Biology subjects

Wu, S.

Publications and source records attributed to Wu, S..

At least 145 records · Page 8Linked to original sources

bioRxiv2025

A Reductive Uric Acid Degradation Pathway in Anaerobic Bacteria

Uric acid is a key intermediate in purine degradation across diverse organisms, while its accumulation in humans leads to inflammation and gout disease. Aerobic organisms degrade uric acid via a well-known "oxidative pathway" involving dearomatization of the purine core catalyzed by uric acid oxidases or dehydrogenases. The ability to degrade uric acid is also widespread in anaerobic bacteria, including gut bacteria, although the mechanisms are incompletely understood. Here, we report the biochemical characterization of a recently identified uric acid degradation gene cluster from Escherichia coli, and show that it encodes a "reductive pathway" for uric acid degradation. In this pathway, uric acid is first reduced to isoxanthine (2,8-dioxopurine) by a xanthine dehydrogenase homolog (XdhD), followed by dearomatization of the purine core catalyzed by a flavin-dependent reductase (YgfK). Stepwise cleavage of the pyrimidine and imidazole rings forms 2,3-diureidopropionate, and stepwise cleavage of the 2- and 3-ureido groups then forms 2,3-diaminopropionate, which is cleaved by a pyridoxal 5-phosphate-dependent lyase (YgeX) to pyruvate and ammonia. Detection of isoxanthine in clinical serum samples suggests it is a physiologically relevant circulating metabolite. A probiotic E coli Nissle strain was engineered for constitutive overexpression of the gene cluster, and oral administration in a uricase-knockout hyperuricemic mouse model significantly reduced the serum uric acid level and alleviated associated kidney injury, suggesting a potential route towards uricolytic probiotics.

biochemistry↗

bioRxiv2025

Mechanistic Insights into the Plasmodium Phosphatase UIS2 in eIF2α Dephosphorylation via Integrated Structure-Based Modeling

The development of novel antimalarial drugs requires the identification of parasite-specific vulnerabilities. Translation control, regulated by eIF2 dephosphorylation, is essential for Plasmodium development during infection. The parasite phosphatase UIS2 regulates this modification. However, the structural basis for UIS2 substrate recognition remains unknown. Here, we show that UIS2 is crucial for parasite development in both liver and blood stages. Its N-terminal and phosphatase domains each independently bind the eIF2 phosphoserine-59 loop through electrostatic interactions. Integrated structural modeling, using AlphaFold and molecular dynamics simulations, reveals a defined binding pocket within the phosphatase domain, with a geometry distinct from human PP1. This pocket contains six cooperative binding patches that use an electrostatic network to stabilize the phosphopeptide near the active site and contribute to substrate specificity. Metadynamics simulations show that the inhibitor Salubrinal competes with the phosphopeptide for binding to this pocket. Molecular docking and free energy perturbation analyses show that Salubrinal targets three of these binding patches through hydrophobic and hydrogen-bonding interactions, blocking substrate binding. These findings show the structural and energetic basis of eIF2 dephosphorylation by UIS2. They provide an integrated modeling approach for phosphatase-substrate interactions and a mechanistic rationale for selective inhibition of a parasite-specific translation regulator.

biophysics↗

bioRxiv2025

Ferret model of bleomycin-induced lung injury shares features of human idiopathic pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is a debilitating lung disease with limited therapeutic options. The development of effective therapies has been hindered by the lack of models that recapitulate key features of human disease. Here we report a bleomycin-induced ferret PF model characterized by an irreversible decrease in pulmonary compliance and an increase of opacification, accompanied by "honeycomb cyst-like" structures and "proximalization" of distal lung epithelium. Cellular and molecular analysis by single-nucleus RNA sequencing revealed a significant shift in distal lung epithelium towards proximal epithelial phenotype. Importantly, a histopathological pattern of bronchiolization encompassing divergent atypical epithelial cells and KRT17+/TP63+/KRT5low "basaloid-like" cells was present in the distal fibrotic lung lesions. Trajectory analysis revealed AT2 cells transition through multiple cell-states in bleomycin injured ferret lungs, particularly AT2 to KRT8high/KRT7low/SOX4+ and eventually to KRT8high/KRT7high/SFN+/TP63+/KRT5low "basaloid-like" cells. Further, immunofluorescence analyses demonstrated KRT7 and KRT8 populations reside overlaying the ACTA2-positive myofibroblasts in fibrotic foci, implying their pro-fibrogenic activity similar to human IPF lungs. Collectively, our results provide evidence that bleomycin-induced lung injury in ferrets recapitulates pathophysiological, cellular, and molecular features of human IPF, suggesting that they may be a reliable model for understanding mechanisms of IPF pathogenesis and for testing therapeutic strategies for treatment of IPF. Take Home MessageBleomycin-induced acute lung injury in the ferret recapitulates pathophysiological, cellular, and molecular features of human IPF; thus the ferret may be a reliable species for studying mechanisms of IPF pathogenesis and testing therapeutic strategies.

