Biology subjects

Gu, C.

Publications and source records attributed to Gu, C..

At least 19 recordsLinked to original sources

bioRxiv2026

SubcellPert: Benchmarking Subcellular Perturbation Prediction

Perturbations change both RNA abundance and intracellular organization, but gene-count predictors omit the positions needed to model spatial responses. To address this limitation, we introduce \textbf{\textit{SubcellPert}}, a benchmark for perturbation-response prediction at single-RNA-molecule resolution. It comprises 14 imaging datasets with 13.88 million cells and 3.65 billion RNA molecules. Given source observations and a directed condition change, models generate target RNA populations in normalized two-dimensional coordinates. Two independently trained tasks separate abundance from localization: \textit{Oracle} predicts coordinates given exact target counts; \textit{Joint} predicts both. Eight baselines span source resampling, classical transport, and frozen foundation-model adapters. Fixed perturbation and cellular-context holdouts evaluate abundance error, target-gene coverage, and conditional spatial error. Through within-dataset analyses, we find context-dependent gains from spatial features in condition decoding. Interpreting spatial responses requires distinguishing changes within spatial clusters from population composition, and RNA fractions from enrichment relative to compartment geometry. Through comprehensive experiments, we find that Gaussian transport achieves the lowest Oracle spatial error on eight of eleven cellular-context OOD datasets. Audits show that better centroid accuracy can accompany worse radial distributions, and that 19 of 190 Joint adapter fits retain source counts after validation. SubcellPert opens a spatial frontier for virtual cell research, laying the groundwork for predictive models that capture both the molecular composition and intracellular organization of cellular responses. The code is available at \url{https://github.com/king159/SubcellPert}.

bioinformatics↗

bioRxiv2026

Host soluble inositol phosphate signaling promotes coronavirus replication

Coronaviruses rely extensively on host pathways for replication, making host-directed therapies an attractive strategy for broad-spectrum antivirals with reduced risk of viral resistance. Here we identify the host soluble inositol phosphate pathway as a previously unrecognized dependency for coronavirus infection. Genetic or pharmacologic inhibition of several kinases in this pathway markedly suppresses replication of both alpha- and betacoronaviruses, while increasing pathway activity promotes viral replication. We developed UNC7844, a potent multi-target inhibitor of these kinases, which reduces coronavirus replication by more than four orders of magnitude in cultured cells and suppresses coronavirus infection in mice. Mechanistically, UNC7844 suppresses inositol (pyro)phosphates production, disrupts phosphoinositide homeostasis, and impairs late endosomal dynamics, blocking early post-entry steps required for viral genome release and replication. Together, our findings establish the soluble inositol (pyro)phosphate pathway as an important regulator of coronavirus infection and highlight its inhibition as a promising host-directed antiviral strategy.

microbiology↗

bioRxiv2026

Evolutionary constraints limit additional mammalian adaptation of bovine-derived H5N1 influenza viruses in ferrets

The outbreak of clade 2.3.4.4b H5N1 viruses among U.S. dairy cattle has raised concerns that sustained circulation among agricultural mammals could facilitate viral adaptation toward efficient human transmission. However, the evolutionary dynamics governing such adaptation remain poorly understood. Here we investigated the evolution of two bovine-derived H5N1 B3.13 genotype viruses during infection and airborne transmission in ferrets, building on prior characterization of their robust replication and inefficient airborne transmission. Within hosts, viral genetic diversity was limited and viruses were subject to genetic drift and weak purifying selection. Transmission, when it occurred, was characterized by stringent bottlenecks that sharply reduced viral genetic diversity. We found no evidence of mammalian adaptation during infection or transmission. Together, these findings indicate that bovine-derived H5N1 viruses face evolutionary constraints during acute mammalian infection and transmission, limiting movement toward enhanced airborne spread. These constraints may help explain why efficient mammalian replication does not necessarily coincide with efficient transmission. Continued circulation of HA clade 2.3.4.4b viruses nevertheless creates repeated opportunities for rare but consequential evolutionary events, underscoring the importance of sustained surveillance and risk mitigation.

microbiology↗

bioRxiv2026

Spatial distribution of blood-brain barrier membrane proteins is controlled by sorting motifs and physiological signals in vivo

