Identification of regulators of polyploidization presents therapeutic targets for treatment of AMKL.

The mechanism by which cells decide to skip mitosis to become polyploid is largely undefined. Here we used a high-content image-based screen to identify small-molecule probes that induce polyploidization of megakaryocytic leukemia cells and serve as perturbagens to help understand this process. Our study implicates five networks of kinases that regulate the switch to polyploidy. Moreover, we find that dimethylfasudil (diMF, H-1152P) selectively increased polyploidization, mature cell-surface marker expression, and apoptosis of malignant megakaryocytes. An integrated target identification approach employing proteomic and shRNA screening revealed that a major target of diMF is Aurora kinase A (AURKA). We further find that MLN8237 (Alisertib), a selective inhibitor of AURKA, induced polyploidization and expression of mature megakaryocyte markers in acute megakaryocytic leukemia (AMKL) blasts and displayed potent anti-AMKL activity in vivo. Our findings provide a rationale to support clinical trials of MLN8237 and other inducers of polyploidization and differentiation in AMKL.

Systematic, multiparametric analysis of Mycobacterium tuberculosis intracellular infection offers insight into coordinated virulence.

A key to the pathogenic success of Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis, is the capacity to survive within host macrophages. Although several factors required for this survival have been identified, a comprehensive knowledge of such factors and how they work together to manipulate the host environment to benefit bacterial survival are not well understood. To systematically identify Mtb factors required for intracellular growth, we screened an arrayed, non-redundant Mtb transposon mutant library by high-content imaging to characterize the mutant-macrophage interaction. Based on a combination of imaging features, we identified mutants impaired for intracellular survival. We then characterized the phenotype of infection with each mutant by profiling the induced macrophage cytokine response. Taking a systems-level approach to understanding the biology of identified mutants, we performed a multiparametric analysis combining pathogen and host phenotypes to predict functional relationships between mutants based on clustering. Strikingly, mutants defective in two well-known virulence factors, the ESX-1 protein secretion system and the virulence lipid phthiocerol dimycocerosate (PDIM), clustered together. Building upon the shared phenotype of loss of the macrophage type I interferon (IFN) response to infection, we found that PDIM production and export are required for coordinated secretion of ESX-1-substrates, for phagosomal permeabilization, and for downstream induction of the type I IFN response. Multiparametric clustering also identified two novel genes that are required for PDIM production and induction of the type I IFN response. Thus, multiparametric analysis combining host and pathogen infection phenotypes can be used to identify novel functional relationships between genes that play a role in infection.

Rare variants in PPARG with decreased activity in adipocyte differentiation are associated with increased risk of type 2 diabetes.

Peroxisome proliferator-activated receptor gamma (PPARG) is a master transcriptional regulator of adipocyte differentiation and a canonical target of antidiabetic thiazolidinedione medications. In rare families, loss-of-function (LOF) mutations in PPARG are known to cosegregate with lipodystrophy and insulin resistance; in the general population, the common P12A variant is associated with a decreased risk of type 2 diabetes (T2D). Whether and how rare variants in PPARG and defects in adipocyte differentiation influence risk of T2D in the general population remains undetermined. By sequencing PPARG in 19,752 T2D cases and controls drawn from multiple studies and ethnic groups, we identified 49 previously unidentified, nonsynonymous PPARG variants (MAF < 0.5%). Considered in aggregate (with or without computational prediction of functional consequence), these rare variants showed no association with T2D (OR = 1.35; P = 0.17). The function of the 49 variants was experimentally tested in a novel high-throughput human adipocyte differentiation assay, and nine were found to have reduced activity in the assay. Carrying any of these nine LOF variants was associated with a substantial increase in risk of T2D (OR = 7.22; P = 0.005). The combination of large-scale DNA sequencing and functional testing in the laboratory reveals that approximately 1 in 1,000 individuals carries a variant in PPARG that reduces function in a human adipocyte differentiation assay and is associated with a substantial risk of T2D.

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.

Identification of host-targeted small molecules that restrict intracellular Mycobacterium tuberculosis growth.

