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The development of mouse models that replicate the genetic and pathological features of human disease is important in preclinical research because these types of models enable the completion of meaningful pharmacokinetic, safety, and efficacy studies. Numerous relevant mouse models of human disease have been discovered in high-throughput screening programs, but there are important specific phenotypes revealed by histopathology that are not reliably detected by any other physiological or behavioral screening tests. As part of comprehensive phenotypic analyses of over 4000 knockout (KO) mice, histopathology identified 12 lines of KO mice with lesions indicative of an autosomal recessive myopathy. This report includes a brief summary of histological and other findings in these 12 lines. Notably, the inverted screen test detected muscle weakness in only 4 of these 12 lines ( Scyl1, Plpp7, Chkb, and Asnsd1), all 4 of which have been previously recognized and published. In contrast, 6 of 8 KO lines showing negative or inconclusive findings on the inverted screen test ( Plppr2, Pnpla7, Tenm1, Srpk3, Sidt2, Yif1b, Mrs2, and Pnpla2) had not been previously identified as having myopathies. These findings support the need to include histopathology in phenotype screening protocols in order to identify novel genetic myopathies that are not clinically evident or not detected by the inverted screen test.

Background A number of immunoassays have been developed to measure antibodies specific to SARS-CoV-2. More data is required on their comparability, particularly among those with milder infections and in the general practice population. The aim of this study was to compare four high-throughput automated anti-SARS-CoV-2 assays using samples collected from hospitalized patients and healthcare workers with confirmed SARS-CoV-2 infection. In addition, we collected general practice samples to compare antibody results and determine seroprevalence. Methods Samples were collected from 57 hospitalized patients and nine healthcare workers at 14 days and at 28 days following confirmed SARS-CoV-2 infection. Samples were also collected from 225 patients presenting to general practice. Four assays were used: Abbott Architect IgG, Beckman Coulter DxI 800 IgG, Roche Cobas e801 total antibody and Siemens Advia Centaur XPT total antibody. Results All four assays showed concordance at 14 days in 83.9% of hospitalized patients and in 66.7% of healthcare workers. All four assays showed concordance at 28 days in 88.4% of hospitalized patients and 77.8% of healthcare workers. The sensitivity to detect recent infection was higher for the IgG assays than the total assays. All four assays showed concordance of 95.1% in the general practice population. Seroprevalence ranged from 4.9 to 5.8% depending on the assay used. Conclusions All four assays showed excellent comparability, but it may be possible to obtain a negative result for any of the anti-SARS-CoV-2 assays in patients with confirmed previous SARS-CoV-2 infection. An equivocal range would be useful for all anti-SARS-CoV-2 assays.

Small-molecule screening is a powerful approach to identify modulators of either specific biological targets or cellular pathways with phenotypic endpoints. A myriad of assay technologies are available to assess the activity of enzymes, monitor protein-protein interactions, measure transcription factor activity in reporter assays, or detect cellular features and activities using high-content imaging. A common challenge during small-molecule screening is, however, the presence of hit compounds generating assay interference, thereby producing false-positive hits. Thus, efforts are needed to uncover such interferences to prioritize high-quality hits for further analysis. This process encompasses (1) computational approaches to flag undesirable compounds, and (2) the use of experimental approaches like counter, orthogonal, and cellular fitness screens to identify and eliminate artifacts. In this brief guide, we provide an overview for first-time users, highlighting experimental screening strategies to prioritize high-quality bioactive hits from high-throughput screening/high-content screening (HTS/HCS) campaigns.

Frequent outbreaks of novel coronaviruses (CoVs), highlighted by the current severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, necessitate the development of therapeutics that could be easily and effectively administered worldwide. The conserved mRNA-capping process enables CoVs to evade their host immune system and is a target for antiviral development. Nonstructural protein (nsp) 16 in complex with nsp10 catalyzes the final step of coronaviral mRNA capping through its 2'-O-methylation activity. Like other methyltransferases, the SARS-CoV-2 nsp10-nsp16 complex is druggable. However, the availability of an optimized assay for high-throughput screening (HTS) is an unmet need. Here, we report the development of a radioactivity-based assay for the methyltransferase activity of the nsp10-nsp16 complex in a 384-well format, kinetic characterization, and optimization of the assay for HTS (Z' factor = 0.83). Considering the high conservation of nsp16 across known CoV species, the potential inhibitors targeting the SARS-CoV-2 nsp10-nsp16 complex may also be effective against other emerging pathogenic CoVs.

