Biology subjects

Wang, J.

Publications and source records attributed to Wang, J..

At least 271 records · Page 15Linked to original sources

bioRxiv2026

Toward a Random Background for Ligand Optimization

Ligand optimization is central to drug discovery as hundreds of analogs might be designed and synthesized between an initial hit and a therapeutic candidate. The efficiency of this process is unclear, at least partly because there is no random background for optimization against which to compare. Such a random background might emerge from synthetically accessible but otherwise systematic random small substitutions across starting ligands, measuring likelihood of achieving a substantial improvement in affinity/potency or other property by any single perturbation. Recent literature and ligand-affinity/potency databases suggest that perhaps 10% of analogs with minor modifications improve upon a parents potency substantially (by [≥]10-fold), but this number is clouded by reporting bias, intentional improvement, and inter-group reproducibility. To begin to establish a background expectation for ligand optimization, we comprehensively and systematically modified 18 lead molecules across six targets with single atom changes; 257 compounds were synthesized. Unexpectedly, 11.2% of these random small perturbation analogs improved potency by [≥]10-fold over their parents. Conversely, these more potent analogs typically had worse in vitro pharmacokinetics (e.g. reduced metabolic stability, lower plasma free fraction). While it was possible to find analogs where the potency increase compensated for inferior exposure and half-life, resulting in more potent compounds in vivo, overall a frustrated landscape for ligand optimization is revealed. This study begins to establish a background expectation for ligand potency optimization and offers a simple strategy to do so. It also begins to quantify the challenges confronting the field in moving beyond in vitro potency.

pharmacology and toxicology↗

bioRxiv2026

Cell-Level Virtual Screening

Virtual screening methods prioritize therapeutic candidates by predicting molecular properties and interactions. However, molecular models are insufficient to predict higher-order effects that arise in real biological systems, leading to late-stage failures in drug discovery. Virtual cells have been posed as a solution to this problem by predicting gene expression responses to drugs, but they remain weakly validated as screening tools; gene expression is only an intermediate in understanding drug success or failure. Despite burgeoning progress in virtual cells, some basic questions remain. Is expression even a good representation of higher-order drug effects? How can expression and other cell-level representations be applied to prioritize therapeutic candidates? Can cell-level methods be fairly compared against traditional molecular-level screens? We address these questions in a two-pronged approach. First, we curate two benchmarks, Drug-Disease Retrieval Bench (DDR-Bench) and Drug-Target Retrieval Bench (DTR-Bench), which directly compare cell-level methods against traditional molecular methods on canonical drug discovery tasks. DDR-Bench evaluates a methods ability to prioritize disease indications for drugs with novel target profiles. DTR-Bench evaluates a methods ability to reconstruct drug-target interactions from separate perturbation modalities that act on shared mechanisms, bridging the gap between cell-level methods and classic molecular screens. We identify shortcomings of existing screening methods on these benchmarks, and propose an alternative representation of drug effects: perturbed gene networks. Inferring post-perturbation gene networks on-demand for unseen drugs requires methods that generalize beyond traditional plug-in network estimators. We develop a scalable differentiable surrogate loss for multivariate Gaussians, which we apply to train a context-adaptive amortized estimator that maps perturbation metadata to gene-gene dependency network parameters. The resulting model, CellVS-Net, achieves SOTA on predicting how gene networks restructure under a variety of complex multivariate experimental conditions, including different cell types, small molecule therapeutics, signaling molecules, gene knockdowns, and gene over-expressions. When compared to other molecular and cell-level representations of drugs, we find that CellVS-Net achieves SOTA on both virtual screening benchmarks. Overall, CellVS-Net demonstrates that cell-level virtual screening methods are a viable alternative to molecular screening, and associated benchmarks enable hill-climbing on relevant drug discovery tasks.

bioinformatics↗

bioRxiv2026

The phosphoproteomic landscape of the DNA damage response

The DNA damage response (DDR) comprises an intricate network of protein-protein interactions and signaling pathways activated by DNA lesions and genomic instability. Central to this response is protein phosphorylation, which orchestrates DNA repair, cell cycle checkpoint activation, and chromatin organization. The response of the human phosphoproteome to different DNA damage-inducing agents and the functional role of regulated phosphorylation sites remains insufficiently characterized. Here, we systematically profiled the cellular phosphoproteome following exposure to eleven DNA damage-inducing agents that humans encounter physiologically or during cancer therapy. We identified a core set of DNA damage responsive phosphorylation sites, along with DDR signatures associated with DNA double strand breaks, replication stress and a pleiotropic response. Regulated phosphorylation sites are enriched within intrinsically disordered regions (IDRs), often forming clusters of nearby modifications that can affect IDR conformations or overlap with short linear interaction motifs. We discover that the RNA damage response predominantly shapes the changes induced by reactive aldehyde formaldehyde, alkylating agent methyl methanesulfonate and oxidative stress. Finally, we demonstrate that the proteasome-associated ubiquitin E3 ligase UBE3A is targeted by ATM and ATR kinases, thus linking proteasome regulation with the DDR.

