Biology subjects

Du, Y.

Publications and source records attributed to Du, Y..

At least 55 records · Page 3Linked to original sources

bioRxiv2026

Origins of reactivity in SAM-utilizing ribozyme SAMURI-catalyzed RNA alkylation

Unlocking the design principles of programmable RNA catalysts capable of sitespecific chemical modification is critical for expanding the functional and therapeutic potential of RNA. The SAM analogue-utilizing ribozyme (SAMURI) enables sitespecific RNA alkylation using either S-adenosylmethionine (SAM) or the synthetic cofactor propargylic Se-2,6-diaminopurinribosyl-selenomethionineamide (ProSeDMA), yet the molecular determinants of its reactivity remain incompletely understood. Here, we combined molecular dynamics, 3D-RISM solvation analysis, alchemical free-energy calculations, quantum pKa shift predictions, and ab initio QM/MM free-energy simulations to characterize the conformational and electronic factors that govern catalysis. Simulations show that, although the global fold of SAMURI remains stable in solution, the formation of catalytically competent near-attack configurations is rare, indicating that the observed rate depends on access to a minor fraction of these reactive conformations (freact). A putative Mg2+ binding site between the SAM carboxylate and the G30 phosphate, together with a hydrogen bond between the cofactor -amine and U8:O2, enriches freact. QM/MM simulations support an SN2-like alkyl transfer mechanism and show that ProSeDMA reacts more readily than SAM primarily due to its more favorable electronic leaving-group properties that enhance the intrinsic rate (kint). Atomic substitutions at A52 that tune the N3 pKa enhance nucleophilicity, further lower the activation barrier, and increase kint. Together, these results show that SAMURI catalysis is governed by a combination of conformational preorganization and electronic effects, providing a framework to guide the design of new programmable RNA alkyltransferases. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/720726v1_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@90e0c1org.highwire.dtl.DTLVardef@193b8d6org.highwire.dtl.DTLVardef@14c0d49org.highwire.dtl.DTLVardef@1fc6793_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2026

Cardiac oxidative stress monitoring enabled by hierarchical mechanical adaptation

Soft bioelectronics have advanced cardiac monitoring through electrophysiological tracking, yet this alone cannot resolve the metabolic pathology essential to surgical decision-making. However, real-time molecular sensing on beating hearts remains unresolved due to deformation-induced sensor failure and stress-induced metabolite artifacts. This challenge is exemplified by ischemia-reperfusion injury (IRI), a major cardiac surgery complication characterized by reactive oxidative species (ROS) bursts, where true pathological ROS signals being confounded by mechanotransduction-induced ROS artifacts. Herein, we propose an enzymatic cardiac oxidative stress biosensor (E-cardiac) with hierarchical mechanical adaptation: macro-scale biofluid-mediated contact, micro-scale fiber reorganization, and nano-scale enzymatic confinement within gold nanoarches dissipate interfacial stress. This produces ultrathin ([~]460 nm), soft (0.79 kPa) E-cardiac with robust electrochemical stability (100% strain), low detection limit (380 nM), rapid adhesion (<3 s), stable biosensing on beating heart, as well as minimal invasive deployment capability. Mechanical analysis and cellular studies confirm mitigated stress-induced ROS and absent PIEZO channel activation. Validated across cardiomyocytes, ex vivo tissues, multi-species ischemia models (mouse, rat, rabbit, pig), rat ischemia-reperfusion injury, and Langendorff hearts simulating graded perfusion deficits, E-cardiac quantitatively differentiates IRI severity (sham < ischemia < reperfusion) as well as detecting the "ECG blind window". The E-cardiac platform provides real-time metabolic feedback for surgical guidance during cardiac procedures, enabling timely intervention before irreversible damage.

bioengineering↗

bioRxiv2026

Modeling Synthetic Audience Reactions to Social-Cognitive Narratives: A Generative GSR Model to Predict Real-World Autonomic Alignment during Film Viewing

