Biology subjects

Lee, S. J.

Publications and source records attributed to Lee, S. J..

At least 19 recordsLinked to original sources

bioRxiv2026

Non-invasive Vagal Nerve Stimulation as a Potential Treatment for Repetitive Blast Trauma

BackgroundPolytrauma caused by exposure to high explosives (blast) is increasingly common among military personnel and civilians yet treatment for related post-concussive symptoms and chronic behavioral dysfunction is limited. Therapeutic targets following these injuries are typically focused on the central nervous system, with less attention placed on potentially more accessible peripheral targets. Vagus nerve stimulation (VNS) has recently gained traction as a potential therapeutic modality but has yet to be examined in a blast trauma setting. MethodsOur well-established blast overpressure model was utilized to induce repetitive (3x) blast trauma, followed by treatment with non-invasive transcutaneous VNS one hour following each blast exposure in male mice. Acutely following repetitive blast exposure, we measured serum and brain cytokine levels, fecal microbial abundance, and locomotion and anxiety-like behavior in the open field assay. Chronically (1-3 months post blast), mice were assessed for behavioral outcomes related to mild traumatic brain injury (mTBI) and posttraumatic stress disorder (PTSD), including acoustic startle (hyperreactivity), probabilistic discounting (risky decision making), and two-bottle choice test (voluntary alcohol consumption). ResultsVNS treatment following blast exposure decreased acute blast-induced inflammatory response in the blood and brain, especially serum IL-9 and IP-10, and brain MPC-1. Chronic behavior tests demonstrated a VNS-dependent reduction in blast-induced risky decision-making and a decreased intake and preference for ethanol. Conversely, VNS was not effective in preventing acute blast effects on the microbiome or chronic hyperreactivity behaviors measured with acoustic startle. DiscussionThis study identifies the vagus nerve as a novel peripheral target for treating acute and chronic blast-induced dysfunction.

neuroscience↗

bioRxiv2026

Rhizo-PET: A Dedicated PET System for 4D Imaging of Carbon Dynamics in the Rhizosphere

Imaging carbon movements in the rhizosphere is fundamentally limited by high soil heterogeneity, low signal levels, and lack of methodology. We present Rhizo-PET, a dedicated positron emission tomography (PET) imaging and analysis framework designed to characterize the 4D spatiotemporal patterns of tracer distribution in intact plant-soil systems. The system achieved a global energy resolution of 11.93 {+/-} 0.02% FWHM at 511 keV and maintained stable performance over 8 h of continuous acquisition, with a coincidence rate variation of only 0.7%. Spatial resolution reached 1.06 mm near the center of the field of view, establishing a high-fidelity region for root-scale analysis. Dynamic datasets were acquired from live Phaseolus vulgaris plants (N= 3) over 180 min following 11CO2 pulse labeling and reconstructed into 3 min temporal frames. Quantitative analysis across 243 independent regions of interest (ROI) revealed that cumulative tracer accumulation decreases monotonically with radial distance from the root axis, while axial transport delays increase systematically in lower root segments (p <0.001). Hierarchical variability analysis showed that within-plant spatial organization (CVTTP = 0.03) is significantly more stable than inter-plant variation (CVTTP = 0.14), proving that the observed heterogeneity reflects biological spatial organization rather than experimental instability. These results establish Rhizo-PET as a robust, reproducible platform for the non-invasive, time-resolved analysis of carbon dynamics in the rhizosphere under realistic soil conditions.

plant biology↗

bioRxiv2026

Programmable domestication of thermophilic bacteria through removal of non-canonical defense systems

