Biology subjects

Zhuang, J.

Publications and source records attributed to Zhuang, J..

At least 19 recordsLinked to original sources

bioRxiv2026

Parasitic Vectors in Aquaculture: Neobenedenia girellae and Leeches as Potential Transmission Agents for Trypanosoma carassii spectrum and Pathogenic bacteria

Parasitic infections pose multifaceted threats to farmed fish, extending beyond direct pathogenicity to facilitate infections of bacteria, viruses, and microparasites. This synergistic interaction often leads to co-infections that significantly exacerbate disease outbreaks and mortality, presenting a severe challenge to aquaculture sustainability. Recently, a novel trypanosomiasis caused by the Trypanosoma carassii spectrum has emerged in cage-cultured Larimichthys crocea along the southeast coast of China, resulting in widespread prevalence and high mortality rates. Although this pathogen is hypothesized to originate from freshwater fish, its transmission route in marine environments has remained elusive. In this study, we investigated potential vectors and intermediate hosts of T. carassii spectrum, including leeches and monogenean in natural marine settings, and simulated transmission pathways using an established laboratory model involving T. carassii spectrum, Micropterus salmoides and the leech Poecilobdella manillensis. First, our field surveys in the coast of Ningde, Fujian Province, revealed a nearly 100% co-infection rate of T. carassii spectrum and the monogenean Neobenedenia girellae in diseased juvenile L. crocea. PCR analysis detected T. carassii spectrum traces in some N. girellae specimens, and subsequent experiments confirmed that N. girellae ingests the trypanosome while feeding on host blood. Furthermore, bacterial co-pathogens, such as Vibrio harveyi, were also detected within N. girellae. We also document two fatal leech infestations: Zeylanicobdella arugamensis in hybrid groupers (Epinephelus moara [female] X Epinephelus lanceolatus [male]) in Zhangpu, and Limnotrachelobdella okae in E. lanceolatus and E. fuscoguttatus in Raoping. These leeches tested negative for trypanosomes but carried pathogenic bacteria that co-infected the host fish; nonetheless, they are established vectors for trypanosome transmission. In a laboratory cohabitation model simulating T. carassii spectrum transmission, infected M. salmoides were housed with healthy conspecifics under three conditions: Group A (with the leech P. manillensis), Group B (no leeches), and Group C (no leeches, with physical separation between infected and healthy fish). After 14 days, blood smear microscopy and PCR analysis revealed infection rates in healthy fish of 58.33% in Group A, 40.00% in Group B, and 0% in Group C. Conclusively, T. carassii spectrum can be transmitted via leeches (with higher efficiency) and may also spread through direct contact under high-density aquaculture conditions, whereas N. girellae may act as an incidental vector, further research is warranted to clarify transmission dynamics in natural marine ecosystems. Additionally, our findings highlight the role of ectoparasites, including N. girellae and leeches, as potential reservoirs and vectors for bacterial pathogens of fish. In high-density intensive aquaculture, this vectorial capacity transforms parasites from primary pathogens into key drivers of polymicrobial disease outbreaks.

zoology↗

bioRxiv2026

Modeling Meibomian Gland Development and Dysfunction: A Mouse-Derived Organoid System Reveals Hippo-YAP as a Critical Regulator

The developmental program governing meibomian gland (MG) morphogenesis and proliferation remains poorly understood, largely due to the lack of physiologically relevant model systems. Here, we established a novel high-fidelity, three-dimensional organoids model derived from mouse meibomian gland (mMGO) epithelium. Transcriptomic and phenotypic analyses demonstrated that mMGOs faithfully recapitulate postnatal gland development in vivo, including dynamic transcription program, branching morphogenesis, lineage differentiation, and functional lipid accumulation. Leveraging this model, we identified the Hippo-YAP pathway as a pivotal regulator of MG epithelial proliferation and homeostasis for the first time. YAP inhibition severely impaired organoids growth, while pharmacological inhibition of Hippo pathway with XMU-MP-1 enhanced proliferation and progenitor clonogenicity. Crucially, in inflammation-induced atrophic organoids, XMU-MP-1 treatment rescued YAP nuclear localization and stimulated regrowth and functional restoration. Our study provided new mechanistic insights and a robust organoids platform for MG development research, and nominated targeted Hippo pathway inhibition as a promising strategy to reverse glandular atrophy in meibomian gland dysfunction.

developmental biology↗

bioRxiv2026

The Spatiotemporal Proteome Landscape of Aging: Structural determinants of age-sensitive proteome remodeling

