Biology subjects

Han, D.

Publications and source records attributed to Han, D..

At least 19 recordsLinked to original sources

bioRxiv2026

An interferon-like off-switch in invertebrates: Vago4 downregulates Domeless to restrain JAK/STAT signaling

Whether invertebrates possess a functional interferon (IFN)-like system remains controversial, as canonical IFN ligands and their receptors are absent from invertebrate genomes. Although Vago proteins in Drosophila and shrimp are compelling functional analogs of IFN, direct evidence for a canonical cytokine-receptor axis and, importantly, for how such signaling is restrained to prevent excessive immune activation, has been lacking. Here, we identify Vago4 as a bona fide ligand of Domeless, the canonical type I cytokine receptor upstream of JAK/STAT signaling. Vago4 binds the extracellular CBM1 and CBM2 domains of Domeless, triggering receptor endocytosis followed by lysosomal trafficking and K27-linked ubiquitination-dependent proteasomal degradation. This ligand-induced receptor downregulation serves as a negative feedback mechanism that restrains excessive JAK/STAT activation. During acute Vibrio infection, Vago4 silencing accelerated shrimp mortality, whereas recombinant Vago4 alleviated inflammatory lesions and oxidative stress, enhanced phagocytosis, and improved survival, phenocopying JAK or STAT knockdown. Thus, by downregulating Domeless, Vago4 limits immunopathology and defines an IRF-Vago4-Domeless-JAK/STAT IFN-like axis in invertebrates, offering new insight into the evolution of IFN-mediated immune regulation.

immunology↗

bioRxiv2026

Predicting conformational changes induced by biomolecular interactions

Biomolecular interactions trigger structural changes of protein complexes essential for cellular signaling, regulation, and drug action. Modern co-folding models can now generate detailed structures of multi-component complexes directly from sequence. However, recent evaluations reveal that they frequently fail to capture specific conformational states induced by a ligand or partner. Here, we show that explicitly modeling the structural transition from an unbound to a bound state, rather than generating the bound complex alone, better resolves these interaction-induced states. Our generative learning framework, K-Fold, transforms independently predicted unbound component priors into an assembled complex through an ultrafast diffusion bridge, operating entirely without multiple sequence alignments. By eliminating co-evolutionary dependencies, K-Fold accurately recovers non-coevolved interfaces in antibody-antigen and targeted-degrader complexes, as well as ligand-directed regulatory states in GPCRs and kinases. Furthermore, by coupling this diffusion bridge with diverse monomeric equilibrium ensembles, K-Fold provides a computationally tractable foundation for sampling complex multi-state landscapes without retraining. These results demonstrate that formulating molecular assembly as an explicit structural transition moves structure prediction beyond static geometries toward capturing biomolecular dynamics.

molecular biology↗

bioRxiv2026

ERK signaling integrates multiple mechanisms to drive cortical evolutionary expansion

A critical first step in human evolutionary divergence from chimpanzees and other primates is the production of greatly increased numbers of cortical pyramidal neurons during development and over evolutionary time. This expansion underpins the enlarged human cerebral cortex and, consequently, higher-order cognition and consciousness. However, the cellular and molecular mechanisms driving this progressive increase in cortical neuron number remain incompletely understood. Here we show that elevated ERK signaling in human cortical radial glia (RGs), relative to mouse RGs, arises from evolutionary changes in the developmental expression of existing shared genes. Using the Emx1-Cre line to overexpress MEK1DD, a constitutively active mutant of rat MAP2K1, we found that enhanced ERK signaling in mouse cortical RGs upregulates cAMP-PKA signaling, along with promoting self-renewal, expanding the RG pool, and accelerating cell cycle progression. Conversely, overexpression of PKA signaling in mouse cortical RGs via in utero electroporation of constitutively active PRKACA mutants (L206R or W196G) reduces ERK activity, prolongs the cell cycle, suppresses SHH-SMO and YAP/TAZ pathway activity, and blocks ependymal gliogenesis. Together, our results demonstrate that ERK and PKA signaling in cortical RGs engage a dynamic balance of synergistic and antagonistic interactions. This interplay couples evolutionarily enhanced ERK and PKA activities to increased cortical RG numbers, prolonged cell cycle progression, and an extended neurogenic period, which collectively culminate in a marked increase in neuronal production. We conclude that heightened ERK pathway activity in cortical RGs serves as a central driver of progressive neocortical expansion across mammalian evolution. Significance StatementThe human brains extraordinary cognitive abilities stem from a dramatic increase in cortical neuron numbers during evolution. This study reveals that enhanced ERK signaling in human cortical radial glia neural stem cells, relative to other primates, is a key driver of this expansion. By manipulating this pathway in mice, we demonstrate that ERK coordinates multiple mechanisms--including self-renewal, cell cycle acceleration, and a dynamic interplay with PKA signaling--to boost neuronal output. These findings identify a core molecular axis underlying mammalian cortical evolution and provide a framework for understanding how the human cortex acquired its unique size and, consequently, its remarkable complexity.