The Mac1 domain of the multifunctional SARS-CoV-2 non-structural protein 3 (nsp3) is a potential COVID-19 drug target because it is suspected to enhance the ability of the virus to evade the human immune system. The SARS-CoV-2 Mac1 domain binds ADP-ribose and proteins harboring this important post-translational modification. Small molecules that bind the Mac1 domain in place of ADP-ribose might therefore be useful as molecular probes or scaffolds for antiviral drug discovery. Two high throughput screens were used here to identify such ligands in small libraries of drugs and drug-like compounds. The first screen used differential scanning fluorimetry (DSF, aka the thermal shift or ThermoFluor assay) to examine the melting temperature of SARS-CoV-2 Mac1 domain in the presence of various compounds. In the second screen, various high-resolution SARS-CoV-2 Mac1 structures were used with Autodock VINA to identify potential ligands. Numerous hit compounds were either steroids (estradiol valerate & flunisolide), beta-lactams (cefaclor & cefatrizine), or benzimidazoles (telmisartan, rabeprazole, omeprazole, & esomeprazole). Isothermal titration calorimetry was used to confirm that rabeprazole, omeprazole, and compounds in other chemical classes, such as irinotecan, nifedipine, trifluoperazine, bind SARS-CoV-2 Mac1 with an affinity similar to ADP-ribose.

The assay metric Z’ has come to play a critical gatekeeping role in determining whether high-throughput assays can be performed. While Z’ is commonly required to be > 0.5, this expectation is not well supported. Requiring Z’ > 0.5 likely prevents many potentially useful phenotypic and cell-based screens from being conducted, and causes other assays to be conducted under extreme conditions that may prevent activity from being found. We used power analysis and a novel numerical simulation approach to determine how Z’ reflects assay performance under a variety of conditions. Our results show that assays with Z’ > 0.5 perform better than assays with lower Z’, but when an appropriate threshold is selected, assays with Z’ < 0.5 can almost always find useful compounds without generating too many false positives. We provide a method that will allow researchers to estimate how to set an appropriate threshold for their assay. We suggest that instead of always requiring Z’ > 0.5, assays with Z’ < 0.5 should be performed when they can be justified in terms of the importance of the target and the limitations of alternate assay formats.

The European Lead Factory (ELF) consortium provides European academics and small and medium enterprises access to ~0.5 million unique compounds, a state-of-the-art ultra-high-throughput screening (u-HTS) platform, and industrial early drug discovery (DD) expertise with the aim of delivering innovative DD starting points. From 2013 to 2018, 154 proposals for eight target classes in seven therapeutic areas were submitted to the ELF consortium, 88 of which were accepted by the selection committee. During this period, 76 primary assays based on seven different readout technologies were optimized and mainly miniaturized to 1536-well plates. In total, 72 u-HTS campaigns were carried out, and follow-up work including hit triage through orthogonal, deselection, selectivity, and biophysical assays were finalized. This ambitious project showed that besides the quality of the compound library and the primary assay, the success of centralized u-HTS of large compound libraries across many target classes, various assay types, and different readout technologies is also largely dependent on the capacity and flexibility of the automation on one hand and the hit-triaging phase on the other, particularly because of undesired compound-assay interference. Thus far, the delivered hit lists from the ELF consortium have resulted in spinoffs, patents, in vivo proof of concepts, preclinical development programs, peer-reviewed publications, PhD theses, and much more, demonstrating early success indications.

Determining microplastics in environmental samples quickly and reliably is a challenging task. With a largely automated combination of optical particle analysis, Fourier transform infrared (FT-IR), and Raman microscopy along with spectral database search, particle sizes, particle size distributions, and the type of polymer including particle color can be determined. We present a self-developed, open-source software package for realizing a particle analysis approach with both Raman and FT-IR microspectroscopy. Our software GEPARD (Gepard Enabled PARticle Detection) allows for acquiring an optical image, then detects particles and uses this information to steer the spectroscopic measurement. This ultimately results in a multitude of possibilities for efficiently reviewing, correcting, and reporting all obtained results.

