Difference between revisions of "Team:NAU-CHINA/Auxiliary Understanding"

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         <p class="top-title">Model</p>
 
         <p class="top-title">Model</p>
         <p class="sec-title">Auxiliary Understanding</p>
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         <p class="sec-title">Overview</p>
 
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     <a href="https://2018.igem.org/Team:NAU-CHINA/Model%20Details">
 
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             <h1>Part1 Why we use stochastic simulation</h1>          
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             <h1>Introduction</h1>
             <p>Ordinary differential equation is a commonly used mathematical tool to describe the chemical reaction. It can be accurate to use the description of the ordinary differential equations, if the simulated system contains more than 10 ^ 3 molecules. However, it is sometimes inappropriate when applying in biological systems, because the life behavior of biochemical reactions involved in small number of molecules. For example, in the gene expression, there is usually only one kind of protein, while a few dozen mRNA molecules, corresponding to these genes. In protein interactions, the number of proteins as reactant is small, far less than the number of molecules in ordinary chemical reactions. The time of chemical reaction in organisms, on the other hand, is longer than that of ordinary chemical reactions. For example, it usually takes a few minutes to complete gene transcription process. The small number of molecules and their slow reaction produces large randomness in chemical reactions. This randomness is caused by two factors. Firstly, the reactant collision response may occur. When the molecules are in a small number or in low concentration, the reactant collision probability is very small. Another factor is a thermodynamic fluctuation. Even in reaction of reactant collision together, the activation energy, which is affected by the fluctuation of heat, has a significant randomness. </p>
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             <p>We propose post-integration conditions, rationally simplify the complex situation, and split the whole process into a series of chemical reactions. Assuming that intervals between two reactions obey exponential distribution, we use the Gillespie algorithm [1] to calculate the changes in various substances in the system with reference to the Dynamics of the Brusselator [2]. The ideas and methods of this model have strong promotion prospects and adaptability. Our model demonstrates the necessity of using the recombinase(rec) system,the improvement effect of the system after adding the pathways expressing RDF-inhibitor and rec-inhibitor in turn, and the robustness of the model .The experimental team verified some assumptions and results of the model and selected materials according to the parameters of the model.</p>
 
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             <h1>Part2 Gillespie algorithm(stochastic simulation algorithm)</h1>          
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             <h1>For judging handbook</h1>
             <p>We are the users of the algorithm, not the inventor, and the following literature is the explanation made by the algorithm inventor. </p>
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             <p>"It is a relatively simple digital computer algorithm which uses a rigorously derived Monte Carlo procedure to numerically simulate the time evolution of the given chemical system." </p>
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            <a href="https://2018.igem.org/Team:NAU-CHINA/Model_Details">What kind of modeling is being done and what information it will provide?</a>
             <p>Exact stochastic simulation of coupled chemical reactions</p>
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             <p>We use the Gillespie algorithm to calculate the changes in various substances in the system</p>
             <p>Daniel T. Gillespie</p>
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             <p>The Journal of Physical Chemistry 1977 81 (25), 2340-2361</p>
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            <a href="#Assumptions">What assumptions were made and why? </a>
             <p>DOI: 10.1021/j100540a008</p>
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            <p>One of our assumptions is that the length of the interval between consecutive reactions obeys an exponential distribution so that we can use the Gillespie algorithm [1] to calculate the changes in various substances in the system.</p>
 +
 
 +
            <a href="#Parameters">What kind of data was used to build/assess the model</a>
 +
             <p> (a) Expression rate of each gene (production rate of related proteins, consumption rate of each protein.<br>
 +
                (b) The computing coefficient of each reaction’s rate.
 +
            </p>
 +
           
 +
            <a href="#Guide for Experiment">How the model results affected the project design and development?</a>
 +
            <p>Our model shows the improvement effect of the system after adding the pathways expressing RDF-inhibitor and rec-inhibitor in turn, so as to provide guidance to the experimental team.</p>
 +
           
 +
            <a href="#Guide for Experiment">1.  How impressive is the modeling?  </a>
 +
             <p>Our model has successfully done a proof of concept and played a key role in guiding experimental direction and path design.</p>
 +
 
 +
            <a href="#Guide for Experiment">Did the model help the team understand a part, device, or system? </a>
 +
             <p>Of course we did</p>
 +
 
