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Yang, J.

Publications and source records attributed to Yang, J..

At least 145 records · Page 8Linked to original sources

Towards building a World Model to simulate perturbation-induced cellular dynamics by AlphaCell

Predicting cellular responses to perturbations is crucial for therapeutic discovery, yet experimental screening is severely constrained by the combinatorial vastness of biological space. While computational simulations offer a scalable alternative, current models are limited by the incomplete latent representation----mainly relying on highly variable genes in feature representation; the poor genome-wide reconstruction fidelity; and the ungeneralizable dynamic laws across diverse contexts. Consequently, they fail to mechanistically transfer learned dynamics to unseen cellular contexts. To address these systemic flaws, we introduce AlphaCell, a generative Virtual Cell World Model that unifies genome-wise representation with continuous state transition modeling. AlphaCell achieves three synergistic innovations: (1) Latent Manifold Rectification, processing the full protein-coding transcriptome to construct a differentiable Virtual Cell Space, effectively filtering noise while preserving intrinsic cellular topology; (2) Biological Reality Reconstruction, utilizing a massive, knowledge-rich decoder to translate abstract latent states back into high-fidelity, genome-wide expression profiles; and (3) Universal State Transition, applying Optimal Transport Conditional Flow Matching to model perturbations as continuous, deterministic vector fields. By abstracting perturbation mechanisms into generalized dynamic laws, AlphaCell makes robust prediction of perturbation responses in a compositional generalization scenario and enables zero-shot prediction of cellular dynamics in entirely unseen cellular contexts, providing a foundational engine for cellular-context-generalizable perturbation prediction and perturbation-induced cellular dynamics simulation.

bioinformatics↗

G-screen: Scalable Receptor-Aware Virtual Screening through Flexible Ligand Alignment

Virtual screening has long been a central computational tool for rational ligand discovery, enabling the systematic prioritization of candidate molecules from large chemical libraries. Although docking and related approaches that explicitly account for protein-ligand interactions have been developed and refined over several decades, achieving both reliable protein-aware interaction modeling and computational scalability remains an open challenge, particularly for ultra-large chemical spaces. Ligand-based methods are fast and robust but do not explicitly incorporate protein structure, whereas docking-based approaches model protein-ligand interactions more directly at substantially higher computational cost. Here, we present G-screen, a freely available and scalable protein-aware virtual screening framework designed for cases in which an experimentally determined or predicted reference protein-ligand complex structure is available. Rather than performing computationally intensive full docking with explicit pose sampling and optimization, G-screen rapidly generates alignment-guided pose hypotheses using a flexible global alignment algorithm (G-align). The resulting aligned poses are subsequently evaluated using protein-aware pharmacophore interactions derived from the reference complex, enabling explicit atomic-level interaction analysis while retaining the scalability and robustness of ligand-based alignment methods. Benchmarking on DUD-E, LIT-PCBA, and MUV datasets demonstrates that G-screen achieves competitive discrimination and early enrichment relative to representative ligand-based and docking-based methods, while maintaining millisecond-scale per-molecule runtimes under multi-threaded execution. These results position G-screen as a practical and scalable intermediate strategy between conventional ligand-based virtual screening and computationally intensive docking workflows for efficiently filtering ultra-large chemical libraries when a reference complex structure is available. G-screen and G-align are freely available at https://github.com/seoklab/gscreen and https://github.com/seoklab/galign, respectively. Scientific ContributionWe have developed a scalable virtual screening framework for efficiently filtering ultra-large chemical libraries using a flexible global alignment algorithm combined with protein- aware pharmacophore evaluations and alignment-guided pose hypotheses. Despite explicitly capturing atomic-level interactions, the method remains highly efficient, maintaining millisecond-scale per-molecule runtimes under parallel execution. It achieves competitive discrimination and early enrichment, serving as an intermediate strategy between conventional ligand-based virtual screening and computationally intensive docking while combining the speed of ligand-based approaches with the structural context of traditional docking.