While media consumption can be a solitary act, it produces a shared, socially coordinated experience where audiences bodies align in response to shared narrative events that are often social-affective in nature. Despite this recognition, traditional descriptive models of Galvanic skin response (GSR) have existed for decades, yet the socially coordinated aspect remains to be fully reflected in physiological models with the field of communication often treating the underlying generators of autonomic activity as a black box. To bridge this gap, we introduce a computational framework that models the underlying neural driver and its convolution to sweat gland physiology to explain how narrative events translate into measurable conductance. By leveraging multimodal AI models to "interpret" the social-cognitive content of a film, we generated a predictor timeline for a synthetic audience comprised of digital agents (i.e. artificial body systems responding to the film events with GSR responses). We then test this computational audience model by comparing its predictions against an empirical dataset collected as audience members (N = 96) processed the same stimulus, finding that AI-identified social triggers, like moments of comedic violence or shared emotional shifts, significantly predict the GSR time-course of audience engagement. In sum, this paper moves beyond simple and often retrospective labels like "arousal" to offer a computational account of how shared social narratives grip the human nervous system. We provide a scalable and expandable framework and a set of tools to predict media impact and understanding the psychophysiological basis of media.

animal behavior and cognition↗

bioRxiv2026

STDrug enables spatially informed personalized drug repurposing from spatial transcriptomics

Drug repurposing offers a scalable route to accelerate therapeutic discovery, yet existing approaches based on single-cell RNA sequencing (scRNA-seq) often overlook spatial tissue context, limiting their ability to capture microenvironment-dependent drug responses. Here we present STDrug, a spatially informed computational framework that integrates spatial transcriptomics, graph-based modeling, and multimodal learning to enable patient-specific therapeutic prioritization. STDrug identifies and aligns disease and control spatial domains using graph convolutional networks and coherent point drift, and prioritizes candidate drugs through an integrative scoring scheme combining tumor-reversible gene signatures, perturbation-based reversal scores, and knowledge-guided gene weighting within a machine learning framework. By modeling spatial domain interactions alongside predicted drug efficacy and toxicity, STDrug generates robust patient-level drug scores. Across hepatocellular carcinoma and prostate cancer datasets, STDrug outperforms existing single-cell and spatial transcriptomics-based drug repurposing methods, achieving signficantly improved predictive accuracy (AUCs=0.81-0.82) across patients. Validation using large-scale electronic health records and in vitro assays further supports the translational relevance of top-ranked candidates. Taking together, STDrug establishes a generalizable framework for incorporating spatial omics into therapeutic discovery, advancing spatially informed and personalized drug repurposing.

bioinformatics↗

bioRxiv2026

Exploration of Orally Disintegrating Tablet for Sublingual Vaccination against Mucosal Bacterial Infection

Oral mucosal bacterial infections impose a substantial global disease burden, yet current clinical management typically reduces microbial load only transiently and rarely establishes durable protection at the oral surface. Analysis of 200 patients with periodontitis revealed that elevated levels of pathogen-specific salivary secretory Immunoglobulin A (sIgA) were strongly associated with reduced bacterial burden and improved clinical periodontal outcomes, identifying sIgA as a key determinant of effective oral protection. Guided by this observation, we developed a sublingual, orally disintegrating tablet vaccine (Capot) that incorporates bacterial extracellular vesicles providing a comprehensive repertoire of native antigens and multiple pathogen-associated molecular patterns, encapsulated within a calcium phosphate nanoshell to enable safe transmucosal delivery to submandibular lymph nodes. The rapidly disintegrating tablet format minimizes inadvertent swallowing and enhances local mucosal bioavailability. In mice and non-human primates, Capot induced robust and long-lasting salivary sIgA responses without overt oral mucosal or gastrointestinal inflammation and conferred strong protection against primary, recurrent, and antibiotic-resistant periodontitis. Together, these findings establish sublingual tablet vaccination as a practical strategy for selectively engaging oral mucosal immunity and preventing chronic bacterial diseases at oral mucosal surfaces.