 +
 
 +
             <a href="https://2018.igem.org/Team:NAU-CHINA/Demonstrate">3.  Did the team use measurements of a part, device, or system to develop the model?</a>
 +
            <p>The experimental group verifies the feasibility of the path step by step and roughly determines the parameter dimensions of the model.
 +
             </p>
 +
            <a href="https://2018.igem.org/Team:NAU-CHINA/Auxiliary_Understanding#Part3 Our program code and instructions">4.  Does the modeling approach provide a good example for others?</a>
 +
                The ideas and methods of this model have strong promotion prospects and adaptability. The codes are showed on our wiki , you can copy and run in you Matlab convenient.<b>code</b>
 +
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             <h1>Part3 Our program code and instructions</h1>          
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             <h1>Symbol System </h1>
 +
            <table style='width: 75%; margin: 0px 14% 20px 14%;'>
 +
                <thead>
 +
                    <tr>
 +
                        <th align='center'>Symbol</th>
 +
                        <th align='center'>Meaning</th>
 +
                    </tr>
 +
                </thead>
 +
                <tbody>
 +
                    <tr>
 +
                        <td align='center'>Grec</td>
 +
                        <td align='center'>Gene of recombinase</td>
 +
                    </tr>
 +
                    <tr>
 +
                        <td align='center'>rec</td>
 +
                        <td align='center'>Recombinase [3]</td>
 +
                    </tr>
 +
                    <tr>
 +
                        <td align='center'>GsynNotch-TEV</td>
 +
                        <td align='center'>SynNotch-TEV gene</td>
 +
                    </tr>
 +
                    <tr>
 +
                        <td align='center'>synNotch</td>
 +
                        <td align='center'>Active synNotch [4] on endomembrane system. In our model synNotch is synNotch-TEV</td>
 +
                    </tr>
 +
                    <tr>
 +
                        <td align='center'>GTetR</td>
 +
                        <td align='center'>Gene of operon TetO’s repressor proteins [5]</td>
 +
                    </tr>
 +
                    <tr>
 +
                        <td align='center'>TetR</td>
 +
                        <td align='center'>TetO operon’s repressor proteins</td>
 +
                    </tr>
 +
                    <tr>
 +
                        <td align='center'>tetO</td>
 +
                        <td align='center'>Operon which can be repressed by TetR</td>
 +
                    </tr>
 +
                    <tr>
 +
                        <td align='center'>TetOR</td>
 +
                        <td align='center'>Binary complex of operon TetO and repressor proteins TetR</td>
 +
                    </tr>
 +
                    <tr>
 +
                        <td align='center'>TEV</td>
 +
                        <td align='center'>
 +
                            synNotch’s intracellular domain which is falling off by shearing,
 +
                            an enzyme can divide TetOR binary complex while separate TetR and
 +
                            degrade it [6].
 +
                        </td>
 +
                    </tr>
 +
                    <tr>
 +
                        <td align='center'>RDF</td>
 +
                        <td align='center'>
 +
                            Reverse recombination factor, which can inverse DNA sequence
 +
                            between sites and make it back to the morphology not affected by rec [7].
 +
                        </td>
 +
                    </tr>
 +
                    <tr>
 +
                        <td align='center'>Ts</td>
 +
                        <td align='center'>Target signal</td>
 +
                    </tr>
 +
                    <tr>
 +
                        <td align='center'>Gx</td>
 +
                        <td align='center'>Gene of a protein x</td>
 +
                    </tr>
 +
                    <tr>
 +
                        <td align='center'>∅</td>
 +
                        <td align='center'>Degraded material</td>
 +
                    </tr>
 +
                    <tr>
 +
                        <td align='center'>U</td>
 +
                        <td align='center'>Unconsidered substance</td>
 +
                    </tr>
 +
                </tbody>
 +
            </table>
 
