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Plasmodium parasite resistance to antimalarial drugs is a serious threat to public health in malaria-endemic areas. Compounds that target core cellular processes like translation are highly desirable, as they should be capable of killing parasites in their liver and blood stage forms, regardless of molecular target or mechanism. Assays that can identify these compounds are thus needed. Recently, specific quantification of native Plasmodium berghei liver stage protein synthesis, as well as that of the hepatoma cells supporting parasite growth, was achieved via automated confocal feedback microscopy of the o-propargyl puromycin (OPP)-labeled nascent proteome, but this imaging modality is limited in throughput. Here, we developed and validated a miniaturized high content imaging (HCI) version of the OPP assay that increases throughput, before deploying this approach to screen the Pathogen Box. We identified only two hits; both of which are parasite-specific quinoline-4-carboxamides, and analogs of the clinical candidate and known inhibitor of blood and liver stage protein synthesis, DDD107498/cabamiquine. We further show that these compounds have strikingly distinct relationships between their antiplasmodial and translation inhibition efficacies. These results demonstrate the utility and reliability of the P. berghei liver stage OPP HCI assay for the specific, single-well quantification of Plasmodium and human protein synthesis in the native cellular context, allowing the identification of selective Plasmodium translation inhibitors with the highest potential for multistage activity.

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The use of organoid models in biomedical research has grown substantially since their inception. As they gain popularity among scientists seeking more complex and biologically relevant systems, there is a direct need to expand and clarify potential uses of such systems in diverse experimental contexts. Herein we outline a high-content screening (HCS) platform that allows researchers to screen drugs or other compounds against three-dimensional (3D) cell culture systems in a multi-well format (384-well). Furthermore, we compare the quality of robotic liquid handling with manual pipetting and characterize and contrast the phenotypic effects detected by confocal imaging and biochemical assays in response to drug treatment. We show that robotic liquid handling is more consistent and amendable to high throughput experimental designs when compared to manual pipetting due to improved precision and automated randomization capabilities. We also show that image-based techniques are more sensitive to detecting phenotypic changes within organoid cultures than traditional biochemical assays that evaluate cell viability, supporting their integration into organoid screening workflows. Finally, we highlight the enhanced capabilities of confocal imaging in this organoid screening platform as they relate to discerning organoid drug responses in single-well co-cultures of organoids derived from primary human biopsies and patient-derived xenograft (PDX) models. Altogether, this platform enables automated, imaging-based HCS of 3D cellular models in a non-destructive manner, opening the path to complementary analysis through integrated downstream methods.

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Quantitative morphological phenotyping (QMP) is an image-based method used to capture morphological features at both the cellular and population level. Its interdisciplinary nature, spanning from data collection to result analysis and interpretation, can lead to uncertainties, particularly among those new to this actively growing field. High analytical specificity for a typical QMP is achieved through sophisticated approaches that can leverage subtle cellular morphological changes. Here, we outline a systematic workflow to refine the QMP methodology. For a practical review, we describe the main steps of a typical QMP; in each step, we discuss the available methods, their applications, advantages, and disadvantages, along with the R functions and packages for easy implementation. This review does not cover theoretical backgrounds, but provides several references for interested researchers. It aims to broaden the horizons for future phenome studies and demonstrate how to exploit years of endeavors to achieve more with less.

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This study demonstrated the strengths of in vivo molecular staining coupled with automated imaging analysis in Daphnia magna. A multiwell plate protocol was developed to assess mitochondrial membrane potential using the JC-1 dye. The suitability of five common anesthetics was initially tested, and 5% ethanol performed best in terms of anesthetic effects and healthy recovery. The staining conditions were optimized to 30 min staining with 2 µM JC-1 for best J-aggregate formation. The protocol was validated with the model compound carbonyl cyanide 3-chlorophenylhydrazone (CCCP) and used to measure the effect of four environmental contaminants, 2,4-dinitrophenol, triclosan, n-(1,3-dimethylbutyl)-N'-phenyl-p-phenylenediamine (6PPD), and ibuprofen, on mitochondrial health. Test organisms were imaged using an automated confocal microscope, and fluorescence intensities were automatically quantified. The effect concentrations for CCCP were lower by a factor of 30 compared with the traditional OECD 202 acute toxicity test. Mitochondrial effects were also detected at lower concentrations for all tested environmental contaminants compared to the OCED 202 test. For 2,4-dinitrophenol, mitochondria effects were detectable after 2 h exposure to environmentally relevant concentrations and predicted organism death was observed after 24 h. The high sensitivity and time efficiency of this novel automated imaging method make it a valuable tool for advancing ecotoxicological testing.

