The multidimensional perturbation value: a single metric to measure similarity and activity of treatments in high-throughput multidimensional screens

High throughput screening of mesenchymal stromal cell morphological response to inflammatory signals for bioreactor-based manufacturing of extracellular vesicles that modulate microglia

Due to their immunomodulatory function, mesenchymal stromal cells (MSCs) are a promising therapeutic with the potential to treat neuroinflammation associated with neurodegenerative diseases. This function is mediated by secreted extracellular vesicles (MSC-EVs). Despite established safety, MSC clinical translation has been unsuccessful due to inconsistent clinical outcomes resulting from functional heterogeneity. Current approaches to mitigate functional heterogeneity include 'priming' MSCs with inflammatory signals to enhance function. However, comprehensive evaluation of priming and its effects on MSC-EV function has not been performed. Furthermore, clinical translation of MSC-EV therapies requires significant manufacturing scale-up, yet few studies have investigated the effects of priming in bioreactors. As MSC morphology has been shown to predict their immunomodulatory function, we screened MSC morphological response to an array of priming signals and evaluated MSC-EV identity and potency in response to priming in flasks and bioreactors. We identified unique priming conditions corresponding to distinct morphologies. These conditions demonstrated a range of MSC-EV preparation quality and lipidome, allowing us to discover a novel MSC-EV manufacturing condition, as well as gain insight into potential mechanisms of MSC-EV microglia modulation. Our novel screening approach and application of priming to MSC-EV bioreactor manufacturing informs refinement of larger-scale manufacturing and enhancement of MSC-EV function.

A versatile information retrieval framework for evaluating profile strength and similarity

In profiling assays, thousands of biological properties are measured in a single test, yielding biological discoveries by capturing the state of a cell population, often at the single-cell level. However, for profiling datasets, it has been challenging to evaluate the phenotypic activity of a sample and the phenotypic consistency among samples, due to profiles' high dimensionality, heterogeneous nature, and non-linear properties. Existing methods leave researchers uncertain where to draw boundaries between meaningful biological response and technical noise. Here, we developed a statistical framework that uses the well-established mean average precision (mAP) as a single, data-driven metric to bridge this gap. We validated the mAP framework against established metrics through simulations and real-world data applications, revealing its ability to capture subtle and meaningful biological differences in cell state. Specifically, we used mAP to assess both phenotypic activity for a given perturbation (or a sample) as well as consistency within groups of perturbations (or samples) across diverse high-dimensional datasets. We evaluated the framework on different profile types (image, protein, and mRNA profiles), perturbation types (CRISPR gene editing, gene overexpression, and small molecules), and profile resolutions (single-cell and bulk). Our open-source software allows this framework to be applied to identify interesting biological phenomena and promising therapeutics from large-scale profiling data.

An Enantioselective Aminocatalytic Cascade Reaction Affording Bioactive Hexahydroazulene Scaffolds

A novel cascade reaction initiated by an enantioselective aminocatalysed 1,3-dipolar [6+4] cycloaddition between catalytically generated trienamines and 3-oxidopyridinium betaines is presented. The [6+4] cycloadduct spontaneously undergoes an intramolecular enamine-mediated aldol, hydrolysis, and E1cb sequence, which ultimately affords a chiral hexahydroazulene framework. In this process, three new C-C bonds and three new stereocenters are formed, enabled by a formal unfolding of the pyridine moiety from the dipolar reagent. The hexahydroazulenes are formed with excellent diastereo-, regio- and periselectivity (>20 : 1), up to 96 % ee, and yields up to 52 %. Synthetic elaborations of this scaffold were performed, providing access to a variety of functionalised hydroazulene compounds, of which some were found to display biological activity in U-2OS osteosarcoma cells in cell painting assays.

High throughput screening of mesenchymal stromal cell morphological response to inflammatory signals for bioreactor-based manufacturing of extracellular vesicles that modulate microglia

