Farnesoid X receptor activation by bile acids suppresses lipid peroxidation and ferroptosis.

Ferroptosis is a regulated cell death modality that occurs upon iron-dependent lipid peroxidation. Recent research has identified many regulators that induce or inhibit ferroptosis; yet, many regulatory processes and networks remain to be elucidated. In this study, we performed a chemical genetics screen using small molecules with known mode of action and identified two agonists of the nuclear receptor Farnesoid X Receptor (FXR) that suppress ferroptosis, but not apoptosis or necroptosis. We demonstrate that in liver cells with high FXR levels, knockout or inhibition of FXR sensitized cells to ferroptotic cell death, whereas activation of FXR by bile acids inhibited ferroptosis. Furthermore, FXR inhibited ferroptosis in ex vivo mouse hepatocytes and human hepatocytes differentiated from induced pluripotent stem cells. Activation of FXR significantly reduced lipid peroxidation by upregulating the ferroptosis gatekeepers GPX4, FSP1, PPARα, SCD1, and ACSL3. Together, we report that FXR coordinates the expression of ferroptosis-inhibitory regulators to reduce lipid peroxidation, thereby acting as a guardian of ferroptosis.

The therapeutic potential of targeting regulated non-apoptotic cell death.

Cell death is critical for the development and homeostasis of almost all multicellular organisms. Moreover, its dysregulation leads to diverse disease states. Historically, apoptosis was thought to be the major regulated cell death pathway, whereas necrosis was considered to be an unregulated form of cell death. However, research in recent decades has uncovered several forms of regulated necrosis that are implicated in degenerative diseases, inflammatory conditions and cancer. The growing insight into these regulated, non-apoptotic cell death pathways has opened new avenues for therapeutic targeting. Here, we describe the regulatory pathways of necroptosis, pyroptosis, parthanatos, ferroptosis, cuproptosis, lysozincrosis and disulfidptosis. We discuss small-molecule inhibitors of the pathways and prospects for future drug discovery. Together, the complex mechanisms governing these pathways offer strategies to develop therapeutics that control non-apoptotic cell death.

CellDeathPred: a deep learning framework for ferroptosis and apoptosis prediction based on cell painting.

Cell death, such as apoptosis and ferroptosis, play essential roles in the process of development, homeostasis, and pathogenesis of acute and chronic diseases. The increasing number of studies investigating cell death types in various diseases, particularly cancer and degenerative diseases, has raised hopes for their modulation in disease therapies. However, identifying the presence of a particular cell death type is not an obvious task, as it requires computationally intensive work and costly experimental assays. To address this challenge, we present CellDeathPred, a novel deep-learning framework that uses high-content imaging based on cell painting to distinguish cells undergoing ferroptosis or apoptosis from healthy cells. In particular, we incorporate a deep neural network that effectively embeds microscopic images into a representative and discriminative latent space, classifies the learned embedding into cell death modalities, and optimizes the whole learning using the supervised contrastive loss function. We assessed the efficacy of the proposed framework using cell painting microscopy data sets from human HT-1080 cells, where multiple inducers of ferroptosis and apoptosis were used to trigger cell death. Our model confidently separates ferroptotic and apoptotic cells from healthy controls, with an average accuracy of 95% on non-confocal data sets, supporting the capacity of the CellDeathPred framework for cell death discovery.

ABCA3 Deficiency-Variant-Specific Response to Hydroxychloroquine.

