E. coli Automatic Directed Evolution Machine - 2009.igem.org2009.igem.org/files/presentation/USTC.pdf · University of Science and Technology of China - iGEM 2009 - E.coli Automatic

University of Science and Technology of China - iGEM 2009 - E.coli Automatic Directed Evolution Machine

E. coli Automatic Directed Evolution Machine

a Universal Framework for Evolutionary Approaches in Synthetic Biology

University of Science and Technology of China


The power of evolution


Biology Engineering

Evolutionary

Algorithm

Directed

Evolution

E. coli Automatic Directed Evolution Machine

Our inspiration


The Goal


The Goal


E.ADEM Framework

Change

Act On

PoPS

Score

PoPS

Score

Kill

PoPSVariation PoPS Selection


Demand Analysis

Variaton = C Score

Death = Population [ ( . )]BasalC Score Avg Score

1 2Death Population ( . ) ( )C Avg Score C Score


The Prototype


pCon 0.15 luxI pCon 0.70 luxR

tetR

AHL

luxR

luxI tetR

pLux-Tet

Self-Adaptive Controller

luxR-AHL

PoPS

PoPS




tetR

AHL

luxR

luxI tetR

pLux-Tet


luxR-AHL

PoPS

PoPS




tetR

AHL

luxR

luxI tetR

pLux-Tet


luxR-AHL

PoPS

PoPS




tetR

AHL

luxR

luxI tetR

pLux-Tet


luxR-AHL

PoPS

PoPS




tetR

AHL

luxR

pCon X

VR X

mRFP luxI tetR

pLux-Tet ccdB

Selection FunctionScoring Function

Self-Adaptive ControllerReporter


Selection function

tetR

pLux-Tet ccdB

luxR-AHL


tetR

pLux-Tet ccdB

luxR-AHL

AHL

High AHL & Low tetR

tetR

pLux-Tet ccdB

luxR-AHL

AHL

High AHL & High tetR

tetR

pLux-Tet ccdB

AHL

Low AHL & High tetR

luxR

tetR

pLux-Tet ccdB

luxR

AHL

Low AHL & Low tetR

Selection function


pCon X

VR X

mRFP luxI tetR

tetRAHL

High score E.coli

tetRAHLLow score E.coli

pLux-Tet ccdB

pCon X

VR X

mRFP luxI tetRpLux-Tet ccdB


pCon X

VR X

mRFP luxI tetR

tetRAHL

High score E.coli


pLux-Tet ccdB

pCon X

VR X

mRFP luxI tetRpLux-Tet ccdB


pCon X

VR X

mRFP luxI tetR

tetR

AHL


High score E.coli

pLux-Tet ccdB

pCon X

VR X

mRFP luxI tetR


Measurement and Modeling


• Basic measurement strategy

B0034 GFP B0015

PoPS

Use spectrfluorophotometer to measure fluorescence intensity

Measurement and Modeling

Reporter


• Standard measurement

Standard unit: ustc_st1Strains : TOP10Plasmid: pSB1A3Medium: M9 supplemented mediumReporter: GFP BBa_I13504

Measurement

More details about the measurement are available on our team wiki:http://2009.igem.org/Team:USTC/Standard_%26_Protocol

http://2009.igem.org/Team:USTC/Standard_&_Protocol


pCon 0.15 pCon 0.70 luxR

tetR

AHL

luxR

pCon X

VR X

mRFPtetR

ccdB

luxI

pLux-Tet



luxI

luxR-AHL


1. pLux-Tet2. pLux-Tet + GFP3. pCon×4 + luxR + pLux-Tet4. ccdB×85. pCon×86. pCon×8 + GFP7. pCon + luxR8. pCon×7 + luxI (AHL detection by 9)9. pCon×4 + luxR + pLux-Tet + GFP (AHL)10. pCon×4 + luxR + pLux-Tet + ccdB×8 (AHL)11. tetR×212. tetR×2 + pCon×2 + luxR + pLux-Tet [+ GFP]13. pCon×4 + tetR×2 + pCon×2 + luxR + pLux-Tet

[+ GFP] (AHL/aTc)14. [pCon×7 +] luxI + pCon×2 + luxR + pLux-Tet

[+ ccdB×8 | + GFP] (AHL)15. VR×1016. (VR + pCon)×717. tetR + pCon + luxI + pCon + luxR + pLux-Tet [+ ccdB | + GFP]18. [mRFP +] luxI + tetR + pCon + luxI + pCon + luxR + pLux-Tet [+ ccdB | + GFP]19. (VR + pCon)×5 + tetR + pCon + luxI + pCon + luxR + pLux-Tet [+ ccdB | + GFP]20. (VR + pCon)×5 + mRFP + luxI + tetR + pCon + luxI + pCon + luxR + pLux-Tet [+ ccdB | +

