![]() Each of the 406 multi-well plates was imaged using an ImageXpress Micro XLS automated microscope (Molecular Devices, Sunnyvale, CA, USA), with 5 fluorescent channels at ×20 magnification, and 6 fields of view (sites) imaged per well (Table 1). After incubation, the cells were fixed with formaldehyde, permeabilized with Triton X-100, and stained with the remaining dyes to identify the nucleus (Hoechst), nucleoli and cytoplasmic RNA (SYTO 14), endoplasmic reticulum (concanavalin A), Golgi and plasma membrane (wheat germ agglutinin), and the actin cytoskeleton (phalloidin). Live cell staining was first performed to stain the mitochondria. Of these compounds, 10 080 compounds came from the Molecular Libraries Small Molecule Repository (MLSMR), 2260 were drugs, natural products, and small-molecule probes that are part of the Broad Institute known bioactive compound collection, 269 were confirmed screening hits from the Molecular Libraries Program (MLP), and 18 051 were novel compounds derived from diversity-oriented synthesis. Briefly, U2OS cells were plated in 384-well plates, then treated with each of 30 616 compounds in quadruplicate. The protocols for staining and imaging have been described in detail elsewhere. The columns display the 5 channels imaged in the Cell Painting assay protocol (see Table 1 for details about the stains and channels imaged). Images are shown from a DMSO well (negative control, top row) and a parbendazole well (bottom row). ![]() Sample images of U2OS cells from the small-molecule Cell Painting experiment. Balancing technical and cost considerations, we developed the Cell Painting assay protocol, in which cells are stained for 8 major organelles and sub-compartments, using a mixture of 6 well-characterized fluorescent dyes suited for use in high throughput (Fig. To maximize the morphological information extracted from a single assay, we sought to “paint the cell” with as many distinct fluorescent morphological markers as possible simultaneously. Data acquisition protocol and quality control Integration of this dataset with datasets resulting from other types of perturbations (e.g., patient cell samples or genetically perturbed samples) enables identification of small-molecule mimetics of particular disease- or gene-related phenotypes that could be useful as probes or potential starting points for development of future potential therapeutics. A dataset comprising small-molecule perturbations, as presented here, can be used for small-molecule library enrichment (to create smaller libraries while retaining high diversity of phenotypic impact) and small-molecule mechanism-of-action studies, including target identification. The applications of image-based profiling are many and diverse. Further analysis then aggregates the data into multivariate profiles of these features to compare signatures among sample treatments. The “Cell Painting” assay used for the dataset presented here uses fluorescent markers to broadly stain a number of cellular structures in high-throughput format, while automated software extracts the single-cell image-based morphological features. In contrast to a screening strategy, where a usually limited number of features are quantified to select for a known cellular phenotype, profiling relies on collecting a large suite of per-cell morphological features and then using statistical analysis to uncover subtle morphological patterns (“signatures”) by which the perturbations can be characterized. Phenotypic profiling has emerged as a powerful tool to discern subtle differences among treated samples in a relatively unbiased manner. ![]() In this way, the morphological characteristics (or “phenotype”) of cells, tissues, or even whole organisms can be examined, along with the concomitant changes induced by the perturbants of choice. ![]() Ī typical imaging assay uses several fluorescent probes (or fluorescently tagged proteins) simultaneously with stain cells, each labeling distinct cellular components in each sample. Concurrently, the advent of high-throughput imaging has also become an engine for pharmacological screening and basic research by allowing multiparametric image-based interrogation of physiological processes at a large scale. While microscopy has enriched our understanding of biology for centuries, only recently has robotic sample preparation and microscopy equipment become widely available, together with large libraries of chemical and genetic perturbations. High-throughput quantitative analysis of cellular image data has led to critical insights across many fields in biology.
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