The blood-brain barrier (BBB), formed by brain endothelial cells (BECs), creates a safe and homeostatic environment for proper brain function. Together with pericytes and astrocytes, the BBB controls substance influx and efflux into and out of the brain. While BECs are extraordinarily thin, their luminal and abluminal plasma membranes face markedly different environments: the blood and brain parenchyma, respectively. How BBB membrane proteins are spatially distributed between these membranes and the factors regulating their localization are not clear. Here, we establish a method for measuring polarized protein sorting at the BBB in vivo. We characterize the distribution of transporters and receptors on the luminal and abluminal plasma membranes and identify protein-intrinsic motifs that control polarized sorting. Finally, we observe a change in membrane protein distribution that aligns with circadian rhythms, revealing an under-appreciated dimension of BBB dynamics. This method can be broadly used for evaluating membrane protein landscape changes during development and disease and for choosing optimal molecular targets for BBB-crossing therapeutics.

cell biology↗

bioRxiv2026

ActSeekN: A Structural-Motif-Based Pipeline for Interpretable Enzyme Function Annotation

Accurate enzyme function annotation remains a major bottleneck in genome analysis despite the rapid expansion of available protein sequence and structure data. Most existing methods rely on sequence similarity or machine-learning representations, which often perform poorly for proteins with low sequence identity or convergent evolutionary histories. Because enzymatic activity is determined by the three-dimensional arrangement of catalytic and binding-site residues, structure-based approaches offer a mechanistically grounded alternative. However, their broader application has been constrained by the limited size and coverage of curated active-site reference databases. To address this challenge, we developed ActSeekN, a structural-motif-based functional annotation pipeline that combines the ActSeek active-site search algorithm with a newly constructed large-scale reference database derived from AlphaFold-predicted structures, UniProt annotations, and curated catalytic residue information. This framework enables rapid and scalable identification of conserved catalytic motifs across structurally related proteins, allowing function to be transferred on the basis of local three-dimensional catalytic geometry rather than global sequence similarity. In this way, ActSeekN overcomes a central limitation of previous structure-based methods by expanding the searchable space of catalytic motifs while retaining mechanistic interpretability. Benchmarking against state-of-the-art machine-learning approaches demonstrates competitive or superior performance. Applications to yeast, human, and Trichoderma reesei proteomes refine existing annotations, complete partial EC assignments, and identify previously unrecognized enzymatic functions, highlighting ActSeekN as a powerful tool for genome annotation and biotechnology. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=99 SRC="FIGDIR/small/720574v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@f5da16org.highwire.dtl.DTLVardef@c0faa4org.highwire.dtl.DTLVardef@18765fforg.highwire.dtl.DTLVardef@3960b9_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2026

nELAVL phosphorylation by CDKL5 regulates inter-condensates composition and communication to promote experience-dependent maturation of the visual cortex

Mutations in Cyclin-Dependent Kinase-Like 5 (CDKL5) cause CDKL5 deficiency disorder (CDD), an X-linked neurodevelopmental condition. Through a phosphoproteomic screen, we identified the neuron-specific nELAVL family of RNA-binding proteins as direct activity-dependent substrates of CDKL5. In support of this regulatory axis, single-nuclei transcriptomics of Cdkl5 knockout (KO) cortices revealed an enriched reduction in activity-dependent mRNAs. Mechanistically, we show that nELAVL proteins undergo phase separation to form biomolecular condensates, the size of which is gated by CDKL5 phosphorylation. Loss of CDKL5 leads to enlarged nELAVL condensates, which exhibit reduced binding affinity for the target mRNA Fos, resulting in its accelerated degradation. This disruption extends to inter-condensate communication: phosphodeficient nELAVL show diminished interaction with P-bodies, which themselves become enlarged in CDD mutant iNeurons. Functionally, the absence of nELAVL phosphorylation recapitulates the deficits in experience-dependent visual function observed in Cdkl5 KO mice. Our findings establish a critical molecular mechanism by which CDKL5-mediated phosphorylation governs mRNA metabolism by tuning the properties of nELAVL condensates and their communication with other biomolecular condensates, ultimately promoting experience-dependent maturation of the visual cortex.

neuroscience↗

bioRxiv2026

Immune reprogramming of 3D tumor models via optoporation-mediatedtargeted gene delivery to macrophages

