SLAS Discovery

The p21-activated kinases (PAKs) are a group of serine-threonine kinases central to multiple signaling pathways that govern cell survival and proliferation. Aberrant activity of PAK1, the most well characterized member of the PAK family, drives progression of several malignancies and brain disorders, including Alzheimers disease and neurodevelopmental disorders. Despite growing interest in PAK1 as a drug target for these diseases, there is no assay to evaluate the intracellular target engagement of PAK1 inhibitors. To address this need, we developed first-in-class NanoBRET assays for wild-type PAK1 and a neurodevelopmental disorder-causing gain-of-function PAK1 mutant. Furthermore, we executed our novel PAK1 NanoBRET assay to evaluate target engagement of PAK1 inhibitors in primary hippocampal neurons. To the best of our knowledge, this is the first demonstration of a NanoBRET cellular target engagement assay in primary neurons, thereby increasing the relevance of our work by confirming PAK1 inhibitor binding to the aberrant form of the protein in primary neurons.

Malaria remains a major global health challenge, with emerging partial resistance to first-line therapies in Africa threatening current control efforts. Drug combinations are essential to improve treatment efficacy and restrain resistance development. However, in vitro assays that quantify parasite viability after drug exposure and characterize pharmacodynamic drug interactions are labor- and resource-intensive, with standard approaches such as the parasite reduction ratio assay limiting systematic, high-resolution evaluation of drug combinations. We present the MUltidimensional Luminescence Test for integration of interactions (MULT-i2), an in vitro assay that enables scalable, high-resolution assessment of parasite viability across multidimensional drug concentration spaces. For dual drug combinations, the MULT-i2 assay characterizes interaction surfaces while requiring [~]50-fold fewer resources and more than two-fold less time than conventional methods, enabling exploration of broader combination scenarios. The assay combines a highly sensitive chemiluminescence readout with inducible reporter expression in Plasmodium falciparum, supporting potential extension to multidimensional combination testing. Using the general pharmacodynamic interaction (GPDI) model, the MULT-i2 assay quantified interaction potency and directionality, confirming and refining the known synergy between atovaquone and proguanil, and revealing detailed interaction patterns for additional drug combinations. Overall, this approach provides an efficient framework for testing and characterizing pharmacodynamic drug interactions and supports the rational development of antimalarial combination therapies.

Advances in transcriptome profiling have revealed transcriptomic differences across different cellular states. However, functional interpretation requires precise perturbation tools and experimental frameworks. This study benchmarked two widely used modalities: CRISPR interference (CRISPRi) and Cas13d/CasRx. A standardized workflow was established to generate human pluripotent stem cells (PSCs) with inducible ZIM3-dCas9 or CasRx expression. The cell lines were subjected to flow cytometry, copy number, and immunocytochemical analyses. The knockdown performance was validated via robust OCT4 suppression and the expected downstream effects on pluripotency genes. Time-course measurements indicated that CRISPRi produced faster and stronger repression but slower recovery after inducer withdrawal. In contrast, CasRx yielded slower and typically weaker knockdown with rapid reversibility. Furthermore, a key limitation of CRISPRi was demonstrated using the ATF5-NUP62 locus, wherein CRISPRi could co-repress genes with overlapping promoter regions. In contrast, CasRx avoids these limitations and supports isoform-resolved targeting of circular and alternatively spliced transcripts, albeit with variable efficiency. These results provide practical guidance for selecting complementary knockdown tools to improve the interpretability of transcriptomic function studies. MOTIVATIONAdvances in transcriptome profiling have enabled the detection of subtle cell type-specific differences. However, mechanistic interpretation still depends on perturbation tools that can modulate transcripts with high precision and efficiency. Recent CRISPR-based modalities, CRISPRi and Cas13/CasRx, function as robust and orthogonal methods to achieve the knockdown of specific gene targets. However, a standardized approach for cell line preparation and comparative studies on their relative performances and limitations remains unclear. Consequently, this study presents a standardized workflow for generating cell lines that support high-efficiency knockdown using CRISPRi and CasRx. Moreover, it compares the trade-offs in potency, reversibility, and isoform resolution, along with a practical overview of method-specific pitfalls to guide tool selection and data interpretation in future studies. HIGHLIGHTSO_LIDoxycycline-inducible AAVS1 knock-in human PSC platforms for CRISPRi (ZIM3-dCas9) and CasRx (RfxCas13d) were generated to enable standardized RNA perturbation experiments. C_LIO_LIThe prepared cell lines demonstrated strong OCT4 knockdown, with expected downstream effects on the expression of another pluripotency gene, NANOG. C_LIO_LIA comparison of knockdown characteristics and their reversibility revealed rapid and sustained repression with CRISPRi, whereas slow but rapid recovery was observed with CasRx. C_LIO_LIA CRISPRi-specific off-target effect arising from TSS proximity/overlap (ATF5-NUP62) was identified, whereas CasRx achieved ATF5 knockdown without collateral repression of the neighboring NUP62 gene. C_LIO_LICasRx enables isoform-resolved knockdown of structural isoforms (circHIPK3 vs. linear HIPK3 mRNA) and splice isoforms (RAB6A-iso1 vs. RAB6A-iso2). C_LI

