Difference between revisions of "Team:ETH Zurich"

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    <h1 class="headline">Modelling the Behavior of CATE inside Tumor</h1>
 
  
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    <section class="first">
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<div class="banner">
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        <!--<h1>What</h1>-->
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<figure class="banner" id="banner">
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        <p><em>We developed a model to gauge the behavior of our sensing circuit in the real life conditions of solid tumor colonization.</em></p>
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    <img src="https://static.igem.org/mediawiki/2017/c/c3/T--ETH_Zurich--Banner.png" alt="CATE" />
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    </section>
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</figure>
  
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    <section>
 
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        <h1>Model Overview</h1>
 
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        <p>This section presents a brief overview of the COMSOL model.</p>
 
  
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        <h2>Geometry  <button><a href="https://2017.igem.org/Team:ETH_Zurich/Model/In_Vivo_Detailed#InVivo_Geometry" class="more">Learn More</a></button> </h2>
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<figure class="scroll">
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        <p class="description">As mentioned in <a href="https://2017.igem.org/Team:ETH_Zurich/Model/Environment_Sensing/system_specifications">system specifications</a>, the tumour has been chosen as a solid sphere of radius 20mm and the bactierial colonization pattern as a homogenous distribution in a spherical shell-shaped 0.5mm thick layer in the tumour at a distance of 10mm from the centre of the tumor, as shown in Figure 1. For more details go to the <a href="https://2017.igem.org/Team:ETH_Zurich/Model/In_Vivo_Detailed">detailed description</a> of the model.</p>
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<a class="scroll-down-button" href="#scrollstart">
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    <img src="https://static.igem.org/mediawiki/2017/1/14/T--ETH_Zurich--Scroll.png">
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</a>
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<figure>
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</div>
  
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        <figure class="fig-nonfloat" style="max-width: 600px;">
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<section id="scrollstart"></section>
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            <img src="https://static.igem.org/mediawiki/2017/3/36/T--ETH_Zurich--tumor_geometry.png"
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                alt="Geometry of tumor and bacterial colony" />
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            <figcaption>Figure 1: Geometry of the tumor and bacteria colony (green area: colonized by <span class="bacterium">E. coli</span> Nissle)</figcaption>
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−
        </figure>
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−
        <h2>Equations  <button><a href="https://2017.igem.org/Team:ETH_Zurich/Model/In_Vivo_Detailed#InVivo_Equations" class="more">Details</a></button> </h2>
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<section id="start" class="step">
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        <p class="description">
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    <div class="why">
−
            Transport of Diluted Species physics was used in COMSOL to integrate diffusion into our model. The partial differential equation for diffusion of a species <em>C</em> with reaction source rate <em>R<sub>C</sub></em> is <span class="math">\[\frac{\partial \text{[C]}}{\partial t} + \nabla \cdot (-D_{\text{C}} \nabla \text{[C]})= R_{\text{C}}\]</span>. The reaction rates of the species depends on the domain – tumor (no production and only extracellular degradation) or bacterial layer (production and intracellular degradation). Read <a href="https://2017.igem.org/Team:ETH_Zurich/Model/In_Vivo_Detailed">here</a> about the details of the domain-wise reaction rates for each species (AHL, LuxI and Azurin) and equations used.
+
    <h1>WHY</h1>
−
        </p>
+
        <p>Cancer kills over 8 million people every year. That's the entire population of Switzerland!</p>
 +
        <p>We need more specific therapies because current approaches result in many side-effects. That's why we invented <span title="Came close to being FUSBa (<yyyeaah no ;))">CATE</span>, the first all-in-one living cancer therapeutic with an integrated two-step safety mechanism.
 +
        <p>A living cure to a living disease!</p>
 +
        <br>
 +
        <p><button><a href="https://2017.igem.org/Team:ETH_Zurich/Description" class="more"> BACKGROUND</a></button></p>
 +
    </div>
 +
</section>
  
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        <h2>Parameters  <button><a href="https://2017.igem.org/Team:ETH_Zurich/Model/In_Vivo_Detailed#InVivo_Parameters" class="more">Get Values</a></button> </h2>
 
−
        <p class="description">The parameters that were used in the COMSOL model were obtained partly from literature, partly from characterizations of previous iGEM teams and finally the most important ones were estimated by fitting our experimental data and tuning the fitted-results in the context of the intended applciation, as explained in detail by the <a href="https://2017.igem.org/Team:ETH_Zurich/Model/Environment_Sensing/parameter_space">Functional Parameter Search</a>. Check out <a href="https://2017.igem.org/Team:ETH_Zurich/Model/In_Vivo_Detailed">details about the model</a> to read more about the different parameter values used.</p>
 
