Difference between revisions of "Team:OLS Canmore Canada/Model"

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<tr><td><a href="https://static.igem.org/mediawiki/2018/c/c3/T--OLS_Canmore_Canada--PD.jpg" target="_blank"><img width="100%"src="https://static.igem.org/mediawiki/2018/c/c3/T--OLS_Canmore_Canada--PD.jpg"></a></td></tr>
 
<tr><td><a href="https://static.igem.org/mediawiki/2018/c/c3/T--OLS_Canmore_Canada--PD.jpg" target="_blank"><img width="100%"src="https://static.igem.org/mediawiki/2018/c/c3/T--OLS_Canmore_Canada--PD.jpg"></a></td></tr>
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<tr><td class="imagecaptiontext">Some members of our team at the Canmore Sorting Facility.</td></tr>
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<tr><td class="imagecaptiontext">Figure-1</td></tr>
 
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<p style="max-width: 60%;">
 
When examining our project, we need to consider how long it will take for the proteins to secrete out of the chassis organism. This is where our basic models come into play. We used these models to determine approximately how much of the protein our bacteria would be able to produce over any given 24 hour period. We began this process by researching how long, on average, it may take our bacteria, B.subtilis, to produce and secrete this protein. With our results, we continued on further, creating a graph (Figure- 1) portraying this data.The first graph (Figure-1) was based off of the assumption that all of the protein created inside of the cell in a 24 hour period would then also be completely secreted by cell. This was done to get an average baseline, which might then be used later as a way to determine if the data graphed later on still followed the same general linear path so that we may be able to see approximations and identify clear outliers.  
 
When examining our project, we need to consider how long it will take for the proteins to secrete out of the chassis organism. This is where our basic models come into play. We used these models to determine approximately how much of the protein our bacteria would be able to produce over any given 24 hour period. We began this process by researching how long, on average, it may take our bacteria, B.subtilis, to produce and secrete this protein. With our results, we continued on further, creating a graph (Figure- 1) portraying this data.The first graph (Figure-1) was based off of the assumption that all of the protein created inside of the cell in a 24 hour period would then also be completely secreted by cell. This was done to get an average baseline, which might then be used later as a way to determine if the data graphed later on still followed the same general linear path so that we may be able to see approximations and identify clear outliers.  
 
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<tr><td><a href="https://static.igem.org/mediawiki/2018/c/cd/T--OLS_Canmore_Canada--SD.jpg " target="_blank"><img width="100%"src="https://static.igem.org/mediawiki/2018/c/cd/T--OLS_Canmore_Canada--SD.jpg "></a></td></tr>
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<tr><td class="imagecaptiontext">Figure-2</td></tr>
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This creates the graph that you see as Figure-1. That is obviously not the case, as no bacteria is able to secrete 100% of all its protein. The next graph is a graph based on the assumption that not all the protein will be secreted and allows for an approximation of about a 10e^3 for each hour mark, as seen in figure-2. After that the next logical step, of course, was to run the test multiple times. This will yield a more accurate result in hopes to get a more precise representation of protein yield. As you can see, we are able to generate a result which closely matches that of our control line above. However, it is clear that through our calculations, some major outliers were found and marked in a different colour than black in our figure-3 graph.  
 
This creates the graph that you see as Figure-1. That is obviously not the case, as no bacteria is able to secrete 100% of all its protein. The next graph is a graph based on the assumption that not all the protein will be secreted and allows for an approximation of about a 10e^3 for each hour mark, as seen in figure-2. After that the next logical step, of course, was to run the test multiple times. This will yield a more accurate result in hopes to get a more precise representation of protein yield. As you can see, we are able to generate a result which closely matches that of our control line above. However, it is clear that through our calculations, some major outliers were found and marked in a different colour than black in our figure-3 graph.  
 
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<tr><td><a href="https://static.igem.org/mediawiki/2018/7/77/T--OLS_Canmore_Canada--SMT.jpg " target="_blank"><img width="100%"src="https://static.igem.org/mediawiki/2018/7/77/T--OLS_Canmore_Canada--SMT.jpg "></a></td></tr>
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<tr><td class="imagecaptiontext">Figure-3</td></tr>
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<h1 class="subtitle">The Subtitle</h1>
 
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<p>The project will use synthetic biology to create a novel fusion protein that can specifically bio-tag polyethylene terephthalate (PET) plastic, so that it can be sorted and recycled correctly. The project involves two proteins, a polyethylene terephthalate hydrolase (PETase) and a hydrophobin called BsIA, that is produced by a bacterium chassis called Bacillus subtilis. The PETase protein naturally binds to PET and would be paired with a red fluorescent protein called mCherry to visually indicate when the protein has adhered. The hydrophobin is “water-fearing”, therefore it will bind to anything, but for this project, it will help to adhere the PETase specifically to PET plastic. The project plan is to experiment with the use of both proteins, together and independently. If successful, the bio-tag would be proof of concept for a novel technology that can be implement easily in existing recycling facilities.
 
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Before incorporating it into the recycling facility, the protein would be isolated and purified, and the team will run numerous proof-of-concept assays. The next step in the project is prototyping. The team has explored a prototype which would use a streamlined linear process that involves both existing technology and new robotics to effectively sort plastics. Early business modelling suggests that this project is desirable by people, feasible with technology and viable as a business. 
 
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<p>In summary, the OLS SynBio team is creating a novel protein bio-tag that will adhere selectively to PET plastics.  This product has the potential to revolutionize the recycling industry, and reduce the current practice of landfilling poorly sorted plastics. This will create a truly circular life cycle for plastic products.</p>
 
  
 
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Revision as of 12:09, 17 October 2018

MODELLING

Modelling

Figure-1

When examining our project, we need to consider how long it will take for the proteins to secrete out of the chassis organism. This is where our basic models come into play. We used these models to determine approximately how much of the protein our bacteria would be able to produce over any given 24 hour period. We began this process by researching how long, on average, it may take our bacteria, B.subtilis, to produce and secrete this protein. With our results, we continued on further, creating a graph (Figure- 1) portraying this data.The first graph (Figure-1) was based off of the assumption that all of the protein created inside of the cell in a 24 hour period would then also be completely secreted by cell. This was done to get an average baseline, which might then be used later as a way to determine if the data graphed later on still followed the same general linear path so that we may be able to see approximations and identify clear outliers.

Figure-2
This creates the graph that you see as Figure-1. That is obviously not the case, as no bacteria is able to secrete 100% of all its protein. The next graph is a graph based on the assumption that not all the protein will be secreted and allows for an approximation of about a 10e^3 for each hour mark, as seen in figure-2. After that the next logical step, of course, was to run the test multiple times. This will yield a more accurate result in hopes to get a more precise representation of protein yield. As you can see, we are able to generate a result which closely matches that of our control line above. However, it is clear that through our calculations, some major outliers were found and marked in a different colour than black in our figure-3 graph.

Figure-3