Due to their immunomodulatory function, mesenchymal stromal cells (MSCs) are a promising therapeutic with the potential to treat neuroinflammation associated with neurodegenerative diseases. This function can be mediated by secreted extracellular vesicles (MSC-EVs). Despite established safety, MSC clinical translation has been unsuccessful due to inconsistent clinical outcomes resulting from functional heterogeneity. Current approaches to mitigate functional heterogeneity include 'priming' MSCs with inflammatory signals to enhance function. However, comprehensive evaluation of priming and its effects on MSC-EV function has not been performed. Clinical translation of MSC-EV therapies requires significant manufacturing scale-up, yet few studies have investigated the effects of priming in bioreactors. As MSC morphology has been shown to predict their immunomodulatory function, we screened MSC morphological response to an array of priming signals and evaluated MSC-EV identity and potency in response to priming in flasks and bioreactors. We identified unique priming conditions corresponding to distinct morphologies. These conditions demonstrated a range of MSC-EV preparation quality and lipidome, allowing us to discover a novel MSC-EV manufacturing condition, as well as gain insight into potential mechanisms of MSC-EV microglia modulation. Our novel screening approach and application of priming to MSC-EV bioreactor manufacturing informs refinement of larger-scale manufacturing and enhancement of MSC-EV function.

Reference compounds for characterizing cellular injury in high-content cellular morphology assays

Robust, generalizable approaches to identify compounds efficiently with undesirable mechanisms of action in complex cellular assays remain elusive. Such a process would be useful for hit triage during high-throughput screening and, ultimately, predictive toxicology during drug development. Here we generate cell painting and cellular health profiles for 218 prototypical cytotoxic and nuisance compounds in U-2 OS cells in a concentration-response format. A diversity of compounds that cause cellular damage produces bioactive cell painting morphologies, including cytoskeletal poisons, genotoxins, nonspecific electrophiles, and redox-active compounds. Further, we show that lower quality lysine acetyltransferase inhibitors and nonspecific electrophiles can be distinguished from more selective counterparts. We propose that the purposeful inclusion of cytotoxic and nuisance reference compounds such as those profiled in this resource will help with assay optimization and compound prioritization in complex cellular assays like cell painting.

BioProfiling.jl: profiling biological perturbations with high-content imaging in single cells and heterogeneous populations

MOTIVATION

High-content imaging screens provide a cost-effective and scalable way to assess cell states across diverse experimental conditions. The analysis of the acquired microscopy images involves assembling and curating raw cellular measurements into morphological profiles suitable for testing biological hypotheses. Despite being a critical step, general-purpose and adaptable tools for morphological profiling are lacking and no solution is available for the high-performance Julia programming language.

RESULTS

Here, we introduce BioProfiling.jl, an efficient end-to-end solution for compiling and filtering informative morphological profiles in Julia. The package contains all the necessary data structures to curate morphological measurements and helper functions to transform, normalize and visualize profiles. Robust statistical distances and permutation tests enable quantification of the significance of the observed changes despite the high fraction of outliers inherent to high-content screens. This package also simplifies visual artifact diagnostics, thus streamlining a bottleneck of morphological analyses. We showcase the features of the package by analyzing a chemical imaging screen, in which the morphological profiles prove to be informative about the compounds' mechanisms of action and can be conveniently integrated with the network localization of molecular targets.

AVAILABILITY AND IMPLEMENTATION

The Julia package is available on GitHub: https://github.com/menchelab/BioProfiling.jl. We also provide Jupyter notebooks reproducing our analyses: https://github.com/menchelab/BioProfilingNotebooks. The data underlying this article are available from FigShare, at https://doi.org/10.6084/m9.figshare.14784678.v2.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Morphological profiling of human T and NK lymphocytes by high-content cell imaging

The immunological synapse is a complex structure that decodes stimulatory signals into adapted lymphocyte responses. It is a unique window to monitor lymphocyte activity because of development of systematic quantitative approaches. Here we demonstrate the applicability of high-content imaging to human T and natural killer (NK) cells and develop a pipeline for unbiased analysis of high-definition morphological profiles. Our approach reveals how distinct facets of actin cytoskeleton remodeling shape immunological synapse architecture and affect lytic granule positioning. Morphological profiling of CD8⁺ T cells from immunodeficient individuals allows discrimination of the roles of the ARP2/3 subunit ARPC1B and the ARP2/3 activator Wiskott-Aldrich syndrome protein (WASP) in immunological synapse assembly. Single-cell analysis further identifies uncoupling of lytic granules and F-actin radial distribution in ARPC1B-deficient lymphocytes. Our study provides a foundation for development of morphological profiling as a scalable approach to monitor primary lymphocyte responsiveness and to identify complex aspects of lymphocyte micro-architecture.

