A cell-level quality control workflow for high-throughput image analysis.

BACKGROUND: Image-based high throughput (HT) screening provides a rich source of information on dynamic cellular response to external perturbations. The large quantity of data generated necessitates computer-aided quality control (QC) methodologies to flag imaging and staining artifacts. Existing image- or patch-level QC methods require separate thresholds to be simultaneously tuned for each image quality metric used, and also struggle to distinguish between artifacts and valid cellular phenotypes. As a result, extensive time and effort must be spent on per-assay QC feature thresholding, and valid images and phenotypes may be discarded while image- and cell-level artifacts go undetected. RESULTS: We present a novel cell-level QC workflow built on machine learning approaches for classifying artifacts from HT image data. First, a phenotype sampler based on unlabeled clustering collects a comprehensive subset of cellular phenotypes, requiring only the inspection of a handful of images per phenotype for validity. A set of one-class support vector machines are then trained on each biologically valid image phenotype, and used to classify individual objects in each image as valid cells or artifacts. We apply this workflow to two real-world large-scale HT image datasets and observe that the ratio of artifact to total object area (ARcell) provides a single robust assessment of image quality regardless of the underlying causes of quality issues. Gating on this single intuitive metric, partially contaminated images can be salvaged and highly contaminated images can be excluded before image-level phenotype summary, enabling a more reliable characterization of cellular response dynamics. CONCLUSIONS: Our cell-level QC workflow enables identification of artificial cells created not only by staining or imaging artifacts but also by the limitations of image segmentation algorithms. The single readout ARcell that summaries the ratio of artifacts contained in each image can be used to reliably rank images by quality and more accurately determine QC cutoff thresholds. Machine learning-based cellular phenotype clustering and sampling reduces the amount of manual work required for training example collection. Our QC workflow automatically handles assay-specific phenotypic variations and generalizes to different HT image assays.

Suppressors of superoxide production from mitochondrial complex III.

Mitochondrial electron transport drives ATP synthesis but also generates reactive oxygen species, which are both cellular signals and damaging oxidants. Superoxide production by respiratory complex III is implicated in diverse signaling events and pathologies, but its role remains controversial. Using high-throughput screening, we identified compounds that selectively eliminate superoxide production by complex III without altering oxidative phosphorylation; they modulate retrograde signaling including cellular responses to hypoxic and oxidative stress.

In silico activity profiling reveals the mechanism of action of antimalarials discovered in a high-throughput screen.

The growing resistance to current first-line antimalarial drugs represents a major health challenge. To facilitate the discovery of new antimalarials, we have implemented an efficient and robust high-throughput cell-based screen (1,536-well format) based on proliferation of Plasmodium falciparum (Pf) in erythrocytes. From a screen of approximately 1.7 million compounds, we identified a diverse collection of approximately 6,000 small molecules comprised of >530 distinct scaffolds, all of which show potent antimalarial activity (<1.25 microM). Most known antimalarials were identified in this screen, thus validating our approach. In addition, we identified many novel chemical scaffolds, which likely act through both known and novel pathways. We further show that in some cases the mechanism of action of these antimalarials can be determined by in silico compound activity profiling. This method uses large datasets from unrelated cellular and biochemical screens and the guilt-by-association principle to predict which cellular pathway and/or protein target is being inhibited by select compounds. In addition, the screening method has the potential to provide the malaria community with many new starting points for the development of biological probes and drugs with novel antiparasitic activities.

Time-resolved fluorescence resonance energy transfer and surface plasmon resonance-based assays for retinoid and transthyretin binding to retinol-binding protein 4.

Retinol-binding protein-4 (RBP4) is an emerging candidate drug target for type 2 diabetes and lipofuscin-mediated macular degeneration. The retinoic acid derivative fenretinide (N-(4-hydroxyphenyl) retinamide; HPR) exerts therapeutic effects in mouse models of obesity, diabetes, and Stargardt's disease by targeting RBP4. Fenretinide competes with retinoids for RBP4 binding, disrupts RBP4-transthyretin (TTR) complexes, and results in urinary secretion of RBP4 and systemic depletion of retinol. To enable the search for nonretinoid molecules with fenretinide-like activities we developed a HTS-compatible homogeneous TR-FRET assay monitoring the displacement of retinoic acid derivatives from RBP4 in high-density 384-well and 1536-well microtiter plate formats. The retinoid displacement assay proved to be highly sensitive and robust after miniaturization with IC(50)s for fenretinide and retinol ranging around 50 and 100 nM, respectively, and Z'-factors around 0.7. In addition, a surface plasmon resonance (SPR)-based secondary assay was developed to interrogate small molecule RBP4 binders for their ability to modulate the RBP4-TTR interaction. Finally, a 1.6 x 10(6) compound library was screened against the retinoid displacement assay. Several potent retinoid competitors were identified that also appeared to disrupt RBP4-TTR complexes. Some of these compounds could potentially serve as valuable tools to further probe RBP4 biology in the future.

Suppressors of Superoxide-H2O2 Production at Site IQ of Mitochondrial Complex I Protect against Stem Cell Hyperplasia and Ischemia-Reperfusion Injury.