Validation of somatic mutation burden assays is fundamentally constrained by the absence of a robust ground truth, limiting the interpretability of performance metrics. To address this, we propose a framework based primarily on relative validation, complemented by a suite of secondary metrics aligned to common failure modes. We implement this approach in SomaticCODEC, a ready-to-run assay for quantifying SNV burden in primary human samples, demonstrating strong linearity across mixtures of sperm and blood samples (R2 = 0.91) and high intra-batch precision (CV = 3.3%). This framework provides a practical approach for validating somatic mutation burden assays without requiring a ground truth.

In vitro methods to characterize drug combinations typically involve phenotypic screenings using checkerboard assays (CBA) or, more recently, DiaMOND. Such approaches rely on the Fractional Inhibitory Concentration Index (FICI), a fixed-time measurement of growth inhibition that, nonetheless, necessitates secondary validation by time-kill assays (TKA). Longitudinal time-kinetics of bacterial killing are considered the gold standard in vitro proxy for antimicrobial activity, but they required increased assay complexity, particularly against the slow growing Mycobacterium tuberculosis. Here, we developed a new methodology named OPTIKA (Optimized Time Kill Assays) that enhances the capacity of traditional TKA by over 1000-fold. This allows for easy and dynamic examination of n-way drug interactions by simultaneously monitoring bactericidal and sterilizing capacities in a longitudinal manner. We then replicated previous DiaMOND studies and performed comparisons using CBA and OPTIKA methodologies. We demonstrate that selection of the efficacy parameters (either routed on bacteriostatic, bactericidal or sterilizing properties) affects the interpretation of in vitro drug interactions and, consequently, its potential translational value. The increased assay throughput provided by OPTIKA offers a novel framework for developing tuberculosis treatment regimens. TeaserOPTIKA is a new methodology that increases time-kill assay performance against Mycobacterium tuberculosis by over 1,000-fold

Leukocyte immunoglobulin-like receptor B4 (LILRB4, ILT3) is an inhibitory immune checkpoint expressed on myeloid cells, where it contributes to immunosuppression within the tumor microenvironment. Secretogranin 2 (SCG2) has recently been identified as a functional ligand of LILRB4, yet small molecule modulators of this interaction remain unexplored. Here, we report the development of a high-throughput time-resolved fluorescence resonance energy transfer (TR-FRET) assay to interrogate the LILRB4 (ILT3)-SCG2 interaction. The assay demonstrated robust performance and was validated using a blocking anti-LILRB4 antibody, consistent with orthogonal ELISA measurements. Pilot screening of chemical libraries identified 23 primary hits, of which two compounds, BMS-813160 and PSB-603, showed reproducible, dose-dependent inhibition with TR-FRET IC50 values of 26.7 {+/-} 1.03 {micro}M and 37.2 {+/-} 2.14 {micro}M, respectively. Activity was confirmed by ELISA, supporting the robustness of the assay. This platform enables high-throughput discovery of first-in-class small molecule modulators of the LILRB4-SCG2 immune checkpoint and provides a foundation for targeting myeloid-driven immunosuppression.