Thermophilic bacteria offer major advantages for industrial biotechnology, yet most remain genetically intractable because cellular defense systems block efficient DNA acquisition. Here, we present a programmable domestication strategy that converts wild Geobacillus strains into genetically tractable thermophilic hosts. We developed the Domestication of Non-Model Bacteria (DNMB) Suite, a multi- omics-guided computational framework that systematically identifies genetic barriers to transformation. DNMB analysis revealed that non-canonical nuclease-based defense systems, including Wadjet II, constitute dominant barriers to DNA uptake in previously intractable Geobacillus strains. Targeted deletion of these loci increased transformation efficiency by up to six orders of magnitude. We further established a hierarchical thermophilic engineering toolkit that integrates plasmid artificial modification, conjugation-assisted DNA delivery, and genome editing using an endogenous CRISPR-Cas9 system. The resulting domesticated strains support stable heterologous expression and tunable genetic control at elevated temperatures. Together, these results establish a generalizable framework for transforming genetically intractable thermophiles into programmable industrial chassis.

bioengineering↗

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

Lipid metabolic suppression accompanies an immunometabolic signature in the spinal cord during chronic neuropathic pain.

Peripheral nerve injury-induced persistent pain hypersensitivity cannot be fully explained by increased neuronal excitability alone. Rather, it is increasingly recognized as a pathological tissue state characterized by sustained glial activation, immune signaling, and synaptic remodeling within the spinal cord. In this context, metabolic remodeling of the spinal cord has emerged as a potentially important feature of neuropathic pain. However, the metabolic patterns associated with this state, and their relationship to underlying molecular programs, remain incompletely defined. Here, we performed GC-MS-based untargeted metabolomic profiling of the spinal cord dorsal horn on day 7 after spinal nerve transection (SNT). To provide orthogonal validation, we integrated pathway-analysis results from four independent spinal cord RNA-sequencing datasets derived from distinct neuropathic pain models and further conducted qPCR-based validation. Metabolic profiling revealed a clear separation between SNT and sham samples, marked by broad depletion of the free fatty acid pool and features consistent with an immunometabolic shift. Consistently, analyses across RNA-sequencing datasets and qPCR validation demonstrated upregulation of immune and inflammatory programs, together with downregulation of fatty acid metabolism and cholesterol homeostasis. Collectively, these findings suggest that persistent neuropathic pain should be interpreted not simply as a consequence of neuronal and immune signaling, but also through the metabolic tissue environment that supports and sustains this pathological state.

neuroscience↗

bioRxiv2025

Dopamine biosynthesis in plants

Dopamine, an essential human neurotransmitter, also plays important roles in plant-microbe interactions and abiotic stress tolerance. While dopamine biosynthesis is well-characterized in mammals, it remains largely unclear in plants. Through metabolite-based genome-wide association studies, we identified two putative polyphenol oxidase genes for dopamine biosynthesis in Brachypodium distachyon, located in the same chromosomal region as two tyrosine decarboxylase genes. Biochemical and knockout mutant analyses demonstrated that dopamine biosynthesis proceeds primarily via tyramine as an intermediate and contributes to plant tissue browning. Homology searches and functional assays indicate that this dopamine biosynthetic pathway is conserved across diverse plant species. This discovery provides valuable insights into plant dopamine biosynthesis with potential applications in reducing food browning, improving stress resilience, and bioengineering valuable compounds.

plant biology↗

bioRxiv2025

Fine-Tuning Protein Language Models Enhances the Identification and Interpretation of the Transcription Factors