bioengineering↗

bioRxiv2026

Combined Menin and XPO1 inhibition drive synergistic antileukemic activity in KMT2Ar and NPM1-m AML

Menin scaffolds the oncogenic histone-lysine-N-methyltransferase (KMT2A)-fusion protein (FP) complex in KMT2A-r and wild-type KMT2A complex in NPM1-m acute myeloid leukemia (AML). Menin inhibitors (MIs) are effective in KMT2A-r AML and NPM1-m AML. However, not all patients respond to MIs as monotherapy. In this preclinical study, we demonstrate that the MI ziftomenib, in combination with the XPO1 inhibitor selinexor, synergistically inhibited the growth of multiple KMT2A-r and NPM1-m AML cell lines (CI<1). The combination suppressed colony formation in primary CD34+ KMT2A-r progenitor cells without affecting normal stem cells. Robust apoptosis and decreased G2/M populations were also evident. The combination downregulated HOXA9 and MEIS1 while upregulating monocytic differentiation marker CD11b in both the AML molecular signatures. RNA sequencing and proteomic analysis in KMT2A-r revealed suppression of multiple bona fide menin-KMT2A target genes. Our mechanistic studies also identified a novel role of XPO1 in stabilizing menins binding to chromatin and its interactions with KMT2A and KMT2A/MLLT3. XPO1 inhibitor-mediated disruption of these interactions, particularly in combination with ziftomenib, synergistically impairs oncogenic transcriptional programs. In vivo, combination therapy improved survival in both MV4;11 and OCI-AML3 cell line and primary patient-derived KMT2A-r and NPM1-m AML xenograft models in NSG mice, effective even at reduced drug doses. These preclinical findings demonstrate that simultaneous inhibition of the menin-KMT2A interaction and XPO1 can be a more effective translational strategy for treating KMT2A-r and NPM1-m AML than MI monotherapy to deepen responses and delay/prevent relapses.

cancer biology↗

bioRxiv2026

Impaired Endosomal Recycling of Signaling Receptors Activates an Extracellular UPR

Mitochondrial dysfunction and extracellular protein aggregation occur in neurodegenerative diseases such as Alzheimers disease (AD). However, it remains unclear if these processes are functionally linked. Here, we identify a signaling pathway that is activated upon accumulation of aggregation-prone proteins in the extracellular space. We find that the transcription factor ATFS-1, which regulates the mitochondrial unfolded protein response, also regulates transcripts required for endosomal recycling, multiple plasma membrane-localized signaling receptors, and secreted proteins that bind aggregation-prone proteins in the extracellular space, including transthyretin and A{beta}, and promote their degradation. Interestingly, A{beta}(1-42) aggregation induces atfs-1-dependent transcription by promoting degradation of the bZIP protein ZIP-3, which antagonizes ATFS-1. ZIP-3 accumulates in the cytosol when it is phosphorylated by kinases that function downstream of plasma membrane-localized signaling receptors, including the WNT and glutamate receptors. Upon ligand binding, the signaling receptors stimulate the cognate kinase, many of which we found phosphorylate ZIP-3, impeding ZIP-3 degradation, allowing it to antagonize atfs-1-dependent transcription. However, accumulation of aggregation-prone proteins such as A{beta}(1-42) causes endosomal swelling, which impairs endosomal recycling, instead diverting signaling receptors to lysosomes for degradation. In turn, the depletion of signaling receptors reduces the level of ZIP-3 phosphorylation, resulting in ZIP-3 degradation and activation of atfs-1-dependent transcription, which promotes extracellular proteostasis. Our findings uncover an unexpected coupling between endocytic quality control and mitochondrial signaling, revealing a circuit that preserves extracellular proteostasis and promotes organismal resilience.

cell biology↗

bioRxiv2026

AATRhg1 is a tonoplast protein that alters amino acid, metabolic and defense responses and nematode resistance