Simple and rapid imaging and analysis of 2D and 3D cell culture compatible with miniaturized arrays of nanoliter droplets are essential for high-throughput screening and personalized medicine applications. In this study, we have developed a simple one-step, cost-effective and sensitive colorimetric method for the analysis of cell viability in 2D and 3D cell cultures on a nanoliter droplet microarray. The method utilizes a flatbed document scanner that detects a color change in response to cell metabolism in nanoliter droplets with high sensitivity in a single step without the need for expensive specialized equipment. This new nanoliter-based method is faster and more sensitive than equivalent methods using multi-well plate assays. The method detects quantifiable signal from as few as 10 cells and requires only 5 min. This is 2.5 to 10-fold more sensitive and 12 times faster than the same assay in multi-well plates. The method is simple, affordable, fast and sensitive. It can be used for various applications including high-throughput cell-based and biochemical screenings.

Porcine epidemic diarrhea virus (PEDV) is an emerging porcine coronavirus that causes a tremendous economic burden on the swine industry. The assessment of PEDV-neutralizing antibody levels provides a valuable tool to assess and predict herd immunity. We evaluated the performance of a PEDV imaging cytometry–based high-throughput neutralization test (HTNT) and compared the HTNT to a fluorescent focus neutralization (FFN) assay using serum samples from pigs of known PEDV infection status ( n = 159). Estimates of diagnostic sensitivity and specificity for HTNT and FFN assays derived from receiver-operator characteristic (ROC) curve analyses showed that both PEDV FFN and HTNT provided excellent diagnostic performance. However, in the laboratory, imaging cytometry provided an objective and semi-automated approach that removed human subjectivity from the testing process and reduced the read-time of a 96-well plate to

Extracellular protein interactions coordinate cellular responses with their local environment and have important roles in pathogen invasion and disease. Due to technical challenges associated with studying binding events at the cell surface, the systematic and reliable identification of novel ligand-receptor pairs remains difficult. Here, we describe the development of a cell-based assay using large-scale transient transfections and high-content imaging (HCI) to detect extracellular binding events. We optimized the parameters for efficient transfection of human cells with cDNA plasmids encoding full-length cell surface receptors in 384-well plates. Using a range of well-characterized structurally diverse low-affinity cell surface interactions, we show that transfected cells probed with highly avid ligands can be used to successfully identify ligand-receptor pairs using an HCI platform and automated image analysis software. To establish the high-throughput potential of this approach, we also screened a pool of ligands against a collection of 2455 cell surface expression clones and found that known ligand-receptor interactions could be robustly and consistently detected across the library using this technology.

The etiological underpinnings of many CNS disorders are not well understood. This is likely due to the fact that individual diseases aggregate numerous pathological subtypes, each associated with a complex landscape of genetic risk factors. To overcome these challenges, researchers are integrating novel data types from numerous patients, including imaging studies capturing broadly applicable features from patient-derived materials. These datasets, when combined with machine learning, potentially hold the power to elucidate the subtle patterns that stratify patients by shared pathology. In this study, we interrogated whether high-content imaging of primary skin fibroblasts, using the Cell Painting method, could reveal disease-relevant information among patients. First, we showed that technical features such as batch/plate type, plate, and location within a plate lead to detectable nuisance signals, as revealed by a pre-trained deep neural network and analysis with deep image embeddings. Using a plate design and image acquisition strategy that accounts for these variables, we performed a pilot study with 12 healthy controls and 12 subjects affected by the severe genetic neurological disorder spinal muscular atrophy (SMA), and evaluated whether a convolutional neural network (CNN) generated using a subset of the cells could distinguish disease states on cells from the remaining unseen control-SMA pair. Our results indicate that these two populations could effectively be differentiated from one another and that model selectivity is insensitive to batch/plate type. One caveat is that the samples were also largely separated by source. These findings lay a foundation for how to conduct future studies exploring diseases with more complex genetic contributions and unknown subtypes.

With the advent of checkpoint inhibitors, there is increasing need to study the dynamics of CD8+ T-cells in the tumor microenviroment. In this article, we describe a semi-automated method to quantify and interrogate spatial relationships between T-cells and collagenous stroma in human and mouse tissue samples. The assay combines CD8 immunohistochemistry with modified Masson’s trichrome. Slides are scanned and digital images are analyzed using an adjustable MATLAB algorithm, allowing for high-throughput quantification of cytotoxic T-cells and collagen. This method provides a flexible tool for unbiased quantification of T-cells and their interactions with tumor cells and tumor microenvironment in tissue samples.

