Team:UCSF/Modeling

From 2013.igem.org

(Difference between revisions)
Line 112: Line 112:
<div id="photos">
<div id="photos">
-
<center><img style="margin-top:10px"; padding:0;"  
+
<center><img style="height:150px; margin-top:10px"; padding:0;"  
src="https://static.igem.org/mediawiki/2013/6/61/Variables.jpg"> </center></div>
src="https://static.igem.org/mediawiki/2013/6/61/Variables.jpg"> </center></div>

Revision as of 03:06, 28 September 2013

Modeling: Decision Making Circuit

The primary goal of the modeling portion for the synthetic circuit project is to create a model that will help us figure out the right parameters, given our assumptions, which will generate the desired result. The model can help us test out different promoters and repression strengths in the computer without wasting time trying to do all of that in the lab. The circuit is designed to produce different outputs according to different levels of inducer by utilizing the CRISPRi system. In lower concentrations of inducer, the guide RNA (gRNA) will be made to repress RFP. In higher concentrations of inducer, another gRNA will be made to repress GFP. Since our circuit should express GFP at lower inducer concentrations and RFP at high inducer concentrations, we should expect the graph to look something like the one below:


If we can get this result from our model, then it would help us figure out how to change our parameters in order to generate the desired behavior.
The first step in modeling our system is to come up with a way to represent our synthetic circuit mathematically. It’s essentially the same diagram as the one shown on the synthetic circuit page, but we added letters to represent each variable for our model. (R:C – gRNA/dCas9 complex; R – gRNA; C – dCas9; L – low inducible promoter; H – high inducible promoter)


ASSUMPTIONS: While creating the model for our system, we made five assumptions in order to simplify some of the aspects of the model:
1) protein degradation is linear;
2) protein production is based on a hill function and also depends on inducer concentration;
3) repression is governed by a hill function and depends on the concentration of dCas9 and gRNA complex;
4) that the binding and unbinding of dCas9 and gRNA complex happens much faster than the production/degradation of gRNA and fluorescent proteins (the complex is at Quasi Steady State).
5) everything diffuses quickly throughout the cell so that our differential equations depends on the concentration at any given time.

VARIABLES:


EQUATIONS:

For fluorescent proteins

These equations show that the amount of fluorescent proteins depends on the production of, as well as the degradation of, the proteins.

Protein Production Equations Depend on Inducer & Repressor Complex:

These next two equations describe the binding and unbinding of the gRNA and dCas9 complex:

Repressor (gRNA) & Repressor/dCas9 Complex:

Retrieved from "http://2013.igem.org/Team:UCSF/Modeling"