The dynamics of the tumor microenvironment (TME) are a key determinant of cancer progression and therapeutic resistance through complex interactions between tumor, stromal and immune cell populations. Among these, tumor-associated macrophages (TAMs) play a central role in promoting tumor growth and immune suppression. However, the specific contributions of TAMs remain poorly understood due to the lack of tools enabling selective genetic manipulation in three-dimensional (3D) tumor models. Here, we present a gold nanoparticle-assisted optoporation approach that enables spatially selective plasmid-based gene delivery to TAMs within intact heterocellular 3D pancreatic ductal adenocarcinoma (PDAC) spheroids, thereby modulating the TME. In two-dimensional (2D) TAM cultures, conventional transfection of IRF5- and IKBKB-encoding plasmids validated their capacity to induce TAM repolarization, as evidenced by activation of interferon signaling. Extending this approach to 3D PDAC spheroids, nanoparticle-assisted optoporation achieved selective transfection of TAMs with IRF5- and IKBKB-encoding plasmids by transiently generating nanoscale membrane pores in illuminated cells. TAMs transfection elicited a robust interferon response, marked by transcriptional upregulation of IFNA, IFNB1, and CXCL10, and increased protein levels of IFNB1, IFNL1, and CXCL13, together with downregulation of pro-tumorigenic markers CEACAM5, IL19, and IL32. These coordinated changes indicate a shift towards an anti-tumorigenic TME. By enabling minimally invasive, TAM-specific gene delivery in complex multicellular 3D spheroids, this strategy allows precise modulation of the TME and opens new avenues for modeling its dynamics in cancer progression and therapeutic response.

bioengineering↗

bioRxiv2026

MANF Clears Mutant Uromodulin in Human Kidney Organoids of Autosomal Dominant Tubulointerstitial Kidney Disease

Autosomal dominant tubulointerstitial kidney disease due to uromodulin mutations (ADTKD-UMOD) is one of the leading hereditary kidney diseases. Currently there is no targeted treatment. To illuminate human relevance of mesencephalic astrocyte-derived neurotrophic factor (MANF)-based therapy, we have established patient induced pluripotent stem cell (iPSC)-derived kidney organoid model carrying UMOD p.H177-R185del, the leading mutation causing ADTKD. We have discovered that MANF can directly bind and repress ER calcium release channel IP3R1, thus enhancing AMPK-induced autophagy in a TRIB3-dependent manner. The therapeutic implication of this finding may well be extended to other protein misfolding diseases.

genetics↗

bioRxiv2026

Circadian-Modulated Thresholds as a Mechanistic Basis for Sleep-Wake Transitions, Recovery, and Sleepiness

Human sleep-wake cycles arise from the interplay between homeostatic sleep pressure and circadian rhythms, yet the underlying mechanistic basis by which these drives jointly govern state transitions, recovery from sleep loss, and subjective sleepiness remains unclear. Here, we use the extended Phillips-Robinson model incorporating circadian excitation of orexin and locus coeruleus populations, yielding analytically tractable, circadian-modulated thresholds for sleep onset and awakening, and delineating the roles of circadian and homeostatic drives. We show that homeostatic feedback alone generates intrinsic sleep-wake oscillations via a saddle-node on invariant circle bifurcation, while circadian drive reshapes the stability landscape to account for immediate sleep onset and partial first-night recovery after prolonged deprivation, and enables analytic predictions of sleep timing and duration. We further define sleepiness as the distance between the homeostatic state and the active circadian sleep threshold, which robustly predicts subjective sleepiness across various deprivation, restriction, extension, and recovery protocols. Together, these results establish circadian-modulated thresholds as a unifying dynamical principle linking sleep-wake transitions, recovery dynamics, and sleepiness, with implications for circadian misalignment, shift work, and individualized sleep interventions. Author summarySleep and wakefulness arise from the interaction between circadian timing and the gradual accumulation and dissipation of sleep pressure. Although existing computational models have advanced understanding of these processes, most rely on fixed or heuristic rules for switching between sleep and wake states, limiting their ability to explain behavior under sleep deprivation, extension, or restriction. Here, we present a mechanistic description of state switching in which circadian and homeostatic influences act as separable but interacting control dimensions, providing a framework for how circadian modulation shapes state stability, recovery sleep, and subjective sleepiness, without invoking separate mechanisms for normal and perturbed conditions. By recasting sleep regulation in terms of state-dependent dynamical boundaries, our results offer a unified perspective on sleep timing, duration, recovery, and vulnerability to fatigue. This work provides a more physiologically grounded foundation for sleep-wake modeling and a principled basis for understanding circadian misalignment, shift work, jet lag, and other real-world challenges to sleep health.