The binding of transmembrane (TM) ligands to their cognate TM receptors on neighboring cells governs intercellular adhesion and direct cell-cell communication. However, these interactions are difficult to study in vitro because they depend on membrane presentation, ligand orientation, receptor clustering, and avidity, features often not captured by soluble recombinant ligands or cell-free assays. Here, we describe a flow cytometry-based assay using fluorescent, lentiviral-derived virus-like particles (VLPs) displaying TM ligands to quantify binding to their receptors on target cells. Fluorescent VLPs are generated in-house by plasmid transfection in HEK293T cells and enable direct fluorescent detection without fluorochrome-conjugated secondary antibodies. The system is modular and readily accommodates engineered ligand constructs, including patient-derived variants. We applied this platform to generate ICAM-1-displaying fluorescent VLPs and to study human LFA-1 function in patient-derived leukocytes. This protocol provides a detailed workflow for VLP production and in vitro binding assays, offering a simple, quantitative, and cost-effective approach for studying TM ligand-receptor interactions in a membrane context. The system is well suited for mechanistic studies, functional assessment of patient-derived variants, and direct binding assays using patient-derived cells. Integrating the assay into multicolor flow cytometry panels enables simultaneous immunophenotyping and quantification of up to four ligand-receptor interactions at single-cell resolution. Key featuresO_LIQuantifies TM ligand-receptor binding in a membrane context using fluorescent VLPs and flow cytometry. C_LIO_LIFully in-house, modular system based on plasmid transfection in HEK293T cells, without reliance on recombinant ligands or fluorochrome-conjugated secondary antibodies. C_LIO_LISupports testing of engineered ligand variants, including patient-derived alleles, and direct functional studies on patient-derived cells. C_LIO_LICompatible with multicolor flow cytometry panels, enabling simultaneous immunophenotyping and quantification of up to four ligand-receptor interactions at single-cell resolution. C_LI Graphical overview O_FIG O_LINKSMALLFIG WIDTH=197 HEIGHT=200 SRC="FIGDIR/small/725198v1_ufig1.gif" ALT="Figure 1"> View larger version (55K): org.highwire.dtl.DTLVardef@a43069org.highwire.dtl.DTLVardef@166491borg.highwire.dtl.DTLVardef@49c7d4org.highwire.dtl.DTLVardef@1de36a0_HPS_FORMAT_FIGEXP M_FIG C_FIG

Variants affecting RNA splicing are a major contributor to human disease, yet the consequences of variants outside of the canonical splice motifs are often difficult to determine. Here, we present a protocol for minigene-based evaluation of candidate splice-altering variants. The methodology described includes locus-specific insert design, commercial gene fragment synthesis, and long-read sequencing. The combined approach enables rapid assay development and nucleotide level resolution of the effect on splice isoforms in vitro, providing a scalable framework for functional validation of predicted cryptic splice variants. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=197 SRC="FIGDIR/small/723105v1_ufig1.gif" ALT="Figure 1"> View larger version (42K): org.highwire.dtl.DTLVardef@1a88cb5org.highwire.dtl.DTLVardef@adda98org.highwire.dtl.DTLVardef@1ea587corg.highwire.dtl.DTLVardef@574a63_HPS_FORMAT_FIGEXP M_FIG C_FIG

