bioRxiv Science⌕ Search

Biology subjects

Du, J.

Publications and source records attributed to Du, J..

At least 73 records · Page 4Linked to original sources

Gene Therapy Rescues Cone Function in an All-cone Retina Mouse Model for Blue Cone Monochromacy with the Most Common C203R Missense Mutation

Blue cone monochromacy (BCM) is an X-linked cone dystrophy characterized by loss of long- (L) and medium-wavelength (M) cone function. A common cause is the C203R missense mutation, which occurs in both OPN1LW and OPN1MW, or in hybrid OPN1LW/OPN1MW opsin genes. Because BCM primarily affects foveal cones, we generated Opn1mwC198R/Opn1sw-/-/Nrl-/- (C198RAC) mice carrying the murine equivalent of the human C203R mutation on an all-cone retinal background. C198RAC mice exhibited absent photopic ERG responses and significantly shortened cone outer segments, recapitulating foveal cone deficits in BCM. Metabolomic profiling further revealed altered retinal metabolism, including reduced cGMP and elevated oxidative stress-related metabolites. To evaluate therapy, we delivered AAV8-Y733F expressing human L-opsin (OPN1LW) cDNA under the cone-specific PR2.1 promoter at 1 and 5 months of age. Treatment restored cone function, regenerated outer segment structures, and provided rescue for at least 5 months post-injection in both early- and late-treatment groups. These results demonstrate that densely packed cones expressing only the C198R mutant opsin remain viable targets for gene therapy. Together, this study establishes the C198RAC mouse as a cone-rich model of BCM and provides compelling preclinical evidence that AAV-mediated gene augmentation can restore cone structure and function, supporting the feasibility of gene therapy for BCM.

molecular biology↗

Structural insights and engineering of deep-sea halophilic PET hydrolytic enzymes

Pervasive use of polyethylene terephthalate (PET) poses tremendous challenges for global waste management and environmental sustainability, fueling growing interests in enzymatic degradation as an eco-friendly solution. While PET hydrolases hold significant promise, their industrial deployment is hindered by insufficient performance, particularly under high-salinity conditions raised from high substrate loads. Building on our previous discovery of three deep-sea PET hydrolases (dsPETase01, dsPETase05 and dsPETase06) with exceptional halophilicity and PET-degrading activity, we here present their three-dimensional structures and mechanistic characterization. Structural comparison, site-directed mutagenesis, and domain swapping reveal key structural features and the essential role of C-terminal acidic residues in salt tolerance. Integrating semi-rational protein design, Transformer-based modeling, and disulfide bond engineering, we synergistically enhance the thermostability and catalytic efficiency of dsPETase05. These findings elucidate the unique structural features and salt adaptation mechanisms of deep-sea halophilic PET hydrolases, and inform the future engineering of biocatalysts for application in harsh industrial environments.

molecular biology↗

Cyclin-dependent kinase 9 inhibitors as oncogene signaling modulators in combination with targeted therapy for the treatment of colorectal cancer

BackgroundColorectal cancer (CRC) is the second deadliest cancer worldwide and new treatment options are urgently needed. Cyclin dependent kinase 9 (CDK9) promotes aberrant RNA transcription in cancer and is a promising target for cancer therapies. MethodsUsing CRC cell lines as well as newly established patient-derived organoid models of CRC, we studied the clinically promising CDK9 inhibitors (AZD4573, BAY1125152/VIP152/enitociclib, and NVP2) to determine their therapeutic potential. We investigated the efficacy and mechanisms of action through cell growth and cytotoxicity assays, RNAseq, immunoblotting, and IHC. ResultsWe found CDK9 inhibitors to be highly potent against CRC, through suppression of proliferation and induction of apoptosis. Our results demonstrated CDK9 inhibitors to be broadly active against a set of CRC models derived from a diverse patient population. Our mechanistic studies showed significant suppression of the Mitogen-active protein kinase (MAPK) signaling pathway due to CDK9 inhibitor treatment, suggesting that CDK9 inhibitor efficacy could be enhanced when combined with MAPK pathway inhibitors. As proof-of-concept, we found that CDK9 inhibitors and MEK inhibitors could be combined to synergistically suppress CRC growth and survival. ConclusionsCDK9 inhibitors show promising activity against patient-derived models of CRC. MAPK signaling is particularly suppressed by CDK9 inhibitors. Combining CDK9 inhibitors and targeted therapy against MAPK signaling pathway may be a viable strategy worthy of further investigation preclinically and clinically. State of translational relevanceNovel therapies for chemotherapy-refractory CRC remain urgently needed. Rapid validation of efficacy in appropriate translational models can provide the necessary rationale to test new therapies in clinical trials. Using newly established patient-derived organoids, we validate the preclinical efficacy of transcriptional CDK9 inhibitors against CRC. This is a therapeutic class that has been scarcely evaluated for efficacy against CRC. We found that CDK9 inhibitors potently inhibit patient-derived organoid models of CRC. Our mechanistic work also reveals that clinically achievable concentrations of CDK9 inhibitor treatment results in suppression of MAPK signaling. As proof-of-concept of the potential actionability of our findings, we demonstrate that CDK9 inhibitors can be combined with MEK inhibitors to synergistically suppress CRC growth. Our study provides new patient-derived CRC models as a resource available to others for therapeutic testing, as well as a roadmap for novel hypotheses about synergistic combination treatments using CDK9 inhibitors.

