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Saccharomyces cerevisiae to produce acrylic acid.</h4> | Saccharomyces cerevisiae to produce acrylic acid.</h4> | ||
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− | </ | + | <center> |
+ | <img src="https://static.igem.org/mediawiki/2017/2/21/%E5%A4%A7%E8%82%A0%E5%8E%9F%E5%A7%8B%E4%BB%A3%E8%B0%A2.png" class="img-responsive"> | ||
+ | <h5 style="text-align:center"> Primitive metabolic path map in E.Coli</h5> | ||
+ | </center> | ||
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<br> | <br> | ||
+ | <center> | ||
+ | <img src="https://static.igem.org/mediawiki/2017/1/10/%E5%A4%A7%E8%82%A0%E8%B7%AF%E5%BE%84%E5%9B%BE.png" class="img-responsive"> | ||
+ | <h5 style="text-align:center"> New route map in E.Coli</h5> | ||
+ | </center> | ||
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</h4> | </h4> | ||
<h4>The overall workflow is as follows:</h4> | <h4>The overall workflow is as follows:</h4> | ||
− | <h2 style="text-align:center ">Parameter estimation</h2> | + | <h2 style="text-align:center">Parameter estimation</h2> |
<h4>There are many parameters to be determined in the model. Most of these kinetic parameters can | <h4>There are many parameters to be determined in the model. Most of these kinetic parameters can | ||
be found in the literature or in the database, but at the same time, there are some kinetic | be found in the literature or in the database, but at the same time, there are some kinetic | ||
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we do the fitting of the probability density according to the two methods of the parameter | we do the fitting of the probability density according to the two methods of the parameter | ||
vector: 1.kernel density estimatebsp;2. Gaussian mixed model. | vector: 1.kernel density estimatebsp;2. Gaussian mixed model. | ||
− | <div align="center "> | + | <div align="center"> |
− | <img src="https://static.igem.org/mediawiki/2017/3/32/Model-4.png " class="img-responsive | + | <img src="https://static.igem.org/mediawiki/2017/3/32/Model-4.png" class="img-responsive" width="60%" height="60%"> |
− | + | ||
</div> | </div> | ||
<br> | <br> | ||
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<br> | <br> | ||
<br> | <br> | ||
− | <h2 style="text-align:center ">The basic workflow of parameter estimation:</h2> | + | <h2 style="text-align:center">The basic workflow of parameter estimation:</h2> |
<h4>The Gaussian mixture model can be approximated to any real probability distribution in theory. | <h4>The Gaussian mixture model can be approximated to any real probability distribution in theory. | ||
The EM algorithm is used to estimate the parameters required for the model. And we use the | The EM algorithm is used to estimate the parameters required for the model. And we use the | ||
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parameters. | parameters. | ||
− | <div align="center "> | + | <div align="center"> |
− | <img src="https://static.igem.org/mediawiki/2017/f/f7/Model-5.png " class="img-responsive | + | <img src="https://static.igem.org/mediawiki/2017/f/f7/Model-5.png" class="img-responsive" width="60%" height="60%"> |
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</div> | </div> | ||
− | <div align="center "> | + | <div align="center"> |
− | <img src="https://static.igem.org/mediawiki/2017/b/b2/Model-6.1.png " class="img-responsive | + | <img src="https://static.igem.org/mediawiki/2017/b/b2/Model-6.1.png" class="img-responsive" width="60%" height="60%"> |
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</div> | </div> | ||
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corresponding parameters when the bin reach average value. | corresponding parameters when the bin reach average value. | ||
− | <div align="center "> | + | <div align="center"> |
− | <img src="https://static.igem.org/mediawiki/2017/e/e5/Model-6.2.png " class="img-responsive | + | <img src="https://static.igem.org/mediawiki/2017/e/e5/Model-6.2.png" class="img-responsive" width="20%" height="20%"> |
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</div> | </div> | ||