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Convalescent sera, rich in pathogen-specific antibodies, offers passive immunity to patients with infectious diseases. Screening assays using convalescent sera are crucial for evaluating therapeutic efficacy, selecting suitable serum donors, and standardizing assays. They measure antibody levels, neutralizing potential, and specificity against viruses like SARS-CoV-2, ensuring therapeutic serum contains potent antibodies. Standardized procedures enable reliable results and wider adoption of serum therapy for COVID-19. We have developed a high-content image-based assay for screening convalescent sera against SARS-CoV-2 variants. Using various cell lines, we identified optimal candidates, employed immunofluorescence to visualize infected cells, and assessed neutralizing antibody efficacy. Screening convalescent sera for therapeutic potential identified neutralizing activity against SARS-CoV-2 variants. Dose-response analysis showed variable neutralizing activity, with some sera exhibiting broad neutralization. Additionally, we explored the synergy between neutralizing sera and ß-d-N4-hydroxycytidine (NHC), an initial metabolite of molnupiravir. These assays enhance serum therapy's benefits for COVID-19 treatment and aid in understanding neutralizing activity against SARS-CoV-2 variants, addressing viral challenges.

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Amyotrophic lateral sclerosis (ALS) is a rapidly progressing, highly heterogeneous neurodegenerative disease, underscoring the importance of obtaining information to personalize clinical decisions quickly after diagnosis. Here, we investigated whether ALS-relevant signatures can be detected directly from biopsied patient fibroblasts. We profiled familial ALS (fALS) fibroblasts, representing a range of mutations in the fused in sarcoma (FUS) gene and ages of onset. To differentiate FUS fALS and healthy control fibroblasts, machine-learning classifiers were trained separately on high-content imaging and transcriptional profiles. "Molecular ALS phenotype" scores, derived from these classifiers, captured a spectrum from disease to health. Interestingly, these scores negatively correlated with age of onset, identified several pre-symptomatic individuals and sporadic ALS (sALS) patients with FUS-like fibroblasts, and quantified "movement" of FUS fALS and "FUS-like" sALS toward health upon FUS ASO treatment. Taken together, these findings provide evidence that non-neuronal patient fibroblasts can be used for rapid, personalized assessment in ALS.

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The development of inhaled drugs for respiratory diseases is frequently impacted by lung pathology in non-clinical safety studies. To enable design of novel candidate drugs with the right safety profile, predictive in vitro lung toxicity assays are required that can be applied during drug discovery for early hazard identification and mitigation. Here, we describe a novel high-content imaging-based screening assay that allows for quantification of the tight junction protein occludin in A549 cells, as a model for lung epithelial barrier integrity. We assessed a set of compounds with a known lung safety profile, defined by clinical safety or non-clinical in vivo toxicology data, and were able to correctly identify 9 of 10 compounds with a respiratory safety risk and 9 of 9 compounds without a respiratory safety risk (90% sensitivity, 100% specificity). The assay was sensitive at relevant compound concentrations to influence medicinal chemistry optimization programs and, with an accessible cell model in a 96-well plate format, short protocol and application of automated imaging analysis algorithms, this assay can be readily integrated in routine discovery safety screening to identify and mitigate respiratory toxicity early during drug discovery. Interestingly, when we applied physiologically-based pharmacokinetic (PBPK) modelling to predict epithelial lining fluid exposures of the respiratory tract after inhalation, we found a robust correlation between in vitro occludin assay data and lung pathology in vivo, suggesting the assay can inform translational risk assessment for inhaled small molecules.