GFP]

1

4

5

2

3

6

8

7

9

10

12

14

18

17 16

20

19

15

13

11

Delayed

Waiting

Working

Done

Sequenced

Measurement



tetR

AHL

luxR

mRFP luxI tetR

pLux-Tet ccdB

pCon X

VR X

Constitutive Promoter


pCon X

VR X

FLU

/OD

(ust

c_st

1)

Constitutive Promoter

6,658.77 4,686.81

1,025.27

88.39

4.50 2.88

1

10

100

1000

10000

Promoter strength

K176011 K176012 K176013 K176014 K176015 K176016



tetR

AHL

luxR

pCon X

VR X

mRFP luxI tetR

ccdBpLux-Tet

Hybrid Promoter

Hybrid promoter as a logic gate


pLux-Tet

Hybrid Promoter




tetR

AHL

luxR

pCon X

VR X

mRFP luxI tetR

ccdBpLux-Tet

Hybrid Promoter



0

200

400

600

800

1000

1200

1400

1600

0 0.2 0.4 0.6 0.8FL

U/u

stc_

st1

OD600

Pcon+LuxI-->Hybrid promoter

Pcon0.01

Pcon0.04

Pcon0.15

Pcon0.36

Pcon0.70

Other measurement


Hybrid promoter response to LuxI



Other measurement


0500

1000150020002500300035004000

0 2 20 200 2000

FLU

/OD

/ust

c_st

1

c(aTc)ng/ml

aTc response

cAHL 1e-6M

cAHL 1e-4M


Hybrid promoter response to aTc



Other measurement



Hybrid promoter response to aTc

Efficiency of cI/pcI inverter

0

200

400

600

800

1000

1200

1400

0 0.2 0.4 0.6

FLU

/ust

c_st

1

OD600

Inverter

K176016+Q+G

K176015+Q+G

K176014+Q+G



• Previous work: lacZα-ccdB

• Did not work very well. Still working…

• Different versions of ccdB we have tried

ccdB

lacZα-ccdB

B0031

B0031

B0015

B0015

ccdB-LVA

lacZα-ccdB-LVA

B0031

B0031

B0015

B0015

ccdB

lacZα-ccdB

B0034

B0034

B0015

B0015

ccdB-LVA

lacZα-ccdB-LVA

B0034

B0034

B0015

B0015

ccdB parts

You L, Cox RS 3rd, Weiss R, Arnold FH. Programmed population control by cell-cell communication and regulated killing. Nature. 2004 Apr 22;428(6985):868-71.


We estimate the values of k3, rAHLin, C1, C2, C3 and C4, using the data from our measurements. The simulation results as follows. k3=0.8min-1; rAHL=0.001min-1; C1=1.5*10-10; C2=1*1010; C3=8*10-7; C4=5.8*1011

ModelingpLux-Tet


The dots in the graph represent our experiment data and the curve and surface represent our simulation results.

Simulation results


★ Submit over 160 BioBrick parts to the registry

★ Characterize most of the parts

★ Comprehensive measurement data for whole system modeling

★ Introduce evolutionary algorithm into synthetic biology

★ A modular framework for automatic in vivodirected evolution

Summary


Future Plan

Short-term plan:

Use GFP to check the output of the self-adaptive controller

Try alternative proposal of the selection function, such as antisense RNA



tetR

AHL

luxR

pCon X

VR X

mRFP luxI tetR

pLux-Tet ccdB



Quorum-sensing I

Quorum-sensing II

luxR-AHL



tetR

AHL

luxR

pCon X

VR X

mRFP luxI tetR

pLux-Tet ccdB



Quorum-sensing I

Quorum-sensing II

luxR-AHL

PoPS

GFP


Future Plan

Short-term plan:

Use GFP to check the output of the self-adaptive controller

Try alternative proposal of the selection function, such as antisense RNA


Future Plan

Long-term plan:

E.ADEM as collaborative project in OpenWetWare

Realize the scoring functions for transcription repressor, sensor, logic gate, enzyme and binding partner

Develop variation functions for site-specific mutagenesis and recombination

Fine-tune the parameters in the self-adaptive controller


• Sponsors

• iGEM community

• Teaching Affairs Office, USTC

• Graduate School, USTC

• Foreign Affairs Office, USTC

• School of Life Sciences, USTC

Acknowledgments


Tsien Hsue-shen (钱学森)1911.12.11-2009.10.31

Father of Space Tech in China

Bei Shi-zhang (贝时璋)1903.10.10-2009.10.29

Father of Biophysics in China

In Memory of Our Great Masters


Thank You


Supplementary Slides:


Directed Evolution vs.Evolutionary Algorithm

Poelwijk et al. 2007. Empirical fitness landscapes reveal accessible evolutionary paths. Nature 445, 383-386.


