integrated evolution machine
TRANSCRIPT
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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
mz10姚润文9
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Directed Evolution
Diversification
Selection
Amplification
A lot of limitationsTime-consuming
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Integrated Evolution Machine
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Overview
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Overview Overview
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Overview What is the IgEM?
IgEM
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Overview
Defective Phage
Without geneVIII
E. Coli
Can express geneVIIIUnder special condition
What is the IgEM?
Mutagenesis Module Screening Module Synchronization Module
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Overview Beginning— Synchronizing the penetration
E. coli
0 ℃30 ℃
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Overview
E. coli
0 ℃30 ℃
E. coli
Mutation
Step 2 Diversification—Generate the library
• Inhibit proofreading activity • Enhance the SOS response
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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 ℃
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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
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Overview
0 ℃30 ℃
E. coli
mRNA of geneVIII Rise to 37℃
37 ℃0 ℃
Step 4 Amplification—Synchronize the phage release
RNA Thermometer
Next Cycle
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Diversification
Selection
Amplification
StartRestart
Design & Result
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Design & Result Design & Result
Diversification
Selection
Amplification
StartRestart
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Design & Result Library generated by Mutagenesis
MutagenesisPlasmid
Diversification
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Design & Result Mutagenesis plasmid
Diversification
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Design & Result 5 - fold dnaQ926 is sufficient
Aver
age
Mut
atio
n R
ate
(sub
stitu
tions
/bp)
c(dnaQ926)/c(dnaQ)
Diversification
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Design & Result
Blank A B
All genes are expressed
RFP RFP
Diversification
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Design & Result
?selection
Bacterial Two-Hybrid System
Diversification Selection
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Design & Result Bacterial Two-Hybrid System
Genotype Phenotype
Diversification Selection
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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
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Design & Result The Bacterial Two-Hybrid System ( B2H)Protein interaction ↔ Gene transcription
Three plasmid(pBT, pTRG, pRPT) co-transformation
Diversification Selection
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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
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Design & Result Weak or Strong?
Different Interaction strength
Different Reporter gene expression
Diversification Selection
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Design & Result
Negative Original Low Medium High
Weak or Strong?
Point mutation→Low, Medium, High strength of interaction
Between LGF and GAL11P
Diversification Selection
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Design & Result Weak or Strong?
Interaction strength
The B2H system can tell the difference
Diversification Selection
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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
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Design & Result Model simulation of the B2H in IgEM
?
Diversification Selection
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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
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Design & Result Binding energy is positively related to progeny number
Diversification Selection
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Design & Result Selectable Binding Energy Interval
Diversification Selection
7.7 10.7
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Design & Result Selectable Binding Energy Interval
Diversification Selection
Selectable Interval
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Design & Result ‐‐Tune [ ] expression according to stages of evolution
Diversification Selection
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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
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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
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3939Diversification Selection Amplification
Design & Result RNA thermometer(RNAT)
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The Rose element(BBa_K115001)
The PrfA element(BBa_K115003)
The FourU Element(BBa_K115002)
control
4040Diversification Selection Amplification
Design & Result Testing RNAT
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FourU worked well
4141Diversification Selection Amplification
Design & Result Testing the FourU
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3h
FourU respond rapidly to temperature change
Design & Result Shift Experiment
4242Diversification Selection Amplification
千凝微1姚润文7
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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
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4343Diversification Selection Amplification
Design & Result Integration with B2H system
FourUworked well with B2H system
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Diversification Selection Amplification
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How evolution takes place in each cycle of experiments?
Modeling
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Modeling ModelingSequence Evolution
Method: Direct simulation
Processes:• DNA replication• Point mutation• Translation• Score • High pressure selection
Original Sequence
↓evolvedTarget Sequence
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Modeling Sequence Evolution
Target InitialEvolving
Score
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Modeling Population Evolution
Assumption: Similarity is positively related to progeny number
Not change
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Modeling Population Evolution
Accumulate diversityForm wide similarity distribution
Evolution
Initial Plateau
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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……
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Modeling
Increase [DNAQ] in the beginning for fast evolutionDecrease [DNAQ] later for high final similarity
Tune [DNAQ] for fast evolution and high final similarity
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More
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More More
AchievementFuture WorkApplicationReference
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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
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Applications
Valuable Proteins
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Traditional method
Human Infective
Quickly Mutated
Fiercely Break UpPathogen
Time-consumingLimited
Less effective
Applications
single-chain antibody fragment
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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
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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/
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Interlab√ Measure GFP√ Extra credits:
Measure cell-to-cell variation for the three required devices
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iGEM China Community iGEM Coference Newsletter
Human Practice
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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.
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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:
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Thank you all