Biology subjects

Kim, M.

Publications and source records attributed to Kim, M..

At least 73 records · Page 4Linked to original sources

bioRxiv2026

Multimodality Molecular Profiling Nominates Targetable Mechanisms in Progressive RV Dysfunction

BackgroundRight ventricular dysfunction (RVD) is a robust predictor of mortality in multiple cardiovascular diseases. Currently, it remains unclear whether the severity of RVD corresponds to distinct cellular and molecular alterations, and this has important implications for defining optimal therapeutic targets. To address this knowledge gap, we performed a multi-omics evaluation of pulmonary artery banded (PAB) pigs with differing degrees of RV compromise. MethodsPAB pigs were stratified into mild and severe RVD groups using an RV ejection fraction cutoff of 35%. RV tissue from control, mild RVD, and severe RVD animals was analyzed using single-nucleus RNA sequencing, mitochondrial and cytoplasmic proteomics, and phosphoproteomics. Histological analyses corroborated multi-omic findings. ResultsCardiac MRI revealed progressive structural and functional alterations in mild and severe RVD pigs. snRNAseq demonstrated that advancing RVD was associated with loss of cardiomyocytes, accumulation of efferocytosis-impaired macrophages, and dysregulated endothelial cells and pericytes. Combined transcriptomic and proteomic analyses showed escalating impairments of complex cardiomyocyte metabolism with worsening RVD. RV microvasculature was compromised with severe RVD as there were alterations in endothelial cell/pericyte genetic regulation, co-localization patterns in RV sections, and ectopic cardiomyocyte HIF1 expression. Analysis of both mitochondrial and global proteostasis revealed greater compromise in mitochondrial proteostasis, including downregulation of mitochondrial proteases, chaperones, and ribosomes. Paradoxically, cytoplasmic ribosomes were upregulated in severe RVD. The predicted kinome and phosphatome were uniquely altered in mild RVD as compared to severe RVD. Finally, integration of multi-omic approaches identified insufficient mitochondrial unfolded protein response, impaired macrophage efferocytosis, and activation of the ribotoxic stress response as potential contributors to severe RVD. ConclusionsOur multi-omic analysis defines the cellular and molecular landscape of progressive RVD and nominates druggable pathways that may promote progressive RV dysfunction. Future studies are needed to determine how targeting these pathways influences RV phenotypes.

physiology↗

bioRxiv2026

Disrupted Higher-Order Topology in OCD Brain Networks Revealed by Hodge Laplacian - an ENIGMA Study

Brain disorders are increasingly understood as disorders of distributed brain circuits, yet functional connectivity (FC), the dominant framework for mapping them, treats the brain as a collection of pairwise relationships between regions and cannot represent pathology distributed across coordinated sets of connections. We introduce a Hodge-Laplacian topological framework that localizes higher-order "loop" (1-cycle) organization within functional connectome, maps each loop to specific edges and networks, and yields a subject-level measure of loop expression. Applied to resting-state fMRI from the ENIGMA-OCD consortium (1,024 patients and 1,028 controls across 28 sites), the framework identified 93 loop-level abnormalities in obsessive-compulsive disorder (OCD), concentrated in frontoparietal and somatomotor systems. The edges forming these loops largely showed no significant differences between groups, indicating that the abnormalities were invisible to conventional FC analysis. The frontoparietal and somatomotor loop clusters recurred across the clinical subgroups, suggesting convergence on a shared higher-order phenotype. Robustness analyses showed the loop signal reflected higher-order organization rather than an artifact of individual edges, the network backbone, or any single site. These results indicate that coordinated, multi-edge pathology exists and can be localized even when pairwise analyses fail to detect it, positioning higher-order topology as a generalizable axis for mapping circuit pathology across psychiatric and neurological disorders.