pathology↗

bioRxiv2025

Sialin2 Functions as a Mammalian Nitrate Sensor to Sustain Mitochondrial Homeostasis

Nitrogen homeostasis is fundamental for cellular physiology, yet mammalian nitrate (NO3-) sensing mechanisms remain elusive. Here, we identify Sialin2--a proteolytic fragment of the nitrate transporter Sialin generated by cathepsin B (CTSB) cleavage-- as the first mammalian nitrate sensor. Microscale thermophoresis (MST) reveals Sialin2 as a high-affinity nitrate sensor, while Cryo-Electron Microscopy (Cryo-EM) uncovers its structural basis for signaling. We show that Sialin2 localizes to mitochondria and scaffolds liver kinase B1 (LKB1)-AMP-activated protein kinase (AMPK) complexes to drive organelle-specific metabolic adaptation via spatiotemporally controlled AMPK activation, enhancing mitochondrial biogenesis, ATP production, and cell survival. Real-time tracking using the sCiSiNiS biosensor demonstrates nitrate signaling dynamics at physiological levels. This signaling axis redefines nitrate as a direct ligand activating receptor-like cascades, independent of classical nitric oxide synthesis. Our findings establish a paradigm of "inorganic salt signaling biology", wherein anions co-opt trafficking systems to achieve signaling specificity, offering therapeutic avenues for mitochondrial disorders.

cell biology↗

bioRxiv2025

ScIsoX: A Multidimensional Framework for Measuring Transcriptomic Complexity in Single-Cell Long-Read Sequencing Data

Single-cell isoform sequencing enables high-resolution characterisation of transcript isoform expression, yet analytical frameworks to systematically measure transcriptomic complexity are lacking. Here, we introduce ScIsoX, a computational framework that integrates a novel hierarchical data structure, a suite of complexity metrics, and dedicated visualisation tools for isoform-level analysis. ScIsoX supports systematic exploration of global and cell-type-specific isoform expression patterns arising from alternative splicing, revealing multidimensional complexity signatures across diverse datasets - insights often missed by conventional gene-level approaches.

bioinformatics↗

bioRxiv2025

Phage lysis protein LysM acts as a wedge to block MurJ conformational changes

Many antibiotics target essential cellular processes. To combat multidrug-resistant bacteria, new antibacterial strategies are needed. In the peptidoglycan biogenesis pathway in Escherichia coli, MurJ, the lipid II flippase, is an essential membrane protein. The 37-residue protein M from the Levivirus phage, known as LysM or SglM, targets MurJ and induces cell lysis; however, its molecular mechanism remains unclear. Here, we present the cryo-EM structure of the MurJ/LysM (JM) complex at 3.09 [A] resolution, revealing that LysM interacts with the crevasse between TM2 and TM7 of MurJ, locking MurJ in an outward-facing conformation, with LysM acting like a wedge. Alanine-scanning mutagenesis and pull-down assays revealed key residues responsible for LysM function, and molecular dynamics simulations showed that LysM stabilizes MurJs outward-facing state. These findings demonstrate an unprecedented phage-derived mechanism for blocking lipid II transport, providing a structural framework for designing MurJ-targeted antimicrobial agents.