Biallelic variants in ABCA3, the gene encoding the lipid transporter ATP-binding cassette subfamily A member 3 (ABCA3) that is predominantly expressed in alveolar type II cells, may cause interstitial lung diseases in children (chILD) and adults. Currently, there is no proven therapy, but, frequently, hydroxychloroquine (HCQ) is used empirically. We hypothesized that the in vitro responsiveness to HCQ might correlate to patients' clinical outcomes from receiving HCQ therapy. The clinical data of the subjects with chILD due to ABCA3 deficiency and treated with HCQ were retrieved from the literature and the Kids Lung Register data base. The in vitro experiments were conducted on wild type (WT) and 16 mutant ABCA3-HA-transfected A549 cells. The responses of the functional read out were assessed as the extent of deviation from the untreated WT. With HCQ treatment, 19 patients had improved or unchanged respiratory conditions, and 20 had respiratory deteriorations, 5 of whom transiently improved then deteriorated. The in vitro ABCA3 functional assays identified two variants with complete response, five with partial response, and nine with no response to HCQ. The variant-specific HCQ effects in vivo closely correlated to the in vitro data. An ABCA3+ vesicle volume above 60% of the WT volume was linked to responsiveness to HCQ; the HCQ treatment response was concentration dependent and differed for variants in vitro. We generated evidence for an ABCA3 variant-dependent impact of the HCQ in vitro. This may also apply for HCQ treatment in vivo, as supported by the retrospective and uncontrolled data from the treatment of chILD due to ABCA3 deficiency.

Unleashing high content screening in hit detection - Benchmarking AI workflows including novelty detection.

Complex mixtures containing natural products are still an interesting source of novel drug candidates. High content screening (HCS) is a popular tool to screen for such. In particular, multiplexed HCS assays promise comprehensive bioactivity profiles, but generate also high amounts of data. Yet, only some machine learning (ML) applications for data analysis are available and these usually require a profound knowledge of the underlying cell biology. Unfortunately, there are no applications that simply predict if samples are biologically active or not (any kind of bioactivity). Within this work, we benchmark ML algorithms for binary classification, starting with classical ML models, which are the standard classifiers of the scikit-learn library or ensemble models of these classifiers (a total of 92 models tested). Followed by a partial least square regression (PLSR)-based classification (44 tested models in total) and simple artificial neural networks (ANNs) with dense layers (72 tested models in total). In addition, a novelty detection (ND) was examined, which is supposed to handle unknown patterns. For the final analysis the models, with and without upstream ND, were tested with two independent data sets. In our analysis, a stacking model, an ensamble model of class ML algorithms, performed best to predict new and unknown data. ND improved the predictions of the models and was useful to handle unknown patterns. Importantly, the classifier presented here can be easily rebuilt and be adapted to the data and demands of other groups. The hit detector (ND + stacking model) is universal and suitable for a broader application to support the search for new drug candidates.

Structure-based design, synthesis and evaluation of a novel family of PEX5-PEX14 interaction inhibitors against Trypanosoma.

Trypanosomiases are neglected tropical diseases caused by Trypanosoma (sub)species. Available treatments are limited and have considerable adverse effects and questionable efficacy in the chronic stage of the disease, urgently calling for the identification of new targets and drug candidates. Recently, we have shown that impairment of glycosomal protein import by the inhibition of the PEX5-PEX14 protein-protein interaction (PPI) is lethal to Trypanosoma. Here, we report the development of a novel dibenzo[b,f][1,4]oxazepin-11(10H)-one scaffold for small molecule inhibitors of PEX5-PEX14 PPI. The initial hit was identified by a high throughput screening (HTS) of a library of compounds. A bioisosteric replacement approach allowed to replace the metabolically unstable sulphur atom from the initial dibenzo[b,f][1,4]thiazepin-11(10H)-one HTS hit with oxygen. A crystal structure of the hit compound bound to PEX14 surface facilitated the rational design of the compound series accessible by a straightforward chemistry for the initial structure-activity relationship (SAR) analysis. This guided the design of compounds with trypanocidal activity in cell-based assays providing a promising starting point for the development of new drug candidates to tackle trypanosomiases.

Small molecule mediated inhibition of protein cargo recognition by peroxisomal transport receptor PEX5 is toxic to Trypanosoma.

