Reasonably Random Synthetic Biology at ?· Reasonably Random Synthetic Biology at Amyris ... ispA. G6P.…

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  • Reasonably Random Synthetic Biology at Amyris

    Tim GardnerDirector, Research Programs & Operations

    October 27, 2010

  • 2

    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

  • 3

    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

  • 4

    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

  • 5

    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.

  • 6

    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

  • 7

    ispA

    G6P

    FDP

    G3P

    PEP

    PYR

    AcCoA

    OAA

    MAL

    CIT

    IPP

    TCACycle

    FPP

    idiDMAP

    Glucose

    Farenesene

    steroidsquinonesmembranes

    MevalonatePathway

    Diesel production

  • 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

  • 9

    >$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

  • 10

    Lower cost of production enables access to larger markets

  • 11

    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

  • 12

    like getting a toddler to eat salad

  • 13

    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 weve made rapid progress

    Fuels strain improvement since program start

    Artemisinin base strain(modified for fuel synthesis)

  • 14

    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)

  • 15

    What can we learn from the mutants?

    Illumina paired-end sequencing performed by Prognosys, Sequence assembly & analysis by Amyris

  • 16

    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 inPost-translational regulationCofactor synthesis

    Most genes wed never considered. None on pathway

    One we had tried rationally but not with the right mutation

    improvement

    MutantStrain X

    X

  • 17

    What about rational engineering?

    Are electronics and machines the right paradigm?

    Synthetic Biology: the dream of plug and play biology

  • 18

    The neutral chassis hypothesis

    Add a little synthetic biology

  • 19

    Biology is designed by natural selection

    It works, but its not always pretty

  • 20

    Too many parts kinda complexity

  • 21

    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

  • 22

    How much does diversity influence pathway production?

    Sporulate(haploidize)

    4 diverse hybrid haploids.Select for production

    FarnesenePathway

  • 23

    Impact of diversity on Mevalonate production

    Ref

    eren

    cest

    rainF

    old

    incr

    ease

    in m

    eval

    onat

    e tit

    er o

    ver r

    efer

    ence

  • 24

    Frequencies for top and bottom Mevalonate pools

  • 25

    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.

  • 26

    1. Rational: Modeling / Isotopomers

    Input-Public models-Yeastcyc-Amyris knowledge-Experimental data

    Output-Balanced models-Simulatable models-Matlab, Excel, GAMS format

    Yeast metabolic database

  • 27

    FermentationDownstreamProcessing(DSP)

    Scale-Up

    2. & 3. Industrialize strain improvement

    AnalyticsKnowledgeManagement

    ScreeningRational StrainDesign

    RandomMutagenesis

    StrainEngineering

    Capacity:Screen >70,000 strains / weekTest >40 2L fermentations / week

  • 28

    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.

  • 29

    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

  • 30

    HT screening pipelineProcess improvement is easier said than done

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