Difference between revisions of "Team:CHINA CD UESTC/Modeling"
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− | + | <B>MODELING</B> | |
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− | + | In order to predict the potential of enzyme biofuel cell, analyze in hypothesis condition, speculate the efficiency of laccase’s catalytic, calculate the electron transfer coefficient and verify our formula, we have established a number of models and conducted a series of calculations. The following page will show you the details. | |
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− | + | <h3>Model</h3> | |
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− | + | <p> | |
− | + | Biological fuel cell (BFC) is a device with the use of enzymes or microorganisms as catalysts. According to the types of catalysts, it can be divided into microbial fuel cells(MFC)and enzymatic biofuel cell (EBFC). Our project is focused on improving the catalytic efficiency of laccase in biofuel cell. Laccase, which produced by advanced plants, fungi, and some bacterial strains, is a multicopper oxidoreductase and oxidizes phenolic compounds while reducing oxygen to water directly without requiring H<sub>2</sub>O<sub>2</sub> | |
− | + | or any other co-factors for its catalysis <sup>[1]</sup> | |
− | + | . In addition to be applied in the biological fuel cells, it also has various applications containing pulp and paper industry, environmental applications, food industry, and biosensors. | |
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− | + | <h3>The Cathodic Potential Prediction</h3> | |
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− | + | One criteria of evaluating a microbial fuel cell is potential. We use the laccase as a bio-cathode to achieve electron transfer function from pole to oxygen. | |
− | + | </p> | |
− | + | <p> | |
− | + | According to E. Laviron's article <sup>[2]</sup> | |
− | + | , we can use the Laviron formula to estimate the cathodic peak potential: | |
− | + | </p> | |
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− | + | <img src="https://static.igem.org/mediawiki/2015/b/bc/CHINA_CD_UESTC_MODELING01.png" width="60%"></div> | |
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− | + | <h3>Hypothesis Condition</h3> | |
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− | + | If we want to do some analysis, hypothesis condition is necessary from existing literatures. | |
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− | + | <img src="https://static.igem.org/mediawiki/2015/a/a8/CHINA_CD_UESTC_MODELING03.png" width="60%"></div> | |
− | + | <p> | |
− | + | From the formula (1), we can judge that the electron transfer coefficient determines the potential size. In order to study the relationship between them, we use MATLAB for the operation. The result is as follows(Figure 1): | |
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− | + | <strong>Figure 1.</strong> With the increase of electron transfer coefficient, cathodic peak potential is also increasing rapidly. But the value of α is form 0.3 to 0.7 in general. | |
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− | + | <h3>The Conjecture of Catalytic Efficiency</h3> | |
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− | + | <p> | |
− | + | We want to improve the catalytic efficiency of laccase to make biological fuel cells more efficient. So we guess that enrichment of laccase in the electrode can improve the efficiency of electron transfer.The following Figure 2 shows our conjecture: | |
− | + | </p> | |
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− | + | <strong>Figure 2.</strong> We predict the enrichment of laccase will improve the efficiency of the BFC. | |
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− | + | <h3>Theoretical Calculation</h3> | |
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− | + | The Michaelis-Menten equation describes the relationship between an enzyme (at constant concentration) and the concentration of enzyme’s substrate. | |
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− | + | Form Figure 1, we learn about the electron transfer coefficient determines the potential. So what determines the electron transfer coefficient? We think enzyme quantity per unit area and the distance between enzymes and electrodes are the main influence factors. So we establish the formula: | |