biophysics↗

STCS: A Platform-Agnostic Framework for Cell-Level Reconstruction in Sequencing-Based Spatial Transcriptomics

Sequencing-based spatial transcriptomics technologies, including Visium HD and Stereo-seq, now enable transcriptome-wide profiling at subcellular resolution. However, these platforms generate measurements over spatially barcoded units rather than biologically segmented cells, creating a fundamental bottleneck for cell-centric analysis and interpretation. Robust recon-struction of coherent single-cell transcriptomes from high-density spatial bins remains an unresolved computational challenge. Here we present STCS (Spatial Transcriptomics Cell Segmentation), a platform-agnostic framework that reconstructs cell-level gene expression profiles by integrating nuclei segmentation with a joint transcriptomic-spatial distance model. STCS is governed by two interpretable parameters and incorporates a reference-free parameter selection strategy based on internal stability and spatial coherence metrics, enabling adaptable deployment across tissue types and technologies without requiring matched ground-truth annotations. We benchmark STCS on a Visium HD human lung cancer dataset with matched Xenium-derived cell segmentation, enabling direct cell-level validation, and on high-resolution Stereo-seq mouse brain data to assess cross-platform generalizability. Across multiple evaluation dimensions--including cell-type agreement, spatial organization, gene-expression fidelity, and compositional accuracy--STCS achieves consistent improvements over existing methods while preserving biologically coherent spatial structure. As sequencing-based spatial transcriptomics is rapidly adopted across biomedical research, STCS provides a broadly applicable and open-source solution for reconstructing cell-resolved transcriptomes, facilitating more reliable downstream analyses and cross-platform integration.

bioinformatics↗

Reverse electron transfer at mitochondrial complex I restrains dopaminergic neuron activity to promote early-life sleep in Drosophila

Sleep is especially abundant during early life, yet the cellular mechanisms that maintain elevated juvenile sleep drive remain poorly understood. To identify cell-intrinsic regulators of juvenile sleep, we profiled gene expression in Drosophila dopaminergic neurons (DANs) at different ages and performed a targeted RNAi screen of genes with enriched juvenile expression. We found that the magnitude of mitochondrial complex I (MCI) disruption produced strikingly distinct physiological outcomes. Severe MCI loss-of-function caused profound mitochondrial dysfunction, reduced dopaminergic activity, and locomotor impairment. In contrast, partial MCI inhibition left overall mitochondrial function intact but instead reduced sleep, with disproportionately strong effects on juvenile sleep fragmentation and depth, consistent with a gain of dopaminergic signaling. Multiple genetic manipulations that deplete the reduced coenzyme Q pool (CoQH2) converged on a phenotype of increased dopaminergic activity and wakefulness, indicating that coenzyme Q redox balance itself regulates dopaminergic output. These findings support a model in which CoQH2-driven reverse electron transfer (RET) at MCI restrains dopaminergic arousal. By dissociating mitochondrial redox signaling from catastrophic mitochondrial failure, our work identifies a physiological role for coenzyme Q-dependent signaling in the regulation of neural activity and behavioral state. More broadly, these findings suggest that sleep phenotypes may serve as sensitive indicators of emerging mitochondrial dysfunction and reveal a potential link between the regulation of early-life sleep and later dopaminergic vulnerability.

neuroscience↗

Experimental Time Points Guided Transcriptomic Velocity Inference

Time-series single-cell RNA sequencing enables longitudinal tracking of biological processes, yet cellular trajectory reconstruction informed by experimental time remains challenging. Existing trajectory inference methods either perform de novo reconstruction without leveraging experimental time points, or prioritize transitions between time points while paying less attention to intra-time-point dynamics. To reconcile experimental time points with local precision, we present CellDyc, a semi-supervised learning framework that leverages experimental time-point supervision to reconstruct transcriptomic velocities and recover an intrinsic gene-embedded time. CellDyc consistently outperforms existing approaches in reconstructing cellular trajectories across development, disease, and reprogramming contexts. Biologically, CellDyc provides novel insights, such as resolving temporal heterogeneity in erythroid maturation and quantitatively demonstrating that the immunosuppressive environment delays monocyte differentiation in glioblastoma. CellDyc integrates seamlessly with downstream tools like CellRank and remains robust even when only inferred temporal information is available. Collectively, CellDyc offers a rigorous, data-driven solution for deciphering time-resolved cellular dynamics.