Cardiac rhythm is a critical clinical indicator for cardiac arrhythmias and adverse events during drug toxicity studies. In vivo, cardiomyocyte responses to pharmacological agents occur within minutes and are strongly influenced by dynamic drug delivery through blood flow. However, conventional 2D and 3D static culture systems fail to replicate these fluid flow kinetics, limiting their physiological relevance for assessing beat rate responses. Here, we present Mera, an advanced microphysiological system (MPS) developed by Hooke Bio, designed for high-throughput, long-term culture and functional analysis of 3D cardiac spheroids composed of human induced pluripotent stem cell-derived cardiomyocytes and cardiac fibroblasts. Mera enables dynamic perfusion, allowing investigation of cardiomyocyte beat rates under physiologically relevant flow conditions. The platform supports up to 640 spheroids per run and integrates automated imaging, fluid handling, and user-friendly software, operating under controlled physiological conditions (37{degrees}C, 5% CO2). Flow rates are tunable between 0 and 12.5 mL/min to mimic in vivo environments. Pharmacological testing with verapamil, isoproterenol, calcium chloride, and propranolol demonstrated real-time, reversible modulation of beat rate under flow, including recovery following drug-induced suppression. System variability was comparable to a temperature-controlled reference platform, supporting robust statistical analysis. Dose-response studies yielded IC values consistent with literature, confirming physiological relevance. Collectively, these results demonstrate that Mera provides a reproducible, scalable, and human-relevant platform for cardiac drug testing. By enabling dynamic drug exposure and automated analysis, Mera represents a powerful new approach methodology (NAM) for improving the predictive assessment of cardiac safety and beat-rate modulation drug responses.

Different omics types such as genomics and proteomics all contribute to deciphering biology. Applying these omics approaches in a spatial context helps reveal biology in situ at a single cell level. Here we present a protocol for the combined multiplexed detection of targeted genes using DNA FISH, and proteins using multiplexed immunofluorescence. The protocol is integrated on the commercial PhenoCycler platform and generates one single dataset with gene and protein readout at a single cell level in large tissue sections, allowing for a throughput of thousands to millions of cells. The workflow can be used for characterising malignant cells in large tumor areas based on genetic aberrations, while deciphering the cellular landscape and microenvironment from multiplexed protein detection using immunofluorescence.

The microtubule and actin cytoskeletons form dynamic, interconnected networks that are critical for eukaryotic cell function. These networks govern intracellular organization, cargo transport, cell migration, and tissue morphogenesis. Microtubules and actin filaments are regulated by diverse binding proteins that control many aspects of their function. However, identifying cytoskeletal-interacting proteins has been challenging due to the transient and weak nature of many interactions and the disruption of native architecture by conventional biochemical approaches. These limitations suggest that numerous physiologically relevant cytoskeletal regulators remain undiscovered. Identifying these factors requires novel and sensitive methodologies that can capture cytoskeletal interactions under native cellular conditions. Here, we present MT-ID and Act-ID, powerful proximity-labeling tools for identifying microtubule and actin-interacting proteins, respectively. MT-ID employs the microtubule-binding domain of MAP7 (EMTB) fused to TurboID, a highly active promiscuous biotin ligase. Act-ID utilizes the actin-binding domain of ITPKA (F-tractin) similarly fused to TurboID. We validate both approaches by successfully identifying numerous known cytoskeletal regulators and discovering potentially novel interacting proteins. Functional characterization reveals that LIMCH1 is a previously unrecognized microtubule-associated protein whose depletion increases microtubule density. Additionally, we identify FBXO30 as a novel actin-interacting protein, with its loss promoting increased focal adhesion formation. MT-ID and Act-ID will be useful not only to identify cytoskeletal interacting proteins but also to define changes to the cytoskeletal interactome when cells are exposed to changing physiological conditions.

Orthohantaviruses cause severe human diseases including hemorrhagic fever with renal syndrome (HFRS) and hantavirus cardiopulmonary syndrome (HCPS), with case fatality rates up to 40%. No FDA-approved therapeutics are currently available, highlighting urgent need for drug development following recent outbreak events. We systematically examined host protease dependencies in hantavirus replication, focusing on Signal Peptidase (SP) and Signal Peptide Peptidase (SPP) essential for viral glycoprotein maturation. Through comprehensive database mining and molecular docking analysis, we identified six potential protease inhibitors, with Compound E achieving the highest binding confidence score (-0.28) against SPP. Our analysis reveals that targeting host ER proteases represents a viable antiviral strategy, providing a systematic framework for protease-targeted antihantavirus drug development and identifying specific lead compounds for experimental validation.