cell biology↗

bioRxiv2026

In-situ structure of the flagellar export apparatus in Borrelia burgdorferi

The transmembrane export apparatus is a conserved core of bacterial type III secretion systems, shared by the flagellum and injectisome. Powered by the proton-motive force (PMF), this machinery translocates protein substrates across the bacterial envelope to support motility and virulence. However, its assembly and operation within native membranes remain poorly understood. Here, using in-situ single-particle cryo-electron microscopy, we resolve near-atomic-resolution structures of the flagellar export apparatus within the periplasmic flagellar motor of the Lyme disease spirochete Borrelia burgdorferi. Structural and genetic analyses suggest that coordinated, stepwise assembly of the flagellar export apparatus and MS-ring drives local deformation of the cytoplasmic membrane through extensive protein-lipid-protein interactions, constructing a funnel-shaped conduit optimal for substrate translocation. In addition, a conserved hydrophilic pathway lies within core export protein FlhA, with key acidic residues essential for export activity and supporting PMF-driven substrate translocation. Together, these findings establish a mechanistic framework for export apparatus assembly and energy transduction, defining core principles of type III secretion.

microbiology↗

bioRxiv2026

Reversible in vivo regulation of drug metabolizing enzyme CYP1A2 activity through a dTAG knock-in strategy

Drug-metabolizing enzymes determine therapeutic exposure, efficacy and toxicity, but defining their isoform-specific functions in vivo remains challenging. Cytochrome P450 enzymes (P450s) are central to drug metabolism and pharmacokinetics (DMPK) and mediate the phase I metabolism of [~]75% of all marketed drugs. However, conventional knockout models can induce develop-mental and compensatory adaptations, and selective inhibitors are unavailable for many P450 isoforms. Here, we report the use of an inducible chemical-genetic platform for acute and specific degradation of the endogenous P450 enzyme Cyp1a2 in mice. Using CRISPR-Cas9-mediated knock-in editing, we introduced an FKBP12F36V degron into the endogenous Cyp1a2 locus to generate Cyp1a2dTAG mice. Treatment with the dTAG degrader dTAG-13 recruited an E3 ubiquitin ligase to CYP1A2dTAG, resulting in rapid and reversible proteasomal depletion of CYP1A2dTAG in vivo. Temporally controlled CYP1A2dTAG loss altered caffeine pharmacokinetics as expected, validating this model as a functional tool for DMPK studies. By enabling reversible suppression of drug-metabolizing enzymes without permanent deletion or chronic inhibitor exposure, this work establishes targeted protein degradation as a broadly adaptable strategy for studying drug metabolism in vivo and provides a foundation for extending inducible DMPK control to other P450s, conjugating enzymes and transporters.

pharmacology and toxicology↗

bioRxiv2026

Culsma: A Formal Language for Laboratory Protocols

Laboratory protocols are commonly communicated in natural language, leaving room for variation in how experimental commitments are understood and carried out. We present Culsma, an executable specification language in which protocols are written as programs. The same program is legible to bench scientists and directly machine-readable by software that checks and runs it. It serves as the protocol's operational specification, making experimental commitments explicit for checking before execution and retaining them in results. Culsma addresses how experimental procedures are modeled: it defines operations by the experimental changes and relationships they establish, giving a fine-grained, compositional basis whose technique- and device-specific realizations remain extensible. We examine this boundary in workflows spanning molecular and cell biology, protein biochemistry, and immunoassays, which combine material handling, separation, and measurement differently, asking which distinctions the operation interface preserves. A maintained, source-linked benchmark broadens this evaluation with versioned checks of source-step correspondence and software execution.

bioinformatics↗

bioRxiv2026

Receptor-Anchored Olfaction Representation through Perception-Consistent Metric Learning