neuroscience↗

bioRxiv2026

In silico prediction of metabolic trait robustness in microbial cells

In industrial applications, microbial strains undergo notable biomass expansion subjecting them to Darwinian selection. The consequent adaptive evolution may threaten the often tediously developed desired traits of the strains, such as flavor or platform chemical production. Yet, it remains unresolved how to predict the evolutionary trait robustness. Here, we propose TRAEV (Trait Robustness Against EVolution), a computational framework for in silico prediction of evolutionary trajectories and robustness of desired metabolic traits in application environments. TRAEV uses constraint-based metabolic model simulations to predict environment-dependent trait-fitness dependencies and Monte Carlo-based perturbation analysis to account for the stochasticity of adaptive evolution. First, TRAEV predicts the immediate phenotypic adaptation to the new environment, and then, the evolutionary trajectories of fitness and desired trait by sampling enzyme usage changes. From the predicted trajectories, trait robustness is quantified as two scores: Robustness Score (RS) and Trade-off Score (TS). RS and TS are the mean of a normalized desired trait and the mean of the product of normalized changes in the desired trait and in fitness, respectively, over intermediate metabolic states along the evolutionary trajectory. We validated TRAEV by demonstrating that it predicted the relative robustness of heterologous pigmentation of genetically engineered Saccharomyces cerevisiae strains in synthetic defined chemical environments aligned with experimental observations. We then further applied TRAEV to predictively assess the robustness of desired aroma generation trait in a wine must environment by multiple S. cerevisiae strains if they were developed via a laboratory selection process. Thus, we showed how TRAEV predictions could guide such strain development. TRAEV can be integrated into computational strain design workflows across microbial strains, metabolic traits, and application environments. Ultimately, model-predicted evolutionary robustness of desired traits can guide both strain and process development and help avoiding production losses and enhancing the economic attractiveness of industrial applications using microbial cells. Author summaryMicrobial cells developed to express desired traits by genetic engineering or selection processes are used in a wide range of applications, from biotechnological chemical production to food and beverage fermentations. However, when the cells replicate in the application environment the traits are subject to Darwinian selection and consequent adaptive evolution. As a result, desired traits can be rapidly lost. To mitigate such undesired evolutionary changes, we developed TRAEV (Trait Robustness Against EVolution), a computational framework for in silico assessment of evolutionary trajectories and robustness of desired traits in application environments by integrating constraint-based modeling and Monte Carlo-based perturbation analysis methods. We demonstrate the usability of TRAEV by validating its predictions with experimental data on the robustness of heterologous pigmentation of engineered Saccharomyces cerevisiae strains, and applying it to predict the robustness of aroma generation in wine must by multiple S. cerevisiae strains if they were developed by laboratory selection in specific conditions. As being applicable across microbial strains, metabolic traits, and application environments, we believe that TRAEV can help to avoid production losses, and thus, contribute to the development of economically attractive industrial applications using microbial cells.

evolutionary biology↗

bioRxiv2025

Multicolored, Sonosensitizer-optimized Organic Mechanoluminescent Nanoparticles for Functional Sono-optogenetics

Light enables precise visualization and control of cellular processes, but its utility in deep tissues is fundamentally limited by poor optical penetration, particularly in the deep brain. Ultrasound-triggered mechanoluminescence offers a non-invasive strategy for remote light delivery, yet existing organic systems remain monochromatic and low-intensity, largely due to an incomplete understanding of ultrasound-induced emission. Here, we report a multicolor mechanoluminescence platform that couples reactive oxygen species-responsive chemiluminescent donors with fluorescent acceptors via Forster resonance energy transfer, generating tunable emission from blue (459 nm) to red (592 nm). Systematic screening potentially reveals that electronic energy gap-dependent reactive oxygen species generation serves as a predictive design principle for high-performance mechanoluminescent materials. The emitted spectrum and intensity are sufficient to activate ChR2 and ChRmine and inhibit eOPN3, enabling bidirectional, fiber-free neuromodulation under focused ultrasound. By integrating spatially precise ultrasound with programmable photon output, this platform establishes a non-invasive strategy for deep-tissue neural monitoring and provides a foundation for applications in bioimaging, gene editing, and precision therapeutics.

bioengineering↗

bioRxiv2025

Causality-oriented regulatory inference and rational transcriptomic reprogramming design with CASCADE