SARS-CoV-2, the coronavirus that causes COVID-19, evades the human immune system by capping its RNA. This process protects the viral RNA and is essential for its replication. Multiple viral proteins are involved in this RNA capping process, including the nonstructural protein 16 (nsp16), which is an S-adenosyl-l-methionine (SAM)-dependent 2'-O-methyltransferase. Nsp16 is significantly active when in complex with another nonstructural protein, nsp10, which plays a key role in its stability and activity. Here we report the development of a fluorescence polarization (FP)-based RNA displacement assay for nsp10-nsp16 complex in a 384-well format with a Z' factor of 0.6, suitable for high-throughput screening. In this process, we purified the nsp10-nsp16 complex to higher than 95% purity and confirmed its binding to the methyl donor SAM, the product of the reaction, S-adenosyl-l-homocysteine (SAH), and a common methyltransferase inhibitor, sinefungin, using isothermal titration calorimetry (ITC). The assay was further validated by screening a library of 1124 drug-like compounds. This assay provides a cost-effective high-throughput method for screening the nsp10-nsp16 complex for RNA competitive inhibitors toward developing COVID-19 therapeutics.

As of July 22, 2020, more than 14.7 million infections of SARS-CoV-2, the virus responsible for Coronavirus Disease 2019 (COVID-19), have been confirmed globally. Serological assays are essential for community screening, assessing infection prevalence, aiding identification of infected patients, and enacting appropriate treatment and quarantine protocols in the battle against this rapidly expanding pandemic. Antibody detection by agglutination-PCR (ADAP) is a pure solution phase immunoassay that generates a PCR amplifiable signal when patient antibodies agglutinate DNA-barcoded antigen probes into a dense immune complex. Here, we present an ultrasensitive and high-throughput automated liquid biopsy assay based on the Hamilton Microlab ADAP STAR automated liquid-handling platform, which was developed and validated for the qualitative detection of total antibodies against spike protein 1 (S1) of SARS-CoV-2 that uses as little as 4 µL of serum. To assess the clinical performance of the ADAP assay, 57 PCR-confirmed COVID-19 patients and 223 control patients were tested. The assay showed a sensitivity of 98% (56/57) and a specificity of 99.55% (222/223). Notably, the SARS-CoV-2-negative control patients included individuals with other common coronaviral infections, such as CoV-NL63 and CoV-HKU, which did not cross-react. In addition to high performance, the hands-free automated workstation enabled high-throughput sample processing to reduce screening workload while helping to minimize analyst contact with biohazardous samples. Therefore, the ADAP STAR liquid-handling workstation can be used as a valuable tool to address the COVID-19 global pandemic.

High-content screening to monitor disease-modifying phenotypes upon small-molecule addition has become an essential component of many drug and target discovery platforms. One of the most common phenotypic approaches, especially in the field of oncology research, is the assessment of cell viability. However, frequently used viability readouts employing metabolic proxy assays based on homogeneous colorimetric/fluorescent reagents are one-dimensional, provide limited information, and can in many cases yield conflicting or difficult-to-interpret results, leading to misinterpretation of data and wasted resources.The resurgence of high-content, phenotypic screening has significantly improved the quality and breadth of cell viability data, which can be obtained at the very earliest stages of drug and target discovery. Here, we describe a relatively inexpensive, high-throughput, high-content, multiparametric, fluorescent imaging protocol using a live-cell method of three fluorescent probes (Hoechst, Yo-Pro-3, and annexin V), that is amenable to the addition of further fluorophores. The protocol enables the accurate description and profiling of multiple cell death mechanisms, including apoptosis and necrosis, as well as accurate determination of compound IC50, and has been validated on a range of high-content imagers and image analysis software. To validate the protocol, we have used a small library of approximately 200 narrow-spectrum kinase inhibitors and clinically approved drugs. This fully developed, easy-to-use pipeline has subsequently been implemented in several academic screening facilities, yielding fast, flexible, and rich cell viability data for a range of early-stage high-throughput drug and target discovery programs.