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of the original PDF. The specific form and parameter values are as follows: | of the original PDF. The specific form and parameter values are as follows: | ||
<br> The reaction path of the original pathway is Gly to Gly-3-p and then to DAHP | <br> The reaction path of the original pathway is Gly to Gly-3-p and then to DAHP | ||
− | <div align="center "> | + | <div align="center"> |
− | <img src="https://static.igem.org/mediawiki/2017/d/da/Model-7.png " class="img-responsive | + | <img src="https://static.igem.org/mediawiki/2017/d/da/Model-7.png" class="img-responsive" width="40%" height="40%"> |
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</div> | </div> | ||
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paticipating - glpk and glpD. We assume that the reaction concentration of these two enzymes | paticipating - glpk and glpD. We assume that the reaction concentration of these two enzymes | ||
is 0.01 mM, assuming that the initial [Gly] concentration is 10 mM, the initial concentration | is 0.01 mM, assuming that the initial [Gly] concentration is 10 mM, the initial concentration | ||
− | of ATP 10 mM, | + | of ATP 10 mM, The concentration of Gly-3-p 0 mM and the concentration of DHAP 0 mM at the |
same time. | same time. | ||
<br> | <br> | ||
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<br> 2. Assume that the substrate involved in the reaction does not participate in other reactions. | <br> 2. Assume that the substrate involved in the reaction does not participate in other reactions. | ||
<br> In order to determine the yield of the target product, we chose to observe the efficiency | <br> In order to determine the yield of the target product, we chose to observe the efficiency | ||
− | of the DHAP yield estimation system in view of the lack of basic | + | of the DHAP yield estimation system in view of the lack of basic ceaS2 enzyme data. |
<br> | <br> | ||
</h4> | </h4> | ||
− | <div align="center "> | + | <div align="center"> |
− | <img src="https://static.igem.org/mediawiki/2017/9/95/Model-8.png " class="img-responsive | + | <img src="https://static.igem.org/mediawiki/2017/9/95/Model-8.png" class="img-responsive" width="60%" height="60%"> |
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</div> | </div> | ||
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<br> | <br> | ||
</h4> | </h4> | ||
− | <h4 style="text-align:center ">Metabolic pathways after transformation</h4> | + | <h4 style="text-align:center">Metabolic pathways after transformation</h4> |
− | <div align="center "> | + | <div align="center"> |
− | <img src="https://static.igem.org/mediawiki/2017/3/33/Model-10.png " class="img-responsive | + | <img src="https://static.igem.org/mediawiki/2017/3/33/Model-10.png" class="img-responsive" width="60%" height="60%"> |
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</div> | </div> | ||
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than glpK. Thus we assume that the GlyDH enzyme and the glpK enzyme satisfy the following | than glpK. Thus we assume that the GlyDH enzyme and the glpK enzyme satisfy the following | ||
relationship: | relationship: | ||
− | <div align="center "> | + | <div align="center"> |
− | <img src="https://static.igem.org/mediawiki/2017/5/50/Model-11.1.png " class="img-responsive | + | <img src="https://static.igem.org/mediawiki/2017/5/50/Model-11.1.png" class="img-responsive" width="30%" height="30%"> |
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</div> | </div> | ||
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have been known in previous studies. Next we adjust the alpha coefficient to study the effect | have been known in previous studies. Next we adjust the alpha coefficient to study the effect | ||
of different ratios on the overall metabolic flow. | of different ratios on the overall metabolic flow. | ||
− | <div align="center "> | + | <div align="center"> |
− | <img src="https://static.igem.org/mediawiki/2017/9/9c/Model-11.2.png " class="img-responsive | + | <img src="https://static.igem.org/mediawiki/2017/9/9c/Model-11.2.png" class="img-responsive" width="60%" height="60%"> |
