Discovery of JNJ-63576253, a Next-Generation Androgen Receptor Antagonist Active Against Wild-Type and Clinically Relevant Ligand Binding Domain Mutations in Metastatic Castration-Resistant Prostate Cancer.

Numerous mechanisms of resistance arise in response to treatment with second-generation androgen receptor (AR) pathway inhibitors in metastatic castration-resistant prostate cancer (mCRPC). Among these, point mutations in the ligand binding domain can transform antagonists into agonists, driving the disease through activation of AR signaling. To address this unmet need, we report the discovery of JNJ-63576253, a next-generation AR pathway inhibitor that potently abrogates AR signaling in models of human prostate adenocarcinoma.

Tales of 1,008 small molecules: phenomic profiling through live-cell imaging in a panel of reporter cell lines.

Phenomic profiles are high-dimensional sets of readouts that can comprehensively capture the biological impact of chemical and genetic perturbations in cellular assay systems. Phenomic profiling of compound libraries can be used for compound target identification or mechanism of action (MoA) prediction and other applications in drug discovery. To devise an economical set of phenomic profiling assays, we assembled a library of 1,008 approved drugs and well-characterized tool compounds manually annotated to 218 unique MoAs, and we profiled each compound at four concentrations in live-cell, high-content imaging screens against a panel of 15 reporter cell lines, which expressed a diverse set of fluorescent organelle and pathway markers in three distinct cell lineages.

PREDECT Protocols for Complex 2D/3D Cultures.

PREDECT, a European IMI consortium, has assumed the task to generate robust 2D and 3D culture platforms. Protocols established for 2D and 3D monoculture and stromal coculture models of increasing complexity (spheroid, stirred-tank bioreactor, Matrigel- and collagen-embedded cultures) have been established between six laboratories within academia, biotech, and pharma. These models were tested using three tumor cell lines (MCF7, LNCaP, and NCI-H1437), covering three pathologies (breast, prostate, and lung), but should be readily transferable to other model systems.

Integrating images from multiple microscopy screens reveals diverse patterns of change in the subcellular localization of proteins.

The evaluation of protein localization changes on a systematic level is a powerful tool for understanding how cells respond to environmental, chemical, or genetic perturbations. To date, work in understanding these proteomic responses through high-throughput imaging has catalogued localization changes independently for each perturbation. To distinguish changes that are targeted responses to the specific perturbation or more generalized programs, we developed a scalable approach to visualize the localization behavior of proteins across multiple experiments as a quantitative pattern.

Repurposing High-Throughput Image Assays Enables Biological Activity Prediction for Drug Discovery.

In both academia and the pharmaceutical industry, large-scale assays for drug discovery are expensive and often impractical, particularly for the increasingly important physiologically relevant model systems that require primary cells, organoids, whole organisms, or expensive or rare reagents. We hypothesized that data from a single high-throughput imaging assay can be repurposed to predict the biological activity of compounds in other assays, even those targeting alternate pathways or biological processes. Indeed, quantitative information extracted from a three-channel microscopy-based screen for glucocorticoid receptor translocation was able to predict assay-specific biological activity in two ongoing drug discovery projects.

Ellipsoid Segmentation Model for Analyzing Light-Attenuated 3D Confocal Image Stacks of Fluorescent Multi-Cellular Spheroids.

In oncology, two-dimensional in-vitro culture models are the standard test beds for the discovery and development of cancer treatments, but in the last decades, evidence emerged that such models have low predictive value for clinical efficacy. Therefore they are increasingly complemented by more physiologically relevant 3D models, such as spheroid micro-tumor cultures. If suitable fluorescent labels are applied, confocal 3D image stacks can characterize the structure of such volumetric cultures and, for example, cell proliferation.

Liquid Growth of Arrayed Fluorescently Tagged Saccharomyces cerevisiae Strains for Live-Cell High-Throughput Microscopy Screens.

This protocol describes culturing arrays of fluorescently tagged yeast strains to early log-phase in a 96-well format for imaging on a high-throughput (HTP) microscope. The method assumes the use of the synthetic genetic array (SGA) technique to create the array of marked strains. When this approach is coupled with automated image analysis, the subcellular distribution and abundance of tagged proteins can be systematically and quantitatively examined in different genetic backgrounds and/or under different growth regimes.

CYCLoPs: A Comprehensive Database Constructed from Automated Analysis of Protein Abundance and Subcellular Localization Patterns in Saccharomyces cerevisiae.

