Team:Peking/ProjectApplication

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         <li><a href="#8008">Introduction</a></li>
         <li><a href="#8008">Introduction</a></li>
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         <li><a href="#8009">Method</a></li>
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         <li><a href="#8009">Methods</a></li>
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          <h2 id="8008">Introduction</h2>
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          <h2 id="8008">Introduction</h2>
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         <p> In order to the estimate the effect of killing and improve the application method, other than varied tests in laboratory, we also develop a macro-level model to examine whether our <i>E. coli</i> will work well considering spatial distribution and diffusion. We described interaction and diffusion of elements in the fresh water system by using Partial Differential Equations (PDEs). Even though we don’t know the analytical expression of interaction of elements in water, we can propose a possible interaction function, and analyze its spatial properties, in order to find an optimized way to pour bacterium solution.  </p>
+
         <p> In order to estimate the effect of killing and improve the application methods, except for varied tests in laboratory, we also developed a macro-level model to examine whether our <i>E. coli</i> will take effect considering spatial distribution and diffusion. We described interaction and diffusion of elements in the fresh water system by using Partial Differential Equations (PDEs). Even though we didn’t know the analytical expression of interaction of elements in water, we can propose a possible interaction function, and analyze its spatial properties, in order to find an optimized way to pour bacteria solution.  </p>
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     <h2 id="8009">Method</h2>
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     <h2 id="8009">Methods</h2>
     <p> Finite-difference methods are applied in solving PDEs in this model.</p>
     <p> Finite-difference methods are applied in solving PDEs in this model.</p>
         <h3 id="80091">Diffuision</h3>
         <h3 id="80091">Diffuision</h3>
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         <p>Differentials to space coordinates are given by <i><b><a href="http://en.wikipedia.org/wiki/Fick%27s_laws_of_diffusion" target="_blank">Fick Law</a></b></i>. The length of a time step is approximated to &Delta;t = 1<i>min</i>, and the discretization of space coordinates is approximated to &Delta;s = 1<i>dm</i>(s = x, y, z), considering the scale of boundary is 10<sup>2</sup><i>m</i> and the time scale is 10<sup>1</sup> days.</p>
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         <p>Differentials to space coordinates are given by <i><b><a href="http://en.wikipedia.org/wiki/Fick%27s_laws_of_diffusion" target="_blank">Fick Law</a></b></i>. The length of a time step is approximated to &Delta;t = 1<i>min</i>, and the discretization of space coordinates is approximated to &Delta;s = 1<i>dm</i> (s = x, y, z), considering the scale of boundary is 10<sup>2</sup><i>m</i> and the time scale is 10<sup>1</sup> days.</p>
         <h3 id="80092">Interaction</h3>
         <h3 id="80092">Interaction</h3>
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         <p><b></b><i>A, E, L</i></b> indicate the concentration of algae, our programming <i>E. coli</i>, lysozym which kills algae. We also introduce a variable which describes the organic nutrition released by cracked algae(indicated by <b><i>N</i></b>), which contributes to respiration of  <i>E. coli</i>. Interacitons between them are given below.</p>
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         <p><b><i>A, E, L</i></b> indicate the concentration of cyanobacteria, our programmed <i>E. coli</i>, lysozyme which kills cyanobacteria. We also introduced a variable which described the organic nutrition released by cracked cyanobacteria (indicated by <b><i>N</i></b>), which contributed to respiration of  <i>E. coli</i>. Interacitons between them are given below.</p>
         <figure><img src="https://static.igem.org/mediawiki/2014/d/db/Peking2014ncj_PAequ.png" /></figure>
         <figure><img src="https://static.igem.org/mediawiki/2014/d/db/Peking2014ncj_PAequ.png" /></figure>
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         <p>The first term in <b>Equ(1)</b> describes the growth of algae by logistic model, in which K1 indicate the growth rate of algae and k2 indicate the steady value. The second term means the Killing effect by lysozyme. <b>Equ(2)</b> describes the accumulation and consumption of organic nutrition. <b>Equ(3)</b> describes the reproduction and natural mortality of our E. coli and <b>Equ(4)</b> describes secretion and reduction of lysozyme</p>
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         <p>The first term in <b>Equ(1)</b> describes the growth of cyanobacteria by logistic model, in which K1 indicate the growth rate of cyanobacteria and k2 indicate the steady value. The second term means the killing effect by lysozyme. <b>Equ(2)</b> describes the accumulation and consumption of organic nutrition. <b>Equ(3)</b> describes the reproduction and natural mortality of our E. coli and <b>Equ(4)</b> describes secretion and reduction of lysozyme.</p>
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         <p>There are several factors which are not considered in equations above such as nutrition accumulation by algae which dies naturally, degradation of lysozyme, evaluation by binding part and so on, because they are either too small compared with other items, or they are irrelevant to the issue that we care. As this model is focused on the application in macro-scale water system, accurate parameters are not required meanwhile not available, considering the form of equations could not be proved. So some parameters are given by speculation to satisfy our expactation</p>
+
         <p>There are several factors which are not considered in equations above such as nutrition accumulation by cyanobacteria which dies naturally, degradation of lysozyme, evaluation by binding part and so on, because they are either too small compared with other items, or they are irrelevant to the issue that we care. As this model is focused on the application in macro-scale water system, accurate parameters are not required meanwhile not available, considering the form of equations could not be proved. So some parameters were given by speculation to satisfy our expactation.</p>
          