Olfactory perception arises from distributed activation across hundreds of olfactory receptors (ORs), yet our understanding of this landscape remains constrained by the scarcity of OR affinity measurements. Here, we present Receptor-Anchored Metric Supervision (RAMS), a transfer learning framework using perceptual consistency as weak supervision to predict OR activation spectra. RAMS fine-tunes a pretrained drug-target affinity model by imposing constraints derived from olfactory perception, where similar odorants are encouraged to exhibit similar OR activations. It transfers protein-ligand interaction knowledge learned from large-scale pharmacological data into the olfactory domain and reshapes it toward OR activation prediction. Evaluations against experimental measurements show that RAMS improves the accuracy of receptor-spectrum prediction and yields biologically plausible activation patterns. The predicted spectra show concordance between receptor discriminative capacity and expression level, and highlight the understudied OR52 family as a potential contributor to primary odor recognition. Together, RAMS provides a scalable framework for reconstructing receptor-anchored olfactory representations.

bioinformatics↗

bioRxiv2026

ProteinFlux: accurate, rapid and scalable generative prediction of protein dynamics driven by post-translational modifications

The function of proteins, the building blocks of life, in health and disease depends not only on their 3D-conformational states but most importantly on the dynamic transition between states controlled by a wide array of post-translational modifications (PTMs). Recent major advances have been made in our ability to predict static 3D structures; however, understanding and predicting the impact of PTMs on protein conformational dynamics remains a major question and challenge in the field. Molecular dynamics (MD) simulation remains the major computational approach for studying protein dynamics. However, the high computational cost, lack of integration of PTMs as conditioning inputs and inefficient generation of continuous protein dynamics largely precludes PTM-regulated conformational dynamics and the study of slow conformational processes. To address this critical bottleneck, we developed ProteinFlux, a flow-matching generative framework that links PTM-conditioned conformational dynamics to evolutionary constraints encoded by PTM sites. Evolutionary information plays a critical role in capturing conformational dynamics beyond sequence identity, and PTM sites inherently encode evolutionary constraints critical to protein functional regulation. We therefore built FluxSite, a dual-modal PTM site predictor that integrates sequence evolutionary information and 3D structural features to generate a continuous conditional signal encoding conservation and functional importance for each predicted site. FluxSite achieves robust generalization across 18 PTM types and 30 disease-associated proteomes. ProteinFlux generates phosphorylation-conditioned, all-atom conformational trajectories across diverse protein fold classes, faithfully reproducing both thermodynamic properties such as free energy landscapes and kinetic features such as conformational transition pathways. It outperforms state-of-the-art predictors while achieving inference speeds several orders of magnitude faster than traditional MD. In addition, we introduce DynaMo-phos, a benchmark dataset of phosphorylated protein MD simulations. Together, ProteinFlux, FluxSite and DynaMo-phos provide a scalable, high-throughput platform for elucidating PTM-driven conformational mechanisms, with potential applications across allosteric drug design, functional annotation of disease-associated modifications and mechanism-guided therapeutic development.

bioinformatics↗

bioRxiv2026

LSD persistently disrupts affective pain processing

Psychedelics produce long-lasting effects, but their circuit mechanisms remain unclear. Here we show that, in rats, a single dose of lysergic acid diethylamide (LSD) persistently reduces pain affect. This effect is recapitulated by local administration in the anterior cingulate cortex (ACC), but not primary somatosensory cortex. Neuropixels recordings reveal that LSD suppresses stimulus-evoked nociceptive responses in the ACC, reducing the encoding of aversive value. Despite increasing intrinsic excitability ex vivo, LSD reduces the maximum stimulus-evoked firing of ACC neurons in vivo, indicating a dissociation between excitability and sensory encoding. Together, these findings show that psychedelics disrupt the cortical transformation of nociceptive input into aversive representations.