molecular biology↗

bioRxiv2025

Uev1A counteracts oncogenic Ras stimuli in both polyploid and diploid cells

Oncogenic Ras is known to induce DNA replication stress, leading to cellular senescence or death. In contrast, we found that it can also trigger polyploid Drosophila ovarian nurse cells to die by inducing aberrant division stress. To explore intrinsic protective mechanisms against this specific form of cellular stress, here we conducted a genome-wide genetic screen and identified the E2 enzyme Uev1A as a key protector. Reducing its expression levels exacerbates the nurse cell death induced by oncogenic Ras, while overexpressing it or its human homologs, UBE2V1 and UBE2V2, mitigates this effect. Although Uev1A is primarily known for its non-proteolytic functions, our studies demonstrate that it collaborates with the E3 APC/C complex to mediate the proteasomal degradation of Cyclin A, a key cyclin that drives cell division. Furthermore, Uev1A and UBE2V1/2 also counteract oncogenic Ras-driven tumorigenesis in diploid cells, suppressing the overgrowth of germline tumors in Drosophila and human colorectal tumor xenografts in nude mice, respectively. Remarkably, elevated expression levels of UBE2V1/2 correlate with improved survival rates in human colorectal cancer patients harboring oncogenic KRAS mutations, indicating that their upregulation could represent a promising therapeutic strategy.

cell biology↗

bioRxiv2025

Large-scale single-neuron recording using the uFINE array in human cortex

Monitoring neural population activity at single-cell resolution is essential for driving fundamental research and clinical innovations. However, translating advanced recording techniques from animal models to humans remains a significant challenge. Flexible neural electrodes have recently emerged as powerful tools for large-scale single-unit recordings due to their superior biocompatibility and high recording density. Here, we demonstrate reliable, high-density single-unit recordings during intraoperative procedures in human patients using ultra-Flexible Implantable Neural Electrode (uFINE) arrays. The uFINE array exhibited sufficient mechanical robustness to maintain structural integrity throughout surgical operations. We successfully recorded 616 single units from 10 patients, with up to 135 single units simultaneously recorded. The flexibility of uFINE array minimized signal disturbances from brain pulsations, enabling stable and continuous single-unit detection. Stimulus and response tuning were observed at the level of individual neurons in awake patients. This uFINE-based recording approach offers unique opportunities to investigate human-specific cognitive functions and develop next-generation brain-machine interfaces.

bioengineering↗

bioRxiv2025

Protective effects of central leptin on whole-body energy homeostasis upon acute olanzapine exposure

Second-generation antipsychotic use is associated with severe metabolic side effects such as obesity and type 2 diabetes. Leptin is a hormone that is secreted by adipose tissue, and it acts on the brain to decrease body weight by reducing food intake and stimulating energy expenditure. Leptin also improves glucose and lipid metabolism. We examined the short-term impact of olanzapine, a commonly used second-generation antipsychotic, on the central leptin-mediated regulation of energy balance, lipid metabolism, and hypothalamic kinase activity. Male Sprague Dawley rats were given an acute intracerebroventricular (ICV, 3rd ventricle) injection of either leptin or vehicle, combined with subcutaneous olanzapine or vehicle. As expected, ICV leptin decreased food intake and importantly, olanzapine did not block this effect. Administration of leptin, olanzapine, or their combination reduced the average respiratory exchange ratio (RER) during the light cycle, which indicates that fat oxidation was increased. In the dark cycle, leptin decreased the average RER regardless of olanzapine administration, and in the presence of leptin, olanzapine did not affect the average RER. Leptin did not alter the olanzapine-induced increase in serum triglyceride concentrations. Olanzapine and central leptin treatment differentially activated hypothalamic kinases. In conclusion, regulation of food intake and fuel preference by central leptin is intact following acute olanzapine administration.

neuroscience↗

bioRxiv2025

Single-Cell eQTL Mapping Reveals Cell Type-Specific Genetic Regulation in Lung Cancer