Organocatalytic Asymmetric Multicomponent Cascade Reaction for the Synthesis of Contiguously Substituted Tetrahydronaphthols

Isobenzopyrylium ions are unique, highly reactive, aromatic intermediates which are largely unexplored in asymmetric catalysis despite their high potential synthetic utility. In this study, an organocatalytic asymmetric multicomponent cascade via dienamine catalysis, involving a cycloaddition, a nucleophilic addition, and a ring-opening reaction, is disclosed. The reaction furnishes chiral tetrahydronaphthols containing four contiguous stereocenters in good to high yield, high diastereoselectivity (up to >20:1), and excellent enantioselectivity (93-98% ee). The obtained products are important synthetic intermediates, and it is demonstrated that they can be used for the generation of frameworks such as octahydrobenzo[h]isoquinoline and [2.2.2]octane scaffolds. Furthermore, mechanistic experiments involving oxygen-18-labeling studies and density functional theory calculations provide a vivid picture of the reaction mechanism. Finally, the bioactivity of 16 representative tetrahydronaphthol compounds has been evaluated in U-2OS cancer cells with some compounds showing a unique profile and a clear morphological change.

Morphological profiling of small molecules

Profiling approaches such as gene expression or proteome profiling generate small-molecule bioactivity profiles that describe a perturbed cellular state in a rather unbiased manner and have become indispensable tools in the evaluation of bioactive small molecules. Automated imaging and image analysis can record morphological alterations that are induced by small molecules through the detection of hundreds of morphological features in high-throughput experiments. Thus, morphological profiling has gained growing attention in academia and the pharmaceutical industry as it enables detection of bioactivity in compound collections in a broader biological context in the early stages of compound development and the drug-discovery process. Profiling may be used successfully to predict mode of action or targets of unexplored compounds and to uncover unanticipated activity for already characterized small molecules. Here, we review the reported approaches to morphological profiling and the kind of bioactivity that can be detected so far and, thus, predicted.

Expanding the antibacterial selectivity of polyether ionophore antibiotics through diversity-focused semisynthesis

Polyether ionophores are complex natural products capable of transporting cations across biological membranes. Many polyether ionophores possess potent antimicrobial activity and a few selected compounds have ability to target aggressive cancer cells. Nevertheless, ionophore function is believed to be associated with idiosyncratic cellu-lar toxicity and, consequently, human clinical development has not been pursued. Here, we demonstrate that structurally novel polyether ionophores can be efficiently constructed by recycling components of highly abundant polyethers to afford analogues with enhanced anti-bacterial selectivity compared to a panel of natural polyether ionophores. We used classic degradation reactions of the natural polyethers lasalocid and monensin and combined the resulting fragments with building blocks provided by total synthesis, including halogen-functionalized tetronic acids as cation-binding groups. Our results suggest that structural optimization of polyether ionophores is possible and that this area represents a potential opportunity for future methodological innovation.

SARS-CoV2-mediated suppression of NRF2-signaling reveals potent antiviral and anti-inflammatory activity of 4-octyl-itaconate and dimethyl fumarate

Antiviral strategies to inhibit Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV2) and the pathogenic consequences of COVID-19 are urgently required. Here, we demonstrate that the NRF2 antioxidant gene expression pathway is suppressed in biopsies obtained from COVID-19 patients. Further, we uncover that NRF2 agonists 4-octyl-itaconate (4-OI) and the clinically approved dimethyl fumarate (DMF) induce a cellular antiviral program that potently inhibits replication of SARS-CoV2 across cell lines. The inhibitory effect of 4-OI and DMF extends to the replication of several other pathogenic viruses including Herpes Simplex Virus-1 and-2, Vaccinia virus, and Zika virus through a type I interferon (IFN)-independent mechanism. In addition, 4-OI and DMF limit host inflammatory responses to SARS-CoV2 infection associated with airway COVID-19 pathology. In conclusion, NRF2 agonists 4-OI and DMF induce a distinct IFN-independent antiviral program that is broadly effective in limiting virus replication and in suppressing the pro-inflammatory responses of human pathogenic viruses, including SARS-CoV2.

Multiple Chemical Features Impact Biological Performance Diversity of a Highly Active Natural Product-Inspired Library

A systematic, diversity-oriented synthesis approach was employed to access a natural product-inspired flavonoid library with diverse chemical features, including chemical properties, scaffold, stereochemistry, and appendages. Using Cell Painting, the effects of these diversity elements were evaluated, and multiple chemical features that predict biological performance diversity were identified. Scaffold identity appears to be the dominant predictor of performance diversity, but stereochemistry and appendages also contribute to a lesser degree. In addition, the diversity of chemical properties contributed to performance diversity, and the driving chemical property was dependent on the scaffold. These results highlight the importance of key chemical features that may inform the creation of small-molecule, performance-diverse libraries to improve the efficiency and success of high-throughput screening campaigns.

