Difference between revisions of "Team:IIT Delhi/Deterministic Model"

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The biological networks are highly nonlinear and exhibit interesting phenotypical be-
 +
havior for certain operating conditions. One of such behaviour is the limit cycle in the
  
 +
mathematical sense, which shows a sustained oscillations of protein levels in the cell. It
  
A Mathematical model captures the essential dynamics of the system in the form of mathematical equations and helps to study and analyze the biological system before stepping into lab work. All of the chemical reactions in the system can essentially be written in the form of differential equations that capture the biological processes in the cell. These equations can then be simulated and the dynamics can be analyzed, in order to understand how a particular network is going to behave inside the cell. <br><br>
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is quite interesting as well important to look for topologies which can produce such os-
 +
cillations for different amplitude, oscillation and shape. Here, we have used a theoretical
  
The two molecular processes that are central to the functioning of a cell are transcription and translation. The cell consists of DNA, which contains all the genetic information of the cell. It contains information for synthesis of various proteins required for normal functioning of the cell. The process of transcription leads to creation of mRNA from DNA which contains the information for protein synthesis. This mRNA is then translated into protein with the help of ribosomes and tRNA. <br><br>
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framework to begind with for identifying topology based on following theorem.
 +
Theorem:1 Consider a system  ̇x = f(x), which is of ring in nature, and f is a monotone
 +
function and in the form
  
<img src = "https://static.igem.org/mediawiki/2017/4/42/T--IIT_Delhi--picture1.png" style='border:3px solid #000000' width = "80%"><br><br>
+
Then, if the Jacobian of f and x has no repeated eigenvalues and has any eigenvalue
 +
with positive real parts, then the system must have a consistent periodic orbit.
 +
To design a squarewave oscillator, we used the theorem to idenify the biological system
 +
which can satisfies such condition. One of classical example is Repressillator (Elowitz et
 +
all) or 5n1 ring oscillator (Murray et al). This kind of oscillator is based on negative
 +
feedback with delay and able to produce stable limit cycle in computation and as well as
 +
experimentally. However, these oscillators are more of a phaselag oscillator matching the
 +
sinusoidal umbrella behavior. As the the philosophy behind our work is to design towards
 +
square wave, we exploit the system parameters to produce relaxation oscillations. The
 +
relaxation oscillator typically works on the principle to level of concentration, where once
 +
the level is reached it relaxes there for some additional time and falls back to another
 +
level and resides there for some till till it jumps back (slowly). The time evolution of such
 +
trajectories portray a square wave-sih in state-space.
 +
The dynamical model of the five node oscillator can be written as;
  
Thus, the entire set of reactions happening inside a cell leading to the expression of a gene can be broken down into the following –<br><br>
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where i ∈ [0 = 5, 1, 2, 3, 4, 5], xmi is the mRNA concentration level, xpi is the protein
<img src = "https://static.igem.org/mediawiki/2017/5/55/T--IIT_Delhi--picture2.png" style='border:3px solid #000000' width = "80%"><br><br>
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transcription level, βm0 is the leaky expression, βmi is the production rate of mRNA, βpi
 +
is the production rate of protein, γmi is the degradation/dilution of mRNA and γpi is
 +
the degradation/dilution of protein for ith protein. The simulation results of the model
  
Here, the major processes occurring are as follows -
+
presented in Fig. . It is evident the such system can exhibit a oscillation resembling a
<br><br>
+
squarewave.
<h3 id="pfont2"><u>mRNA</u> </h3>
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<br><br>
+
  
<ol class="centered">
+
As the dynamical model comprises of two time-scale, one can use the singular pertur-
<li>mRNA is being produced from the plasmid DNA that has been introduced into the cell via transformation, by the process of transcription.
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bation analysis to reduce the model in to smaller one, i.e. 5th order, as discussed earlier.
 