neuroscience↗

bioRxiv2026

A normative reference for large-scale human brain dynamics across the lifespan

Human brain function emerges from dynamic reconfigurations of large-scale neural networks. While population-level reference charts have transformed the study of static brain structure and connectivity, an equivalent normative framework for intrinsic brain dynamics has been lacking. This gap has limited our ability to characterize individual variability, development, ageing, and mental health conditions at scale. Here, we establish a population-level normative reference for large-scale human brain dynamics using resting-state fMRI data from more than 10,000 individuals spanning the lifespan and 91 scanning sites. We derive a compact set of recurring brain-state configurations that are reproducible across scanners and acquisition paradigms and that generalize to previously unseen cohorts. Anchoring these dynamic states to normative lifespan models enables the quantification of individual deviations relative to population reference distributions. We show that intrinsic brain dynamics undergo systematic reorganization across development and ageing, with pronounced changes before early adulthood and more gradual modulation thereafter. Applying this framework across multiple mental health conditions reveals disorder-specific and highly heterogeneous deviations in brain dynamics that are not captured by static neuroimaging measures. Robust transfer to independent cohorts and longitudinal analyses demonstrate that normative brain dynamics can be reliably assessed out of distribution. These results delineate a population-scale dynamic architecture of the human brain and extend normative brain mapping from static phenotypes to the temporal domain, providing a reference framework for studying brain function across the lifespan in health and disease.

neuroscience↗

bioRxiv2026

Virome DNA stable isotope probing reveals diverse active soil phage communities across ecosystem types

Viruses are increasingly recognized as important players in soil ecosystems, but the active lytic virus populations that influence microbe-mediated terrestrial ecosystem processes remain mostly uncharacterized. Here, we trace 13C-labelled glucose from host microorganisms into virus genomic DNA to identify virus populations actively involved in soil carbon (C) cycling, i.e., viruses that lysed 13C-incorporating microbes. We present experimental evidence of isotope labelling (i.e., lytic activity) of more than 5,000 virus populations. The active viruses lysed hosts from 197 microbial families across 28 prokaryote phyla. Viral lysis was greater in C-limited agricultural soils compared with C-rich forest soils, highlighting C availability/inputs as key factors that mediate virus life cycles. Active viruses disproportionately lysed microorganisms in the Bacillota, Bacteroidota, and Pseudomonadota phyla, likely reflecting glucose-induced growth responses of microbial copiotrophs within those groups. Supporting this, we observed that the degree of virus genome isotope labelling was positively correlated with the growth potential of the microbial hosts. Furthermore, the active viruses exhibited unique genomic characteristics compared to the inactive viruses, including greater prevalence of lysogeny-associated genes and distinct profiles of putative auxiliary metabolism genes in the active virus genomes. Overall, our results demonstrate a link between microbial growth traits and virus activity and suggest that substrate-induced viral lysis significantly influences microbial population turnover in soil. Our results also show that virus activity in response to C inputs is highly variable among soil contexts, with implications for the varying ecosystem-scale influences of viruses among terrestrial environments.

microbiology↗

bioRxiv2026

Bottom-up and generative computations both uniquely explain social brain responses

Making social evaluations from visual input is a core human ability that engages brain regions involved in social perception, including portions of the superior temporal sulcus (STS), as well as higher-level mentalizing regions, such as the temporoparietal junction (TPJ). One common hypothesis proposes that these regions operate hierarchically: social perception regions like posterior STS (pSTS) implement bottom-up computations to generate fast, stimulus-derived representations of social interactions, while mentalizing regions like TPJ perform inverse-planning computations to infer the underlying goals and motivations driving agents behavior. However, this computational-neural mapping has never been formally tested, in large part due to the lack of successful computational models of social processing. We developed computational models aligned with these two frameworks: a graph-neural-network (GNN) model that recognizes social interactions by relying on relational visual information, and a generative inverse-planning model that does so by inverting a model of agents goals and the physical world. In this preregistered study, we collected fMRI responses while participants watched videos of agentive animated shapes depicting social interactions and compared neural responses to both computational models. Surprisingly, we found that both the GNN and inverse-planning model explained neural responses in pSTS and TPJ, even after controlling for variance explained by the other model. Exploratory analyses, however, revealed a shift from early perceptual processing towards later higher-order reasoning in both regions, suggesting a temporal rather than spatial hierarchy. Overall, this study provides the first evidence that both social perception and mentalizing regions carry out a combination of relational bottom-up and higher-level inferential computations, perhaps on distinct timescales. This work also provides the first comparison of an inverse-planning model to neural activity and demonstrates that theory-driven cognitive models can successfully predict fMRI responses to social scenes. Significance StatementThe ability to recognize social interactions between others is central to humans daily lives and engages brain regions supporting social perception and mental state inference. The neural computations underlying this ability, however, are poorly understood. Here we leveraged new models of bottom-up social perception and generative social inference to test the hypothesis that these complementary computations are carried out in separate brain regions. We compared both models to brain responses from subjects viewing procedurally generated videos of social interactions. Surprisingly, we found that both models explained neural activity in both perceptual and mentalizing regions, even when controlling for effects of the other model. These findings challenge the idea of a strict division of labor in the social brain and refine our understanding of the computations supporting human social inference.