cancer biology↗

Site-Specific Nanobody Inhibitors of the Proteasomal Deubiquitinase UCH37

Dysregulation of the ubiquitin (Ub) proteasome system (UPS) is linked to numerous human diseases, making its components attractive therapeutic targets. Among these, the proteasomal deubiquitinase UCH37 (also known as UCHL5) has two distinct Ub-processing activities: C-terminal Ub hydrolysis and K48-linkage-specific chain debranching. Separating these activities has not been possible with existing small-molecule inhibitors, which target the catalytic site and broadly affect both functions along with many other DUBs. Here, we report the development of two site-specific nanobody inhibitors of UCH37 that together enable this separation. Using yeast surface display, we generated Nb-cS1, which binds the canonical Ub-binding (S1) site and blocks both activities, and Nb-ncS1, which binds the non-canonical K48-specific (ncS1) site and selectively impairs chain debranching without affecting C-terminal Ub hydrolysis. X-ray crystallography and hydrogen-deuterium exchange mass spectrometry define the distinct binding surfaces engaged by each nanobody. In cells, both nanobodies selectively engage UCH37, with Nb-ncS1 showing the cleanest target engagement. These tools provide the first means to independently interrogate UCH37s two enzymatic activities and offer new approaches for dissecting the distinct roles of UCH37 in proteasomal and chromatin-associated contexts.

biochemistry↗

MuSHIN: A multi-way SMILES-based hypergraph inference network for metabolic model reconstruction

Genome-scale metabolic models (GEMs) are indispensable tools for probing cellular metabolism, enabling predictions of metabolic fluxes, guiding strain optimization, and advancing biomedical research. However, their predictive capacity is often compromised by incomplete reaction networks, stemming from gaps in biochemical knowledge, annotation inaccuracies, and insufficient experimental validations. Here we present MuSHIN (Multi-way SMILES-based Hypergraph Interface Network), a novel deep hypergraph learning method that integrates network topology with biochemical domain knowledge to predict missing reactions in GEMs. Evaluated on 926 high- and intermediate-quality GEMs with artificially removed reactions, MuSHIN significantly outperforms state-of-the-art methods, achieving up to a 17% improvement across multiple metrics and maintaining robust recovery even under severe network sparsity. Furthermore, MuSHIN substantially enhances phenotypic predictions in 24 draft GEMs associated with fermentation by resolving critical metabolic gaps, as validated against experimental measurements. Together, these findings highlight MuSHINs potential to advance GEM reconstruction and accelerate discoveries in systems biology, metabolic engineering, and precision medicine.

bioinformatics↗

DREAM-GNN: Dual-route embedding-aware graph neural networks for drug repositioning

