Biology subjects

Deng, Y.

Publications and source records attributed to Deng, Y..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

A Pan-pangenome illuminates complex structural variation and selection in humans, chimpanzees, and bonobos

Complete, haplotype-resolved genome assemblies have provided unprecedented insight into the evolution of structurally complex, rapidly evolving regions of human genomes1-6; however, population-scale pangenome resources of our closest relatives, chimpanzees and bonobos (genus, Pan), are necessary to ascertain the origins and evolutionary context of these loci. Here, we sequence and assemble 58 haplotypes from four distinct Pan clades to high contiguity (median contig NG50=54 Mb), including eight near-T2T genomes. These genomes reveal previously intractable genetic variation increasing estimates of genome-wide genetic diversity 6-37% across populations compared to short-read estimates7. We identify recurrent structural polymorphisms across species impacting genes associated with immune response and host-pathogen interaction and find that structural variants (SVs) are 170- to 260-fold more likely than single nucleotide variants (SNVs) to exhibit high-impact effects across species. Contrasting SV patterns across primates we find that transposable element mutation rates differ by as much as threefold between species. We show that human disease-associated short tandem repeat (TR) loci have uniquely expanded in humans sensitizing our species to these TR-expansion disorders. Physically phased haplotypes enable reconstruction of genome-wide genealogical histories, uncovering ancient, functional genetic variation maintained by balancing selection, as well as signatures of recent adaptation in chimpanzee subspecies. Several malaria-associated loci exhibit ancient structural polymorphism, including the African great ape-specific glycophorin (GYP) gene expansion. We characterize the sequence, structure, and composition of diverse glycophorin haplotypes in humans and chimpanzees. We identify independent malaria-protective GYPA-B fusion events in humans and novel chimpanzee glycophorin genes resulting from both ancient and recent fusion events demonstrating parallel adaptations to pathogen resistance across hominins. Together, our resource highlights the critical importance of nonhuman primate population-scale pangenomics for understanding the evolution of complex genome structures and the biodiversity of our endangered closest living relatives.

evolutionary biology↗

bioRxiv2026

Inhibition benefits neural system identification

Neural system identification approaches use empirical data to fit the stimulus-response functions of neurons. Augmented by deep neural networks, such models have achieved high predictive performance and allow to perform in silico experiments to test hypotheses. Yet, many of these methods ignore common features in visual systems, such as inhibitory interactions between neurons, which are essential for nonlinear neural computation. Here, we incorporate inhibition as an inductive bias into a deep model for neural prediction and investigate the influence of inhibition on the learned transfer functions. To this end, we employ difference-of-Gaussian (subtraction) and within-channel divisive normalization (division), which have been proposed to relate inhibition to neural processing, in deep networks for predicting visual responses. We observe that incorporating such operations maintains the predictive performance and encourages the learning of biologically plausible kernels reminiscent of neural representation in early vision. Additionally, our in silico experiments demonstrate that implementing either sub-tractive or divisive operation benefits the learning of surround suppression but not cross-orientation inhibition. Interestingly, while division increases the sparsity of activation and reduces the sparsity of weights, subtraction has the reverse effect.

neuroscience↗

bioRxiv2026

Vision-Based Genomic Model for Copy Number Variant Pathogenicity Prediction

Copy number variants (CNVs) are a major class of structural genomic alterations underlying rare disease, including neurodevelopmental delay and intellectual disability, yet predicting their pathogenicity remains challenging. Existing methods reduce CNVs to region-level numerical features, discarding the positional structure and cross-track patterns that expert clinical reviewers use to interpret genomic evidence. To address this, we introduce TO_SCPLOWESSERACTC_SCPLOW for CNV, a track-based spatial representation for CNV pathogenicity prediction, which represents each variant as a base-pair-resolution multi-track image and models spatial genomic patterns across annotation tracks while preserving positional structure and cross-track dependencies. Trained on a chromosome-level hold-out split of the ClinVar dataset, TO_SCPLOWESSERACTC_SCPLOW outperforms prior methods on held-out and curated noncoding benchmarks, improving AUROC by up to 0.10 over the state-of-the-art baseline. On the independent DECIPHER cohort, the model demonstrates generalizability by maintaining the highest AUROC and the highest F1 score across baselines. Furthermore, our model localizes pathogenic signals to clinically meaningful genomic subregions, providing track-annotated evidence that supports practical clinical interpretation.

