Characterization of Foodborne Pathogens in Biofilms: A Four-Dimensional Structural Dynamics Approach Using HCS-CLSM.

The functional properties of biofilms are intimately related to their spatial architecture. Structural data are therefore of prime importance to dissect the complex social and survival strategies of biofilms and ultimately to improve their control. Confocal laser scanning microscopy (CLSM) is the most widespread microscopic tool to decipher biofilm structure, enabling noninvasive three-dimensional investigation of their dynamics down to the single-cell scale. The emergence of fully automated high content screening (HCS) systems, associated with large-scale image analysis, has radically amplified the flow of available biofilm structural data. In this contribution, we present a HCS-CLSM protocol used to analyze biofilm four-dimensional structural dynamics at high throughput. Meta-analysis of the quantitative variables extracted from HCS-CLSM will contribute to a better biological understanding of biofilm traits.

Development and characterization of reverse genetics systems of feline infectious peritonitis virus for antiviral research.

Feline infectious peritonitis (FIP) is a lethal, immune-mediated disease in cats caused by feline infectious peritonitis virus (FIPV), a biotype of feline coronavirus (FCoV). In contrast to feline enteric coronavirus (FECV), which exclusively infects enterocytes and causes diarrhea, FIPV specifically targets macrophages, resulting in the development of FIP. The transmission and infection mechanisms of this complex, invariably fatal disease remain unclear, with no effective vaccines or approved drugs for its prevention or control. In this study, a full-length infectious cDNA clone of the wild-type FIPV WSU79-1149 strain was constructed to generate recombinant FIPV (rFIPV-WT), which exhibited similar growth kinetics and produced infectious virus titres comparable to those of the parental wild-type virus. In addition, the superfold green fluorescent protein (msfGFP) and Renilla luciferase (Rluc) reporter genes were incorporated into the rFIPV-WT cDNA construct to generate reporter rFIPV-msfGFP and rFIPV-Rluc viruses. While the growth characteristics of the rFIPV-msfGFP virus were similar to those of its parental rFIPV-WT, the rFIPV-Rluc virus replicated more slowly, resulting in the formation of smaller plaques than did the rFIPV-WT and rFIPV-msfGFP viruses. In addition, by replacing the S, E, M, and ORF3abc genes with msfGFP and Rluc genes, the replicon systems repFIPV-msfGFP and repFIPV-Rluc were generated on the basis of the cDNA construct of rFIPV-WT. Last, the use of reporter recombinant viruses and replicons in antiviral screening assays demonstrated their high sensitivity for quantifying the antiviral effectiveness of the tested compounds. This integrated system promises to significantly streamline the investigation of virus replication within host cells, enabling efficient screening for anti-FIPV compounds and evaluating emerging drug-resistant mutations within the FIPV genome.

High Content Screening Assay of Inhibitors of the Legionella pneumophila Histone Methyltransferase RomA in Infected Cells.

Resistance to anti-microbial agents is a world-wide health threat. Thus there is an urgent need for new treatments. An alternative approach to disarm pathogens consists in developing drugs targeting epigenetic modifiers. Bacterial pathogens can manipulate epigenetic regulatory systems of the host to bypass defences to proliferate and survive. One example is Legionella pneumophila, a Gram-negative intracellular pathogen that targets host chromatin with a specific, secreted bacterial SET-domain methyltransferase named RomA. This histone methyltransferase specifically methylates H3K14 during infection and is responsible for changing the host epigenetic landscape upon L. pneumophila infection. To inhibit RomA activity during infection, we developed a reliable high-content imaging screening assay, which we used to screen an in-house chemical library developed to inhibit DNA and histone methyltransferases. This assay was optimised using monocytic leukemic THP-1 cells differentiated into macrophages infected with L. pneumophila in a 96- or 384-well plate format using the Opera Phenix® (Perkin Elmer) confocal microscope, combined with Columbus™ software for automated image acquisition and analysis. H3K14 methylation was followed in infected, single cells and cytotoxicity was assessed in parallel. A first pilot screening of 477 compounds identified a potential starting point for inhibitors of H3K14 methylation.