neuroscience↗

bioRxiv2026

Structural basis of MK-97 positive allosteric modulation at the M4 mAChR

Positive allosteric modulators (PAMs) of the M4 muscarinic acetylcholine receptor (mAChR) represent a promising therapeutic strategy for treating cognitive deficits and neuropsychiatric disorders. While first-generation M4 mAChR PAMs, like LY2033298, demonstrated proof-of-concept, second-generation compounds, such as MK-97, exhibit substantially improved potency and reduced species variability. Here we report the cryo-EM structure of the M4 mAChR bound to the endogenous agonist, acetylcholine, and MK-97 at 2.7 [A] resolution, revealing the molecular basis for improved M4 mAChR PAM activity. MK-97 adopts a distinctive boomerang-shaped conformation within the extracellular-facing allosteric binding site, with a central pyridine vertex, a lower cyclopentylmethylpyrazole arm extending toward the floor of the orthosteric site, and an upper isoindolinone arm projecting toward extracellular loop 2 (ECL2). This extended binding mode establishes a distributed interaction network across transmembrane helices TM2, TM3, TM5, TM6, and TM7, with key contacts including a hydrogen bond with Y922.64 and a {pi}-{pi} stacking interaction with W4357.35. Integration of structural data, molecular dynamics simulations, and mutagenesis validation reveals that the high affinity of MK-97 derives from optimized engagement across all three binding regions rather than dependence on any single critical contact. Insights from comprehensive structure-activity relationship (SAR) studies provide a molecular framework for the rational design of next-generation M4 mAChR PAMs with improved pharmacological properties. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=70 SRC="FIGDIR/small/723386v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@75cb90org.highwire.dtl.DTLVardef@1876c9corg.highwire.dtl.DTLVardef@1eba8d0org.highwire.dtl.DTLVardef@9818ad_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

bioRxiv2026

Unraveling the metabolic interactions of a Dehalobacter-containinganaerobic mixed culture for bioremediation

Organohalide-respiring bacteria (OHRB), such as Dehalobacter, play key roles in the bioremediation of anoxic environments contaminated with chlorinated aromatic compounds. These obligate anaerobes rely on syntrophic interactions to obtain essential resources--hydrogen, acetate, and corrinoid cofactors--from acetogens and fermenters. However, the metabolic interactions enabling complete reductive dehalogenation of compounds like 1,2,4-trichlorobenzene (1,2,4-TCB) to benzene remain incompletely understood. In this study, we asked: (1) What are the key microbial taxa and their functional roles within a Dehalobacter-containing anaerobic microbial community detoxifying chlorinated benzenes? (2) How do syntrophic interactions enable complete dehalogenation of 1,2,4-TCB to benzene under anaerobic conditions? (3) Can genome-resolved metagenomics and genome-scale metabolic modeling elucidate the metabolic dependencies supporting organohalide respiration in complex consortia? To address these questions, we cultivated microbial communities in batch reactors using methanol as electron donor and either 1,2,4-TCB or monochlorobenzene (MCB) as electron acceptor. In active MCB-fed cultures, benzene increased from 0 to 62.3{micro}mol per bottle while MCB decreased from 88.3 to 22.0{micro}mol per bottle over 120 days, with this pattern repeating across multiple substrate additions. Using genome-resolved metagenomics to identify dominant taxa and select 12 high-quality metagenome-assembled genomes (MAGs) for modeling, we reconstructed genome-scale metabolic models (GEMs) to identify candidate metabolic interactions and predict syntrophic dependencies that may support organohalide respiration in these consortia. Community flux sampling predicted that methanol, H2, acetate, and CO2 formed the dominant exchange backbone of the modeled community, while also indicating competition for shared electron donors between the two Dehalobacter populations. Model-guided minimal-community analysis further identified a narrow dechlorinating core in which all feasible minimal consortia retained a Dehalobacter member together with Methanothrix. These results provide a modeling-informed framework for hypothesis generation and future experimental validation of anaerobic consortia relevant to bioremediation.

systems biology↗

bioRxiv2026

3'UTR Insertion of a Directed-Evolved RNA Element for Enhanced Translation

Translation efficiency remains a major limitation for RNA therapeutics. Conventional optimization targets the 5 untranslated region (5 UTR), while the 3 UTR is viewed mainly as a stabilizing element. Here, we demonstrate that the 3 UTR can be rationally engineered to actively enhance translation. Using an intracellular directed-evolution platform based on the SINEB2 element, we identified RNA modules P51 and its compact variant P51t3,which markedly increased protein output without affecting mRNA levels. P51t3 consistently boosted expression two- to six-fold across plasmid, in vitro transcribed mRNA, and recombinant AAV systems. Mechanistic studies revealed that P51t3 binds ribosomal protein RPL39, recruiting 60S subunits to the initiation site through the natural closed-loop translation model. By integrating evolutionary selection with 3 UTR design, this work redefines the 3 UTR as an active translational enhancer and provides a broadly applicable regulatory element for next-generation mRNA and gene-delivery therapeutics.

molecular biology↗

bioRxiv2026

BART-spatial unravels biologically significant transcriptional regulators from spatial omics data

