High-throughput platform for yeast morphological profiling predicts the targets of bioactive compounds

Shinsuke Ohnuki, Itsuki Ogawa, Kaori Itto-Nakama, Fachuang Lu, Ashish Ranjan, Mehdi Kabbage, Abraham Abera Gebre, Masao Yamashita, Sheena C. Li, Yoko Yashiroda, Satoshi Yoshida, Takeo Usui, Jeff S. Piotrowski, Brenda J. Andrews, Charles Boone, Grant W. Brown, John Ralph, Yoshikazu Ohya

Research output: Contribution to journalArticlepeer-review

Abstract

Morphological profiling is an omics-based approach for predicting intracellular targets of chemical compounds in which the dose-dependent morphological changes induced by the compound are systematically compared to the morphological changes in gene-deleted cells. In this study, we developed a reliable high-throughput (HT) platform for yeast morphological profiling using drug-hypersensitive strains to minimize compound use, HT microscopy to speed up data generation and analysis, and a generalized linear model to predict targets with high reliability. We first conducted a proof-of-concept study using six compounds with known targets: bortezomib, hydroxyurea, methyl methanesulfonate, benomyl, tunicamycin, and echinocandin B. Then we applied our platform to predict the mechanism of action of a novel diferulate-derived compound, poacidiene. Morphological profiling of poacidiene implied that it affects the DNA damage response, which genetic analysis confirmed. Furthermore, we found that poacidiene inhibits the growth of phytopathogenic fungi, implying applications as an effective antifungal agent. Thus, our platform is a new whole-cell target prediction tool for drug discovery.

Original languageEnglish (US)
Article number3
Journalnpj Systems Biology and Applications
Volume8
Issue number1
DOIs
StatePublished - Dec 2022

Bibliographical note

Funding Information:
We thank Seiko Morinaga for obtaining morphological data with high-throughput microscopy; Yuko Sukegawa, Taichi Kimura, and Karen Kubo for obtaining preliminary results; Mami Yoshimura and Hiromi Kimura for preparation of the rdh54Δ strain; and Kuninori Suzuki and other members of the Laboratory of Signal Transduction for helpful discussions. This work was supported by JSPS KAKENHI Grant Numbers JP15H04402 and JP19H03205 (Y.O.), JP15H04483 (C.B. and Y.O.), JP18K14351 (K.I.N.), and JP17H06411 (C.B. and Y.Y.); JST/OPERA (Y.O.) and the GAP fund of The University of Tokyo (Y.O.). F.L. and J.R. were funded by the DOE Great Lakes Bioenergy Research Center (DOE Office of Science BER DE-SC0018409). G.W.B was funded by the Canadian Institutes of Health Research (FDN-159913).

Publisher Copyright:
© 2022, The Author(s).

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