Genome-wide association studies (GWAS) have identified over 50 lung cancer risk loci; however, the precise cellular context of these genetic mechanisms remains unclear due to limitations in bulk tissue eQTL analyses. Here, we present the largest single-cell eQTL atlas of human lung tissue to date, profiling 222 donors using multiplexed scRNA-seq. We identified 16,785 eQTLs across 17 cell types, with over 90% of sc-eQTLs and 59% eGene being cell-type-specific, and fewer than 23% were detectable in paired bulk datasets. Integration with GWAS for non-small cell lung cancer highlighted epithelial and immune cells as key contributors to genetic susceptibility, identifying 28 candidate genes within known risk loci and 24 in novel regions. Notably, 47% of established NSCLC susceptibility loci exhibited cell-type-specific pleiotropic genetic regulation. This study provides a valuable resource of lung sc-eQTLs and illuminates how genetic variation modulates gene expression in a cell-type-specific fashion, contributing to lung cancer susceptibility.

genetics↗

bioRxiv2025

Development of Replay-DMN Coordination Predicts Entorhinal Grid Codes

Neural replay, the reactivation of experience-related activity patterns during offline periods, has been implicated in organising memories into cognitive maps. However, how replay processes mature through childhood and adolescence remains unclear. Here we studied 106 participants aged 8-25 who learned a hidden two-dimensional (2D) associative structure and then underwent magnetoencephalography (MEG) during a map-based inference task and post-task rest to detect spontaneous replay. We found that during post-task rest, younger individuals relied primarily on replay alone to represent the 2D relationships, whereas older individuals showed increasingly precise timing alignment between replay events and activity in the default mode network (DMN), particularly when replay occurred at the trough of a DMN theta oscillation. Such replay-DMN coupling predicted the strength of a grid-cell-like code in the entorhinal cortex identified in this cohort with fMRI. Furthermore, resting-state fMRI revealed that DMN functional connectivity strengthened with age, in parallel with reduced reliance on replay and more efficient inference performance. These results reveal a developmental progression in which replay shifts from an isolated process in youth to a coordinated DMN mechanism by adulthood. This transition predicts the maturation of grid-like schema representations, shedding light on how children gradually build internal knowledge structures to support flexible inference.

neuroscience↗

bioRxiv2025

Multidimensional characterization of cellular ecosystems in Hodgkin lymphoma

The tissue architecture of classic Hodgkin Lymphoma (CHL) is unique among cancers and characterized by rare malignant Hodgkin and Reed-Sternberg cells that co-evolve with a complex ecosystem of immune cells in the tumor microenvironment (TME). The lack of a comprehensive systems-level interrogation has hindered the description of disease heterogeneity and clinically relevant molecular subtypes. Here, we employed an integrative, multimodal approach to characterize CHL tumors using malignant cell sequencing, spatial transcriptomics and imaging mass cytometry. We identified four molecular subtypes (CST, CN913, STB, and CN2P), each characterized by distinct clinical features, mutational patterns, malignant cell gene expression profiles, and spatial architecture involving immune cell populations. Functional modeling of CSF2RB mutations, a characteristic feature of the CST subtype, revealed dysregulated oncogenic signaling and unique TME crosstalk. These findings highlight the significance of multi-dimensional profiling in elucidating patterns of molecular alterations that drive immune ecosystems and underlie therapeutically exploitable vulnerabilities.

cancer biology↗

bioRxiv2025

Acquired resistance to sotorasib in mutant NSCLC is vulnerable to PI3K-mTOR pathway inhibition mediated by 4E-BP1 regulator of cap-dependent translation