Transcriptional regulators (TRs) are crucial regulators of cell fate decisions by activating or repressing lineage-specific genes and integrating environmental signals with intrinsic networks. Identifying functional TRs is essential for understanding development, tissue organization, and disease. Emerging spatial transcriptomics and epigenomics technologies now provide near- single-cell resolution mapping of genomic features while preserving information of each cells physical location and microenvironment which influence TR activity. Despite these advances, identifying active TRs in spatial data remains challenging due to low TR expression and the fact that TR activity often does not correlate directly with mRNA levels. Moreover, existing tools mainly designed for non-spatial single-cell data overlook spatial heterogeneity. To bridge this gap, we developed BART-spatial (Binding Analysis for Regulation of Transcription for spatial omics data), an innovative computational method to infer functional TRs from spatial omics data. BART-spatial integrates spatial variability and pseudotemporal information with publicly available TR binding profiles. Applied to multiple spatial datasets from diverse platforms, including 10x Visium, Visium HD, Atera, and spatial RNA-ATAC-seq, BART-spatial consistently outperforms existing methods, identifying state-specific TRs and revealing regulators undetectable by expression alone. Its compatibility with spatial epigenomics data further strengthens its utility and enables cross-validation. Overall, BART-spatial provides a powerful and robust tool for decoding spatially resolved gene regulatory programs.

bioinformatics↗

bioRxiv2026

Scalable longitudinal imaging and transcriptomics of cells in dynamic enclosures

Dynamic transitions between cell states underlie both normal physiology and disease. However, most single-cell technologies capture only static snapshots. To address this gap, we developed a platform that integrates light-guided hydrogel polymerization with computer vision to generate on-demand compartments around live cells, enabling longitudinal imaging of cellular behavior paired with whole-transcriptome profiling of the same cells at scale. These data link dynamic phenotypes with molecular programs, enabling deeper characterization of cellular states. This approach revealed an adaptive, drug-resistant state in lung cancer cells characterized by potassium channel upregulation and p53-dependent quiescence. In models of adipogenesis and microglial phagocytosis, joint analysis of imaging and transcriptomic data identified key drivers of cellular function that were missed by transcriptomic clustering alone. These results establish the value of paired functional and transcriptomic analysis to resolve molecular drivers of complex cellular behaviors.

systems biology↗

bioRxiv2026

Linking live-cell behavior to transcriptional responses across perturbations using dynamic caging

Single-cell technologies, encompassing molecular, morphological, and functional assays, have emerged as cornerstones of modern biological research and discovery. However, current experimental methods often fail to explicitly link these omic modalities, especially in live cells or longitudinally through time, impeding the study of multi-scale interactions and mechanisms of regulation. CellCage Enclosure (CCE) technology overcomes these limitations by dynamically compartmentalizing cells, allowing for scalable, live-cell, longitudinal exploration and simultaneous analysis of transcriptomic, proteomic, and morphological profiles. Using this novel technology, we generate previously inaccessible insights across various in vitro cellular systems under a diverse set of perturbations, including the discovery of morphological and proteomic features linked to immune suppressive gene set expression in human primary regulatory T cells (Tregs), as well as direct association of morphological and proteomic features with inflammatory gene modules in human colonic fibroblasts. We then develop a novel pooled CRISPR genetic screening technology using CCEs, PERTURB-LINK (PERTURBational LINKage of transcriptomics and imaging in single cells via enclosure-based screening) and apply this approach in murine bone marrow derived macrophages (BMDMs), enabling multiomic dissection of NF-{kappa}B pathway regulation in response to lipopolysaccharide (LPS) stimulation. Together, these findings demonstrate the broad impact that advancements in live-cell, paired multimodal technologies, especially upon perturbation, may offer in deepening our understanding of cellular biology.

cell biology↗

bioRxiv2026

A Continuum of Atrial Peristalsis Initiates the Bicuspid to Quadricuspid Valve Transition

How chamber-specific hemodynamic shear forces coordinate the spatial and temporal patterning of cardiac valves remains poorly understood. The zebrafish atrioventricular (AV) valve transitions from 2-cusp to 4-cusp at 14 days post-fertilization (dpf) through commissural remodeling, differential cell proliferation, and chondrogenic matrix secretion. Orthogonal valvular axes are present at 25 hpf (hours), preceding endocardial cushion formation. AV canal remodeling aligns the shear stress with leaflet formation at 48 hpf and 14 dpf. At 28 hpf, the ventricle develops functional syncytium, while the atrial peristalsis remains and is necessary for the Klf2a-Snai1b signaling in Notch-negative and ccm1-positive endocardial cells. Without atrial contraction, the 2-to 4-cusp transition (86.7%) fails to occur. In the absence of ventricular contraction and relaxation, the formation of the first pair of leaflets (100%) does not initiate. As a corollary, we demonstrate that KLF4/SNAI1 expression at the commissure is conserved in the mammalian AV 2- to 4-cushion transition.