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Hereditary spastic paraplegias (HSPs) are a heterogeneous group of mono-genetic inherited neurological disorders, whose primary manifestation is the disruption of the pyramidal system, observed as a progressive impaired gait and leg spasticity in patients. Despite the large list of genes linked to this group, which exceeds 80 loci, the number of cellular functions which the gene products engage is relatively limited, among which endoplasmic reticulum (ER) morphogenesis appears central. Mutations in genes encoding ER-shaping proteins are the most common cause of HSP, highlighting the importance of correct ER organisation for long motor neuron survival. However, a major bottleneck in the study of ER morphology is the current lack of quantitative methods, with most studies to date reporting, instead, on qualitative changes. Here, we describe and apply a quantitative image-based screen to identify genetic modifiers of ER organisation using a mammalian cell culture system. An analysis reveals significant quantitative changes in tubular ER and dense sheet ER organisation caused by the siRNA-mediated knockdown of HSP-causing genes ATL1 and RTN2. This screen constitutes the first attempt to examine ER distribution in cells in an automated and high-content manner and to detect genes which impact ER organisation.

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Introduction: In mitochondrial DNA (mtDNA) depletion syndrome (MDS), patients cannot maintain sufficient mtDNA for their energy needs. MDS presentations range from infantile encephalopathy with hepatopathy (Alpers syndrome) to adult chronic progressive external ophthalmoplegia. Most are caused by nucleotide imbalance or by defects in the mtDNA replisome. There is currently no curative treatment available. Nucleoside therapy is a promising experimental treatment for TK2 deficiency, where patients are supplemented with exogenous deoxypyrimidines. We aimed to explore the benefits of nucleoside supplementation in POLG and TWNK deficient fibroblasts. Methods: We used high-content fluorescence microscopy with software-based image analysis to assay mtDNA content and membrane potential quantitatively, using vital dyes PicoGreen and MitoTracker Red CMXRos respectively. We tested the effect of 15 combinations (A, T, G, C, AT, AC, AG, CT, CG, GT, ATC, ATG, AGC, TGC, ATGC) of deoxynucleoside supplements on mtDNA content of fibroblasts derived from four patients with MDS (POLG1, POLG2, DGUOK, TWNK) in both a replicating (10% dialysed FCS) and quiescent (0.1% dialysed FCS) state. We used qPCR to measure mtDNA content of supplemented and non-supplemented fibroblasts following mtDNA depletion using 20 µM ddC and after 14- and 21-day recovery in a quiescent state. Results: Nucleoside treatments at 200 µM that significantly increased mtDNA content also significantly reduced the number of cells remaining in culture after 7 days of treatment, as well as mitochondrial membrane potential. These toxic effects were abolished by reducing the concentration of nucleosides to 50 µM. In POLG1 and TWNK cells the combination of ATGC treatment increased mtDNA content the most after 7 days in non-replicating cells. ATGC nucleoside combination significantly increased the rate of mtDNA recovery in quiescent POLG1 cells following mtDNA depletion by ddC. Conclusion: High-content imaging enabled us to link mtDNA copy number with key read-outs linked to patient wellbeing. Elevated G increased mtDNA copy number but severely impaired fibroblast growth, potentially by inhibiting purine synthesis and/or causing replication stress. Combinations of nucleosides ATGC, T, or TC, benefited growth of cells harbouring POLG mutations. These combinations, one of which reflects a commercially available preparation, could be explored further for treatment of POLG patients.

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Interference in cell cycle progression has been noted as one of the important properties of anticancer drugs. In this study, we developed the cell cycle prediction model using high-content imaging data of recipient cells after drug exposure and DNA-staining with a low-toxic DNA dye, SiR-DNA. For this purpose, we exploited HeLa and MCF7 cells introduced with a fluorescent ubiquitination-based cell cycle indicator (Fucci). Fucci-expressing cancer cells were subjected to high-content imaging analysis using OperettaCLS after 36-h exposure to anticancer drugs; the nuclei were segmented, and the morphological and intensity properties of each nucleus characterized by SiR-DNA staining were calculated using imaging analysis software, Harmony. For the use of training, we classified cells into each phase of the cell cycle using the Fucci system. Training data (n = 7500) and validation data (n = 2500) were randomly sampled and the binary classification prediction models for G1, early S, and S/G2/M phases of the cell cycle were developed using four supervised machine learning algorithms. We selected random forest as the model with the best performance through 10-fold cross-validation; the accuracy rate was approximately 75%-87%. Regarding feature importance, variables expected to be biologically related to the cell cycle, for example, signal intensity and nuclear size, were highly ranked, suggesting the validity of the model. These results showed that the cell cycle can be predicted in cancer cells by simply exploiting the current prediction model using fluorescent images of DNA-staining dye, and the model could be applied for the use of future ex vivo drug sensitivity diagnosis.