bioinformatics↗

A biofidelic Goat Model of Traumatic Optic Neuropathy with Optic Canal Fracture via Transnasal Endoscopy

Traumatic optic neuropathy (TON) is a major cause of irreversible vision loss following blunt cranial trauma, yet the absence of clinically relevant large animal models that faithfully recapitulate human TON has significantly impeded translational research. Current rodent models do not reproduce optic canal fracture, a key injury mechanism in many patients with TON. Here, we combined high-fidelity finite element analysis (FEA) with iterative engineering to establish a reproducible goat model of TON. We first built a high-resolution human-head finite element model to characterize force transmission to the optic nerve. Across clinically relevant periorbital impacts, stress preferentially concentrated in the intracanalicular segment, reaching a peak force density of approximately 500 N/m2 at 50.6 ms, about fivefold higher than in the intraorbital segment. Simulations further showed that direct optic canal impact reproduced comparable intracanalicular stress with a markedly lower input force: 195 N, compared with 3900 N for periorbital impact. Guided by these insights, we developed transnasal endoscopic impact systems capable of inducing optic canal fractures in goats. TON was confirmed within 24 hours by a characteristic relative afferent pupillary defect (RAPD), and at 1 month post-injury goats (n = 14) exhibited a 10%-20% reduction in ganglion cell complex (GCC) thickness and 40%-65% reductions in flash visual evoked potential (FVEP) and pattern electroretinogram (PERG) amplitude ratios (all P [≤] 0.001), with structural and functional preservation of the fellow eye. This study presents a robust, standardized, and clinically relevant large-animal platform for investigating TON pathophysiology.

neuroscience↗

Trait diversity enhances biomass gains via canopy packing in old-growth but not in disturbed Amazon forests.

The existence of a causal link between biodiversity and forest productivity remains largely unexplored in natural systems, especially in hyper-diverse tropical forests. Canopy packing-- greater crown complementarity, resulting in more densely packed canopies--has recently emerged as a key structural pathway through which diversity influences forest functioning, though evidence remains limited and sometimes contradictory.In this study, we used repeated airborne LiDAR acquisitions and long-term field monitoring from a tropical logging experiment in French Guiana to quantify canopy packing using the Shannon evenness of plant area density (PAD) and assess its role in mediating the relationship between trait diversity and biomass gains in old-growth and disturbed Amazonian forest stands.Our results show that, in undisturbed forests, functionally diverse communities promote greater canopy packing, which in turn enhances biomass gains. However, this effect was absent in previously logged stands, where forest structural diversity did not fully recover even after 40 years. Our findings indicate that logging reduces canopy structural complexity and disrupts the link between species composition, canopy packing, and productivity in these hyper-diverse, hyper-productive ecosystems. Significance StatementIn this study, measurements from repeated airborne LiDAR acquisitions and long-term field monitoring from a tropical logging experiment in the Amazon forest are used to understand the causal link between biodiversity and forest productivity. The study shows that greater crown complementarity mediates diversity-productivity relationships, with functionally diverse communities promoting greater canopy packing, which in turn enhances biomass gains. However, this effect is lost in disturbed forests. These findings are relevant for understand the ecological mechanisms driving forest productivity and tropical forests response to disturbance and for forest carbon management strategies.