− | + | ||
</div> | </div> | ||
</h4> | </h4> | ||
<br> | <br> | ||
− | <h4 style="text-align:center ">KATA Sensitivity Test before Modification</h4> | + | <h4 style="text-align:center">KATA Sensitivity Test before Modification</h4> |
− | <div align="center "> | + | <div align="center"> |
− | <img src="https://static.igem.org/mediawiki/2017/8/89/Model-12.1.png " class="img-responsive | + | <img src="https://static.igem.org/mediawiki/2017/8/89/Model-12.1.png" class="img-responsive" width="60%" height="60%"> |
− | + | ||
</div> | </div> | ||
<br> | <br> | ||
− | <h4 style="text-align:center ">KATA Sensitivity Test after Modification</h4> | + | <h4 style="text-align:center">KATA Sensitivity Test after Modification</h4> |
− | <div align="center "> | + | <div align="center"> |
− | <img src="https://static.igem.org/mediawiki/2017/e/e9/Model-12.2.png " class="img-responsive | + | <img src="https://static.igem.org/mediawiki/2017/e/e9/Model-12.2.png" class="img-responsive" width="60%" height="60%"> |
− | + | ||
</div> | </div> | ||
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<br> | <br> | ||
<br> | <br> | ||
− | <h4 style="text-align:center ">Before transformation</h4> | + | <h4 style="text-align:center">Before transformation</h4> |
− | <div align="center "> | + | <div align="center"> |
− | <img src="https://static.igem.org/mediawiki/2017/9/91/Model-14.1.png " class="img-responsive | + | <img src="https://static.igem.org/mediawiki/2017/9/91/Model-14.1.png" class="img-responsive" width="60%" height="60%"> |
− | + | ||
</div> | </div> | ||
<br> | <br> | ||
− | <h4 style="text-align:center ">After trransformation</h4> | + | <h4 style="text-align:center">After trransformation</h4> |
− | <div align="center "> | + | <div align="center"> |
− | <img src="https://static.igem.org/mediawiki/2017/d/d8/Model-14.2.png " class="img-responsive | + | <img src="https://static.igem.org/mediawiki/2017/d/d8/Model-14.2.png" class="img-responsive" width="60%" height="60%"> |
− | + | ||
</div> | </div> | ||
<h4> | <h4> | ||
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<br> But when we adjust the standard deviation of the normal distribution random variable to | <br> But when we adjust the standard deviation of the normal distribution random variable to | ||
0.05, the result is shown below. | 0.05, the result is shown below. | ||
− | <div align="center "> | + | <div align="center"> |
− | <img src="https://static.igem.org/mediawiki/2017/f/f2/Model-15.1.png " class="img-responsive | + | <img src="https://static.igem.org/mediawiki/2017/f/f2/Model-15.1.png" class="img-responsive" width="60%" height="60%"> |
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</div> | </div> | ||
− | <div align="center "> | + | <div align="center"> |
− | <img src="https://static.igem.org/mediawiki/2017/c/ce/Model-15.2.png " class="img-responsive | + | <img src="https://static.igem.org/mediawiki/2017/c/ce/Model-15.2.png" class="img-responsive" width="60%" height="60%"> |
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</div> | </div> | ||
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</div> | </div> | ||
− | <div class="tab-pane fade " id="service-two "> | + | <div class="tab-pane fade" id="service-two"> |
− | < | + | <h2 style="text-align:center"> Mutation Design of ceaS2 by using AEMD</h2> |
− | < | + | <h3 style="text-align:center">Abstract</h3> |
<h4>Engineering for the desired enzyme catalytic properties plays an important role in the biosynthesis | <h4>Engineering for the desired enzyme catalytic properties plays an important role in the biosynthesis | ||
of bulk chemicals and natural products. However, it is a time-consuming task to improve enzyme | of bulk chemicals and natural products. However, it is a time-consuming task to improve enzyme | ||
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protein structure often was limited by the lack of protein structure for target enzymes and | protein structure often was limited by the lack of protein structure for target enzymes and | ||
