Difference between revisions of "Team:ETH Zurich/Modeling"
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Each module was then first evaluated at the single cell level using MATLAB, in order to evaluate the initial states, the steady states and to study the dynamics of the system. Then, the model was implemented in COMSOL multiphysics to characterize the spatial and temporal behavior.</p> | Each module was then first evaluated at the single cell level using MATLAB, in order to evaluate the initial states, the steady states and to study the dynamics of the system. Then, the model was implemented in COMSOL multiphysics to characterize the spatial and temporal behavior.</p> | ||
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<h2> Goals </h2> | <h2> Goals </h2> | ||
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<li> <a href="https://2015.igem.org/Team:ETH_Zurich/Modeling/Experiments_Model">Characterization</a> of the biological part, to be included in the simulations</li> | <li> <a href="https://2015.igem.org/Team:ETH_Zurich/Modeling/Experiments_Model">Characterization</a> of the biological part, to be included in the simulations</li> | ||
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+ | <h2> Modules </h2> | ||
+ | <p>One advantage of our system is its modularity. The two modules are almost independent since only one species LuxR connects both ends. The modules can therefore be used again in other systems. </p> | ||
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Revision as of 10:35, 18 September 2015
- Project
- Modeling
- Lab
- Human
Practices - Parts
- About Us
Modeling
Overview
Our system consists of a signalling chain, with a lactate sensor triggering the amplification of AHL for neighboring cells to finally produce a fluorescent signal. We divided the model into two modules which were modelled and tested separately before being merged into a single model of the whole system.
- Lactate module
- AHL module
Each module was then first evaluated at the single cell level using MATLAB, in order to evaluate the initial states, the steady states and to study the dynamics of the system. Then, the model was implemented in COMSOL multiphysics to characterize the spatial and temporal behavior.
Goals
Modules
One advantage of our system is its modularity. The two modules are almost independent since only one species LuxR connects both ends. The modules can therefore be used again in other systems.
AND-gate
GFP concentration over time in four cases: A) Cancer cell, bound E. coli B)Cancer cell, unbound E. coli C) Normal cell, bound E. coli D) Normal cell, unbound E. coli
Conclusions
We characterized our system by simulating its modules separately and together through a series of increasingly-complex models. We show that under certain parameters, our lactate module is able to produce LuxR such that the lactate production input signal is amplified. Simulation of the AHL module with a simplified compartment model and with a more accurate reaction-diffusion model show that degradation of AHL by the E. coli does not significantly delay the self-activation of our LuxI and AHL production feedback loop. Instead, riboregulation of the LuxR promoter to prevent leaky expression of LuxI is sufficient to prevent this self-activation within the timescale of our experiment. This demonstrates the viability of our system as a specific CTC detection system utilizing these two general cancer markers.