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Organophosphate esters (OPEs), used as flame retardants and plasticizers, are present ubiquitously in the environment. Previous studies suggest that exposure to OPEs is detrimental to female fertility in humans. However, no experimental information is available on the effects of OPE mixtures on ovarian granulosa cells, which play essential roles in female reproduction. We used high-content imaging to investigate the effects of environmentally relevant OPE mixtures on KGN human granulosa cell phenotypes. Perturbations to steroidogenesis were assessed using ELISA and qRT-PCR. A high-throughput transcriptomic approach, TempO-Seq, was used to identify transcriptional changes in a targeted panel of genes. Effects on lipid homeostasis were explored using a cholesterol assay and global lipidomic profiling. OPE mixtures altered multiple phenotypic features of KGN cells, with triaryl OPEs in the mixture showing higher potencies than other mixture components. The mixtures increased basal production of steroid hormones; this was mediated by significant changes in the expression of critical transcripts involved in steroidogenesis. Further, the total-OPE mixture disrupted cholesterol homeostasis and the composition of intracellular lipid droplets. Exposure to complex mixtures of OPEs, similar to those found in house dust, may adversely affect female reproductive health by altering a multitude of phenotypic and functional endpoints in granulosa cells. This study provides novel insights into the mechanisms of actions underlying the toxicity induced by OPEs and highlights the need to examine the effects of human relevant chemical mixtures.

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Introduction: Antiretroviral (ARV) drugs have improved prognoses for people living with HIV. However, HIV-associated neurocognitive disorders (HAND) persist despite undetectable viral loads. Some ARVs have been linked to neuropsychiatric effects that may contribute to HAND. Synapse loss correlates with cognitive decline in HAND and synaptic deficits may contribute to the neuropsychiatric effects of ARV drugs. Methods: Using an automated high content assay, rat hippocampal neurons in culture expressing PSD95-eGFP to label glutamatergic synapses and mCherry to fill neuronal structures were imaged before and after treatment with 25 clinically used ARVs. Results and Discussion: At a concentration of 10 µM the protease inhibitors nelfinavir and saquinavir, the non-nucleoside reverse transcriptase inhibitors etravirine and the 8-OH metabolite of efavirenz, the integrase inhibitor bictegravir, and the capsid inhibitor lenacapavir produced synaptic toxicity. Only lenacapavir produced synapse loss at the nanomolar concentrations estimated free in the plasma, although all 4 ARV drugs induced synapse loss at Cmax. Evaluation of combination therapies did not reveal synergistic synaptic toxicity. Synapse loss developed fully by 24 h and persisted for at least 3 days. Bictegravir-induced synapse loss required activation of voltage-gated Ca2+ channels and bictegravir, etravirine, and lenacapavir produced synapse loss by an excitotoxic mechanism. These results indicate that select ARV drugs might contribute to neuropsychiatric effects in combination with drugs that bind serum proteins or in disease states in which synaptic function is altered. The high content imaging assay used here provides an efficient means to evaluate new drugs and drug combinations for potential CNS toxicity.

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Per- and polyfluoroalkyl substances (PFAS) is a large compound class (n > 12,000) that is extensively present in food, drinking water, and aquatic environments. Reduced serum triglycerides and hepatosteatosis appear to be the common phenotypes for different PFAS chemicals. However, the hepatosteatosis potential of most PFAS chemicals remains largely unknown. This study aims to investigate PFAS-induced hepatosteatosis using in vitro high-throughput phenotype profiling (HTPP) and high-throughput transcriptomic (HTTr) data. We quantified the in vitro hepatosteatosis effects and mitochondrial damage using high-content imaging, curated the transcriptomic data from the Gene Expression Omnibus (GEO) database, and then calculated the point of departure (POD) values for HTPP phenotypes or HTTr transcripts, using the Bayesian benchmark dose modeling approach. Our results indicated that PFAS compounds with fully saturated C-F bonds, sulfur- and nitrogen-containing functional groups, and a fluorinated carbon chain length greater than 8 have the potential to produce biological effects consistent with hepatosteatosis. PFAS primarily induced hepatosteatosis via disturbance in lipid transport and storage. The potency rankings of PFAS compounds are highly concordant among in vitro HTPP, HTTr, and in vivo hepatosteatosis phenotypes (ρ = 0.60-0.73). In conclusion, integrating the information from in vitro HTPP and HTTr analyses can accurately project in vivo hepatosteatosis effects induced by PFAS compounds.