Aging is marked by a decline in cellular functions accompanied by widespread changes in mRNA and protein abundance, yet whether aging broadly remodels subcellular protein localization and concentration--and why some proteins change while others remain stable--remains unclear. This gap matters because cellular function depends not only on expression levels but also on correct spatial organization. Using yeast replicative aging as a model, we built a robotic pipeline to enrich old cells from 5,661 strains, acquired 90 million single-cell 3D images, and applied machine learning to map proteome-wide changes in localization, concentration, and aggregation throughout aging. This age-resolved single-cell atlas uncovers widespread proteome remodeling and rewiring of protein interaction networks. Moreover, structural analysis reveals biophysical determinants of age-sensitive proteome remodeling across ages and species. Together, these results reveal a structure-encoded intrinsic principle underlying spatial proteome breakdown during aging and provide a resource to dissect mechanistic links among aging hallmarks.

systems biology↗

bioRxiv2026

Single-Cell Spatial Proteomics Uncovers Molecular Interconnectivity among Hallmarks of Aging

Aging is accompanied by conserved hallmarks including genomic instability, epigenetic alterations, loss of proteostasis, and mitochondrial dysfunction, but how these processes emerge and become mechanistically linked remains unclear. Here we leverage a proteome-wide, single-cell, subcellular atlas of protein expression, localization, and aggregation across yeast replicative aging to map hallmark-linked remodeling in its spatial context. We identify hundreds of previously unappreciated molecular changes that underlie major hallmarks of aging and show that hallmark phenotypes frequently manifest as compartment-specific erosion of spatial confinement, relocalization, and aggregation. 91.6% human orthologs of these hallmark-linked yeast proteins also change during human aging. Integrating these spatial phenotypes reveals many molecular connections linking different hallmarks. Temporal analysis suggests that disorganization of nucleolar ribosome biogenesis, proteostasis decline, and mitochondrial dysfunction precede other hallmarks. Together, our findings substantially deepen the molecular underpinnings of aging hallmarks and provide a framework for linking them into a hierarchical sequence of cellular failures.

systems biology↗

bioRxiv2025

The Hippo Pathway Regulates Corneal Endothelial Regeneration

Corneal endothelial cells (CECs) have limited regeneration capacity in primates while display a potent restorative capability in some species such as rodents after wounding. The mechanism which determines the regenerative capability of CECs remains poorly understood. Here, we identify that the Hippo signaling pathway is inhibited and the downstream effector YAP is activated during CEC wound healing in rabbit and mouse. Knockdown of Yap1 and pharmacological inhibition of YAP suppresses CECs wound healing in rodents in both in vitro and in vivo models. XMU-MP-1, a specific small molecular inhibitor for Hippo signaling pathway, can promote the corneal endothelial regeneration in rodents and corneal endothelial proliferation in cultured primate CECs, as well as in vivo non-human primate CEC wounding model. These findings suggest that Hippo pathway serves as a conserved signal to regulate corneal endothelial regeneration among various species, providing a novel target for non-invasive treatment of corneal endothelium decompensation.

cell biology↗

bioRxiv2025

A standardized and reproducible behavioral protocol to elicit visual spatial attention in mice

Understanding how neural activity gives rise to cognitive processes such as selective attention is a fundamental goal of neuroscience. An important but often overlooked advance towards this goal requires the development and sharing of rigorous and reproducible behavioral tasks across labs; this is particularly important given the recent surge in studies of cognition and perception in mice. Here, we developed a standardized training protocol for head-fixed mice to become experts in a psychometric visual contrast detection task in just 17 days. Experts detected stimuli at two distinct spatial locations for several hundred trials per day. As consecutive trials elapsed at either location, the speed, accuracy, and contrast sensitivity of visual perception improved - all hallmarks of spatial attention improving performance, as seen in primates. These findings validate the efficacy of this protocol to reveal multiple aspects of selective spatial attention in mice, establishing a rigorous and reproducible tool for the community.

neuroscience↗

bioRxiv2025

Sequence-aware Prediction of Point Mutation-induced Effects on Protein-Protein Binding Affinity using Deep Learning

