Difference between revisions of "Team:Valencia UPV/Model"

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<a class="dropdown-toggle" href="#intro">Introduction</a>
 
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<li><a href="#deterystcomod">Deterministic and Stochastic Models</a></li>
 
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<a class="dropdown-toggle" href="#overview">Overview</a>
 
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<li><a href="#what">What We Are Modeling?</a></li>
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<h2><span>INTRODUCTION</span></h2>
 
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<p class="jopesangria">Modeling our gene circuits is of paramount importance since it provides us with deep insight and prediction capability of the biological processes taking place in ChatterPlant. This way, we aim to break the traditional wall imposed by trial-error approaches, which often result in unnecessary or inconclusive experiments.</p>
 
<p class="jopesangria">Mathematical models in synthetic biology contribute not only to generate empirically contrastable hypothesis but also to manage laboratory time and hardware resources efficiently. Furthermore, because of the understanding and foresight provided by modeling, tuning and programing ChatterPlant according to the necessities of certain situations is possible more than ever.</p>
 
<div id="deterystcomod" class="heading-color jopesubapartado">
 
<h4><span>DETERMINISTIC AND STOCHASTIC MODELS</span></h4>
 
</div>
 
<p class="jopesangria">In ChatterPlant we analyze the dynamic behavior of our biological system considering the biochemical species involved in a certain set of reactions. According to the degree of approximation to capture the dynamic behavior, we can differentiate two approaches:</p>
 
<ol class="jopenumeracion">
 
<li>
 
<p class="jopesangria" style="margin-bottom: 0px !important;"><strong class="jopenegrita">Deterministic</strong>. Deterministic models do not take into account the natural randomness of the reactions. For each chemical species, the amount of molecules transformed within reactions only depends on the initial amount of molecules, reaction rates and stoichiometry relations.</p>
 
<p class="jopesangria">The type of deterministic model that we implement is a system of Ordinary Differential Equations (ODEs)</p>
 
</li>
 
<li><strong class="jopenegrita">Stochastic</strong>. Inherent noise due to random events plays a relevant role in the dynamics. As a deterministic model does not capture noise, we use stochastic linear differential equations</li>
 
</ol>
 
<div class="divider"><!-- divider /ESTO ES LA BARRITA QUE SALE TRAS UN APARTADO NO SE PUEDE QUITAR/ --></div>
 
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<div id="motivation" class="heading-color jopesubapartado">
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<h4><span>MOTIVATION</span></h4>
 +
</div>
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<p class="jopesangria">In ChatterPlant we aim to understand and program <u><a href="https://2017.igem.org/Team:Valencia_UPV/Design" target="_blank">our synbio device</u></a> according to the necessities of certain situations.</p>
 +
<p class="jopesangria">Modeling our gene circuits provides us with <strong class="jopenegrita">deep insight </strong> and <strong class="jopenegrita">prediction capability</strong> of the biological processes taking place in ChatterPlant.</p>
 +
<p class="jopesangria">Furthermore, mathematical models in synthetic biology contribute not only to generate empirically contrastable hypothesis, but also to manage resources efficiently, skipping unnecessary experiments imposed by trial-error approaches.</p>
 
<div id="what" class="heading-color jopesubapartado">
 
<div id="what" class="heading-color jopesubapartado">
 
<h4><span>WHAT WE ARE MODELING?</span></h4>
 
<h4><span>WHAT WE ARE MODELING?</span></h4>
 
</div>
 
</div>
<p class="jopesangria">The SynBio-based design integrated in ChatterPlant is composed by two gene circuits. The analysis of both their single performance and their interaction with several factors (e.g. the cell medium, environment and ChatterBox), is basic to reach one of our main goals: a new sustainable and efficient agriculture system.</p>
+
<p class="jopesangria">The SynBio-based design integrated in ChatterPlant is composed by <strong class="jopenegrita">two gene circuits</strong>. In order to set ChatterPlant as <u><a href="https://2017.igem.org/Team:Valencia_UPV/HP/Gold_Integrated" target="_blank">a new sustainable and efficient agriculture system</a></u>, we analyzed both their single performance and their interaction with several factors (e.g. the cell medium, environment and ChatterBox).</p>
 