animal behavior and cognition↗

bioRxiv2026

Microfluidic Agarose Microdroplets for DNA-Encoded Chemical Library Screening

DNA-encoded library (DEL) technology enables high-throughput small-molecule discovery but is typically performed using purified proteins under in vitro conditions that do not reflect native intracellular environments. Here, we present a microfluidic agarose -droplet platform for cellular-context DEL screening. The porous hydrogel droplets provide mechanically stable yet permeable microenvironments that protect weak protein-ligand interactions while enabling efficient buffer exchange and ligand diffusion. Importantly, mild cell permeabilization within droplets selectively retained chromatin-associated proteins, allowing screening directly in a cellular context. Using BRD4 as a model target, we validated intracellular ligand engagement by fluorescence imaging and super-resolution microscopy. Small-scale DEL screening selectively enriched JQ1 in both bead-based and cell-based formats, and large-scale DEL screening across millions of encoded compounds successfully identified hit molecules by sequencing. This agarose -droplet-based strategy expands DEL technology toward biologically relevant and chromatin-associated targets under near-native conditions.

bioengineering↗

bioRxiv2026

Accurate somatic variant detection from formalin fixed, paraffin embedded tissue (FFPE) derived WES and WGS by DeepOmicsFFPE-PLUS, a sequence context-based transformer

Formalin-fixed paraffin-embedded (FFPE) tissues represent a vast archival resource for genomic studies, yet their utility remains constrained by fixation-induced DNA damage and subsequent sequencing artifacts. To comprehensively characterize and address this challenge, we analyzed matched FFPE and fresh-frozen tumor samples from two institutions, spanning different storage durations, DNA qualities, sequencing platforms (WES and WGS), exome capture kits, and somatic variant callers. We found that FFPE-induced artifacts exhibit strong batch- and age-specific patterns, with a predominance of C:G>T:A substitutions, which particularly complicate the accurate identification of low allele frequency true variants. Enzymatic repair methods partially alleviated these artifacts but remained insufficient. To overcome these limitations, we developed DeepOmicsFFPE-PLUS(https://github.com/Theragen-Bio/DeepOmicsFFPE-PLUS), an advanced AI-based tool to accurately distinguish true somatic variants from FFPE-specific artifacts. DeepOmicsFFPE-PLUS demonstrated consistently superior performance across diverse conditions, achieving high sensitivity and specificity--even for low-frequency variants--outperforming existing tools. Application of our model to WGS data further enabled recovery of biologically relevant mutational signatures, including restoration of microsatellite instability (MSI)-associated signatures initially obscured by FFPE artifacts. Our findings underscore the necessity of artifact-aware variant calling in FFPE genomics and establish DeepOmicsFFPE-PLUS as a robust tool for artifact removal, enabling high-fidelity downstream analyses and personalized therapeutic target discovery.

cancer biology↗

bioRxiv2026

HiChIA-Rep quantifies the similarity between enrichment-based chromatin interactions datasets