Mapping the perturbome network of cellular perturbations

Drug combinations provide effective treatments for diverse diseases, but also represent a major cause of adverse reactions. Currently there is no systematic understanding of how the complex cellular perturbations induced by different drugs influence each other. Here, we introduce a mathematical framework for classifying any interaction between perturbations with high-dimensional effects into 12 interaction types. We apply our framework to a large-scale imaging screen of cell morphology changes induced by diverse drugs and their combination, resulting in a perturbome network of 242 drugs and 1832 interactions. Our analysis of the chemical and biological features of the drugs reveals distinct molecular fingerprints for each interaction type. We find a direct link between drug similarities on the cell morphology level and the distance of their respective protein targets within the cellular interactome of molecular interactions. The interactome distance is also predictive for different types of drug interactions.

Our understanding of the mechanisms of drug interactions remains limited. Here the authors introduce a framework to study how complex cellular perturbations induced by different drugs affect each other in morphological feature space.

Systematic Diversity-Oriented Synthesis of Reduced Flavones from γ-Pyrones to Probe Biological Performance Diversity

Diversity-oriented synthesis (DOS) has historically focused on the development of small-molecule collections with considerable chemical diversity with the hypothesis that chemical diversity will lead to diverse biological activities. We took a systematic approach to DOS to develop a focused library of reduced flavones from γ-pyrones with diversity of appendage, stereochemistry, and chemical properties to determine which features of small molecules are most predictive of biological performance diversity. The effects of these systematic modifications on biodiversity were determined using Cell Painting and cytotoxicity assays to compare the results of multiple methods of assessment. We observed that a greater fraction of sp³ hybridized atoms (fsp³) does not always lead to enhanced biodiversity, that stereochemistry and appendage diversity both contribute to biodiversity, and that lipophilicity of the pyrone class of compounds correlates with biodiversity. These results will contribute to the development of a general algorithm to predict which chemical features should be considered during the synthesis of DOS libraries to create biological performance-diverse collections of small molecules for probe and drug discovery.

Next generation diversity-oriented synthesis: a paradigm shift from chemical diversity to biological diversity

Diversity-oriented synthesis adds biological performance as a new diversity element.

The Cell Painting Assay as a Screening Tool for the Discovery of Bioactivities in New Chemical Matter

Multiparametric phenotypic screening based on cellular morphology interrogates many biological pathways simultaneously and is therefore a valuable screening tool for the discovery of new biological activities. The cell painting assay stains various cellular features using six different dyes in one well. By automated image analysis, hundreds of parameters are calculated from the images which deliver a phenotypic profile of the cell. It has been shown that compounds with similar modes of action deliver similar phenotypic profiles. Using a reference set of compounds with known modes of action, it is possible to assign probable modes of action to new compounds and to discover compounds with potentially new modes of action.Here we describe the cell painting assay as a screening tool using a hit identification workflow which has been implemented using open-source software.

Synergistic Effects of Stereochemistry and Appendages on the Performance Diversity of a Collection of Synthetic Compounds

Target- and phenotype-agnostic assessments of biological activity have emerged as viable strategies for prioritizing scaffolds, structural features, and synthetic pathways in screening sets, with the goal of increasing performance diversity. Here, we describe the synthesis of a small library of functionalized stereoisomeric azetidines and its biological annotation by "cell painting," a multiplexed, high-content imaging assay capable of measuring many hundreds of compound-induced changes in cell morphology in a quantitative and unbiased fashion. Using this approach, we systematically compare the degrees to which a core scaffold's biological activity, inferred from its effects on cell morphology, is affected by variations in stereochemistry and appendages. We show that stereoisomerism and appendage diversification can produce effects of similar magnitude, and that the concurrent use of these strategies results in a broader sampling of biological activity.

Data-analysis strategies for image-based cell profiling

Image-based cell profiling is a high-throughput strategy for the quantification of phenotypic differences among a variety of cell populations. It paves the way to studying biological systems on a large scale by using chemical and genetic perturbations. The general workflow for this technology involves image acquisition with high-throughput microscopy systems and subsequent image processing and analysis. Here, we introduce the steps required to create high-quality image-based (i.e., morphological) profiles from a collection of microscopy images. We recommend techniques that have proven useful in each stage of the data analysis process, on the basis of the experience of 20 laboratories worldwide that are refining their image-based cell-profiling methodologies in pursuit of biological discovery. The recommended techniques cover alternatives that may suit various biological goals, experimental designs, and laboratories' preferences.