Amino acid mutations may lead to significant changes in the binding affinity of protein complexes, thereby causing a series of cellular dysfunctions. Therefore, accurate prediction of protein-protein binding affinity changes ({Delta}{Delta}G) induced by amino acid mutations is of great importance for understanding protein-protein interactions (PPIs). In this study, we propose SAMAffinity, a protein sequence-aware deep learning architecture for predicting changes in protein-protein binding affinity caused by amino acid mutations. SAMAffinity predicts mutation-induced {Delta}{Delta}G by integrating multi-source sequence features, leveraging a Mutation-Site Identification (MSI) module to highlight local semantic shifts and a Binding-Interface Awareness (BIA) module to capture interaction changes. Benchmark evaluations on public datasets show that under the mutation-level data splitting strategy, SAMAffinity outperforms the state-of-the-art sequence-based method AttABseq by 33.3%, 72.3%, 31.8%, and 30.5% on S1131, S4169, S645, and M1101 datasets, respectively. Moreover, under the complex-level data splitting strategy, SAMAffinity surpasses the structure-based method MpbPPI by 22.9%, 22.7%, 5.0%, and 11.4% on the corresponding datasets. Beyond predictive accuracy, the strong consistency between the models predicted distribution and natural amino-acid mutation tendencies indicates that SAMAffinity effectively captures the underlying mutational landscape shaped by intrinsic biochemical and evolutionary factors. Based on this capability, SAMAffinity demonstrated strong generalization in a study of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cases, suggesting its potential for optimizing therapeutic antibody design.

bioinformatics↗

bioRxiv2025

High-accuracy structure modeling for antibody-antigen complexes

Accurate modeling of antibody-antigen complexes is crucial for advancing therapeutics and diagnostics, yet predicting their binding interface remains a formidable challenge. To address this, we introduce DeepAAAssembly, a protocol that enhances static structural information from AlphaFold3 by integrating dynamic interaction patterns to guide complex assembly. Our approach leverages predicted inter-chain residue distances to construct a flexibility-aware energy function, which drives a two-stage conformational sampling process for global exploration and local exploitation. On a benchmark set of 67 representative antibody-antigen complexes, by incorporating a built-in confidence selection mechanism, DeepAAAssembly outperforms AlphaFold3, achieving not only a 12.9% higher average DockQ score and more medium- and high-quality models, but also reliably elevating the most challenging cases from incorrect to acceptable accuracy. These results demonstrate that DeepAAAssembly effectively captures conserved interaction motifs and conformational flexibility, offering a robust framework for high-accuracy antibody-antigen modeling.

bioinformatics↗

bioRxiv2025

MultiSAAI: Sequence-informed Antibody-Antigen Interactions Prediction using Multi-scale Deep Learning

MotivationAntibodies possess high specificity toward target antigens, making them critical for therapeutic applications. However, experimental screening of antibody-antigen interactions is labor-intensive and costly. Existing structure-based computational methods often face significant challenges in modeling the dynamic conformational flexibility that governs antibody-antigen interactions, which limits their ability to accurately identify binding. Therefore, there is an urgent need for accurate and efficient sequence-based prediction method to accelerate antibody discovery and reduce experimental burden. ResultsWe propose MultiSAAI, a sequence-informed framework that models antibody-antigen interactions by explicitly accounting for the distinct roles of antibody heavy and light chains in antigen binding. MultiSAAI integrates language model embeddings, physicochemical properties, geometric constraints, and residue substitutability to characterize antibody-antigen interactions across multiple scales, employing a multi-scale network architecture that simultaneously evaluates global residue-pair compatibility and local amino acid fitness at the binding interface. Furthermore, the incorporation of site-specific information and biologically grounded binding principles allows the model to more closely reflect the actual mechanisms of interactions. Benchmark results demonstrate that MultiSAAI achieves AUROC scores of 0.757 on the generic antibody-antigen interactions dataset and 0.946 on the SARS-CoV-2 dataset, outperforming existing methods such as A2binder and AbAgIntPre. Finally, large-scale preliminary antibody screening further validates the potential of MultiSAAI for high-throughput therapeutic antibody discovery.

bioinformatics↗

bioRxiv2025

The HORMA-domain protein ASY1 recruits the plant-specific cyclin SDS to promote DMC1-mediated meiotic recombination