Drug repositioning presents a compelling strategy to accelerate therapeutic development by uncovering new indications for existing compounds. However, current computational methods are often limited in their ability to integrate heterogeneous biomedical data and model the intricate, multi-scale relationships underlying drug-disease associations, while large-scale experimental validation remains prohibitively resource-intensive. Here we present DREAM-GNN (Dual-Route Embedding-Aware Model for Graph Neural Networks), a multi-view deep graph learning framework that incorporates biomedical domain knowledge with two complementary graphs capturing both topological structure and feature similarity to enable accurate and biologically meaningful prediction of drug-disease associations. Extensive experiments on benchmark datasets demonstrate that DREAM-GNN significantly outperforms current state-of-the-art methods in recovering artificially removed repositioning candidates. These results establish DREAM-GNN as a robust and generalizable computational framework with broad potential to streamline drug discovery and advance precision medicine.

bioinformatics↗

Endothelial Kallikrein-Related Peptidase 8 Promotes Diabetic Nephropathy through a LIFR dependent mechanism

BackgroundDiabetic nephropathy (DN) is the primary microvascular complication of diabetes mellitus; however, the exact pathways in endothelial cells (ECs) linked to DN progress remain unclear. Tissue kallikrein-related peptidases (KLKs) participate in pathophysiological processes in ECs. We aimed to explore the roles of endothelial KLKs in DN and define the underlying mechanisms. Methods and resultsKLK8 was the most highly upregulated member of KLKs in renal tissues in streptozotocin (STZ)-induced diabetic mice and cultured glomerular ECs (GECs) upon high glucose (HG) treatment. Both global (Klk8-/-) and endothelial Klk8 knockout (Klk8{Delta}EC) mice displayed improved albuminuria, mesangial matrix expansion and glomerulosclerosis caused by STZ compared to Klk8f/f mice. Single-cell RNA seq (scRNA-seq) showed that many pathways associated with DN in ECs, mesangial cells (MCs) and tubule cells were reversed in Klk8{Delta}EC mice. Endothelial-to-mesenchymal transition (EndMT) was extensively improved in Klk8{Delta}EC mice, and by KLK8 siRNA in cultured GECs upon HG. Using proteome and other biochemical approaches, we revealed that KLK8 cleaved syndecan-4(SDC4), which contributed to loss of glycocalyx integrity in GECs in cultured cells and animal diabetic models. Furthermore, scRNA-seq showed that Lifr was one of the key genes linked to the disease progressed in ECs and MCs and regulated by endothelial Klk8. LIFR signaling contributed to HG-induced GEC dysfunction and MC activation, which was associated with endothelial Klk8. Knockdown of Lifr by lentivirus-Lifr shRNA ameliorated hallmark features of DN and improved EndMT and Sdc4 expression glomeruli of diabetic mice. LIFR was upregulated in GECs and MCs in DN patients. Circulatory levels of LIF, KLK8 and soluble SDC4 were increased in patients with DN, and KLK8 level was positively correlated with LIF, soluble SDC4 and creatinine levels. ConclusionEndothelial KLK8 promotes GECs dysfunction and abnormal crosstalk with MCs through a LIFR-dependent signaling in DN, which immediately highlights therapeutic targets for DN. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=171 SRC="FIGDIR/small/662673v1_ufig1.gif" ALT="Figure 1"> View larger version (42K): org.highwire.dtl.DTLVardef@dae3b1org.highwire.dtl.DTLVardef@9aab24org.highwire.dtl.DTLVardef@59eaa5org.highwire.dtl.DTLVardef@13c138a_HPS_FORMAT_FIGEXP M_FIG C_FIG

pathology↗

Divergent Neurobehavioral Effects of CFTR Modulators Elexacaftor and Ivacaftor in Mice

Recent advances in cystic fibrosis transmembrane conductance regulator (CFTR) modulator combination therapies have markedly improved survival and quality of life for people with cystic fibrosis (CF). Among these, the elexacaftor-tezacaftor-ivacaftor combination (Trikafta) and its updated formulation, vanzacaftor-tezacaftor-deutivacaftor (Alyftrek), represent major therapeutic milestones. However, emerging reports suggest that Trikafta may contribute to anxiety and depression in some people with CF. In this study, we investigated the neurobehavioral effects of elexacaftor and ivacaftor in mice. Acute administration of elexacaftor elicited anxiety-like behavior, while ivacaftor induced depressive-like behavior. Additionally, we confirmed the presence of Cftr mRNA in the amygdala and hippocampus, brain regions implicated in anxiety and depression. These findings provide preclinical support for the reported mental health side effects experienced by some people with CF and offer new insights into CFTR function within the central nervous system, potentially guiding the development of future CF therapies with improved neuropsychiatric profiles.