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 +
        <div class="textblock">
 +
            <h1><a name="Assumptions">Assumptions</a></h1>
 +
            <p>Tips: Click the button named Aim.  </p>
 +
            <p>1. Normal protein expression is a reaction which satisfies the post-integration conditions. All reactions which satisfy post-integration conditions can be viewed as one single chemical reaction. part1 . Aim>>To simplify calculation.Model Interpretation</p>
 +
            <p>2. Different reactions in cells occur independently. Aim>>To determine when the next reaction occurs and which reaction occurs.</p>
 +
            <p>3. The length of the interval between consecutive reactions obeys an exponential distribution. Aim>>To determine when the next reaction occurs and which reaction occurs. </p>
 +
            <p>4. The degradation of protein can be viewed as linear degradation. Aim>>To simplified calculation,this model is also compatible with other methods of calculating degradation for example Michaelis-Menten equation.</p>
 +
            <p>5. The repressor effect of the protein can be described by the Hill equation. Aim>>To calculate the expression of rec. </p>
 +
 
 +
        </div>
 +
 
 +
        <div class="textblock">
 +
            <h1><a name="Parameters">Parameters</a></h1>
 +
            <table style='width: 75%; margin: 0px 14% 20px 14%;'>
 +
                <tbody>
 +
                    <tr>
 +
                        <td align='center'>c21=5;</td>
 +
                        <td align='center'> % TetR Gene expression</td>
 +
                    </tr>
 +
                    <tr>
 +
                        <td align='center'>c22=0.001;</td>
 +
                        <td align='center'>% TetR degradation</td>
 +
                    </tr>
 +
                    <tr>
 +
                        <td align='center'>c23=200;</td>
 +
                        <td align='center'>% generate dipolymer</td>
 +
                    </tr>
 +
                    <tr>
 +
                        <td align='center'>c24=0.003;  </td>
 +
                        <td align='center'>  % TEV causes decomposition of dipolymer</td>
 +
                    </tr>
 +
                    <tr>
 +
                        <td align='center'>c25=0.000005;  </td>
 +
                        <td align='center'> % self decomposition of dipolymer</td>
 +
                    </tr>
 +
                    <tr>
 +
                        <td align='center'>NTetO=5;  </td>
 +
                        <td align='center'>% Hill coefficient</td>
 +
                    </tr>
 +
                    <tr>
 +
                        <td align='center'>Swichpoint=2000;</td>
 +
                        <td align='center'>% parameter to the hill equation</td>
 +
                    </tr>
 +
                    <tr>
 +
                        <td align='center'>c31=8; </td>
 +
                        <td align='center'>% rec's Maximum gene expression rate</td>
 +
                    </tr>
 +
                    <tr>
 +
                        <td align='center'>c32=12; </td>
 +
                        <td align='center'>  % RDF-inhibitor's Maximum gene expression rate</td>
 +
                    </tr>
 +
                    <tr>
 +
                        <td align='center'> c33=0.01;    </td>
 +
                        <td align='center'> % rec degradation</td>
 +
                    </tr>
 +
                    <tr>
 +
                        <td align='center'>c34=0.01;    </td>
 +
                        <td align='center'> % rec-RDF-inhibitor degradation</td>
 +
                    </tr>
 +
                    <tr>
 +
                        <td align='center'>c35=2;</td>
 +
                        <td align='center'> % rec-inhibitor Gene expression(No rec-inhibitor can be set to 0)</td>
 +
                    </tr>
 +
                    <tr>
 +
                        <td align='center'>c36=0.1;  </td>
 +
                        <td align='center'> % rec-inhibitor in combination with rec</td>
 +
                    </tr>
 +
                    <tr>
 +
                        <td align='center'>c37=200;  </td>
 +
                        <td align='center'>  % The noise reduction reaction of rec</td>
 +
                    </tr>
 +
                    <tr>
 +
                        <td align='center'> c41=0.0000006; </td>
 +
                        <td align='center'> % rec reverse reaction</td>
 +
                    </tr>
 +
                    <tr>
 +
                        <td align='center'>c51=7;    </td>
 +
                        <td align='center'> % Turn on GENE expression downstream </td>
 +
                    </tr>
 +
                    <tr>
 +
                        <td align='center'> c52=0.01; </td>
 +
                        <td align='center'>  % RDF degradation </td>
 +
                    </tr>
 +
                    <tr>
 +
                        <td align='center'>c53=200; </td>
 +
                        <td align='center'> % rec-inhibitor in combination with rec </td>
 +
                    </tr>
 +
                    <tr>
 +
                        <td align='center'> c61=0.0000005;  </td>
 +
                        <td align='center'> % rec-RDF reverse reaction</td>
 +
                    </tr>
 +
                </tbody>
 +
            </table>
 +
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 +
 