ecology↗

A Druggable G Protein Checkpoint in Cholesterol Efflux

Immunometabolic diseases such as obesity, fatty liver, and atherosclerosis arise when lipid-associated macrophages (LAMs) fail to resolve lipid overload via reverse cholesterol transport (RCT), the bodys sole pathway for lipid disposal. How RCT is restrained in disease remains unknown. Integrating systems modeling with human plaque transcriptomes, we identify LAM subpopulations associated with plaque progression and uncover CCDC88A (GIV) as a macrophage-intrinsic checkpoint on RCT. Myeloid-specific GIV deletion in mice reduces aortic plaque burden, mobilizes hepatic and adipose lipid stores and promotes fecal sterol disposal. Mechanistically, GIV sequesters the cholesterol transporter ABCA1 within endomembranes and activates Gi[bullet]{beta}{gamma} signaling to suppress cAMP/PKA-CREB-dependent efflux programs. Pharmacogenomic disruption of this checkpoint reactivates efflux programs. In human plaque-in-a-dish models targeting this pathway restored efflux where statins and {beta}-blockers failed, translating to an estimated [~]98% reduction in plaque-progression risk in outcome modeling. Thus, RCT-restoration represents a macrophage-intrinsic therapeutic paradigm for immunometabolic disease. GRAPHIC ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=199 SRC="FIGDIR/small/705962v2_ufig1.gif" ALT="Figure 1"> View larger version (64K): org.highwire.dtl.DTLVardef@50dd10org.highwire.dtl.DTLVardef@e16d9borg.highwire.dtl.DTLVardef@1e2eaf3org.highwire.dtl.DTLVardef@af29b9_HPS_FORMAT_FIGEXP M_FIG C_FIG eTOC blurbLipid-associated macrophages drive immunometabolic disease. Katkar et al. show that disabling a GIV-dependent G-protein brake restores cholesterol efflux, reverses plaque lipid accumulation, and establishes reverse cholesterol transport as a druggable therapeutic axis. HighlightsO_LIStatins slow but rarely reverse plaque burden, leaving residual risk driven by LAM dysfunction C_LIO_LIGIV (CCDC88A) non-canonically modulates Gi to suppress macrophage cholesterol efflux C_LIO_LIGIV loss or inhibition restores ABCA1 activity via transcriptional and post-translational control C_LIO_LIBlocking GIV[bullet]Gi checkpoint defats LAMs, regresses plaques, and relieves systemic lipid overload C_LIO_LISIdentifies a druggable node that redefines RCT restoration as a therapeutic paradigm in immunometabolic disease C_LI

immunology↗

Doxorubicin-induced Cardiotoxicity is Propagated by Paracrine Signaling through Small Extracellular Vesicles

Cardiovascular disease (CVD) is the leading cause of death in the United States and worldwide. While most of these deaths are the result of chronic heart diseases, some CVDs are induced artificially. Doxorubicin (DOX) is a chemotherapeutic that is commonly used to treat breast cancer which is one of the most common types of cancer in the United States. While DOX is an effective anti-cancer agent, over 10% of treated women show signs of acute cardiotoxicity immediately following treatment, and approximately 2% develop severe cardiotoxicity up to 10 years after the end of treatment. Despite this prevalence, the mechanism by which the onset of this cardiotoxicity occurs over time is not well understood. Here, we show that treatment of cardiac cells with DOX changes the cardiac function and the resulting paracrine signaling profile. Subsequent exposure of healthy cells to these altered paracrine agents can recapitulate the effects of direct DOX exposure in 2D and 3D in vitro models. We suggest that this is the result of an altered paracrine miRNA profile and other paracrine factors that propagate the initial disruption caused by direct DOX exposure. Plasma EV miRNA profiling of blinded patient samples revealed distinct clustering by DOX-cardiotoxicity risk, with high-risk patients exhibiting miRNA signatures similar to those from DOX-treated tissue-engineered models. Pathway analysis of the most distinguishing miRNAs linked them to cardiac homeostasis and cardiotoxicity-related mechanisms, supporting the potential of plasma EV miRNAs as noninvasive biomarkers for early risk stratification and personalized cardioprotective interventions in oncological care, and the targeting of key clusters of miRNAs to enhance both understanding of and intervention strategies for preventing the onset of DOX cardiotoxicity.

