Biology subjects

Wotring, J. W.

Publications and source records attributed to Wotring, J. W..

10 recordsLinked to original sources

bioRxiv2026

Exposure to p,p'-dichlorodiphenyldichloroethylene (p,p'-DDE) Perturbs Cell State and Stem Cell Markers and Induces an Epidermal Phenotype in Human Breast Cells

Breast cancer is the second leading cause of cancer deaths in U.S. women. Endocrine disruptors, such as the DDT metabolite DDE, are environmental factors linked to breast cancer risk. Emerging evidence shows that during carcinogenesis, cells reacquire stem cell traits and exhibit phenotypic plasticity. In these phenotypically plastic states, breast cells transition between phenotypes, for example, from epithelial to mesenchymal (EMT) phenotypes, or from luminal to basal. Discovering how environmental factors alter cell phenotype may be a critical step in preventing and treating breast cancer. We applied a novel high-content imaging method for the evaluation of expression of stemness and cell state markers (ALDH1A3, CD44, CD24, KRT8, and KRT14) and evaluated these markers after introducing environmentally relevant concentrations of DDE (25 nM to 25 M) to non-tumorigenic MCF10A breast epithelial cells grown in 3D anchorage independent conditions. After identifying surprisingly profound cell state alterations, including a loss of KRT8 and KRT14 expression, by 25 M DDE exposure, we used transcriptomic profiling along with pharmaceutical and genetic knockdown approaches to characterize the molecular mechanisms by which DDE exposure modulates breast epithelial cell state. Keratinization and formation of the cornified envelope were biological pathways upregulated with a maximum fold change of 360.47. We identify DLX3 as a transcription factor which is inducible by DDE exposure and is also highly upregulated in human breast cancers, reflecting a novel mechanism by which environmental exposures may promote cellular plasticity and breast carcinogenesis.

pharmacology and toxicology↗

bioRxiv2026

A High-Content Pseudotime Framework for Morphological Profiling of Dengue Virus Inhibitors from a Drug-Repurposing Library

Dengue virus (DENV) causes dengue fever, a globally prevalent, epidemic-prone disease with no FDA-approved antivirals. Additionally, the available vaccine for DENV can increase the risk of severe dengue fever for those who have never had a DENV infection due to antibody-dependent enhancement. Thus, there is an urgent need to identify DENV antivirals. Drug repurposing, high-content screening, and machine learning were leveraged to efficiently identify antivirals likely to inhibit DENV replication. Using high-content screening in a DENV infection model, we characterized the morphological patterns of NS4B and envelope (E) protein expression over time and developed a viral pseudotime model that predicts infection progression to aid in phenotypic interpretation of drug effects. We then developed a single cell infection classifier for antiviral efficacy and performed high-throughput drug screening of 960 compounds. We identified four concentration-dependent inhibitors of DENV with nanomolar-to-submicromolar potencies: esomeprazole, GW4064, pralatrexate, and LY411575. With our pseudotime machine learning model trained on data from the time-series assay, we scored the concentration-dependent inhibitors to map their mechanism of action onto time points in the viral life cycle. Our most notable results show that LY411575, a gamma secretase inhibitor, exhibited an IC of 72 nM and reduced percent infection to near the level of the mock infection control. Pseudotime inferences generated mechanistic predictions that were supported by time-of-addition experiments, indicating that LY411575 arrests DENV infection before the development of late-stage infection associated morphologies, while retaining activity when added after inoculation.

cell biology↗

bioRxiv2026

High-Throughput Morphological Profiling of Patient-Derived Human Liver Organoids for Hepatotoxicity Hazard Identification and Compound Prioritization

Drug-induced liver injury (DILI) remains a major challenge in drug development because existing in vitro models poorly predict clinical hepatotoxicity. We coupled patient-derived human liver organoids (HLOs) with high-content imaging and automated machine learning (ML) to detect hepatotoxicity-associated phenotypes by morphological profiling. HLOs from six DILI patients and one healthy donor (n = 7) retained donor-specific baseline phenotypes in hepatocyte maturity, metabolism, and morphology. ML models trained per line on MAD-robustized, well-level-aggregated median features achieved compound-level AUROCs of 0.88 (95% CI 0.86-0.90) to 0.91 (95% CI 0.89-0.93) and balanced accuracies of 0.81-0.84 in distinguishing 54 hepatotoxicants from 20 non-hepatotoxic controls. Averaging predictions across all seven lines at an optimized threshold gave 94.4% sensitivity (95% CI 84.6-98.8%) and 85.0% specificity (95% CI 62.1-96.8%), substantially outperforming HLO cytotoxicity assays and cancer cell line profiling. Lines were moderately-to-highly concordant (Pearson r = 0.66-0.85), and benchmark concentration modeling revealed reproducible inter-line differences in phenotypic sensitivity (median 4.0-fold, several compounds exceeding 20-fold). Exposure anchoring of benchmark concentrations to human-equivalent plasma concentrations, using in vitro mass-balance dosimetry and curated plasma free fractions, placed organoid points of departure within 100-fold of clinical Cmax for 60 of 66 compounds (23-fold residual offset, 95% CI 12-45), and placed two of the three misclassified negative controls an order of magnitude above clinical Cmax. Sulindac injury signatures were significantly enhanced by TNF co-treatment, demonstrating capacity to detect pro-inflammatory-mediated DILI. This platform preserves inter-line variability while enabling reproducible, scalable multi-line consensus hazard classification; because compounds were tested over a common nominal concentration range, the readout defines hepatocellular hazard, which must be combined with exposure as an independent input to estimate clinical DILI risk.