The goal of high-throughput screening is to enable screening of compound libraries in an automated manner to identify quality starting points for optimization. This often involves screening a large diversity of compounds in an assay that preserves a connection to the disease pathology. Phenotypic screening is a powerful tool for drug identification, in that assays can be run without prior understanding of the target and with primary cells that closely mimic the therapeutic setting. Advanced automation and high-content imaging have enabled many complex assays, but these are still relatively slow and low throughput. To address this limitation, we have developed an automated workflow that is dedicated to processing complex phenotypic assays for flow cytometry. The system can achieve a throughput of 50,000 wells per day, resulting in a fully automated platform that enables robust phenotypic drug discovery. Over the past 5 years, this screening system has been used for a variety of drug discovery programs, across many disease areas, with many molecules advancing quickly into preclinical development and into the clinic. This report will highlight a diversity of approaches that automated flow cytometry has enabled for phenotypic drug discovery.

The Lush Science Prize 2016 was awarded to Daniele Zink and Lit-Hsin Loo for the interdisciplinary and collaborative work between their research groups in developing alternative methods for the prediction of nephrotoxicity in humans. The collaboration has led to the establishment of a series of pioneering alternative methods for nephrotoxicity prediction, which includes: predictive gene expression markers based on pro-inflammatory responses; predictive in vitro cellular models based on pluripotent stem cell-derived proximal tubular-like cells; and predictive cellular phenotypic markers based on chromatin and cytoskeletal changes. A high-throughput method was established for chemical testing, which is currently being used to predict the potential human nephrotoxicity of ToxCast compounds in collaboration with the US Environmental Protection Agency. Similar high-throughput imaging-based methodologies are currently being developed and adapted by the Zink and Loo groups, to include other human organs and cell types. The ultimate goal is to develop a portfolio of methods accepted for the accurate prediction of human organ-specific toxicity and the consequent replacement of animal experiments.

Angiogenesis is an important hallmark of cancer, contributing to tumor formation and metastasis. In vitro angiogenesis models for analyzing tube formation serve as useful tools to study these processes. However, current in vitro co-culture models using primary cells have limitations in usefulness and consistency. Therefore, in the present study, an in vitro co-culture assay system was optimized in a 1536-well format for high-throughput screening using human telomerase reverse transcriptase (hTERT)-immortalized mesenchymal stem cells and aortic endothelial cells. The National Center for Advancing Translational Sciences (NCATS) Pharmaceutical Collection (NPC) library containing 2816 drugs was evaluated using the in vitro co-culture assay. From the screen, 35 potent inhibitors (IC50 ≤1 µM) were identified, followed by 15 weaker inhibitors (IC50 1-50 µM). Moreover, many known angiogenesis inhibitors were identified, such as topotecan, docetaxel, and bortezomib. Several potential novel angiogenesis inhibitors were also identified from this study, including thimerosal and podofilox. Among the inhibitors, some compounds were proved to be involved in the hypoxia-inducible factor-1α (HIF-1α) and the nuclear factor-kappa B (NF-κB) pathways. The co-culture model developed by using hTERT-immortalized cell lines described in this report provides a consistent and robust in vitro system for antiangiogenic drug screening.

Background The global occurrence of dengue, a mosquito-borne viral disease caused by four distinct dengue viruses (DENV-1, -2, -3 and -4), is reported to have increased approximately 30-fold in the last 50 years, causing approximately 400 million infections a year. A limited use, sub-optimal live attenuated dengue vaccine has become available recently. It is becoming apparent that antibodies to DENVs can promote infection by Zika virus (ZIKV), a related mosquito-borne flavivirus. A drug to treat these flaviviral infections continues to be an unmet public health need. Methods We screened an ‘in-house’ library of approximately 2,000 small molecules for inhibitors of cloned DENV-2 protease. Putative inhibitor binding to DENV-2 protease was analysed by in silico docking. Anti-DENV activity was analysed by monitoring viral antigen synthesis by ELISA, viral RNA synthesis by reverse-transcription coupled to real-time polymerase chain reaction and infectious virus production by plaque assay, in DENV-infected Vero cells. Results A quinoline derivative, BT24, was identified for the first time as a potent inhibitor of the cloned DENV-2 protease (half maximal inhibitory concentration [IC50]=0.5 μM). In silico analysis revealed that BT24 binds to an allosteric site in the vicinity of the active site of DENV-2 protease. Cell-based assays demonstrated that BT24 can inhibit all four DENVs in infected Vero cells. Conclusions BT24 is a DENV-2 protease inhibitor which manifests the capacity to inhibit the replication of all four DENVs in cultured cells. It may provide a lead for a pan-DENV inhibitory drug.