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Functional genomics and chemical screens can identify and characterize novel cellular factors regulating signaling networks and chemical tools to modulate their function for the treatment of disease. Screening methods have relied primarily on immortalized and/or transformed cancer cell lines, which can limit the generalization of results to more physiologically relevant systems. Most have also relied on immunofluorescence, or on stably expressed recombinant fluorescent proteins, to detect specific protein markers using high-content imaging readouts. In comparison, high-throughput methods to visualize and measure RNA species have been less explored. To address this, we have adapted an isothermal signal amplification chemistry for RNA FISH known as hybridization chain reaction (HCR) to an automated, high-content imaging assay format. We present a detailed protocol for this technique, which we have named high-content HCR (hcHCR). The protocol focuses on the measurement of changes in mRNA abundance at the single-cell level in human primary cells, but it can be applied to a variety of primary cell types and perturbing agents. We anticipate that hcHCR will be most suitable for low- to medium-throughput screening experiments in which changes in transcript abundance are the desired output measure.

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Alternative lengthening of telomeres (ALT) is a telomerase-independent and recombination-based mechanism used by approximately 15% of human cancers to maintain telomere length and to sustain proliferation. ALT-positive cells display unique features that could be exploited for tailored cancer therapies. A key limitation for the development of ALT-specific treatments is the lack of an assay to detect ALT-positive cells that is easy to perform and that can be scaled up. One of the most broadly used assays for ALT detection, CCA (C-circle assay), does not provide single-cell information and it is not amenable to High-Throughput Screening (HTS). To overcome these limitations, we developed Native-FISH (N-FISH) as an alternative method to visualize ALT-specific single-stranded telomeric DNA. N-FISH produces single-cell data, can be applied to fixed tissues, does not require DNA isolation or amplification steps, and it can be miniaturized in a 384-well format. This protocol details the steps to perform N-FISH protocol both in a low- and high-throughput format to analyze ALT. While low-throughput N-FISH is useful to assay the ALT state of cell lines, we expect that the miniaturized N-FISH assay coupled with high-throughput imaging will be useful in functional genomics and chemical screens to identify novel cellular factors that regulate ALT and potential ALT therapeutic targets for cancer therapies directed against ALT-positive tumors, respectively.

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BACKGROUND: COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can affect multiple organ systems, including the pulmonary vasculature. Endothelial cells (ECs) are thought to play a key role in the propagation of COVID-19, however, our understanding of the exact scale of dysregulation sustained by the pulmonary microvasculature (pMV) remains incomplete. Here we aim to identify transcriptional, phenotypic, and functional changes within the pMV induced by COVID-19. METHODS AND RESULTS: Human pulmonary microvascular endothelial cells (HPMVEC) treated with plasma acquired from patients hospitalised with severe COVID-19 were compared to HPMVEC treated with plasma from patients hospitalised without COVID-19 but with other severe illnesses. Exposure to COVID-19 plasma caused a significant functional decline in HPMVECs as seen by a decrease in both cell viability via the WST-1 cell-proliferation assay and cell-to-cell barrier function as measured by electric cell-substrate impedance sensing. High-content imaging using a Cell Painting image-based assay further quantified morphological variations within sub-cellular organelles to show phenotypic changes in the whole endothelial cell, nucleus, mitochondria, plasma membrane and nucleolus morphology. RNA-sequencing of HPMVECs treated with COVID-19 plasma suggests the observed phenotype may, in part, be regulated by genes such as SMAD7, BCOR, SFMBT1, IFIT5 and ZNF566 which are involved in transcriptional regulation, protein monoubiquitination and TGF-ß signalling. CONCLUSION AND IMPACT: During COVID-19, the pMV undergoes significant remodelling, which is evident based on the functional, phenotypic, and transcriptional changes seen following exposure to COVID-19 plasma. The observed morphological variation may be responsible for downstream complications, such as a decline in overall cellular function and cell-to-cell barrier integrity. Moreover, genes identified through bulk RNA sequencing may contribute to our understanding of the observed phenotype and assist in developing strategies that can inform the rescue of the dysregulated endothelium.