3D genome mapping technologies ChIA-PET, HiChIP, PLAC-seq, HiCAR, and ChIATAC yield pairwise contacts and a one-dimensional signal indicating protein binding or chromatin accessibility. However, a lack of computational tools to quantify the reproducibility of these enrichment-based 3C data prevents rigorous data quality assessment and interpretation. We developed HiChIA-Rep, an algorithm incorporating both 1D and 2D signals to measure similarity via graph signal processing methods. HiChIA-Rep can distinguish biological replicates from non-replicates, cell lines, and protein factors, outperforming tools designed for Hi-C data. With a large amount of multi-ome datasets being generated, HiChIA-Rep will likely be a fundamental tool for the 3D genomics community.

bioinformatics↗

bioRxiv2026

Repeated experience drives multiscale engram reorganization to shape memory strength and precision

How memories are shaped by repeated experiences remains unclear. Reorganization of memory engram could underlie memory transformation. Here, by combining c-Fos-based engram cell tagging with optogenetics, spine imaging, and reactivation analyses in the dentate gyrus (DG) and medial prefrontal cortex (mPFC), we discovered a distinct system-wide engram reorganization following repeated learning; that is, a reshuffling of engram cells in the DG, as well as the rapid maturation of mPFC engram cells, forming a dual engram distributed within the hippocampal-mPFC network. These mPFC engram cells were crucial for relearning-dependent enhancement of memory precision. In addition, we found that reactivation of DG engram cells during retraining is critical for engram reorganization-dependent memory strengthening. These findings establish a causal link between engram reorganization and memory transformation by relearning.

neuroscience↗

bioRxiv2026

Co-repression of Yap1 and Sox9 Abrogates Established Cholangiocarcinoma by Eliminating Transcriptional Compensation

Background/AimsIntrahepatic cholangiocarcinoma (iCCA) represents an unmet clinical need due to its increasing incidence, aggressive biology, and limited treatment options. The extremely low-response rates to current systemic regimens and the emergence of adaptive resistance to targeted therapies underscore the urgent need for alternative therapeutic strategies. Given that the lineage-defining transcription factors SOX9 and YAP1 are central regulators of cholangiocyte and iCCA identity, we investigated their functional roles as potential therapeutic vulnerabilities across multiple preclinical models. MethodsPatient tissue-microarray (TMA) analysis, Sleeping-Beauty hydrodynamic tail vein injection-based iCCA models, and Cre-mediated inducible gene deletion systems were used to investigate the roles of Sox9 and Yap1. Deep-learning-based prediction, RNA-seq, ChIP-seq and immunohistochemistry analyses were performed to delineate transcriptional networks and downstream effectors associated with SOX9/YAP1 signaling. ResultsDual deletion of Sox9 and Yap1 effectively eradicated advanced iCCA while preserving intrahepatic bile ducts, regardless of oncogenic drivers. Mechanistically, SOX9 and YAP1 transcriptionally compensated for each other when one was absent, and ILF2, MGAT5, and WWTR1 were identified as key downstream effectors mediating this compensatory mechanism. Loss of Ilf2, Mgat5, or Taz suppressed iCCA, whereas overexpression of Ilf2 or Taz following Sox9/Yap1 co-deletion restored tumor development, indicating that ILF2 or TAZ can functionally substitute for YAP1 and SOX9 in sustaining iCCA. ConclusionsCo-targeting SOX9 and YAP1 offers a promising and safe broad-spectrum preventive/therapeutic approach for iCCA, potentially overcoming resistance to YAP1 inhibition. The adaptive resistance mechanism identified may extend to other malignancies, providing insights for addressing the advanced resistant to YAP1-TEAD-directed therapies.

cancer biology↗

bioRxiv2026

BiomarkerKB: FAIR and Integrated Biomarker Knowledge Connecting Biomolecular and Clinical Data Types

