Team:Heidelberg/Project/miRNA Kit
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The constructs were tested in two different backbones: pBS_U6 and pBS_H1. Both are in viral context, meaning that they contain inverted terminal repeats (ITRs). The constructs can be packed into the capsid of an adeno-associated virus (AAV). Those constructs we also chose for [https://2010.igem.org/Team:Heidelberg/Notebook/Methods#Virus_Production virus production] to infect cells even more efficiently as compared to transfections. Because of the significant data, we decided to inject the viruses into mice to see the tuning effect also <i>[https://2010.igem.org/Team:Heidelberg/Project/Mouse_Infection in vivo]</i>. The pBS_H1 construct should be preferred for mice injections since the expressed synthetic shRNA miR against human alpha-1-antitrypsine (shhAAT) is cytotoxic in higher concentrations. The pBS_H1 backbone leads to moderate expression ranges, still obviously showing the tuning effect. | The constructs were tested in two different backbones: pBS_U6 and pBS_H1. Both are in viral context, meaning that they contain inverted terminal repeats (ITRs). The constructs can be packed into the capsid of an adeno-associated virus (AAV). Those constructs we also chose for [https://2010.igem.org/Team:Heidelberg/Notebook/Methods#Virus_Production virus production] to infect cells even more efficiently as compared to transfections. Because of the significant data, we decided to inject the viruses into mice to see the tuning effect also <i>[https://2010.igem.org/Team:Heidelberg/Project/Mouse_Infection in vivo]</i>. The pBS_H1 construct should be preferred for mice injections since the expressed synthetic shRNA miR against human alpha-1-antitrypsine (shhAAT) is cytotoxic in higher concentrations. The pBS_H1 backbone leads to moderate expression ranges, still obviously showing the tuning effect. | ||
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+ | ===Modeling=== | ||
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+ | After creating a binding site library and testing the miRNA-binding site interaction <i>in vitro</i>, we were able to compute an [https://2010.igem.org/Team:Heidelberg/Modeling/miGUI <i>in silico</i> model] based on a machine learning approach to predict knockdown efficiencies. A more detailed description of the different binding sites, we characterized can be found in our [https://2010.igem.org/Team:Heidelberg/Project/miMeasure measurements] page. | ||
==Methods== | ==Methods== |
Revision as of 16:10, 27 October 2010
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