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This study aimed to identify inhibitors of the translocated intimin receptor (Tir) of enteropathogenic Escherichia coli (EPEC). EPEC is an intestinal pathogen that causes diarrhea and is a major health concern worldwide. Because Tir is a key virulence factor involved in EPEC pathogenesis, inhibiting its function is a potential strategy for controlling EPEC infections. Virtual screening was applied to chemical libraries to search for compounds that inhibit Tir-mediated bacterial adherence to host cells. Three sites were targeted using the cocrystal structure published earlier. A selection of compounds was then assessed in a cell-based infection model and fluorescence microscopy assay. The results of this study provide a basis for further optimization and testing of Tir inhibitors as potential therapeutic agents for EPEC infections.

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Combining high-throughput generation and high-content imaging of embryo models will enable large-scale screening assays in the fields of (embryo) toxicity, drug development, embryogenesis, and reproductive medicine. This study shows the continuous culture and in situ (i.e., in microwell) imaging-based readout of a 3D stem cell-based model of peri-implantation epiblast (Epi)/extraembryonic endoderm (XEn) development with an expanded pro-amniotic cavity (PAC) (E3.5 E5.5), namely XEn/EPiCs. Automated image analysis and supervised machine learning permit the identification of embryonic morphogenesis, tissue compartmentalization, cell differentiation, and consecutive classification. Screens with signaling pathway modulators at different time windows provide spatiotemporal information on their phenotypic effect on developmental processes leading to the formation of XEn/EPiCs. Exposure of the biological model in the microwell platform to pathway modulators at two time windows, namely 0-72 h and 48-120 h, show that Wnt and Fgf/MAPK pathway modulators affect Epi differentiation and its polarization, while modulation of BMP and Tgfß/Nodal pathway affects XEn specification and epithelialization. Further, their collective role is identified in the timing of the formation and expansion of PAC. The newly developed, scalable culture and analysis platform, thereby, provides a unique opportunity to quantitatively and systematically study effects of pathway modulators on early embryonic development.

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The recent pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) posed a major threat to global health. Although the World Health Organization ended the public health emergency status, antiviral drugs are needed to address new variants of SARS-CoV-2 and future pandemics. To identify novel broad-spectrum coronavirus drugs, we developed a high-content imaging platform compatible with high-throughput screening. The platform is broadly applicable as it can be adapted to include various cell types, viruses, antibodies, and dyes. We demonstrated that the antiviral activity of compounds against SARS-CoV-2 variants (Omicron BA.5 and Omicron XBB.1.5), SARS-CoV, and human coronavirus 229E could easily be assessed. The inclusion of cellular dyes and immunostaining in combination with in-depth image analysis enabled us to identify compounds that induced undesirable phenotypes in host cells, such as changes in cell morphology or in lysosomal activity. With the platform, we screened ∼900K compounds and triaged hits, thereby identifying potential candidate compounds carrying broad-spectrum activity with limited off-target effects. The flexibility and early-stage identification of compounds with limited host cell effects provided by this high-content imaging platform can facilitate coronavirus drug discovery. We anticipate that its rapid deployability and fast turnaround can also be applied to combat future pandemics.

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A defining feature of sea urchins is their extreme fecundity. Urchins produce millions of transparent, synchronously developing embryos, ideal for spatial and temporal analysis of development. This biological feature has been effectively utilized for ensemble measurement of biochemical changes. However, it has been underutilized in imaging studies, where single embryo measurements are used. Here we present an example of how stable genetics and high content imaging, along with machine learning-based image analysis, can be used to exploit the fecundity and synchrony of sea urchins in imaging-based drug screens. Building upon our recently created sea urchin ABCB1 knockout line, we developed a high-throughput assay to probe the role of this drug transporter in embryos. We used high content imaging to compare accumulation and toxicity of canonical substrates and inhibitors of the transporter, including fluorescent molecules and antimitotic cancer drugs, in homozygous knockout and wildtype embryos. To measure responses from the resulting image data, we used a nested convolutional neural network, which rapidly classified embryos according to fluorescence or cell division. This approach identified sea urchin embryos with 99.8% accuracy and determined two-cell and aberrant embryos with 96.3% and 89.1% accuracy, respectively. The results revealed that ABCB1 knockout embryos accumulated the transporter substrate calcein 3.09 times faster than wildtypes. Similarly, knockouts were 4.71 and 3.07 times more sensitive to the mitotic poisons vinblastine and taxol. This study paves the way for large scale pharmacological screens in the sea urchin embryo.