pharmacology and toxicology↗

bioRxiv2026

Identification and characterization of the functional LolB ortholog in Bacteroides

Bacteroidota are prolific members of the human gut microbiota, influencing overall health through the degradation of various polysaccharides. To aid in this process, these bacteria deploy cell surface lipoproteins, proteins anchored to the membrane by a lipidated N-terminal cysteine. Despite their importance, lipoprotein synthesis and transport in Bacteroidota is not well defined, particularly how lipoproteins reach the outer membrane and cell surface. In Escherichia coli, lipoproteins are inserted into the outer membrane by LolB, the final step of the Lol pathway for localizing lipoproteins, previously thought to be confined to {gamma}- and {beta}-proteobacteria. Herein, we report a structural ortholog of LolB in Bacteroides that rescues the lethal phenotype associated with LolB depletion in E. coli. We demonstrate this orthologs LolB-like activity through mutagenesis studies and a lipoprotein insertion activity assay. We find that the gene cannot be deleted from Bacteroides, but that depletion does not significantly impact growth on polysaccharides, nor the surface localization of lipoproteins involved in starch degradation. Nonetheless, depletion significantly alters the composition of many proteins in both the inner and outer membranes, while others remain unchanged. Altogether, our findings contribute to elucidating the lipoprotein transport pathway in Bacteroides and how it impacts cell physiology. ImportanceBacteroidota are abundant members of the human gut microbiota that influence health and disease. These bacteria deploy numerous cell surface lipoproteins that mediate their interactions with the host and play key roles in cell physiology. However, their mechanism(s) of lipoprotein transport is understudied. Here, we used a genetic screen to identify orthologs to E. coli LolB, the protein responsible for lipoprotein insertion into the outer membrane. Our screen revealed a structural ortholog to LolB in Bacteroides that performs this function. We show that when LolB is depleted, lipoproteins still reach the cell surface, even though the overall protein composition of the membrane is significantly altered. Our results broaden the understanding of both lipoprotein transport and Bacteroidota physiology.

microbiology↗

bioRxiv2025

Phenotypic Screening Coupled with AI-Driven Target Deconvolution Identifies α-Terthienyl as a Dual DPP-IV/HSD17β13 Modulator with Efficacy in a Mouse Model of MASLD

BackgroundMetabolic dysfunction-associated steatotic liver disease (MASLD) is a highly prevalent condition characterized by fat build-up in the liver and ranges from benign steatosis to progression to metabolic dysfunction-associated steatohepatitis (MASH), fibrosis, cirrhosis and end-stage liver disease including hepatocellular carcinoma, representing a significant cause of chronic liver disease globally.1,2 Current treatment options are limited, primarily relying on lifestyle modifications, highlighting an urgent need for novel therapeutic strategies. MethodsA Cell Painting-style high-content screening phenotypic assay was employed using the PH5CH8 human hepatocyte cell line to identify small molecules capable of modulating induced hepatic steatosis. The Plex Research artificial intelligence (AI) platform was utilized for target deconvolution of the lead hit compound, -terthienyl. In vivo efficacy was assessed in a diet-induced obesity (DIO) C57BL/6J mouse model of MASLD. Biochemical assays and molecular docking simulations were performed to validate predicted target interactions. ResultsPhenotypic screening identified 15 chemical probes/drugs that elicit dose-responsive inhibition of steatosis, and 16 that exacerbate steatosis, which could contribute to worsening of the disease clinically. -terthienyl, a plant-derived natural product, was identified as a potent and non-toxic inhibitor of steatosis in PH5CH8 cells with an EC50 of 106 nM. In vivo, -terthienyl administration to diet-induced obesity (60% fat diet) mice significantly reduced hepatic steatosis histologically, improved glucose tolerance, and favorably modulated serum biomarkers including ALT and AST. AI-driven analysis predicted dipeptidyl peptidase 4 (DPP-IV) and 17-beta hydroxysteroid dehydrogenase 13 (HSD17{beta}13) as potential molecular targets of -terthienyl. Biochemical inhibition of DPP-IV was observed and an oxidized -terthienyl analog inhibited HSD17{beta}13. Molecular docking supported these predictions, indicating binding to DPP-IV and HSD17{beta}13. ConclusionThis study demonstrates the successful application of phenotypic screening integrated with AI-driven target deconvolution to identify compounds and drugs that ameliorate or exacerbate hepatic steatosis. -terthienyl was identified as a novel modulator of hepatic steatosis with in vivo efficacy in a MASLD model. Our findings suggest a dual-target mechanism involving DPP-IV and HSD17{beta}13, potentially engaged by the parent compound and its metabolite, respectively, offering a promising polypharmacological approach for MASLD treatment.

