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BIOMD0000000315 - Montagne2011_Oligator_optimised

 

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Reference Publication
Publication ID: 21283142
Montagne K, Plasson R, Sakai Y, Fujii T, Rondelez Y.
Programming an in vitro DNA oscillator using a molecular networking strategy.
Mol. Syst. Biol. 2011 Feb; 7: 466
LIMMS/CNRS-IIS, Institute of Industrial Science, University of Tokyo, Meguro-ku, Tokyo, Japan.  [more]
Model
Original Model: BIOMD0000000315.origin
Submitter: Raphaël Plasson
Submission ID: MODEL1010260000
Submission Date: 26 Oct 2010 06:34:14 UTC
Last Modification Date: 18 May 2017 11:22:36 UTC
Creation Date: 17 Feb 2011 01:23:22 UTC
Encoders:  Lukas Endler
set #1
bqbiol:hasTaxon Taxonomy cellular organisms
set #2
bqbiol:isVersionOf Gene Ontology DNA metabolic process
Notes

This is the model of the in vitro DNA oscillator called oligator with the optmized set of parameters described in the article:
Programming an in vitro DNA oscillator using a molecular networking strategy.
Montagne K, Plasson R, Sakai Y, Fujii T, Rondelez Y. Mol Syst Biol. 2011 Feb 1;7:466. PubmedID:21283142, Doi:10.1038/msb.2010.120

Abstract:
Living organisms perform and control complex behaviours by using webs of chemical reactions organized in precise networks. This powerful system concept, which is at the very core of biology, has recently become a new foundation for bioengineering. Remarkably, however, it is still extremely difficult to rationally create such network architectures in artificial, non-living and well-controlled settings. We introduce here a method for such a purpose, on the basis of standard DNA biochemistry. This approach is demonstrated by assembling de novo an efficient chemical oscillator: we encode the wiring of the corresponding network in the sequence of small DNA templates and obtain the predicted dynamics. Our results show that the rational cascading of standard elements opens the possibility to implement complex behaviours in vitro. Because of the simple and well-controlled environment, the corresponding chemical network is easily amenable to quantitative mathematical analysis. These synthetic systems may thus accelerate our understanding of the underlying principles of biological dynamic modules.

The model reproduces the time courses in fig 2B. The parameter identifiers of the reaction constants are not the same as in the supplemental material, but are just called kXd and kXr for the forward and backwards constant of reaction X respectively.

This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team.
For more information see the terms of use.
To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.

Model
Publication ID: 21283142 Submission Date: 26 Oct 2010 06:34:14 UTC Last Modification Date: 18 May 2017 11:22:36 UTC Creation Date: 17 Feb 2011 01:23:22 UTC
Mathematical expressions
Reactions
ass_aa_l m_ass_aa_lr m_ass_aa_r m_ass_aa_rl
pol_aa dis_aa nick_aa ass_ab_l
m_ass_ab_lr m_ass_ab_r m_ass_ab_rl pol_ab
dis_ab nick_ab ass_bc_l m_ass_bc_lr
ass_bc_r ass_bc_rl pol_bc dis_bc
nick_bc inh_ac inh_displ_ac m_inh_displ_ca
exo_a exo_b exo_c  
Rules
Assignment Rule (variable: Bp_concentration) Assignment Rule (variable: fluorescence) Assignment Rule (variable: Inh_total) Assignment Rule (variable: beta_total)
Assignment Rule (variable: alpha_total)      
Physical entities
Compartments Species
sample T1 alpha alpha_T1
alpha_T1_alpha T1_alpha alpha_alpha_T1
T2 alpha_T2 alpha_T2_beta
beta T2_beta alpha_beta_T2
T3 beta_T3 beta_T3_Inh
Inh T3_Inh beta_Inh_T3
Inh_T1 empty  
Global parameters
k0d k0r k1d k1r
k2d k2r k3d k3r
k4d k5d k6d k7d
k7r k8d k8r k9d
k9r k10d k10r k11d
k12d k13d k14d k14r
k15d k15r k16d k16r
k17d k17r k18d k19d
k20d k21d k21r k22d
k22r k23d k23r k24d
k25d k26d Bp_concentration fluorescence
Inh_total beta_total alpha_total  
Reactions (27)
 
 ass_aa_l [T1] + [alpha] ↔ [alpha_T1];  
 
 m_ass_aa_lr [alpha_T1_alpha] ↔ [alpha] + [alpha_T1];  
 
