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Reasonably Random Synthetic Biology at Amyris
Tim GardnerDirector, Research Programs & Operations
October 27, 2010
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Overview
► Amyris is an integrated renewable products company producing advanced renewable fuels and chemicals
► Founded in 2003 on principle of social responsibility: use our know-how to address biggest health and environmental challenges
► Public company (IPO September 2010) with R&D, Manufacturing and Distribution facilities in the Emeryville, CA, Campinas, Brazil & Chicago, IL
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Artemisinin is 95% effective against malariaThe Challenge: Supplying Artemisinin Anti-Malarials
50X increase in production10X decrease in price
Treating malaria would require:300 to 500 million treatments per year
Artemisinin treatments needed:225 to 400 tons of artemisinin per year
This would require:6,000,000 tons of plant material
Malaria causes:1 to 3 million deaths per year
Total Chemical Synthesis too expensive
Amyris’ fouding product: Artemsinin
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ispA
G6P
FDP
G3P
PEP
PYR
AcCoA
OAA
MAL
CIT
IPP
TCACycle
FPP
idiDMAP
Glucose
MevalonatePathway
Amorphadiene(arteminin precurser)
Artemisaannua
steroidsquinonesmembranes
Non-profit effort to manufacture Artemsinin
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Strain performance targets reached
0
10
20
30
40
50
0.00 20.00 40.00 60.00 80.00 100.00 120.00 140.00
Am
orph
adie
ne [g
/L]
Time (hrs)
Improvement 1Improvement 2Improvement 3Improvement 4
25g/L target
• Sanofi-aventis now ramping production, formulation and product stability testing• Aim for world-wide distribution in 2012.
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From drugs to fuels
Phase-contrast micrograph of Amyris engineered microbes producing precursor to Amyris Renewable Diesel
Isoprenoid technology platform capable of making more than 50,000 molecules
• Hydrocarbons, not alcohols or esters
• Can be used in existing engines with no performance trade-offs
• Superior environmental profile– substantially lower greenhouse
gas emissions than petroleum– No sulfur– Lower particulates and NOx
• Can be delivered using existing distribution infrastructure
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ispA
G6P
FDP
G3P
PEP
PYR
AcCoA
OAA
MAL
CIT
IPP
TCACycle
FPP
idiDMAP
Glucose
Farenesene
steroidsquinonesmembranes
MevalonatePathway
Diesel production
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8Note: Amyris diesel will be used in blends with conventional fuels; values shown for Amyris diesel is for our biomass derived blending component; SME = Soy Methyl Esters
+1
< – 50 AmyrisDiesel
FAME
# 2-D
47
58.1
40-55
Cetane Number
AmyrisDiesel
FAME
# 2-D
Energy Density1000 BTU/gal
118
121
115-142
AmyrisDiesel
FAME
# 2-D
0 50 100 1500 20 40 60-75 -50 -25 0
-9 to-30
Cloud Point (°C)(cold temp operation)
Additional benefits of Amyris renewable diesel compared to #2-Diesel• 90%+ lower greenhouse gas emissions• No sulfur & produces lower NOx and particulate emissions• Registered with the EPA for 20% blends
Amyris Renewable Diesel: a better fuel
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>$1 Trillion dollar market accessible
fermentation
• Consumer products– detergents– Cosmetics– fragrances
• Lubricants– family of base oils – designed to be high
performance
• Polymers– adhesives– oxygen scavenger– toughening agent
• Renewable diesel– “plug-in” fuels – meets or exceeds stds– substantially lower
emissions
• Other applications– crop protection– many others
Farnesene
By combining biology and chemistry, Biofenebecomes a building block of renewable products for a diverse set of applications
biology
chemistry
$48B
$337B
$809B
>$50B
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Lower cost of production enables access to larger markets
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Low-cost production drives everything in strain R&D
Short term Medium term Long term
Time to value
Fam
iliar
Unf
amili
arU
ncer
tain
Leve
l of r
isk
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
Capital cost-saving opportunities
Engineering decisions drive strain performance criteria
Multi-parameter strain optimization problem• yield• productivity• reduced media supplements• temperature• biocatalyst stability• GMM certification
Amount of savings
For fuel synthesis we aim to direct >90% of cell resources to the synthesis of byproducts under stringent productivity, temperature, and media conditions
2M ton/yr plant
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like getting a toddler to eat salad
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Apr
May
JunJulAug
SepOct
Nov
Dec
JanFebMar
Apr
May
JunJulAug
SepOct
Nov
Dec
Jan
FebMar
Apr
May
JunJulAug
Sep
Oct
Nov
Dec
2007 2008 2009
Fene
prod
uction
But we’ve made rapid progress
Fuels strain improvement since program start
Artemisinin base strain(modified for fuel synthesis)
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Apr
May
JunJulAug
SepOct
Nov
Dec
JanFebMar
Apr
May
JunJulAug
SepOct
Nov
Dec
Jan
FebMar
Apr
May
JunJulAug
Sep
Oct
Nov
Dec
2007 2008 2009
Fene
prod
uction
How we got there
+ process development
+ rational engineering
+ breeding
mutagenesisArtemisinin base strain(modified for fuel synthesis)
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What can we learn from the mutants?