Development of an automated high-content immunofluorescence assay of pSmads quantification: Proof-of-concept with drugs inhibiting the BMP/TGF-ß pathways.

INTRODUCTION: Bone morphogenetic proteins (BMPs) and transforming growth factors (TGF-ß) are members of the TGF-ß superfamily, known for their roles in several physiological and pathological processes. These factors are known to bind in vivo to BMP and TGF-ß receptors, respectively, which induces the phosphorylation of Smad (pSmad) transcription factors. This pathway is generally studied with Western blot and luciferase bioluminescence assay, which presents some limitations. PURPOSE: In this work, we developed and optimized a high-throughput assay to study pSmad pathways using immunofluorescence (IF) as an alternative to Western blot. We aimed to overcome the technical challenges usually faced in the classical IF assay in image acquisition, analysis, and quantification. METHODS: We used C2C12 cells as a cellular model. The cells were stimulated with BMP-2 and TGF-ß1 that were delivered either in solution (soluble) or via a biomaterial presenting the growth factor (GF), that is in a "matrix-bound" manner. Image acquisition parameters, analysis methods, and quantification of pSmads using IF were optimized for cells cultured on two types of supports: on bare glass and on a biomimetic coating made by self-assembly of the biopolymers hyaluronic acid and poly(l-lysine), which was crosslinked and then loaded with the GFs. RESULTS: We performed high-content kinetic studies of pSmad expression for cells cultured in 96-well microplates in response to soluble and matrix-bound BMP-2 and TGF-ß1. The detection limit of the IF-based assay was found to be similar to Western blot. Additionally, we provide a proof-of-concept for drug testing using inhibitors of BMP and TGF-ß receptors, under conditions where specific signaling pathways are engaged via the ligand/receptor interactions. Altogether, our findings offer perspectives for future mechanistic studies on cell signaling and for studies at the single cell level using imaging methods.

BIOMERO: A scalable and extensible image analysis framework.

In the rapidly evolving field of bioimaging, the integration and orchestration of findable, accessible, interoperable, and reusable (FAIR) image analysis workflows remains a challenge. We introduce BIOMERO (bioimage analysis in OMERO), a bridge connecting OMERO, a renowned bioimaging data management platform; FAIR workflows; and high-performance computing (HPC) environments. BIOMERO facilitates seamless execution of FAIR workflows, particularly for large datasets from high-content or high-throughput screening. BIOMERO empowers researchers by eliminating the need for specialized knowledge, enabling scalable image processing directly from OMERO. BIOMERO notably supports the sharing and utilization of FAIR workflows between OMERO, Cytomine/BIAFLOWS, and other bioimaging communities. BIOMERO will promote the widespread adoption of FAIR workflows, emphasizing reusability, across the realm of bioimaging research. Its user-friendly interface will empower users, including those without technical expertise, to seamlessly apply these workflows to their datasets, democratizing the utilization of AI by the broader research community.

Development of an automated 3D high content cell screening platform for organoid phenotyping.

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.

Automated Image-Based Fluorescence Screening of Mitochondrial Membrane Potential in Daphnia magna: An Advanced Ecotoxicological Testing Tool.

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.

Silencing of spindle apparatus coiled-coil protein 1 suppressed the progression of hepatocellular carcinoma through farnesyltransferase-beta and increased drug sensitivity.