professional backgrounds of bioinformatics. | professional backgrounds of bioinformatics. | ||
− | <br> | + | <br> ceaS2 enzyme is the most important enzyme in our entire acrylic acid synthesis pathway, |
− | <br> | + | but the activity of wild type is not high. So it is exceedingly necessary to modify it on |
− | + | the basis of the "part" level to improve its catalytic reactivity. We used the AEMD platform | |
− | <h3 style="text-align: center | + | to conduct the mutational design for ceaS2 enzyme in order to figure out a more accurate |
− | <h4 | + | scheme of mutation, which can also exert great beneficial impact on the later experiments. |
− | + | <br> We have totally identified 32 mutational sites, and its point mutation transformation. The | |
+ | experimental results show that there are 11 sites, where the enzyme activity gets boosted, | ||
+ | after the transformation. Compared to wild type ceaS2 enzyme, the highest activity has increased | ||
+ | by 11 times, whose effect is obviously noticeable. This also demonstrates the ability of | ||
+ | this designing platform. </h4> | ||
+ | <h3 style="text-align:center">Introduction</h3> | ||
+ | <h4>Enzyme engineering has been extensively used to optimize biocatalysts in industrial biotechnology | ||
since most of enzymes in nature prefer to organisms adaptation but not industrial production | since most of enzymes in nature prefer to organisms adaptation but not industrial production | ||
(Alvizo, et al., 2014; Ma, et al., 2009; Savile, et al., 2010). Traditionally, optimized | (Alvizo, et al., 2014; Ma, et al., 2009; Savile, et al., 2010). Traditionally, optimized | ||
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thermo-stability based on the known PDB structure, and often request professional backgrounds | thermo-stability based on the known PDB structure, and often request professional backgrounds | ||
in protein structure, biochemistry, bioinformatics and so on. | in protein structure, biochemistry, bioinformatics and so on. | ||
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</h4> | </h4> | ||
− | <h3 style="text-align: center | + | |
− | <h4 | + | <h3 style="text-align:center">What is AEMD?</h3> |
− | + | ||
+ | <h4>AEMD is a web-based pipeline, which integrates several approaches together for enzyme stability, | ||
selectivity and activity engineering. This pipeline can generate comprehensive reports, which | selectivity and activity engineering. This pipeline can generate comprehensive reports, which | ||
include the recommended mutation for improving enzyme catalytic property. Specifically, users | include the recommended mutation for improving enzyme catalytic property. Specifically, users | ||
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of mutations for almost all enzyme even without protein structure. In the future, we will | of mutations for almost all enzyme even without protein structure. In the future, we will | ||
construct a comprehensive enzymatic mutant database and integrate new computing technology, | construct a comprehensive enzymatic mutant database and integrate new computing technology, | ||
− | to improve the efficiency of enzyme engineering in industrial biotechnology. | + | to improve the efficiency of enzyme engineering in industrial biotechnology. </h4> |
− | + | ||
− | (C). The blue color rectangle blocks represent the inputs of sequence or PDB file, and the | + | |
+ | |||
+ | <h4>Fig.1 Workflow of the Stability analysis (A), Selectivity analysis (B) and Activity analysis | ||
+ | (C).The blue color rectangle blocks represent the inputs of sequence or PDB file, and the | ||
output of recommended mutation sites. The green and gray color rectangle blocks represent | output of recommended mutation sites. The green and gray color rectangle blocks represent | ||
the evolution- and energy-based analysis process, respectively. The yellow color diamond | the evolution- and energy-based analysis process, respectively. The yellow color diamond | ||