Biomarkers are essential tools for disease detection, risk assessment, therapeutic monitoring, and precision medicine. However, biomarker data are dispersed across heterogeneous resources, inconsistently reported in the literature, and rarely standardized for computational use. This fragmentation limits reproducibility, cross-study integration, and the discovery of novel biomarker and disease relationships. We developed BiomarkerKB, a knowledgebase designed to harmonize and integrate biomarker information under a standardized data model. The model follows the FDA-NIH BEST biomarker definition and captures both core fields (biomarker entity, disease/condition, exposure agent) and contextual metadata (specimen, biomarker role, evidence, provenance). Biomarker data and related annotations were either curated from publications or collected from public resources (e.g., OpenTargets, GWAS Catalog, ClinVar, CIViC, OncoMX) and were also contributed by the Common Fund Data Coordinating Centers and the Early Detection Research Network (EDRN). Standardization was achieved using ontologies and reference resources such as Disease Ontology, UBERON, UniProtKB, and HUGO Gene Nomenclature Committee (HGNC) gene symbols. BiomarkerKB data were ingested into a Neo4j-based knowledge graph and integrated with the Common Fund Data Ecosystem (CFDE) Knowledge Graph. The initial release of BiomarkerKB contains over 200,000 biomarker-disease associations spanning genes, proteins, metabolites, glycans, and chemical elements. The knowledge graph comprises more than 300,000 nodes and 1.2 million edges, enabling structured exploration of biomarker relationships within CFDE data as demonstrated through the knowledge graph query-based use cases presented in this study. A publicly accessible web portal (https://biomarkerkb.org) provides keyword search, filtering, data downloads, and access to graph visualization to support both researchers and computational analyses. BiomarkerKB addresses a critical gap in biomarker informatics by providing an integrated, FAIR (Findable, Accessible, Interoperable, and Reusable), and unified framework for biomarker knowledge exploration and discovery.

bioinformatics↗

bioRxiv2026

Single-nuclei RNA-sequencing uncovers sexually divergent exercise signatures partially mimicked by TFEB overexpression in mouse skeletal muscle

Exercise induces extensive, cell-type-specific transcriptional remodeling in skeletal muscle to support metabolic flexibility and adaptation. However, the regulatory mechanisms underlying these transcriptional programs, and the extent to which they differ between sexes, remain poorly defined. We previously reported that lifelong, muscle-specific overexpression of human Transcription Factor E-B (cTFEB;HSACre transgenic mice) recapitulates many adaptive features of endurance training in both sexes, leading to profound geroprotective effects during aging even in the absence of exercise. Here, we profile transcriptional adaptations to voluntary wheel running (VWR) and TFEB-overexpression at single-nucleus resolution in young male and female mouse tibialis anterior muscle. This represents, to our knowledge, the first integrated analysis of exercise and TFEB signaling using sex as a biological variable. Using robust bioinformatic and single-nuclei RNA-sequencing approaches, we profiled six muscle-resident cell populations and uncover previously unrecognized, sex-dependent signaling nodes governing exercise-associated metabolic plasticity. TFEB activation and endurance training by VWR elicit strongly correlated transcriptional programs enriched for lipid metabolism, mitochondrial remodeling, and immune modulation, establishing TFEB-overexpression as a partial exercise mimetic. In general, female muscle exhibited enhanced extracellular matrix and lipid-associated responses to endurance training and TFEB overexpression, whereas males preferentially engaged in angiogenic and oxidative networks, revealing distinct sex-specific, sex-dimorphic, or sex-agnostic regulatory routes to metabolic flexibility. Integration with independent multi-omics datasets from endurance-trained rats (MoTrPAC) confirms the conservation of TFEB-exercise transcriptional convergence in skeletal muscle across species and potentially muscle types. Together, these findings define TFEB as a regulator of exercise transcriptional programs and reveal sex-specific molecular frameworks that drive metabolic adaptation in skeletal muscle. Furthermore, the resulting sex-resolved, single-nucleus transcriptional atlas provides a unique resource for the field, enabling comparative, mechanistic, and hypothesis-driven exploration of exercise-responsive skeletal muscle regulatory networks across sexes.