developmental biology↗

bioRxiv2026

From Hodgkin-Huxley to Pretrained Neural Inference AI

High-density probes record from thousands of neurons simultaneously, yet resolving single-neuron identity remains an illposed inverse problem. While detailed simulations precisely characterize the biophysical forward process, their utility for interpreting brain signal remains unclear. Here we show that biophysical simulations of population neuronal electrical signals serve as an effective bridge between theory and experiment. By pre-training artificial neural networks exclusively on large-scale synthetic data, we demonstrate robust zero-shot generalization across diverse brain regions, experimental paradigms and species, enabling the accurate inference of single-unit activities and cell-type properties without exposure to real data. Further-more, uncovering a substantial population of functionally competent but weakly active neurons systematically obscured by conventional heuristics, our framework resolves a long-standing discrepancy regarding ocular dominance in mouse primary visual cortex. These findings establish biophysical simulations as a reference standard, bridging the gap between theoretical understanding and experimental observation through data-driven inference.

neuroscience↗

bioRxiv2026

Metabolic signals regulate resuscitation speed of antibiotic persister bacteria during infection

All living organisms adjust their metabolism in response to environmental changes. Under unfavorable conditions, organisms enter a state of dormancy by halting metabolism, enabling survival. Dormant bacteria become highly tolerant to antibiotics-a phenomenon called persistence. Here, we demonstrate that selective metabolic reprogramming controls the resuscitation speed of persister after antibiotic exposure. Using multi-omics and in silico modeling, we found that dormant bacteria reprogram metabolic pathways to modulate persister awakening. Accumulation of L-serine and reduction of arginine drive rapid resuscitation. L-serine promotes cysteine biosynthesis and motility while reducing energy metabolism to facilitate rapid resuscitation. In contrast, arginine slows regrowth from dormancy by enhancing ethanol-aldehyde and energy metabolism. L-serine and arginine can, respectively, promote or inhibit the regrowth of antibiotic persister cells in macrophages and mouse models, and regulate the awakening speed of Salmonella, E. coli, and methicillin-resistant Staphylococcus aureus (MRSA). These findings suggest new strategies to target chronic bacterial infections. TeaserL-serine speeds and arginine slows the awakening of antibiotic persisters, revealing targets for chronic infection.

microbiology↗

bioRxiv2026

Vagal dopaminergic afferents link interoception to trigeminal pain modulation

The vagus nerve conveys interoceptive information, yet how specific vagal sensory afferents regulate pain remains unclear. Here, we tested whether vagus nerve stimulation (VNS) modulates temporomandibular disorder (TMD)-related pain. In a mouse model of TMD, auricular VNS (aVNS) attenuated temporomandibular joint (TMJ) pain behaviors and suppressed sensitization of trigeminal nociceptors. We identified a subset of vagal sensory afferents with dopaminergic features that was sufficient to mediate these effects, as selective activation of these afferents recapitulated the analgesic actions of aVNS. These findings highlight an underappreciated peripheral interoceptive pathway and provide a mechanistic framework for targeted neuromodulation in chronic craniofacial pain.

neuroscience↗

bioRxiv2026

Chemical activation of mitophagy via the N-degron pathway alleviates mitochondrial neuropathies