Sotorasib and adagrasib have shown significant efficacy in KRASG12C mutant NSCLC; however, acquired resistance (AR) occurs within 6-12 months. While some resistance arises from new mutations, over half of the resistant cases lack identifiable genomic alterations. We hypothesize that resistance is driven by signaling network rewiring, creating new therapeutic vulnerabilities. To investigate AR mechanisms, multiple AR models, including cell lines, PDXs, CDXs, and PDXOs, were developed. H23AR and H358AR cells displayed >600-fold and 200-fold; and PDXO303AR and PDXO314AR organoids exhibited >300-fold and >100-fold resistance to sotorasib, respectively; however, no additional mutations in KRAS or other potential genetic alterations were identified. The AR cells and PDXOs also showed comparable resistance to adagrasib. Distinct protein signatures associated with KRAS reactivation, mTORC1 signaling upregulation, and PI3K/AKT/mTOR pathway activation were identified in TC303AR & TC314AR PDXs. PI3K protein levels were significantly elevated in AR PDXs, H23AR, and H358AR cells. Pharmacological inhibition of PI3K with copanlisib or genetic knockout via CRISPR-Cas9 restored sotorasib sensitivity, suppressed colony formation, and inhibited downstream effectors, including p-AKT, p-mTOR, p-S6, p70S6K, p-GSK3{beta}, and p-PRAS40 in AR cells. Copanlisib also sensitized both acquired and primary resistant PDXOs and synergized with sotorasib in restoring drug sensitivity. p4E-BP1 was significantly upregulated in H23AR and H358AR cells, which is suppressed by copanlisib. The level of p4E-BP1 expression was correlated with Sotorasib sensitivity in PI3K knockout clones, where the most sensitive clone displayed reduced or no p4E-BP1 expression. CRISPR-Cas9-mediated knockout of 4E-BP1, either alone or in combination with PI3K knockout, dramatically restored sotorasib sensitivity to levels comparable to parental cells. Suppression of 4E-BP1 hyperphosphorylation required dual inhibition of mTORC1 and mTORC2, and treatment with AZD8055 or sapanisertib (mTORC1/2 dual inhibitors) significantly dephosphorylated 4E-BP1 and restored sotorasib sensitivity in resistant cells and PDXOs. In PDX, CDX, and xenograft models in vivo, the combination of sotorasib with either copanlisib or sapanisertib resulted in robust, synergistic, and durable tumor regression at well-tolerated doses. These findings showed the critical role of PI3K/mTOR signaling as a bypass mechanism of resistance to KRASG12C inhibitors. We conclude that mTORC1/2 mediated inhibition of p4E-BP1 and combination strategies targeting this pathway effectively overcome acquired resistance to KRASG12C inhibitors in NSCLC.

cancer biology↗

bioRxiv2025

Longitudinal analysis of retinal cell state transitions in RB1-deficient retinal organoids reveals the nascent cone precursors are the earliest cell-origin of human retinoblastoma

All cancers develop from malignant transformation of normal cells, while it is challenging to identify these "cells-of-origin" since it is impossible to witness the dynamic changes in human cancers. Retinoblastoma (Rb), an intraocular malignant cancer, is a typical model for study the molecular and cellular mechanisms of cancers. Although the maturing cone precursors (CPs) are proposed as the cellular origin of human Rb, it is unknow whether other retinal cells are also sensitive to RB1 inactivation. Here we developed RB1-deficient human retinal organoids (ROs) models from RB1-/- or RB1+/- human induced pluripotent stem cells (hiPSCs). RB1-/- hiPSCs developed into Rb tumors which recapitulated the features of human native Rb and had the ability to form consecutive orthotopic xenografts in mice. Importantly, RB1 loss induced the overproliferation of ATOH7+ neurogenic retinal progenitor cells (nRPCs), which disrupted the retinal development by generating proliferative, nascent retinal cells including retinal ganglion cells and CPs. scRNA-seq analysis verified the ATOH7+/RXR{gamma}+ nascent CPs survived and finally drove Rb development. In contrast, monoallelic RB1 inactivation with low pRB expression did not induce nascent CPs proliferation, but only induced nRPCs overproliferation which caused retinocytoma-like phenotype. Finally, a potential therapeutic agent for Rb was identified from multi-omics data. Our findings firstly indicate that nRPCs are the most sensitive cells to RB1 loss inducing nascent retinal cells abnormal proliferation, and ATOH7+ nascent CPs are the earliest cellular origin of human Rb, facilitating drug development for Rb.

cell biology↗

bioRxiv2025

CHIEF: An Attention-based Ensemble Learning Framework for Functional Protein Design