− | blocks represent the use of other softwares and approaches. The processes were shown in | + | blocks represent the use of other softwares and approaches. The processes were shown in |
− | methods | + | <a href="https://static.igem.org/mediawiki/2017/0/09/AEMD_Supplementary_materials.pdf">Supplementary methods</a> in more detail.</h4> |
− | <br> | + | |
− | < | + | <h3 style="text-align:center">Process</h3> |
+ | |||
+ | <h4>This time we utilized AEMD's Stability mode (click here for AEMD user's guide) to screen for | ||
+ | mutational sites that benefit the ceaS2 enzyme activity. | ||
+ | <br> Because of the complexity of enzyme catalysis, it’s difficult to predict point mutation | ||
+ | improving protein activity accurately. How AEMD work? | ||
+ | <br> Firstly,the development team of AEMD recently described a method which is able to identify | ||
+ | desired mutations by analyzing the coevolution information of protein sequences (Liu, et | ||
+ | al., 2016). In the AEMD-web, some point mutations are suggested by this method. Besides, | ||
+ | AEMD’s analysis generated some residues close to active center and transport tunnels which | ||
+ | are recommended to saturated mutation to improve activity (Fig. 1C). For the input of target | ||
+ | protein sequence, AEMD first obtain the PDB file using RosettaCM (Song, et al., 2013). Next, | ||
+ | the substrate of template PDB was mapped into target PDB using the “struct_align” funciton | ||
+ | of Schrodinger software (QikProp, 2015). The spatial location of substrate in target PDB | ||
+ | can help to determine the ligand-binding pocket of target enzyme. If all potential template | ||
+ | PDB had no substrate in the PDB file, AEMD predicted the ligand-binding pocket by a Rosetta | ||
+ | script (gen_apo_grids.linuxgccrelease) (Zanghellini, et al., 2006). After the determination | ||
+ | of ligand-binding pocket, AEMD generated the possible catalytic sites by search local Catalytic | ||
+ | Site Atlas (Furnham, et al., 2014); the residues within 5Å distance from ligands by calculating | ||
+ | the minimum distance between residue and substrate; and the residues located within 3 Å distance | ||
+ | from transport tunnels by CAVER (Chovancova, et al., 2012).(see the Fig.1 (C)) | ||
+ | <br> We submitted the amino acid sequence and PDB file of ceaS2 online and got the prediction | ||
+ | result in half an hour.As shown below, you can also | ||
+ | <a href="https://static.igem.org/mediawiki/2017/5/57/CeaS2_analysis_report.pdf">download PDF version</a>. | ||
</h4> | </h4> | ||
− | <h3 style="text-align: center | + | <br> |
+ | <img src="https://static.igem.org/mediawiki/2017/e/e2/Model_result.png" class="img-responsive"> | ||
+ | <br> | ||
+ | <br> | ||
+ | <h3 style="text-align:center">Result</h3> | ||
<h4> | <h4> | ||
− | <br> | + | <br> We first selected the mutations within the 5Å distance of active site, altogether 33 kinds, |
− | + | and then used point mutation to conduct molecular cloning operation. Next step was to synthesize | |
− | + | the acrylic acid using the whole cell catalysis and determined the acrylic acid yield by | |
− | + | HPLC. The results are as follows: | |
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<br> | <br> | ||
+ | <center> | ||
+ | <img src="https://static.igem.org/mediawiki/2017/e/e4/NPU-26.png" class="img-responsive"> | ||
+ | </center> | ||
+ | In these total 33 mutations of mutational sites, there are 11 mutations' acrylic acid yield higher than that of the wild | ||
+ | type, which indicates a higher activity. The highest mutational site F438M presents a yield | ||
+ | 11 times the wild type. Therefore, it is valid and tangible for us to implement AEMD to design | ||
+ | the mutational sites! | ||
</h4> | </h4> | ||
+ | |||
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</div> | </div> | ||
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</div> | </div> | ||
− | <img src="https://static.igem.org/mediawiki/2017/0/0c/Jz.png " class="img-responsive "> | + | <img src="https://static.igem.org/mediawiki/2017/0/0c/Jz.png" class="img-responsive"> |
</div> | </div> | ||
</div> | </div> |
Latest revision as of 03:00, 2 November 2017