Integrated Evolution Machine

YAO Runwen     HUANG Junxiang ZHANG Mingxuan TANG Wei     JI Xiang     XIE Yanwen

Sun Yat‐Sen University, Guangzhou, China

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Nothing in Biology Makes Sense Except in the Light of                   .

Theodosius DobzhanskyEvolution

Directed

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Directed Evolution

Diversification

Selection 

Amplification

A lot of limitationsTime-consuming

Integrated Evolution Machine

Overview

Overview Overview

Overview What is the IgEM?

IgEM

Overview

Defective Phage

Without geneVIII

E. Coli

Can express geneVIIIUnder special condition

What is the IgEM?

Mutagenesis Module  Screening Module Synchronization Module

Overview Beginning— Synchronizing the penetration

E. coli

0 ℃30 ℃

Overview

E. coli

0 ℃30 ℃

E. coli

Mutation

Step 2 Diversification—Generate the library

• Inhibit proofreading activity • Enhance the SOS response

Gene VIII：Make the defective phage enable to

release

Bacterial Two-Hybrid system ：

Protein-protein Interaction ↓

Reporter gene Expression

Overview Step 3 Selection—Screen the best gene

0 ℃30 ℃

Gene VIII：Make the defective phage enable

to release

E. coli

Mutation

E. coli

Overview Step 3 Selection—Screen the best gene

0 ℃30 ℃

mRNA of geneVIII

Overview

0 ℃30 ℃

E. coli

mRNA of geneVIII Rise to 37℃

37 ℃0 ℃

Step 4 Amplification—Synchronize the phage release

RNA Thermometer

Next Cycle

Diversification

Selection

Amplification

StartRestart

Design & Result

Design & Result Design & Result

Diversification

Selection

Amplification

StartRestart

Design & Result Library generated by Mutagenesis

MutagenesisPlasmid

Diversification

Design & Result Mutagenesis plasmid

Diversification

Design & Result 5 - fold dnaQ926 is sufficient

Aver

age

Mut

atio

n R

ate

(sub

stitu

tions

/bp)

c(dnaQ926)/c(dnaQ)

Diversification

Design & Result

Blank A B

All genes are expressed

RFP RFP

Diversification

Design & Result

？selection

Bacterial Two-Hybrid System

Diversification Selection

Design & Result Bacterial Two-Hybrid System

Genotype Phenotype

Diversification Selection

Design & Result

bind to λ operator (Or2)

RNA Polymerase α subunit:Activate transcription

Protein Interaction

The Bacterial Two-Hybrid System ( B2H)Protein interaction ↔ Gene transcription 

Diversification Selection

Design & Result The Bacterial Two-Hybrid System ( B2H)Protein interaction ↔ Gene transcription 

Three plasmid(pBT, pTRG, pRPT) co-transformation

Diversification Selection

Design & Result Work or not?The B2H system can work

Bait PreyRFP GAL11P

RFP RFP

LGF GAL11P

LGF RFP

MCS GAL11P

MCS GAL11P

Diversification Selection

Design & Result Weak or Strong?

Different Interaction strength

Different Reporter gene expression

Diversification Selection

Design & Result

Negative Original Low Medium High

Weak or Strong?

Point mutation→Low, Medium, High strength of interaction

Between LGF and GAL11P

Diversification Selection

Design & Result Weak or Strong?

Interaction strength

The B2H system can tell the difference

Diversification Selection

shift RNAPα‐Preyfrom pTRGto a gene Ⅷ deficient M13 vector

Change the reporter gene to gene Ⅷ

M13

Design & Result Adaptation for IgEM

Diversification Selection

Design & Result Model simulation of the B2H in IgEM

?

Diversification Selection

Design & Result Chemical Dynamics Model

Diversification Selection

Processes considered:

Parameters from Wet‐lab & Relative Materials

Methods:• Chemical Dynamics• Differential Equations• Numerical Computation

• Bacterial Two‐hybrid system• Protein interactions • Background expression• Transcription of GeneVIII

• Life cycle of M13 phage• Rolling cycle replication• Gene expression• Synthesis & degradation of protein• Assembly & Release

Design & Result Binding energy is positively related to progeny number

Diversification Selection

Design & Result Selectable Binding Energy Interval

Diversification Selection

7.7 10.7

Design & Result Selectable Binding Energy Interval

Diversification Selection

Selectable Interval

Design & Result ‐‐Tune [ ] expression according to stages of evolution

Diversification Selection

Design & Result ‐‐Tune [ ] expression according to stages of evolution

Diversification Selection

StrongInteraction

Weak interaction

Strong interaction

Increase [ ] when interaction is weak in the beginningDecrease [ ] when  interaction is strong 

Synchronizing the release of M13 phage offspring

Strictly control

Better performance

Two requirements

One cell

Selection step

Amplification step

Design & Result Amplification

38Diversification Selection Amplification

3939Diversification Selection Amplification

Design & Result RNA thermometer(RNAT)

The Rose element(BBa_K115001) 

The PrfA element(BBa_K115003)

The FourU Element(BBa_K115002)

control

4040Diversification Selection Amplification

Design & Result Testing RNAT

FourU worked well

4141Diversification Selection Amplification

Design & Result Testing the FourU

3h

FourU respond rapidly to temperature change

Design & Result Shift Experiment

4242Diversification Selection Amplification

千凝微1姚润文7

幻灯片 42

千凝微1  @学霸，曲线图要放么？主要对照度是有下降…千凝微, 2014/10/21

姚润文7  也放上去吧姚润文, 2014/10/21

4343Diversification Selection Amplification

Design & Result Integration with B2H system

FourUworked well with B2H system

Diversification Selection Amplification

How evolution takes place in each cycle of experiments?