physiology↗

Microglial GSDMD-Mediated Pyroptosis Drives Neuroinflammation in Parkinson's Disease

RationaleParkinsons disease (PD), a globally prevalent neurodegenerative disorder, is characterized by substantia nigra dopaminergic neuron degeneration and striatal dopamine depletion. While microglial pyroptosis is implicated in neuroinflammation and neural injury via inflammatory cytokine release, the role of the CASPASE-1/GSDMD pathway in PD pathogenesis remains incompletely defined. Methods1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) was used to construct PD model in vivo, GSDMD-knockout mice was employed to assess pyroptotic mechanisms. MPP-stimulated BV2 microglia were treated with a CASPASE-1 inhibitor in vitro. Microglia-specific GSDMD conditional knockout mice were generated to evaluate cell-type contributions to neuroinflammation and motor deficits. ResultsGSDMD deficiency attenuated MPTP-induced neuroinflammation, dopaminergic neuron loss, and motor dysfunction in vivo. MPP exposure triggered NLRP3 inflammasome activation and pyroptosis in BV2 microglia, which was suppressed by CASPASE-1 inhibition. Critically, microglia-specific GSDMD ablation mitigated nigrostriatal degeneration and dyskinesia in PD mice, confirming the centrality of microglial pyroptosis. ConclusionOur findings demonstrate that microglia drive neuroinflammation in PD via CASPASE-1/GSDMD-mediated pyroptosis, directly linking this pathway to dopaminergic neurodegeneration and motor impairment. Targeting GSDMD-dependent pyroptosis represents a promising therapeutic strategy.

neuroscience↗

Precision Prediction of Microbial Ecosystem Impact on Host Metabolism Using Genome-Resolved Metagenomics

Microorganisms often drive ecosystem function, yet precision disturbance response and ecosystem impact predictions remain challenging due to poorly captured ecological and metabolic interconnectedness and functional redundancy. For example, while mammalian gut dysbiosis is recognized to influence host metabolism, key microbiota and mechanisms governing their effects remain poorly understood. Here we developed a genome-resolved eco-systems biology workflow to predict how gut microbial metabolism affects mammalian health, and we applied it to a spinal cord-gut axis dataset. By scaling and integrating temporally resolved network analytics and consensus statistical approaches, we identified largely previously uncharacterized microbial species that best predict host physiology following neurological impairment. In silico validation through "complete" pathway-centric and comparative genomic analyses revealed that among these species, the major encoded microbial metabolic changes were in pathways directly linked to host nitrogen balance, and they varied by host sex and microbial ecotype/species. Moreover, we identified the exact bacterial species (and their draft genome sequences) driving urease-dependent versus amino acid-dependent nitrogen gut metabolism - findings that explain previously mechanistically-ambiguous, but clinically relevant, ammonia-driven host nitrogen imbalance. More broadly, these ecology- and community-aware approaches provide a framework to study dynamic, interconnected microbiomes that advances from enrichment-based single-taxon and single-gene correlations towards building microbe(s)-driven mechanistic insights that integrate community context and whole pathways.

microbiology↗

Directional growth of developing myelin mediated by Wnt gradient and required for proper axon functions

Axon-wrapping myelin sheaths formed by oligodendrocytes are essential for proper functions of the central nervous system. Although much is known about oligodendrocyte development, how the myelin dynamically forms remains unclear. Here we show the preferentially unidirectional extension of developing myelin mediated by Wnt gradient and required for proper axon functions. Using larval zebrafish as an in vivo model, we found that developing myelin in the spinal cord preferentially extends to the anterior end, and this process is dependent on an anterior-to-posterior Wnt4b gradient. Taking advantage of the large size of Mauthner-cell axons, we further showed that disruption of this directional extension impairs the even length distribution of myelin sheaths and faithful transduction of action potentials along the axon, and reduces the reliability of escape behavior. Thus, our study reveals a novel process for precise regulation of myelination, providing a new insight into myelin structuring and functioning.