bioinformatics↗

bioRxiv2026

Neutrophil migration in the lung is altered by alveolar collapse and stretch

RationaleHeterogeneous alveolar collapse is prevalent in inflammatory lung conditions such as chronic obstructive pulmonary disease, acute respiratory distress syndrome, and pneumonia. Although neutrophil-released proteases contribute to the tissue remodeling that leads to alveolar collapse, how this altered mechanical environment in turn affects neutrophil migration remains largely unexplored. ObjectivesIn this study, we investigate how alveolar collapse and stretch influence neutrophil migration and identify the mechanical and biochemical factors that govern regional migration differences. MethodsWe developed a novel precision-cut lung slice platform that generates collapsed vs non-collapsed regions within the same slice. Neutrophils in both regions were longitudinally imaged for up to 5 hours to quantify motility behavior. Migration mechanisms were probed using migration-related inhibitors, collagenase, and cigarette smoke extract. A crystal ribcage system, which preserves intact alveolar shape and the air-liquid interface, was also used to assess the effects of ventilation on neutrophil migration. ResultsNeutrophil migration was faster in the collapsed region compared to not-collapsed regions. This regional difference was eliminated by Rho-associated protein kinase (ROCK) inhibition, which selectively increased migration speed in the non-collapsed region. The regional difference persisted with the addition of collagenase and cigarette smoke extract, both of which significantly increased the migration speed in both regions. In the crystal ribcage, the preserved air-liquid interface and ventilation together enhanced neutrophil migration compared with a collapsed lung. ConclusionsAlveolar collapse and stretch facilitate neutrophil migration, indicating the role of localized tissue remodeling in driving neutrophil activity and further disease progression.

bioengineering↗

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

A de novo CO2 Reductase Featuring a Cysteine-Ligated Cobalt Porphyrin Cofactor

Modern protein design methods based on deep learning allow generation of customized protein scaffolds with diverse geometries and functionalities. Here, we capitalize on these recent advances to develop hyper-thermostable de novo CO2 reductases featuring a cobalt porphyrin IX cofactor (CoPPIX). CoPPIX containing enzymes were assembled in vivo through media supplementation with cobalt salts and assessed for photocatalytic CO2 reductase activity. We identified two cysteine-ligated designs that exhibit high activity (>1000 turnovers at rates of up to 25 min-1) while suppressing competing hydrogen evolution pathways. A 2.1 [A] crystal structure shows close agreement to the design model with the Co-Cys bond programmed as intended. This study showcases the power of computational protein design in developing artificial enzymes to activate challenging molecules such as CO2.

biochemistry↗

bioRxiv2026

Advancing ab initio genome annotation with OrionGeno

The rapid expansion of eukaryotic genome sequencing has created an urgent demand for accurate and scalable genome annotation. Existing ab initio methods often struggle to reconstruct complex gene architectures and generalize across distant lineages, limiting their use for large-scale annotation. Here we present OrionGeno, a phylogeny-aware deep learning model for end-to-end eukaryotic genome annotation. OrionGeno integrates phylogenetic context, long-range sequence modeling and joint prediction of gene structures and repetitive elements to annotate exons, introns, untranslated regions and repeats directly from genomic sequences. Applied to chromosome-level eukaryotic genomes from NCBI that lack annotations, OrionGeno generates annotations for more than 5,300 genomes, substantially expanding public annotation resources. Across diverse eukaryotic lineages, OrionGeno outperforms state-of-the-art methods at the exon, gene, protein-sequence, and protein-structural levels. It also identifies candidate protein-coding loci absent from reference protein-coding annotations in well-curated genomes. Together with a web platform and integrated annotation database, OrionGeno provides a scalable and accessible framework for translating genome assemblies into functional biological resources and supporting large-scale biodiversity initiatives such as the Earth BioGenome Project.