Hepatocellular carcinoma (HCC) is the major cause of cancer-associated mortality worldwide. Despite great advances have been made on the treatment of HCC, the survival rate of patients remains poor. Spindle apparatus coiled-coil protein 1 (SPDL1) is involved in the development of various cancers in humans. However, the role of SPDL1 in HCC remains unclear. In this study, we found high expression of SPDL1 in HCC tissues as compared to normal samples. In vitro, silencing of SPDL1 induced HCC cell apoptosis, and suppressed HCC cell propagation and migration. In vivo, knockdown of SPDL1 inhibited the tumor growth of HCC cells. These findings indicated the tumor-promoting role of SPDL1 in HCC. Mechanistically, we identified farnesyltransferase-beta (FNTB) as the downstream target protein of SPDL1 based on immunoprecipitation and mass spectrometry, which were confirmed by western blotting. Rescue assay determined that FNTB played a tumor promoting role in SPDL1-trigger HCC cell growth. Overexpression of FNTB recovered HCC cell viability and migration in SPDL1 knockdown cells. We also found that silencing of SPDL1 increased the sensitivity of Huh7 cells to sorafenib and lenvatinib, suggesting that SPDL1 is a new therapeutic target in HCC. Collectivity, the present study identified a new axis SPDL1/FNTB involved in the progression of HCC. Hence, SPDL1/FNTB is a potential target for the treatment of HCC.

A fluorescent reporter for rapid assessment of autophagic flux reveals unique autophagy signatures during C. elegans post-embryonic development and identifies compounds that modulate autophagy.

Autophagy is important for many physiological processes; and disordered autophagy can contribute to the pathogenesis of a broad range of systemic disorders. C. elegans is a useful model organism for studying the genetics of autophagy, however, current methods for studying autophagy are labor-intensive and not readily amenable to high-throughput procedures. Here we describe a fluorescent reporter, GFP::LGG-1::mKate2, which is useful for monitoring autophagic flux in live animals. In the intestine, the fusion protein is processed by endogenous ATG-4 to generate GFP::LGG-1 and mKate2 proteins. We provide data indicating that the GFP:mKate ratio is a suitable readout for measuring cellular autophagic flux. Using this reporter, we measured autophagic flux in L1 larvae to day 7 adult animals. We show that basal autophagic flux is relatively low during larval development but increases markedly in reproductive adults before decreasing with age. Furthermore, we show that wild-type, eat-2, and daf-2 mutant animals have distinct autophagic flux profiles through post-embryonic development. Finally, we demonstrate the utility of this reporter by performing a high-content small molecule screen to identify compounds that alter autophagic flux in C. elegans.

[Phenotypic drug discovery promotes research and development of innovative drugs based on traditional Chinese medicine].

Traditional Chinese medicine with rich resources in China and definite therapeutic effects on complex diseases demonstrates great development potential. However, the complex composition, the unclear pharmacodynamic substances and mechanisms of action, and the lack of reasonable methods for evaluating clinical safety and efficacy have limited the research and development of innovative drugs based on traditional Chinese medicine. The progress in cutting-edge disciplines such as artificial intelligence and biomimetics, especially the emergence of cell painting and organ-on-a-chip, helps to identify and characterize the active ingredients in traditional Chinese medicine based on the changes in model characteristics, thus providing more accurate guidance for the development and application of traditional Chinese medicine. The application of phenotypic drug discovery in the research and development of innovative drugs based on traditional Chinese medicine is gaining increasing attention. In recent years, the technology for phenotypic drug discovery keeps advancing, which improves the early discovery rate of new drugs and the success rate of drug research and development. Accordingly, phenotypic drug discovery gradually becomes a key tool for the research on new drugs. This paper discusses the enormous potential of traditional Chinese medicine in the discovery and development of innovative drugs and illustrates how the application of phenotypic drug discovery, supported by cutting-edge technologies such as cell painting, deep learning, and organ-on-a-chip, propels traditional Chinese medicine into a new stage of development.

A bypass flow model to study endothelial cell mechanotransduction across diverse flow environments.