pharmacology and toxicology↗

bioRxiv2023

Imaging-based screening identifies modulators of the eIF3 translation initiation factor complex in Candida albicans

Fungal pathogens like Candida albicans can cause devastating human disease. Treatment of candidemia is complicated by the high rate of resistance to common antifungal therapies. Additionally, there is host toxicity associated with many antifungal compounds due to the conservation between essential mammalian and fungal proteins. An attractive new approach for antimicrobial development is to target virulence factors: non-essential processes that are required for the organism to cause disease in human hosts. This approach expands the potential target space while reducing the selective pressure towards resistance, as these targets are not essential for viability. In C. albicans, a key virulence factor is the ability to transition to hyphal morphology. We developed a high-throughput image analysis pipeline to distinguish between yeast and filamentous growth in C. albicans at the single cell level. Based on this phenotypic assay, we screened the FDA drug repurposing library of 2,017 compounds for their ability to inhibit filamentation and identified 33 compounds that block the hyphal transition in C. albicans with IC50 values ranging from 0.2 to 150 {micro}M. Multiple compounds showed a phenyl vinyl sulfone chemotype, prompting further analysis. Of these phenyl vinyl sulfones, NSC 697923 displayed the most efficacy, and by selecting for resistant mutants, we identified eIF3 as the target of NSC 697923 in C. albicans.

microbiology↗

bioRxiv2023

High-Content Screening to Identify Inhibitors of Dengue Virus Replication

Dengue Virus (DENV) causes dengue fever, a pandemic-potential disease with currently no FDA-approved antivirals. Additionally, the available vaccine for DENV can increase the risk of severe dengue fever for those who have never had a DENV infection due to antibody-dependent enhancements. Thus, there is an urgent need to identify dengue virus antivirals. Antivirals that target NS4B, the replication compartment forming protein of DENV and the flavivirus family, are a promising new drug class that minimize cytotoxic effects to host cells. Drug-repurposing and high-content screening were leveraged to efficiently identify antivirals likely to inhibit NS4B. Using high-content screening, we quantified the morphological patterns of NS4B and envelope (E) protein expression versus time and developed a viral pseudotime model that was able to predict the infection progression to enable drug screening. We then developed a single cell infection classifier for antiviral efficacy and performed high-throughput drug screening of 960 compounds. We identified four concentration-dependent inhibitors of DENV with nanomolar potencies including: Nexium, Pralatrexate, GW4064, and LY411575. LY411575, a gamma secretase inhibitor, exhibited an IC50 of 72nM and reduced percent infection to levels indistinguishable from the mock infection control.

cell biology↗

bioRxiv2022

In Vitro Evaluation and Mitigation of Niclosamide Liabilities as a COVID-19 Treatment.