Transcription factors (TFs) are pivotal regulators of gene expression and play essential roles in diverse cellular activities. The three-dimensional organization of the genome and transcriptional regulation are predominantly orchestrated by TFs. By recruiting the transcriptional machinery to gene enhancers or promoters, TFs can either activate or repress transcription, thereby controlling gene activity and various biological pathways. Accurate identification of TFs is vital for elucidating gene regulatory mechanisms within cells. However, experimental identification remains labor-intensive and time-consuming, highlighting the necessity for efficient computational approaches. In this study, we present a two-layer predictive framework utilizing protein language models (pLMs) via full fine-tuning and parameter-efficient fine-tuning. The initial layer robustly classifies and identifies transcription factors, while the subsequent layer predicts TFs with a binding preference for methylated DNA (TFPMs). Our approach further incorporates attention weights and protein sequence motifs to enhance interpretability and predictive capability. By leveraging attention mechanisms, we highlight biologically relevant regions of the protein sequences that contribute most strongly to the predictions. Additionally, motif analysis facilitates the identification of conserved sequence patterns that are critical for TF recognition and function. Across both TF and TFPM classification tasks, the inclusion of these features allowed our methods to consistently surpass contemporary models, as demonstrated by independent test results. KeypointsO_LIDeveloped a two-layer predictive framework using protein language models (pLMs) with both full fine-tuning and parameter-efficient fine-tuning methods. C_LIO_LIThe first layer accurately identifies transcription factors (TFs), and the second layer predicts TFs with binding preference for methylated DNA (TFPMs). C_LIO_LIIntegrated attention weights and protein sequence motifs to enhance model interpretability by highlighting biologically relevant sequence regions and conserved patterns. C_LIO_LIAchieved superior performance compared to state-of-the-art methods, validated by independent testing. C_LI Mir Tanveerul Hassan obtained his M.Tech. in Computer Science from the University of Kashmir, India, in 2020, and later earned his Ph.D. in Electronics and Information Engineering from Jeonbuk National University, Jeonju, South Korea. He is currently serving as a postdoctoral fellow at the Jeonbuk RICE Intelligence Innovation Research Center. His research interests encompass computational biology, bioinformatics, and pattern recognition. Saima Gaffar received her B.Tech. and M.Tech. degrees in Computer Science from the University of Kashmir, Srinagar, India, and her Ph.D. in Electronics and Information Engineering from Jeonbuk National University, South Korea. Her research focuses on bioinformatics, computational biology, deep learning, and image processing. Hamza Zahid received his B.S. degree in Mechatronics Engineering from the University of Engineering and Technology, Peshawar, Pakistan. He is currently pursuing the integrated M.S. and Ph.D. degrees in Electronics and Information Engineering at Jeonbuk National University, South Korea. His primary research interests include the applications of artificial intelligence in computational drug discovery. Sang Jun Lee received his B.S., M.S., and Ph.D. degrees in Electrical Engineering from POSTECH, South Korea. Following his doctoral studies, he worked as a senior researcher at the Samsung Advanced Institute of Technology (SAIT). He is currently an Associate Professor in the Division of Electronics and Information Engineering at Jeonbuk National University, South Korea. His research interests include image analysis, deep learning, and medical image processing.

bioinformatics↗

bioRxiv2025

Development of Recombinant Anti-TLR2 Antibodies and PLGA Nanoparticle-based Gene Therapy for the Treatment of Neuropathic Pain

Neuroinflammation is a key contributor to neuropathic pain, with microglial Toll-like receptor 2 (TLR2) playing a central role in initiating and sustaining proinflammatory responses. However, existing TLR2-targeting antibody therapies are limited by poor delivery to the central nervous system and short-lived efficacy. We developed a non-viral gene therapy strategy using biodegradable poly(lactic-co-glycolic acid) (PLGA) nanoparticles (NPs) to deliver recombinant anti-TLR2 antibody genes. High-affinity nanobody and single-chain variable fragment candidates were selected through phage display screening and shown to suppress TLR2-dependent signaling both in vitro and in vivo. In mouse models of neuropathic pain, a single intrathecal administration of PLGA NP-encapsulated antibody genes produced robust and sustained analgesia, accompanied by reduced glial activation and proinflammatory cytokine expression. These findings demonstrate a modular NP-based platform for sustained antibody expression in the central nervous system and establish its potential for the treatment of chronic pain driven by innate immune activation.

neuroscience↗

bioRxiv2025

Reverse target screening identifies putative L-AAA targets in astrocyte-selective toxicity