  
−
        <p>For more details about the model go to the <a href="https://2017.igem.org/Team:ETH_Zurich/Model/In_Vivo_Detailed">detailed description</a> and <a href="https://2017.igem.org/Team:ETH_Zurich/Model/Environment_Sensing/parameter_space">Functional Parameter Search</a>.</p>
 
−
    </section>
 
  
−
    <section>
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<section id="second" class="step">
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        <h1>Strengths</h1>
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    <div class="vision">
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        <!--<p>The COMSOL model helped us to extend our MATLAB model in the following ways:</p>-->
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<figure class="EcN">
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        <h2>We could simulate for a geometry of the system closer to the real-life tumor conditions <button><a href="https://2017.igem.org/Team:ETH_Zurich/Model/In_Vivo_Detailed#InVivo_Treatment" class="more">Simulating the Treatment</a></button></h2>
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        <img src="https://static.igem.org/mediawiki/2017/0/02/T--ETH_Zurich--Ec.png">
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        <p class="description">Since it was not practically feasible to conduct experiments of bacterial colonization inside tumors, we simulated the bacterial colonization in a thin spherical layer inside a solid tumor considering the simplifications and assumptions as mentioned in the <a href="https://2017.igem.org/Team:ETH_Zurich/Model/Environment_Sensing/system_specifications">system specifications</a>. This helped us to test our tumour sensing AND-Gate switch functionality in all the possible real-life scenarios that CATE might encounter in context of the intended application.</p>
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</figure>
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        <h2>Exact diffusion physics of AHL was included witout any simplifications <button><a href="https://2017.igem.org/Team:ETH_Zurich/Model/In_Vivo_Detailed#InVivo_AND_Switch" class="more">AND-Gate Operation</a></button></h2>
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<br>
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         <p class="description">Our <a href="https://2017.igem.org/Team:ETH_Zurich/Model/Environment_Sensing/system_specifications">MATLAB model</a> uses a simplified AHL diffusion model with the assumption of negligible degradation inside the layer and and not taking into consideration the diffusion of AHL far from the source. Extending the diffusion physics ordinary differential equations into partial differential equations using the COMSOL model helped us gauge and verify the behavior of our tumor-sensing circuit in more real-life conditions pertaining to the intended application context of a solid spherical tumor. Using the results obtained from our simulations, we could check the behavior of the <em>AND Gate Switching</em> in different conditions of d<sub>cell</sub> and lactate.</p>
+
<br>
−
         <h2>Diffusion physics of Azurin was included to simulate the effect of lysis <button><a href="https://2017.igem.org/Team:ETH_Zurich/Model/In_Vivo_Detailed#InVivo_Killing" class="more">Killing Area Estimation</a></button></h2>
+
    <h1>VISION</h1>
−
         <p class="description">To simulate the effect of lysis, our COMSOL model stops the production of Azurin and starts its diffusion when temperature reaches 42&deg;C. This simulates the effect of increase in temperature with FUS to cause cell lysis. Using data obtained from such a simulation, we could also find the temporal-maximum concentrations of Azurin at each point in the tumor, effectively helping us to estimate the killing area and the time-scale of the treatment. </p>
+
         <p>To tackle the challenge of treating cancer, we decided to look beyond classical approaches and from the point of view of a synthetic biologist. </p>
−
         <h2>Simulation of different colonization patterns <button><a href="https://2017.igem.org/Team:ETH_Zurich/Model/In_Vivo_Detailed#InVivo_Patterns" class="more">Colonization Patterns</a></button></h2>
+
         <p>Our search led us to the concept of bacterial cancer therapy.</p>
−
        <p class="description">Using our model, we also tried a few other colonization patterns to show our system works as expected inside a tumor while stays dormant in healthy tissue. We simulated the following patterns:</p>
+
         <br>
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        <ul>
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         <p><button><a href="https://2017.igem.org/Team:ETH_Zurich/Description" class="more">STORY OF CATE</a></button></p>
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            <li>
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    </div>
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                Homogeneous distribution in a Single spherical-shell-shaped layer in Tumor <br>
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−
                <p class="description"></p>
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            </li>
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−
            <li>
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−
                Heterogeneous distribution in a Single spherical-shell-shaped layer in Tumor<br>
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                <p class="description"></p>
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            </li>
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−
            <li>
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                Heterogeneous distribution in Double spherical-shell-shaped layer in Tumor<br>
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                <p class="description"></p>
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            </li>
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            <li>
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                Homogeneous distribution in Healthy tissue<br>
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                <p class="description"></p>
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−
            </li>
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−
        </ul>
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−
    </section>
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</section>
  