          
         <h3 id="80093">Spatial Analysis</h3>
         <h3 id="80093">Spatial Analysis</h3>
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         <p>We control the total volume of bacteriuma solution, and we tried several basic mode of pouring: at one point, at several points, along a line or evenly on the whole surface. Then we measured the time scale of algae elimination. From this, we can find out if mode of pouring</p>
+
         <p>We controlled the total volume of bacteria solution, and we tried several basic mode of pouring: at one point, at several points, along a line or evenly on the whole surface. Then we measured the time scale of cyanobacteria elimination. From this, we could find out if mode of pouring</p>
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     <h2 id="8010">Result</h2>
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     <h2 id="8010">Results</h2>
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         <h3 id="80101">Parameter manipulation</h3>
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         <h3 id="80101">Parameters manipulation</h3>
         <p>Ignoring the diffusion, the PDEs were converted to Ordinary Differential Equations (ODE).</p>
         <p>Ignoring the diffusion, the PDEs were converted to Ordinary Differential Equations (ODE).</p>
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         <p>Speculatively the equations have two typical form of solution, indicating the success and failure of the project. For there is a positive feedback mechanic by introducing organic nutrition, oscillatory solution could not exist.</p>
+
         <p>Speculatively the equations have two typical forms of solution, indicating the success and failure of the project. For there is a positive feedback mechanism by introducing organic nutrition, oscillatory solution could not exist.</p>
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         <p>Through the test, we noticed that the reasonable type of the solution is the only “success” (<b>Fig. 1</b>) regardless of reasonable variation of <b>K<sub>9</sub></b> and <b>K<sub>5</sub></b>. The other paremeters are not the crucial factor of the type of the solution as the magnitude of order are estimable, for example, <b>K<sub>6</sub></b>, the growth rate of <i>E. coli.</i></p>  
+
         <p>Through the test, we noticed that the reasonable type of the solution is the only "success" (<b>Fig. 1</b>) regardless of reasonable variation of <b>K<sub>9</sub></b> and <b>K<sub>5</sub></b>. The other parameters were not the crucial factor of the type of the solution as the magnitude of order are estimable, for example, <b>K<sub>6</sub></b>, the growth rate of <i>E. coli.</i></p>  
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         <figure><img href="https://static.igem.org/mediawiki/2014/3/39/Peking2014ncj_PAfig1.png" />
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         <figure><img src="https://static.igem.org/mediawiki/2014/3/39/Peking2014ncj_PAfig1.png" alt="Figure.1"/>
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         <figcaption> <b>Figure. 1</b> <b>(A)</b> <b>K<sub>9</sub></b> indicates the number of lysozymes consumed to crack an algae. In this figure, <b>K<sub>9</sub></b> equals to 10<sup>3</sup>, 10<sup>4</sup>,10<sup>5</sup>. And we can see that the solution keeps the same type. <b>(B)</b> <b>K<sub>5</sub></b> indicates utilization of the nutrition from cracked algae by <i>E. coli</i>. We tested the condition  where <b>K<sub>5</sub></b> equaling to 1.5&times;10<sup>-2</sup>,1.5&times;10<sup>0</sup>, 1.5&times;10<sup>2</sup>, and the solution also keeps the same type.</figcaption></figure>
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         <figcaption> <b>Figure. 1</b> <b>(A)</b> <b>K<sub>9</sub></b> indicates the number of lysozymes consumed to crack an cyanobacteria. In this figure, <b>K<sub>9</sub></b> equals to 10<sup>3</sup>, 10<sup>4</sup>,10<sup>5</sup>. And we can see that the solution keeps the same type. <b>(B)</b> <b>K<sub>5</sub></b> indicates utilization of the nutrition from cracked cyanobacteria by <i>E. coli</i>. We tested the condition  where <b>K<sub>5</sub></b> equaling to 1.5&times;10<sup>-2</sup>,1.5&times;10<sup>0</sup>, 1.5&times;10<sup>2</sup>, and the solution also keeps the same type.</figcaption></figure>
 +
 