The chromosome axis is a proteinaceous scaffold essential for crossover formation in meiosis. While the axis associated HORMA-domain protein ASY1 is known to be necessary for the localization of the recombinase DMC1 to the axis, the molecular mechanism linking ASY1 to DMC1 loading remains unclear. Here, we demonstrate that ASY1 directly recruits the plant-specific cyclin SDS to chromosomes, which ensures efficient DMC1 localization and interhomolog recombination. Live-cell imaging and immunodetection revealed that SDS localizes to chromosomes from leptotene to zygotene and dissociates from chromosomes after pachytene resembling DMC1 dynamics. Biochemical assays demonstrated a direct interaction between ASY1 and SDS. Further analyses revealed that ASY1s closure motif, a conformational regulatory element, is required for SDS recruitment despite being dispensable for ASY1s own chromosome association. Moreover, unlike in sds mutants, depletion of the DMC1 inhibitor FIGL1-FLIP complex failed to restore DMC1 foci in asy1 mutants, positioning ASY1 upstream of both positive (SDS) and negative (FIGL1-FLIP) regulators of DMC1. These findings establish ASY1 as a key coordinator of meiotic recombination, bridging chromosome axis architecture with recombinase dynamics to control crossover formation and genome stability.

plant biology↗

bioRxiv2025

Integrated Classification of Cortical Cells and Quantitative Projectomic Mapping Unveil Organizational Principles of Brain-Wide Connectomes at Single Cell Level

Molecularly defined cortical cell types have recently been linked to whole neuronal morphology (WNM), particularly those characterized by whole-brain-wide projections, such as intratelencephalic (IT), extratelencephalic (ET), and corticothalamic (CT) neurons. In contrast, classical morphological classifications (e.g., tufted TPC, small tufted SPC, and stellate SSC) are based primarily on local dendrosomatic and axonal structures, especially apical dendrites. This study bridges these perspectives by establishing a new neuronal taxonomy, analyzing the connectomes of defined cortical cell types, and comparing them with those obtained from bulk anterograde injections. Neurons were sparsely labeled via tamoxifen-inducible Cre lines with GFP reporters, and 1,419 WNM cells were comprehensively reconstructed with Vaa3D-TeraVR from [~]15 areas across six functional regions of molecularly labeled brains imaged with 2p-fMOST. These cells were newly classified by integrating current molecular-WNM and classical morphological perspectives, with sample size augmented by 1,455 publicly available WNM cells reconstructed from the Mouse-Light project and CEBSIT. This effort defined ten combined molecular-WNM-classical morphological cell types: L5ET_TPC, L6CT_NPC, L6b_HPC, and seven IT types--L2/3IT_TPC, L4IT_SSC, L4IT_UPC, L4IT_TPC, L5IT_SPC, L6IT_IPC, and L6IT_car3PC. Clustering, quantitative analyses and random Forest classifier objectively validated these types and revealed their distinct connectomes, along with convergent, topographic, and hierarchical organizations across their projection brain regions. At the single-cell level, multiple organizational principles governing cortico-cortical (C-C) and cortico-subcortical (C-subC) connectomes emerged with unprecedented detail, offering a precise GPS-like tool for in vivo recordings and robust datasets for neuronal network modeling. Comparisons with bulk anterograde injection data underscored the limitations of traditional methods in identifying projection targets. Overall, our approach provides significant insights into cortical circuitry and elucidates the complex interplay between neuronal molecular identity, whole morphology, and classical morphological classification.

neuroscience↗

bioRxiv2025

Hebb's Vision: The Structural Underpinnings of Hebbian Assemblies

1In 1949, Donald Hebb proposed that groups of neurons that activate stereotypically form the organizational building blocks of perception, cognition, and behavior. Finding the structural underpinning of such assemblies has been technically challenging, due to a lack of large-scale structure-activity maps. Here, we analyze this relation using a novel dataset that links in vivo optical physiology to connectivity using postmortem elec-tron microscopy (EM). From the fluorescence traces, we extract neural assemblies from higher-order correlations in neural activity. Physiologically, we show that these assemblies exhibit properties consistent with Hebbs theory, including more reliable responses to repeated natural movie inputs than size-matched random ensembles and superior decoding of visual stimuli. Structurally, we find that neurons that participate in assemblies are significantly more integrated into the structural network than those that do not. Contrary to Hebbs original prediction, we do not observe a marked increase in the strength of monosynaptic excitatory connections between cells participating in the same assembly. However, we find significantly stronger indirect feed-forward inhibitory connections targeting cells in other assemblies. These results show that assemblies can be useful components of perception, and, surprisingly, they are delineated by mutual inhibition.

neuroscience↗

bioRxiv2025

A unified eIF1A+ luminal cells-centered hypoxic and "cold" tumor microenvironment promotes PCa progression among different subtypes