− | + | </p> | |
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− | + | <h3>Ideal Assumptions</h3> | |
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− | + | In order to verify whether our formula is correct. We need some ideal assumptions to meet calculation conditions. | |
− | + | </p> | |
− | + | <div class="list_txt"> | |
− | + | <ul> | |
− | + | <li> | |
− | + | <p> <strong>1. the EBFC can work well and smoothly.</strong> | |
− | + | </p> | |
− | + | </li> | |
− | + | <li> | |
− | + | <p> <strong>2. the amount of substrate is enough</strong> | |
− | + | </p> | |
− | + | </li> | |
− | + | <li> | |
− | + | <p> | |
− | + | <strong>3. Laccases adhere to electrode strongly enough</strong> | |
− | + | </p> | |
− | + | </li> | |
− | + | </ul> | |
− | + | </div> | |
− | + | <p> | |
− | + | We calculate the equation (3), and simulate the results with MATLAB(Figure 3). The electron transfer coefficient variation tendency are as follows: | |
− | + | </p> | |
− | + | <div class="project_pic"> | |
− | + | <p id="pic_title"></p> | |
− | + | <img src="https://static.igem.org/mediawiki/2015/a/a6/CHINA_CD_UESTC_MODELING09.png" width="60%"> | |
− | + | <p id="pic_illustration"><strong>Figure 3.</strong> The electron transfer coefficient variation tendency relates with enzyme quantity per unit | |
− | + | area and the distance between enzymes and electrodes. Our model result is consistent with | |
− | + | the experimental conclusions[3].</p></div> | |
+ | <p> | ||
+ | There are many methods to fix laccase on the electrode. However, we came up with a novel idea utilizing biology magnetotaxis. Magnetotactic bacterium(MTB) is a special microbe in nature which can be attracted by magnet . Magnetosome, covered by membrane with some Fe3O4s nanocrystals, which is the reason why MTB has the ability to be attracted. We design a expression system for <i>E.coli</i> expressing magnetosomes. And then we link laccases to magnetosomes by the method of structuring fusion protein with MamW. The ultimate goal is showing in the Figure 4: | ||
+ | </p> | ||
− | + | <div class="project_pic"> | |
− | + | <p id="pic_title"></p> | |
− | + | <img src="https://static.igem.org/mediawiki/2015/1/1a/CHINA_CD_UESTC_MODELING10.png" width="60%"> | |
− | + | <p id="pic_illustration"> | |
− | + | <strong>Figure 4.</strong> Fixing laccase on the electrode with Magnetosome. It has the advantage of simple operation , environmental protection, as well as good biocompatibility. | |
− | + | </p> | |
− | + | </div> | |
− | + | <p> | |
− | + | According to previous experiments and papers, we verifiy our model by their experiment data. For exampe, Maryam Nazari et al | |
− | + | <sup>[3]</sup> | |
− | + | assembled a MFC with laccase. Detected voltage was 256mV, and when =0.75, the result our model predicted was 238mV. In the error range, our model is correct! | |
− | + | </p> | |
− | + | <div class="reference"> | |
− | + | <h4>Reference</h4> | |
− | + | <p> | |
− | + | [1] Babadostu A, Guldu O K, Demirkol D O, et al. Affinity Based Laccase Immobilization on Modified Magnetic Nanoparticles: Biosensing Platform for the Monitoring of Phenolic Compounds[J]. International Journal of Polymeric Materials and Polymeric Biomaterials, 2015, 64(5): 260-266. | |
− | + | </p> | |
− | + | <p> | |
− | + | [2] Laviron E. General expression of the linear potential sweep voltammogram in the case of diffusionless electrochemical systems[J]. Journal of Electroanalytical Chemistry & Interfacial Electrochemistry, 1979, 101(1):19–28. | |
− | + | </p> | |
− | + | <p> | |
− | + | [3] Nazari M, Kashanian S, Rafipour R. Laccase immobilization on the electrode surface to design a biosensor for the detection of phenolic compound such as catechol[J]. Spectrochimica Acta Part A Molecular & Biomolecular Spectroscopy, 2015, 145:130–138. | |
− | + | </p> | |
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Latest revision as of 11:21, 18 September 2015
<!DOCTYPE html>
MODELING
In order to predict the potential of enzyme biofuel cell, analyze in hypothesis condition, speculate the efficiency of laccase’s catalytic, calculate the electron transfer coefficient and verify our formula, we have established a number of models and conducted a series of calculations. The following page will show you the details.