SD, Verho O, Dandapani S, Wagner BK, Clemons PA, Booker-Milburn K, Boskovic ZV, Schreiber SL. Real-Time Biological Annotation of Synthetic Compounds

Organic chemists are able to synthesize molecules in greater number and chemical complexity than ever before. Yet, a majority of these compounds go untested in biological systems, and those that do are often tested long after the chemist can incorporate the results into synthetic planning. We propose the use of high-dimensional "multiplex" assays, which are capable of measuring thousands of cellular features in one experiment, to annotate rapidly and inexpensively the biological activities of newly synthesized compounds. This readily accessible and inexpensive "real-time" profiling method can be used in a prospective manner to facilitate, for example, the efficient construction of performance-diverse small-molecule libraries that are enriched in bioactives. Here, we demonstrate this concept by synthesizing ten triads of constitutionally isomeric compounds via complexity-generating photochemical and thermal rearrangements and measuring compound-induced changes in cellular morphology via an imaging-based "cell painting" assay. Our results indicate that real-time biological annotation can inform optimization efforts and library syntheses by illuminating trends relating to biological activity that would be difficult to predict if only chemical structure were considered. We anticipate that probe and drug discovery will benefit from the use of optimization efforts and libraries that implement this approach.

Distribution Analyzer, a methodology for identifying and clustering outlier conditions from single-cell distributions, and its application to a Nanog reporter RNAi screen

Background

Chemical or small interfering (si) RNA screens measure the effects of many independent experimental conditions, each applied to a population of cells (e.g., all of the cells in a well). High-content screens permit a readout (e.g., fluorescence, luminescence, cell morphology) from each cell in the population. Most analysis approaches compare the average effect on each population, precluding identification of outliers that affect the distribution of the reporter in the population but not its average. Other approaches only measure changes to the distribution with a single parameter, precluding accurate distinction and clustering of interesting outlier distributions.

Results

We describe a methodology to identify outlier conditions by considering the cell-level measurements from each condition as a sample of an underlying distribution. With appropriate selection of a distance metric, all effects can be embedded in a fixed-dimensionality Euclidean basis, facilitating identification and clustering of biologically interesting outliers. We demonstrate that measurement of distances with the Hellinger distance metric offers substantial computational efficiencies over alternative metrics. We validate this methodology using an RNA interference (RNAi) screen in mouse embryonic stem cells (ESC) with a Nanog reporter. The methodology clusters effects of multiple control siRNAs into their true identities better than conventional approaches describing the median cell fluorescence or the commonly used Kolmogorov-Smirnov distance between the observed fluorescence distribution and the null distribution. It identifies outlier genes with effects on the reporter distribution that would have been missed by other methods. Among them, siRNA targeting Chek1 leads to a wider Nanog reporter fluorescence distribution. Similarly, siRNA targeting Med14 or Med27 leads to a narrower Nanog reporter fluorescence distribution. We confirm the roles of these three genes in regulating pluripotency by mRNA expression and alkaline phosphatase staining using independent short hairpin (sh) RNAs.

Conclusions

Using our methodology, we describe each experimental condition by a probability distribution. Measuring distances between probability distributions permits a multivariate rather than univariate readout. Clustering points derived from these distances allows us to obtain greater biological insight than methods based solely on single parameters. We find several outliers from a mouse ESC RNAi screen that we confirm to be pluripotency regulators. Many of these outliers would have been missed by other analysis methods.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0636-7) contains supplementary material, which is available to authorized users.

Toward performance-diverse small-molecule libraries for cell-based phenotypic screening using multiplexed high-dimensional profiling

High-throughput screening has become a mainstay of small-molecule probe and early drug discovery. The question of how to build and evolve efficient screening collections systematically for cell-based and biochemical screening is still unresolved. It is often assumed that chemical structure diversity leads to diverse biological performance of a library. Here, we confirm earlier results showing that this inference is not always valid and suggest instead using biological measurement diversity derived from multiplexed profiling in the construction of libraries with diverse assay performance patterns for cell-based screens. Rather than using results from tens or hundreds of completed assays, which is resource intensive and not easily extensible, we use high-dimensional image-based cell morphology and gene expression profiles. We piloted this approach using over 30,000 compounds. We show that small-molecule profiling can be used to select compound sets with high rates of activity and diverse biological performance.

