|
|
Line 136: |
Line 136: |
| <section class='sub_sections'> | | <section class='sub_sections'> |
| <div style='text-align: justify;'> | | <div style='text-align: justify;'> |
− | <p>Thanks to this combined analysis, we have designed the Biobricks to use in the experiments/simulations and made a strong case for the case-by-case use of a transcriptioal or post-trascriptional repressor according to a the miRNA dataset.</p> | + | <p>Thanks to this combined analysis, we have designed the Biobricks to use in the experiments/simulations and made a strong case for the case-by-case use of a transcriptional or post-trascriptional repressor according to the miRNA dataset.</p> |
| </div> | | </div> |
| </section> | | </section> |
Line 151: |
Line 151: |
| <section class='sub_sections'> | | <section class='sub_sections'> |
| <div style='text-align: justify;'> | | <div style='text-align: justify;'> |
− | <p>We envisage pANDORRA as a cloning toolkit with standard parts (designed in the previous step) that can be easily applicable to the construction of a wide range of transcriptional/posttranscriptional synthetic circuits. In this endeavor, we focused on two aspects, interoperability and modularity, by <a href='https://2017.igem.org/Team:Greece/HP/Gold_Integrated'>integrating extensive technical feedback from experts in the field.</a></p> | + | <p>We envisage pANDORRA as a cloning toolkit with standard parts (designed in the previous step) that can be easily applicable to the construction of a wide range of transcriptional/post-transcriptional synthetic circuits. In this endeavor, we focused on two aspects, interoperability and modularity, by <a href='https://2017.igem.org/Team:Greece/HP/Gold_Integrated'>integrating extensive technical feedback from experts in the field.</a></p> |
| <p>According to Benenson et al., 2012 [<a href='#ref9_pd'>9</a>], an effective molecular switch or gate is characterized by:</p> | | <p>According to Benenson et al., 2012 [<a href='#ref9_pd'>9</a>], an effective molecular switch or gate is characterized by:</p> |
| <ul> | | <ul> |
− | <li style='list-style: disc'>The existence of a robust digital regime (that is, input levels that produce either a very low or a very high (saturated) output)</li> | + | <li style='list-style: disc'>The existence of a robust digital regime (that is, input levels that produce either a very low or a very high (saturated) output).</li> |
− | <li style='list-style: disc'>Gate scalability, which is the capacity to receive an increasing number of inputs without dramatic design alterations</li> | + | <li style='list-style: disc'>Gate scalability, which is the capacity to receive an increasing number of inputs without dramatic design alterations.</li> |
− | <li style='list-style: disc'>Composability, which is the capacity to operate together with other gates in parallel and/or in cascades in a predictable manner</li> | + | <li style='list-style: disc'>Composability, which is the capacity to operate together with other gates in parallel and/or in cascades in a predictable manner.</li> |
| </ul> | | </ul> |
| <p>In order to add the aforementioned features to our toolkit and to aid in the cloning process, we created various Composite Parts, that can be used to create multi-layered classifiers. At first glance, the constructs have the following general structure:</p> | | <p>In order to add the aforementioned features to our toolkit and to aid in the cloning process, we created various Composite Parts, that can be used to create multi-layered classifiers. At first glance, the constructs have the following general structure:</p> |
Line 171: |
Line 171: |
| </table> | | </table> |
| <p>Notably, the output module can include either a coding region for a fluorescent protein, DsRed or a toxin, Apoptin (<a href='http://parts.igem.org/Part:BBa_K1061001'>BBa_K1061001</a>), a selective cancer cell killer derived from the Chicken Anemia Virus (CAV) known to cause p53-independent apoptosis in more than 70 human cancer cell lines while leaving normal cells unharmed [<a href='#ref12_pd'>12</a>]. The use of Apoptin instead of hbax [<a href='#ref4_pd'>4</a>] was a change incorporated for increased cytotoxicity and an additional safety fail-safe after discussing with <a href='https://2017.igem.org/Team:Greece/HP/Gold_Integrated'>Prof. JD Keasling and interpreting OSIRIS results.</a></p> | | <p>Notably, the output module can include either a coding region for a fluorescent protein, DsRed or a toxin, Apoptin (<a href='http://parts.igem.org/Part:BBa_K1061001'>BBa_K1061001</a>), a selective cancer cell killer derived from the Chicken Anemia Virus (CAV) known to cause p53-independent apoptosis in more than 70 human cancer cell lines while leaving normal cells unharmed [<a href='#ref12_pd'>12</a>]. The use of Apoptin instead of hbax [<a href='#ref4_pd'>4</a>] was a change incorporated for increased cytotoxicity and an additional safety fail-safe after discussing with <a href='https://2017.igem.org/Team:Greece/HP/Gold_Integrated'>Prof. JD Keasling and interpreting OSIRIS results.</a></p> |