Soybean cyst nematode (SCN, Heterodera glycines) causes significant soybean yield losses. The Rhg1 locus is a major contributor to SCN resistance and contains three genes that mediate this trait including Rhg1-GmAAT (Glyma.18G022400), which encodes putative amino acid transporter AATRhg1. The molecular function of AATRhg1 in SCN resistance is not understood. In this study, rhg1-b soybean lines with Rhg1-GmAAT silencing demonstrated that Rhg1-GmAAT can contribute resistance against HG 0 SCN and also against problematic HG 2.5.7 populations that partially overcome rhg1-b-mediated resistance. An AATRhg1 Y268L mutant complemented SCN resistance in Rhg1-GmAAT-silenced plants while an AATRhg1 D122A mutant did not. Overexpression of Rhg1-GmAAT was not sufficient to enhance SCN resistance, suggesting that AATRhg1 requires coordinated activity with other proteins or pathways. Confocal microscopy demonstrated that AATRhg1 localizes to the tonoplast in soybean root cells. Amino acid, transcriptomic and metabolomic profiles were determined for SCN-infected root segments 3 days after SCN inoculation. In Rhg1-GmAAT-silenced plants relative to fully resistant (non-silenced) rhg1-b plants, levels of leucine, isoleucine, and tyrosine were significantly elevated. Rhg1-GmAAT silencing reduced SCN-responsive transcript abundances for multiple processes, significantly including genes for MAPK signaling, ethylene responses and starch and sucrose metabolism. The most common identified metabolomic changes were in amino acid derivatives, shikimate/phenylpropanoid/isoflavonoid compounds, terpenoids, and especially fatty acids. These findings can guide further investigation into the mechanisms by which AATRhg1 contributes to SCN resistance.

plant biology↗

bioRxiv2026

A Single-Cell Temporal Atlas of Mouse Nasal Embryonic Development

The mammals breathe and perceive odors through anatomically and functionally distinct respiratory and olfactory regions of the nose; however, how the early embryo endows this system remains largely unknown. Here, we present a temporal high-resolution single-cell RNA sequencing (scRNA-seq) atlas of mouse nasal development, comprising 183,247 cells collected from 20 embryos spanning embryonic day 10.5 (E10.5) to E18.5. We identified 7 major cell clusters and 52 molecularly defined subtypes, including previously unrecognized rare populations and niche-derived signaling components involved in progenitor cell maintenance. Lineage reconstruction of epithelial and mesenchymal compartments revealed dynamic cell fate transitions and highlighted candidate regulators of lineage specification, including Foxa1 as a regulator of nasal respiratory ciliated epithelium differentiation. Integration with adult nasal epithelium datasets further delineated transcriptional dynamics of olfactory stem cells. This study provides a molecular roadmap of nasal development and offers a valuable resource for future research into nasal biology and regenerative strategies.

developmental biology↗

bioRxiv2026

Mapping spatially organized molecular and genetic signatures of schizophrenia across multiple scales in human prefrontal cortex

The dorsolateral prefrontal cortex (dlPFC) is central to cognitive dysfunction in schizophrenia (SCZ), yet how molecular changes are organized across cortex remains unclear. Here, we applied complementary spatial transcriptomic approaches spanning laminar domains, microenvironments, and cell types in postmortem human dlPFC. At the laminar level, SCZ-associated transcriptional changes were strongest in glia-enriched domains (layer 1/meninges and white matter), including down-regulation of microglia-associated genes, whereas genetic risk localized to neuronal-rich gray matter. We next analyzed SCZ-linked microenvironments including neuropil, neuronal, perineuronal net, and vascular compartments. Within these, neuronal and synaptic transcriptional changes were most prominent in neuropil, showing down-regulation of activity-dependent synaptic genes and inhibitory neuron markers. At the cellular level, these signals reflected intrinsic alterations localized to cell types. Across analyses, patterns converged on altered BDNF-TrkB signaling and inhibitory circuit dysfunction. Together, our findings highlight spatial scale as a key determinant in resolving neuronal and non-neuronal aspects of SCZ-associated biology.