Along with the membrane potential and respiration, mitochondrial matrix volume is a critical parameter that determines mitochondrial function. Mitochondria undergo constant changes in matrix volume and cristae dynamics, and in processes that are critical for normal metabolic rates and pathophysiological responses. Changes in matrix volume cannot be easily measured by conventional fluorescence imaging techniques due to the size of the sub-organellar structures, which are below resolution. This challenge was successfully resolved in studies of isolated mitochondria with the use of scattered light. Here we use dark-field imaging, which relies on scattered light contrast, to measure matrix volume dynamics in living cells. We demonstrate that mitochondrial volume changes can be easily detected as changes in intensity of the scattered light following matrix volume modulation with K+ ionophores or by onset of the permeability transition. Specifically, we found that stimulation of K+ influx leads to increase of mitochondrial matrix volume while stimulation of K+ efflux leads to matrix shrinkage, and that activation of the permeability transition leads to high-amplitude mitochondrial swelling in wild-type but not in cells lacking subunit c of ATP synthase. These results directly demonstrate the dynamic nature of mitochondrial matrix volume and its link to physiological and pathological ion transport.

The rise of new, rapidly mutating viruses presents increasing challenges for drug developers. Traditional methods, such as high-throughput screening and drug repurposing against mutagenic viral targets, have recently shown their limitations. Our current rational molecular engineering approach offers a sustainable solution by targeting viral ion channels, which generally have low mutation rates. First, extending the amantadine molecule led to the development of new compounds that better match the alternating hydrophobic and hydrophilic patterns of the inner walls of ion channels--a common feature across many viruses. Then, simplifying the structure yielded a cyclohexylamine-based minimalist scaffold that effectively blocks the ion channel and demonstrates improved antiviral activity compared to well-known agents such as amantadine and arterolane. SARS-CoV-2 variants served as test systems in laboratory experiments. The new molecular scaffolds presented here provide a strong foundation for designing potent, broad-spectrum viral ion channel blockers.

Metastasis remains the major cause of cancer-related mortality, and circulating tumor cells (CTCs) are both candidate liquid-biopsy biomarkers and plausible intermediates of metastatic dissemination. Because CTCs are extremely rare in peripheral blood, platform comparisons have often focused solely on recovery. That focus is insufficient for applications that depend on the quality of the recovered material, including single-cell profiling, short-term culture, and functional testing. Here, we compared four CTC isolation approaches: TellDx CTC System, Genesis System, RosetteSep, and flow cytometry, using spike-in experiments in human blood. Capture efficiency was evaluated across all four platforms; purity was assessed for TellDx, Genesis, and RosetteSep; and post-isolation GFP signal persistence in culture was assessed for TellDx and Genesis as an exploratory proxy for short-term post-isolation preservation. Under the conditions tested, TellDx showed the highest recovery (88.1% {+/-} 3.7%), followed by Genesis (40.6% {+/-} 12.1%), RosetteSep (36.5% {+/-} 9.0%), and flow cytometry (7.6% {+/-} 4.5%). TellDx also showed the highest purity score (3.76), whereas Genesis (2.25) and RosetteSep (2.09) did not differ substantially. In the short-term culture assay, TellDx-derived samples retained a higher normalized GFP signal than Genesis-derived samples at 48 h and 72 h. To synthesize these readouts, we propose the Recovery Performance Index (RPI), a composite score integrating recovery, purity, and post-isolation signal persistence. Within this experimental framework, TellDx achieved the highest RPI. These data support two conclusions. First, platform benchmarking for CTC workflows benefits from multidimensional evaluation rather than recovery alone. Second, under this spike-in model and within the specific workflows used here, TellDx performed best among the platforms tested. The principal contribution of this study is therefore the establishment of a practical benchmarking framework that can be expanded in future work using clinical samples, multiple CTC phenotypes, and orthogonal viability assays.