Changes in protein subcellular localization and abundance are central to biological regulation in eukaryotic cells. Quantitative measures of protein dynamics in vivo are therefore highly useful for elucidating specific regulatory pathways. Using a combinatorial approach of yeast synthetic genetic array technology, high-content screening, and machine learning classifiers, we developed an automated platform to characterize protein localization and abundance patterns from images of log phase cells from the open-reading frame-green fluorescent protein collection in the budding yeast, Saccharomyces cerevisiae.

Yeast Proteome Dynamics from Single Cell Imaging and Automated Analysis.

Proteomics has proved invaluable in generating large-scale quantitative data; however, the development of systems approaches for examining the proteome in vivo has lagged behind. To evaluate protein abundance and localization on a proteome scale, we exploited the yeast GFP-fusion collection in a pipeline combining automated genetics, high-throughput microscopy, and computational feature analysis. We developed an ensemble of binary classifiers to generate localization data from single-cell measurements and constructed maps of ∼3,000 proteins connected to 16 localization classes.

Local statistics allow quantification of cell-to-cell variability from high-throughput microscope images.

Motivation: Quantifying variability in protein expression is a major goal of systems biology and cell-to-cell variability in subcellular localization pattern has not been systematically quantified.

Results: We define a local measure to quantify cell-to-cell variability in high-throughput microscope images and show that it allows comparable measures of variability for proteins with diverse subcellular localizations. We systematically estimate cell-to-cell variability in the yeast GFP collection and identify examples of proteins that show cell-to-cell variability in their subcellular localization.

Unsupervised clustering of subcellular protein expression patterns in high-throughput microscopy images reveals protein complexes and functional relationships between proteins.

Protein subcellular localization has been systematically characterized in budding yeast using fluorescently tagged proteins. Based on the fluorescence microscopy images, subcellular localization of many proteins can be classified automatically using supervised machine learning approaches that have been trained to recognize predefined image classes based on statistical features. Here, we present an unsupervised analysis of protein expression patterns in a set of high-resolution, high-throughput microscope images.

Exploring the yeast acetylome using functional genomics.

Lysine acetylation is a dynamic posttranslational modification with a well-defined role in regulating histones. The impact of acetylation on other cellular functions remains relatively uncharacterized. We explored the budding yeast acetylome with a functional genomics approach, assessing the effects of gene overexpression in the absence of lysine deacetylases (KDACs).

Proteome-wide screens in Saccharomyces cerevisiae using the yeast GFP collection.

The budding yeast is a simple and genetically tractable eukaryotic organism. It remains a leading system for functional genomic work and has been the focus of many pioneering efforts, including the systematic construction and analysis of gene deletion mutants. Over the past decade, many large-scale studies have made use of the deletion and other mutant collections to assay genetic interactions, chemical sensitivities, and other phenotypes, contributing enormously to our understanding of gene function.

A quantitative literature-curated gold standard for kinase-substrate pairs.

We describe the Yeast Kinase Interaction Database (KID, http://www.moseslab.csb.

A novel mechanism for SUMO system control: regulated Ulp1 nucleolar sequestration.

The small ubiquitin-related modifiers (SUMOs) are evolutionarily conserved polypeptides that are covalently conjugated to protein targets to modulate their subcellular localization, half-life, or activity. Steady-state SUMO conjugation levels increase in response to many different types of environmental stresses, but how the SUMO system is regulated in response to these insults is not well understood. Here, we characterize a novel mode of SUMO system control: in response to elevated alcohol levels, the Saccharomyces cerevisiae SUMO protease Ulp1 is disengaged from its usual location at the nuclear pore complex (NPC) and sequestered in the nucleolus.

Characterization of the Arabidopsis thaliana exocyst complex gene families by phylogenetic, expression profiling, and subcellular localization studies.

*The exocyst is a complex of eight proteins (Sec3p, Sec5p, Sec6p, Sec8p, Sec10p, Sec15p, Exo70p and Exo84p) involved in tethering vesicles to the plasma membrane during regulated or polarized secretion. Here, the plant exocyst complex was explored in phylogenetic, expression, and subcellular localization studies. *Evolutionary relationships of predicted exocyst subunits were examined in the complete genomes of Arabidopsis thaliana, Oryza sativa, Populus trichocarpa and Physcomitrella patens.

Cellular pathways regulating responses to compatible and self-incompatible pollen in Brassica and Arabidopsis stigmas intersect at Exo70A1, a putative component of the exocyst complex.

In the Brassicaceae, compatible pollen-pistil interactions result in pollen adhesion to the stigma, while pollen grains from unrelated plant species are largely ignored. There can also be an additional layer of recognition to prevent self-fertilization, the self-incompatibility response, whereby self pollen grains are distinguished from nonself pollen grains and rejected. This pathway is activated in the stigma and involves the ARM repeat-containing 1 (ARC1) protein, an E3 ubiquitin ligase.