J 2014

Development of a Kinetic Assay for Late Endosome Movement

EŠNER, Milan; Felix MEYENHOFER; Michael KUHN; Melissa THOMAS; Yannis KALAIDZIDIS et al.

Základní údaje

Originální název

Development of a Kinetic Assay for Late Endosome Movement

Autoři

EŠNER, Milan ORCID; Felix MEYENHOFER; Michael KUHN; Melissa THOMAS; Yannis KALAIDZIDIS a Marc BICKLE

Vydání

Journal of Biomolecular Screening, Thousand Oaks, SAGE Publications Inc. 2014, 1087-0571

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

10600 1.6 Biological sciences

Stát vydavatele

Spojené státy

Utajení

není předmětem státního či obchodního tajemství

Impakt faktor

Impact factor: 2.423

Označené pro přenos do RIV

Ano

Kód RIV

RIV/00216224:14110/14:00077529

Organizační jednotka

Lékařská fakulta

EID Scopus

Klíčová slova anglicky

live cell; tracking; high-content imaging; Lamp1; cardiac glycoside

Štítky

Příznaky

Mezinárodní význam, Recenzováno
Změněno: 28. 11. 2014 13:19, Soňa Böhmová

Anotace

V originále

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.