<p class="jopesangria">Our model comprises of:</p>
 
<p class="jopesangria">Our model comprises of:</p>
 
<ol class="jopenumeracion">
 
<ol class="jopenumeracion">
<li><strong class="jopenegrita">Optogenetic circuit</strong>. How long has to remain the light pulse in order to get a certain protein amount? How could be optimized the energetic supply of LEDs light in order to maximize a cycle of protein production? These questions among others arose to our minds as we were designing the LED’s system.</li>
+
<li><strong class="jopenegrita">HUMAN-PLANT: Optogenetic circuit. </strong>. How to tune the synbio circuit parameters to get the desired plant response to red light stimulus? How long has to remain the <u><a href="https://2017.igem.org/Team:Valencia_UPV/Hardware" target="_blank">LEDs system</a></u> switched ON in order to get a certain protein amount? </li>
<li><strong class="jopenegrita">Sensor circuit</strong>. Bearing in mind the time span during which the biological sensor is transiently ON, it is mandatory to design a sampling rate test according to the plant’s periodic security necessities.</li>
+
<p><u><a href="#HPoptcir" target="_blank">Check our Optogenetic circuit model</a></u></p>
 +
<li><strong class="jopenegrita">PLANT-HUMAN: AND gate. </strong>  How much GP3 is necessary to let the color be expressed? Which is the optimal proportion between recombinases and GP3?</li>
 +
<p><u><a href="#HPand" target="_blank">Check our AND gate model</a></u></p>
 +
</ol>
 +
<p class="jopesangria">In our in silico experiments, we analysed empirical data and used optimization algorithms in order to set the optimal conditions which ensure a smooth bidirectional communication between plants and humans.</p>
 +
<div id="how" class="heading-color jopesubapartado">
 +
<h4><span>HOW WE ARE MODELING?</span></h4>
 +
</div>
 +
<p class="jopesangria">In ChatterPlant we analyze the dynamic behavior of our biological system considering the biochemical species involved in a certain set of reactions. According to the degree of approximation to capture the dynamic behavior, we can differentiate two approaches:</p>
 +
<ol class="jopenumeracion">
 +
<li><strong class="jopenegrita">Deterministic</strong>. Deterministic models do not take into account the natural randomness of the reactions. For each chemical species, the amount of molecules transformed within reactions only depends on the initial amount of molecules, reaction rates and stoichiometry relations.</li>
 +
<p><u><a href="#HPdeter" target="_blank">Check our Deterministic Optogenetic Model</a></u></p>
 +
<p><u><a href="#PHdeter" target="_blank">Check our Deterministic Recombinase-GP3 Model</a></u></p>
 +
<li><strong class="jopenegrita">Stochastic</strong>. Inherent noise due to random events plays a relevant role in the dynamics. As a deterministic model does not capture noise, we use stochastic linear differential equations.</li>
 
</ol>
 
</ol>
 
<div id="software" class="heading-color jopesubapartado">
 
<div id="software" class="heading-color jopesubapartado">
 
<h4><span>MODELING SOFTWARE MODULES</span></h4>
 
<h4><span>MODELING SOFTWARE MODULES</span></h4>
 
</div>
 
</div>
<p class="jopesangria">We start building the genetic circuits from basic modules, coupling them to generate the mathematical model of the whole system. As UPV_iGEM is an interdisciplinary team, most of the models generated in ChatterPlant are included in the modeling software tool and are represented by modules in an artistic graphic interface, for the purpose of introducing researchers to a more realistic conception of the engineering in biology, meanly, SynBio.</p>
+
<p class="jopesangria">We start building the genetic circuits from basic modules, coupling them to generate the mathematical model of the whole system. As UPV_iGEM is an interdisciplinary team, most of the models generated in ChatterPlant are included in the <u><a href="https://2017.igem.org/Team:Valencia_UPV/Software#modeling" target="_blank">modeling software tool</a></u> and are represented by modules in an artistic graphic interface, for the purpose of introducing researchers to a more realistic conception of the engineering in biology, meanly, SynBio.</p>
 
<div class="divider"><!-- divider --></div>
 
<div class="divider"><!-- divider --></div>
 
</div>
 
</div>

Revision as of 22:18, 1 November 2017

Home • Dry Lab •

MODELING

OVERVIEW

MOTIVATION

In ChatterPlant we aim to understand and program our synbio device according to the necessities of certain situations.

Modeling our gene circuits provides us with deep insight and prediction capability of the biological processes taking place in ChatterPlant.