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<li>The mRNA produced is also being degraded, because it has a certain half life (just like radioactive elements decay, all chemicals have a half life, and so do DNA and RNA!).
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</ol>
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<h3 id="pfont2"><u>Protein</u> </h3><ol class="centered"><left>
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<li>Protein is produced from the mRNA transcript by the process of translation.
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<li>Protein is also degraded since it has a half life, similar to the mRNA.
+
</ol><br><br></left>
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What needs to be noted before we start to write a model for this is that this is a very simplistic model that makes use of several assumptions and simplifications. This is because biological systems are extremely complex, and at a single instant of time, there are several hundred reactions happening. Thus, we need to simplify and lump certain intermediate reactions, in order to have some quantitative estimate of how our system will behave.
+
<br><br>
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Some of the assumptions made here are -  
+
<br><br>
+
<ol class="centered"><left>
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<li>mRNA is made directly from DNA, and all the other components and processes in between, such as pulling of RNA polymerase (RNAp) by the TATA box in the promoter, binding of RNAp to the promoter and initiation of transcription are sufficiently fast, so that the parameters can be lumped and variables (such as RNAp and Promoter) can be ignored.
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<li>Degradation of molecules such as mRNA and protein is spontaneous, and is not triggered or accelerated by certain components (such as ssrA).  
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<li>The rates of production and degradation are constant.
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<li>mRNA is not degraded, damaged, or consumed in any way during translation or production (transcription).
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<li>Total DNA inside a cell is constant.
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<li>Mass action kinetics is valid for the reactions occurring above
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</ol></left>
+
  
 +
The simpler version of the model, where multiple constants product are clubbed into one,
 +
can be reproduced as follows,
  
 +
where αi can be considered as the protein production rate constant and γ as the degra-
 +
dation constant. The simulation of 5th order comes model presented in FigX is almost
  
 +
identical to the simulation for full order model. Both of the model can exhibit sustained
 +
square wave like response of arbitrary initial conditions.
  
  

Revision as of 17:01, 1 November 2017

iGEM IIT Delhi


Deterministic Model

                                                                                                                                                                                                                 

The biological networks are highly nonlinear and exhibit interesting phenotypical be- havior for certain operating conditions. One of such behaviour is the limit cycle in the mathematical sense, which shows a sustained oscillations of protein levels in the cell. It is quite interesting as well important to look for topologies which can produce such os- cillations for different amplitude, oscillation and shape. Here, we have used a theoretical framework to begind with for identifying topology based on following theorem. Theorem:1 Consider a system ̇x = f(x), which is of ring in nature, and f is a monotone function and in the form Then, if the Jacobian of f and x has no repeated eigenvalues and has any eigenvalue with positive real parts, then the system must have a consistent periodic orbit. To design a squarewave oscillator, we used the theorem to idenify the biological system which can satisfies such condition. One of classical example is Repressillator (Elowitz et all) or 5n1 ring oscillator (Murray et al). This kind of oscillator is based on negative feedback with delay and able to produce stable limit cycle in computation and as well as experimentally. However, these oscillators are more of a phaselag oscillator matching the sinusoidal umbrella behavior. As the the philosophy behind our work is to design towards square wave, we exploit the system parameters to produce relaxation oscillations. The relaxation oscillator typically works on the principle to level of concentration, where once the level is reached it relaxes there for some additional time and falls back to another level and resides there for some till till it jumps back (slowly). The time evolution of such trajectories portray a square wave-sih in state-space. The dynamical model of the five node oscillator can be written as; where i ∈ [0 = 5, 1, 2, 3, 4, 5], xmi is the mRNA concentration level, xpi is the protein transcription level, βm0 is the leaky expression, βmi is the production rate of mRNA, βpi is the production rate of protein, γmi is the degradation/dilution of mRNA and γpi is the degradation/dilution of protein for ith protein. The simulation results of the model presented in Fig. . It is evident the such system can exhibit a oscillation resembling a squarewave. As the dynamical model comprises of two time-scale, one can use the singular pertur- bation analysis to reduce the model in to smaller one, i.e. 5th order, as discussed earlier. The simpler version of the model, where multiple constants product are clubbed into one, can be reproduced as follows, where αi can be considered as the protein production rate constant and γ as the degra- dation constant. The simulation of 5th order comes model presented in FigX is almost identical to the simulation for full order model. Both of the model can exhibit sustained square wave like response of arbitrary initial conditions.




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