bioengineering↗

GP130 Y814 SIGNALING IS REQUIRED FOR THE DYNAMIN-MEDIATED ENDOCYTOSIS, MAPK/P38 ACTIVATION AND PERSISTENCE OF CHRONIC SYSTEMIC INFLAMMATION INDUCED BY HIGH FAT DIET

In chronic inflammatory diseases such as obesity, tissue and cellular homeostasis are disrupted by persistent low-grade inflammation, where one of the most prominent pro-inflammatory cytokines that correlates with age and body mass index (BMI) is IL-6. All members of the IL-6 family of cytokines signal through their obligate co-receptor gp130, in whichsignaling tyrosines on the intracellular portion of gp130 activate multiple downstream pathways such as the canonical STAT and MAPK pathways. However, non-canonical gp130 pathways such as SRC family of kinases (SFKs) signaling have emerged as drivers of cellular stress response. Our recently published mutant mouse model carrying a constitutive inactivation of gp130-Y814 (F814 mice), which impairs SFK activation, exhibited an enhanced resolution of inflammatory responses and improved regenerative outcomes in both acute skin wound healing and post-traumatic osteoarthritis models. The current study was designed to explore whether the gp130-Y814 mutation reduces systemic chronic inflammation and multimorbidity in a high-fat diet (HFD)-induced model and to interrogate the possible downstream cellular mechanisms that are affected. In response to HFD, F814 mice showed significantly reduced systemic and tissue-specific inflammatory responses and protection from obesity-induced bone loss and osteoarthritis compared to wild type (WT) mice. After extensive characterization, the role of gp130-Y814 in monocytes/macrophages appeared to be dispensable, but we discovered that the F814 mutation blunts gp130 receptor internalization, p38/MAPK activation and the release of matrix metalloproteinases (MMPs) in chondrocytes. Finally, we showed that F814 chondrocytes had markedly reduced activation of the SFK-dependent GTPase dynamin 2 (Dyn2) in response to catabolic IL-6 cytokines. Introduction of a dominant-negative Dyn2 mutant into WT chondrocytes phenocopied the effects of the F814 mutation, resulting in attenuated p38/MAPK signaling and reduced MMP activation following stimulation with IL-6 cytokines. This study demonstrates, for the first time, that the Y814 residue is directly implicated in Dyn2-mediated internalization of the gp130 receptor, thereby modulating downstream signaling and contributing to pathological outcomes in chronic inflammatory and degenerative diseases in a cell type-specific manner.

cell biology↗

PhyloSOLID: Robust phylogeny reconstruction from single-cell data despite inherent error and sparsity

While lineage tracing based on somatic mutations in single-cell sequencing data offers a powerful approach to reconstructing cellular histories in vivo, its reliability is fundamentally limited by pervasive technical artifacts--specifically, high error rates and data sparsity. These issues introduce false phylogenetic signals that corrupt tree topology and lead to spurious evolutionary conclusions. To overcome these limitations, we present PhyloSOLID, a phylogenetic algorithm designed to be inherently robust to these data imperfections. PhyloSOLID employs a progressive scaffolding strategy that begins with graph-based construction of a low-resolution, high-confidence backbone tree from reliable and uniformly covered mutations. This scaffold is then refined through the iterative integration of remaining data, guided by a Bayesian statistical model that penalizes phylogenetic inconsistencies to effectively separate the true evolutionary signal from technical artifacts. Benchmarking on both simulated datasets and multiple ground-truth datasets demonstrates that PhyloSOLID achieves superior lineage reconstruction accuracy over existing methods, for both single-cell RNA-seq and DNA-seq data. Additionally, a user-friendly web interface enables customized quality assessment, artifact removal, and interpretation of lineage structures. PhyloSOLID provides a powerful solution for decoding cellular evolution in developmental and disease contexts.