physiology↗

bioRxiv2026

MONTE: Methylation-based Observation Normalization and Tumorpurity Estimation

Bulk DNA methylation profiling is widely used to study cancer epigenomics in clinical settings, but these measurements aggregate signals from malignant and non-malignant cells, introducing composition-dependent confounding that complicates tumor-intrinsic interpretation and cross-cohort analyses. While existing methods can estimate tumor purity and, in some cases, correct methylation measurements, they typically require cancer-specific reference models, matched normal samples, or predefined probe sets, limiting their applicability to rare cancers, different clinical cohorts, and cross-dataset comparisons. We present MONTE (Methylation-based Observation Normalization and Tumor purity Estimation), a unified, cancer label-free framework for tumor purity inference and CpG-resolved methylation correction from bulk DNA methylation data. MONTE learns probe-wise relationships between methylation and tumor purity using an empirical Bayes-moderated linear model and infers purity in new samples via signal-to-noise weighted aggregation, without requiring matched normals, cancer labels, or predefined probe sets. A single pan-cancer MONTE model outperforms existing cancer-specific methods for purity estimation across 21 cancer types, generalizes across purity references, and runs orders of magnitude faster on full-dataset analyses. MONTE also introduces Bayesian transfer learning, which enables efficient recalibration to alternative purity definitions, validated on three independent external cohorts. Methylation correction with MONTE further amplifies tumor-relevant regulatory signal and improves the reproducibility of differential methylation analyses. By unifying purity estimation and correction in a single flexible, scalable, and interpretable framework, MONTE broadens the accessibility of tumor-intrinsic methylation analysis across cancer types and datasets.

bioinformatics↗

bioRxiv2026

Identification of Lupus Immune Complex-Driven Pathogenic Pro-inflammatory Monocytes and Macrophages in Systemic Lupus Erythematosus

Systemic lupus erythematosus (SLE or lupus) is an autoimmune disease characterized by anti-nuclear antibody (ANA) production and inflammation, though the mechanisms by which ANAs induce inflammation and tissue injury are incompletely understood. Here, we identified distinct subsets of mononuclear phagocytes (MPs), including monocytes (Mo) and macrophages (M{Phi}), driven by lupus immune complex (IC), comprised of ANAs and their target antigens. scRNA-seq of human Mo incubated with U1-snRNP (snRNP) lupus IC revealed expansion of distinct pro-inflammatory Mo subsets with upregulation of inflammatory genes including those encoding cytokines, NLRP3, and transcription factors. These transcriptomic changes strongly correlated with protein expression, as determined by proteomic analysis. Mo developed similar pro-inflammatory transcriptomic changes in response to other lupus ICs containing anti-dsDNA and Ro60 antibodies. Interrogation of scRNA-seq datasets from the skin, kidney, and peripheral blood of lupus patients revealed the presence and expansion of pro-inflammatory Mo and M{Phi} populations exhibiting transcriptomic signatures similar to those observed in lupus IC-stimulated Mo. Some of these cells expressing the snRNP IC gene signature exhibited low expression of the type I IFN signature, suggesting that lupus IC and type I IFN signaling may independently affect Mo subsets. In lupus nephritis, infiltration of CD68+ M{Phi} expressing NLRP3 was associated with treatment outcomes. Inhibiting activation of the transcription factor ETS2, a master regulator of Mo/M{Phi}-driven inflammation, attenuated lupus IC-induced activation of pro-inflammatory Mo. Collectively, these findings provide novel insights into the role of lupus IC-driven pro-inflammatory MPs in the pathogenesis of SLE and highlight their relevance as therapeutic targets. Significance StatementSystemic lupus erythematosus (SLE or lupus) is a multi-systemic autoimmune inflammatory disease characterized by anti-nuclear antibody (ANA) production. Lupus immune complex (IC), consisting of ANAs and their target antigens, likely play a critical role in the pathogenesis of lupus through activation of mononuclear phagocytes (MPs), including monocytes (Mo) and macrophages (M{Phi}), which can produce an array of inflammatory molecules. Using transcriptomic and proteomic analyses, our study identified distinct pro-inflammatory Mo populations driven by lupus IC, along with expansion of similar pro-inflammatory Mo and M{Phi} subsets in the skin, kidneys, and peripheral blood of lupus patients. These findings provide novel insights into the pathogenic role of lupus IC-driven pro-inflammatory MPs and support a scientific rationale for therapeutically targeting these cells. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=155 HEIGHT=200 SRC="FIGDIR/small/700902v2_ufig1.gif" ALT="Figure 1"> View larger version (43K): org.highwire.dtl.DTLVardef@1839430org.highwire.dtl.DTLVardef@175dd1dorg.highwire.dtl.DTLVardef@107b54forg.highwire.dtl.DTLVardef@11096b0_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2026