Modeling

Modeling ModelingSequence Evolution

Method: Direct simulation

Processes:• DNA replication• Point mutation• Translation• Score • High pressure selection

Original Sequence

↓evolvedTarget Sequence

Modeling Sequence Evolution

Target InitialEvolving

Score

Modeling Population Evolution

Assumption: Similarity is positively related to progeny number

Not change

Modeling Population Evolution

Accumulate diversityForm wide similarity distribution

Evolution

Initial Plateau

Modeling Parameters of Simulations

• Mutation rate• Population of phages• Selection time• Size of protein• Background expression of GeneVIII• Maximum binding energy• Maximum Progeny number• Original similarity……

Modeling

Increase [DNAQ] in the beginning for fast evolutionDecrease [DNAQ] later for high final similarity

Tune [DNAQ] for fast evolution and high final similarity

More

More More

AchievementFuture WorkApplicationReference

Achievements

√ Tested every part independently

√ Constructed 45 BioBricks;Deposited 41 BioBricks in Registry

√ Improved characterization of 2 previous BioBricks

√ BBa_K1333000 ~ BBa_K1333005√ BBa_K1333101 ~ BBa_K1333112√ BBa_K1333200 ~ BBa_K1333204√ BBa_K1333300 ~ BBa_K1333321

√ BBa_I12210√ BBa_K577881

Applications

Valuable Proteins

Traditional method

Human Infective

Quickly Mutated

Fiercely Break UpPathogen

Time-consumingLimited

Less effective

Applications

single-chain antibody fragment

Traditional method

Human Infective

Quickly Mutated

Fiercely Break UpPathogen

EfficientlyDiversely

More effective

http://www.theguardian.com/ http://www.improntalaquila.org/ http://www.medicinenet.com

Applications

Robert F. Weaver. Molecular Biology, 5th edition

Flu Virus Ebola VirusSARS Virus

single-chain antibody fragment

Future Work

• Integrate all parts into one

• Model and improve the performance

• Apply CRISPR to realize site-directed mutagenesis

• Apply IgEM to more organisms

http://www.k618.cn/ http://www.im.cas.cn/

Interlab√ Measure GFP√  Extra credits:

Measure cell-to-cell variation for the three required devices

iGEM China Community iGEM Coference Newsletter

Human Practice

References

[1]Calendar, R. The Bacteriophages (Oxford Univ. Press, 2006) .[2]van Wezenbeek PM, et al., Nucleotide sequence of the filamentous bacteriophage M13 DNA genome: comparison with phage fd, Gene 1980.[3]Russel M, Moving through the membrane with filamentous phages, Trends Microbiol. 1995 Jun;3(6):223‐8.[4]. Esvelt, K.M., J.C. Carlson and D.R. Liu, A system for the continuous directed evolution of biomolecules. Nature, 2011. 472(7344): p. 499‐503.[5]. Fijalkowska, I.J. and R.M. Schaaper, Mutants in the Exo I motif of Escherichia coli dnaQ: defective proofreading and inviability due to error catastrophe. Proc Natl Acad Sci U S A, 1996. 93(7): p. 2856‐61.[6]. Opperman, T., et al., A model for a umuDC‐dependent prokaryotic DNA damage checkpoint. Proc Natl Acad Sci U S A, 1999. 96(16): p. 9218‐23.[7]. Lavery, P.E. and S.C. Kowalczykowski, Biochemical basis of the constitutive repressor cleavage activity of recA730 protein. A comparison to recA441 and recA803 proteins. J Biol Chem, 1992. 267(29): p. 20648‐58.[8]Simon L. Dove et al. Activation of prokaryotic transcription through arbitrary protein‐protein contacts. Nature. 1997,386: 627‐630.[9] Patricia Hidalgo et al, Recruitment of the transcriptional machinery through GAL11P: structure and interactions of the GAL4 dimerization domain, GENES & DEVELOPMENT, 2001, 15:1007–1020.[10] Helen Tzagoloff and David Pratt, The Initial Steps in Infection with Coliphage M13, VIROLOGY 1964(24): 372‐380.[11]Jens Kortmann and Franz Narberhaus, Bacterial RNA thermometers: molecular zippers and switches, Nature Reviews, 2012(10):255‐265.[12] Birgit Klinkert, et al, Thermogenetic tools to monitor temperature‐dependent gene expression in bacteria, Journal of Biotechnology, 2012(160): 55– 63.[13] Franz Narberhaus, Translational control of bacterial heat shock and virulence genes by temperature‐sensing mRNAs, RNA Biology 2010, 7(1): 84‐89.[14] Jens Kortmann, et al, Translation on demand by a simple RNA‐based Thermosensor, Nucleic Acids Research, 2010,1–14.

Acknowledgements

• Instructors:

Prof. Yongjun Lu Prof. Jianguo HeProf. Yan Zhang Prof. Xionglei He Dr. Junfeng XieProf. Junjiu Huang

• Advisors：

• Lab supporters:State Key Laboratory of Biocontrol and MOE Key Laboratory of Aquatic Product SafetyStem Cell and Functional genomics LaboratoryMolecular and Cellular Microbiology Lab

Shuai Jiang Runqing Huang Yan Shi Shaowei Yang 2013 SYSU‐China  team members

• Sponsor:

Thank you all