 +
 
 +
        <div class="textblock">
 +
            <h1><a name="Guide for Experiment">Guide for Experiment</a></h1>
 +
            <p>1. By improving the cell culture environment, the noise in signal conversion process could be reduced by more than 10 percent. <b>Model Interpretation part4 </b></p>
 +
            <p>2. Our model shows the improvement effect of the system after adding the pathways expressing RDF-inhibitor and rec-inhibitor in turn, so as to provide guidance to the experimental team.<b> Model Interpretation part5.</b></p>
 +
            <p> 3. We determined the design parameters to simulate the ideal results and verify the feasibility of the experimental design. <b>Model Interpretation part6. </b></p>
 +
 
 +
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 +
 
 +
 
 +
        <div class="textblock">
 +
            <h1>References</h1>
 +
            <p>[1] Gillespie, D. T. Exact Stochastic Simulation of couple chemical reactions. J. Phys. Chem. 81, 2340–2361 (1977).</p>
 +
            <p>[2] Ault, S. & Holmgreen, E. Dynamics of the Brusselator. Math 715 Proj. (Autumn 2002) 1–17 (2003). doi:10.1103/PhysRevE.61.2361</p>
 +
            <p> [3]    Stark WM. 2014. The serine recombinase. MicrobiolSpectrum2 (6):MDNA3-0046-2014. </p>
 +
            <p>[4] Morsut, L. et al. Engineering Customized Cell Sensing and Response Behaviors Using Synthetic Notch Receptors. Cell 164, 780–791 (2016).</p>
 +
            <p>[5] Ramos, J. L. et al. The TetR Family of Transcriptional Repressors The TetR Family of Transcriptional Repressors. Microbiol. Mol. Biol. Rev. 69, 326–356 (2005).</p>
 +
            <p>[6] Phan, J. et al. Structural basis for the substrate specificity of tobacco etch virus protease. J. Biol. Chem. 277, 50564–50572 (2002).</p>
 +
            <p>[7] Olorunniji, F. J. et al. Control of serine integrase recombination directionality by fusion with the directionality factor. Nucleic Acids Res. 45, 8635–8645 (2017).</p>
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Revision as of 22:11, 17 October 2018

Template:2018_NAU-CHINA

header
Engagement

Model

Overview

Introduction

We propose post-integration conditions, rationally simplify the complex situation, and split the whole process into a series of chemical reactions. Assuming that intervals between two reactions obey exponential distribution, we use the Gillespie algorithm [1] to calculate the changes in various substances in the system with reference to the Dynamics of the Brusselator [2]. The ideas and methods of this model have strong promotion prospects and adaptability. Our model demonstrates the necessity of using the recombinase(rec) system,the improvement effect of the system after adding the pathways expressing RDF-inhibitor and rec-inhibitor in turn, and the robustness of the model .The experimental team verified some assumptions and results of the model and selected materials according to the parameters of the model.

For judging handbook

What kind of modeling is being done and what information it will provide?

We use the Gillespie algorithm to calculate the changes in various substances in the system

What assumptions were made and why?

One of our assumptions is that the length of the interval between consecutive reactions obeys an exponential distribution so that we can use the Gillespie algorithm [1] to calculate the changes in various substances in the system.

What kind of data was used to build/assess the model

(a) Expression rate of each gene (production rate of related proteins, consumption rate of each protein.
(b) The computing coefficient of each reaction’s rate.

How the model results affected the project design and development?

Our model shows the improvement effect of the system after adding the pathways expressing RDF-inhibitor and rec-inhibitor in turn, so as to provide guidance to the experimental team.

1. How impressive is the modeling?

Our model has successfully done a proof of concept and played a key role in guiding experimental direction and path design.

Did the model help the team understand a part, device, or system?

Of course we did

3. Did the team use measurements of a part, device, or system to develop the model?

The experimental group verifies the feasibility of the path step by step and roughly determines the parameter dimensions of the model.