Novel Lignan and stilbenoid mixture shows anticarcinogenic efficacy in preclinical PC-3M-luc2 prostate cancer model

Prostate cancer is the most common cancer of men in the Western world, and novel approaches for prostate cancer risk reduction are needed. Plant-derived phenolic compounds attenuate prostate cancer growth in preclinical models by several mechanisms, which is in line with epidemiological findings suggesting that consumption of plant-based diets is associated with low risk of prostate cancer. The objective of this study was to assess the effects of a novel lignan-stilbenoid mixture in PC-3M-luc2 human prostate cancer cells in vitro and in orthotopic xenografts. Lignan and stilbenoid –rich extract was obtained from Scots pine (Pinus sylvestris) knots. Pine knot extract as well as stilbenoids (methyl pinosylvin and pinosylvin), and lignans (matairesinol and nortrachelogenin) present in pine knot extract showed antiproliferative and proapoptotic efficacy at ≥40 μM concentration in vitro. Furthermore, pine knot extract derived stilbenoids enhanced tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) induced apoptosis already at ≥10 μM concentrations. In orthotopic PC-3M-luc2 xenograft bearing immunocompromized mice, three-week peroral exposure to pine knot extract (52 mg of lignans and stilbenoids per kg of body weight) was well tolerated and showed anti-tumorigenic efficacy, demonstrated by multivariate analysis combining essential markers of tumor growth (i.e. tumor volume, vascularization, and cell proliferation). Methyl pinosylvin, pinosylvin, matairesinol, nortrachelogenin, as well as resveratrol, a metabolite of pinosylvin, were detected in serum at total concentration of 7−73 μM, confirming the bioavailability of pine knot extract derived lignans and stilbenoids. In summary, our data indicates that pine knot extract is a novel and cost-effective source of resveratrol, methyl pinosylvin and other bioactive lignans and stilbenoids. Pine knot extract shows anticarcinogenic efficacy in preclinical prostate cancer model, and our in vitro data suggests that compounds derived from the extract may have potential as novel chemosensitizers to TRAIL. These findings promote further research on health-related applications of wood biochemicals.

Multiparametric Analysis of Screening Data: Growing Beyond the Single Dimension to Infinity and Beyond

Advances in instrumentation now allow the development of screening assays that are capable of monitoring multiple readouts such as transcript or protein levels, or even multiple parameters derived from images. Such advances in assay technologies highlight the complex nature of biology and disease. Harnessing this complexity requires integration of all the different parameters that can be measured rather than just monitoring a single dimension as is commonly used. Although some of the methods used to combine multiple measurements, such as principal component analysis, are commonly used for microarray analysis, biologists are not yet using many of the tools that have been developed in other fields to address such issues. Visualization of multiparametric data sets is one of the major challenges in this field, and a depiction of the results in a manner that can be readily interpreted is essential. This article describes a number of assay systems being used to generate such data sets en masse, and the methods being applied to their visualization and analysis. We also discuss some of the challenges of applying methods developed in other fields to biology.

High-content analysis to leverage a robust phenotypic profiling approach to vascular modulation

Phenotypic screening seeks to identify substances that modulate phenotypes in a desired manner with the aim of progressing first-in-class agents. Successful campaigns require physiological relevance, robust screening, and an ability to deconvolute perturbed pathways. High-content analysis (HCA) is increasingly used in cell biology and offers one approach to prosecution of phenotypic screens, but challenges exist in exploitation where data generated are high volume and complex. We combine development of an organotypic model with novel HCA tools to map phenotypic responses to pharmacological perturbations. We describe implementation for angiogenesis, a process that has long been a focus for therapeutic intervention but has lacked robust models that recapitulate more completely mechanisms involved. The study used human primary endothelial cells in co-culture with stromal fibroblasts to model multiple aspects of angiogenic signaling: cell interactions, proliferation, migration, and differentiation. Multiple quantitative descriptors were derived from automated microscopy using custom-designed algorithms. Data were extracted using a bespoke informatics platform that integrates processing, statistics, and feature display into a streamlined workflow for building and interrogating fingerprints. Ninety compounds were characterized, defining mode of action by phenotype. Our approach for assessing phenotypic outcomes in complex assay models is robust and capable of supporting a range of phenotypic screens at scale.