Difference between revisions of "Team:Rice/Model"

 
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<h1>MODELING</h1>
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<h2>Wastewater Treatment Process</h2>
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<p> Wastewater initially has most of its suspended solids settled out in primary treatment and then it is sent to a process called secondary treatment where most of the organic solutes are removed from the water by aerobic bacteria. After secondary treatment, any remaining bacteria are killed in tertiary treatment and then the water is released. We decided to implement our engineered bacteria as a part of an activated sludge secondary treatment system because there is already an existing environment for bacteria, a system for biocontainment, and a method of disposal for the chromium our bacteria will absorb and reduce.</p>
  
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<p>We used a differential equation model to evaluate the feasibility of our bacterium’s incorporation in an activated sludge system. </p>
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<script type="text/javascript" src="http://cdn.mathjax.org/mathjax/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML">
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<p>Our model takes into account the following processes:</p>
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<p>$k_{cat,Cr}$: rate constant of Cr (VI) catalysis $min^{-1}$</p>
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<p>$K_{M,Cr}$: Michaelis-Menten constant of Cr (VI) catalysis $\mu{}M$</p>
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<h1> Modeling</h1>
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<p>Mathematical models and computer simulations provide a great way to describe the function and operation of BioBrick Parts and Devices. Synthetic Biology is an engineering discipline, and part of engineering is simulation and modeling to determine the behavior of your design before you build it. Designing and simulating can be iterated many times in a computer before moving to the lab. This award is for teams who build a model of their system and use it to inform system design or simulate expected behavior in conjunction with experiments in the wetlab.</p>
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<h3> Gold Medal Criterion #3</h3>
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To complete for the gold medal criterion #3, please describe your work on this page and fill out the description on your <a href="https://2017.igem.org/Judging/Judging_Form">judging form</a>. To achieve this medal criterion, you must convince the judges that your team has gained insight into your project from modeling. You may not convince the judges if your model does not have an effect on your project design or implementation.
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Please see the <a href="https://2017.igem.org/Judging/Medals"> 2017 Medals Page</a> for more information.
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<h3>Best Model Special Prize</h3>
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To compete for the <a href="https://2017.igem.org/Judging/Awards">Best Model prize</a>, please describe your work on this page  and also fill out the description on the <a href="https://2017.igem.org/Judging/Judging_Form">judging form</a>. Please note you can compete for both the gold medal criterion #3 and the best model prize with this page.
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You must also delete the message box on the top of this page to be eligible for the Best Model Prize.
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<h5> Inspiration </h5>
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Here are a few examples from previous teams:
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<li><a href="https://2016.igem.org/Team:Manchester/Model">Manchester 2016</a></li>
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<li>chromium transport </li>
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<li><a href="https://2016.igem.org/Team:TU_Delft/Model">TU Delft 2016  </li>
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<li>chromium reduction</li>
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<li><a href="https://2014.igem.org/Team:ETH_Zurich/modeling/overview">ETH Zurich 2014</a></li>
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<li>induced cell death</li>
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<li><a href="https://2014.igem.org/Team:Waterloo/Math_Book">Waterloo 2014</a></li>
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<li>cellular respiration and growth</li>
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<li>bacterial sedimentation</li>
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<li>interspecies competition </li>
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<li>occasional sludge purging</li>
 
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<p>The model is capable of considering temporal variation in chromium levels and rate of wastewater arrival as well as events like purging of excess sludge and seeding with our engineered bacteria.  We are also able to predict the amount of our bacteria and chromium in the system’s output.  We were also able to predict the efficacy of our chromium remediation.</p>
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<p><div class="images"><img width="70%" src="https://static.igem.org/mediawiki/2017/4/4b/Watertreatment2.jpeg"></div></p>
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<h2>Schematics of Modeled Processes</h2>
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<p><div class="images"><img width="70%" src="https://static.igem.org/mediawiki/2017/9/99/Finalized_Water_Treatment_for_Modeling_Expanded-01.jpg"></div></p>
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<p> Early <a href = "https://static.igem.org/mediawiki/2017/a/a9/Schematicofmodeledprocesses.pdf">figure concepts</a> designed to illustrate model behavior.</p>
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<h2>Differential Equations</h2>
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<h2>Figures</h2>
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<p><div class = "images"><img width="70%" src="https://static.igem.org/mediawiki/2017/e/eb/Fig1.jpeg"></div></p>
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<p><div class = "images"><img width="70%" src="https://static.igem.org/mediawiki/2017/6/63/Fig2.jpg"></div></p>
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<p><div class = "images"><img width="70%" src="https://static.igem.org/mediawiki/2017/8/82/Fig3.jpg"></div></p>
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<p><div class = "images"><img width="70%" src="https://static.igem.org/mediawiki/2017/5/57/Fig4.jpg"></div></p>
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Latest revision as of 03:58, 2 November 2017

Hexatri

MODELING

Wastewater Treatment Process

Wastewater initially has most of its suspended solids settled out in primary treatment and then it is sent to a process called secondary treatment where most of the organic solutes are removed from the water by aerobic bacteria. After secondary treatment, any remaining bacteria are killed in tertiary treatment and then the water is released. We decided to implement our engineered bacteria as a part of an activated sludge secondary treatment system because there is already an existing environment for bacteria, a system for biocontainment, and a method of disposal for the chromium our bacteria will absorb and reduce.

We used a differential equation model to evaluate the feasibility of our bacterium’s incorporation in an activated sludge system.

Our model takes into account the following processes:

  • chromium transport
  • chromium reduction
  • induced cell death
  • cellular respiration and growth
  • bacterial sedimentation
  • interspecies competition
  • occasional sludge purging

The model is capable of considering temporal variation in chromium levels and rate of wastewater arrival as well as events like purging of excess sludge and seeding with our engineered bacteria. We are also able to predict the amount of our bacteria and chromium in the system’s output. We were also able to predict the efficacy of our chromium remediation.

Schematics of Modeled Processes

Early figure concepts designed to illustrate model behavior.

Differential Equations

Figures