Mycobacterium tuberculosis remains a significant threat to global health. Macrophages are the host cell for M. tuberculosis infection, and although bacteria are able to replicate intracellularly under certain conditions, it is also clear that macrophages are capable of killing M. tuberculosis if appropriately activated. The outcome of infection is determined at least in part by the host-pathogen interaction within the macrophage; however, we lack a complete understanding of which host pathways are critical for bacterial survival and replication. To add to our understanding of the molecular processes involved in intracellular infection, we performed a chemical screen using a high-content microscopic assay to identify small molecules that restrict mycobacterial growth in macrophages by targeting host functions and pathways. The identified host-targeted inhibitors restrict bacterial growth exclusively in the context of macrophage infection and predominantly fall into five categories: G-protein coupled receptor modulators, ion channel inhibitors, membrane transport proteins, anti-inflammatories, and kinase modulators. We found that fluoxetine, a selective serotonin reuptake inhibitor, enhances secretion of pro-inflammatory cytokine TNF-α and induces autophagy in infected macrophages, and gefitinib, an inhibitor of the Epidermal Growth Factor Receptor (EGFR), also activates autophagy and restricts growth. We demonstrate that during infection signaling through EGFR activates a p38 MAPK signaling pathway that prevents macrophages from effectively responding to infection. Inhibition of this pathway using gefitinib during in vivo infection reduces growth of M. tuberculosis in the lungs of infected mice. Our results support the concept that screening for inhibitors using intracellular models results in the identification of tool compounds for probing pathways during in vivo infection and may also result in the identification of new anti-tuberculosis agents that work by modulating host pathways. Given the existing experience with some of our identified compounds for other therapeutic indications, further clinically-directed study of these compounds is merited.

An open-source computational tool to automatically quantify immunolabeled retinal ganglion cells.

A fully automated and robust method was developed to quantify ß-III-tubulin-stained retinal ganglion cells, combining computational recognition of individual cells by CellProfiler and a machine-learning tool to teach phenotypic classification of the retinal ganglion cells by CellProfiler Analyst. In animal models of glaucoma, quantification of immunolabeled retinal ganglion cells is currently performed manually and remains time-consuming. Using this automated method, quantifications of retinal ganglion cell images were accelerated tenfold: 1800 images were counted in 3 h using our automated method, while manual counting of the same images took 72 h. This new method was validated in an established murine model of microbead-induced optic neuropathy. The use of the publicly available software and the method's user-friendly design allows this technique to be easily implemented in any laboratory.

CellProfiler Tracer: exploring and validating high-throughput, time-lapse microscopy image data.

BACKGROUND: Time-lapse analysis of cellular images is an important and growing need in biology. Algorithms for cell tracking are widely available; what researchers have been missing is a single open-source software package to visualize standard tracking output (from software like CellProfiler) in a way that allows convenient assessment of track quality, especially for researchers tuning tracking parameters for high-content time-lapse experiments. This makes quality assessment and algorithm adjustment a substantial challenge, particularly when dealing with hundreds of time-lapse movies collected in a high-throughput manner. RESULTS: We present CellProfiler Tracer, a free and open-source tool that complements the object tracking functionality of the CellProfiler biological image analysis package. Tracer allows multi-parametric morphological data to be visualized on object tracks, providing visualizations that have already been validated within the scientific community for time-lapse experiments, and combining them with simple graph-based measures for highlighting possible tracking artifacts. CONCLUSIONS: CellProfiler Tracer is a useful, free tool for inspection and quality control of object tracking data, available from http://www.cellprofiler.org/tracer/.

ProtocolNavigator: emulation-based software for the design, documentation and reproduction biological experiments.

MOTIVATION: Experimental reproducibility is fundamental to the progress of science. Irreproducible research decreases the efficiency of basic biological research and drug discovery and impedes experimental data reuse. A major contributing factor to irreproducibility is difficulty in interpreting complex experimental methodologies and designs from written text and in assessing variations among different experiments. Current bioinformatics initiatives either are focused on computational research reproducibility (i.e. data analysis) or laboratory information management systems. Here, we present a software tool, ProtocolNavigator, which addresses the largely overlooked challenges of interpretation and assessment. It provides a biologist-friendly open-source emulation-based tool for designing, documenting and reproducing biological experiments. AVAILABILITY AND IMPLEMENTATION: ProtocolNavigator was implemented in Python 2.7, using the wx module to build the graphical user interface. It is a platform-independent software and freely available from http://protocolnavigator.org/index.html under the GPL v2 license.