Systematically elucidating the causal structure of gene expression regulation is the foundation for identifying key regulators of cellular function and designing rational interventions thereof. While advances in high-content perturbation screens enables experimental probing of causal regulatory effects, the massive genomic scale, measurement noise and confounding factors pose significant challenges for existing causal discovery and inference algorithms. Here, we present CASCADE, an end-to-end framework that integrates de novo causal discovery with prior regulatory knowledge for genome-wide causal discovery and inference. In addition to its superior performance on causal regulatory structure discovery and counterfactual inference for unseen perturbation effects, CASCADE enables, for the first time, causality-oriented rational intervention design for transcriptomic programming towards various targeted cells within a unified framework.

bioinformatics↗

bioRxiv2025

The Rise and Fall of SARM1 Base-Exchange Inhibitors

The sterile alpha and TIR motif containing 1 (SARM1) enzyme is a key driver of axonal degeneration in response to injury, making it an attractive target for treating chemotherapy-induced peripheral neuropathy (CIPN) and other nervous system diseases. In this study, we identified and optimised a new class of base-exchange inhibitors (BEXi) targeting SARM1 and explored their molecular interactions and conformational effects using cryo-EM, HDX-MS and SAXS. Although BEXi produced robust inhibition across all biochemical and cellular assay formats, application at sub-inhibitory concentrations consistently led to paradoxical SARM1 activation, and in neuronal assays, accelerated neurite degeneration. Further analysis showed that BEXi only delayed, rather than prevented, neurite degeneration when applied to primary neuronal cells, even at exceedingly high inhibitor concentrations. These results prompted us to discontinue BEXi development in favour of alternative strategies, underscoring the complexity of SARM1 as a therapeutic target and the need for comprehensive, mechanistically informed screening cascades.

neuroscience↗

bioRxiv2025

HaloTrace: A spatiotemporally precise fluorescent readout of blood-brain barrier permeability in mice

The blood-brain barrier (BBB) is an indispensable, selectively permeable interface that controls the entry and exit of nutrients, ions and waste products into the brain. Despite its biological importance, most measurements of BBB permeability rely on dyes that suffer from nonspecific signals, lack of spatial fidelity, and incompatibility with longitudinal or repeated measurements. Here we present HaloTrace: a method which leverages the HaloTag ligand-receptor tool to generate a precise spatiotemporal readout of BBB integrity that avoids major pitfalls of existing methods. We present evidence that the fluorescent HaloTag ligand has minimal interactions with blood contents but can enter the brain specifically at sites of BBB dysfunction, where it covalently binds to nearby HaloTag receptors. The ligand accumulates in the brain during its short lifetime in circulation and is stably anchored in place for at least 24 hours. Unlike existing tracers, free ligand is not retained in the blood vessels at detectable levels, so the entirety of ligand fluorescence represents true BBB leakage. Furthermore, we demonstrate that HaloTrace can quantify BBB permeability at multiple discrete timepoints prior to the experiment endpoint. This offers researchers the ability to study the progression or resolution of BBB permeability in a way current methods cannot. HaloTrace is thus uniquely poised to characterize the spatiotemporal dynamics of BBB leakage in mouse models.

neuroscience↗

bioRxiv2025

A deep reinforcement learning platform for antibiotic discovery

Antimicrobial resistance (AMR) is projected to cause up to 10 million deaths annually by 2050, underscoring the urgent need for new antibiotics. Here we present ApexAmphion, a deep-learning framework for de novo design of antibiotics that couples a 6.4-billion-parameter protein language model with reinforcement learning. The model is first fine-tuned on curated peptide data to capture antimicrobial sequence regularities, then optimised with proximal policy optimization against a composite reward that combines predictions from a learned minimum inhibitory concentration (MIC) classifier with differentiable physicochemical objectives. In vitro evaluation of 100 designed peptides showed low MIC values (nanomolar range in some cases) for all candidates (100% hit rate). Moreover, 99 our of 100 compounds exhibited broad-spectrum antimicrobial activity against at least two clinically relevant bacteria. The lead molecules killed bacteria primarily by potently targeting the cytoplasmic membrane. By unifying generation, scoring and multi-objective optimization with deep reinforcement learning in a single pipeline, our approach rapidly produces diverse, potent candidates, offering a scalable route to peptide antibiotics and a platform for iterative steering toward potency and developability within hours.

molecular biology↗

bioRxiv2025

Physics-based nucleosome-resolution modeling of epigenetic-driven chromatin domain dynamics