L--aminoadipic acid (L-AAA) is widely used to ablate astrocytes, yet the molecular basis of its cell-type selectivity remains unclear. We combined structure-based reverse screening with an enantiomeric control D--aminoadipic acid (D-AAA), network propagation on a signed, directed interactome, and cell-type-resolved transcriptomics to nominate mechanistic targets of L-AAA. Two independent AlphaFold-enabled screens converged on a small set of proteins; integrating apoptosis connectivity and astrocyte enrichment prioritized pyruvate carboxylase (PC). Docking placed L-AAA in the pyruvate/acetyl-CoA pocket of PC and supported stereoselective engagement over D-AAA. These results motivate a testable model in which L-AAA limits PC-driven anaplerosis in astrocytes, constraining oxaloacetate/aspartate supply and redox buffering to lower the threshold for apoptosis. The workflow generalizes to polar metabolites that evade standard chemoproteomics and reframes how L-AAA-based astrocyte ablation should be interpreted. SignificanceL--aminoadipic acid is a staple tool for selective astrocyte ablation, but its molecular effectors have remained elusive. By unifying AlphaFold-enabled reverse screening with network-level apoptosis inference and single-cell expression filters, we nominate pyruvate carboxylase as a plausible mediator of L-AAA toxicity. The resulting metabolism-centric mechanism--partial inhibition of glial anaplerosis that depletes aspartate and erodes NADPH-glutathione buffering--offers concrete, falsifiable predictions and clarifies how L-AAA should be interpreted in vivo and in vitro. Our pipeline is broadly applicable to small, highly polar metabolites that are challenging to profile by conventional target-deconvolution approaches.

biochemistry↗

bioRxiv2025

Persistence of vestibular function in the absence of glutamatergic transmission from hair cells

Quantal synaptic transmission in vestibular end-organs is glutamatergic. Although genetic deletion of Slc17a8 (termed Vglut3) leads to deafness in mice, the dependence of vestibular function on VGLUT3-mediated quantal transmission is unknown. Here, we investigated the vestibular phenotype of Vglut3-/- mice at the cellular, systems, and behavioral levels. The type-II vestibular hair cells (VHCs) in Vglut3+/+mice were strongly immunoreactive for VGLUT3, while type-I VHCs showed poor immunoreactivity. In Vglut3-/- mice quantal synaptic transmission in utricular calyces was reduced in rate and amplitude by > 95%. In vivo recordings of spontaneous activity in the vestibular nerve revealed similar action potential rates and regularity in Vglut3+/+and Vglut3-/- mice, suggesting a divergent underlying mechanism compared to the silent Vglut3-/- auditory nerve. In behavioral studies, Vglut3-/- mice did not exhibit considerable sensorimotor or balance deficits. Collectively, these data support the view that non-quantal transmission is the predominant mode of neurotransmission between type I VHCs and vestibular calyceal afferent neurons. We propose that non-quantal transmission alone underlies the apparently normal vestibular nerve physiology and behavioral function in Vglut3-/- mice.

neuroscience↗

bioRxiv2025

Scalable 3D Bioprinting of Human Islets in a Pancreatic Decellularized Extracellular Matrix-Enriched Bioink for Beta-Cell Replacement Therapy

Allogeneic cell transplantation such as beta-cell replacement for treatment of type 1 diabetes (T1D) is constrained by poor graft survival and functionality, immune rejection, and the lack of scalable biomanufacturing processes. Here, we engineered functional human islet constructs that replicate the physiomimetic human pancreatic microenvironment by employing a clinically-scalable 3D bioprinting system. To support human islet viability and function, we developed alginate-based bioinks incorporating human pancreatic decellularized extracellular matrix (dECM). These bioink formulations were optimized for shear-thinning properties for extrusion of human islets, as well as selective permeability that supports nutrient and therapeutic molecule exchange. Extrusion-based printing parameters were refined to minimize shear stress-induced damage to human islets. The resulting bioprinted pancreatic constructs demonstrated robust structural integrity, high human islet viability (>85%), and long-term glucose-stimulated insulin secretion (GSIS) over a 21-days in vitro culture period, even at a high islet packing density (10,000 islet equivalent/mL) while free islet controls displayed a significant functional decline. The higher performance of bioprinted islets maybe attributable to the supportive 3D dECM-rich microenvironment mitigating culture-induced stress by recapitulating the islet pancreatic niche. This scalable 3D dECM-alginate bioprinted platform represents a new advanced functional material for advancing clinically translatable bio-artificial pancreas therapies for T1D.