Pharmacological activation of mitophagy offers a promising strategy to eliminate dysfunctional mitochondria. We previously identified the autophagy receptor p62/SQSTM1 as an N-recognin whose activity is enhanced by Arg/N-degrons. Here, we show that Arg/N-degrons generated by ATE1-encoded R-transferase regulate p62-mediated mitophagy by promoting its recruitment to damaged mitochondria. Structural modification of Arg/N-degrons yielded ATB1071, a 443.5-Da orally bioavailable compound that activates p62 and induces stress-selective mitophagy through both Parkin-independent pathways involving NIPSNAP1 and NIPSNAP2, and a Parkin-dependent pathway involving the substrate EBP1/PA2G4. In Ndufs4-/- mice, a Leigh syndrome (LS) model, ATB1071 induced mitophagy in the brain and exerted therapeutic benefits by reducing neuroinflammation, improving muscle strength and neuromuscular coordination, and extending lifespan. In cerebral ischemia-reperfusion (IR) model mice, ATB1071 reduced infarct volume and neuronal death, and ameliorated multiple behavioral deficits through EBP1-dependent mitophagy. Pharmacokinetic (PK) and toxicological analyses support ATB1071 as a preclinical candidate for mitochondria-associated neurological injury.

cell biology↗

bioRxiv2026

A Cationic Amphiphilic Drug (CAD) Defense System in the Nematode Caenorhabditis elegans

Cationic Amphiphilic Drugs (CADs) severely disrupt lysosomal function, which leads to a cellular pathology characterized by excess phospholipids called phospholipidosis. Through a forward genetic screen and mining of published datasets, we discovered that CADs induce the expression of the CYP-35B family of cytochrome P450s and the PGP-13 p-glycoprotein pump via the nuclear receptors NHR-70 and NHR-107 in the nematode C. elegans. A pgp-13 fluorescent reporter revealed hundreds of human drugs that upregulate the CAD defense system in vivo. Chemoinformatic analyses indicate that the pgp-13 reporter may be useful in identifying CADs that have pathogenic potential in humans. Mutant analyses coupled to metabolomics and structural modeling show that the CYP-35Bs are necessary and sufficient for CAD metabolism, and that CYP-35B2 D311 is key in mediating electrostatic interactions with the positively charged CADs. We also show that CAD metabolites are effluxed via PGP-13 acting partially redundantly with PGP-14 and that an intact defense system is necessary to resist CAD-induced pathology. Finally, we demonstrate that bacteria that likely cohabitate with C. elegans in nature trigger the CAD defense system, providing a plausible explanation for why a pathway that protects against anthropogenic small molecules exists in nematodes.

pharmacology and toxicology↗

bioRxiv2025

Ensemble-DeepSets: an interpretable deep learning framework for single-cell resolution profiling of immunological aging

Immunosenescence increases susceptibility to infection and reduces vaccine responsiveness, yet bulk transcriptomic clocks obscure the cellular heterogeneity underlying this process. Here, we present IDEAL-Age, an interpretable deep learning framework that operates directly on single-cell PBMC transcriptomes. Benchmarking against 31 methods across independent cohorts demonstrates superior predictive performance. The frameworks interpretability uncovers linear and non-linear transcriptomic dynamics that reveal phase-specific physiological transitions, and identifies pro-youthful or pro-aging cellular contributions. Application to systemic lupus erythematosus (SLE) reveals accelerated immunological aging driven by interferon-associated monocyte shifts. IDEAL-Age establishes a high-resolution computational framework for deciphering systemic immune aging.

bioinformatics↗

bioRxiv2025

Multiparametric Assessment of TNNI3 Variant Phenotypes in Human iPSC-Cardiomyocytes Correlates with Disease Severity in Patients