bioinformatics↗

A real-time, multi-animal model for automatic face detection and identification of freely moving common marmosets based on YOLOv8 algorithms

Precise and up-to-date information about animal location and identity allows us to better quantify individual behaviors in studies of neural activity, cognition, and animal health. In socially housed laboratory animals, identification is usually defined by observation or invasive markers, making the data collection time-consuming, variable across experimenters, and disruptive to animals. We established an automatic pipeline for real-time identification of common marmosets in captivity using a close-view camera. It uses the supervised deep-learning YOLOv8 model to localize individuals, detect faces, and classify identities. Moreover, we use recognition of uniquely color-coded collar beads to improve detection accuracy among visually similar individuals. Across adult and juvenile marmosets, our system automatically identifies marmosets with > 82.9% precision and > 91.5% recall, achieving human level performance. This pipeline is designed to be easy-to-use and generalizable across non-human primate species, ages, and recording hardware, providing rapid and automatic identity recognition from real-time video.

animal behavior and cognition↗

Cell type-resolved proteomics reveals intra- and intercellular signalingin Alzheimers disease

Alzheimers disease (AD) arises from pathological interactions among diverse brain cell types, but cell-specific proteomic changes remain underexplored. Here, we present deep proteomic profiling of sorted or proximity-labeled brain cells from AD mouse models (5xFAD and AppNL-G-F) at multiple ages, quantifying 13,411 proteins in microglia (three subtypes), astrocytes, oligodendrocyte precursor cells, and neurons. We identified 3,028 differentially abundant proteins across these cell types, the majority of which were not detected in bulk proteomic datasets, and constructed cell type-specific networks to define functional modules and hub proteins. Comparison with transcriptomic data revealed that [~]30% of proteomic changes are RNA-independent. Further analyses uncovered cross-cell type signaling proteins conserved in human AD brains, such as pleiotrophin (Ptn), which is transcriptionally enriched in astrocytes but accumulates in microglia. Importantly, recombinant PTN directly activates induced microglia-like (iMG) human cells. Thus, these findings provide a comprehensive cell type-resolved proteomic atlas of AD models, highlighting novel intra- and intercellular signaling events. HighlightsO_LIA high-resolution cell type-resolved proteomic atlas of Alzheimers disease mouse models C_LIO_LI[~]3,000 cell type-specific protein alterations identified beyond bulk tissue analyses C_LIO_LIProteomic profiling of microglial subtypes reveals subtype-specific changes in Alzheimers disease C_LIO_LIAstrocyte-microglia signaling is highlighted and validated through PTN-mediated interactions C_LI

neuroscience↗

HistoSweep enables cellular-resolution tissue quality control for gigapixel images in digital pathology and spatial omics

High-resolution histology images are indispensable for pathology and increasingly serve as the structural backbone for spatial omics. Yet whole-slide images (WSIs) frequently contain artifacts, acellular voids, and background regions that, when included in computational workflows, introduce noise, degrade model accuracy, and compromise biological interpretation. Existing tools provide only coarse foreground-background separation, leaving a gap in fine-grained quality control (QC). Here we present HistoSweep, a scalable framework that generates morphology-aware tissue masks at cellular resolution. By integrating density filtering, texture descriptors, and adaptive thresholding, HistoSweep systematically removes non-informative tissue regions while preserving biologically meaningful microstructures. It processes billion-pixel WSIs in minutes on standard CPUs, requiring no GPU acceleration, and is deployable across research and clinical settings. Across 25 WSIs spanning distinct tissues, disease states, and spatial omics platforms, HistoSweep consistently outperformed existing methods. It enhanced visualization and segmentation, improved virtual cell type predictions, and safeguarded spatial transcriptomics integrity by detecting transcript leakage and transcript-histology misalignment. By enabling fine-grained, scalable QC, HistoSweep provides a foundational preprocessing step for reliable and reproducible digital pathology and spatial omics analyses.