Disturbed flow is one of the pathological initiators of endothelial dysfunction in intimal hyperplasia (IH) which is commonly seen in vascular bypass grafts, and arteriovenous fistulas. Various in vitro disease models have been designed to simulate the hemodynamic conditions found in the vasculature. Nonetheless, prior investigations have encountered challenges in establishing a robust disturbed flow model, primarily attributed to the complex bifurcated geometries and distinctive flow dynamics. In the present study, we aim to address this gap by introducing an in vitro bypass flow model capable of inducing disturbed flow and other hemodynamics patterns through a pulsatile flow in the same model. To assess the model's validity, we employed computational fluid dynamics (CFD) to simulate hemodynamics and compared the morphology and functions of human umbilical venous endothelial cells (HUVECs) under disturbed flow conditions to those in physiological flow or stagnant conditions. CFD analysis revealed the generation of disturbed flow within the model, pinpointing the specific location in the channel where the effects of disturbed flow were observed. High-content screening, a single-cell morphological profile assessment, demonstrated that HUVECs in the disturbed flow area exhibited random orientation, and morphological features were significantly distinct compared to cells in the physiological flow or stagnant condition after a two days of flow exposure. Furthermore, HUVECs exposed to disturbed flow underwent extensive remodeling of the adherens junctions and expressed higher levels of endothelial cell activation markers compared to other hemodynamic conditions. In conclusion, our in vitro bypass flow model provides a robust platform for investigating the associations between disturbed flow pattern and vascular diseases.

Identification of chemical composition in Gnetum montanum extract and plasma components after oral administration in cynomolgus monkey by UPLC-Q-TOF-MS and its anti-tumor active components analysis.

Gnetum montanum Markgr. (Gnetaceae) is a commonly used traditional herbal medicine among the Yao ethnic group, with potential effects in preventing and treating tumors. However, the substance basis of its anti-tumor properties remains unclear. This study utilized ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) to identify the chemical components of G. montanum extract (GME) and its absorbed prototypes in cynomolgus monkey plasma after oral administration. A total of 57 compounds were detected in the GME, with 14 compounds in positive ion mode and 43 compounds in negative ion mode. In the cynomolgus monkey plasma, 17 compounds were identified, with 3 compounds in positive ion mode and 14 compounds in negative ion mode. Subsequently, we utilized high content screening technology to investigate the anti-tumor effects of GME on colon cancer, lung cancer, breast cancer, gastric cancer, liver cancer, and esophageal cancer. We found that the GME exhibited significant proliferation inhibition on colon cancer cells SW480, with an IC50 value of 50.77 µg/mL. Further research using component separation and pharmacological tracking revealed that the F2 component of the GME demonstrated notable anti-tumor effects. Through UPLC-MS identification, the chemical components in the F2 fraction were identified as pinoresinol diglucoside, (+)-pinoresinol-4-O-beta-D-glucopyranoside, ursolic acid, and gnetol. In conclusion, this study contributes to elucidating the anti-tumor pharmacological basis of GME and provides robust support for future drug design and development.

A Decade in a Systematic Review: The Evolution and Impact of Cell Painting.

High-content image-based assays have fueled significant discoveries in the life sciences in the past decade (2013-2023), including novel insights into disease etiology, mechanism of action, new therapeutics, and toxicology predictions. Here, we systematically review the substantial methodological advancements and applications of Cell Painting. Advancements include improvements in the Cell Painting protocol, assay adaptations for different types of perturbations and applications, and improved methodologies for feature extraction, quality control, and batch effect correction. Moreover, machine learning methods recently surpassed classical approaches in their ability to extract biologically useful information from Cell Painting images. Cell Painting data have been used alone or in combination with other -omics data to decipher the mechanism of action of a compound, its toxicity profile, and many other biological effects. Overall, key methodological advances have expanded Cell Painting's ability to capture cellular responses to various perturbations. Future advances will likely lie in advancing computational and experimental techniques, developing new publicly available datasets, and integrating them with other high-content data types.

A Decade in a Systematic Review: The Evolution and Impact of Cell Painting.

High-content image-based assays have fueled significant discoveries in the life sciences in the past decade (2013-2023), including novel insights into disease etiology, mechanism of action, new therapeutics, and toxicology predictions. Here, we systematically review the substantial methodological advancements and applications of Cell Painting. Advancements include improvements in the Cell Painting protocol, assay adaptations for different types of perturbations and applications, and improved methodologies for feature extraction, quality control, and batch effect correction. Moreover, machine learning methods recently surpassed classical approaches in their ability to extract biologically useful information from Cell Painting images. Cell Painting data have been used alone or in combination with other - omics data to decipher the mechanism of action of a compound, its toxicity profile, and many other biological effects. Overall, key methodological advances have expanded Cell Painting's ability to capture cellular responses to various perturbations. Future advances will likely lie in advancing computational and experimental techniques, developing new publicly available datasets, and integrating them with other high-content data types.

