Team:Berkeley

From 2012.igem.org

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  <p style="text-align:center; color:#CECECE;">Localization tags and promoter optimization.</p> </div>
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  <p style="text-align:center; color:#CECECE;">Localization tags, promoter optimization, and promoter characterization.</p> </div>
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<p style="text-align:center; color:#CECECE;">MiCode construction.</p></div>
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<p style="text-align:center; color:#CECECE;">MiCode construction using Golden Gate Assembly.</p></div>
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<p style="text-align:center; color:#CECECE;">Automation.</p> </div>
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<p style="text-align:center; color:#CECECE;">Automation with Matlab and Cell Profiler.</p> </div>
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  <p style="text-align:center; color:#CECECE;">Leucine Zippers.<br></p></div>
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  <p style="text-align:center; color:#CECECE;">Leucine Zippers affinity assay.<br></p></div>
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Revision as of 21:40, 26 September 2012

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iGEM Berkeley iGEMBerkeley iGEMBerkeley

Berkeley iGEM 2012

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Many applications in synthetic biology demand precise control over subcellular localization, cell morphology, motility, and other such phenotypes that are only observable via microscopy. At present, engineering these properties is challenging due in large part to the inherent throughput limitation imposed by microscopy. We have developed a strategy that enables high-throughput library screening with microscopy by coupling a unique fluorescence signature with each genotype present in a library. These MiCodes (microscopy barcodes) are generated by targeting combinations of fluorophores to several organelles within yeast, and they eliminate the need to isolate and observe clonal populations separately. MiCodes can potentially scale to library sizes of 10^6 or more, and their analysis can be largely automated using existing image processing software. As a proof of principle, we applied MiCodes to the problem of finding unique pairs of protein-protein interaction parts.

Localization tags, promoter optimization, and promoter characterization.

MiCode construction using Golden Gate Assembly.

Automation with Matlab and Cell Profiler.

Leucine Zippers affinity assay.


ACKNOWLEDGEMENTS

The UC Berkeley iGEM team would like to thank Agilent for their financial support and Synberc for their administrative support.