bioengineering↗

bioRxiv2025

Cancer-associated metabolic alterations facilitated by astrocyte glycogenolysis mediate neuropathic pain chronicity

Chronic pain remains a major unmet medical challenge, yet the metabolic checkpoints that govern its persistence are poorly defined. Astrocytes are increasingly recognized as chemically programmable hubs that tune neuronal excitability through metabolic circuits. Building on reports that astrocyte-neuron lactate shuttling (ANLS) in the anterior cingulate cortex (ACC) supports chronic pain, we asked how astrocytic metabolic states evolve over the course of pain chronification. Using untargeted metabolomics of the ACC combined with GFAP-RiboTag-based astrocyte-specific transcriptomics, we provide a time-resolved map of astrocytic metabolism across the transition from acute nociception to chronic neuropathic pain. This analysis reveals a biphasic glycogen program--an acute glycogenolysis-triggered glycogen supercompensation--that culminates in the emergence of a Warburg-like metabolic signature with tissue acidification associated with sustained lactate shuttling and persistent circuit activation. Using glycogen phosphorylase inhibitors (GPI-1, GPI-2) as pharmacological probes, we show that early glycogenolysis blockade attenuates this Warburg-like shift, partially normalizes ACC metabolic signatures, and reduces long-lasting mechanical hypersensitivity, without impairing acute nociceptive sensitization. These findings identify astrocytic metabolic reprogramming as a pharmacologically tractable circuit-level process and nominate glycogenolysis as an upstream biochemical gate and potential therapeutic control point in neuropathic pain. HIGHLIGHTSMost experimental models of chronic pain emphasize progressive sensitization, yet few have identified a chemically tractable switch that converts transient nociception into a persistent cortical state. Here, we propose astrocytic glycogenolysis as such a switch--a gatekeeper process whose brief engagement can reconfigure neuroglial metabolism toward a Warburg-like signature that stabilizes hyperexcitable circuit dynamics. By leveraging small-molecule glycogen phosphorylase inhibitors as mechanistic precision probes, we move beyond correlation to delineate a pathway-level control architecture that can be transiently perturbed to dissociate acute nociceptive processing from pain chronification. This framework reframes astrocytes from metabolic support cells to state-setting regulators of cortical excitability and positions glycogenolysis as a therapeutically actionable leverage point. More broadly, our findings underscore a methodological opportunity: applying chemical biology to neuroglial metabolism can expose governing checkpoints that are often obscured by descriptive physiology, enabling mechanism-first, pathway-directed intervention strategies across neurological disease contexts.

neuroscience↗

bioRxiv2025

Spatial transcriptomics AI agent charts hPSC-pancreas maturation in vivo

Spatial transcriptomics has revolutionized our understanding of tissue organization by simultaneously capturing gene expression and spatial localization within intact tissues. However, analyzing these increasingly complex datasets requires specialized expertise across computational biology, statistics, and biological context. To address this challenge, we introduce the Spatial Transcriptomics AI Agent (STAgent), an autonomous multimodal agentic AI that integrates multimodal large language models (LLMs) with specialized computational tools to transform weeks-long analysis tasks into minutes of automated processing. Unlike conventional machine learning approaches that are limited to narrow, predefined tasks, STAgent leverages the emergent capabilities of multimodal LLMs - such as flexible reasoning, contextual understanding, and cross-modal integration - which allow it to adapt to novel data, execute multi-step analyses, and generate biologically meaningful insights with minimal human input. STAgent enables autonomous deep research through integrated capabilities, including dynamic code generation for complex analytical workflows, visual reasoning for interpreting spatial patterns, real-time retrieval of relevant peer-reviewd scientific literature, and synthesis of comprehensive, actionable reports. We applied STAgent to investigate the in vivo maturation of human stem cell-derived pancreatic cells (SC-pancreas) transplanted into immunodeficient mice. We generated single-cell spatial transcriptomics data spanning multiple developmental timepoints. STAgent autonomously (1) identified the maturation of initially scattered endocrine cells into well-defined islet-like structures, with predominantly peripheral -cells surrounding {beta}-cell cores supported by an expanding mesenchymal network; (2) revealed strengthening endocrine-endocrine cell interactions over time and, through context-aware gene set analysis, uncovered spatially resolved biological processes driving maturation; (3) unlike traditional analytical approaches, STAgent offers mechanistic explanations of spatial patterns, contextualizing findings with relevant literatures and developing cohesive insights into human pancreatic development. This agentic approach establishes a new paradigm in spatial transcriptomics analysis by substantially lowering the expertise barrier and reducing analysis time, accelerating biological and biomedical discovery.