bioinformatics↗

A unified pipeline for discovering previously unknown enzyme activities

Enzymes catalyze diverse chemical transformations and offer a sustainable approach to both breaking and making chemical bonds. However, finding an enzyme capable of performing a specific chemical reaction remains a challenge. We developed a new framework, Enzyme-toolkit (Enzyme-tk), that integrates 23 open-source tools to enable the discovery of enzymes that have activity toward a specific target reaction. Additionally, we introduce two new methods to facilitate enzyme discovery: (1) Func-e, an ML tool that searches large databases for enzymes that potentially catalyze a specific chemical transformation and (2) Oligopoolio, a gene assembly approach that reduces the cost of accessing protein sequences and thus the barrier to their experimental validation. We applied Enzyme-tk to find enzymes for chemical degradation of two man-made pollutants, di-(2-ethylhexyl) phthalate (DEHP) and triphenyl phosphate (TPP). We demonstrate that new, previously unannotated enzymes with favorable characteristics, such as high thermostability, can be identified using Enzyme-tk for reactions that are dissimilar to the training set.

biochemistry↗

Bacteroides intestinalis-Driven Arabinoxylan Fermentation Mitigates Inflammatory and Metabolic Dysfunction

Insufficient dietary fiber intake is closely linked to gut microbiome dysfunction and increased risk of noncommunicable diseases. Synergistic synbiotics, pairing defined microbes with their dietary substrates, offer a precise strategy to restore microbiome function. Here, we show that pairing the human colonic commensal Bacteroides intestinalis with insoluble wheat arabinoxylan (inWAX) yields pronounced metabolic and anti-inflammatory benefits. Using mono-associated gnotobiotic mice and high-fat diet-induced obese mice, we demonstrate that this synbiotic enhances resistance to intestinal inflammation and improves glucose homeostasis. Mechanistically, this synbiotic increases production of 6-hydroxylated bile acids with anti-diabetic and anti-steatotic effects. It also promotes microbial transformation of phenolic compounds and redirects protein metabolism toward neuroactive metabolites. These metabolic shifts are accompanied by transcriptional remodeling in the colon, spleen and liver, involving induction of genes essential for circadian rhythm, lipid metabolism, immune defense, and bile acid 6-hydroxylation. Notably, Y chromosome-linked genes associated with epigenetic regulation and protein turnover are also induced, suggesting a potential sex-specific response to synbiotics. Together, our findings establish a mechanistic framework for targeted synbiotic interventions to combat inflammatory and metabolic disorders.

microbiology↗

Smooth Muscle Dysfunction Drives Cerebrovascular Reserve Failure and End-Organ Brain Injury