Trypanosomiases are life-threatening infections of humans and livestock, and novel effective therapeutic approaches are needed. Trypanosoma compartmentalize glycolysis into specialized organelles termed glycosomes. Most of the trypanosomal glycolytic enzymes harbor a peroxisomal targeting signal-1 (PTS1) which is recognized by the soluble receptor PEX5 to facilitate docking and translocation of the cargo into the glycosomal lumen. Given its pivotal role in the glycosomal protein import, the PEX5-PTS1 interaction represents a potential target to inhibit import of glycolytic enzymes and thus kill the parasite. We developed a fluorescence polarization (FP)-based assay for monitoring the PEX5-PTS1 interaction and performed a High Throughput Screening (HTS) campaign to identify small molecule inhibitors of the interaction. Six of the identified hits passed orthogonal selection criteria and were found to inhibit parasite growth in cell culture. Our results validate PEX5 as a target for small molecule inhibitors and provide scaffolds suitable for further pre-clinical development of novel trypanocidal compounds.

Methods to Detect Small Molecule Inhibition of RING E3 Ligase Activity.

Protein ubiquitination is an essential post-translational modification that regulates a large number of cellular processes. This reaction is facilitated by the consecutive action of three central enzymes, i.e., E1 activating enzyme, E2 conjugating enzyme, and the E3 ligase. More than 600 E3 enzymes guarantee the specificity and selectivity of these reactions and thus represent an exciting, while highly underrepresented, class of drug targets. Specific methods can be employed to monitor their activity and thus query compound libraries for inhibitory small molecules. Here, we describe two protocols-one high-throughput and one low-throughput method-to detect E3 ligase activity and test small molecule modulation. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: AlphaScreen assay to measure TRAF6-Ubc13 interaction Basic Protocol 2: Gel-based in vitro ubiquitination assay (K63-linked chains).

Machine Learning Classifies Ferroptosis and Apoptosis Cell Death Modalities with TfR1 Immunostaining.

Determining cell death mechanisms occurring in patient and animal tissues is a longstanding goal that requires suitable biomarkers and accurate quantification. However, effective methods remain elusive. To develop more powerful and unbiased analytic frameworks, we developed a machine learning approach for automated cell death classification. Image sets were collected of HT-1080 fibrosarcoma cells undergoing ferroptosis or apoptosis and stained with an anti-transferrin receptor 1 (TfR1) antibody, together with nuclear and F-actin staining. Features were extracted using high-content-analysis software, and a classifier was constructed by fitting a multinomial logistic lasso regression model to the data. The prediction accuracy of the classifier within three classes (control, ferroptosis, apoptosis) was 93%. Thus, TfR1 staining, combined with nuclear and F-actin staining, can reliably detect both apoptotic and ferroptotis cells when cell features are analyzed in an unbiased manner using machine learning, providing a method for unbiased analysis of modes of cell death.

Acriflavine, a clinically approved drug, inhibits SARS-CoV-2 and other betacoronaviruses.

The COVID-19 pandemic caused by SARS-CoV-2 has been socially and economically devastating. Despite an unprecedented research effort and available vaccines, effective therapeutics are still missing to limit severe disease and mortality. Using high-throughput screening, we identify acriflavine (ACF) as a potent papain-like protease (PLpro) inhibitor. NMR titrations and a co-crystal structure confirm that acriflavine blocks the PLpro catalytic pocket in an unexpected binding mode. We show that the drug inhibits viral replication at nanomolar concentration in cellular models, in vivo in mice and ex vivo in human airway epithelia, with broad range activity against SARS-CoV-2 and other betacoronaviruses. Considering that acriflavine is an inexpensive drug approved in some countries, it may be immediately tested in clinical trials and play an important role during the current pandemic and future outbreaks.

High-Content Screening Identifies Cyclosporin A as a Novel ABCA3-Specific Molecular Corrector.

ABCA3 (ATP-binding cassette subfamily A member 3) is a lipid transporter expressed in alveolar type II cells and localized in the limiting membrane of lamellar bodies. It is crucial for pulmonary surfactant storage and homeostasis. Mutations in the ABCA3 gene are the most common genetic cause of respiratory distress syndrome in mature newborns and of interstitial lung disease in children. Apart from lung transplant, there is no cure available. To address the lack of causal therapeutic options for ABCA3 deficiency, a rapid and reliable approach is needed to investigate variant-specific molecular mechanisms and to identify pharmacologic modulators for monotherapies or combination therapies. To this end, we developed a phenotypic cell-based assay to autonomously identify ABCA3 wild-type-like or mutant-like cells by using machine learning algorithms aimed at identifying morphologic differences in wild-type and mutant cells. The assay was subsequently used to identify new drug candidates for ABCA3-specific molecular correction by using high-content screening of 1,280 Food and Drug Administration-approved small molecules. Cyclosporin A was identified as a potent corrector, specific for some but not all ABCA3 variants. Results were validated by using our previously established functional small-format assays. Hence, cyclosporin A may be selected for orphan drug evaluation in controlled repurposing trials in patients.