Transcriptional bursts regulate gene expression by altering burst size or burst frequency. Here, we present a protocol that integrates fixed-cell smFISH and live-cell single-molecule imaging to analyze estrogen-responsive transcriptional bursting of the TFF1 gene in human breast cancer cell lines. This workflow enables measurement of burst size, burst initiation, and active allele frequency to determine how endocrine disruptor chemicals modulate transcriptional bursting dynamics. For complete details on the use and execution of this protocol, please refer to Day, Yasar et al.1

The binding of fluorescent dyes to nucleic acids and their fluorogenic properties are indispensable tools for nucleic acid detection, quantification, and imaging, yet the molecular structures of several widely used commercial dyes have remained unknown. Here, we de novo determined the molecular structures of RiboGreen and OliGreen and confirmed the previously proposed structure of PicoGreen using high-field NMR spectroscopy. All three dyes were identified as unsymmetric cyanine dyes, where a benzoxazole/benzothiazole moiety is linked to a 4-quinoline by a monomethine bridge. Complete 1H and 13C resonance assignments enabled us to expand the existing chemical shift reference set for this important class of dyes. Photophysical characterization with standardized single- and double-stranded DNA and RNA targets indicated that all dyes performed similarly upon binding despite being marketed towards different nucleic acid types. NMR spectroscopy and long-timescale molecular dynamics simulations showed that RiboGreen interacts with double-stranded DNA predominantly by two binding modes, electrostatic interactions with the phosphodiester backbone and {pi}-{pi} stacking with the ultimate and penultimate base pairs of the DNA molecule. These results establish the molecular structures of three widely used commercial dyes and provide a structural and mechanistic framework for understanding the fluorogenic properties of this class of dyes. HighlightsO_LIDetermination of the molecular structures of nucleic acid dyes RiboGreen, OliGreen, and PicoGreen C_LIO_LINMR spectroscopic characterization of all three dyes. C_LIO_LINMR and MD data indicate binding to be dominated by electrostatic and {pi}-{pi} stacking interactions C_LI

Background and PurposeCardiotoxicity is a major cause for drug failure throughout the drug development process, with particular concern for action potential prolongation and arrhythmia. Hence, such liabilities are heavily considered during the early phases of drug design to pre vent dangerous compounds from progressing. New approach methodologies (NAMs) that efficiently examine this risk early in the discovery pipeline should help streamline drug development programs. We developed a cardiac NAM, a 384-well open bath platform consisting of cardiac tissue derived from human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes, enabling high-throughput drug screening while maintaining the structural and functional complexity of 3D cardiac micromuscles. MethodsWe dramatically increased throughput without compromising physiological relevance provided by the 3D micromuscle structure. Our 384-well open bath high-throughput platform allowed evaluation of multiple compounds at a time, enabling us to study the CiPA (comprehensive in vitro proarrhythmia assay) drug panel for proarrhythmia screening. We obtained phenotypic fingerprints of all 28 compounds (9 low, 11 intermediate, and 8 high arrhythmia risk; https://cipaproject.org) in dose-escalation studies around their respective clinical concentrations. The analysis was augmented with an in silico pipeline that used phenotypic biomarkers to invert data into a mathematical model of cellular currents to infer which ion channels were affected upon drug exposure, and then trained a ML model to predict channel block. Results and ConclusionsWe found accurate detection of arrhythmic potential for most of the compounds, and the in silico model inversions were consistent with published values of compound channel block. All the high risk compounds showed action potential duration (APD) prolongation coupled with either action potential abnormalities, early afterdepolarizations (EADs), or beat cessation. For the intermediate risk group, 9 out of 11 compounds caused APD prolongation alone or in combination with EADs while 2 others showed either beat cessation or beat rate change. Augmentation of APD analysis with detailed biophysical modeling and ML tools provided meaningful insight into the mechanisms involved in APD changes. Overall, our cardiac NAM allowed for fast and relevant screening for mechanistic understanding of APD prolongation and proarrhythmic activity, at massively increased throughput compared to other 3D micromuscle models. SummaryCardiotoxicity testing is critical in drug development to prevent arrhythmogenic side effects. Current stringent regulations have greatly reduced market withdrawals; however, these strict evaluations often lead to costly late-stage failures and loss of promising candidates as false positives. We developed a cardiac new approach methodology (NAM), a 384-well open bath cardiac micromuscle platform created from hiPSC-derived cardiomyocytes, enabling high-throughput drug screening while maintaining the structural and functional complexity of 3D cardiac micromuscles. Using the comprehensive in vitro proarrhythmia assay (CiPA) drug panel, we validated the system to accurately detect proarrhythmic potential. Our assay provided phenotypic fingerprints based on mechanical and electrophysiological biomarkers. Integration with computational modeling offered insights into multi-ion channel effects (MICE). Particularly, we identified sodium channel block contributions as a significant factor for poor risk prediction based on traditional parameters. The combined experimental and computational platform can enhance early drug screening, thereby reducing late-stage failures and promoting the progression of low-risk compounds with complex electrophysiological profiles.