− | <p>The aforementioned Biobricks can be used to fuse any desired complementary miRNA binding site into the 3’-untranslated region, between the BbsI restriction sites hardcoded into the coding and the terminator sequences to control the expression of each module by specific miRNAs. This process has the following requirements:</p> | + | <p>The aforementioned Biobricks can be used to fuse any desired complementary miRNA binding site (target tandem repeats) into the 3’-untranslated region, between the BbsI restriction sites hardcoded into the coding and the terminator sequences to control the expression of each module by specific miRNAs. This process has the following requirements:</p> |
| <ul> | | <ul> |
| <li style='list-style:none'>(1) Composite Parts in the form of Promoter + Protein Coding Region + <a href='http://parts.igem.org/Part:BBa_K515105'>BBa_K515105</a> + polyA signal & terminator, BioBrick compatible format</li> | | <li style='list-style:none'>(1) Composite Parts in the form of Promoter + Protein Coding Region + <a href='http://parts.igem.org/Part:BBa_K515105'>BBa_K515105</a> + polyA signal & terminator, BioBrick compatible format</li> |
Line 181: |
Line 181: |
| <ul> | | <ul> |
| <li style='list-style:none'>(1) PCR amplification of the miRNA binding sites BioBricks</li> | | <li style='list-style:none'>(1) PCR amplification of the miRNA binding sites BioBricks</li> |
− | <li style='list-style:none'>(2) Digestion with BbsI of the Promoter + Protein Coding Region + <a href='http://parts.igem.org/Part:BBa_K515105'>BBa_K515105</a> + polyA signal & terminator BioBricks</li> | + | <li style='list-style:none'>(2) Digestion of the Promoter + Protein Coding Region + <a href='http://parts.igem.org/Part:BBa_K515105'>BBa_K515105</a> + polyA signal & terminator BioBricks with BbsI</li> |
− | <li style='list-style:none'>(3) Digestion with BsaI of the PCR amplified miRNA binding sites BioBricks</li> | + | <li style='list-style:none'>(3) Digestion of the PCR amplified miRNA binding sites BioBricks with BsaI</li> |
− | <li style='list-style:none'>(4) The digested products have compatible sticky ends. As a result one example of the final constructs is:</li> | + | <li style='list-style:none'>(4) The digested products have compatible sticky ends. As a result, one example of the final constructs is:</li> |
| </ul></br> | | </ul></br> |
| <div style='text-align:center'><img class='sub_images' src='https://static.igem.org/mediawiki/2017/8/8b/Greekom_Design_pANDORRAfinal2.png' /></div> | | <div style='text-align:center'><img class='sub_images' src='https://static.igem.org/mediawiki/2017/8/8b/Greekom_Design_pANDORRAfinal2.png' /></div> |
Line 194: |
Line 194: |
| <section class='sub_sections'> | | <section class='sub_sections'> |
| <div style='text-align: justify;'> | | <div style='text-align: justify;'> |
− | <p>The multiple architectures that emerge from the pANDORRA toolkit can be evaluated by using the <a href='https://2017.igem.org/Team:Greece/RNAi%20Classifier%20Design'>RNAi classifier design model</a> in order to recognize the optimal one for every different classification task, for example classifying Caco-2 cells. Moreover, in our model the number of repeats for miRNA binding sites is evaluated. Another point that gets elucidated is the position of the TFF4 binding site. In our models, it is adjacent to the polyA terminator as Haefliger et al., 2016 [<a href='#ref14_pd'>14</a>] showed that when the TFF4 is upstream of other binding sites, the downstream binding sites for other miRNAs are not affected by their miRNA mimics and thus optimal knockdown efficiency isn’t observed. Check the results of this process <a href='https://2017.igem.org/Team:Greece/RNAi%20Classifier%20Design'>here</a>.</p> | + | <p>The multiple architectures that emerge from the pANDORRA toolkit can be evaluated by using the <a href='https://2017.igem.org/Team:Greece/RNAi%20Classifier%20Design'>RNAi classifier design model</a> in order to recognize the optimal one for every different classification task, for example for classifying Caco-2 cells. Moreover, in our model, the number of repeats for miRNA binding sites is evaluated. Another point that gets elucidated is the position of the TFF4 binding site. In our models, it is adjacent to the polyA terminator, as Haefliger et al., 2016 [<a href='#ref14_pd'>14</a>] showed that when the TFF4 is upstream of other binding sites, the downstream binding sites for other miRNAs are not affected by their miRNA mimics and thus optimal knockdown efficiency isn’t observed. You can check the results of this process <a href='https://2017.igem.org/Team:Greece/RNAi%20Classifier%20Design'>here</a>.</p> |
| </div> | | </div> |
| </section> | | </section> |
Line 203: |
Line 203: |
| <section class='sub_sections'> | | <section class='sub_sections'> |
| <div style='text-align: justify;'> | | <div style='text-align: justify;'> |
− | <p>By this back-and-forth approach, the optimal classifier can be computationally predicted and assembled from compartmentalized modules. The architectures that emerged through this exhaustive analysis have been characterized in 3 cell lines, Caco-2, HEK-293, A549. Check the results of this process <a href='https://2017.igem.org/Team:Greece/Results'>here</a>.</p> | + | <p>By this back-and-forth approach, the optimal classifier can be computationally predicted and assembled from compartmentalized modules. The architectures that emerged through this exhaustive analysis have been characterized in 3 cell lines, Caco-2, HEK-293, A549. You can check the results of this process <a href='https://2017.igem.org/Team:Greece/Results'>here</a>.</p> |
| </div> | | </div> |
| </section> | | </section> |