High- and low-throughput scoring of fat mass and body fat distribution in C. elegans.

Fat accumulation is a complex phenotype affected by factors such as neuroendocrine signaling, feeding, activity, and reproductive output. Accordingly, the most informative screens for genes and compounds affecting fat accumulation would be those carried out in whole living animals. Caenorhabditis elegans is a well-established and effective model organism, especially for biological processes that involve organ systems and multicellular interactions, such as metabolism. Every cell in the transparent body of C. elegans is visible under a light microscope. Consequently, an accessible and reliable method to visualize worm lipid-droplet fat depots would make C. elegans the only metazoan in which genes affecting not only fat mass but also body fat distribution could be assessed at a genome-wide scale. Here we present a radical improvement in oil red O worm staining together with high-throughput image-based phenotyping. The three-step sample preparation method is robust, formaldehyde-free, and inexpensive, and requires only 15min of hands-on time to process a 96-well plate. Together with our free and user-friendly automated image analysis package, this method enables C. elegans sample preparation and phenotype scoring at a scale that is compatible with genome-wide screens. Thus we present a feasible approach to small-scale phenotyping and large-scale screening for genetic and/or chemical perturbations that lead to alterations in fat quantity and distribution in whole animals.

Automated image-based assay for evaluation of HIV neutralization and cell-to-cell fusion inhibition.

BACKGROUND: Standardized techniques to detect HIV-neutralizing antibody responses are of great importance in the search for an HIV vaccine. METHODS: Here, we present a high-throughput, high-content automated plaque reduction (APR) assay based on automated microscopy and image analysis that allows evaluation of neutralization and inhibition of cell-cell fusion within the same assay. Neutralization of virus particles is measured as a reduction in the number of fluorescent plaques, and inhibition of cell-cell fusion as a reduction in plaque area. RESULTS: We found neutralization strength to be a significant factor in the ability of virus to form syncytia. Further, we introduce the inhibitory concentration of plaque area reduction (ICpar) as an additional measure of antiviral activity, i.e. fusion inhibition. CONCLUSIONS: We present an automated image based high-throughput, high-content HIV plaque reduction assay. This allows, for the first time, simultaneous evaluation of neutralization and inhibition of cell-cell fusion within the same assay, by quantifying the reduction in number of plaques and mean plaque area, respectively. Inhibition of cell-to-cell fusion requires higher quantities of inhibitory reagent than inhibition of virus neutralization.

Enhancing the Small-Scale Screenable Biological Space beyond Known Chemogenomics Libraries with Gray Chemical Matter─Compounds with Novel Mechanisms from High-Throughput Screening Profiles.

Phenotypic assays have become an established approach to drug discovery. Greater disease relevance is often achieved through cellular models with increased complexity and more detailed readouts, such as gene expression or advanced imaging. However, the intricate nature and cost of these assays impose limitations on their screening capacity, often restricting screens to well-characterized small compound sets such as chemogenomics libraries. Here, we outline a cheminformatics approach to identify a small set of compounds with likely novel mechanisms of action (MoAs), expanding the MoA search space for throughput limited phenotypic assays. Our approach is based on mining existing large-scale, phenotypic high-throughput screening (HTS) data. It enables the identification of chemotypes that exhibit selectivity across multiple cell-based assays, which are characterized by persistent and broad structure activity relationships (SAR). We validate the effectiveness of our approach in broad cellular profiling assays (Cell Painting, DRUG-seq, and Promotor Signature Profiling) and chemical proteomics experiments. These experiments revealed that the compounds behave similarly to known chemogenetic libraries, but with a notable bias toward novel protein targets. To foster collaboration and advance research in this area, we have curated a public set of such compounds based on the PubChem BioAssay dataset and made it available for use by the scientific community.

Myocyte shape regulates lateral registry of sarcomeres and contractility.

