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Development of a Kinetic Assay for Late Endosome Movement.

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/persons/resource/persons219142

Esner,  Milan
Max Planck Institute of Molecular Cell Biology and Genetics, Max Planck Society;

/persons/resource/persons219446

Meyenhofer,  Felix
Max Planck Institute of Molecular Cell Biology and Genetics, Max Planck Society;

/persons/resource/persons219354

Kuhn,  Michael
Max Planck Institute of Molecular Cell Biology and Genetics, Max Planck Society;

/persons/resource/persons219734

Thomas,  Melissa
Max Planck Institute of Molecular Cell Biology and Genetics, Max Planck Society;

/persons/resource/persons219285

Kalaidzidis,  Yannis
Max Planck Institute of Molecular Cell Biology and Genetics, Max Planck Society;

/persons/resource/persons219009

Bickle,  Marc
Max Planck Institute of Molecular Cell Biology and Genetics, Max Planck Society;

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Citation

Esner, M., Meyenhofer, F., Kuhn, M., Thomas, M., Kalaidzidis, Y., & Bickle, M. (2014). Development of a Kinetic Assay for Late Endosome Movement. Journal of Biomolecular Screening, 19(7), 1070-1078.


Cite as: https://hdl.handle.net/21.11116/0000-0001-0562-B
Abstract
Automated imaging screens are performed mostly on fixed and stained samples to simplify the workflow and increase throughput. Some processes, such as the movement of cells and organelles or measuring membrane integrity and potential, can be measured only in living cells. Developing such assays to screen large compound or RNAi collections is challenging in many respects. Here, we develop a live-cell high-content assay for tracking endocytic organelles in medium throughput. We evaluate the added value of measuring kinetic parameters compared with measuring static parameters solely. We screened 2000 compounds in U-2 OS cells expressing Lamp1-GFP to label late endosomes. All hits have phenotypes in both static and kinetic parameters. However, we show that the kinetic parameters enable better discrimination of the mechanisms of action. Most of the compounds cause a decrease of motility of endosomes, but we identify several compounds that increase endosomal motility. In summary, we show that kinetic data help to better discriminate phenotypes and thereby obtain more subtle phenotypic clustering.