Illumina paired-end sequencing performed by Prognosys, Sequence assembly & analysis by Amyris
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Mutant family tree and performance gains
M
N O
A B
C
D
E
IH
G
LF
P
K
J
Postchild
29 18
8
16
3.1
20
20
11
13
-2
7
18
0high
medium
low
No change
Causal mutations found in•Post-translational regulation•Cofactor synthesis
Most genes we’d never considered. None “on pathway”
One we had tried rationally but not with the right mutation
improvement
MutantStrain X
X
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What about rational engineering?
Are electronics and machines the right paradigm?
Synthetic Biology: the dream of plug and play biology
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The neutral chassis hypothesis
Add a little synthetic biology
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Biology is designed by natural selection
It works, but it’s not always pretty
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Too many parts kinda complexity
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Promoter strength varies depending on its insertion siteG
ene
Exp
ress
ion
1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 41 2 3
A B C D EPromoter
Genome locus
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How much does diversity influence pathway production?
Sporulate(haploidize)
4 diverse hybrid haploids.Select for production
FarnesenePathway
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Impact of diversity on Mevalonate production
Ref
eren
cest
rainFo
ld in
crea
se in
mev
alon
ate
titer
ove
r ref
eren
ce
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Frequencies for top and bottom Mevalonate pools
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A practical approach
Enzyme kinetics
Doable but hard
Context-effects & post-transcriptional regulation
Shooting in the dark
Stoichiometry & mRNA expression
Routine
We always start here
1 Rational Semi-rationalRandom
Random
Pathway PoC Pathway Optimization
We have targeted activities here when bottlenecks become clear
2 3
This is where most of the strain improvement “action” is.
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1. Rational: Modeling / Isotopomers
Input-Public models-Yeastcyc-Amyris knowledge-Experimental data
Output-Balanced models-Simulatable models-Matlab, Excel, GAMS format
Yeast metabolic database
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FermentationDownstreamProcessing(DSP)
Scale-Up
2. & 3. Industrialize strain improvement
AnalyticsKnowledgeManagement
ScreeningRational StrainDesign
RandomMutagenesis
StrainEngineering
Capacity:Screen >70,000 strains / weekTest >40 2L fermentations / week
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Continuous process improvement is critical
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
7.0%
8.0%
5 10 15 20 25 30
Yield of parent strain
Relative improvement for a constant absolute yield gain
CV required to detect winning mutant
Assuming constant absolute yield gain per improved mutant strain. • S/N will drop as yield increases. • So too must CV.
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The value of process control
Original strain screening assay
New assay
Relative production by shake plate assay
Relative production by shake plate assay
Yiel
d in
2L
tank
sYi
eld
in 2
L ta
nks
The reward:
Overall screening process CV <4%
Enables detection of 4% improvements w/ 5% FN and 5% FPs through 2 tiered screen
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HT screening pipelineProcess improvement is easier said than done
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Diagnosing sources of variation
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Y4921
Cou
ntBetter decisions via informatics integrationLIMS systems is identifying and eliminating sources of error
Systematic drops in median plate titer traced to worn posts in one plate shaker
Stra
in s
core
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0.940.260.00
Multivariate optimization – picking winnersInformatics integration is critical to good decisions (get data out of silos)
winner
Stress resistance
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Strain hit from Screening(HTS Proj.)
Calculate Yield
(PV Proj.)
Tank Testing (PV Proj.)
Plate, pick, assay (HTS proj.)
MAD DB
Plate re-testing (MAD Proj.)
PV DB
HTS DB
Data Warehouse
Calculator App Filter, calculate,
store, visualize (K2Y proj.)
Informatics integration enables assessment of stress resistance
Stress resistance metric
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Let the data guideUse empirical data mining to guide library construction, screening conditions, process dev.
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Conclusions
• Rational engineering gets the ball rolling
• Industrialization enables rapid strain optimization– Harnessing nature’s way of “thinking”: randomness and diversity– We are doing in 4 years what used to take 12
• Continuous process improvement is critical to the success of an industrial platform– Informatics is fundamental– Data mining & omics is fundamental
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Thanks to the >200 folks in R&D contributing to our success