Using high-throughput screening we identified small molecules that suppress superoxide and/or H2O2 production during reverse electron transport through mitochondrial respiratory complex I (site IQ) without affecting oxidative phosphorylation (suppressors of site IQ electron leak, "S1QELs"). S1QELs diminished endogenous oxidative damage in primary astrocytes cultured at ambient or low oxygen tension, showing that site IQ is a normal contributor to mitochondrial superoxide-H2O2 production in cells. They diminished stem cell hyperplasia in Drosophila intestine in vivo and caspase activation in a cardiomyocyte cell model driven by endoplasmic reticulum stress, showing that superoxide-H2O2 production by site IQ is involved in cellular stress signaling. They protected against ischemia-reperfusion injury in perfused mouse heart, showing directly that superoxide-H2O2 production by site IQ is a major contributor to this pathology. S1QELs are tools for assessing the contribution of site IQ to cell physiology and pathology and have great potential as therapeutic leads.

Homogeneous high-throughput screening assays for HIV-1 integrase 3beta-processing and strand transfer activities.

HIV-1 integrase (HIV-IN) is a well-validated antiviral drug target catalyzing a multistep reaction to incorporate the HIV-1 provirus into the genome of the host cell. Small molecule inhibitors of HIV-1 integrase that specifically target the strand transfer step have demonstrated efficacy in the suppression of virus propagation. However, only few specific strand transfer inhibitors have been identified to date, and the need to screen for novel compound scaffolds persists. Here, the authors describe 2 homogeneous time-resolved fluorescent resonance energy transfer-based assays for the measurement of HIV-1 integrase 3'-processing and strand transfer activities. Both assays were optimized for high-throughput screening formats, and a diverse library containing more than 1 million compounds was screened in 1536-well plates for HIV-IN strand transfer inhibitors. As a result, compounds were found that selectively affect the enzymatic strand transfer reaction over 3beta processing. Moreover, several bioactive molecules were identified that inhibited HIV-1 reporter virus infection in cellular model systems. In conclusion, the assays presented herein have proven their utility for the identification of mechanistically interesting and biologically active inhibitors of HIV-1 integrase that hold potential for further development into potent antiviral drugs.

Chemical activation of the mechanotransduction channel Piezo1.

Piezo ion channels are activated by various types of mechanical stimuli and function as biological pressure sensors in both vertebrates and invertebrates. To date, mechanical stimuli are the only means to activate Piezo ion channels and whether other modes of activation exist is not known. In this study, we screened ~3.25 million compounds using a cell-based fluorescence assay and identified a synthetic small molecule we termed Yoda1 that acts as an agonist for both human and mouse Piezo1. Functional studies in cells revealed that Yoda1 affects the sensitivity and the inactivation kinetics of mechanically induced responses. Characterization of Yoda1 in artificial droplet lipid bilayers showed that Yoda1 activates purified Piezo1 channels in the absence of other cellular components. Our studies demonstrate that Piezo1 is amenable to chemical activation and raise the possibility that endogenous Piezo1 agonists might exist. Yoda1 will serve as a key tool compound to study Piezo1 regulation and function.

Cellular Ser/Thr-kinase assays using generic peptide substrates.

High-throughput cellular profiling has successfully stimulated early drug discovery pipelines by facilitating targeted as well as opportunistic lead finding, hit annotation and SAR analysis. While automation-friendly universal assay formats exist to address most established drug target classes like GPCRs, NHRs, ion channels or Tyr-kinases, no such cellular assay technology is currently enabling an equally broad and rapid interrogation of the Ser/Thr-kinase space. Here we present the foundation of an emerging cellular Ser/Thr-kinase platform that involves a) coexpression of targeted kinases with promiscuous peptide substrates and b) quantification of intracellular substrate phosphorylation by homogeneous TR-FRET. Proof-of-concept data is provided for cellular AKT, B-RAF and CamK2delta assays. Importantly, comparable activity profiles were found for well characterized B-Raf inhibitors in TR-FRET assays relying on either promiscuous peptide substrates or a MEK1(WT) protein substrate respectively. Moreover, IC(50)-values correlated strongly between cellular TR-FRET assays and a gold standard Ba/F3 proliferation assay for B-Raf activity. Finally, we expanded our initial assay panel by screening a kinase-focused cDNA library and identified starting points for >20 cellular Ser/Thr-kinase assays.

An efficient rapid system for profiling the cellular activities of molecular libraries.

Rapid quantitative methods for characterizing small molecules, peptides, proteins, or RNAs in a broad array of cellular assays would allow one to discover new biological activities associated with these molecules and also provide a more comprehensive profile of drug candidates early in the drug development process. Here we describe a robotic system, termed the automated compound profiler, capable of both propagating a large number of cell lines in parallel and assaying large collections of molecules simultaneously against a matrix of cellular assays in a highly reproducible manner. To illustrate its utility, we have characterized a set of 1,400 kinase inhibitors in a panel of 35 activated tyrosine-kinase-dependent cellular assays in dose-response format in a single experiment. Analysis of the resulting multidimensional dataset revealed subclusters of both inhibitors and kinases with closely correlated activities. The approach also identified activities for the p38 inhibitor BIRB796 and the dual src/abl inhibitor BMS-354825 and exposed the expected side activities for Glivec/STI571, including cellular inhibition of c-kit and platelet-derived growth factor receptor. This methodology provides a powerful tool for unraveling the cellular biology and molecular pharmacology of both naturally occurring and synthetic chemical diversity.