BackgroundThe routine genetic testing of cardiomyopathy patients has significantly accelerated the identification of causative cardiomyopathy variants. However, translating these genetic insights into effective patient management poses significant challenges, since the impact of gene variants on physiological function and clinical outcomes is not yet fully understood. Therefore, there is an urgent need for large-scale methods to assess the effects of genetic variants on cardiomyocyte physiology and to establish correlations between functional phenotypes and clinical severity. MethodsWe developed a high throughput imaging platform to measure force generation and calcium handling throughout the cardiac cycle of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs). By expressing variants of a sarcomeric protein [cardiac Troponin-I (TNNI3)] in a healthy genetic background, we were able to assess sarcomeric calcium sensitivity as well as systolic and diastolic function. Analysis of these parameters distinguished subgroups of variants, and permitted the correlation of in vitro physiological effects with a measure of disease severity in a single-center cardiomyopathy cohort. ResultsCombining contractile force and calcium cycling measurements accurately distinguished known pathogenic from non-pathogenic TNNI3 variants and also revealed pathogenicity of two variants of unknown significance (VUS) that occurred in two families, suggesting the ability to prospectively discern pathogenicity. Clustering of TNNI3 variants based on quantitative physiological phenotypes identified subgroups that correlated with age of disease onset across a well-characterized cardiomyopathy patient cohort, showing clinical relevance of the in vitro phenotypes. Interestingly, normalized measures of in vitro diastolic function correlated with age of onset (R2 = 0.6), but calcium sensitivity, which accurately predicted pathogenicity, did not translate into disease severity. ConclusionsA high throughput in vitro platform that measures multidimensional cardiomyocyte function can link subgroups of human genetic variants in TNNI3 with differential patient outcomes. Comprehensive determination of variant effects on disease-relevant cardiomyocyte function will help classify variants into different pathogenic mechanisms leading to variable disease severity, and potentially lead to class-targeted ameliorative strategies.

genetics↗

bioRxiv2025

Optogenetic Rescue Reveals Spatiotemporal Rules of Germ-Layer Patterning

Embryonic cells must interpret morphogen signals that vary in both time and space, but the rules by which they decode these dynamics remain unclear. Here we combine optogenetics with human 2D gastruloids to define minimal WNT signaling rules for germ-layer patterning. We block endogenous WNT secretion to create a "blank canvas" and reconstitute signaling using light-gated LRP6. Systematic temporal scans reveal a narrow competence window when the onset and duration of WNT signaling specify mesoderm; this window is shifted by cell density and amplified by BMP priming, whereas identical WNT inputs outside it invert germ-layer order or generate alternative mesodermal subtypes. Using micromirror-based illumination, we restricted WNT activation to a mid-ring during this temporal window; combined with BMP4, this fully restored germ layer domains with boundaries sharper than those generated by ligand stimulation. Thus, precise spatiotemporal control of a single pathway is sufficient to optically rebuild germ-layer architecture and reveals WNT as a temporal morphogen.

developmental biology↗

bioRxiv2025

XChrom: a cross-cell chromatin accessibility prediction model integrating genomic sequence and cellular context

Single-cell chromatin accessibility offers unique insights into transcriptional regulation beyond gene expression. However, paired datasets of these two modalities remain relatively scarce, and existing computational models cannot simultaneously predict chromatin accessibility for unseen genomic regions and cells. Here, we present XChrom, a deep learning framework for genome-wide cross-cell chromatin accessibility prediction that integrates genomic sequence and single-cell transcriptomics-derived cell identity into a unified model. Comprehensive evaluations show that XChrom consistently outperforms existing methods in cross-region and cross-cell predictions, and uniquely enables cross-both predictions. It also supports cross-sample prediction when batch effects are properly corrected. Cross-species analyses demonstrate XChroms robust performance and its ability to capture evolutionarily conserved regulatory rules. Applied to peripheral blood mononuclear cells from COVID-19 patients, XChrom accurately identifies transcription factor activities in novel cell subpopulations and reveals pathogenesis-associated regulatory alterations. XChrom is available as an open-source Python package, facilitating single-cell transcriptional regulation research.

bioinformatics↗

bioRxiv2025

Optimization of fermentation conditions for Metarhizium robertsii and its effect on rice growth

