brown igem international genetically engineered machines competition july update 1/86
Post on 01-Apr-2015
221 Views
Preview:
TRANSCRIPT
Brown iGEMinternational genetically engineered machines competition
July Update
1/86
What is iGEM?
• Biology
• Engineering
• Standardization
2/86
Making it easier to engineer biology
3/86
DNA is a language:
AATGAATATCCAGATCG
4/86
Biological Part:
PromoterPromoter
5/86
---
Different Parts connect together
--- ---GeneGene ---TerminatTerminatoror
This is a device
PromoterPromoter
6/86
---
Different Parts connect together
ConstitutiveConstitutivePromoterPromoter--- ------TerminatTerminat
oror
This is a device
GFPGFP
7/86
Biological parts are building blocks made of
genetic material
8/86
Science
• Systematic engineering
• Standardizing biology
• Apply biological technology
9/86
Brown iGEM
• Lead-detector
• Tri-stable Switch
Two projects being built with biological parts
10/86
Lead Detector
11/86
Version 1.0: Lead Detector
Fluorescent ProteinFluorescent Protein
Lead Promoter
Problem: Only one cell will light up!12/86
Version 1.1: Amplify the Signal
Fluorescent Fluorescent ProteinProtein
Lead Promoter
Amplifier
Problem: Promoter Leakiness = False Positives!13/86
Version 1.2: Filter False Positives
Three Possible Solutions:
1.Modify the Promoter (weaker baseline)
2.Tight intermediate promoter (T7)
3. Make amplifier less sensitive (increase threshold)
14/86
Final Version: The System
FluorescenFluorescent Proteint Protein
Lead Promoter
AmplifierLeakiness
Filter
15/86
So how will this system work in the cell?
16/86
TetR (always on)
PbrR LuxR
Lead Promoter
LuxI
pLuxLuxI GFP
NO LEAD
Transcription factors are constitutively made by the first promoter.
These proteins are poised to activate the
Lead Detector promoter and Message Receiver promoter upon addition
of lead.
17/86
LuxR
Lead Promoter
LuxI
pLuxLuxI GFP
+
Fluorescent Protein Output
Lead turns on Detector promoter
TetR (always on)
PbrR
18/86
Experimental Design
iGEM’s more than just design. This will take some lab work.
19/86
Experimental DesignThree Independent System Components
AHL unifies three components with a common language to
match Inputs with Outputs.
Lead Receptor
and Promoter
Filter Amplifier
20/86
Experimental DesignThree Independent System Components
AHL unifies three components with a common language to
match Inputs with Outputs.
Lead Receptor
and Promoter
Filter Amplifier
Develop AHL Assay for testing all components.
STEP 1
STEP 2a and 2b
STEP 321/86
What is AHL?
Cell Signaling Molecule
Common input and output of different devices within our system
Why and How do we measure it?
Acyl Homoserine Lactone
22/86
GFP output over time at different AHL concentrations
0.00E+00
2.00E+04
4.00E+04
6.00E+04
8.00E+04
1.00E+05
1.20E+05
1.40E+05
1.60E+05
0 0 10^-13 10^-13 10^-11 10^-11 10^-9 10^-9 10^-7 10^-7 10^-5 10^-5 10^-4
Molar Concentration AHL added
GFP output
2h45m
AHL BioAssay
23/86
More AHL --> More GFP
Need more than 10 nM AHL to overcome threshold
GFP output over time at different AHL concentrations
0.00E+00
2.00E+04
4.00E+04
6.00E+04
8.00E+04
1.00E+05
1.20E+05
1.40E+05
1.60E+05
0 0 10^-13 10^-13 10^-11 10^-11 10^-9 10^-9 10^-7 10^-7 10^-5 10^-5 10^-4
Molar Concentration AHL added
GFP output
2h45m
5h05m
29hours
AHL BioAssay
24/86
Experimental Design
Lead Receptor
and Promoter
Filter
Amplifier
Develop AHL Assay for testing all components.