BackgroundFailure of cerebrovascular reserve is a fundamental determinant of ischemic vulnerability, yet the mechanisms by which vascular smooth muscle dysfunction compromises reserve and predisposes the brain to injury remain incompletely defined. We therefore tested whether a pathogenic smooth muscle mutation produces a baseline failure of cerebrovascular reserve sufficient to render the brain vulnerable to hypoperfusion, even in the absence of fixed arterial occlusion. MethodsWe examined cerebrovascular structure, hemodynamics, and reserve in a genetically defined mouse model of ACTA2-associated multisystemic smooth muscle dysfunction syndrome with systemic or brain-restricted expression of the mutant allele. Cerebral artery morphology was assessed using magnetic resonance angiography and black ink angiography. Vascular smooth muscle phenotype was evaluated by immunohistochemistry and proliferation assays. Blood pressure reactivity and cerebral blood flow (CBF) were measured simultaneously using femoral arterial catheterization and laser speckle flowmetry during vasoactive challenges and controlled hypotension. Cerebrovascular stress responses were tested using unilateral common carotid artery occlusion. Downstream brain effects were assessed by histology, resting state functional connectivity imaging, and behavioral testing. ResultsImpaired smooth muscle contractility drove rectification and narrowing of major cerebral arteries, downregulation of contractile markers, and increased vascular cell proliferation. These structural changes produced a distinct physiological phenotype: mutant mice exhibited blunted vasoreactivity, diminished spontaneous vasodynamic activity, and a downward shift in the blood pressure-CBF relationship across a wide range of arterial pressures, consistent with loss of cerebrovascular reserve. As a result, CBF was reduced at baseline and could not be maintained during hypotension or acute vascular stress. During carotid occlusion, mutant mice showed impaired compensatory perfusion, greater physiological instability, and worse behavioral outcomes. Chronic reserve failure coincided with white matter loss, reduced neuronal density, disrupted large-scale functional connectivity, and deficits in locomotion, anxiety-related behavior, and working memory. ConclusionsPathogenic smooth muscle dysfunction caused by ACTA2 mutation produces a baseline failure of cerebrovascular reserve that renders the brain vulnerable to hypoperfusion and stress-induced ischemic injury. These findings establish cerebrovascular reserve failure as a central physiological mechanism linking vascular dysfunction to end-organ brain injury and identify reserve preservation as a critical, potentially actionable determinant of brain health in hypotension-prone vascular disease. Clinical PerspectiveO_ST_ABSWhat Is New?C_ST_ABS- ACTA2 smooth muscle dysfunction produces baseline cerebrovascular reserve impairment, with reduced cerebral blood flow and a downward-shifted pressure-flow relationship in the absence of critical large-vessel occlusion. - Vascular tone dysregulation is coupled to end-organ brain injury, including white matter and neuronal loss, disrupted functional connectivity, and behavioral deficits. - The results support complementary disease mechanisms in ACTA2 vasculopathy: baseline reserve limitation and injury-provoked occlusive remodeling. Clinical Implications- Patients with ACTA2 vasculopathy may be vulnerable to ischemic brain injury during hypotension or systemic stress despite the absence of critical stenosis or occlusion on routine imaging. - Peri-procedural and acute-care management should emphasize preserving perfusion pressure and cerebrovascular reserve (e.g., during anesthesia, dehydration, or systemic illness). - More broadly, cerebrovascular reserve is a clinically relevant, potentially modifiable determinant of brain health in hypotension-prone vasculopathies and conditions characterized by impaired vascular reactivity.

physiology↗

Widespread Regulatory Turnover Across Human Segmental Duplications

Segmental duplications (SDs) are a pervasive feature of eukaryotic genomes, enabling genomic innovation via the duplication of genes and cis-regulatory elements. However, the regulatory mechanisms that govern these regions of the genome after duplication are not well understood. The repetitive nature of SDs pose problems for short-read assays such as ChIP-seq and DNase-seq as they create reads that map to more than one location along the genome. Moreover, the newest Telomere-to-Telomere (T2T) human genome assembly has revealed previously unknown segmental duplications. In this study, we used the Telomere-to-Telomere genome assembly along with the probabilistic allocation of multi-mapped reads by our software Allo to better understand the regulatory mechanisms governing segmental duplications in the human genome. Using 134 transcription factor ChIP-seq datasets in GM12878, we found that transcription factor binding sites within segmental duplications are rarely conserved across paralogous copies. Similarly, chromatin states defined via histone ChIP-seq datasets are also poorly conserved across segmentally duplicated regions. In contrast, paralogous genes within SDs exhibit highly correlated expression patterns. Hi-C analysis revealed that many SD paralogs have higher than expected spatial proximity, suggesting that three-dimensional genome organization may buffer transcriptional divergence following duplication despite the loss of cis-regulatory regions. Together, our results suggest that regulatory regions undergo rapid turnover following segmental duplication, but the regulatory impact may be buffered by spatial proximity within the nucleus. Tissue-specific genes and transcription factors showed greater divergence, highlighting the role of SDs in expanding specialized cellular functions.

bioinformatics↗