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Brown iGEM international genetically engineered machines competition July Update 1/86
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Feb 06, 2016

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Brown iGEM. international 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:. Promoter. 5/86. - PowerPoint PPT Presentation
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Page 1: Brown iGEM

Brown iGEMinternational genetically engineered machines competition

July Update

1/86

Page 2: Brown iGEM

What is iGEM?

• Biology

• Engineering

• Standardization

2/86

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Making it easier to engineer biology

3/86

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DNA is a language:

AATGAATATCCAGATCG

4/86

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Biological Part:

PromoterPromoter

5/86

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---

Different Parts connect together

--- ---GeneGene ---TerminatTerminatoror

This is a device

PromoterPromoter

6/86

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---

Different Parts connect together

ConstitutiveConstitutivePromoterPromoter--- ------TerminatTerminat

oror

This is a device

GFPGFP

7/86

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Biological parts are building blocks made of

genetic material

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Science

• Systematic engineering

• Standardizing biology

• Apply biological technology

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Brown iGEM

• Lead-detector

• Tri-stable Switch

Two projects being built with biological parts

10/86

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Lead Detector

11/86

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Version 1.0: Lead Detector

Fluorescent ProteinFluorescent Protein

Lead Promoter

Problem: Only one cell will light up!12/86

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Version 1.1: Amplify the Signal

Fluorescent Fluorescent ProteinProtein

Lead Promoter

Amplifier

Problem: Promoter Leakiness = False Positives!13/86

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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

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Final Version: The System

FluorescenFluorescent Proteint Protein

Lead Promoter

AmplifierLeakiness

Filter

15/86

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So how will this system work in the cell?

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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.

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LuxR

Lead Promoter

LuxI

pLuxLuxI GFP

+

Fluorescent Protein Output

Lead turns on Detector promoter

TetR (always on)

PbrR

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Experimental Design

iGEM’s more than just design. This will take some lab work.

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Experimental DesignThree Independent System Components

AHL unifies three components with a common language to

match Inputs with Outputs.

Lead Receptor

and Promoter

Filter Amplifier

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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

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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

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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

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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

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Experimental Design

Lead Receptor

and Promoter

Filter

Amplifier

Develop AHL Assay for testing all components.

STEP 1

STEP 2a and 2b

STEP 3

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Amplifier

• Chemical Transformation• Electroporation• Ordering from MIT• Build it ourselves• Measure AHL output

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Experimental Design

Lead Receptor

and Promoter

Filter

Amplifier

Develop AHL Assay for testing all components.

STEP 1

STEP 2a and 2b

STEP 3

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Lead Receptor and Promoter

Ralstonia Metallidurans CH34

Survives in metallic environments.

http://genome.jgi-psf.org/finished_microbes/ralme/ralme.home.html

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Lead Receptor and PromoterWe chose to examine:

1. Lead Receptor Protein PbrR691

2. Corresponding Lead Promoter

PbrR691

Lead Promoter

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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.

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Original Design

pTet (Constitutive On)

PbrR691

Lead Promoter

Amplifier

PbrR691

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Lead Receptor PbrR691 and Lead Promoter must be BioBricked!

PbrR691GACTGATCGATAGATCGAGATCGATCGATAGAGGCTCTCGAGATCGCGAGATATCG

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BioBrick Assembly

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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

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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

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Experimental Design

Lead Receptor

and Promoter

Filter

Amplifier

Develop AHL Assay for testing all components.

STEP 1

STEP 2a and 2b

STEP 3

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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

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T7 Promoter LuxI

T7 polymerase

will transcribe LuxIpPbr

T7 polymerase

Amplifier

T7 Filter Schematic

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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?

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T7 registry parts

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Experimental Design

Lead Receptor

and Promoter

Filter

Amplifier

Develop AHL Assay for testing all components.

STEP 1

STEP 2a and 2b

STEP 3

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Tri-Stable Switch

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Tristable Switch Team

1. Introduction2. System

Design3. Modeling4. System Tests5. Labwork 43/86

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Introduction• Stable Switch: A system with 2 or more distinct and inducible states.

AB

Introduction > System Design > Modeling > System Tests > Labwork44/86

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Bistable Switch

• This is the simplest switch.

• It only involves two separate states.

Introduction > System Design > Modeling > System Tests > Labwork45/86

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Uses for a Bistable Switch

•Drug Delivery•Simple Logic

Introduction > System Design > Modeling > System Tests > Labwork46/86

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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

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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

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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

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Tristable Switch

• A switch with three distinct inducible states.

ABC

Introduction > System Design > Modeling > System Tests > Labwork50/86

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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

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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

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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

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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

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Why does our system lend itself to modeling?

Modeling

•Sensitive system

•Future adaptations

Introduction > System Design > Modeling > System Tests > Labwork55/86

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Variables in the Model

1.Rate of repressor production

2.Strength of repression

Introduction > System Design > Modeling > System Tests > Labwork56/86

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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

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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

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Variables in the ModelGraph of [repressor]^; where = .5, 1, 1.5, 2

*β = cooperativity of repression

Introduction > System Design > Modeling > System Tests > Labwork59/86

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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

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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

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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

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The Bi Stable Region

β = cooperativity α = repressor production rate

Introduction > System Design > Modeling > System Tests > Labwork63/86

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The Tri Stable Region

Introduction > System Design > Modeling > System Tests > Labwork64/86

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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

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So what can we do with the modelling?

Introduction > System Design > Modeling > System Tests > Labwork66/86

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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

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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

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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

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Testing Constructs

1. () Promoter/RBS Strength

2. () Repressor Strength3. Inducer Strength

Introduction > System Design > Modeling > System Tests > Labwork70/86

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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

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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

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Inducer Strength

Promoter RBS Repressor

Promoter RBS GFP

X

Variable [Inducer]

Introduction > System Design > Modeling > System Tests > Labwork73/86

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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

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What we’ve been up to…

Introduction > System Design > Modeling > System Tests > Labwork75/86

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KABOBS

Introduction > System Design > Modeling > System Tests > Labwork76/86

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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

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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

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QuickTime™ and aTIFF (Uncompressed) decompressor

are needed to see this picture.

Introduction > System Design > Modeling > System Tests > Labwork79/86

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Goals

Testing Ligations

Introduction > System Design > Modeling > System Tests > Labwork80/86

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QuickTime™ and aTIFF (Uncompressed) decompressor

are needed to see this picture.

Introduction > System Design > Modeling > System Tests > Labwork81/86

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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

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2007 Brown iGEM Team

• 7 undergraduates

• 7 grad student advisors

• 2 Faculty advisors

• 9 faculty sponsors

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Sponsors

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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:

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Thank you for listening!

Questions?86/86