The heart actively remodels architecture in response to various physiological and pathological conditions. Gross structural change of the heart chambers is directly reflected at the cellular level by altering the morphological characteristics of individual cardiomyocytes. However, an understanding of the relationship between cardiomyocyte shape and the contractile function remains unclear. By using in vitro assays to analyze systolic stress of cardiomyocytes with controlled shape, we demonstrated that the characteristic morphological features of cardiomyocytes observed in a variety of pathophysiological conditions are correlated with mechanical performance. We found that cardiomyocyte contractility is optimized at the cell length/width ratio observed in normal hearts, and decreases in cardiomyocytes with morphological characteristics resembling those isolated from failing hearts. Quantitative analysis of sarcomeric architecture revealed that the change of contractility may arise from alteration of myofibrillar structure. Measurements of intracellular calcium in myocytes revealed unique characteristics of calcium metabolism as a function of myocyte shape. Our data suggest that cell shape is critical in determining contractile performance of single cardiomyocytes by regulating the intracellular structure and calcium handling ability.

GATA1 deletion in human pluripotent stem cells increases differentiation yield and maturity of neutrophils.

Human pluripotent stem cell (hPSC)-derived tissues can be used to model diseases in cell types that are challenging to harvest and study at-scale, such as neutrophils. Neutrophil dysregulation, specifically neutrophil extracellular trap (NET) formation, plays a critical role in the prognosis and progression of multiple diseases, including COVID-19. While hPSCs can generate limitless neutrophils (iNeutrophils) to study these processes, current differentiation protocols generate heterogeneous cultures of granulocytes and precursors. Here, we describe a method to improve iNeutrophil differentiations through the deletion of GATA1. GATA1 knockout (KO) iNeutrophils are nearly identical to primary neutrophils in form and function. Unlike wild-type iNeutrophils, GATA1 KO iNeutrophils generate NETs in response to the physiologic stimulant lipopolysaccharide, suggesting they are a more accurate model when performing NET inhibitor screens. Furthermore, through deletion of CYBB, we demonstrate that GATA1 KO iNeutrophils are a powerful tool in determining involvement of a given protein in NET formation.

Improved structure, function and compatibility for CellProfiler: modular high-throughput image analysis software.

UNLABELLED: There is a strong and growing need in the biology research community for accurate, automated image analysis. Here, we describe CellProfiler 2.0, which has been engineered to meet the needs of its growing user base. It is more robust and user friendly, with new algorithms and features to facilitate high-throughput work. ImageJ plugins can now be run within a CellProfiler pipeline. AVAILABILITY AND IMPLEMENTATION: CellProfiler 2.0 is free and open source, available at http://www.cellprofiler.org under the GPL v. 2 license. It is available as a packaged application for Macintosh OS X and Microsoft Windows and can be compiled for Linux. CONTACT: anne@broadinstitute.org SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Self-organization of muscle cell structure and function.

The organization of muscle is the product of functional adaptation over several length scales spanning from the sarcomere to the muscle bundle. One possible strategy for solving this multiscale coupling problem is to physically constrain the muscle cells in microenvironments that potentiate the organization of their intracellular space. We hypothesized that boundary conditions in the extracellular space potentiate the organization of cytoskeletal scaffolds for directed sarcomeregenesis. We developed a quantitative model of how the cytoskeleton of neonatal rat ventricular myocytes organizes with respect to geometric cues in the extracellular matrix. Numerical results and in vitro assays to control myocyte shape indicated that distinct cytoskeletal architectures arise from two temporally-ordered, organizational processes: the interaction between actin fibers, premyofibrils and focal adhesions, as well as cooperative alignment and parallel bundling of nascent myofibrils. Our results suggest that a hierarchy of mechanisms regulate the self-organization of the contractile cytoskeleton and that a positive feedback loop is responsible for initiating the break in symmetry, potentiated by extracellular boundary conditions, is required to polarize the contractile cytoskeleton.

Cell Painting predicts impact of lung cancer variants.

Most variants in most genes across most organisms have an unknown impact on the function of the corresponding gene. This gap in knowledge is especially acute in cancer, where clinical sequencing of tumors now routinely reveals patient-specific variants whose functional impact on the corresponding genes is unknown, impeding clinical utility. Transcriptional profiling was able to systematically distinguish these variants of unknown significance as impactful vs. neutral in an approach called expression-based variant-impact phenotyping. We profiled a set of lung adenocarcinoma-associated somatic variants using Cell Painting, a morphological profiling assay that captures features of cells based on microscopy using six stains of cell and organelle components. Using deep-learning-extracted features from each cell's image, we found that cell morphological profiling (cmVIP) can predict variants' functional impact and, particularly at the single-cell level, reveals biological insights into variants that can be explored at our public online portal. Given its low cost, convenient implementation, and single-cell resolution, cmVIP profiling therefore seems promising as an avenue for using non-gene specific assays to systematically assess the impact of variants, including disease-associated alleles, on gene function.

