Difference between revisions of "Team:ShanghaiFLS China/Model"

Revision as of 14:10, 16 October 2019

ShanghaiFLS_China: Model

This is

ShanghaiFLS_China

We designed our constructs (pGMP1-pAOX1-GFP, pAPM1-pAOX1-GFP and pGMP1-pAPM1-AOX1-GFP) using homogenous promoters and transcription factors in P. pastoris GS115 to moderately up-regulate the activity of the AOX1 (alcohol oxidase 1) promoter. To get an idea of how much more efficient our constructs will be compared with the wild-type P. pastoris, we modeled our constructs based on various statistics published in Wang et al., 2016, Shi et al., 2019 and Liang et al., 2012. We then calculated basic parameters for each promoter and transcription factor in our three constructs, specifically, the activity of a promoter under the effect of 1 unit transcription factor. As it turned out, we relatively successfully calculated the eventual GFP expression by pAOX1 in each of our constructs and compared that to the GFP expression by pAOX1 in the pAOX1-GFP strain (GFP expressed by AOX1 promoter homologously reintegrated into wild type P. pastoris GS115, in which GFP indicates pAOX1 activity).

Model

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                      <h3 class="editContent">This is</h3>
                      <h2 class="editContent">ShanghaiFLS_China</h2>
-                     <p>We designed our constructs (pGMP1-pAOX1-GFP, pAPM1-pAOX1-GFP and pGMP1-pAPM1-AOX1-GFP) using homogenous promoters and transcription factors in P. pastoris GS115 to moderately up-regulate the activity of the AOX1 (alcohol oxidase 1) promoter. To get an idea of how much more efficient our constructs will be compared with the wild-type P. pastoris, we tried to model our constructs based on various statistics published in Wang et al., 2016, Shi et al., 2019 and Liang et al., 2012. Based on these data, we calculated basic parameters for each promoter and transcription factor in our three constructs, specifically, the activity of a promoter under the effect of 1 unit transcription factor. This first step is very important as our construct involves promoters and two transcription factors that not only interact among themselves but also with their copies in the P. pastoris GS115 strain, resulting in a very complicated combined effect. Modeling individual promoters and transcription factors is like creating the building blocks for predicting something more complex. And indeed, with these building blocks, we relatively successfully calculated the eventual GFP expression by pAOX1 in each of our constructs and compared that to the GFP expression by pAOX1 in the pAOX1-GFP strain (GFP expressed by AOX1 promoter homologously reintegrated into wild type P. pastoris GS115, in which GFP indicates pAOX1 activity).</p>
+                     <p>We designed our constructs (pGMP1-pAOX1-GFP, pAPM1-pAOX1-GFP and pGMP1-pAPM1-AOX1-GFP) using homogenous promoters and transcription factors in <em>P. pastoris</em> GS115 to moderately up-regulate the activity of the AOX1 (alcohol oxidase 1) promoter. To get an idea of how much more efficient our constructs will be compared with the wild-type <em>P. pastoris</em>, we modeled our constructs based on various statistics published in Wang et al., 2016, Shi et al., 2019 and Liang et al., 2012. We then calculated basic parameters for each promoter and transcription factor in our three constructs, specifically, the activity of a promoter under the effect of 1 unit transcription factor. As it turned out, we relatively successfully calculated the eventual GFP expression by pAOX1 in each of our constructs and compared that to the GFP expression by pAOX1 in the pAOX1-GFP strain (GFP expressed by AOX1 promoter homologously reintegrated into wild type P. pastoris GS115, in which GFP indicates pAOX1 activity).</p>
                      <a href="https://static.igem.org/mediawiki/2019/9/93/T--ShanghaiFLS_China--model.pdf"> Model </a>
                  </div>