Highly Accurate Filters to Flag Frequent Hitters in AlphaScreen Assays by Suggesting their Mechanism.

AlphaScreen is one of the most widely used assay technologies in drug discovery due to its versatility, dynamic range and sensitivity. However, a presence of false positives and frequent hitters contributes to difficulties with an interpretation of measured HTS data. Although filters do exist to identify frequent hitters for AlphaScreen, they are frequently based on privileged scaffolds. The development of such filters is time consuming and requires deep domain knowledge. Recently, machine learning and artificial intelligence methods are emerging as important tools to advance drug discovery and chemoinformatics, including their application to identification of frequent hitters in screening assays. However, the relative performance and complementarity of the Machine Learning and scaffold-based techniques has not yet been comprehensively compared. In this study, we analysed filters based on the privileged scaffolds with filters built using machine learning. Our results demonstrate that machine-learning methods provide more accurate filters for identification of frequent hitters in AlphaScreen assays than scaffold-based methods and can be easily redeveloped once new data are measured. We present highly accurate models to identify frequent hitters in AlphaScreen assays.

Phenotypic drug screening in a human fibrosis model identified a novel class of antifibrotic therapeutics.

Fibrogenic processes instigate fatal chronic diseases leading to organ failure and death. Underlying biological processes involve induced massive deposition of extracellular matrix (ECM) by aberrant fibroblasts. We subjected diseased primary human lung fibroblasts to an advanced three-dimensional phenotypic high-content assay and screened a repurposing drug library of small molecules for inhibiting ECM deposition. Fibrotic Pattern Detection by Artificial Intelligence identified tranilast as an effective inhibitor. Structure-activity relationship studies confirmed N-(2-butoxyphenyl)-3-(phenyl)acrylamides (N23Ps) as a novel and highly potent compound class. N23Ps suppressed myofibroblast transdifferentiation, ECM deposition, cellular contractility, and altered cell shapes, thus advocating a unique mode of action. Mechanistically, transcriptomics identified SMURF2 as a potential therapeutic target network. Antifibrotic activity of N23Ps was verified by proteomics in a human ex vivo tissue fibrosis disease model, suppressing profibrotic markers SERPINE1 and CXCL8. Conclusively, N23Ps are a novel class of highly potent compounds inhibiting organ fibrosis in patients.

Inhalational Anesthetics Do Not Deteriorate Amyloid-ß-Derived Pathophysiology in Alzheimer's Disease: Investigations on the Molecular, Neuronal, and Behavioral Level.