genomics↗

bioRxiv2025

Precise, Specific, and Sensitive De Novo Antibody Design Across Multiple Cases

The precision design of antibodies, which naturally recognize diverse molecules through six variable loops, remains a critical challenge in therapeutic molecule discovery. In this study, we demonstrate that precise, sensitive, and specific antibody design can be achieved without prior antibody information across eight distinct target proteins. For each target, binders were identified from a yeast display scFv library of approximately 106 sequences, constructed by combining 102 designed light chain sequences with 104 designed heavy chain sequences. Binders with varying binding strengths were identified for all eight targets, including a case where no experimentally resolved target protein structure was available, demonstrating the highest level of precision compared to previous de novo antibody design reports. To further validate the designed antibodies, they were characterized in the IgG format for five distinct targets. The antibodies exhibited favorable developability properties, positioning them as promising hit or lead candidates. Notably, for one target in particular, the IgG-formatted antibodies exhibited affinity, activity, and developability, comparable to a commercial antibody, highlighting the sensitivity of the design method. Furthermore, binders capable of distinguishing closely related protein subtypes or mutants were identified, demonstrating that the method can achieve high molecular specificity. Cryo-EM analysis experimentally validated the designs accuracy by confirming that the key binding interactions were precisely as designed. These findings underscore the effectiveness of precision molecular design based on atomic-accuracy structure prediction. This study establishes computational antibody design as a viable approach for generating therapeutic molecules with tailored properties, with promising potential for achieving the efficacy and safety required for successful therapeutics.

bioengineering↗

bioRxiv2025

Novel DNA endonuclease activity of human ERK1 protein

ERK1 is a key kinase in the mitogen-activated protein kinase pathway, which transduces extracellular signals into cellular responses. Following triggering of the pathway, cytosolic ERK1 is phosphorylated, translocates into the nucleus, and activates DNA-bound transcription factors and target genes. This study reports a novel, non-canonical role of human ERK1 as a DNA endonuclease. It catalyzes single-strand DNA breaks in sequence-unspecific yet, topology-sensitive manners. ERK1 catalysis requires magnesium ions and no ATP consumption. Comprehensive biochemical and in silico structural analyses indicate that a Mg2+ pocket, including a residue N171, which is allosterically modulated by the N-terminal domain, is important for DNA substrate binding and catalysis. Fluorescence imaging analysis suggests that ERK1 may interact with cytoplasmic DNAs in molecular condensates and destabilize them. Collectively, this study reveals an unprecedented role of ERK1 in nicking DNA molecules, which highlights the potential to regulate the fate of cytoplasmic DNAs.

molecular biology↗

bioRxiv2025

KHSRP-mediated Decay of Axonally Localized Prenyl-Cdc42 mRNA Slows Nerve Regeneration

The small GTPase CDC42 promotes axon growth through actin filament polymerization and this growth is driven by axonal localization of the mRNA encoding the prenylated CDC42 isoform (Prenyl-Cdc42). Here, we show that axonal Prenyl-Cdc42 mRNA transport and translation are decreased by growth-inhibiting stimulation and increased by growth-promoting stimulation. In contrast, axonal RhoA mRNA transport and translation are increased by growth inhibition but unaffected by growth promotion. Localized increase in KHSRP in response to growth inhibitory stimulation, through elevation of intracellular Ca2+, promotes decay of axonal Prenyl-Cdc42 mRNA. Distinct 3UTR motifs regulate transport and stability of axonal Prenyl-Cdc42 mRNA. KHSRP protein binds to a Prenyl-Cdc42 mRNA motif within nt 801-875 and the mRNA is remarkably increased in axons of Khsrp-/- mice. Selective depletion of Prenyl-Cdc42 mRNA from axons reverses the accelerated axon regeneration seen in Khsrp-/-mice.