neuroscience↗

bioRxiv2026

Looking backward for the future: long-term population recovery, habitat associations, and future climatic vulnerability of the critically endangered Sino-Mongolian beaver (Castor fiber birulai) in China

Despite the successful population recovery of the Eurasian beaver (Castor fiber) across much of Eurasia, its subspecies, the Sino-Mongolian beaver (C. f. birulai), remains critically endangered, with an estimated population of approximately 1,500 individuals confined to a small number of isolated and fragmented refugia along the China-Mongolia border. Effective conservation of this highly threatened subspecies requires a holistic perspective that integrates constraints on population dynamics, habitat associations, and future climatic vulnerability. Here, we combined systematic annual field surveys conducted between 2003 and 2023 with historical survey records from 1975 to 1989 in northern Xinjiang, China, to synthesize long-term spatiotemporal population dynamics, evaluate habitat preferences based on nine local environmental variables, and assess future climatic vulnerability using ensemble species distribution models (SDMs) under projected climate change scenarios. We detected a significant and phased population recovery, with beaver colony numbers increasing from 27 (approximately 100 individuals) in 1975 to 227 (681-908 individuals) in 2023. This recovery closely corresponded with major conservation milestones, including the establishment and upgrading of nature reserves, strengthened legislative protection, and enhanced multi-stakeholder collaboration. Habitat analyses further indicated that the Sino-Mongolian beaver preferentially occupied areas characterized by minimal anthropogenic disturbance and stable hydro-geomorphic conditions. Critically, SDM projections revealed that only 14% of the current study area presently exhibits high climatic suitability, and these highly suitable habitats are expected to disappear entirely by the 2050s. Together, our findings provide a comprehensive overview of the historical population recovery and conservation trajectory of the Sino-Mongolian beaver in China, and offer robust scientific support for developing adaptive management strategies in the face of ongoing climate change and increasing human pressures.

ecology↗

bioRxiv2026

Detection of Somatic Point Mutations Directly from Spatial Transcriptomics Enables in vivo Spatiotemporal Lineage Tracing

Spatial transcriptomics reveals tissue organization but lacks in vivo lineage-tracing methods applicable to humans. We introduce SpaceTracer, a computational framework that accurately detects somatic single-nucleotide variants (SNVs) directly from spatial transcriptomics data. By leveraging naturally occurring somatic SNVs, SpaceTracer reconstructs cellular phylogenies within native tissue architecture, enabling the mapping of lineage spread, migration, lineage-coupled expression changes and lineage-aware local interactions. Applied to human cutaneous squamous cell carcinoma, it traced tumor initiation and progressions, uncovered widespread pre-invasive migration of dedifferentiated epithelial cells and characterized mutant B cells migrating from tertiary lymphoid structures (TLS) into the tumor boundary. The framework also reconstructed developmental lineages across multiple tissues and identified tissue-resident mutant immune cells. SpaceTracer thus provides a perturbation-free platform for high-resolution spatiotemporal lineage tracing, offering a transformative tool for elucidating complex biological systems--especially tumor-immune ecosystems--with direct implications for advancing cancer immunotherapy.

bioinformatics↗

bioRxiv2026

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↗

bioRxiv2026

A selective Cullin 3 RING E3 ligase inhibitor attenuates hyperglycemia via dual insulin sensitizing and insulinotropic action

