Difference between revisions of "Team:UFSCar-Brasil/Modeling"
| (18 intermediate revisions by 5 users not shown) | |||
| Line 3: | Line 3: | ||
<div class="ui hidden divider"></div> | <div class="ui hidden divider"></div> | ||
| − | + | <div class="ui vertical center aligned inverted segment"> | |
| − | + | <div class="ui fluid container"> | |
| − | + | <div class="ui hidden divider"></div> | |
| − | + | <div class="ui text container"> | |
| − | + | <h1 class="ui teal header"> | |
| − | + | Modeling | |
| − | + | </h1> | |
| − | + | <h2 class="ui teal header">Mathematics predicting and explaining events towards repellent</h2> | |
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
</div> | </div> | ||
| + | <div class="spacer"></div> | ||
| + | </div> | ||
| + | </div> | ||
| − | + | <div class="ui vertical stripe segment stackable container"> | |
| − | + | <h3 class="ui header" id="overview">Overview</h3> | |
| − | + | <p> Modeling was made using differential calculus with analytical geometry approaches. Tridimensional solutions were a resource used to explain the multivariable systems obtained in our analysis. This 'joint approach' was chosen to comprise all expected data | |
| − | + | and provide useful evidence of non-validated data. First of all, Bug Shoo is a product and we must answer several questions not testable in lab before manufacturing tracking, such as the product expiration date. Besides this, | |
| − | + | some project parts have a complex functioning as kill switch and a mathematical model could help to determine the effective time of product working. The effectiveness of the product is another important question, for this, some economic solutions, | |
| + | e.g. reduction of PEG 6000 in final formula, optimal zinc chloride concentrations and another parameters could be adjusted with modeling aid. Main used softwares were OriginLab and MatLab. In this sense, we still want to determine the current project | ||
| + | as predictive since some parts of it were not produced and the modeling still is passive to work.</p> | ||
| + | </div> | ||
| − | + | <div class="ui vertical stripe segment stackable container"> | |
| − | </ | + | <h3 class="ui header" id="parts">Plasmolysis</h3> |
| + | <p>Main purpose of plasmolysis modeling was to determine a relative point, where we have the longest time of bacterial viability and lowest possible percentage of PEG 6000. In order to do that, it was carried out a plasmolysis experiment in our microbiology | ||
| + | laboratory for some weeks, along we collected the data. Collected data were processed and analyzed to find a best-fit model. Using it, specific values were simulated to generate a mathematical surface. Finally, tangent lines to surface revealed the | ||
| + | optimal point. Manufacturing tracking is known by its practical nature, and this study was significant to determine the conditions of product storage, besides revealing a technique very useful to other teams in future. Furthermore, this approach provided | ||
| + | a prediction of optimal features for maximal product expiration date. | ||
| + | </p> | ||
| + | <div class="center aligned"> | ||
| + | <a href="https://2015.igem.org/wiki/index.php?title=Team:UFSCar-Brasil/part1.html" class="ui teal big button">See more! <i class="right arrow icon"></i></a> | ||
</div> | </div> | ||
| − | + | </div> | |
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | <div class="ui vertical stripe segment stackable container"> | |
| − | + | <h3 class="ui header" id="result">Protein Solubilization Toolkit</h3> | |
| − | + | <p>In this section, we have developed a statistical approach to study the chaperone efficiency in protein folding, in our specific case, limonene synthase folding. This is extensive to all projects with systems of crossed elements effects. As we have several | |
| − | + | chaperones acting in the same final product, the measurement of each effect is complex and could be ineffective. In this sense, we have developed a best-fit model of chaperone arrangement taking in account the folded protein yield. To this, Euclidian | |
| − | + | mathematical distances were used to clustering analysis generating a dendogram which was used to determine the main groups and statistical differences. After this, the system was solved with a linear system where all relations were input to generate | |
| + | an output of mathematical effect constants for each component.</p> | ||
| − | + | <div class="center aligned"> | |
| − | </ | + | <a href="https://2015.igem.org/wiki/index.php?title=Team:UFSCar-Brasil/part2.html" class="ui teal big button">See more! <i class="right arrow icon"></i></a> |
</div> | </div> | ||
| − | + | </div> | |
| − | + | ||
| − | + | ||
| − | + | ||
| − | + | ||
| − | <h3 class="ui | + | <div class="ui vertical stripe segment stackable container"> |
| − | + | <h3 class="ui header" id="judging">Kill Switch</h3> | |
| − | < | + | <p>One of our prime objectives was to describe the uspA promoter activity (<a href="http://parts.igem.org/Part:BBa_K1620000">BBa_K1620000</a> and <a href="http://parts.igem.org/Part:BBa_K1620005">BBa_K1620005</a>) when exposed to osmotic chock compared |
| − | + | with a constitutive promoter, J23101 derived construct (<a href="http://parts.igem.org/Part:BBa_K1620006">BBa_K1620006</a>). First of all, the adjust of fluorescence points to exponential functions were done to give fluorescence values / GFP molecule | |
| + | quantities related to PEG concentrations or even calculated osmotic pressures. Proper fitted curves were used to model concentration of Zn(II) in culture medium along time (describing a decay curve). The final concentration of Zn(II) in culture medium | ||