Genotoxicants can be identified as aneugens and clastogens through a micronucleus (MN) assay. The current high-content screening-based MN assays usually discriminate an aneugen from a clastogen based on only one parameter, such as the MN size, intensity, or morphology, which yields low accuracies (70–84%) because each of these parameters may contribute to the results. Therefore, the development of an algorithm that can synthesize high-dimensionality data to attain comparative results is important. To improve the automation and accuracy of detection using the current parameter-based mode of action (MoA), the MN MoA signatures of 20 chemicals were systematically recruited in this study to develop an algorithm. The results of the algorithm showed very good agreement (93.58%) between the prediction and reality, indicating that the proposed algorithm is a validated analytical platform for the rapid and objective acquisition of genotoxic MoA messages.

The 21st century paradigm for toxicology and the adverse outcome pathway concept envisage a future toxicology largely based on mechanistic in vitro assays and relying mainly on cellular models. In the skin sensitisation field, this concept was not intuitive at the beginning. Given the high structural diversity of skin sensitising molecules, classical receptor binding as the molecular initiating event in a cell-based assay could be excluded from the start, leaving the question of how cells could sense potential skin sensitising chemicals and be able to differentiate them from non-sensitisers. When we entered this field in 2006, we realised that, in another emerging field of toxicology, detailed work on the antioxidant/electrophile sensing pathway Keap1/Nrf2/ARE was being performed. We postulated that, based on their intrinsic electrophilicity, a large structural variety of skin sensitisers would activate this pathway. This was demonstrated in a preliminary pilot study with an existing, breast cancer-derived reporter cell line. Broader confirmation of this initial hypothesis then came from a multitude of genome-wide studies, in which sensitiser-induced changes to the transcriptome were investigated. The results showed that this regulatory pathway is indeed the most common regulatory pathway activated by sensitisers at the gene expression level, and the underlying event in keratinocytes has become formalised as a Key Event in the Organisation for Economic Co-operation and Development (OECD) Adverse Outcome Pathway for sensitisation. These studies led to the development of the KeratinoSens® assay, which became the first cell-based in vitro test for skin sensitisation to be endorsed by a European Union Reference Laboratory for Alternatives to Animal Testing (EURL ECVAM) statement and an OECD Test Guideline. More recently, a number of studies have further developed this approach into 3-D skin models. Here, we review the underlying mechanism and the development of the KeratinoSens assay. We also present data on the stability of the assay over time, which is a key requirement for a cell-based biological assay to be endorsed in a regulatory context.

Objective: To develop a mouse cell biosensor system for the high-throughput genotoxicity detection of chemicals, such as environmental pollutants. Method: We developed a novel reporter vector pGL4-GFP, wherein the firefly luciferase reporter gene in the pGL4.82 vector was replaced by the green fluorescent protein (GFP) gene from the pAcGFP1-N1 vector. To construct the reporter pGL4-p53-GFP (p53 promoter linked to GFP), a fragment containing the p53 gene promoter was generated by amplifying a region from −481 to +180 of mouse genomic DNA isolated from mouse tail tissue. We developed a mouse cell biosensor system for the high-throughput genotoxicity detection of new drugs by stably integrating the reporter plasmid of pGL4-p53-GFP into the mouse embryonic fibroblast cells. Various genotoxic agents were used to treat this biosensor system. The resulting fluorescence was directly observed under a fluorescence microscope, and the GFP protein level was measured through Western blot analysis. Result: The biosensor system was treated with genotoxic agents, such as doxorubicin, cyclophosphamide, and benzo(a)pyrene. The GFP protein expression was significantly increased in cells exposed to genotoxic agents but negatively responded to the non-genotoxic agent dimethyl sulfoxide, thereby proving the specificity and sensitivity of the biosensor system. Conclusion: This novel in vitro biosensor system can be especially useful in genotoxicity detection.