Hyperglycemia is a hallmark of type-2 diabetes and a key pathogenic driver of diabetic complications. Cullin RING E3 ligases (CRLs) are multi-subunit E3 ubiquitin ligases that mediate cellular protein turnover. The activity of CRLs requires cullin neddylation, a post-translational modification that can be pharmacologically targeted with therapeutic potentials. By using hyperinsulinemic-euglycemic clamp analysis, we discover that pan neddylation inhibitor exerts both insulin sensitization effect in liver and muscle and insulinotropic effect in pancreatic {beta} cells. This dual action is mediated by Cullin 3 (Cul3), a member of the 7 canonical cullin family proteins. DI-1859, a selective Cul3 neddylation inhibitor, effectively protects against hyperglycemia in obese mice. DI-1859 enhances insulin signaling by preventing Cul3-mediated insulin receptor substrate degradation in liver and muscle cells. DI-1859 increases insulin secretion in a glucagon-like peptide-1-independent manner in mice and directly potentiates glucose-stimulated insulin secretion in INS-1 832/13 {beta} cells and human islets. Mechanistic studies reveal that DI-1859 does not promote glycolytic flux or bioenergetics function but potentiates glucose-stimulated insulin secretion via mechanisms involving RhoA activation and cytoskeleton remodeling in {beta} cells. This study shows that a single agent targeting Cul3 neddylation simultaneously promotes insulin sensitization and insulin secretion to attenuate hyperglycemia in mice. Article Highlightsa. Pan cullin neddylation inhibitors exhibit potent hypoglycemic effect. b. The target organs and mechanisms underlying the hypoglycemia effect of cullin pan neddylation inhibitors are incompletely understood. c. We found that inhibition of Cul3 leads to a dual insulin sensitization and insulinotropic effect. d. Selective inhibition of Cul3 neddylation is a feasible approach to lower hyperglycemia.

physiology↗

bioRxiv2026

Transforming macromolecular structures into simulations of self-assembly

Macromolecular self-assembly is a fundamental process in living and engineered systems, producing molecular machines like the ribosome or highly symmetric viral capsids. Thanks to sources like the Protein Data Bank (PDB) and AlphaFold3, the final target complexes are often known, but these static structures do not provide information on the self-assembly process directly. Computational models provide critical tools to study these essential pathways of self-assembly, but substantial coarse-graining of assembly subunits is necessary to achieve computational tractability of these relatively slow processes while retaining multi-valency. While rule-based or local interactions overcome the often-prohibitive enumeration of all possible assembly intermediates, they must ensure global structural constraints are met. We here demonstrate ioNERDSS, a user-friendly Python package that transforms 3D atomic structures into coarse-grained models for immediate simulation with the stochastic reaction-diffusion NERDSS software, converting static structures into time-resolved assembly trajectories. NERDSS uses rule-based interactions to simulate multi-component self-assembly at the minutes timescales and without limits to complex size or growth pathways. With ioNERDSS, each protein chain is defined by a rigid subunit with discrete interfaces and explicit orientational constraints that enforce a structured assembly. Repeated subunits (such as in viral capsids) are regularized to preserve the target topology across distinct stochastic assembly pathways, supporting assembly of structures with thousands of subunits. We initialize pairwise binding affinities using open-source machine-learned prediction tools, and our default coarse-grained (CG) models are all constrained by thermodynamic reversibility to reach an equilibrium steady-state. The binding rates and subunit abundances necessary to perform simulations are initialized at default values but represent the key variables (along with affinities) that cells and thus users would tune to control productive assembly. Benchmarking on over 40,000 PDB structures shows that the majority of CG models stochastically assemble into target structures. The ioNERDSS Python library links directly to open-source tools for visualization and analysis to facilitate fast and user-friendly structure validation and analysis of output for thermodynamic, kinetic, and nonequilibrium drivers of macromolecular self-assembly.

biophysics↗

bioRxiv2026

Myeloid CD209 impairs T-cell activation by inducing ICAM-2-ERM-dependent cortical stiffening

