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

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.

PIQUE: An ImageJ plugin for the quantification of toroidal nuclei in biological images

“…U2OS and HeLa cells were grown on sterile coverslips and fixed with 4% PFA for 10 minutes before counterstaining with DAPI for DNA detection, as explained previously (Pons et al, 2022). We acquired 100 images with a fluorescent microscope equipped with a 405 nm laser and a 40x air objective, containing nuclei of heterogeneous size and shape, with different levels of intensity saturation depending on their cell cycle phase when fixed.…”

“…Thus, further characterization of the toroidal nucleus demands the processing of large sets of images. However, quantification of toroidal nuclei currently relies on the manual analysis of fluorescent biological images (Pons et al, 2022), which is work-intensive and a limiting factor for large-scale analyses.…”

“…Characterization of these stimuli requires extensive comparisons across cell types and conditions. Also, the prevalence of the toroidal nucleus is not fully understood, and the existing collections of morphological images, both in human, like the Broad Institute image collection (Ljosa et al ., 2012), and yeast (Ohnuki et al ., 2022; Mattiazzi Usaj et al ., 2020), represent an invaluable resource to scan for its presence in very heterogeneous genetic backgrounds and conditions. Thus, further characterization of the toroidal nucleus demands the processing of large sets of images.…”

Deciphering the Biological Activities of Antifungal Agents with Chemical Probes

“…Interestingly, the mechanism of poacidiene differs from that of poacic acid despite the similarities in the structures of these compounds. Evidence suggests that poacidiene interferes with the DNA damage response [57] . The discovery of the antifungal properties of diferulate derivatives suggests that the byproducts generated during biomass processing for biofuel production should be evaluated for other valuable bioactive compounds.…”

Poacic Acid, a Plant-Derived Stilbenoid, Augments Cell Wall Chitin Production, but Its Antifungal Activity Is Hindered by This Polysaccharide and by Fungal Essential Metals

“…14,20,21 In 2022, another diferulate derivative, poacidiene (Scheme 1B), was identified as a novel antifungal agent by Ohya and coworkers. 23 Surprisingly, despite the high molecular similarity with PA, experimental evidence suggests that their mechanisms of action are fundamentally different. Morphological profiling of yeast cells treated with poacidiene implied that poacidiene impacts DNA damage response and not the yeast cell wall integrity, which was also supported by cell morphology and genetic analysis.…”