ETHZ/Simulations

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Contents

Basic Model

Constitutively produced proteins

Model01b.png

Learning system

Model02b.png

Reporter system

Model03b.png

System Equations

Constitutively produced proteins

Eq01.png

Learning system

Eq02.png

Reporter system

Eq03.png

Allosteric regulation

Eq04.png


Comments

Note that the three constitutively produced proteins lacI, tetR and luxR exist in two different forms: as free proteins and in complexes they build with IPTG, aTc and AHL, respectively.

In this new formulation of the model equations, the characterization is more amenable to human interpretation (although equivalent to the previous formuation). The promoters are now characterized by their maximum transcription rate (cimax) and the basic production (aX), which gives the 'leakage' if the gene is fully inhibited. Note that in the given mathematical formulation the basic production is specified as a percentage of the max. transcription rate and is therefore unitless.

The max. transcription rate is given per gene (as agreed with Sven during the meeting at Sep 20.). This means that to get the total transcription rate we need to multiply with the number of gene copies per cell which is represented as llo/lhi in the model equations.

Model Parameters

Parameter Value Description Comments
c1max 0.01 [mM/h] max. transcription rate of constitutive promoter (per gene) promoter no. J23105; Reference: Estimate
c2max 0.01 [mM/h] max. transcription rate of luxR-activated promoter (per gene) Reference: Estimate
lhi 25 high-copy plasmid number Reference: Estimate
llo 5 low-copy plasmid number Reference: Estimate
aQ2,R 0.1 - 0.2 basic production of Q2/R-inhibited genes Reference: Conclusions after discussion
aQ2 0.1 - 0.2 basic production of Q2-inhibited genes Reference: Conclusions after discussion
aQ1,S 0.1 - 0.2 basic production of Q1/S-inhibited genes Reference: Conclusions after discussion
aQ1 0.1 - 0.2 basic production of Q1-inhibited genes Reference: Conclusions after discussion
aQ2,S 0.1 - 0.2 basic production of Q2/S-inhibited genes Reference: Conclusions after discussion
aQ1,R 0.1 - 0.2 basic production of Q1/R-inhibited genes Reference: Conclusions after discussion
dR 2.31e-3 [per sec] degradation of lacI Ref. [10]
dS 1e-5 [pro sec]/2.31e-3 [per sec] degradation of tetR Ref. [9]/ Ref. [10]
dL 1e-3 - 1e-4 [per sec] degradation of luxR Ref: [6]
dQ1 7e-4 [per sec] degradation of cI Ref. [7]
dQ2 degradation of p22cII
dYFP 6.3e-3 [per min] degradation of YFP suppl. mat. to Ref. [8] corresponding to a half life of 110min
dGFP 6.3e-3 [per min] degradation of GFP in analogy to YFP
dRFP 6.3e-3 [per min] degradation of RFP in analogy to YFP
dCFP 6.3e-3 [per min] degradation of CFP in analogy to YFP
KR 0.1 - 1 [pM] lacI repressor dissociation constant Ref. [2]
KIR 1.3 [µM] IPTG-lacI repressor dissociation constant Ref. [2]
KS 179 [pM] tetR repressor dissociation constant Ref. [1]
KIS 893 [pM] aTc-tetR repressor dissociation constant Ref. [1]
KL 55 - 520 [nM] luxR activator dissociation constant Ref: [6]
KIL 0.09 - 1 [µM] AHL-luxR activator dissociation constant Ref: [6]
KQ1
  • 8 [pM]
  • 50 [nM]
cI repressor dissociation constant
  • Ref. [12]
  • starting with values of Ref. [6] and using Ref. [3]
KQ2 0.577 [µM] p22cII repressor dissociation constant Ref. [11]. Note that they use a protein cII and we have p22cII. Does that match?
nR 1 lacI repressor Hill cooperativity Ref. [5]
nIR 2 IPTG-lacI repressor Hill cooperativity Ref. [5]
nS 3 tetR repressor Hill cooperativity Ref. [3]
nIS 2 (1.5-2.5) aTc-tetR repressor Hill cooperativity Ref. [3]
nL 2 luxR activator Hill cooperativity Ref: [6]
nIL 1 AHL-luxR activator Hill cooperativity Ref. [3]
nQ1 1.9 cI repressor Hill cooperativity Ref. [5]
nQ2 4 p22cII repressor Hill cooperativity Ref. [11]. Note that they use a protein cII and we have p22cII. Does that match?

References

  1. A synthetic time-delay circuit in mammalian cells and mice (http://www.pnas.org/cgi/content/abstract/104/8/2643)
  2. Detailed map of a cis-regulatory input function (http://www.pnas.org/cgi/content/full/100/13/7702?ck=nck)
  3. Parameter Estimation for two synthetic gene networks (http://ieeexplore.ieee.org/iel5/9711/30654/01416417.pdf)
  4. Supplementary on-line information for "A Synthetic gene-metabolic oscillator" (no link)
  5. Genetic network driven control of PHBV copolymer composition (http://dx.doi.org/10.1016/j.jbiotec.2005.08.030)
  6. Systems analysis of a quorum sensing network: Design constraints imposed by the functional requirements, network topology and kinetic constants (http://dx.doi.org/10.1016/j.biosystems.2005.04.006)
  7. Stochastic Kinetic Analysis of Developmental Pathway Bifurcation in Phage λ-Infected E. coli Cells
  8. Yeast Cbk1 and Mob2 Activate Daughter-Specific Genetic Programs to Induce Asymmetric Cell Fates
  9. Engineering stability in gene networks by autoregulation
  10. Model-Driven Designs of an Oscillating Gene Network
  11. Synchronizing genetic relaxation oscillators by intercell signaling (http://www.pnas.org/cgi/reprint/99/2/679)

Variable Mapping

Variable Compound
R lacI
IR IPTG
S tetR
IS aTc
L luxR
IL AHL
Q1 cI
Q2 p22cII