 m_ass_aa_r [T1_alpha] ↔ [T1] + [alpha];  
 
 m_ass_aa_rl [alpha_T1_alpha] ↔ [alpha] + [T1_alpha];  
 
 pol_aa [alpha_T1] → [alpha_alpha_T1];  
 
 dis_aa [alpha_T1_alpha] → [alpha] + [alpha_alpha_T1];  
 
 nick_aa [alpha_alpha_T1] → [alpha_T1_alpha];  
 
 ass_ab_l [alpha] + [T2] ↔ [alpha_T2];  
 
 m_ass_ab_lr [alpha_T2_beta] ↔ [alpha_T2] + [beta];  
 
 m_ass_ab_r [T2_beta] ↔ [T2] + [beta];  
 
 m_ass_ab_rl [alpha_T2_beta] ↔ [alpha] + [T2_beta];  
 
 pol_ab [alpha_T2] → [alpha_beta_T2];  
 
 dis_ab [alpha_T2_beta] → [beta] + [alpha_beta_T2];  
 
 nick_ab [alpha_beta_T2] → [alpha_T2_beta];  
 
 ass_bc_l [beta] + [T3] ↔ [beta_T3];  
 
 m_ass_bc_lr [beta_T3_Inh] ↔ [beta_T3] + [Inh];  
 
 ass_bc_r [T3] + [Inh] ↔ [T3_Inh];  
 
 ass_bc_rl [beta] + [T3_Inh] ↔ [beta_T3_Inh];  
 
 pol_bc [beta_T3] → [beta_Inh_T3];  
 
 dis_bc [beta_T3_Inh] → [Inh] + [beta_Inh_T3];  
 
 nick_bc [beta_Inh_T3] → [beta_T3_Inh];  
 
 inh_ac [T1] + [Inh] ↔ [Inh_T1];  
 
 inh_displ_ac [T1_alpha] + [Inh] ↔ [alpha] + [Inh_T1];  
 
 m_inh_displ_ca [alpha] + [Inh_T1] ↔ [alpha_T1] + [Inh];  
 
 exo_a [alpha] ↔ [empty];  
 
 exo_b [beta] ↔ [empty];  
 
 exo_c [Inh] ↔ [empty];  
 
Rules (5)
 
 Assignment Rule (name: Bp_concentration) Bp_concentration = 11*(alpha_T1+T1_alpha+alpha_T2+T2_beta+beta_T3)+16*(T3_Inh+Inh_T1)+22*(alpha_T1_alpha+alpha_alpha_T1+alpha_T2_beta+alpha_beta_T2)+27*(beta_T3_Inh+beta_Inh_T3)
 
 Assignment Rule (name: fluorescence) fluorescence = (-0.38)+0.00093*(11*(alpha_T1+T1_alpha+alpha_T2+T2_beta+beta_T3)+16*(T3_Inh+Inh_T1)+22*(alpha_T1_alpha+alpha_alpha_T1+alpha_T2_beta+alpha_beta_T2)+27*(beta_T3_Inh+beta_Inh_T3))
 
 Assignment Rule (name: Inh_total) Inh_total = Inh+T3_Inh+beta_T3_Inh+Inh_T1
 
 Assignment Rule (name: beta_total) beta_total = beta+T2_beta+alpha_T2_beta+beta_T3+beta_T3_Inh
 
 Assignment Rule (name: alpha_total) alpha_total = alpha+alpha_T1+T1_alpha+2*alpha_T1_alpha+alpha_T2+alpha_T2_beta+alpha_T2
 
  Spatial dimensions: 3.0  Compartment size: 1.0
 
 T1
Compartment: sample
Initial concentration: 38.5
 
 alpha
Compartment: sample
Initial concentration: 10.0
 
 alpha_T1
Compartment: sample
Initial concentration: 0.0
 
 alpha_T1_alpha
Compartment: sample
Initial concentration: 0.0
 
 T1_alpha
Compartment: sample
Initial concentration: 0.0
 
 alpha_alpha_T1
Compartment: sample
Initial concentration: 0.0
 
 T2
Compartment: sample
Initial concentration: 3.89
 
 alpha_T2
Compartment: sample
Initial concentration: 0.0
 
 alpha_T2_beta
Compartment: sample
Initial concentration: 0.0
 
 beta
Compartment: sample
Initial concentration: 0.0
 
 T2_beta
Compartment: sample
Initial concentration: 0.0
 
 alpha_beta_T2
Compartment: sample
Initial concentration: 0.0
 
 T3
Compartment: sample
Initial concentration: 38.5
 
 beta_T3
Compartment: sample
Initial concentration: 0.0
 
 beta_T3_Inh
Compartment: sample
Initial concentration: 0.0
 
 Inh
Compartment: sample
Initial concentration: 0.0
 
 T3_Inh
Compartment: sample
Initial concentration: 0.0
 
 beta_Inh_T3
Compartment: sample
Initial concentration: 0.0
 
 Inh_T1
Compartment: sample
Initial concentration: 0.0
 
 empty
Compartment: sample
Initial concentration: 0.0
 
Global Parameters (47)
 