Resistance to PD-1-based immunotherapy remains a major challenge in cancer treatment, especially in immunologically "cold" tumors characterized by T-cell exclusion and impaired effector function. Tumor-associated myeloid cells are important mediators of this resistance, but whether they directly suppress T-cell immunity through mechanical regulation remains unclear. Here, we identify DC-SIGN (CD209), a myeloid-expressed C-type lectin receptor, as a mechanosuppressive regulator of antitumor T-cell immunity. DC-SIGN is selectively enriched in tumor-infiltrating M2-like macrophages and monocytes, and its expression is associated with poor clinical response to PD-1 blockade and elevated TIDE scores across multiple cancer types. Mechanistically, DC-SIGN directly engages ICAM-2 on T cells and activates ROCK1-ERM signaling. This interaction increases T-cell cortical stiffness, destabilizes T cell-antigen-presenting cell interactions, and attenuates T-cell receptor signaling. Blocking the DC-SIGN-ICAM-2-ERM pathway restores T-cell activation and promotes CD8+ T-cell infiltration and effector function in mouse, humanized, and ex vivo human tumor systems. Importantly, DC-SIGN blockade overcomes resistance to PD-1-based immunotherapy in refractory and immunologically "cold" tumor models, and further enhances the response to PD-1 inhibition. Together, our findings define a myeloid-derived mechanical immune checkpoint and reveal T-cell mechanosuppression as a targetable mechanism of tumor immune evasion and immunotherapy resistance.

immunology↗

bioRxiv2026

Histone 3 lysine 9 dimethylation by the G9a-GLP heterodimer requires intranucleosomal product reading

Repressive histone methyltransferases carry a catalytic ("write") domain and a separate domain specialized for recognizing ("reading") the reaction product. This read-write configuration acts as a positive feedback mechanism for epigenetic maintenance and the growth of repressive chromatin domains. Feedback exhibits as catalytic stimulation and is understood to act towards a proximal (trans) nucleosome. Whether this stimulation affects a specific methylation transition and whether it is restricted to trans-stimulation remains opaque. Here, we dissect the positive feedback in the heterodimeric histone 3 lysine 9 (H3K9) mono- and dimethlyase G9a-GLP, which carries two catalytic SET and two product-reading Ankyrin repeat (ANK) domains. We find that reading by both ANK domains is required for H3K9 di-, but not monomethylation on nucleosomes and for tight binding to them. As this read-writing occurs on dilute mononucleosomes, we propose that intranucleosomal feedback occurs for G9a-GLP. Swapping the ANK domains results in loss of dimethylation while maintaining nucleosome binding, indicating catalytic coupling of nucleosome methylation intermediates to reading. Crosslinking mass spectrometry reveals specific G9a surfaces that contact nucleosomal methylation intermediates. Structural approaches reveal how these surfaces position the G9a ANK domain on the methylation-intermediate nucleosome and stabilize G9a-GLP on chromatin during the reaction.

biochemistry↗

bioRxiv2026

LONP-1 deficiency causes dysregulated protein synthesis within mitochondria that is restored by mitoribosomal mutations

Mitochondrial homeostasis is maintained by multiple molecular chaperones and proteases located within the organelle. The mitochondrial matrix-localized protease LONP-1 degrades oxidatively damaged or misfolded proteins. Importantly, LONP-1 also regulates mitochondrial DNA replication. Here, we show that mutations in C. elegans that impair LONP-1 function cause dysregulation of mitochondrial DNA replication, mitochondrial RNA transcription and protein synthesis within the mitochondrial matrix. LONP-1 deficient worms had reduced levels of oxidative phosphorylation proteins despite increased mtDNA-encoded protein synthesis. Via a forward genetic screen, we identified three mutations that restored mitochondrial function and the rate of development in lonp-1 mutants to levels comparable to those in wildtype worms. Interestingly, all three suppressor mutations were found in genes encoding mitochondrial ribosome proteins. A point mutation in the mitochondrial ribosome protein MRPS-38 restored oxidative phosphorylation in lonp-1 mutant worms. Combined, our results suggest that LONP-1 regulates mitochondrial protein synthesis and that the suppressor mutations within MRPS-38 or MRPS-15 enhance oxidative phosphorylation complex assembly by slowing translation.

cell biology↗