Metarhizium robertsii is an important entomopathogenic fungus and plant endophyte, possessing dual functionality as both an insecticide and a plant growth promoter, which has led to its widespread application in agriculture. However, the effects and underlying mechanisms of M. robertsii (MAA)in promoting rice growth remain poorly understood. This study confirmed the growth-promoting effects of MAA and its fermentation supernatant on rice. Based on single-factor and response surface methodology experiments, the fermentation conditions of MAA were subsequently optimized using rice root length as a key indicator, and the potential mechanisms behind this growth promotion were preliminarily investigated. The results demonstrated that both MAA and its fermentation supernatant exerted significant growth-promoting effects on rice. Sucrose and peptone were identified as the optimal carbon and nitrogen sources, respectively. The most pronounced effect was observed when the fermentation supernatant, produced under the conditions of pH 6.0, 0.2% {beta}-Ala, and 100 mol/L Al2(SO4)3, was applied, resulting in a 21.7% increase in rice root length compared to the control group. Furthermore, significant enhancements in chlorophyll content and denser root hairs were recorded in rice treated with the MAA fermentation supernatant, with the chlorophyll content increasing by 28.17% compared to the control. These findings provide a theoretical basis for the development and application of green and efficient bio-inoculants. IMPORTANCEMetarhizium robertsii is an endogenous plant fungus that can be effective for efficient insect control, but the plant-promoting effect of this fungus and its related studies are less reported. The colonization ability and growth promotion effect of Metarhizium robertsii on different crops vary. In this study, a sterile hydroponic system for rice was established. The research found that Metarhizium robertsii can colonize the root system of rice, significantly promoting rice growth, and its growtion-promoting effect is affected by the differences in its fermentation products. After the optimization of the response surface of the fermentation conditions of Metarhizium robertsii, its growth-promoting ability increased by 21.7%. Developing microbial biofertilizers/biopesticides as a basis for reducing chemical inputs in rice cultivation.

microbiology↗

bioRxiv2025

Predicting enhancer-gene links from single-cell multi-omics data by integrating prior Hi-C information

Enhancers play an important role in transcriptional regulation by modulating gene expression from distal genomic locations. Although single-cell ATAC and RNA sequencing (scATAC/RNA-seq) data have been leveraged to infer enhancer-gene links, establishing regulatory links between enhancers and their target genes remains a challenge due to the absence of chromatin conformation information. Here, we present SCEG-HiC, a machine learning method based on weighted graphical lasso, which decodes enhancer-gene links from single-cell multi-omics data by integrating bulk average Hi-C as prior knowledge. Comprehensive evaluation across ten single-cell multi-omics datasets from both humans and mice demonstrates that SCEG-HiC outperforms existing single-cell models, regardless of using paired scATAC/RNA-seq or scATAC-seq data alone. Application of SCEG-HiC to COVID-19 datasets illustrates its capacity to more reliably reconstruct gene regulatory networks underlying disease severity, and elucidate functional associations between non-coding variants and their putative target genes. SCEG-HiC is freely available as an open-source and user-friendly R package, facilitating broad applications in regulatory genomics research.

bioinformatics↗

bioRxiv2025

Nanopore-based sequencing of active DNA replication reveals key principles of metazoan replication fork progression, origin and termination sites

Balancing replication fork progression and origin usage is essential to maintain genome stability, but measuring replication fork progression rates and origin usage throughout the genome has been challenging. Here, we use nanopore sequencing combined with DNAscent to measure replication fork progression together with origin and termination site usage with single-molecule precision throughout the Drosophila genome with nearly full genome coverage. We find that replication fork progression rates are not uniform throughout the genome. Rather, fork progression is slowest in euchromatin, and this is not correlated with active transcription. Replication origins are also influenced by chromatin, but the exact position of initiation is highly variable and are often several kilobases away from ORC binding sites. Termination sites lack any chromatin or sequence motifs and appear nearly random throughout the genome. By measuring DNA replication dynamics at near full genome coverage, our work reveals key principles of metazoan replication dynamics.

molecular biology↗

bioRxiv2025

Targeted degradation of pathologic tau aggregates via AUTOTAC ameliorates tauopathy