 +
<h3 id="80102">Spatial analysis</h3>
 +
      <p>We set a 11m&times;11m&times;10m test space with well-distributed cyanobacteria. Then we tested 4 basic modes of pouring the bacteria solution. At the center point of the surface <b>(Fig. 2A)</b>, at four points near the border <b>(Fig. 2B)</b>, along with a line <b>(Fig. 2C)</b> and on the whole surface <b>(Fig. 2D)</b>.</p>
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      <figure>
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        <img src="https://static.igem.org/mediawiki/2014/7/7d/Peking2014ncj_AB.png" />
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        <img src="https://static.igem.org/mediawiki/2014/0/04/Peking2014ncj_fig2A.gif" />
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        <img src="https://static.igem.org/mediawiki/2014/2/2f/Peking2014ncj_Fig2B.gif" />
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        <img src="https://static.igem.org/mediawiki/2014/c/ce/Peking2014ncj_CD.png" />
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        <img src="https://static.igem.org/mediawiki/2014/c/c9/Peking2014ncj_Fig2C.gif" />
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        <img src="https://static.igem.org/mediawiki/2014/8/88/Peking2014ncj_Fig2D.gif" />
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        <figcaption><b>Figure 2.</b> The colors from red to blue indicate the concentration of cyanobacteria from a high level to zero. The time scale of the whole procedure is 12h.</figcaption> </figure>
 +
 
 +
    <p>We found that the time scales of cyanobacteria elimination were almost the same in the four conditions. We thought it was because of the positive feedback mechanism by introducing the organic nutrition and limited border. Although we didn't get instructional results from this test, we would get more if correcting the form of interaction and border conditions. We believed that this model would contribute more to our project in application.</p>
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Latest revision as of 03:05, 18 October 2014

Introduction

In order to estimate the effect of killing and improve the application methods, except for varied tests in laboratory, we also developed a macro-level model to examine whether our E. coli will take effect considering spatial distribution and diffusion. We described interaction and diffusion of elements in the fresh water system by using Partial Differential Equations (PDEs). Even though we didn’t know the analytical expression of interaction of elements in water, we can propose a possible interaction function, and analyze its spatial properties, in order to find an optimized way to pour bacteria solution.

Methods

Finite-difference methods are applied in solving PDEs in this model.

Diffuision

Differentials to space coordinates are given by Fick Law. The length of a time step is approximated to Δt = 1min, and the discretization of space coordinates is approximated to Δs = 1dm (s = x, y, z), considering the scale of boundary is 102m and the time scale is 101 days.

Interaction

A, E, L indicate the concentration of cyanobacteria, our programmed E. coli, lysozyme which kills cyanobacteria. We also introduced a variable which described the organic nutrition released by cracked cyanobacteria (indicated by N), which contributed to respiration of E. coli. Interacitons between them are given below.

The first term in Equ(1) describes the growth of cyanobacteria by logistic model, in which K1 indicate the growth rate of cyanobacteria and k2 indicate the steady value. The second term means the killing effect by lysozyme. Equ(2) describes the accumulation and consumption of organic nutrition. Equ(3) describes the reproduction and natural mortality of our E. coli and Equ(4) describes secretion and reduction of lysozyme.

There are several factors which are not considered in equations above such as nutrition accumulation by cyanobacteria which dies naturally, degradation of lysozyme, evaluation by binding part and so on, because they are either too small compared with other items, or they are irrelevant to the issue that we care. As this model is focused on the application in macro-scale water system, accurate parameters are not required meanwhile not available, considering the form of equations could not be proved. So some parameters were given by speculation to satisfy our expactation.

Spatial Analysis

We controlled the total volume of bacteria solution, and we tried several basic mode of pouring: at one point, at several points, along a line or evenly on the whole surface. Then we measured the time scale of cyanobacteria elimination. From this, we could find out if mode of pouring

Results

Parameters manipulation

Ignoring the diffusion, the PDEs were converted to Ordinary Differential Equations (ODE).

Speculatively the equations have two typical forms of solution, indicating the success and failure of the project. For there is a positive feedback mechanism by introducing organic nutrition, oscillatory solution could not exist.

Through the test, we noticed that the reasonable type of the solution is the only "success" (Fig. 1) regardless of reasonable variation of K9 and K5. The other parameters were not the crucial factor of the type of the solution as the magnitude of order are estimable, for example, K6, the growth rate of E. coli.

Figure.1
Figure. 1 (A) K9 indicates the number of lysozymes consumed to crack an cyanobacteria. In this figure, K9 equals to 103, 104,105. And we can see that the solution keeps the same type. (B) K5 indicates utilization of the nutrition from cracked cyanobacteria by E. coli. We tested the condition where K5 equaling to 1.5×10-2,1.5×100, 1.5×102, and the solution also keeps the same type.

Spatial analysis

We set a 11m×11m×10m test space with well-distributed cyanobacteria. Then we tested 4 basic modes of pouring the bacteria solution. At the center point of the surface (Fig. 2A), at four points near the border (Fig. 2B), along with a line (Fig. 2C) and on the whole surface (Fig. 2D).

Figure 2. The colors from red to blue indicate the concentration of cyanobacteria from a high level to zero. The time scale of the whole procedure is 12h.

We found that the time scales of cyanobacteria elimination were almost the same in the four conditions. We thought it was because of the positive feedback mechanism by introducing the organic nutrition and limited border. Although we didn't get instructional results from this test, we would get more if correcting the form of interaction and border conditions. We believed that this model would contribute more to our project in application.