neuroscience↗

An Adaptive Visuomotor Transformation Reservoir Embedded in the Vertebrate Brain

Adaptive visuomotor transformation requires sensorimotor circuits to generate accurate, robust, and flexible outputs, but its underlying cellular mechanism remains poorly understood. Leveraging a zebrafish mesoscopic connectome, we built a biologically constrained spiking neural network of the optic tectum (OT), a conserved vertebrate center for visuomotor transformation, and drove the model with real retinal inputs. Integrating in silico and biological interrogations, we revealed that the OT functions as a biologically structured reservoir complemented by serotonergic systems to implement adaptive visuomotor transformation. Within the tectal reservoir, inhibitory interneurons with layer-matched axonal arborizations suppress task-unrelated pathways to ensure visuomotor accuracy, while excitatory interneurons with deep-layer terminating axons reinforce task-related pathways to enhance noise robustness. Furthermore, visually responsive OT-projecting serotonergic subsystems reweight competing pathways to confer visuomotor flexibility. Thus, our findings delineate how specific interneuron-type-embodied push-pull-like mechanisms coordinate with serotonergic neuromodulation to drive adaptive visuomotor transformation, offering a mechanistic framework for neural computational architectures.

neuroscience↗

Central nervous system atlas of larval zebrafish constructed using the morphology of single excitatory and inhibitory neurons

Single-neuron morphology mapping is fundamental for deciphering brain architecture and function, yet in vertebrates it remains limited in spatial coverage and cell-type information. Here we present a nervous system-wide single-neuron morphology atlas of larval zebrafish with annotated excitatory/inhibitory identity and dendrite-axon polarity. The atlas comprises >20,000 reconstructed neurons from >13,400 animals, spanning the central and peripheral nervous system and representing [~]24.5% of the total excitatory and inhibitory neurons in the brain, all integrated into a common physical space with neuroanatomical parcellations. We define >500 excitatory and inhibitory neuronal morphotypes and construct putative inter-cell-type and interregional connectomes. Projection and morphotype analyses reveal distinct laterality and directionality biases and modular innervation patterns in excitatory and inhibitory neurons, while network analyses uncover fundamental connectivity motifs, hubs, and sensorimotor pathways. Accessible through custom-built interactive platform ZExplorer, this atlas provides a foundational resource for multimodal data integration, circuit analysis, computational modeling, and hypothesis-driven research.

neuroscience↗

Dendritic computation for rule-based flexible categorization

A hallmark of intelligent behavior is the ability to flexibly respond to external sensory inputs based on dynamically changing rules. A central question is how neurons in the brain implement computations underlying intelligent behaviors. The neocortical pyramidal neurons use their elaborated dendritic arbors to segregate a plethora of inputs and dynamically integrate them--a process known as dendritic computation--which may play important roles in rule-dependent sensory processing. However, evidence directly linking dendritic computation with intelligent cognitive behaviors has been absent. Here we combine two-photon imaging and a rule-switching flexible categorization task in mice to show that a projectome-defined extratelencephalic (ET) cortical layer 5 (L5) neurons in the auditory cortex integrate dendritic rule information and somatic sensory input to enable rule-dependent flexible categorization. The apical dendrite and soma within the same ET neurons exhibit distinct compartmental representations for sensory and rule information, with the soma predominantly encoding sensory information and the dendrites representing inferred task rule. Simultaneous optogenetic dendritic inhibition and two-photon imaging revealed that dendritic rule coding is essential for somatic output of flexible categorization. Our findings indicate that nonlinear dendritic integration of rule and sensory information constitutes a neuronal computational mechanism underlying rule-switching flexible decision-making.

neuroscience↗

The Spinal Cord-Gut Axis Regulates Gut Microbial Homeostasis: Insights from a New Murine Metagenomic Catalog

The spinal cord, a nexus for brain-body crosstalk, controls gut physiology and microbial homeostasis, but the underlying mechanisms remain unclear. Using genome-resolved longitudinal metagenomics in male and female C57BL/6 mice before and up to 6 months after disrupting the spinal cord-gut axis, we reconstructed over 6,500 microbial draft genomes. This "Mouse B6 Gut Catalog" improved or doubled species- and strain-level representation in other published catalogs. Impaired spinal cord-gut crosstalk induced persistent, sex-, time- and lesion-specific alterations in community composition, marked by a consistent loss of Lactobacillus johnsonii. Feeding this key bacterium to mice with a clinically relevant spinal cord injury improved host health. Genome-resolved, community-contextualized metabolic profiling revealed that shifts in carbohydrate- mediated microbe-microbe interactions explain the reduction of L. johnsonii. These findings identify carbohydrate metabolism as a keystone mechanism shaping gut microbiota and emphasize that mammalian health and gut ecosystem function depend on a functional spinal cord-gut axis. Additionally, these data improve murine microbiome catalogs and demonstrate that metagenome-informed microbial interventions can improve host health and likely mitigate long-term dysbiosis.

