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Team:Paris Bettencourt/Modeling
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<p>Answering those two questions was essential for our project. We needed to know <em>what to expect in order to design our experiments</em> properly and to know what kind of restults we should obtain.</p> | <p>Answering those two questions was essential for our project. We needed to know <em>what to expect in order to design our experiments</em> properly and to know what kind of restults we should obtain.</p> | ||
| - | <p>In order to | + | <p>In order to answer the first question, we investigated the <em>physical properties of cell membrane</em> and <em>passive diffusion</em> to comprehend how the transfer could occur. We came up with two different ideas that could explain molecule transfer through the nanotubes, and based our original models on these assumptions, done in Java for passive diffusion and in Matlab for assisted diffusion.These two novel models show that transfer through the nanotubes, whether happening by passive diffusion or the so-called assisted diffusion, is happening too quickly to be accurately measured by fluorescent microscopy. As nanotube transfer is too fast compared to genetic response to allow us to measure its time span correctly, our conclusion was that our designs would not allow us to determine which one of these two processes (passive or assisted diffusion) is dominant during the transfer. Even though this makes it impossible to create a definitive model of molecule transfer through the nanotubes, the information provided by our two alternative models gave us an <em>insight on the time scale of the transfer</em>.</p> |
<p>The second question was a crucial step in the design of our experiments. Taking into account the predicted time scale and other information provided by our two general models, we were able to build <em>models of each of our genetic networks</em>. These models are an improvement of Uri Alon's approach in <i>An Introduction to Systems Biology: Design Principles of Biological Circuits</i> and were done in Matlab. With these models we showed that some designs might work better that the others. For instance, we prioritized the T7 RNA polymerase diffusion and tRNA diffusion systems and decided to concentrate our wet lab experiments and characterizatons in these systems. The ComS system, on the other hand, was less developed because of some disadvantages that our model predicted (high background even without induction, very high activation threshold mainly). Moreover, our models let us <em>evaluate the response time of each of our our constructs</em>. With these estimations, were able to prepare protocols for our <a href ="https://2011.igem.org/Team:Paris_Bettencourt/Experiments/Microscopy">microscopic experiments</a> (by evaluating the characteristic response time of our system, the activation thresholds, etc.).</p> | <p>The second question was a crucial step in the design of our experiments. Taking into account the predicted time scale and other information provided by our two general models, we were able to build <em>models of each of our genetic networks</em>. These models are an improvement of Uri Alon's approach in <i>An Introduction to Systems Biology: Design Principles of Biological Circuits</i> and were done in Matlab. With these models we showed that some designs might work better that the others. For instance, we prioritized the T7 RNA polymerase diffusion and tRNA diffusion systems and decided to concentrate our wet lab experiments and characterizatons in these systems. The ComS system, on the other hand, was less developed because of some disadvantages that our model predicted (high background even without induction, very high activation threshold mainly). Moreover, our models let us <em>evaluate the response time of each of our our constructs</em>. With these estimations, were able to prepare protocols for our <a href ="https://2011.igem.org/Team:Paris_Bettencourt/Experiments/Microscopy">microscopic experiments</a> (by evaluating the characteristic response time of our system, the activation thresholds, etc.).</p> | ||
Revision as of 13:42, 28 October 2011
Modeling
Overview
Our modeling was organized around two main questions:
- Can we explain the transfer through nanotubes?
- What will be the behaviour of our constructs and how will it impact our experimental designs?
Answering those two questions was essential for our project. We needed to know what to expect in order to design our experiments properly and to know what kind of restults we should obtain.
In order to answer the first question, we investigated the physical properties of cell membrane and passive diffusion to comprehend how the transfer could occur. We came up with two different ideas that could explain molecule transfer through the nanotubes, and based our original models on these assumptions, done in Java for passive diffusion and in Matlab for assisted diffusion.These two novel models show that transfer through the nanotubes, whether happening by passive diffusion or the so-called assisted diffusion, is happening too quickly to be accurately measured by fluorescent microscopy. As nanotube transfer is too fast compared to genetic response to allow us to measure its time span correctly, our conclusion was that our designs would not allow us to determine which one of these two processes (passive or assisted diffusion) is dominant during the transfer. Even though this makes it impossible to create a definitive model of molecule transfer through the nanotubes, the information provided by our two alternative models gave us an insight on the time scale of the transfer.
The second question was a crucial step in the design of our experiments. Taking into account the predicted time scale and other information provided by our two general models, we were able to build models of each of our genetic networks. These models are an improvement of Uri Alon's approach in An Introduction to Systems Biology: Design Principles of Biological Circuits and were done in Matlab. With these models we showed that some designs might work better that the others. For instance, we prioritized the T7 RNA polymerase diffusion and tRNA diffusion systems and decided to concentrate our wet lab experiments and characterizatons in these systems. The ComS system, on the other hand, was less developed because of some disadvantages that our model predicted (high background even without induction, very high activation threshold mainly). Moreover, our models let us evaluate the response time of each of our our constructs. With these estimations, were able to prepare protocols for our microscopic experiments (by evaluating the characteristic response time of our system, the activation thresholds, etc.).
You can find more about our models below.
Modeling in our project
Investigating nanotube transfer
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Passive diffusion in nanotubes We investigate here the hypothesis of passive diffusion through nanotubes. |
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Assisted diffusion We propose here a model explaining how diffusion through nanotubes could be "assisted" by the tension differential between cell walls. |
Predicting the behaviour of our designs
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The basics about genetic networks modeling You can find here an introduction to our methods and the general idea behind most gene network models. |
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Our assumptions Because of the specificities of our project, we had to adapt the "classic" model to better represent our current situation. On top of that we made and justified a few other hypotheses detailed in this section. |
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Modeling our designs Models predicting the behaviour of our designs are detailled in this section. |