developmental biology↗

bioRxiv2026

Microglial pruning of extinction-ensemble synapses preserves fear memory

Fear extinction suppresses learned fear without erasing the original memory, yet how competing fear and extinction ensembles are selectively updated remains unknown. Here, we show that microglia preserve fear memory by selectively editing extinction-ensemble synapses during retrieval. In medial prefrontal cortex, microglial processes, but not somata, expand, ramify, and tighten their engagement with extinction-ensemble dendrites and spines, where they preferentially engulf excitatory postsynaptic material and bias spine remodeling toward elimination. This selectivity is instructed by local find-me, eat-me, and dont-eat-me cues: purinergic signaling recruits microglial processes, phosphatidylserine exposure licenses engulfment of extinction-ensemble synapses, and CD47-SIRP protects fear ensembles from removal. Weakening microglial recruitment or engulfment, or removing this protection, accelerates extinction without impairing fear acquisition. These findings identify microglial processes as active gatekeepers of ensemble competition and reveal a neuroimmune mechanism that preserves fear memory by limiting extinction. In BriefDuring memory updating, microglial processes selectively engage extinction-ensemble synapses rather than globally pruning active circuits. Local recruitment, engulfment, and protection cues determine this choice, allowing microglia to preserve fear memory by limiting extinction. HighlightsO_LIExtinction retrieval selectively recruits microglial processes to extinction ensembles. C_LIO_LIMicroglia preferentially engulf excitatory postsynaptic material from extinction ensembles. C_LIO_LILocal "find-me," "eat-me," and "dont-eat-me" cues determine synapse selection. C_LIO_LIDisrupting microglial pruning facilitates extinction without impairing fear learning. C_LI

neuroscience↗

bioRxiv2026

IFITM1 inhibits Henipavirus membrane fusion by trapping ephrinB2 receptors in fusion-unfavorable membrane nanodomains.

Nipah (NiV) and Hendra (HeV) viruses are prototype henipaviruses (HNV) within the family of Paramyxoviridae. They are highly pathogenic zoonotic paramyxoviruses that cause fatal encephalitis in humans, with case fatality rates of 40-70%. These viruses use the receptor-binding protein (G) to engage host receptors ephrinB2 and/or ephrinB3, while the fusion protein (F) drives membrane fusion leading to virus entry and cell-cell fusion. Interferon-inducible transmembrane (IFITM) proteins restrict the infection of many unrelated viruses at virus entry. We show that the knockdown of IFITM1 enhances HNV entry and cell-cell fusion in both human epithelial and endothelial cells, while overexpression of IFITM1 inhibits both. Using single-molecule localization microscopy, we observed that IFITM1 forms nanoclusters on the plasma membrane that are enhanced upon interferon stimulation. IFITM1 clusters spatially co-occur with GM1-enriched, raft-like membrane domains. Notably, IFITM1 interacts with ephrinB2, and redistributes ephrinB2 into larger and denser clusters, potentially within GM1-enriched regions. Using single-particle tracking, we further show that ephrinB2s lateral diffusion on the plasma membrane is confined by IFITM1, and this confinement is not reversed by amphotericin B, a membrane-permeabilizing agent that increases membrane fluidity. Our data suggest that IFITM1 sequesters ephrinB2 in fusion-unfavorable membrane domains, thereby enhancing the energy barrier for virus-cell membrane fusion and decreasing the virus-receptor encounters. SignificanceNipah (NiV) and Hendra (HeV) viruses are zoonotic paramyxoviruses that cause fatal encephalitis in humans. Here, we show that IFITM1 inhibits NiV and HeV entry at the surface of epithelial and endothelial cells. We report that IFITM1 restricts NiV entry by sequestering the host receptor ephrinB2 in membrane domains that are energetically unfavorable for virus-cell membrane fusion. IFITM1 also restricts ephrinB2 lateral diffusion on the plasma membrane, thereby reducing productive virus-receptor encounters. Notably, amphotericin B treatment, which increases membrane fluidity, did not rescue IFITM1-mediated confinement of ephrinB2 or restore NiV entry. Our data reveal a new mechanism by which IFITM1 restricts NiV infection, suggesting that its antiviral activity extends beyond simply altering membrane fluidity.

microbiology↗