How to Design the Scoring Function?

Here’s some examples.


Transcription Repressor


pCon

x

pX

Evolution Object

Scoring Function



pCon

x

pX

Evolution Object

Scoring Function



pCon

x

pX

Evolution Object

Scoring Function

!Score



pCon

x

pX

Evolution Object

Scoring Function

!Score


X' = pCon - dX X

!Score = pX KdX / (X + KdX)


pCon

x

pX

Evolution Object

Scoring Function

!Score


X' = pCon - dX X

!Score = pX KdX / (X + KdX)

Xs = pCon / dX

!Scores = pX dX KdX / (pCon + dX KdX)


Device (e.g. Sensor, Logic Gate):Supervised Learning

Input Output

Supervision (Reference Output)

!Score

Scoring Function


More

• For Enzyme:

– If there is a sensor for the product or substrate, use it as the scoring function.

– Else, perform evolution for a sensor first.

• For Binding Partner:

– E. coli two-hybrid systems.

– Logic gates based on binding.


How to Design the Scoring Function?

Conclusion:GenotypePhenotype

Signal TransductionTranscription Rate (PoPS)

Universal Interface of E.ADEM


Control Strategiesin Evolutionary Algorithm

• Deterministic Control

– No Feedback

• Adaptive Control

– Feedback Control

• Self-Adaptive Control

– The Evolution of Evolution Parameters


Variation Function

• Targeted Mutagenesis– Activation Induced (Cytidine) Deaminase (AID)

• iGEM 2008 Peking_University• iGEM 2008 Warsaw

– Multiplex Automated Genome Engineering (MAGE)– Error-prone DNA polymerase I– Bacteriophage

• Recombination– Site-specific recombination

• Including Inversion, Excision/Integration and Translocation

– Homologous recombination– Transposition


Avoiding Non-Specific Mutationis a Must

• One More Immature Idea:Variation Cell

EvolutionObject

Selection CellConjugation ?


Selection Function: Killer or Saver

Death ccdB

Selection Function

Death asRNA

Selection Function

pCon

RBS kanR

Death

Death

OR


Reporter

• Real-time Monitoring Evolution Dynamics by FACS

• Further Screening Reporter

Reporter

iGEM 2008 Tokyo_Tech

mRFP Reporter


21.cI + pCI

22.cI + pCI + GFP

23.(VR + pCon)×7 + cI + pCI + GFP

24.cI + pCI + luxI

25.AID

26.[AID +] mRFP + cI + pCI + luxI

27.[AID +] mRFP + cI + pCI + luxI + tetR + pCon + luxI + pCon + luxR + pLux-Tet [+ ccdB | + GFP]

28.(VR + pCon)×7 + mRFP + cI + pCI + luxI + tetR + pCon + luxI + pCon + luxR + pLux-Tet [+ ccdB | + GFP]

29.pNOT

30.pNOT + GFP

31.pNOT + [AID +] mRFP + cI + pCI + luxI

32.pNOT + [AID +] mRFP + cI + pCI + luxI + tetR + pCon + luxI + pCon + luxR + pLux-Tet [+ ccdB]

33.repressor

34.pNOT + repressor

1726

21

22

23

2731

29

3033

34

25 24

2832


pCon 0.15 luxI-LVA pCon 0.70 luxR

tetR

AHL

luxR

pCon X

VR X

mRFP luxI tetR

pLux-Tet ccdB

Quorum sensing I

Quorum sensing II

AID pCIcI


Human Practice

• Ethic

The chance to play God?

• Safety

Experimental Safety

E.ADEM Safety

• Security

Dilemma


• OpenWetWare

• Restore the System

Supervise the Mutation

Suicide Switch

E. coli Automatic Directed Evolution Machine - 2009.igem.org2009.igem.org/files/presentation/USTC.pdf · University of Science and Technology of China - iGEM 2009 - E.coli Automatic

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