PCa is a malignancy with high heterogeneity arises from both tumor microenvironment (TME) and histological subtypes. To achieve superior clinical efficacy, it is imperative to identify unified progression drivers within such heterogeneity in PCa, thereby enabling the development of more consistent and effective therapeutic strategies. In this study, we applied imaging mass cytometry to stain 39 proteins on 71 tissues comprising para-cancer, low-grade acinar adenocarcinoma (LgPAC), high-grade PAC (HgPAC), intraductal carcinoma (IDC) and ductal adenocarcinoma (DAC) tissues, obtaining the spatial proteomic landscape of 345,233 single cells. We discovered a hypoxic eIF1A+ luminal epithelial (LE) cluster exhibiting both translational activation and immunosuppressive properties, which was enriched in high-risk PCa including HgPAC, IDC and DAC, and associated which tumor progression and unfavorable prognosis. Additionally, eIF1A+ LE orchestrates the formation of an immunologically "cold" TME, characterized by the low infiltration of anti-cancer immune cells including PD1- T cells CD163- macrophages. Through in vivo validation and investigator-initiated study, we further found that Homoharringtonine, an inhibitor targeting protein translation process, effectively inhibited PCa growth, alleviated hypoxic microenvironment, and enhanced immune cell infiltration. This study is the first to apply spatial proteomics to delineate consistent molecular features across histological subtypes, providing transformative insights for clinical management of PCa.

cancer biology↗

bioRxiv2025

Inhibition of DHODH Activates Pyroptosis and cGAS-STING Pathways to Enhance NK cell Infiltration Mediated Anti-tumor Immunity in Melanoma

Cancer cells are heavily reliant on de novo pyrimidine synthesis. Suppression of pyrimidine metabolism directly inhibits tumor growth and fosters immune activation within the tumor microenvironment. Dihydroorotate dehydrogenase (DHODH), a crucial enzyme governing de novo pyrimidine synthesis, is a critical player in this context. Inhibition of DHODH not only reverses immunosuppression but also instigates a mild innate immune response. However, the impact of DHODH inhibition on natural killer (NK) cells remains unexplored. In this study, we found that inhibition of DHODH efficiently promotes NK cells infiltration in tumors. Suppression of DHODH led to increased oxidative stress in mitochondria, the release of mtDNA, and activation of caspase 3, which in turn activated the cGAS-STING pathway and pyroptosis in cancer cells, respectively, contributing to NK cells induced antitumor immune responses in melanoma. Additionally, we developed EA6, a novel DHODH inhibitor with higher efficacy in promoting NK cells infiltration. In summary, this study underscores that modulation of pyrimidine metabolism can effectively trigger antitumor immune responses, with a specific emphasis on NK cells. This finding opens new avenues for enhancing the efficacy of targeted nucleotide metabolism in cancer therapy. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=141 SRC="FIGDIR/small/644471v1_ufig1.gif" ALT="Figure 1"> View larger version (60K): org.highwire.dtl.DTLVardef@88d4fcorg.highwire.dtl.DTLVardef@156fe1aorg.highwire.dtl.DTLVardef@448086org.highwire.dtl.DTLVardef@152079c_HPS_FORMAT_FIGEXP M_FIG C_FIG The anti-tumor mechanisms of DHODH inhibition. Inhibition of DHODH activates cGAS-STING pathways to enhance NK cell infiltration. And the tumor-infiltrating NK cells facilitate melanoma cells pyroptosis which providing a positive feedback mechanism for DHODH-mediated anti-tumor immunity.

cancer biology↗

bioRxiv2024

DeepAssembly2: A Web Server for Protein Complex Structure Assembly Based on Domain-Domain Interactions

Proteins often perform biological functions by forming complexes, thereby accurately predicting the structure of protein complexes is crucial to understanding and mastering their functions, as well as facilitating drug discovery. Protein monomeric structure prediction has made a breakthrough in recent years, but the accurate prediction of complex structure remains a challenge. In this work, we present DeepAssembly2, a web server for automatically assembling protein complex structure based on domain-domain interactions. First, the features are constructed according to the input complex sequence and monomeric structures, then these features are used to predict the inter-chain residue distance through a deep learning model, and finally, the complex structure is assembled under the guidance of inter-chain residue distances. Compared with the previously developed version, DeepAssembly2 is trained on a newly constructed inter-chain domain-domain interaction dataset. Meanwhile, several important features have been added, such as Interface Residue Propensity and Ultrafast Shape Recognition. In addition, we introduced the inter-chain residue distance from the AlphaFold-Multimer model to further improve the accuracy. Finally, we also integrate our recently developed model quality assessment method to select the output models. The performance of DeepAssembly2 is significantly improved compared with the previous version, providing a solution for large protein complex structure modeling through divide-and-conquer assembly strategy, and is expected to provide new insights and an effective tool for drug development, vaccine design, etc. The web server of DeepAssembly2 is freely available at http://zhanglab-bioinf.com/DeepAssembly/.