−
    <section>
 
−
        <h1>Limitations</h1>
 
−
        <p>Our model has some limitations. We do not model protein E production and cell lysis caused by it. Instead lysis is just simulated in effect as the end of production of AHL and Azurin and start of diffusion of Azurin. Moreover, a step signal is used as a trigger for the lysis. As mentioned in the <a href="https://2017.igem.org/Team:ETH_Zurich/Model/In_Vivo_Detailed">parameters description</a>, Azurin production is taken to be 10 times proportional to LuxI production. Also, killing mechanism of Azurin has not been modelled since that was not necessary to demonstrate the working of our project CATE in the scope of iGEM. <!--Moreover, Azurin is not potent enough to kill the tumor but CATE allows it to be replaced with any powerful cytotoxic agent.--></p>
 
−
    </section>
 
  
−
     <section>
+
 
−
         <h1>Tools used</h1>
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<div class="space">
−
         <ul>
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  &nbsp;
−
            <li>
+
</div>
−
                <a href="https://www.comsol.com/">COMSOL Multiphysics</a> 5.2a by COMSOL Inc.
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−
                <p class="description"></p>
+
 
−
            </li>
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<section id="third" class="step">
−
            <li>
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     <div>
−
                <a href="https://www.mathworks.com/products/matlab.html">MATLAB</a> R2016b by <a href="https://www.mathworks.com/">MathWorks</a>
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        <p>CATE consists of the non-pathogenic bacterium <span class="bacterium">E. coli</span> Nissle that has the intrinsic ability to home preferentially in tumors.</p>
−
                <p class="description"></p>
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        <p>It features two safety checkpoint mechanisms to ensure only tumor cells are damaged.</p>
−
            </li>
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        <p>CATE is administered intravenously, travels through the blood and colonizes tumors. When enough bacteria have accumulated in the tumor, they make themselves visible and
−
         </ul>
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      start preparing the cytotoxic payload.</p>
−
     </section>
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        <p> After imaging the tumor with MRI, the doctor can then activate the release of the cancer-killing payload. </p>
 +
        <br>
 +
        <p><button><a href="https://2017.igem.org/Team:ETH_Zurich/Applied_Design" class="more">CATE IN ACTION</a></button></p>
 +
    </div>
 +
 
 +
 
 +
<figure class="process">
 +
  <img src="https://static.igem.org/mediawiki/2017/c/cf/T--ETH_Zurich--process.png">
 +
</figure>
 +
</section>
 +
 
 +
<div class="space">
 +
  &nbsp;
 +
</div>
 +
 
 +
<section id="fourth" class="step">
 +
<div class="circuit">
 +
<figure class="andgate">
 +
  <img src="https://static.igem.org/mediawiki/2017/8/8c/T--ETH_Zurich--ANDgate.png">
 +
</figure>
 +
    <div>
 +
         <p>To achieve all these novel functions, we designed a genetic circuit that is distributed over two synthetic DNA sequences.</p>
 +
         <p> All functions were tested and optimized to make the resulting circuit as safe and well-characterized as possible.</p>
 +
        <br>
 +
      <p><button><a href="https://2017.igem.org/Team:ETH_Zurich/Circuit" class="more">Circuit</a></button></p>
 +
    </div>
 +
</section>
 +
 
 +
 
 +
<section id="fifth" class="step">
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<div class="drylab">
 +
<figure class="drylab">
 +
  <img src="https://static.igem.org/mediawiki/2017/0/0b/T--ETH_Zurich--dry_lab.png">
 +
</figure>
 +
<br>
 +
<h1>ENGINEERING</h1>
 +
        <p>We increased the understanding of the system's underlying mathematics by simulating its behavior with our models.</p><p> The models were then used to define important questions to clarify in experiments and develop efficient experimental and genetic design strategies.</p>
 +
        <br>
 +
        <p><button><a href="https://2017.igem.org/Team:ETH_Zurich/Dry_Lab" class="more">Dry Lab</a></button></p>
 +
  </div>
 +
</section>
 +
 
