Revision as of 18:16, 25 October 2007

Introduction Section Team Members Section Acknowledgments Section Site map Section

Introduction Section Model Overview Section Detailed Model Section Final Model Section Modeling Basics Page Mathematical Model Section FSM View Page Flip-Flop View Page Parameters Page

Introduction Section Test Cases Section Sensitivity Analysis Section

Introduction Section The Complete System Section System Phases Section System Parts Page Lab Notes Page

The ETH Zurich 07 Team Team Description Brainstorming Page

Parameters for the educatETH E.coli system

In order to provide as realistic simulation results as possible and to find good estimates for the simulation parameters, we performed an intensive literature review. However, not all parameters could be found in the literature. Furthermore, one has to take into account that biological parameters often cannot be estimated with high precision.

Model Parameters

General parameters

Parameter	Value	Description	Comments
c₁^max	0.01 [mM/h]	max. transcription rate of constitutive promoter (per gene)	promoter no. J23105; Estimate
c₂^max	0.01 [mM/h]	max. transcription rate of LuxR-activated promoter (per gene)	Estimate
l^hi	25	high-copy plasmid number	Estimate
l^lo	5	low-copy plasmid number	Estimate
a	1%	basic production levels	Estimate

Degradation constants

Parameter	Value	Description	Comments
d_LacI	2.31e-3 [1/s]	degradation of LacI	Ref. [10]
d_TetR	1e-5 [1/s] 2.31e-3 [1/s]	degradation of TetR	Ref. [9] Ref. [10]
d_LuxR	1e-3 - 1e-4 [1/s]	degradation of LuxR	Ref: [6]
d_CI	7e-4 [1/s]	degradation of CI	Ref. [7]
d_P22CII		degradation of P22CII
d_YFP	6.3e-3 [1/min]	degradation of YFP	suppl. mat. to Ref. [8] corresponding to a half life of 110min
d_GFP	6.3e-3 [1/min]	degradation of GFP	in analogy to YFP
d_RFP	6.3e-3 [1/min]	degradation of RFP	in analogy to YFP
d_CFP	6.3e-3 [1/min]	degradation of CFP	in analogy to YFP

Dissociation constants

Parameter	Value	Description	Comments
K_LacI	0.1 - 1 [pM] 800 [nM]	LacI repressor dissociation constant	Ref. [2] Ref. [12]
K_IPTG	1.3 [µM]	IPTG-LacI repressor dissociation constant	Ref. [2]
K_TetR	179 [pM]	TetR repressor dissociation constant	Ref. [1]
K_ATC	893 [pM]	ATC-TetR repressor dissociation constant	Ref. [1]
K_LuxR	55 - 520 [nM]	LuxR activator dissociation constant	Ref: [6]
K_AHL	0.09 - 1 [µM]	AHL-LuxR activator dissociation constant	Ref: [6]
K_CI	8 [pM] 50 [nM]	CI repressor dissociation constant	Ref. [12] starting with values of Ref. [6] and using Ref. [3]
K_P22CII	0.577 [µM]	P22CII repressor dissociation constant	Ref. [11]

Hill cooperativity

Parameter	Value	Description	Comments
n_LacI	1 2	LacI repressor Hill cooperativity	Ref. [5] Ref. [12]
n_IPTG	2	IPTG-LacI repressor Hill cooperativity	Ref. [5]
n_TetR	3	TetR repressor Hill cooperativity	Ref. [3]
n_ATC	2 (1.5-2.5)	ATC-TetR repressor Hill cooperativity	Ref. [3]
n_LuxR	2	LuxR activator Hill cooperativity	Ref: [6]
n_AHL	1	AHL-LuxR activator Hill cooperativity	Ref. [3]
n_CI	2	CI repressor Hill cooperativity	Ref. [12]
n_P22CII	4	P22CII repressor Hill cooperativity	Ref. [11]. Note that they use a protein CII and we have P22CII. Does that match?

References

[http://www.pnas.org/cgi/content/abstract/104/8/2643 [1] Weber W et al.] "A synthetic time-delay circuit in mammalian cells and mice", P Natl Acad Sci USA 104(8):2643-2648, 2007
[http://www.pnas.org/cgi/content/full/100/13/7702?ck=nck [2] Setty Y et al.] "Detailed map of a cis-regulatory input function", P Natl Acad Sci USA 100(13):7702-7707, 2003
[http://ieeexplore.ieee.org/iel5/9711/30654/01416417.pdf [3] Braun D et al.] "Parameter Estimation for Two Synthetic Gene Networks: A Case Study", ICASSP 5:769-772, 2005
[http://www.nature.com/nature/journal/v435/n7038/suppinfo/nature03508.html [4] Fung E et al.] "A synthetic gene--metabolic oscillator", Nature 435:118-122, 2005 (supplementary material)
[http://dx.doi.org/10.1016/j.jbiotec.2005.08.030 [5] Iadevaia S and Mantzais NV] "Genetic network driven control of PHBV copolymer composition", J Biotechnol 122(1):99-121, 2006
[http://dx.doi.org/10.1016/j.biosystems.2005.04.006 [6] Goryachev AB et al.] "Systems analysis of a quorum sensing network: Design constraints imposed by the functional requirements, network topology and kinetic constants", Biosystems 83(2-3):178-187, 2004
[http://www.genetics.org/cgi/content/abstract/149/4/1633 [7] Arkin A et al.] "Stochastic kinetic analysis of developmental pathway bifurcation in phage λ-Infected Escherichia coli cells", Genetics 149: 1633-1648, 1998
[http://download.cell.com/supplementarydata/cell/107/6/739/DC1/index.htm [8] Colman-Lerner A et al.] "Yeast Cbk1 and Mob2 Activate Daughter-Specific Genetic Programs to Induce Asymmetric Cell Fates", Cell 107(6): 739-750, 2001 (supplementary material)
[http://www.nature.com/nature/journal/v405/n6786/abs/405590a0.html [9] Becskei A and Serrano L] "Engineering stability in gene networks by autoregulation", Nature 405: 590-593, 2000
[http://www.biophysj.org/cgi/content/full/89/6/3873?maxtoshow=&HITS=10&hits=10&RESULTFORMAT=&searchid=1&FIRSTINDEX=0&volume=89&firstpage=3873&resourcetype=HWCIT [10] Tuttle et al.] "Model-Driven Designs of an Oscillating Gene Network", Biophys J 89(6):3873-3883, 2005
[http://www.pnas.org/cgi/reprint/99/2/679 [11] McMillen LM et al.] "Synchronizing genetic relaxation oscillators by intercell signaling", P Natl Acad Sci USA 99(2):679-684, 2002
[http://www.nature.com/nature/journal/v434/n7037/full/nature03461.html [12] Basu S et al.] "A synthetic multicellular system for programmed pattern formation", Nature 434:1130-1134, 2005

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-| Ref. [11]. Note that they use a protein CII and we have P22CII. Does that match?
+| Ref. [11]
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