The pathogenesis of tauopathies including Alzheimers disease (AD) and progressive supranuclear palsy (PSP) involves the misfolding and aggregation of tau. Here, we employed AUTOTAC to induce the lysosomal degradation of intraneuronal tau aggregates. ATB2005A is a 734-Da chimera that simultaneously binds {beta}-sheet-rich tau aggregates and the autophagic receptor p62/SQSTM1, leading to autophagosomal sequestration and lysosomal co-degradation. In mouse models of tauopathies, orally administered ATB2005A lowered intraneuronal tau aggregates and exerted the therapeutic efficacy in neuroinflammation as well as cognition, behavior, and muscle movements. A Phase 2 clinical trial (U34401-4/2023/14) with companion dogs carrying canine cognitive dysfunction (CCD) demonstrated the efficacy of ATB2005A, as a veterinary medicine, to reverse the disease progression. ATB2005A is under Phase 1 clinical trial with human participants in Korea (202300697). These results validate AUTOTAC as a versatile platform for developing therapeutics to eradicate toxic protein aggregates in a wide range of proteinopathies.

neuroscience↗

bioRxiv2025

Functional dissection of SPOP on the amino acid level reveals a comprehensive functional landscape of variants during tumorigenesis

Numerous proteins display pleiotropic functions in different clinical contexts. However, molecular mechanism underlying such effects is rarely understood. Speckle-type POZ protein (SPOP) is a typical example, exhibiting tumor-suppressing or -promoting effects in different tumor types in accordance with different amino acid changes; specifically, two distinct sets of variants in SPOP are commonly found in subsets of prostate cancer and endometrial cancer patients. To comprehensively characterize the functional landscape of SPOP alteration, we performed a deep mutational screening (DMS), elucidating the functionality of 7,933 out of 8,228 possible single amino acid changes (96.4% coverage). Leveraging the observation that overexpression of human SPOP leads to yeast growth arrest, we assessed the functionality of each variant using a yeast proliferation assay. In addition, our approach combined long-read and short-read sequencing. Finally, our DMS model enables a clear distinction of likely-loss-of-function (LoF) variants that are enriched in prostate cancers and reveals their differential characteristics in both protein structure and genetic assessments. These results demonstrate the utility of our approach in high resolution mapping and amino-acid-level interpretation of protein function. Significance statementGenetic mutations often play different roles in cancer, driving or suppressing tumor growth depending on their molecular context. The protein SPOP is a striking example that acts as either a tumor-suppressor or oncogene depending on the specific mutation and tissue. However, understanding how thousands of possible mutations alter its function has been a major challenge. Here, we applied deep mutational scanning to experimentally measure the functional effects of nearly every possible amino acid change in SPOP. This work provides the first comprehensive functional map of SPOP variants, not only advancing basic knowledge of cancer biology but also establishing a framework for interpreting patient mutations in precision medicine.

genetics↗

bioRxiv2025

Ubiquitin Receptor-Induced Proximity is Sufficient for Ubiquitin-Independent Targeted Protein Degradation via the 26S Proteasome

The 26S proteasome engages with ubiquitinated substrates primarily through its constituent ubiquitin (Ub) receptors, which initiates a cascade of proteolytic processes. Leveraging this recognition mechanism, we developed a targeted protein degradation (TPD) strategy that recruits substrates directly to the proteasome, thereby bypassing the ubiquitination step. Our proteasome-targeting chimera, Protea-Tac, is a heterobifunctional protein degrader composed of a Ub receptor and an intracellular antibody. This chimera integrates into 26S proteasomes without altering their functional integrity. Localization of target proteins, including c-Fos, BRD4, Flag-TDP43, HA-tau, and GFP-ODC, to the proteasome via Protea-Tac with cognate antibodies resulted in their induced degradation. We demonstrated that this platform is 1) modular, allowing facile switching between targets; 2) Ub-independent; and 3) highly target-specific. Protea-Tac exhibited in vivo anti-tumor efficacy, degrading c-Fos and substantially delaying tumor growth. Overall, these findings identify Protea-Tac as a distinct TPD modality capable of directly degrading intracellular proteins via engineered 26S proteasomes. TeaserProtea-Tac is a heterobifunctional protein degrader that enables Ub-independent TPD, exhibits high specificity and modularity, and demonstrates in vivo applicability.

biochemistry↗