bioinformatics↗

bioRxiv2026

OmicGlaze: Spatial Multi-Omic Mapping of Traumatic Brain Injury

Traumatic brain injury (TBI) is a major cause of mortality and long-term disability worldwide, giving rise to complex neurological complications that impact millions of individuals each year. Cellular stress and neuronal injury vary dramatically across cortical layers, vascular niches, and between the ipsilateral (injured) or contralateral (uninjured) hemispheres. There is a critical need for quantitative measures that capture the spatial distribution of injury-induced cellular changes, as well as the gene regulatory elements that drive them. Here, we developed OmicGlaze, an experimental and computational workflow for systematically profiling the spatial transcriptome and epigenome of mouse brains following mild traumatic brain injury. We established a spatial scoring system, and identified region-specific biological processes post injury, including changes in neuronal activities, cellular stress, immune response, and gliosis. Spatial assay for transposase-accessible chromatin with sequencing (Spatial ATAC-seq) generated the first epigenetic map of traumatic brain injury near single-cell resolution. Notably, we identified the Activator Protein-1 family transcription factor Atf3 as a key gene regulator of injury-induced cellular stress. Together, these spatial multi-omics analyses revealed gene regulatory network in TBI and provided a broadly applicable framework for dissecting cellular and molecular mechanisms underlying complex neurological disorders.

systems biology↗

bioRxiv2026

Mirdametinib and abemaciclib cooperate in atypical teratoid rhabdoid tumor to decrease proliferation and suppress tumor growth

Atypical teratoid rhabdoid tumor (ATRT) is a malignant brain tumor of children that has an overall survival of less than 40 percent even with aggressive therapy. We identified upregulation of the mitogen activated protein (MAP) kinase pathway in ATRT. The novel, brain-penetrant MEK inhibitor mirdametinib inhibited the growth of ATRT cell lines in culture at nanomolar concentrations. Mirdametinib suppressed proliferation as measured by BrdU incorporation and induced apoptosis as measured by cPARP and Annexin V staining. Monotherapy with mirdametinib extended the life of mice bearing orthotopic xenografts. Combination therapy with the brain-penetrant cyclin dependent kinase 4/6 inhibitor abemaciclib further suppressed growth and BrdU incorporation in ATRT cell lines representing all molecular subgroups. Mirdametinib and abemaciclib combined to extend survival of mice bearing orthotopic ATRT xenografts. In conclusion, mirdametinib has single agent activity against ATRT and combines with abemaciclib to decrease proliferation and extend survival in orthotopic xenograft models of ATRT.

cancer biology↗

bioRxiv2026

Paternal behavior is controlled by preoptic Trpc5 neurons

Male parenting behavior is highly conserved and activated only after offspring are born. Here we show that the behavioral switch from infanticide in virgin male mice to caregiving in wild-type sires is associated with enhanced expression and activation of Transient receptor potential channel 5 (Trpc5) in estrogen receptor (Esr1)-expressing neurons in the hypothalamic medial preoptic area (MPOA). While selective deletion of Trpc5 from Esr1MPOA neurons diminishes paternal behavior in sires, overexpression of Trpc5 in these neurons converts the otherwise infanticidal virgin males to exhibit care to pups. Mechanistically, Trpc5-dependent changes in neuronal excitability underlie fatherhood-associated Esr1MPOA neuron plasticity. Notably, Trpc5 overexpression also enhances escape behavior and elicits exploratory diving behavior, suggesting that these neurons control a broader adaptive parenting response in males. These findings establish a Trpc5-dependent MPOA neural signal as a critical regulator of paternal behavior.

neuroscience↗

bioRxiv2026

HMA proteins produce 2',3'-cNMP signaling molecules and activate CNL-mediated immunity in rice

