
OH
cis-(1R,2S)-indandiol
1. Isolation of KY1 (Y=50%)2. Network definition3. Flux analysis4. LimA overexpression (Y=75%)5. pH optimization (Y=95%)
Stafford et al., PNAS, 99:1801-1806, (2002);European J. of Biochemistry, 278: 1450-1460 (2001)
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
Lesson 5
Sometimes it pays to combine some math with genetics and
molecular biology
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
Record of Metabolic Engineering
Aminoacids: Increases in lysine specific productivity by 120-300%Ethanologenic E. coliBiopolymers (Metabolix-ADM)1,3 propane diol (DuPont-Tate and Lyle)Indan-diol production (precursor of Crixivan-HIV protease inhibitor): Yield increased from 25% to >95%Artemisinin (amorphadiene) production by yeast and E. coliLycopene production in E. coli: Increase from 4,500 to ~25,000 ppm of CDW, fermentations > 250 mg/LMany other applications:
Succinate3-HPAThreonineTyrosine
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
Isoprenoid pathway
PYR
G3P
DXP
DMPP
IPPPdxs
idiisp
genes
Chromosome-based Genes Plasmid-based Genes
LycopenecrtEBI
crtE
crtI
crtBCm pACLYC
Other CarotenoidsWS140: dxs, isp, idi
over-expressions: ~4,000ppm
TaxolArtemisininTerpenoids
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
0
1
2
3
4
5
6
7
8
0 10 20 30 40 50 60 70
Time (h)
Glu
cose
(g/L
) , O
D60
0, p
H
0
5000
10000
15000
20000
25000
30000
Lyco
pene
(ppm
)
OD600pHAcetatelycopene
Fed batch fermentation of yjiD over-expressing strain in the background of triple
knock-outs (ΔgdhA, ΔaceE, and ΔFdhF)
0
1
2
3
4
5
6
0 20 40 60 80
Time (hour)
Glu
cose
(g/L
)
Feeding profile
Nature Biotechnology, 23: 612-616 (2005)
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
Constructing an oil-producing, obese microbe
Lesson 7
If an experiment does not work the first time, order new
reagents and repeat
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
How does Metabolic Engineering differ from
Genetic Engineering?
… Metabolic engineering differs from Genetic Engineering and related molecular biological sciences in that it concerns itself with the properties of the entire metabolic network as opposed to individual genes and enzymes.
"Metabolic Engineering: Issues and Methodologies," Trends in Biotechnology, Vol. 11, pp. 392-396 (1993)
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
What is Metabolic Engineering?
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
The biotech revolution, and the chemical-fuels industry (White Biotech)
Fuels and chemicals were the initial biotech targetCetus (Chiron), Genex, Biogen
More challenging technical problem than insulinSwitch of emphasis to medical applications
Changing boundary conditions Emphasis on renewable resourcesRobust US federal funding ⇒ Applied mol. biologyGenomicsSystems Biology: a new mindframe in biological researchMetabolic Engineering
Exploit applications of biology beyond medicine
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
What is different now: The New Biology
Unprecedented ability to transfer and modify (mutate) genes and amplify and control gene expression by molecular biological methods (genetic engineering)Genomics: Genome sequencing and study of
genomes. From a few to lots and lots of genesGenomics-based technologies for probing
intracellular content on cell-wide basisA new mind-frame for studying biological systems
that addresses issues in an integrated manner: Systems Biology
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
Eliciting new multigenic phenotypes
Eliciting tolerance to toxicity in yeast and bacteria
Engineering microbes that can tolerate high concentrations of biofuels (ethanol)
Key in emerging industry of cellulosic biofuels
G. Stephanopoulos, “Challenges in engineering microbes for biofuels production,”Science, 315: 801-804, (2007)
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
Gene-to-phenotype mapping
G1
G2
Gn
Gf
…
P1
P2
Pn
Pf
…
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
Transcriptome-to-phenotype mapping
T1
T2
Tn
Tf
…
P1
P2
Pn
Pf
…
Gx
TF, σ
Global Transcription machinery controls the transcriptome
Gene 1
Gene 2
Transcription machinery
(polymerase)
Promoter 1
Factor
Promote
r 2
XGene 1 mRNA
Protein 1
Factor
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
Exp
ress
ion L
evel
Gene
Exp
ress
ion L
evel
Gene
global Transcription Machinery Eng’g (gTME): a tool for reprogramming the transcriptome
Native machinery Engineered machinery
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
Lesson 9
Diversity pays!
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
rpoD*
rpoD*rpoD*
rpoD*
rpoD*
rpoD
rpoD*
Error-prone PCR
Cloning followed by phenotype selection or screening
Iterative, directed
application of gTME
Sigma factor engineering strategy
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
Ethanol Tolerance
50 g/L Ethanol
60 g/L Ethanol
70 g/L Ethanol
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
Ethanol tolerance—growth curves
20 g/L 40 g/L 50 g/L
60 g/L 70 g/L
Red =Round 3
Blue =Native rpoD
00.10.20.30.40.50.60.70.8
0 2 4 6 8 100
0.05
0.1
0.15
0.2
0.25
0 2 4 6 8 100
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0 2 4 6 8 10
00.0050.01
0.0150.02
0.0250.03
0.0350.04
0 2 4 6 8 100
0.005
0.01
0.015
0.02
0.025
0 2 4 6 8 10
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
Low Inoculum fermentations
Medium: YSC –URAGlucose: 20 g/LCulture: 50 ml in 250 ml flasksAgitation: 225 RPMInitial OD: 0.01
The SPT15 mutant exhibits a nearly identical growth rate to the control, but continues exponential growth longer
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
High cell density fermentations
Medium: YSC –URAGlucose: 100 g/LCulture: 40 ml in 250 ml flasksAgitation: 225 RPMInitial OD: 15
Science, 314: 1565-1568 (2006)Metabolic Engineering, 9: 258-267 (2007)
Proceedings National Academy of Sciences, 105: 2319-2324 (2008).
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
HCDC summary
0.35(86%)
0.310.221.205.394.10
Control
+15%
+14%+41%+69%+20%---
% Improvement
2.03Productivity (g/L h-1)
0.31Specific rate (g/dcw h)
0.40(98%)
True EtOH yield accounting for biomass production(Percent of 0.41 g/g theoretical)
0.36Conversion yield calculated between 6 and 21 hours
6.46Final DCW (g/L)
4.06Initial DCW (g/L)
Mutant
⎟⎟⎠
⎞⎜⎜⎝
⎛1-1-
-1-1
h L consumed Glucose ghL produced EtOH g
⎟⎟⎟⎟⎟
⎠
⎞
⎜⎜⎜⎜⎜
⎝
⎛
⎟⎟⎠
⎞⎜⎜⎝
⎛ 1-1-
1-
L producedgDCW DCW g 0.5
glucose g 1 - L utilized Glucose g
L produced EtOH g
ITE 25th - 2008November 8, 2008G. Stephanopoulos
Bioinformatics and Metabolic Engineering Laboratory
Lesson 10
Exploring the applied side of life sciences during the past
25 years:An incredible journey and a life of
perpetual change