STEP 1
STEP 2a and 2b
STEP 3
25/86
Amplifier
• Chemical Transformation• Electroporation• Ordering from MIT• Build it ourselves• Measure AHL output
26/86
Experimental Design
Lead Receptor
and Promoter
Filter
Amplifier
Develop AHL Assay for testing all components.
STEP 1
STEP 2a and 2b
STEP 3
27/86
Lead Receptor and Promoter
Ralstonia Metallidurans CH34
Survives in metallic environments.
http://genome.jgi-psf.org/finished_microbes/ralme/ralme.home.html
28/86
Lead Receptor and PromoterWe chose to examine:
1. Lead Receptor Protein PbrR691
2. Corresponding Lead Promoter
PbrR691
Lead Promoter
29/86
Lead Receptor and Promoter• Why?
–Incredibly Selective!–Novel–Successfully cloned into E Coli.
30/86
Chen, Peng, Bill Greenberg, Safiyah Taghavi, Christine Romano, Daniel van der Lelie, and Chuan He. “An Exceptionally Selective Lead(II)-Regulatory Protein from Ralstonia Metallidurans: Development of a Fluorescent Lead(II) Probe.” Angew. Chem. Int. Ed. 2005, 44, 2-6.
Original Design
pTet (Constitutive On)
PbrR691
Lead Promoter
Amplifier
PbrR691
31/86
Lead Receptor PbrR691 and Lead Promoter must be BioBricked!
PbrR691GACTGATCGATAGATCGAGATCGATCGATAGAGGCTCTCGAGATCGCGAGATATCG
32/86
BioBrick Assembly
33/86
How do we get PbrR691 and Lead Promoter?
PCR
2 Major Obstacles:
- Biobricking a promoter adds extra bases from the restriction sites to the ends, which may reduce promoter efficiency.
- Length of promoter – very small34/86
Experimental Plan
• Purpose: Match switch components
• PCR 12 variations of promoter and gene
• Ligate to RBS-LuxI-GFP-Term
• Test with AHL against AHL bioassay curve
• Result: promoter output = amplifier input
35/86
Experimental Design
Lead Receptor
and Promoter
Filter
Amplifier
Develop AHL Assay for testing all components.
STEP 1
STEP 2a and 2b
STEP 3
36/86
Problem: Leakiness
• What if the baseline is too high?
• Possible solution: T7 promoter control
• Advantage: strong repression (not leaky) unless T7 RNA polymerase is present
37/86
T7 Promoter LuxI
T7 polymerase
will transcribe LuxIpPbr
T7 polymerase
Amplifier
T7 Filter Schematic
38/86
Possible Issues
• Poor sensitivity
• Poor pPbr induction
• Solution: Need to test pPbr promoter as well as whole T7 system
• What are our choices for T7 systems?
39/86
T7 registry parts
40/86
Experimental Design
Lead Receptor
and Promoter
Filter
Amplifier
Develop AHL Assay for testing all components.
STEP 1
STEP 2a and 2b
STEP 3
41/86
Tri-Stable Switch
42/86
Tristable Switch Team
1. Introduction2. System
Design3. Modeling4. System Tests5. Labwork 43/86
Introduction• Stable Switch: A system with 2 or more distinct and inducible states.
AB
Introduction > System Design > Modeling > System Tests > Labwork44/86
Bistable Switch
• This is the simplest switch.
• It only involves two separate states.
Introduction > System Design > Modeling > System Tests > Labwork45/86
Uses for a Bistable Switch
•Drug Delivery•Simple Logic
Introduction > System Design > Modeling > System Tests > Labwork46/86
Bistable Switch• In 2000, three scientists at Boston University managed to create a synthetic Bistable Switch.
• They showed that you could create the Bistable Switch using relatively simple, standard parts.
