# Team:UC Davis/Modeling

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 Revision as of 02:24, 28 September 2013 (view source)← Older edit Revision as of 02:39, 28 September 2013 (view source)Newer edit → Line 29: Line 29: Included here are the parameters used in this model. Please refer to the References section of this page for the source of each parameter value. Included here are the parameters used in this model. Please refer to the References section of this page for the source of each parameter value.

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MATLAB Simulation

MATLAB Simulation

# Equations

The equations below model the concentrations of bound transcription factors. That is, they serve to model the concentration of araC bound to pBAD and tetR bound to pTET given the concentrations of the ligands, arabinose and aTc.

The subsequent equations model the probability of active complex for each element in our circuit. PBAD represents the probability that the pBAD promoter will be unbound by araC and thus active. PTET represents the probability that the pTET promoter will be unbound by tetR and thus active. PRiboswitch expresses the probability that the riboswitch is bound by theophylline, and thus active. For simplicity, it has been modeled here as an activator-controlled promoter. PTale Binding Site, which may be abbreviated to PTBS expresses the probability that the TALe binding site is unbound by the TAL repressor, and thus active.

The third set of equations are ordinary differential equations modeling the change in concentration over time of the riboswitch-TALe transcript, TAL repressor, GFP mRNA, GFP protein intermediate, and GFP protein. In this model we have taken into account the maturation time of GFP.

# Parameters

Included here are the parameters used in this model. Please refer to the References section of this page for the source of each parameter value.

# MATLAB Simulation

### TALe Binding Site KD as a source of tunability

Each state variable in the system of ODEs was given an initial condition of 0. The dynamic response of the system was calculated and plotted over a time span of 10 hours. The results of the model support our data in that the RiboTALe with the larger dissociation constant (RiboTALe 1) is less effective at repressing GFP than RiboTALe 8 under the same induction conditions. The peak seen in the dynamic response of both simulations is a result of the kinematics of the system; there is lag between the initiation of GFP production and when the concentration of active TAL repressors is enough to tip the system.

### RiboTALe Modulation Through Theophylline Induction Levels

This simulation was carried out under the same conditions defined above, but interrogated only one RiboTALe, RiboTALe 1 with a KD of 240 nM. The concentration of theophylline, however, was varied over a range of 1 mM to 10 mM and the results plotted. This simulation also supports our data in that it is clear that the riboswitch is in fact responsive to theophylline and that final GFP counts are inversely proportional to the amount of theophylline added.