Sarcomere alignment is regulated by myocyte shape.

Cardiac organogenesis and pathogenesis are both characterized by changes in myocyte shape, cytoskeletal architecture, and the extracellular matrix (ECM). However, the mechanisms by which the ECM influences myocyte shape and myofibrillar patterning are unknown. We hypothesized that geometric cues in the ECM align sarcomeres by directing the actin network orientation. To test our hypothesis, we cultured neonatal rat ventricular myocytes on islands of micro-patterned ECM to measure how they remodeled their cytoskeleton in response to extracellular cues. Myocytes spread and assumed the shape of circular and rectangular islands and reorganized their cytoskeletons and myofibrillar arrays with respect to the ECM boundary conditions. Circular myocytes did not assemble predictable actin networks nor organized sarcomere arrays. In contrast, myocytes cultured on rectangular ECM patterns with aspect ratios ranging from 1:1 to 7:1 aligned their sarcomeres in predictable and repeatable patterns based on highly localized focal adhesion complexes. Examination of averaged alpha-actinin images revealed invariant sarcomeric registration irrespective of myocyte aspect ratio. Since the sarcomere sub-units possess a fixed length, this observation indicates that cytoskeleton configuration is length-limited by the extracellular boundary conditions. These results indicate that modification of the extracellular microenvironment induces dynamic reconfiguring of the myocyte shape and intracellular architecture. Furthermore, geometric boundaries such as corners induce localized myofibrillar anisotropy that becomes global as the myocyte aspect ratio increases.

A High-Content Screen Identifies TPP1 and Aurora B as Regulators of Axonal Mitochondrial Transport.

Dysregulated axonal trafficking of mitochondria is linked to neurodegenerative disorders. We report a high-content screen for small-molecule regulators of the axonal transport of mitochondria. Six compounds enhanced mitochondrial transport in the sub-micromolar range, acting via three cellular targets: F-actin, Tripeptidyl peptidase 1 (TPP1), or Aurora Kinase B (AurKB). Pharmacological inhibition or small hairpin RNA (shRNA) knockdown of each target promotes mitochondrial axonal transport in rat hippocampal neurons and induced pluripotent stem cell (iPSC)-derived human cortical neurons and enhances mitochondrial transport in iPSC-derived motor neurons from an amyotrophic lateral sclerosis (ALS) patient bearing one copy of SOD1A4V mutation. Our work identifies druggable regulators of axonal transport of mitochondria, provides broadly applicable methods for similar image-based screens, and suggests that restoration of proper axonal trafficking of mitochondria can be achieved in human ALS neurons.

High-resolution high-speed panoramic cardiac imaging system.

A panoramic cardiac imaging system consisting of three high-speed CCD cameras has been developed to image the surface electrophysiology of a rabbit heart via fluorescence imaging using a voltage-sensitive fluorescent dye. A robust, unique mechanical system was designed to accommodate the three cameras and to adapt to the requirements of future experiments. A unified computer interface was created for this application - a single workstation controls all three CCD cameras, illumination, stimulation, and a stepping motor that rotates the heart. The geometric reconstruction algorithms were adapted from a previous cardiac imaging system. We demonstrate the system by imaging a polymorphic cardiac tachycardia.

Quality Control for High-Throughput Imaging Experiments Using Machine Learning in Cellprofiler.

Robust high-content screening of visual cellular phenotypes has been enabled by automated microscopy and quantitative image analysis. The identification and removal of common image-based aberrations is critical to the screening workflow. Out-of-focus images, debris, and auto-fluorescing samples can cause artifacts such as focus blur and image saturation, contaminating downstream analysis and impairing identification of subtle phenotypes. Here, we describe an automated quality control protocol implemented in validated open-source software, leveraging the suite of image-based measurements generated by CellProfiler and the machine-learning functionality of CellProfiler Analyst.