Furthermore, mathematical models in synthetic biology contribute not only to generate empirically contrastable hypothesis, but also to manage resources efficiently, skipping unnecessary experiments imposed by trial-error approaches.

WHAT WE ARE MODELING?

The SynBio-based design integrated in ChatterPlant is composed by two gene circuits. In order to set ChatterPlant as a new sustainable and efficient agriculture system, we analyzed both their single performance and their interaction with several factors (e.g. the cell medium, environment and ChatterBox).

Our model comprises of:

  1. HUMAN-PLANT: Optogenetic circuit. . How to tune the synbio circuit parameters to get the desired plant response to red light stimulus? How long has to remain the LEDs system switched ON in order to get a certain protein amount?
  2. Check our Optogenetic circuit model

  3. PLANT-HUMAN: AND gate. How much GP3 is necessary to let the color be expressed? Which is the optimal proportion between recombinases and GP3?
  4. Check our AND gate model

In our in silico experiments, we analysed empirical data and used optimization algorithms in order to set the optimal conditions which ensure a smooth bidirectional communication between plants and humans.

HOW WE ARE MODELING?

In ChatterPlant we analyze the dynamic behavior of our biological system considering the biochemical species involved in a certain set of reactions. According to the degree of approximation to capture the dynamic behavior, we can differentiate two approaches:

  1. Deterministic. Deterministic models do not take into account the natural randomness of the reactions. For each chemical species, the amount of molecules transformed within reactions only depends on the initial amount of molecules, reaction rates and stoichiometry relations.
  2. Check our Deterministic Optogenetic Model

    Check our Deterministic Recombinase-GP3 Model

  3. Stochastic. Inherent noise due to random events plays a relevant role in the dynamics. As a deterministic model does not capture noise, we use stochastic linear differential equations.

MODELING SOFTWARE MODULES

We start building the genetic circuits from basic modules, coupling them to generate the mathematical model of the whole system. As UPV_iGEM is an interdisciplinary team, most of the models generated in ChatterPlant are included in the modeling software tool and are represented by modules in an artistic graphic interface, for the purpose of introducing researchers to a more realistic conception of the engineering in biology, meanly, SynBio.

HUMAN-PLANT: OPTOGENETIC CIRCUIT

Two constitutive modules express the E-PIF6 and PhyB-VP64 fusion proteins that regulate the output expression.

Constitutive modules representation of the fusion proteins E-PIF6 and PhyB-VP64.

E-PIF6 binds to the promoter’s operator. When red light (660 nm wavelength) LEDs are switched on, PhyB changes its conformation (PhyB*) and binds to PIF6. Consequently, the transcription of the desired protein starts because of the RNAp recruitment by VP64.

Expression regulated by the transcriptional factors.

Far red light (740 nm wavelength) reverts PhyB* to its natural conformation (PhyB). This change stops de transcriptional activity of the third optogenetic circuit’s module.

Switch off.

DETERMINISTIC

REACTIONS

Now we take into account the principal reactions in each module representing them both graphic design and formal reactions.

E-PIF6 expression

PhyB-VP64 expression

Regulated expression

Constitutive module A=E-PIF6

Constitutive module B=PhyB-VP64

Regulated module

ASSUMPTIONS

Considerations in the model:

  1. The cRNAp constant considers that the cell has the sufficient free RNAp in excess to be utilized by all the active genes that are transcribing simultaneously in the cell, including the gene of interest. Under this conception, the free RNAp vary in an almost unappreciable way in time, so can be defined as the CRNApFree constant and consequently the sum of the RNAp linked to the DNA and the free RNAp as the cRNAp constant.
  2. The RNAp binding-unbinding reactions to the promoter are much faster than the elongation and degradation reactions, so can be considered in the equilibrium state.
  3. Transcription reaction is faster than translation reaction, so can be considered in the equilibrium state.
  4. The conformation change is instantaneous.
FINAL EQUATIONS

After a mathematical development (download here for more information), we obtained the following equations, which define the constitutive and regulated expression respectively (where sub P is a generalization to name the protein)

Constitutive expression production is directly proportional to the translation rate (kx), to the transcription effective rate (kmxe), to the gene copy number (cnx) and inverse proportional to the mRNA degradation rate (dmx). The protein degradation is defined by the protein degradation rate in the cellular medium.