deterministic and stochastic analysis of simple genetic networks
DESCRIPTION
Deterministic and Stochastic Analysis of Simple Genetic Networks. Adiel Loinger. Ofer Biham Azi Lipshtat Nathalie Q. Balaban. Introduction. The E. coli transcription network Taken from: Shen-Orr et al. Nature Genetics 31:64-68(2002). Outline. The Auto-repressor The Toggle Switch - PowerPoint PPT PresentationTRANSCRIPT
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Deterministic and Stochastic Analysis of Simple Genetic Networks
Adiel Loinger
Ofer BihamAzi LipshtatNathalie Q. Balaban
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Introduction
The E. coli transcription network
Taken from: Shen-Orr et al. Nature Genetics 31:64-68(2002)
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Outline
The Auto-repressor
The Toggle Switch
The Repressilator
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The Auto-repressor
Protein A acts as a repressor to its own gene
It can bind to the promoter of its own gene and suppress the transcription
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Rate equations – Michaelis-Menten form
Rate equations – Extended Set
The Auto-repressor
0 1
0 1
[ ](1 [ ]) [ ] [ ](1 [ ]) [ ]
[ ][ ](1 [ ]) [ ]
d Ag r d A A r r
dtd r
A r rdt
[ ][ ]
1 [ ]nd A g
d Adt k A
0 1/k n = Hill Coefficient
= Repression strength
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The Auto-repressor
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The Auto-repressor
The Master Equation
,0( , ) [ ( 1, ) ( , )]rA r N A r A r
dP N N g P N N P N N
dt
[( 1) ( 1, ) ( , )]A A r A A rd N P N N N P N N
0 ,1 ,0[ ( 1) ( 1, 1) ( , )]r rN A A r N A A rN P N N N P N N
1 ,0 ,1[ ( 1, 1) ( , )]r rN A r N A rP N N P N N
Probability for the cell to contain NA free proteins and Nr bound proteins
P(NA,Nr) :
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The Genetic Switch
A mutual repression circuit. Two proteins A and B negatively
regulate each other’s synthesis
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The Genetic Switch
Exists in the lambda phage Also synthetically constructed by
collins, cantor and gardner (nature 2000)
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The Genetic Switch
Previous studies using rate equations concluded that for Hill-coefficient n=1 there is a single steady state solution and no bistability.
Conclusion - cooperative binding (Hill coefficient n>1) is required for a switch
Gardner et al., Nature, 403, 339 (2000)
Cherry and Adler, J. Theor. Biol. 203, 117 (2000)
Warren an ten Wolde, PRL 92, 128101 (2004)
Walczak et al., Biophys. J. 88, 828 (2005)
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The Switch
Stochastic analysis using master equation and Monte Carlo simulations reveals the reason:
For weak repression we get coexistence of A and B proteins
For strong repression we get three possible states:
A domination B domination Simultaneous repression (dead-lock) None of these state is really stable
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The Switch
In order that the system will become a switch, the dead-lock situation (= the peak near the origin) must be eliminated.
Cooperative binding does this – The minority protein type has hard time to recruit two proteins
But there exist other options…
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Bistable Switches
The BRD Switch - Bound Repressor Degradation
The PPI Switch –
Protein-Protein Interaction. A and B proteins form a complex that is inactive
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The Exclusive Switch
An overlap exists between the promoters of A and B and they cannot be occupied simultaneously
The rate equations still have a single steady state solution
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The Exclusive Switch
But stochastic analysis reveals that the system is truly a switch
The probability distribution is composed of two peaks
The separation between these peaks determines the quality of the switch
Lipshtat, Loinger, Balaban and Biham, Phys. Rev. Lett. 96, 188101 (2006)
Lipshtat, Loinger, Balaban and Biham, Phys. Rev. E 75, 021904 (2007)
k=1
k=50
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The Exclusive Switch
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The Repressillator
A genetic oscillator synthetically built by Elowitz and Leibler
Nature 403 (2000)
It consist of three proteins repressing each other in a cyclic way
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The Repressillator
Monte Carlo Simulations
Rate equations
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The Repressillator
Monte Carlo Simulations
(50 plasmids)
Rate equations
(50 plasmids)
Loinger and Biham, preprint (2007)
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Summary
We have studied several modules of genetic networks using deterministic and stochastic methods
Stochastic analysis is required because rate equations give results that may be qualitatively wrong
Current work is aimed at extending the results to large networks, and including post-transcriptional regulation and other effects