The application of patient-derived three-dimensional culture systems as disease-specific drug sensitivity models has enormous potential to connect compound screening and clinical trials. However, the implementation of complex cell-based assay systems in drug discovery requires reliable and robust screening platforms. Here we describe the establishment of an automated platform in 384-well format for three-dimensional organoid cultures derived from colon cancer patients. Single cells were embedded in an extracellular matrix by an automated workflow and subsequently self-organized into organoid structures within 4 days of culture before being exposed to compound treatment. We performed validation of assay robustness and reproducibility via plate uniformity and replicate-experiment studies. After assay optimization, the patient-derived organoid platform passed all relevant validation criteria. In addition, we introduced a streamlined plate uniformity study to evaluate patient-derived colon cancer samples from different donors. Our results demonstrate the feasibility of using patient-derived tumor samples for high-throughput assays and their integration as disease-specific models in drug discovery.

Compound screening in biological assays and subsequent optimization of hits is indispensable for the development of new molecular research tools and drug candidates. To facilitate such discoveries, the European Research Infrastructure EU-OPENSCREEN was founded recently with the support of its member countries and the European Commission. Its distributed character harnesses complementary knowledge, expertise, and instrumentation in the discipline of chemical biology from 20 European partners, and its open working model ensures that academia and industry can readily access EU-OPENSCREEN’s compound collection, equipment, and generated data. To demonstrate the power of this collaborative approach, this perspective article highlights recent projects from EU-OPENSCREEN partner institutions. These studies yielded (1) 2-aminoquinazolin-4(3H)-ones as potential lead structures for new antimalarial drugs, (2) a novel lipodepsipeptide specifically inducing apoptosis in cells deficient for the pVHL tumor suppressor, (3) small-molecule-based ROCK inhibitors that induce definitive endoderm formation and can potentially be used for regenerative medicine, (4) potential pharmacological chaperones for inborn errors of metabolism and a familiar form of acute myeloid leukemia (AML), and (5) novel tankyrase inhibitors that entered a lead-to-candidate program. Collectively, these findings highlight the benefits of small-molecule screening, the plethora of assay designs, and the close connection between screening and medicinal chemistry within EU-OPENSCREEN. The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: NOR-OPENSCREEN, funded by the Research Council of Norway (RCN) and the K.G. Jebsen Centre for Neuropsychiatric Disorders, for financial support (to A.M.). The Danish Research Infrastructure for Chemical Biology, DK-OPENSCREEN, acknowledges financial support from the Ministry of Higher Education and Science (grant case no. 5072-00019B), the Technical University of Denmark, and the other contributing universities. The Latvian Institute of Organic Synthesis acknowledges the European Regional Development Fund (agreement no. 1.1.1.1/16/A/290) for financial support. L.L. acknowledges the Academy of Finland (grant nos. 287063 and 294085) and the Jane and Aatos Erkko Foundation for funding. EU-OPENSCREEN acknowledges its member and observer states for funding and support. P. Bartunek acknowledges MEYS (LO1220 and LM2015063) for funding. P.G. and H.L. acknowledge funding from the German Federal Ministry of Education and Research. J.L.K. and R.P. acknowledge financial support from the Polish Ministry of Science and Higher Education (KNOW program and POL-OPENSCREEN project number 401086). M.J.V. acknowledges the European Regional Development Fund and the Conselleria de Sanitat Universal i Salut Pública (Generalitat Valenciana, GVA) SI

The conjugation/de-conjugation of Small Ubiquitin-like Modifier (SUMO) has been shown to be associated with a diverse set of physiologic/pathologic conditions. The clinical significance and ostensible therapeutic utility offered via the selective control of the global SUMOylation process has become readily apparent in ischemic pathophysiology. Herein, we describe the development of a novel quantitative high-throughput screening (qHTS) system designed to identify small molecules capable of increasing SUMOylation via the regulation/inhibition of members of the microRNA (miRNA)-182 family. This assay employs a SHSY5Y human neuroblastoma cell line stably transfected with a dual firefly-Renilla luciferase reporter system for identification of specific inhibitors of either miR-182 or miR-183. In this study, we have identified small molecules capable of inducing increased global conjugation of SUMO in both SHSY5Y cells and rat E18-derived primary cortical neurons. The protective effects of a number of the identified compounds were confirmed via an in vitro ischemic model (oxygen/glucose deprivation). Of note, this assay can be easily repurposed to allow high-throughput analyses of the potential drugability of other relevant miRNA(s) in ischemic pathobiology.