COMP 116: Introduction to Scientific Programming Lecture 25: Cell Arrays and Structures.
The Programming of a Cell
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The Programming of a Cell
By L Varin and N KharmaBiology and Computer Engineering DepartmentsConcordia University
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Artificial Life GroupThe Programming of a Cell
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Motivation • Cells have advantages
over silicon:• They have/can have built-in
interfaces, to sense and produce many biological substances
• They are easy to mass produce, store and distribute
• They are generally more robust than man-made systems
• They are optimizable via (real) evolution
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Motivation – precisely
• The aim is to produce a cell that implements a configurable Boolean logic function in 2 var’s• Ultimately, we would like to use intercellular signalling to compile larger circuits using many smaller ones
A mechanical AND gate
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Outline
• Motivation & Outline• Biological Background• Problem Statement• Alternative Methods• Biological Realization• Practical Significance
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Biological Background:Flow of genetic information
DNA RNA Protein
We can easily manipulate DNA
Transcription Translation
Gene expression
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Biological Background:Gene expression (promoters)
+1
-10Box
TATAA
-35Box
TTGTCARNA
Core promoter = Binding site for RNA Polymerase
In this configuration transcription is ON
RNA Pol
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+1
-10box
-35box
Biological Background:Gene expression (promoters)
operator
R
R = Repressor
In this configuration RNA Polymerase cannot bindtranscription is OFF
X
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• Construct a promoter• Insert an operator• Select a coding sequence (output)
Biological Background:Gene expression (synthetic gene)
-10box
-35box
operator
Modular structure
Output
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Biological Background:Biological regulatory network
• The lactose operon of E. coli
R
lacIrepressor R
-35 O -10
Transcription is OFF
Active repressor
X
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Biological Background:Biological regulatory network
• The lactose operon of E. coli
R
lacIrepressor
-35 O -10
Transcription is ON
Inactiverepressor
= inducer (lactose)
RNA Pol
X
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Biological Background:Artificial regulatory network
• Select an output gene• Select a promoter• Select an operator-repressor
system• Assemble the parts together
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Biological Background:Artificial regulatory network
Green Fluorescent protein
C1 repressor
promoter
Lac promoterRepressed by lac repressor
Repressed by C1 repressor
lacI
ON
OFF
- lactose
X
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Green Fluorescent protein
C1 repressor
promoter
Lac promoterRepressed by lac repressor
Repressed by C1 repressor
OFF
R+ lactose
X
X
C1
C1
Biological Background:Artificial regulatory network
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Problem Statement ++
• Synthesize a cell that can be configured to implement any one of 16 different Boolean functions in 2 variables
• Such a project will involve 4 phases:1 Designing a regulatory
network2 Constructing a
configurable cell3 Configuring the cell4 Using the cell
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Methodology 1: Using Repressilators
A BOutput
R1
R2
Anti-sense DNA
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Methodology 1: Full PictureA B’
Output
R3
R4
Anti-sense DNA
A BOutput
R1
R2
Anti-sense DNA
A’ B’Output
R5
R6
Anti-sense DNA
A’ BOutput
R7
R8
Anti-sense DNA
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Methodology 2: Using Excision
• A Boolean function in 2 variables has 16 possible truth tables
• They all involve 1-4 (3) different terms of 2 variables
A B Output
00 ?
01 ?
11 ?
10 ?
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Methodology 2: Chosen Path• Design
A regulatory network implementing the 4 terms and allowing for subsequent excision of any term
• ConstructThe regulatory network by embedding 4 gene networks
corresponding to the 4 terms in a real organism (e.g. e.coli)
• ConfigureThe cell by excising those gene networks corresponding to
the unwanted terms
• UseThe configured cell by adding the inducers (variables) it is
designed to respond to, and monitoring the output
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• 2 variables A and B• A = lactose• B = arabinose
• 1 promoter • 4 repressors
• 1 ouput gene (Green Fluorescent Protein)
• 4 terms (A B), (A B), (A B), (A B)
Biological Realization
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Biological Realization
(A B)Output (GFP)
= Lac operon operator (bound by LacI repressor)
= Arabinose operon operator (bound by AraR repressor)
In the absence of A and B
Output (GFP)LacI AraR X
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Biological Realization
(A B)Output (GFP)
In the presence of A and B ( lactose and arabinose)
Output (GFP)
LacI AraR
LacI AraR
X
XX
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Biological Realization
(A B)Output (GFP)
= Pr operator (bound by C1 repressor)
In the absence of A and in presence of B
Output (GFP)
XC1
LacI
= Arabinose operon operator (bound by AraR repressor)
AraR
X
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Biological Realization
(A B)Output (GFP)
= lactose operon operator (bound by lacI repressor)
In the presence of A and in absence of B
Output (GFP)
XCRO
= Prm operator (bound by CRO repressor)
LacI
X
AraR
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Biological Realization
(A B)Output (GFP)
= Pr operator (bound by C1 repressor)
In the absence of A and in absence of B
Output (GFP)
XCRO
= Prm operator (bound by CRO repressor)
AraR
C1
LacI X
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Biological Realization
(A B)
(A B)
(A B)
(A B)
Output (GFP)
Output (GFP)
Output (GFP)
Output (GFP)
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Practical Significance
Limited ConfigurableDecision Logic
Inputs tied to a particular application: lactose, arabinose etc.
Outputs tied to a particular application: GFP etc.
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Practical Significance
Extended Decision Logic
Input Interface
Output Interface
Application-specific inputs
Application-specific outputs
Standardized Signals
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Summary
• A specific Boolean logic function in 5 variables has been recently realized in living cells, but never a configurable bio-logic device theoretic value
• We believe we have found a simple means of realizing a configurable 2-input Boolean function in an e.coli cell simple methodology
• Both the logic functionality and the practical value of the work can be considerably enhanced with the use of intercellular signaling broader vision
• First experiments (for the Method 2) will start in January 2008 and we’ll update you!