Metabolomics offers a sophisticated analytical framework for characterising the molecular phenotype of biological organisms and complex living systems at a high resolution. As the functional endpoint of the omics cascade, the metabolome serves as a close reflection of cellular activity. It integrates genetic, transcriptomic and proteomic variations with external environmental influences. However, the inherent complexity of metabolomic datasets, characterised by high-dimensional chemical diversity, wide dynamic ranges, and significant matrix effects, necessitates a rigorous suite of chemometric and bioinformatic workflows. For researchers uninitiated in computational biology, the multi-stage requirement for raw data pre-processing, signal deconvolution, and multivariate statistical modelling (such as PCA or PLS-DA) presents a substantial barrier to entry. Navigating these convoluted data architectures remains a primary challenge in deriving biological meaning from the global metabolic profile. Here, we present a workflow to use Python Dash Apps to create a user-friendly interface for simplifying data processing and statistical calculations. Users can select their desired samples to initiate calculations for various statistical tests, generating interactive and publication-quality figures to explore their results. These apps were deployed on an Apache server via cPanel, allowing individuals to share their findings with collaborators and for research facilities to share metabolomics results with their users.

Double-stranded RNA (dsRNA) is recognized by cellular receptors as a sign of viral infection, triggering the innate immune response. Increasing evidence shows that cellular dysregulation, for example in immune disorders and neurodegenerative diseases, can also lead to accumulation of endogenously produced dsRNA that stimulates a viral-like immune response. Additionally, dsRNA contamination in RNA therapeutics can lead to harmful side effects via a similar pathway. Despite the clinical relevance of dsRNA, reliable tools for its detection remain limited. At present, dsRNA detection relies almost exclusively on the monoclonal antibodies J2 and K1, which suffer from sequence bias and low sensitivity, limiting their reliability. To address this challenge, we aimed to repurpose naturally occurring dsRNA-binding domains (dsRBDs) to produce reliable, pan-specific affinity reagents for dsRNA. We first systematically screened the dsRBDs of the three human adenosine deaminases acting on RNA (ADARs). This analysis identified ADAR3 dsRBDs as promising candidates due to their reduced sequence dependence compared to the dsRBDs of ADAR1 and ADAR2. We then engineered ADAR3-derived dsRBD constructs having varying linker lengths and domain combinations, allowing us to specifically vary the length cutoff of dsRNA detected, thus creating dsRNA accumulation detected by ADAR3 RBDs (dsRADAR) affinity reagents. Finally, we demonstrate the superior performance of dsRADAR over currently available dsRNA antibodies in a cell model of viral infection and a tissue model of gastric inflammation. Together, dsRADAR provides a sensitive and reliable approach for imaging and quantifying diverse dsRNA structures in a variety of biological contexts. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=124 SRC="FIGDIR/small/724404v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@1d89c30org.highwire.dtl.DTLVardef@1f64fc1org.highwire.dtl.DTLVardef@1ee391forg.highwire.dtl.DTLVardef@e834a6_HPS_FORMAT_FIGEXP M_FIG C_FIG