Introduction > System Design > Modeling > System Tests > Labwork47/86
Bistable Switch Design• The Bistable Switch simply consists of two pathways, each of which represses the other.
pLac TetR
pTet LacI GFP
YFP
Pathway A
Pathway B
Introduction > System Design > Modeling > System Tests > Labwork48/86
Importance of Bistable Switch
• The Bistable Switch is one of the seminal achievements of Synthetic Biology.
• It was one of the first projects that showed that you could combine standard genetic parts together to form working circuits.
Introduction > System Design > Modeling > System Tests > Labwork49/86
Tristable Switch
• A switch with three distinct inducible states.
ABC
Introduction > System Design > Modeling > System Tests > Labwork50/86
Tristable Switch Design
• The design consists of three pathways, each of which represses the other two.
• When one of the pathways is induced it stops the other two from being expressed, and the system achieves stability.
Introduction > System Design > Modeling > System Tests > Labwork51/86
pTet LacI AraC
pLac AraC TetR
pAra TetR LacI
Pathway A
Pathway B
Pathway C
Tristable Switch Design
Introduction > System Design > Modeling > System Tests > Labwork52/86
Tristable Switch Tuning
• While the design is relatively simple, the exact components we put into it have to be carefully chosen to balance the system.
pTet LacI AraC
Introduction > System Design > Modeling > System Tests > Labwork53/86
Why do we model?
Modeling
Introduction > System Design > Modeling > System Tests > Labwork
•A quick and inexpensive way to quantitatively predict behavior
•A foundation to start testing, e.g. what variables do we need to test to understand our system
54/86
Why does our system lend itself to modeling?
Modeling
•Sensitive system
•Future adaptations
Introduction > System Design > Modeling > System Tests > Labwork55/86
Variables in the Model
1.Rate of repressor production
2.Strength of repression
Introduction > System Design > Modeling > System Tests > Labwork56/86
Variables in the Model
• Rate of repressor production depends on:
1. Promoter strength (transcription)
2. RibosomeBindingSite strength (translation)RBS
•In model, α = Promoter * RBS = total repressor production rate
Introduction > System Design > Modeling > System Tests > Labwork57/86
Variables in the Model
• Repressor strength depends on:1. β = the cooperativity of repressors
to promoters
2. [repressor] = the concentration of repressor
Total strength of repressor = [repressor]^
Introduction > System Design > Modeling > System Tests > Labwork58/86
Variables in the ModelGraph of [repressor]^; where = .5, 1, 1.5, 2
*β = cooperativity of repression
Introduction > System Design > Modeling > System Tests > Labwork59/86
EquationsFor the Bi-Stable Switch…
x and y = [repressor concentration] α = repressor production rate β = cooperativity of repression
€
dx
dt=
α 21+ y β 2
− x
€
dy
dt=
α 11+ x β1
− y
Introduction > System Design > Modeling > System Tests > Labwork60/86
Equations
€
dx
dt=
α 21+ y β 2
− x
€
dy
dt=
α 11+ x β1
− y
The equations are extended to a tri stable system.
€
dy
dt=
α 11+ x β1
+α 3
1+ zβ 3− y
€
dz
dt=
α 11+ x β1
+α 2
1+ y β 2− z
€
dx
dt=
α 21+ y β 2
+α 3
1+ zβ 3− x
Vs.
Bistable Tristable
Introduction > System Design > Modeling > System Tests > Labwork61/86
Equations
€
dy
dt=
α 11+ x β1
+α 3
1+ zβ 3− y
The number of repressors correlates to the number
of terms
Introduction > System Design > Modeling > System Tests > Labwork62/86
The Bi Stable Region
β = cooperativity α = repressor production rate
Introduction > System Design > Modeling > System Tests > Labwork63/86
The Tri Stable Region
Introduction > System Design > Modeling > System Tests > Labwork64/86
What the Model Predicts
• β > 1 or larger to maximize the stable region
• α values are similar for all promoters
• α values are within the stable region
A stable system occurs when:
β = cooperativity α = repressor production rate
Introduction > System Design > Modeling > System Tests > Labwork65/86
So what can we do with the modelling?