Plants deploy a sensor repertoire, usually NLRs, to perceive pathogen effectors and activate executor NLR-triggered immunity. Here we reveal that rice HMA proteins function as sensors detecting the Magnaporthe oryzae MAX effector AvrPigm to trigger broad-spectrum blast resistance mediated by the CNL PigmR. AvrPigm is conserved with multiple copies in blast genomes and targets HMA proteins, facilitating HMA translocation into the cytoplasm. Cryo-EM structure of the HPP04HMA reveals a filament-like oligomer with ssDNA/RNA bound inside the filament, which display cyclic nucleotide synthase activity to generate 2',3'-cNMP in a CNL-dependent manner. We further discovered that the LRR domains of the executor CNLs perceive 2',3'-cNMP to mount immunity. Our study thus establishes an unrecognized immunity mode with a distinct repertoire of sensor receptors that produce signaling molecules that are perceived by the LRR domains of executor NLRs to mediate immunity, shedding new light on the sensor-executor conception and immune activation in plants. HighlightsO_LIHMA proteins and CNL receptors form a new sensor-executor mode in plant immunity C_LIO_LICryo-EM reveals the filament-like structure of HMA-ssRNA/ssDNA C_LIO_LIHMA proteins are cyclic nucleotide synthetases to generate 2',3'-cNMP C_LIO_LILRR domains of CNLs perceive 2',3'-cNMP to mediate immunity C_LI

plant biology↗

bioRxiv2026

Toward Computationally Complete Spatial Omics

Multimodal spatial omics has transformed biology by mapping molecular complexity within intact tissues, yet current technologies remain limited in the number of modalities measured simultaneously and often produce lower-quality data than single-modality assays. We present COSIE, a computational framework that generates high-resolution, multilayered molecular landscapes across tissue sections, individuals, and platforms. COSIE integrates histology, epigenome, transcriptome, proteome, and metabolome into a unified representation. Applied to 12 datasets spanning 10 spatial technologies, eight modalities, and nine tissue types, ranging from thousands of spots to millions of cells, COSIE outperforms existing methods. It resolves tissue structures, enhances noisy measurements, predicts unmeasured modalities, and captures dynamic processes. In human tumors, COSIE identifies invasive subregions linked to clinical outcomes and predicts spatial gene expression in TCGA samples using only histology images. By transforming fragmented data into comprehensive spatial maps, COSIE advances computationally complete spatial omics and the creation of digital tissue twins for biomedicine.

genomics↗

bioRxiv2026

A human gut-BBB-brain microphysiological model for studying neurodegenerative diseases

The gut-brain axis has emerged as a crucial factor in neurodegeneration, with growing evidence linking gut dysbiosis and metabolic dysfunction to Alzheimers disease (AD) progression. Unfortunately, the lack of human-relevant in vitro models limits our ability to effectively explore the mechanism of this axis. To address this gap, we have developed a human induced pluripotent stem cell (iPSC)-derived gut-blood-brain barrier (BBB)-brain microphysiological system that enables systematic investigation of gut-brain interaction in the context of AD under controlled conditions. Our findings reveal that the interaction between gut and brain organoids can promote the maturation of brain organoids, making them more similar to their physiological characteristics in vivo. Additionally, co-culture gut and brain organoids better recapitulates the pathological features of AD. We also discovered that gut organoids of AD can trigger neurodegenerative disease manifestations in healthy brain organoids. In summary, our microphysiological system provides a novel and versatile in vitro platform for studying the interaction between the gut and brain in neurodegenerative diseases.

neuroscience↗

bioRxiv2026

DRP1 inhibition confers cardioprotection against doxorubicin while preserving anticancer efficacy