GBA1 deficiency differentially affects endolysosomal trafficking in neurons versus astrocytes

Mutations in the gene glucosidase, beta acid 1 (GBA1) are the strongest genetic risk factor for Parkinsons disease (PD) and are associated with faster disease progression. GBA1 is expressed in all cell types of the central nervous system, with some evidence supporting higher expression in glial cells than neurons. To elucidate possible specific functions in neurons versus glia, we differentiated human induced pluripotent stem cells (iPSCs) generated from an individual with PD heterozygous for the GBA1 pathogenic null variant IVS2+1 (GBA1IVS/+), homozygous GBA1 IVS2+1 isogenic to GBA1IVS/+ (GBA1IVS/IVS) and a healthy unaffected age-and sex-matched individual (GBA1+/+). GBA1 expression was reduced in GBA1IVS/+ and GBA1IVS/IVS neurons and astrocytes. Endolysosomal trafficking was significantly altered in GBA1-deficient neurons with enlarged early and recycling endosome and lysosome compartments in neurons but not in astrocytes. High molecular weight oligomerization of -synuclein and phosphorylated Ser129 -synuclein were present in GBA1IVS/+ and GBA1IVS/IVS neurons but not in GBA1+/+ neurons, or in GBA1-deficient or GBA1+/+ astrocytes. Transcriptomic analysis of GBA1-deficient neurons and astrocytes revealed cell-type specific profiles. GBA1 deficiency in neurons downregulated immune response and upregulated cholesterol synthesis pathways, while GBA1 deficiency in astrocytes downregulated genes associated with translation and upregulated genes involved in extracellular matrix biogenesis. Transcriptomic analysis also suggests that GBA1 deficiency induces neurotoxic reactivity in astrocytes. Together, these findings indicate that GBA1 deficiency has cell type-specific effects, with increased neuronal vulnerability to endolysosomal trafficking leading to -synucleinopathy while GBA1 deficiency in astrocytes leads to increased neurotoxic reactivity independent of endolysosomal trafficking and -synucleinopathy. HighlightsO_LIiPSC-derived neurons and astrocytes modeled GBA1 deficiency C_LIO_LIEndolysosomal trafficking defects occurred only in GBA1-deficient neurons C_LIO_LI-synuclein oligomers accumulated in GBA1-deficient neurons, not astrocytes C_LIO_LIAstrocyte GBA1 loss drove neurotoxic reactive gene signatures C_LIO_LIGBA1 deficiency causes cell-type specific pathology C_LI

neuroscience↗

bioRxiv2026

NFATc3 enhances DREAM complex-driven tumorigenesis

The nuclear factor of activated T cells (NFAT) transcription factors, activated by calcium-calcineurin signaling, regulate various cellular processes, including cell differentiation, angiogenesis, and immune cell activation. Nonetheless, their roles in tumor cells remain largely undefined. The dimerization partner, RB-like, E2F, and multi-vulval class B (DREAM) complex orchestrates cell quiescence and proliferation. Pharmacological mimicry of DREAM-activated transcriptional signatures identified two calcium signaling inhibitors that suppressed lung adenocarcinoma (LUAD) cell proliferation. Among the five NFAT members, NFATc3/NFAT4 was predominantly expressed in LUAD cells and required for both LUAD cell proliferation and DREAM target gene transactivation. NFATc3 was enriched at DREAM target promoters and associated with the DREAM complex, possibly via LIN9, a scaffolding protein of the Multi-Vulva class B (MuvB) core proteins. These findings reveal an unexpected role for NFATc3 in promoting DREAM target gene transactivation and suggest the calcium-NFATc3 axis as a molecular target in LUAD, enriched by DREAM complex activation.