Niclosamide, an FDA-approved oral anthelmintic drug, has broad biological activity including anticancer, antibacterial, and antiviral properties. Niclosamide has also been identified as a potent inhibitor of SARS-CoV-2 infection in vitro, generating interest in its use for the treatment or prevention of COVID-19. Unfortunately, there are several potential issues with using niclosamide for COVID-19, including low bioavailability, significant polypharmacology, high cellular toxicity, and unknown efficacy against emerging SARS-CoV-2 variants of concern. In this study, we used high-content imaging-based immunofluorescence assays in two different cell models to assess these limitations and evaluate the potential for using niclosamide as a COVID-19 antiviral. We show that despite promising preliminary reports, the antiviral efficacy of niclosamide overlaps with its cytotoxicity giving it a poor in vitro selectivity index for anti-SARS-CoV-2 inhibition. We also show that niclosamide has significantly variable potency against the different SARS-CoV-2 variants of concern and is most potent against variants with enhanced cell-to-cell spread including B.1.1.7. Finally, we report the activity of 33 niclosamide analogs, several of which have reduced cytotoxicity and increased potency relative to niclosamide. A preliminary structure-activity relationship analysis reveals dependence on a protonophore for antiviral efficacy, which implicates nonspecific endolysosomal neutralization as a dominant mechanism of action. Further single-cell morphological profiling suggests niclosamide also inhibits viral entry and cell-to-cell spread by syncytia. Altogether, our results suggest that niclosamide is not an ideal candidate for the treatment of COVID-19, but that there is potential for developing improved analogs with higher clinical translational potential in the future. ImportanceThere is still an urgent need for effective anti-SARS-CoV-2 therapeutics due to waning vaccine efficacy, the emergence of variants of concern, and limited efficacy of existing antivirals. One potential therapeutic option is niclosamide, an FDA approved anthelmintic compound that has shown promising anti-SARS-CoV-2 activity in cell-based assays. Unfortunately, there are significant barriers for the clinical utility of niclosamide as a COVID-19 therapeutic. Our work emphasizes these limitations by showing that niclosamide has high cytotoxicity at antiviral concentrations, variable potency against variants of concern, and significant polypharmacology as a result of its activity as a nonspecific protonophore. Some of these clinical limitations can be mitigated, however, through structural modifications to the niclosamide scaffold, which we demonstrate through a preliminary structure activity relationship analysis. Overall, we show that niclosamide is not a suitable candidate for the treatment of COVID-19, but that structural analogs with improved drug properties may have higher clinical-translational potential.

microbiology↗

bioRxiv2022

ARF6 is an important host factor for SARS-CoV-2 infection in vitro

SARS-CoV-2 is a newly emerged beta-coronavirus that enter cells via two routes, direct fusion at the plasma membrane or endocytosis followed by fusion with the late endosome/lysosome. While the viral receptor, ACE2, multiple entry factors, and the mechanism of fusion of the virus at the plasma membrane have been extensively investigated, viral entry via the endocytic pathway is less understood. By using a human hepatocarcinoma cell line, Huh-7, which is resistant to the antiviral action of the TMPRSS2 inhibitor camostat, we discovered that SARS-CoV-2 entry is not dependent on dynamin but dependent on cholesterol. ADP-ribosylation factor 6 (ARF6) has been described as a host factor for SARS-CoV-2 replication and it is involved in the entry and infection of several pathogenic viruses. Using CRISPR-Cas9 genetic deletion, we observed that ARF6 is important for SARS-CoV-2 uptake and infection in Huh-7. This finding was corroborated using a pharmacologic inhibitor, whereby the ARF6 inhibitor NAV-2729 showed a dose-dependent inhibition of viral infection. Importantly, NAV-2729 reduced SARS-CoV-2 viral loads also in more physiologic models of infection: Calu-3 and kidney organoids. This highlighted the importance of ARF6 in multiple cell contexts. Together, these experiments points to ARF6 as a putative target to develop antiviral strategies against SARS-CoV-2.

microbiology↗

bioRxiv2020

Morphological Cell Profiling of SARS-CoV-2 Infection Identifies Drug Repurposing Candidates for COVID-19

The global spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and the associated disease COVID-19, requires therapeutic interventions that can be rapidly identified and translated to clinical care. Traditional drug discovery methods have a >90% failure rate and can take 10-15 years from target identification to clinical use. In contrast, drug repurposing can significantly accelerate translation. We developed a quantitative high-throughput screen to identify efficacious agents against SARS-CoV-2. From a library of 1,425 FDA-approved compounds and clinical candidates, we identified 17 dose-responsive compounds with in vitro antiviral efficacy in human liver Huh7 cells and confirmed antiviral efficacy in human colon carcinoma Caco-2, human prostate adenocarcinoma LNCaP, and in a physiologic relevant model of alveolar epithelial type 2 cells (iAEC2s). Additionally, we found that inhibitors of the Ras/Raf/MEK/ERK signaling pathway exacerbate SARS-CoV-2 infection in vitro. Notably, we discovered that lactoferrin, a glycoprotein classically found in secretory fluids, including mammalian milk, inhibits SARS-CoV-2 infection in the nanomolar range in all cell models with multiple modes of action, including blockage of virus attachment to cellular heparan sulfate and enhancement of interferon responses. Given its safety profile, lactoferrin is a readily translatable therapeutic option for the management of COVID-19. IMPORTANCESince its emergence in China in December 2019, SARS-CoV-2 has caused a global pandemic. Repurposing of FDA-approved drugs is a promising strategy for identifying rapidly deployable treatments for COVID-19. Herein, we developed a pipeline for quantitative high-throughput image-based screening of SARS-CoV-2 infection in human cells that led to the identification of several FDA-approved drugs and clinical candidates with in vitro antiviral activity.

cell biology↗