BackgroundAnthracyclines such as doxorubicin are effective chemotherapeutics but are limited by cardiotoxicity driven in part by mitochondrial dysfunction. Dysregulated mitochondrial dynamics, particularly excessive dynamin-related protein-1 (Drp1)-mediated fission, contribute to doxorubicin-induced cardiac injury and support selective survival of cancer cells. ObjectivesTo determine whether DRP1i2, a novel small molecule Drp1 inhibitor targeting a conserved domain shared between human and mouse, can function as a cardio-oncology therapeutic by reducing doxorubicin-induced cardiotoxicity while maintaining or enhancing anti-cancer efficacy. MethodsCardioprotective effects of DRP1i2 were evaluated in a murine model of chronic doxorubicin cardiotoxicity and in human induced pluripotent stem cell-derived cardiac microtissues exposed to acute doxorubicin injury. Anticancer activity was assessed across multiple cancer cell lines using 2D monolayers and 3D microtissues. ResultsIn vivo, DRP1i2 preserved left ventricular ejection fraction, reduced interstitial fibrosis and cardiomyocyte atrophy, and attenuated doxorubicin-induced myocardial proteomic remodelling. In human cardiac microtissues, DRP1i2 improved viability and restored contractile function despite persistent mitochondrial oxidative stress. DRP1i2 showed modest anticancer activity in MG63 osteosarcoma cells in both 2D and 3D systems and did not diminish doxorubicin efficacy in other cancer models (MDA-MB-231 breast, OVCAR3 ovarian, and A549 lung adenocarcinoma). Combined treatment further enhanced cytotoxicity selectively in MG63 cells. ConclusionsDRP1i2 exerts complementary cardioprotective and anticancer actions through modulation of shared mitochondrial pathways, identifying Drp1 as a druggable target in cardio-oncology. These findings support DRP1i2 as a first-in-class Drp1 inhibitor and highlight mitochondrial dynamics as a promising therapeutic axis to preserve anthracycline efficacy while reducing cardiotoxicity. Clinical PerspectivesExcessive Drp1-mediated mitochondrial fission links anthracycline cardiotoxicity with cancer cell survival. Inhibition with DRP1i2 preserved cardiac structure and function in a chronic doxorubicin cardiotoxicity model without compromising anti-cancer activity, representing mechanism-based cardioprotection, where the heart is protected by directly targeting the molecular processes driving injury. Translation will require pharmacologic profiling and testing in tumour-bearing and comorbid models, followed by early-phase trials to confirm safety and efficacy.

pharmacology and toxicology↗

bioRxiv2026

Prophylactic Lipoxin A4 Attenuates Clostridioides difficile Infection by Augmenting Epithelial Barrier and Resolving Inflammation

Clostridioides difficile infection (CDI) is a leading healthcare-associated diarrhea with high recurrence rates, partially due to antibiotic-induced dysbiosis and dysregulated host inflammation. Specialized pro-resolving mediators (SPMs), such as Lipoxin A4 (LXA4), offer promise in controlling excessive inflammation and promoting tissue repair, yet their role in CDI remains unexplored. Here, we developed a compact, gas-tight gut-on-a-chip (GOC) system that reconciles the anaerobic requirements of C. difficile with the oxic needs of human intestinal epithelium, enabling physiologically relevant co-culture within a standard incubator. A CDI in vitro model was established based on this GOC system. Using the model, we demonstrated that prophylactic administration of LXA4 significantly preserved epithelial barrier integrity, attenuated pro-inflammatory cytokine secretion (IL-8 and IFN-{gamma}), and reduced bacterial colonization. Transcriptomic analysis revealed that LXA4 pretreatment upregulated genes involved in cell junction organization while downregulated immune activation pathways. These protective effects were validated in a murine CDI model, where LXA4 pretreatment reduced weight loss, pathological damage, and fecal bacterial burden. Furthermore, prophylactic administration of LXA4 synergized with vancomycin treatment further enhanced antibiotic efficacy while allowing a 50% dose reduction without compromising therapeutic outcomes. Our study establishes a robust approach for CDI research and highlights the prophylactic and adjuvant potential of inflammation-resolving strategies, offering a novel approach to mitigate CDI incidence and improve treatment outcomes.

bioengineering↗

bioRxiv2026

Antibiotic exposure dynamically generates a substantial number of heterogeneous persisters along a spectrum of tolerance