Protein de novo design is a longstanding challenge in biological field due to the multifaceted physicochemical properties and complexities of proteins. Several deep learning models have emerged for protein de novo design. However, each model exhibits distinct strengths and limitations because of the differences in training strategies or neural network architectures. Therefore, improving the effectiveness of protein design, particularly for functional protein, requires further improvement. To tackle this challenge, we developed CHIEF (Chimera Ensemble Inverse Folding), an attention-based ensemble framework that integrates five pretrained base models (ProteinMPNN-vanilla, ProteinMPNN-soluble, ESM-IF, Frame2seq and PiFold) to leverage their complementary strengths and mitigate limitations. Compared with the base models, CHIEF significantly improved the sequence recovery rate by 16.6-28.0%, while reducing the prediction perplexity by 22.7-34.6%. CHIEF also exhibited superior protein-designing capacity in variable sequence- and structure-based metrics and in large and complex proteins. CHIEF dynamically captured the semantic information from base models in a context-dependent manner and was minimally affected by the ablation of each base model. More importantly, CHIEF demonstrates real-world applicability to design functional malate dehydrogenase (MDH), achieving a 100% success rate. In summary, our study develops an ensemble deep learning model that improves the efficacy of protein sequence design, and will be a valuable platform for protein engineering and drug development.

bioengineering↗

bioRxiv2025

Benchmarking Pre-trained Genomic Language Models for RNA Sequence-Related Predictive Applications

RNA plays a pivotal role in diverse cellular functions across organisms. Developing computational algorithms for RNA sequence related questions is highly valuable. Recently, genomic language models (gLMs) with pre-training have emerged, offering flexibility for various downstream prediction tasks. However, comprehensive and fair evaluations of gLMs are lacking. In this study, we benchmark eight gLMs on prediction tasks covering four RNA processes, highlighting their strengths and limitations. While gLMs excel in performance overall, the larger model is not always better. Interestingly, models that integrate biological information consistently perform well in related tasks. Notably, gLMs demonstrate superior performance with limited training data, whereas task-specific methods achieve comparable performance with better computational efficiency when sufficient training data is available. Finally, we provide recommendations for model selection in different scenarios. These evaluation results underscore the potential of gLMs and suggest areas for future improvement.

genomics↗

bioRxiv2025

Tumor hypoxia adaptation depends on FLAD1 mediated mitochondrial metabolic reprogramming

Hypoxia, a hallmark of solid tumors, promotes the malignant progression and is challenging to target. Metabolic reprogramming and the resulting metabolic vulnerabilities provide a promising strategy to target tumor hypoxia. Here we systematically compared the metabolic network differences between hypoxic and non-hypoxic cells, and developed a deep learning model, "DepFormer", to predict the dependent metabolic genes in hypoxic tumor cells. The performance of DepFormer was validated using CRISPR screening dataset. Oxidative phosphorylation was identified as the most significantly hypoxia-dependent metabolic pathway, and FLAD1 was predicted to be one of the key hypoxia-dependent metabolic genes. FLAD1 locus is amplified, and FLAD1 expression is upregulated in various tumor types, especially in hypoxic tumors. FLAD1 depletion compromises tumors adaptation to hypoxia by disrupting mitochondrial complex II activity, leading to an imbalance between succinate and fumarate, and consequent failure to adapt to hypoxia. Subsequently, we identified a drug-like inhibitor of FLAD1, which selectively inhibits the growth of tumor cells under hypoxia. Our findings reveal FLAD1 as an innovative therapeutic target for hypoxic tumors.

cancer biology↗

bioRxiv2025

Evaluating a Standard Benchmark for Gene Prioritization: The InheriNext(R) Algorithm's Integration of Genomic and Phenotypic Information

This study presents a comprehensive benchmark analysis of InheriNext(R), a domain-specific, AI-powered tool designed for phenotype-driven pathogenic variant prioritization. For this study, 7,244 whole exome test cases were generated using phenotype and genotype data from Phenopackets, along with pools of variants from healthy individuals to serve as genomic backgrounds. Performance was evaluated across diverse testing scenarios and compared against four established tools. The results show InheriNext(R) achieving a 98.6% sensitivity in identifying pathogenic variants and consistent performance across diverse tests for variant types, phenotype counts, and disease groups--supporting the robustness and adaptability of its methodology. Sharing these benchmarking results and samples is intended to drive progress by assisting clinicians and researchers in evaluating interpretation tools and identifying areas for improvement.

genomics↗