microbiology↗

IL-17A-driven Macrophage Disorder Promotes Plaque Instability in Psoriatic Atherosclerosis

Psoriasis is a common chronic inflammatory skin disease that predisposes individuals to cardiovascular diseases such as atherosclerosis. However, the underlying mechanisms linking these conditions have not yet been fully elucidated. Recent studies have indicated that the inflammatory cytokine IL-17A plays a significant role in both diseases. The aim of this study was to investigate how psoriasis affects the stability of atherosclerotic plaques via the IL-17A/IL-17RA pathway. We performed single-cell sequencing on patients with both psoriasis and atherosclerosis to analyze changes in the immune microenvironment within their carotid plaques and psoriatic lesions. We found that IL-17A significantly upregulated the expression of pro-inflammatory factors (e.g., CXCL8) in macrophages of psoriatic atherosclerosis patients, leading to weakening of the fibrous cap structure of plaques. Additionally, IL-17A further exacerbated plaque instability by interfering with macrophage lipid metabolism, particularly sphingolipid metabolism. Finally, using in vitro experiments and animal models, we demonstrated that IL-17A enhances pro-inflammatory and metabolic abnormalities in macrophages by downregulating PPAR{gamma}. Therapeutic strategies targeting IL-17A may contribute to the simultaneous mitigation of psoriasis and atherosclerosis-associated cardiovascular risk, providing new directions for clinical intervention.

cell biology↗

PEARL: Integrative multi-omics classification and omics feature discovery via deep graph learning

Integrating multi-omics data provides valuable insights into biological processes by capturing information across multiple molecular layers, enabling a comprehensive understanding of complex diseases and driving advancements in precision medicine. However, existing computational methods for multi-omics integration face significant challenges, such as low reliability and poor generalizability, due to the high dimensionality and low sample size nature of omics data. To address these challenges, we present PEARL (Pearson-Enhanced spectrAl gRaph convoLutional networks), a novel deep graph learning method for biomedical classification and functional important omics features identification. PEARL leverages a simple yet effective learning architecture to achieve superior and robust performance in high-dimensional, low-sample-size multi-omics settings. Our results demonstrate that PEARL significantly outperforms existing state-of-the-art methods on both synthetic and real biomedical datasets. Furthermore, applied to Alzheimers disease (AD) brain multi-omics data, features prioritized by PEARL lead to functionally important genes that demonstrate significant enrichment in AD-related pathways. These findings highlight PEARLs practical utility in biomedical research and its potential to enhance biological interpretability in multi-omics studies.

bioinformatics↗

Embryonic Durotaxis: A Mechanical Framework for Understanding Cesarean Scar Pregnancy

Cesarean scar pregnancy (CSP) is an increasingly common complication associated with the rise in cesarean section rates, yet its underlying mechanisms remain poorly understood. In this study, we identified a stiffness gradient between healthy and scarred uterine tissues in both human cesarean samples and mouse uterine scar models. By employing gradient stiffness hydrogels, we demonstrated that mouse embryos and human trophoblast spheroids exhibit durotaxis, migrating preferentially toward stiffer areas. This migration occurs through three-dimensional complex behaviors--translation, swinging, and rolling--characterized by periodic patterns that align with cavity oscillations. Embryonic durotaxis is initiated from asymmetric adhesion forces and is driven by embryonic protrusive forces, generated from Marangoni-like tissue flows. The intrinsic cavity oscillations further amplify and sustain embryonic durotaxis. Finally, pharmacological inhibition of embryonic durotaxis significantly reduced CSP incidence in the mouse model. Our findings establish the concept of embryonic durotaxis, which may provide novel therapeutic avenues for CSP prevention.

developmental biology↗