Antibiotics are known to induce new persister cells during treatment, yet the inability to distinguish and quantify pre-existing versus drug-induced persisters has long obscured how antibiotics and genes shape persistence. Here, we develop a quantitative framework integrating kinetic modeling with serial-dilution time-kill (SDTK) assays to resolve persister population dynamics and accurately quantify both persister types. We show that antibiotic exposure dynamically generates a substantial number of persisters that are heterogeneous and distributed along a persistence spectrum. Across antibiotics, we uncover pronounced differences in rates of persister induction and elimination, with ampicillin inducing persisters at the highest rate and kanamycin at the lowest. Depending on dilution history, drug-induced persisters can dominate the persister pool. Our framework enables identification of genetic determinants specific to pre-existing and/or drug-induced persistence and reveals drug-dependent pre-existing persister fractions. Systematic sequential-drug treatments demonstrate that kanamycin persisters form the most tolerant subset, embedded within ciprofloxacin persisters that in turn are nested within the broader ampicillin persister subpopulation. Together, we propose a Drug-Induced Persistence-Spectrum (DIPS) model in which antibiotics differentially induce and select for persister subsets along a tolerance continuum.

microbiology↗

bioRxiv2026

Spatial pharmaco-multiomics reveals drug distribution, metabolic niches, and spatially constrained resistance in medulloblastoma

Single-cell and spatial transcriptomic studies have provided insights into the developmental origins and intratumoural heterogeneity of SHH medulloblastoma (SHH-MB) and suggested how targeted drugs such as CDK4/6 inhibitors remodel tumour ecosystems, yet the interplay between local drug exposure, metabolism, cell state, and drug resistance remains poorly understood. Here we developed a same-section spatial pharmaco-multiomics framework that integrates MALDI-MSI-based spatial metabolomics with Visium whole-transcriptome profiling and high-resolution Xenium imaging to map palbociclib distribution, metabolite landscapes, and transcriptional programs within the same histological contexts of an SHH-MB PDOX model and primary human tumours. Palbociclib-rich tumour bulk exhibited broad suppression of E2F-driven proliferation and a shift toward neuronal differentiation, corroborating and extending prior findings. In contrast, drug-poor tumour-brain interfaces and perivascular regions retained E2F-high proliferative states and were enriched for mesenchymal-like stromal cells and ECM-remodelling genes, indicating anatomically constrained reservoirs of tolerance. Spatial metabolomics linked these interface niches to ganglioside (GM2) and sphingomyelin enrichment, while differentiated, drug-exposed regions displayed phosphatidylcholine, phosphatidic-acid signatures consistent with neuronal maturation. Integrated pathway analysis further revealed a "mitochondrial tuning" program, with upregulation of histidine, folate/one-carbon, CoA, and lipoate metabolism with redox and oxidative-phosphorylation support. These signatures were specific to therapy-exposed border cells. Rare palbociclib-positive, E2F-high resistant spots additionally exhibited mitotic checkpoint and DNA-repair signatures, implying a drug-induced resistance axis independent of scarcity. Together, our study provides a generalisable same-section spatial pharmaco-multiomics pipeline and a spatially resolved model of CDK4/6 response, nominating interface-focused metabolic and cell-intrinsic vulnerabilities for combination therapy.

cancer biology↗

bioRxiv2026

THIK-1 channel mediates microglial glucose sensing and modulates AgRP neurons

Microglia play essential roles in maintaining energy homeostasis, and their dysfunction contributes to metabolic disease. Although high-fat diet (HFD) exposure induces microglial activation, the underlying mechanisms remain poorly defined. Here, we identified a previously unrecognized role for THIK-1 channel in mediating glucose sensing of microglia in arcuate nucleus of the hypothalamus (ARH), during HFD-induced obesity. Pharmacological inhibition of THIK-1 channel with tetrapentylammonium (TPA) suppresses feeding and attenuates body-weight gain in diet induced obese mice. Mechanistically, inhibition of agouti-related peptide (AgRP) neurons is indispensable for TPA-induced hypophagia. Moreover, THIK-1 inhibition promotes microglial phagocytosis of perineuronal nets (PNNs), leading to reduced AgRP neuronal activity and feeding suppression. Together, these findings establish THIK-1 as a critical glucose sensor in hypothalamic microglia and uncover a microglia-dependent pathway through which overnutrition modulates AgRP neuronal activity via PNN remodeling to regulate energy balance, highlighting THIK-1 as a potential therapeutic target for treatment of diet-induced obesity.

neuroscience↗