Decoding phenotypic screening: A comparative analysis of image representations.

Biomedical imaging techniques such as high content screening (HCS) are valuable for drug discovery, but high costs limit their use to pharmaceutical companies. To address this issue, The JUMP-CP consortium released a massive open image dataset of chemical and genetic perturbations, providing a valuable resource for deep learning research. In this work, we aim to utilize the JUMP-CP dataset to develop a universal representation model for HCS data, mainly data generated using U2OS cells and CellPainting protocol, using supervised and self-supervised learning approaches. We propose an evaluation protocol that assesses their performance on mode of action and property prediction tasks using a popular phenotypic screening dataset. Results show that the self-supervised approach that uses data from multiple consortium partners provides representation that is more robust to batch effects whilst simultaneously achieving performance on par with standard approaches. Together with other conclusions, it provides recommendations on the training strategy of a representation model for HCS images.

High-Throughput Methods for the Discovery of Small Molecule Modulators of Pancreatic Beta-Cell Function and Regeneration.

The progression of type II diabetes (T2D) is characterized by a complex and highly variable loss of beta-cell mass, resulting in impaired insulin secretion. Many T2D drug discovery efforts aimed at discovering molecules that can protect or restore beta-cell mass and function have been developed using limited beta-cell lines and primary rodent/human pancreatic islets. Various high-throughput screening methods have been used in the context of drug discovery, including luciferase-based reporter assays, glucose-stimulated insulin secretion, and high-content screening. In this context, a cornerstone of small molecule discovery has been the use of immortalized rodent beta-cell lines. Although insightful, this usage has led to a more comprehensive understanding of rodent beta-cell proliferation pathways rather than their human counterparts. Advantages gained in enhanced physiological relevance are offered by three-dimensional (3D) primary islets and pseudoislets in contrast to monolayer cultures, but these approaches have been limited to use in low-throughput experiments. Emerging methods, such as high-throughput 3D islet imaging coupled with machine learning, aim to increase the feasibility of integrating 3D microtissue structures into high-throughput screening. This review explores the current methods used in high-throughput screening for small molecule modulators of beta-cell mass and function, a potentially pivotal strategy for diabetes drug discovery.

Identification of fangchinoline as a broad-spectrum enterovirus inhibitor through reporter virus based high-content screening.

Hand, foot, and mouth disease (HFMD) is a common pediatric illness mainly caused by enteroviruses, which are important human pathogens. Currently, there are no available antiviral agents for the therapy of enterovirus infection. In this study, an excellent high-content antiviral screening system utilizing the EV-A71-eGFP reporter virus was developed. Using this screening system, we screened a drug library containing 1042 natural compounds to identify potential EV-A71 inhibitors. Fangchinoline (FAN), a bis-benzylisoquinoline alkaloid, exhibits potential inhibitory effects against various enteroviruses that cause HFMD, such as EV-A71, CV-A10, CV-B3 and CV-A16. Further investigations revealed that FAN targets the early stage of the enterovirus life cycle. Through the selection of FAN-resistant EV-A71 viruses, we demonstrated that the VP1 protein could be a potential target of FAN, as two mutations in VP1 (E145G and V258I) resulted in viral resistance to FAN. Our research suggests that FAN is an efficient inhibitor of EV-A71 and has the potential to be a broad-spectrum antiviral drug against human enteroviruses.

Uncovering the toxicity mechanisms of a series of carboxylic acids in liver cells through computational and experimental approaches.

