ArticlePloS one2016
A High-Content Larval Zebrafish Brain Imaging Method for Small Molecule Drug Discovery.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Article
- Observational
- Overview of Beneficial Effects of (Poly)phenol Metabolites in the Context of Neurodegenerative Diseases on Model Organisms.Nutrients · 2021Review
- A Mechanism-Based Targeted Screen To Identify Epstein-Barr Virus-Directed Antiviral Agents.Journal of virology · 2020Article
- Orthogonal Drug Pooling Enhances Phenotype-Based Discovery of Ocular Antiangiogenic Drugs in Zebrafish Larvae.Frontiers in pharmacology · 2019Review
- Article
- High-content screen using zebrafish (Danio rerio) embryos identifies a novel kinase activator and inhibitor.Bioorganic & medicinal chemistry letters · 2017Article
Corrections and comments
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Authors and funding
14 authors.
Funding
Abstract
Drug discovery in whole-organisms such as zebrafish is a promising approach for identifying biologically-relevant lead compounds. However, high content imaging of zebrafish at cellular resolution is challenging due to the difficulty in orienting larvae en masse such that the cell type of interest is in clear view. We report the development of the multi-pose imaging method, which uses 96-well round bottom plates combined with a standard liquid handler to repose the larvae within each well multiple times, such that an image in a specific orientation can be acquired. We have validated this method in a chemo-genetic zebrafish model of dopaminergic neuron degeneration. For this purpose, we have developed an analysis pipeline that identifies the larval brain in each image and then quantifies neuronal health in CellProfiler. Our method achieves a SSMD* score of 6.96 (robust Z'-factor of 0.56) and is suitable for screening libraries up to 105 compounds in size.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.