Image-based annotation of chemogenomic libraries for phenotypic screening
- Phenotypical screening is a widely used approach in drug discovery for the identification of small molecules with cellular activities. However, functional annotation of identified hits often poses a challenge. The development of small molecules with narrow or exclusive target selectivity such as chemical probes and chemogenomic (CG) libraries, greatly diminishes this challenge, but non-specific effects caused by compound toxicity or interference with basic cellular functions still pose a problem to associate phenotypic readouts with molecular targets. Hence, each compound should ideally be comprehensively characterized regarding its effects on general cell functions. Here, we report an optimized live-cell multiplexed assay that classifies cells based on nuclear morphology, presenting an excellent indicator for cellular responses such as early apoptosis and necrosis. This basic readout in combination with the detection of other general cell damaging activities of small molecules such as changes in cytoskeletal morphology, cell cycle and mitochondrial health provides a comprehensive time-dependent characterization of the effect of small molecules on cellular health in a single experiment. The developed high-content assay offers multi-dimensional comprehensive characterization that can be used to delineate generic effects regarding cell functions and cell viability, allowing an assessment of compound suitability for subsequent detailed phenotypic and mechanistic studies.
Author: | Amelie TjadenORCiD, Apirat ChaikuadORCiD, Eric KowarzORCiDGND, Rolf MarschalekORCiDGND, Stefan KnappORCiDGND, Martin SchröderORCiDGND, Susanne MüllerORCiD |
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URN: | urn:nbn:de:hebis:30:3-795962 |
DOI: | https://doi.org/10.3390/molecules27041439 |
ISSN: | 1420-3049 |
Parent Title (English): | Molecules |
Publisher: | MDPI |
Place of publication: | Basel |
Document Type: | Article |
Language: | English |
Date of Publication (online): | 2022/02/21 |
Date of first Publication: | 2022/02/21 |
Publishing Institution: | Universitätsbibliothek Johann Christian Senckenberg |
Release Date: | 2023/11/21 |
Tag: | cell cycle; chemogenomics; high content imaging; machine learning; phenotypic screening |
Volume: | 27 |
Issue: | 4, art. 1439 |
Article Number: | 1439 |
Page Number: | 21 |
First Page: | 1 |
Last Page: | 21 |
Note: | The authors received financial support for the research, authorship and publication of this article: All authors are supported by SGC, a registered charity (no. 1097737) that receives funds from Bayer AG, Boehringer Ingelheim, the Canada Foundation for Innovation, Eshelman Institute for Innovation, Genentech, Genome Canada through Ontario Genomics Institute [OGI-196], EU/EFPIA/OICR/McGill/KTH/Diamond, Innovative Medicines Initiative 2 Joint Undertaking [EUbOPEN grant 875510], Janssen, Merck KGaA (aka EMD in Canada and US), Pfizer, the Sao Paulo Research Foundation-FAPESP~ and Takeda as well as support from the German translational cancer network DKTK and the Frankfurt Cancer Institute (FCI). A.T. is supported by the SFB 1177 "Molecular and Functional Characterization of Selective Autophagy". |
HeBIS-PPN: | 516701975 |
Institutes: | Biochemie, Chemie und Pharmazie |
Fachübergreifende Einrichtungen / Buchmann Institut für Molekulare Lebenswissenschaften (BMLS) | |
Dewey Decimal Classification: | 5 Naturwissenschaften und Mathematik / 54 Chemie / 540 Chemie und zugeordnete Wissenschaften |
Sammlungen: | Universitätspublikationen |
Licence (German): | Creative Commons - CC BY - Namensnennung 4.0 International |