Introduction > System Design > Modeling > System Tests > Labwork66/86
1. Systematic Approach to Construction
• Design tests to assign values to variables in model– Promoter/RBS Strength, Relative Repressor Cooperativity, etc
• Use these values in the model to find the right combination of parts.
Introduction > System Design > Modeling > System Tests > Labwork67/86
Alternative: test, hope it works, if not,
test again.
Systematic Design is the philosophy of Synthetic Biology
Introduction > System Design > Modeling > System Tests > Labwork68/86
2. Characterization of System
•It is a step towards standardization - giving others all the details needed to use the part.
Introduction > System Design > Modeling > System Tests > Labwork69/86
Testing Constructs
1. () Promoter/RBS Strength
2. () Repressor Strength3. Inducer Strength
Introduction > System Design > Modeling > System Tests > Labwork70/86
Promoter/RBS Strength
Promoter RBS GFP
variable
**Because there is no way to measure strength or concentration directly, we measure with florescent proteins.
Introduction > System Design > Modeling > System Tests > Labwork71/86
Repressor Strength
Inducible Promoter RBS Repressor GFP
Repressible Promoter RBS YFP
Variable
β = cooperativity α = repressor production rate
Introduction > System Design > Modeling > System Tests > Labwork72/86
Inducer Strength
Promoter RBS Repressor
Promoter RBS GFP
X
Variable [Inducer]
Introduction > System Design > Modeling > System Tests > Labwork73/86
Testing Restraints
Florescent proteins not perfect read out:
1. Indirect measurement of genea. Protein folding time
b. Degradation Rate
2. Rate of Production: Repressor vs GFP
3. High toll on cell machinery and resources
Introduction > System Design > Modeling > System Tests > Labwork74/86
What we’ve been up to…
Introduction > System Design > Modeling > System Tests > Labwork75/86
KABOBS
Introduction > System Design > Modeling > System Tests > Labwork76/86
Mastering Cloning
• More obstacles than we thought• Transformations, DNA concentration too low, gel readibility, restriction digest buffer compatibility, etc.
• Most kinks worked out of the way• First ligations completed
Introduction > System Design > Modeling > System Tests > Labwork77/86
The Project Itself
• Looking through Modeling• Designed Tests• Created DNA stocks of all parts needed
• Creating a good record keeping infrastructure
Introduction > System Design > Modeling > System Tests > Labwork78/86
QuickTime™ and aTIFF (Uncompressed) decompressor
are needed to see this picture.
Introduction > System Design > Modeling > System Tests > Labwork79/86
Goals
Testing Ligations
Introduction > System Design > Modeling > System Tests > Labwork80/86
QuickTime™ and aTIFF (Uncompressed) decompressor
are needed to see this picture.
Introduction > System Design > Modeling > System Tests > Labwork81/86
References
• Gardner TS, Cantor CR, Collins JJ. “Construction of a genetic toggle Switch in Escherichia coli.” Nature 2000 Jan, 20.
Introduction > System Design > Modeling > System Tests > Labwork82/86
2007 Brown iGEM Team
• 7 undergraduates
• 7 grad student advisors
• 2 Faculty advisors
• 9 faculty sponsors
83/86
Sponsors
84/86
Office of the Dean of the CollegeOffice of the President
The Atlantic PhilanthropiesThe Center for Computational and Molecular Biology
Department of PhysicsEngineering Department
Department of Molecular Biology, Cell Biology, and Biochemistry
Department of Molecular Pharmacology, Physiology, and Biotechnology
The Multi Disciplinary LabPfizerLabnet
Nanodrop
Special Thanks To:
85/86
Thank you for listening!
Questions?86/86
top related