Chromatin spatially organizes the Eukaryotic genome to support key cellular processes such as gene regulation, but the interplay between epigenetics, chromatin structure, and function is still poorly understood. We propose a nucleosome-resolution coarse-grained model that captures the essential features of chromatin organization over multiple scales: from nucleosome dynamics to chromatin fiber folding, and liquid-liquid phase separation. The model describes the effects of DNA linker length, histone tail acetylation, linker histone H1, and multi-bromodomain proteins such as BRD4. It is designed to be experimentally accurate but computationally efficient, allowing the study of 100kb genomic regions on a timescale of seconds with moderate resources. We apply this model to explore the structure and dynamics of two active loci of mouse embryonic stem cells, Pou5f1 and Sox2, as determined by solely their underlying epigenetic patterns. Our simulations reveal that chromatin folds into liquid-like domains characterized by similar histone modifications. These domains are highly dynamic, driving the formation of transient contacts between distant cis-regulatory regions. In silico mutation studies further clarify the distinct roles played by histone acetylation, linker histone, and BRD4. Overall, our physics-based modeling provides evidence that, in addition to other well-established mechanisms, epigenetic-dependent nucleosome-nucleosome interactions can play a key role in shaping the functional organization of genomic loci.

biophysics↗

bioRxiv2025

Ketone body driven lipid remodeling supports thermogenic adaptation to fasting

Metabolic adaptation to fasting may have conferred survival advantage to early humans and predicts weight gain caused by overnutrition in modern societies. Fasting suppresses brown adipose tissue (BAT) thermogenesis; however, it is unclear how BAT rewires cellular metabolism to balance between energy conservation and heat generation. Here, we report that BAT in mice under fasting and cold challenge consumed ketone bodies, specifically acetoacetate (AcAc). Ablating liver ketogenesis decreased, while enhancing hepatic AcAc output defended, body temperature in mice facing the dual challenge. Using stable isotope tracing in brown adipocytes in vitro combined with quantitative analysis of metabolic fluxes and lipidomics in BAT from genetic mouse models, we disentangled the two metabolic fates of AcAc - terminal oxidation in the mitochondria and lipid biosynthesis in the cytosol. Notably, AcAc-sourced carbon preferentially supported polyunsaturated fatty acid synthesis in BAT, linking to the positive impact of intermittent fasting on lipid profiles in both mice and humans. Therefore, ketone body utilization by thermogenic adipocytes contributes to metabolic resilience of mammals and can be targeted to optimize benefits of dietary regimens.

physiology↗

bioRxiv2025

Non-redundant roles of the HDAC3 corepressor complex subunits SMRT and NCOR in controlling inflammatory and metabolic macrophage pathways

Transcription factors and coregulators coordinate inflammatory and metabolic pathways in macrophages through epigenetic and transcriptional mechanisms. The HDAC3 corepressor complex plays fundamental roles in these mechanisms, with the homologous subunits SMRT and NCOR being critical for complex assembly and interactions with transcription factors and chromatin. However, the relative contribution of SMRT and NCOR in controlling complex-dependent macrophage pathways remains poorly understood. Here, we assessed their genome-wide roles in mouse macrophage RAW264.7 cells and in bone marrow-derived macrophages. Transcriptome analysis upon corepressor depletion identified six differentially expressed gene clusters. SMRT depletion primarily upregulated inflammation-related pathways, NCOR depletion primarily upregulated metabolism-related pathways. Epigenome analysis revealed that corepressor depletion differentially altered chromatin accessibility and H3K27 acetylation, consistent with transcriptome changes. Cistrome analysis revealed that both corepressors differentially influence each other at chromatin. SMRT uniquely controls the chromatin binding and nuclear localization of NCOR, GPS2 and HDAC3, thus acting as the chromatin anchor for the corepressor complex. Finally, corepressor depletion differentially modulated macrophage reprogramming in response to TLR4, IL4 and LXR signaling. Overall, our study reveals a hitherto underappreciated non-redundant role of SMRT and NCOR in coordinating chromatin accessibility, H3K27 acetylation, enhancer activity and transcription to differentially regulate inflammatory and metabolic macrophage pathways. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/653058v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@1d9f2dforg.highwire.dtl.DTLVardef@1d81386org.highwire.dtl.DTLVardef@e9e536org.highwire.dtl.DTLVardef@1c74c15_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