BACKGROUND: Studies suggest that general anesthetics like isoflurane and sevoflurane may aggravate Alzheimer's disease (AD) neuropathogenesis, e.g., increased amyloid-ß (Aß) protein aggregation resulting in synaptotoxicity and cognitive dysfunction. Other studies showed neuroprotective effects, e.g., with xenon. OBJECTIVE: In the present study, we want to detail the interactions of inhalational anesthetics with Aß-derived pathology. We hypothesize xenon-mediated beneficial mechanisms regarding Aß oligomerization and Aß-mediated neurotoxicity on processes related to cognition. METHODS: Oligomerization of Aß1-42 in the presence of anesthetics has been analyzed by means of TR-FRET and silver staining. For monitoring changes in neuronal plasticity due to anesthetics and Aß1-42, Aß1-40, pyroglutamate-modified amyloid-(AßpE3), and nitrated Aß (3NTyrAß), we quantified long-term potentiation (LTP) and spine density. We analyzed network activity in the hippocampus via voltage-sensitive dye imaging (VSDI) and cognitive performance and Aß plaque burden in transgenic AD mice (ArcAß) after anesthesia. RESULTS: Whereas isoflurane and sevoflurane did not affect Aß1-42 aggregation, xenon alleviated the propensity for aggregation and partially reversed AßpE3 induced synaptotoxic effects on LTP. Xenon and sevoflurane reversed Aß1-42-induced spine density attenuation. In the presence of Aß1-40 and AßpE3, anesthetic-induced depression of VSDI-monitored signaling recovered after xenon, but not isoflurane and sevoflurane removal. In slices pretreated with Aß1-42 or 3NTyrAß, activity did not recover after washout. Cognitive performance and plaque burden were unaffected after anesthetizing WT and ArcAß mice. CONCLUSION: None of the anesthetics aggravated Aß-derived AD pathology in vivo. However, Aß and anesthetics affected neuronal activity in vitro, whereby xenon showed beneficial effects on Aß1-42 aggregation, LTP, and spine density.

Cilium induction triggers differentiation of glioma stem cells.

Glioblastoma multiforme (GBM) possesses glioma stem cells (GSCs) that promote self-renewal, tumor propagation, and relapse. Understanding the mechanisms of GSCs self-renewal can offer targeted therapeutic interventions. However, insufficient knowledge of GSCs' fundamental biology is a significant bottleneck hindering these efforts. Here, we show that patient-derived GSCs recruit elevated levels of proteins that ensure the temporal cilium disassembly, leading to suppressed ciliogenesis. Depleting the cilia disassembly complex components is sufficient to induce ciliogenesis in a subset of GSCs via relocating platelet-derived growth factor receptor-alpha (PDGFR-α) to a newly induced cilium. Importantly, restoring ciliogenesis enabled GSCs to switch from self-renewal to differentiation. Finally, using an organoid-based glioma invasion assay and brain xenografts in mice, we establish that ciliogenesis-induced differentiation can prevent the infiltration of GSCs into the brain. Our findings illustrate a role for cilium as a molecular switch in determining GSCs' fate and suggest cilium induction as an attractive strategy to intervene in GSCs proliferation.

A drug screen with approved compounds identifies amlexanox as a novel Wnt/ß-catenin activator inducing lung epithelial organoid formation.

BACKGROUND AND PURPOSE: Emphysema is an incurable disease characterized by loss of lung tissue leading to impaired gas exchange. Wnt/ß-catenin signalling is reduced in emphysema, and exogenous activation of the pathway in experimental models in vivo and in human ex vivo lung tissue improves lung function and structure. We sought to identify a pharmaceutical able to activate Wnt/ß-catenin signalling and assess its potential to activate lung epithelial cells and repair. EXPERIMENTAL APPROACH: We screened 1216 human-approved compounds for Wnt/ß-catenin signalling activation using luciferase reporter cells and selected candidates based on their computationally predicted protein targets. We further performed confirmatory luciferase reporter and metabolic activity assays. Finally, we studied the regenerative potential in murine adult epithelial cell-derived lung organoids and in vivo using a murine elastase-induced emphysema model. KEY RESULTS: The primary screen identified 16 compounds that significantly induced Wnt/ß-catenin-dependent luciferase activity. Selected compounds activated Wnt/ß-catenin signalling without inducing cell toxicity or proliferation. Two compounds were able to promote organoid formation, which was reversed by pharmacological Wnt/ß-catenin inhibition, confirming the Wnt/ß-catenin-dependent mechanism of action. Amlexanox was used for in vivo evaluation, and preventive treatment resulted in improved lung function and structure in emphysematous mouse lungs. Moreover, gene expression of Hgf, an important alveolar repair marker, was increased, whereas disease marker Eln was decreased, indicating that amlexanox induces pro-regenerative signalling in emphysema. CONCLUSION AND IMPLICATIONS: Using a drug screen based on Wnt/ß-catenin activity, organoid assays and a murine emphysema model, amlexanox was identified as a novel potential therapeutic agent for emphysema.