TY - JOUR
T1 - High-throughput platform for yeast morphological profiling predicts the targets of bioactive compounds
AU - Ohnuki, Shinsuke
AU - Ogawa, Itsuki
AU - Itto-Nakama, Kaori
AU - Lu, Fachuang
AU - Ranjan, Ashish
AU - Kabbage, Mehdi
AU - Gebre, Abraham Abera
AU - Yamashita, Masao
AU - Li, Sheena C.
AU - Yashiroda, Yoko
AU - Yoshida, Satoshi
AU - Usui, Takeo
AU - Piotrowski, Jeff S.
AU - Andrews, Brenda J.
AU - Boone, Charles
AU - Brown, Grant W.
AU - Ralph, John
AU - Ohya, Yoshikazu
N1 - Publisher Copyright:
© 2022, The Author(s).
PY - 2022/12
Y1 - 2022/12
N2 - 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.
AB - 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.
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U2 - 10.1038/s41540-022-00212-1
DO - 10.1038/s41540-022-00212-1
M3 - Article
C2 - 35087094
AN - SCOPUS:85123786667
SN - 2056-7189
VL - 8
JO - npj Systems Biology and Applications
JF - npj Systems Biology and Applications
IS - 1
M1 - 3
ER -