neuroscience↗

bioRxiv2025

Molecular convergence analyses identify candidate genes for low susceptibility to the ash dieback pathogen

Non-native pests and pathogens increasingly threaten global forest ecosystems. An understanding of the genomic basis of low susceptibility in the natural hosts of such pests and pathogens, with which they share a coevolutionary history, can enhance restoration efforts by facilitating the selection of individuals carrying beneficial alleles. Within the genus Fraxinus (ash trees) low susceptibility to the fungal pathogen Hymenoscyphus fraxineus, the causative agent of the ash dieback disease (ADB) epidemic, is observed in three independent lineages of known or plausible natural hosts. Here, we seek to elucidate the genetic basis of this trait, which is key to the future survival of Fraxinus excelsior populations in Europe, using a molecular convergence approach. We analysed 4,300 protein-coding loci for amino acid convergence between lineages with low susceptibility. After filtering for potential false positives, we find 62 genes that have a signal of excess convergence between Fraxinus lineages with low ADB susceptibility. Eleven of these loci have additional evidence for a role in defence against fungal pathogens, with a further 17 linked to more general immunity or defence, or other functions relevant to the response against ADB such as cell wall biogenesis. The candidate loci discovered here complement those reported by previous genomic studies of F. excelsior, and can be targeted in efforts to mitigate the devastation caused by this deadly disease by informing breeding programmes involving hybridisation and marker-assisted back-crossing. Our study demonstrates the benefit of genomic analyses incorporating natural hosts, when seeking to tackle biotic threats to naive host populations. Significance StatementKnowledge of the genomic basis of variation in susceptibility to emerging forest pests and pathogens can provide the foundation for interventions to mitigate such threats, but studies restricted to the analysis of naive host populations may miss relevant genomic loci that could be present in coevolved hosts. Using comparative genomic analyses for the detection of molecular convergence between lineages of ash trees with low susceptibility to ash dieback, incorporating known and plausible natural hosts, we detect novel candidate loci for defence against this disease. Our findings can be used to support efforts to tackle one of the worlds worst forest pathogens and demonstrate the value of integrating genomic data from coevolved hosts when aiming to identify the basis of low susceptibility to biotic threats.

evolutionary biology↗

bioRxiv2025

Heartbeat-like dynamics drives oxygen activation in methane monooxygenase

Soluble methane monooxygenase (sMMO) is an enzyme that hydroxylates methane (CH4), a potent greenhouse gas, at non-heme di-iron active sites under atmospheric conditions. The regulatory component (MMOB) is essential for the catalytic activity of hydroxylase (MMOH) as it induces conformational changes in the active site and facilitating substrate ingress. Recent advances in cryogenic electron microscopy (cryo-EM) have enabled us to elucidate the high resolution picture of sMMO catalytic mechanism. We describe the 2.85 [A] cryo-EM structure of MMOH-MMOB, with one equivalent of MMOB bound to MMOH (H-1B), which is in contrast with previously solved crystal structures. MMOB allosterically regulates the MMOH protomer ({beta}{gamma}) and induces conformational changes that propagate from the surface to the di-iron coordination site. The N-terminal region of the MMOH {beta}-subunit (NT-H{beta}) stabilizes helices essential for iron coordination and oxygen activation. The MMOB-bound protomer (HBA, {beta}{gamma}B) presents the first structural report of a 2.7 [A] Fe{middle dot}{middle dot}{middle dot}Fe distance, while the non-MMOB-bound protomer (HBB, {beta}{gamma}) and MMOH display a 3.1 [A] distance. The coordination of Fe-ligands is maintained by the structural stabilization provided by the {beta}- and {gamma}-subunits of MMOH. This novel cryo-EM structure reveals new coordination environments, offering crucial mechanistic insights into sMMO catalysis.

biochemistry↗