 +
 
 +
<section>
 +
    <div class="wetlab">
 +
<figure class="wetlab">
 +
  <img src="https://static.igem.org/mediawiki/2017/9/95/T--ETH_Zurich--wetlab.png">
 +
</figure>
 +
<br>
 +
        <p>Experimentally, we collected data to support and refine our models and to show that our system works.</p>
 +
        <br>
 +
        <p><button><a href="https://2017.igem.org/Team:ETH_Zurich/Experiments" class="more">Wet Lab</a></button></p>
 +
    </div>
 +
</section>
 +
 
 +
 
 +
<section>
 +
    <div class="goals">
 +
<figure class="goals">
 +
    <img src="https://static.igem.org/mediawiki/2017/8/83/T--ETH_Zurich--achievementslanding.png">
 +
</figure>
 +
    <h1>ACHIEVEMENTS</h1>
 +
        <p>We could experimentally confirm the predictions of the models. After testing every function individually, we combined them one after the other in milestone experiments to show the system in action.</p> <p> We created and characterized new BioBrick parts as a contribution for the synthetic biology community.</p>
 +
        <br>
 +
        <p><button><a href="https://2017.igem.org/Team:ETH_Zurich/Results" class="more">Achievements</a></button></p>
 +
    </div>
 +
</section>
 +
 
 +
 
 +
<section>
 +
  <div class="HP">
 +
    <h1>HUMAN PRACTICES</h1>
 +
<figure class="HP">
 +
    <img src="https://static.igem.org/mediawiki/2017/4/4a/T--ETH_Zurich--HPlanding.png">
 +
</figure>
 +
        <p>We went beyond the lab and reached out to experts to better understand current technological and safety issues in order to enhance the design of our project.</p><p> Further, we         
 +
        introduced our project and the field of synthetic biology to the general public and together explored issues related to safety, ethics and sustainability.</p>
 +
        <br>
 +
        <p><button><https://2017.igem.org/Team:ETH_Zurich/Human_Practices" class="more">Human Practices</a></button></p>
 +
    </div>
 +
</section>
 +
 
 +
 
 +
<section>
 +
    <div class="team">
 +
<figure class="team">
 +
    <img src="https://static.igem.org/mediawiki/2017/e/ec/T--ETH_Zurich--teamlanding.png">
 +
</figure>
 +
    <h1>TEAM</h1>
 +
         <p>We are an interdisciplinary team of eight master students of ETH Zürich who compete in the iGEM championship against hundreds of other teams from all over the world.</p>
 +
        <br>
 +
        <p><button><a href="https://2017.igem.org/Team:ETH_Zurich/Members" class="more">Team</a></button></p>
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     </div>
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</section>
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Revision as of 07:52, 1 November 2017

WHY

Cancer kills over 8 million people every year. That's the entire population of Switzerland!

We need more specific therapies because current approaches result in many side-effects. That's why we invented CATE, the first all-in-one living cancer therapeutic with an integrated two-step safety mechanism.

A living cure to a living disease!




VISION

To tackle the challenge of treating cancer, we decided to look beyond classical approaches and from the point of view of a synthetic biologist.

Our search led us to the concept of bacterial cancer therapy.


 

CATE consists of the non-pathogenic bacterium E. coli Nissle that has the intrinsic ability to home preferentially in tumors.

It features two safety checkpoint mechanisms to ensure only tumor cells are damaged.

CATE is administered intravenously, travels through the blood and colonizes tumors. When enough bacteria have accumulated in the tumor, they make themselves visible and start preparing the cytotoxic payload.

After imaging the tumor with MRI, the doctor can then activate the release of the cancer-killing payload.


 

To achieve all these novel functions, we designed a genetic circuit that is distributed over two synthetic DNA sequences.

All functions were tested and optimized to make the resulting circuit as safe and well-characterized as possible.



ENGINEERING

We increased the understanding of the system's underlying mathematics by simulating its behavior with our models.

The models were then used to define important questions to clarify in experiments and develop efficient experimental and genetic design strategies.



Experimentally, we collected data to support and refine our models and to show that our system works.


ACHIEVEMENTS

We could experimentally confirm the predictions of the models. After testing every function individually, we combined them one after the other in milestone experiments to show the system in action.

We created and characterized new BioBrick parts as a contribution for the synthetic biology community.


HUMAN PRACTICES

We went beyond the lab and reached out to experts to better understand current technological and safety issues in order to enhance the design of our project.

Further, we introduced our project and the field of synthetic biology to the general public and together explored issues related to safety, ethics and sustainability.


TEAM

We are an interdisciplinary team of eight master students of ETH Zürich who compete in the iGEM championship against hundreds of other teams from all over the world.