molecular biology↗

bioRxiv2026

Crystal structure of the V. parahaemolyticus ToxS dimer suggests a model for bile-induced ToxRS activation

The ToxRS system belongs to a family of co-component transmembrane transcription regulators that act as sensors of environmental cues and regulate virulence gene expression in several bacterial pathogens. These systems are thought to operate by sensing environmental stimuli and transmitting signals through periplasmic domains to activate DNA-binding transcription factors. In the enteric pathogens Vibrio parahaemolyticus and Vibrio cholerae, the ToxRS system regulates virulence factors responsible for severe gastrointestinal symptoms in humans. ToxR is a DNA-binding regulator associated in the periplasm with ToxS, a protein of poorly understood function. ToxS modulates the activity of its binding partner ToxR in the presence of bile salts, antimicrobial cholesterol metabolites secreted into the gut. To date, the molecular mechanism underlying this regulation remains unclear. We present crystal structures of the V. parahaemolyticus ToxS periplasmic domain (ToxSp) with and without the bile salt glycocholate. ToxSp forms an 8-stranded broken {beta}-barrel with a central -helix and is structurally homologous to a group of chaperone proteins. ToxSp has a highly conserved hydrophobic core that stabilizes the {beta}-barrel fold, while the binding pocket tolerates substantial variation, consistent with binding hydrophobic ligands. Strikingly, we discovered that Vp-ToxSp binds three molecules of glycocholate and the presence of this bile salt leads to the formation a strand-swapped ToxS homodimer. Finally, modeling two ToxR periplasmic domains in complex with the glycocholate-bound ToxSp homodimer provides a structure-based model for bile salt-mediated heterotetramerization of the ToxRS system. Overall, our study addresses a major longstanding question in the field of Vibrio virulence regulation providing a scenario that could apply to other pathogens that utilize these membrane-bound family transcriptional regulators. AUTHOR SUMMARYThe ability to sense the environment is essential for bacterial pathogens to successfully colonize the human host. Many pathogenic bacteria utilize members of the family of co-component transmembrane transcription regulators (coTTRs) to regulate pathogenesis in response to host signals. The ToxRS system is a coTTR regulatory pair that is essential for host colonization and virulence regulation of the enteric pathogens Vibrio cholerae and Vibrio parahaemolyticus. This system encompasses a transcription factor, ToxR, and a binding partner of enigmatic function, ToxS. Here, we solved the structure of the ToxS periplasmic domain V. parahaemolyticus and found that it belongs to a larger family of chaperone-like proteins present in many organisms. Strikingly, we discovered that the presence of the bile salt glycocholate leads to the dimerization of the periplasmic domain of ToxS. We propose that bile salt-induced ToxS dimerization brings two ToxR cognates together forming a heterotetramer activating the regulatory system. Our results and model address a major longstanding question in the fields of Vibrio virulence regulation and could apply to other pathogens that utilize these membrane bound family transcriptional regulators.

biochemistry↗

bioRxiv2026

Local translational program at the muscle-tendon junction endows domain identity in muscle syncytia

How cells establish specialized subdomains is a fundamental question in cell and tissue biology. Skeletal muscle fibers, among the largest cells in the body, are multinucleated and form distinct regions such as the neuromuscular and myotendinous junctions (MTJ), the latter forming a critical interface between muscle and tendon that transmits contractile force. While transcriptional heterogeneity among myonuclei has been described, whether local translation contributes to domain identity remains unknown, largely due to the lack of tools for domain-specific manipulation. Here, we introduce MTJ-AAV, a viral system that enables selective genetic targeting of MTJ myonuclei. This approach allowed MTJ-specific ribosome tagging and revealed extensive translational regulation underlying MTJ biology and its remodeling during exercise. Interestingly, untranslated regions of these transcripts were sufficient to control regionalized translation. Notably, the KLF-family transcription factors emerged as translationally upregulated targets at the MTJ, where they drive local gene expression. Our findings establish local translation as a key layer of subcellular specialization and provide a versatile toolkit for dissecting spatial molecular regulation within muscle syncytia.

cell biology↗