 k0d
Value: 0.0294   (Units: nM_per_min)
Constant
 
 k0r
Value: 3.43457943925   (Units: per_min)
Constant
 
 k1d
Value: 3.43457943925   (Units: per_min)
Constant
 
 k1r
Value: 0.0294   (Units: nM_per_min)
Constant
 
 k2d
Value: 3.43457943925   (Units: per_min)
Constant
 
 k2r
Value: 0.0294   (Units: nM_per_min)
Constant
 
 k3d
Value: 3.43457943925   (Units: per_min)
Constant
 
 k3r
Value: 0.0294   (Units: nM_per_min)
Constant
 
 k4d
Value: 15.2   (Units: per_min)
Constant
 
 k5d
Value: 11.8408   (Units: per_min)
Constant
 
 k6d
Value: 3.34   (Units: per_min)
Constant
 
 k7d
Value: 0.0294   (Units: nM_per_min)
Constant
 
 k7r
Value: 3.43457943925   (Units: per_min)
Constant
 
 k8d
Value: 0.610714285714   (Units: per_min)
Constant
 
 k8r
Value: 0.0171   (Units: nM_per_min)
Constant
 
 k9d
Value: 0.610714285714   (Units: per_min)
Constant
 
 k9r
Value: 0.0171   (Units: nM_per_min)
Constant
 
 k10d
Value: 3.43457943925   (Units: per_min)
Constant
 
 k10r
Value: 0.0294   (Units: nM_per_min)
Constant
 
 k11d
Value: 11.8408   (Units: per_min)
Constant
 
 k12d
Value: 9.2239832   (Units: per_min)
Constant
 
 k13d
Value: 2.60186   (Units: per_min)
Constant
 
 k14d
Value: 0.0171   (Units: nM_per_min)
Constant
 
 k14r
Value: 0.610714285714   (Units: per_min)
Constant
 
 k15d
Value: 0.00186296832954   (Units: per_min)
Constant
 
 k15r
Value: 0.027   (Units: nM_per_min)
Constant
 
 k16d
Value: 0.027   (Units: nM_per_min)
Constant
 
 k16r
Value: 0.00186296832954   (Units: per_min)
Constant
 
 k17d
Value: 0.0171   (Units: nM_per_min)
Constant
 
 k17r
Value: 0.610714285714   (Units: per_min)
Constant
 
 k18d
Value: 17.024   (Units: per_min)
Constant
 
 k19d
Value: 5.566848   (Units: per_min)
Constant
 
 k20d
Value: 3.2064   (Units: per_min)
Constant
 
 k21d
Value: 0.027   (Units: nM_per_min)
Constant
 
 k21r
Value: 0.00608108108108   (Units: per_min)
Constant
 
 k22d
Value: 0.021546   (Units: nM_per_min)
Constant
 
 k22r
Value: 4.15391351351E-5   (Units: nM_per_min)
Constant
 
 k23d
Value: 4.15391351351E-5   (Units: nM_per_min)
Constant
 
 k23r
Value: 0.021546   (Units: nM_per_min)
Constant
 
 k24d
Value: 0.411   (Units: per_min)
Constant
 
 k25d
Value: 0.485802   (Units: per_min)
Constant
 
 k26d
Value: 1.7262   (Units: per_min)
Constant
 
  Bp_concentration
Value: NaN   (Units: nM)
 
  fluorescence
Value: NaN
 
  Inh_total
Value: NaN   (Units: nM)
 
  beta_total
Value: NaN   (Units: nM)
 
  alpha_total
Value: NaN   (Units: nM)
 
Representative curation result(s)
Representative curation result(s) of BIOMD0000000315

Curator's comment: (updated: 17 Feb 2011 01:22:00 GMT)

Time courses as in fig 2b of the article. Simulations were performed using Copasi 4.6.33

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