Hepatotoxicity poses a significant concern in drug design due to the potential liver damage that can be caused by new drugs. Among common manifestations of hepatotoxic damage is lipid accumulation in hepatic tissue, resulting in liver steatosis or phospholipidosis. Carboxylic derivatives are prone to interfere with fatty acid metabolism and cause lipid accumulation in hepatocytes. This study investigates the toxic behaviour of 24 structurally related carboxylic acids in hepatocytes, specifically their ability to cause accumulation of fatty acids and phospholipids. Using high-content screening (HCS) assays, we identified two distinct lipid accumulation patterns. Subsequently, we developed structure-activity relationship (SAR) and quantitative structure-activity relationship (QSAR) models to determine relevant molecular substructures and descriptors contributing to these adverse effects. Additionally, we calculated physicochemical properties associated with lipid accumulation in hepatocytes and examined their correlation with our chemical structure characteristics. To assess the applicability of our findings to a wide range of chemical compounds, we employed two external datasets to evaluate the distribution of our QSAR descriptors. Our study highlights the significance of subtle molecular structural variations in triggering hepatotoxicity, such as the presence of nitrogen or the specific arrangement of substitutions within the carbon chain. By employing our comprehensive approach, we pinpointed specific molecules and elucidated their mechanisms of toxicity, thus offering valuable insights to guide future toxicology investigations.

Combined use of multiparametric high-content-screening and in vitro circadian reporter assays in neurotoxicity evaluation.

Accumulating evidence indicates that chronic circadian rhythm disruption is associated with the development of neurodegenerative diseases induced by exposure to neurotoxic chemicals. Herein, we examined the relationship between cellular circadian rhythm disruption and cytotoxicity in neural cells. Moreover, we evaluated the potential application of an in vitro cellular circadian rhythm assay in determining circadian rhythm disruption as a sensitive and early marker of neurotoxicant-induced adverse effects. To explore these objectives, we established an in vitro cellular circadian rhythm assay using human glioblastoma (U87 MG) cells stably transfected with a circadian reporter vector (PER2-dLuc) and determined the lowest-observed-adverse-effect levels (LOAELs) of several common neurotoxicants. Additionally, we determined the LOAEL of each compound on multiple cytotoxicity endpoints (nuclear size [NC], mitochondrial membrane potential [MMP], calcium ions, or lipid peroxidation) using a multiparametric high-content screening (HCS) assay using transfected U87 MG cells treated with the same neurotoxicants for 24 and 72 h. Based on our findings, the LOAEL for cellular circadian rhythm disruption for most chemicals was slightly higher than that for most cytotoxicity indicators detected using HCS, and the LOAEL for MMP in the first 24 h was the closest to that for cellular circadian rhythm disruption. Dietary antioxidants (methylselenocysteine and N-acetyl-l-cysteine) prevented or restored neurotoxicant-induced cellular circadian rhythm disruption. Our results suggest that cellular circadian rhythm disruption is as sensitive as cytotoxicity indicators and occurs early as much as cytotoxic events during disease development. Moreover, the in vitro cellular circadian rhythm assay warrants further evaluation as an early screening tool for neurotoxicants.

Expanding TheCellVision.org: a central repository for visualizing and mining high-content cell imaging projects.

We previously constructed TheCellVision.org, a central repository for visualizing and mining data from yeast high-content imaging projects. At its inception, TheCellVision.org housed two high-content screening (HCS) projects providing genome-scale protein abundance and localization information for the budding yeast Saccharomyces cerevisiae, as well as a comprehensive analysis of the morphology of its endocytic compartments upon systematic genetic perturbation of each yeast gene. Here, we report on the expansion of TheCellVision.org by the addition of two new HCS projects and the incorporation of new global functionalities. Specifically, TheCellVision.org now hosts images from the Cell Cycle Omics project, which describes genome-scale cell cycle-resolved dynamics in protein localization, protein concentration, gene expression, and translational efficiency in budding yeast. Moreover, it hosts PIFiA, a computational tool for image-based predictions of protein functional annotations. Across all its projects, TheCellVision.org now houses >800,000 microscopy images along with computational tools for exploring both the images and their associated datasets. Together with the newly added global functionalities, which include the ability to query genes in any of the hosted projects using either yeast or human gene names, TheCellVision.org provides an expanding resource for single-cell eukaryotic biology.