Related Experiment Video
Updated: Oct 5, 2025
07:55
High Throughput Yeast Strain Phenotyping with Droplet-Based RNA Sequencing
Published on: May 21, 2020
7.1K
High-throughput platform for yeast morphological profiling predicts the targets of bioactive compounds
Shinsuke Ohnuki1, Itsuki Ogawa1, Kaori Itto-Nakama1
1Department of Integrated Biosciences, Graduate School of Frontier Sciences, University of Tokyo, Kashiwa, Chiba, 277-8561, Japan.
NPJ Systems Biology and Applications
|January 28, 2022
Summary
We developed a high-throughput platform for yeast morphological profiling to predict chemical compound targets. This tool aids drug discovery by identifying compound mechanisms of action and potential applications, such as antifungal agents.
Area of Science:
- Cell biology
- Genomics
- Drug discovery
Background:
- Morphological profiling is an omics-based method for predicting intracellular compound targets.
- Existing methods require significant compound use and can be slow for large-scale screening.
Purpose of the Study:
- To develop a reliable high-throughput (HT) platform for yeast morphological profiling.
- To enable efficient prediction of compound targets and mechanisms of action.
- To explore the potential of a novel compound, poacidiene, as an antifungal agent.
Main Methods:
- Utilized drug-hypersensitive yeast strains to minimize compound usage.
- Employed high-throughput microscopy for rapid data acquisition and analysis.
- Applied a generalized linear model for reliable target prediction.
Main Results:
- Successfully validated the platform using six known compounds.
- Predicted poacidiene affects the DNA damage response, confirmed by genetic analysis.
- Demonstrated poacidiene's potent inhibition of phytopathogenic fungi growth.
Conclusions:
- The developed HT morphological profiling platform is an effective whole-cell target prediction tool.
- Poacidiene exhibits potential as a novel antifungal agent.
- This platform accelerates drug discovery by enabling rapid mechanism of action elucidation.
