Team:Brown/Project/Light pattern/Workflow

From 2010.igem.org

(Difference between revisions)
(Workflow)
(Mathematical Modeling Workflow)
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====Mathematical Modeling Workflow====
====Mathematical Modeling Workflow====
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The following are the steps we took to arrive at our in silico model of the Light Pattern Controlled Circuit:
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#We first had to assess what mathematical modeling entails, as none of our team members had previously been exposed to this kind of approach. We determined, largely by reviewing past team's modeling sections, that we had to generate differential equations for each product of the circuit.
 +
#As we did not have any particular experience in this branch of applied math, we consulted with Dr. Sindi, an applied math professor at our University. This meeting helped get us on track for the creation of our many differential equations, as Dr. Sindi was an enormous help.
 +
#Each differential equation we created is accompanied by a set of parameters. The differential equations themselves, without defined parameters, merely show the interrelation of the various parts of our genetic network. Defining parameters for each equation allows the equation to be linked specifically to the function of an individual promoter or factor. Thus, we conducted literature research and reviews past iGEM teams' work to compile the parameters for our equations.
 +
#Given the wide range of sources for the parameters we collected, we made various assumptions to normalize the parameters to more realistic values. Given more time, in vitro characterization of each component of the circuit might have suggested the most appropriate values to use. Unfortunately, we were not able to get to this point, and so relied on literature and past work.
 +
#We then created code in Matlab in order to solve our system of ordinary differential equations. This matlab file collected all of the appropriate parameters, set initial conditions and events, and used built in numerical solvers to generate solutions to each differential equation. This gives equations for the varios products of the circuit over time, and calling graphing methods enabled us to visualize, better understand, and display the functionality in silico of our circuit.
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 +
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Transformation of CI, AraC, Mnt. Design and ordering primers to add bgl-prefix and RBS to the left, bgl-suffix to the right.  
Transformation of CI, AraC, Mnt. Design and ordering primers to add bgl-prefix and RBS to the left, bgl-suffix to the right.  
PCR,
PCR,
-
image of gary's gel (this is in the lab),
 
ligation to pGEM and transformation successful. Colony PCR to test for insert inconclusive.  
ligation to pGEM and transformation successful. Colony PCR to test for insert inconclusive.  

Revision as of 01:32, 28 October 2010

Light-Pattern Controlled Circuit

Workflow

Rack.jpg

Circuit Beginnings

Once we had designed our circuit, we went about obtaining all of the necessary parts for its construction. Because the registry did not contain the majority of parts crucial to our circuit, we collaborated with teams EPF-Lausanne, PKU, and Davidson-Missouri Western to obtain the relevant parts. From EPF-Lausanne, we received <partinfo>BBa_K191003</partinfo> and <partinfo>BBa_K191005</partinfo>. We received from PKU Beijing AraC+pBad+T7ptag+Terminator, NahR+pSal+supD+Terminator, the Bistable switch, and other miscellaneous parts. From Davidson-Missouri Western, we received <partinfo>BBa_K091141</partinfo> and <partinfo>BBa_K091147</partinfo> to aid in the characterization of the pLac/Mnt hybrid promoter in the distribution. Thanks all for the assistance!

Experimental Procedure

Once we began receiving genetic material, we started our attempts at constructing each required module of our circuit. Clearly, our circuit has many components that, to build a complete example, would require an incredible amount of time. We decided that we could demonstrate our ideas in two ways:

  • Through extensive mathematical modeling, we can show the likely functionality of our circuit and the likely functionality of our circuit through extensive mathematical modeling, which is considerably less prone to error than laboratory work.
  • We can establish proof of concept by pairing our Conversion Module with the Memory Module. By testing this segment of the circuit together, we can show a progression across three states (as we move from light OFF->ON->OFF) by changing one input. Because the state of the circuit when the light is turned back off is different from that when the light was originally off, the crux of the circuit concept has been demonstrated and the ability to achieve more states is evident.


Mathematical Modeling Workflow

The following are the steps we took to arrive at our in silico model of the Light Pattern Controlled Circuit:

  1. We first had to assess what mathematical modeling entails, as none of our team members had previously been exposed to this kind of approach. We determined, largely by reviewing past team's modeling sections, that we had to generate differential equations for each product of the circuit.
  2. As we did not have any particular experience in this branch of applied math, we consulted with Dr. Sindi, an applied math professor at our University. This meeting helped get us on track for the creation of our many differential equations, as Dr. Sindi was an enormous help.
  3. Each differential equation we created is accompanied by a set of parameters. The differential equations themselves, without defined parameters, merely show the interrelation of the various parts of our genetic network. Defining parameters for each equation allows the equation to be linked specifically to the function of an individual promoter or factor. Thus, we conducted literature research and reviews past iGEM teams' work to compile the parameters for our equations.
  4. Given the wide range of sources for the parameters we collected, we made various assumptions to normalize the parameters to more realistic values. Given more time, in vitro characterization of each component of the circuit might have suggested the most appropriate values to use. Unfortunately, we were not able to get to this point, and so relied on literature and past work.
  5. We then created code in Matlab in order to solve our system of ordinary differential equations. This matlab file collected all of the appropriate parameters, set initial conditions and events, and used built in numerical solvers to generate solutions to each differential equation. This gives equations for the varios products of the circuit over time, and calling graphing methods enabled us to visualize, better understand, and display the functionality in silico of our circuit.



describes how the expression construct for LOVTAP and the reporter for LOVTAP (WT LOVTAP R2) were transformed, double transformed to generally confirm function,

creation/ordering of primers for WT LOVTAP R2 to isolate the double repressor part and add bgl sites (since not compatible with RFC 10) and subsequent PCR (image of gel if we have) (Now named LOV2).

Describes unsuccessful transformations (3 times!) of Bistable part from PKU.

Transformation of CI, AraC, Mnt. Design and ordering primers to add bgl-prefix and RBS to the left, bgl-suffix to the right. PCR,

ligation to pGEM and transformation successful. Colony PCR to test for insert inconclusive.

Decision that we should test Conversion module and memory module together with just CI to confirm function. Double digest and ligation of RFC 10 CI and Ter+Ter. Successful transformation, PCR on bgl prefix+RBS, bgl-suffix, successful PCR.

NOTE THAT THIS IS WHERE THE WE WERE AT AT THE WIKI FREEZE. NOTE THAT HERE IS WHAT WE HOPE TO HAVE BY THE COMPETITION: ligate PCR product with pGEM, transform, double digest bgl'd CI+TERTER and LOV2 in bgl standard, ligate, transform. Double digest and ligate LOVTAP expression upstream, transform. Transform bistable (with One Shot Invitrogen cells), double transform and test.