| + | will be lower due to metal ions import to intracellular environment followed by immobilization through gradual association to smtA protein (<a href="http://parts.igem.org/Part:BBa_K1620007">BBa_K1620007</a>). This section aims estimate the approximate | ||
| + | time for begin the death cell process, well known when Zn(II) concentration tends to minimal and the Zasp element (<a href="http://parts.igem.org/Part:BBa_K1620001">BBa_K1620001</a>) starts promotion of killer genes. This period is marked by releasing | ||
| + | of our killswitch’s promoter region due to absence of intracellular Zn(II) available to maintain zur factor (<a href="http://parts.igem.org/Part:BBa_K1620004">BBa_K1620004</a>) repressing Zasp element (<a href="http://parts.igem.org/Part:BBa_K1620001">BBa_K1620001</a>). | ||
| + | This section still reveals to us how much time the product will work after its activation.</p> | ||
| − | + | <div class="center aligned"> | |
| − | + | <a href="https://2015.igem.org/wiki/index.php?title=Team:UFSCar-Brasil/part3.html" class="ui teal big button">See more!<i class="right arrow icon"></i></a> | |
| − | </ | + | |
</div> | </div> | ||
| + | |||
| + | </div> | ||
</html> | </html> | ||
{{:Team:UFSCar-Brasil/Templates/Footer}} | {{:Team:UFSCar-Brasil/Templates/Footer}} | ||
Latest revision as of 20:05, 18 September 2015
Modeling
Mathematics predicting and explaining events towards repellent
Overview
Modeling was made using differential calculus with analytical geometry approaches. Tridimensional solutions were a resource used to explain the multivariable systems obtained in our analysis. This 'joint approach' was chosen to comprise all expected data and provide useful evidence of non-validated data. First of all, Bug Shoo is a product and we must answer several questions not testable in lab before manufacturing tracking, such as the product expiration date. Besides this, some project parts have a complex functioning as kill switch and a mathematical model could help to determine the effective time of product working. The effectiveness of the product is another important question, for this, some economic solutions, e.g. reduction of PEG 6000 in final formula, optimal zinc chloride concentrations and another parameters could be adjusted with modeling aid. Main used softwares were OriginLab and MatLab. In this sense, we still want to determine the current project as predictive since some parts of it were not produced and the modeling still is passive to work.
Plasmolysis
Main purpose of plasmolysis modeling was to determine a relative point, where we have the longest time of bacterial viability and lowest possible percentage of PEG 6000. In order to do that, it was carried out a plasmolysis experiment in our microbiology laboratory for some weeks, along we collected the data. Collected data were processed and analyzed to find a best-fit model. Using it, specific values were simulated to generate a mathematical surface. Finally, tangent lines to surface revealed the optimal point. Manufacturing tracking is known by its practical nature, and this study was significant to determine the conditions of product storage, besides revealing a technique very useful to other teams in future. Furthermore, this approach provided a prediction of optimal features for maximal product expiration date.
Protein Solubilization Toolkit
In this section, we have developed a statistical approach to study the chaperone efficiency in protein folding, in our specific case, limonene synthase folding. This is extensive to all projects with systems of crossed elements effects. As we have several chaperones acting in the same final product, the measurement of each effect is complex and could be ineffective. In this sense, we have developed a best-fit model of chaperone arrangement taking in account the folded protein yield. To this, Euclidian mathematical distances were used to clustering analysis generating a dendogram which was used to determine the main groups and statistical differences. After this, the system was solved with a linear system where all relations were input to generate an output of mathematical effect constants for each component.
Kill Switch
One of our prime objectives was to describe the uspA promoter activity (BBa_K1620000 and BBa_K1620005) when exposed to osmotic chock compared with a constitutive promoter, J23101 derived construct (BBa_K1620006). First of all, the adjust of fluorescence points to exponential functions were done to give fluorescence values / GFP molecule quantities related to PEG concentrations or even calculated osmotic pressures. Proper fitted curves were used to model concentration of Zn(II) in culture medium along time (describing a decay curve). The final concentration of Zn(II) in culture medium will be lower due to metal ions import to intracellular environment followed by immobilization through gradual association to smtA protein (BBa_K1620007). This section aims estimate the approximate time for begin the death cell process, well known when Zn(II) concentration tends to minimal and the Zasp element (BBa_K1620001) starts promotion of killer genes. This period is marked by releasing of our killswitch’s promoter region due to absence of intracellular Zn(II) available to maintain zur factor (BBa_K1620004) repressing Zasp element (BBa_K1620001). This section still reveals to us how much time the product will work after its activation.
Our amazing sponsors!
