Clusters of bioactive compounds target dynamic endomembrane networks in vivo. Drakakaki, G., Robert, S., Szatmari, A., Brown, M. Q., Nagawa, S., Damme, D. V., Leonard, M., Yang, Z., Girke, T., Schmid, S. L., Russinova, E., Friml, J., Raikhel, N. V., & Hicks, G. R. Proceedings of the National Academy of Sciences, 108(43):17850–17855, October, 2011. Publisher: National Academy of Sciences Section: Biological Sciences![Clusters of bioactive compounds target dynamic endomembrane networks in vivo [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex 1 download Endomembrane trafficking relies on the coordination of a highly complex, dynamic network of intracellular vesicles. Understanding the network will require a dissection of cargo and vesicle dynamics at the cellular level in vivo. This is also a key to establishing a link between vesicular networks and their functional roles in development. We used a high-content intracellular screen to discover small molecules targeting endomembrane trafficking in vivo in a complex eukaryote, Arabidopsis thaliana. Tens of thousands of molecules were prescreened and a selected subset was interrogated against a panel of plasma membrane (PM) and other endomembrane compartment markers to identify molecules that altered vesicle trafficking. The extensive image dataset was transformed by a flexible algorithm into a marker-by-phenotype-by-treatment time matrix and revealed groups of molecules that induced similar subcellular fingerprints (clusters). This matrix provides a platform for a systems view of trafficking. Molecules from distinct clusters presented avenues and enabled an entry point to dissect recycling at the PM, vacuolar sorting, and cell-plate maturation. Bioactivity in human cells indicated the value of the approach to identifying small molecules that are active in diverse organisms for biology and drug discovery.
@article{drakakaki_clusters_2011,
title = {Clusters of bioactive compounds target dynamic endomembrane networks in vivo},
volume = {108},
issn = {0027-8424, 1091-6490},
url = {https://www.pnas.org/content/108/43/17850},
doi = {10/bf5jvk},
abstract = {Endomembrane trafficking relies on the coordination of a highly complex, dynamic network of intracellular vesicles. Understanding the network will require a dissection of cargo and vesicle dynamics at the cellular level in vivo. This is also a key to establishing a link between vesicular networks and their functional roles in development. We used a high-content intracellular screen to discover small molecules targeting endomembrane trafficking in vivo in a complex eukaryote, Arabidopsis thaliana. Tens of thousands of molecules were prescreened and a selected subset was interrogated against a panel of plasma membrane (PM) and other endomembrane compartment markers to identify molecules that altered vesicle trafficking. The extensive image dataset was transformed by a flexible algorithm into a marker-by-phenotype-by-treatment time matrix and revealed groups of molecules that induced similar subcellular fingerprints (clusters). This matrix provides a platform for a systems view of trafficking. Molecules from distinct clusters presented avenues and enabled an entry point to dissect recycling at the PM, vacuolar sorting, and cell-plate maturation. Bioactivity in human cells indicated the value of the approach to identifying small molecules that are active in diverse organisms for biology and drug discovery.},
language = {en},
number = {43},
urldate = {2021-06-08},
journal = {Proceedings of the National Academy of Sciences},
author = {Drakakaki, Georgia and Robert, Stéphanie and Szatmari, Anna-Maria and Brown, Michelle Q. and Nagawa, Shingo and Damme, Daniel Van and Leonard, Marilyn and Yang, Zhenbiao and Girke, Thomas and Schmid, Sandra L. and Russinova, Eugenia and Friml, Jiří and Raikhel, Natasha V. and Hicks, Glenn R.},
month = oct,
year = {2011},
pmid = {22006339},
note = {Publisher: National Academy of Sciences
Section: Biological Sciences},
keywords = {chemical genomics, endosidin, endosome, high content screen},
pages = {17850--17855},
}
Downloads: 1
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