4. Does the modeling approach provide a good example for others? The ideas and methods of this model have strong promotion prospects and adaptability. The codes are showed on our wiki , you can copy and run in you Matlab convenient.code

Symbol System

Symbol Meaning
Grec Gene of recombinase
rec Recombinase [3]
GsynNotch-TEV SynNotch-TEV gene
synNotch Active synNotch [4] on endomembrane system. In our model synNotch is synNotch-TEV
GTetR Gene of operon TetO’s repressor proteins [5]
TetR TetO operon’s repressor proteins
tetO Operon which can be repressed by TetR
TetOR Binary complex of operon TetO and repressor proteins TetR
TEV synNotch’s intracellular domain which is falling off by shearing, an enzyme can divide TetOR binary complex while separate TetR and degrade it [6].
RDF Reverse recombination factor, which can inverse DNA sequence between sites and make it back to the morphology not affected by rec [7].
Ts Target signal
Gx Gene of a protein x
Degraded material
U Unconsidered substance

Assumptions

Tips: Click the button named Aim.

1. Normal protein expression is a reaction which satisfies the post-integration conditions. All reactions which satisfy post-integration conditions can be viewed as one single chemical reaction. part1 . Aim>>To simplify calculation.Model Interpretation

2. Different reactions in cells occur independently. Aim>>To determine when the next reaction occurs and which reaction occurs.

3. The length of the interval between consecutive reactions obeys an exponential distribution. Aim>>To determine when the next reaction occurs and which reaction occurs.

4. The degradation of protein can be viewed as linear degradation. Aim>>To simplified calculation,this model is also compatible with other methods of calculating degradation for example Michaelis-Menten equation.

5. The repressor effect of the protein can be described by the Hill equation. Aim>>To calculate the expression of rec.

Parameters

c21=5; % TetR Gene expression
c22=0.001; % TetR degradation
c23=200; % generate dipolymer
c24=0.003; % TEV causes decomposition of dipolymer
c25=0.000005; % self decomposition of dipolymer
NTetO=5; % Hill coefficient
Swichpoint=2000; % parameter to the hill equation
c31=8; % rec's Maximum gene expression rate
c32=12; % RDF-inhibitor's Maximum gene expression rate
c33=0.01; % rec degradation
c34=0.01; % rec-RDF-inhibitor degradation
c35=2; % rec-inhibitor Gene expression(No rec-inhibitor can be set to 0)
c36=0.1; % rec-inhibitor in combination with rec
c37=200; % The noise reduction reaction of rec
c41=0.0000006; % rec reverse reaction
c51=7; % Turn on GENE expression downstream
c52=0.01; % RDF degradation
c53=200; % rec-inhibitor in combination with rec
c61=0.0000005; % rec-RDF reverse reaction

Guide for Experiment

1. By improving the cell culture environment, the noise in signal conversion process could be reduced by more than 10 percent. Model Interpretation part4

2. Our model shows the improvement effect of the system after adding the pathways expressing RDF-inhibitor and rec-inhibitor in turn, so as to provide guidance to the experimental team. Model Interpretation part5.

3. We determined the design parameters to simulate the ideal results and verify the feasibility of the experimental design. Model Interpretation part6.

References

[1] Gillespie, D. T. Exact Stochastic Simulation of couple chemical reactions. J. Phys. Chem. 81, 2340–2361 (1977).

[2] Ault, S. & Holmgreen, E. Dynamics of the Brusselator. Math 715 Proj. (Autumn 2002) 1–17 (2003). doi:10.1103/PhysRevE.61.2361

[3] Stark WM. 2014. The serine recombinase. MicrobiolSpectrum2 (6):MDNA3-0046-2014.

[4] Morsut, L. et al. Engineering Customized Cell Sensing and Response Behaviors Using Synthetic Notch Receptors. Cell 164, 780–791 (2016).

[5] Ramos, J. L. et al. The TetR Family of Transcriptional Repressors The TetR Family of Transcriptional Repressors. Microbiol. Mol. Biol. Rev. 69, 326–356 (2005).

[6] Phan, J. et al. Structural basis for the substrate specificity of tobacco etch virus protease. J. Biol. Chem. 277, 50564–50572 (2002).

[7] Olorunniji, F. J. et al. Control of serine integrase recombination directionality by fusion with the directionality factor. Nucleic Acids Res. 45, 8635–8645 (2017).

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