bioinformatics↗

bioRxiv2024

Unveiling the Intricate Sinking behavior of Large Diatoms: Insights from Time-Frequency Analysis of Palmerina hardmaniana Sinking under Silicate-Depleted Conditions

Nutrient limits impact diatom sinking in time domain, but response in time-frequency domain is unclear. Studying the response of large diatoms to nutrients exclusively in the time domain fails to fully capture the complete impact of nutrient limitations on sinking behavior due to the absence of crucial information, including period and frequency. Wavelet analysis provides valuable insights into the period and frequency of signals and unveils their positions in the time. This study investigated the sinking behavior response of the large diatom Palmerina hardmaniana to silicate-depleted conditions in the time-frequency domain using wavelet analysis. The results showed that P. hardmaniana was capable of regulating its sinking speed, and this regulation occurred intermittently in time. The predominant frequency of intermittent regulation fell within the range of 0.13-0.50 Hz (equivalent to a period of 2-8 s) for both control and silicate-depleted conditions. The similarity in the frequency range of regulation between the two groups suggests the involvement of shared physiological mechanisms. P. hardmaniana responded to silicate depletion by intensifying the regulation of 0.13-0.50 Hz, which was reflected in the time domain as a change in the proportion of different instantaneous sinking speeds and consequently lead to a significant increase or decrease in the mean sinking speed (p<0.05). Additionally, the regulation of P. hardmaniana sinking behavior was also influenced by the physiological state of the cells. Short-term silicate stress (30 min) enhanced the oscillation power of sinking regulation, while prolonged silicate stress ([≥] 3 d) led to a decline in oscillation power.

plant biology↗

bioRxiv2024

Thymidine Phosphorylase Promotes the Formation of Abdominal Aortic Aneurysm in Mice Fed a Western Diet

AimsThe precise molecular drivers of abdominal aortic aneurysm (AAA) remain unclear. Thymidine phosphorylase (TYMP) contributes to increased platelet activation, thrombosis, and inflammation, all of which are key factors in AAA development. Additionally, TYMP suppresses the proliferation of vascular smooth muscle cells (VSMCs), which are central to the development and progression of AAA. We hypothesize that TYMP plays a key role in AAA development. Methods and ResultsWe conducted a histological study using human AAA samples and normal abdominal aortas, revealing heightened levels of TYMP in human AAA vessel walls. To validate this observation, we utilized an Ang II perfusion-induced AAA model in wild-type C57BL/6J (WT) and Tymp-/-mice, feeding them a Western diet (TD.88137) starting from 4 weeks of age. We found that Tymp-/-mice were protected from Ang II perfusion-induced AAA formation. Furthermore, by using TYMP-expressing VSMCs as well as primarily cultured VSMCs from WT and Tymp-/- mice, we elucidated the essential role of TYMP in regulating MMP2 expression and activation. TYMP deficiency or inhibition by tipiracil, a selective TYMP inhibitor, led to reduced MMP2 production, release, and activation in VSMCs. Additionally, TYMP was found to promote pro-inflammatory cytokine expression systemically, and its absence attenuates TNF--stimulated activation of MMP2 and AKT. By co-culturing VSMCs and platelets, we observed that TYMP-deficient platelets had a reduced inhibitory effect on VSMC proliferation compared to WT platelets. Moreover, TYMP appeared to enhance the expression of activated TGF{beta}1 in cultured VSMCs in vitro and in human AAA vessel walls in vivo. TYMP also boosted the activation of thrombospondin-1 type 1 repeat domain-enhanced TGF{beta}1 signaling, resulting in increased connective tissue growth factor production. ConclusionOur findings collectively demonstrated that TYMP serves as a novel regulatory force in vascular biology, exerting influence over VSMC functionality and inflammatory responses that promote the development of AAA. Translational PerspectiveThymidine phosphorylase (TYMP) is increased in the vessel walls of patients with abdominal aortic aneurysm (AAA), and TYMP deficiency in mice reduces the incidence of AAA, suggesting that TYMP plays a crucial role in AAA development. This could be attributed to TYMPs role in enhancing systemic inflammation and thrombosis, inhibiting vascular smooth muscle cell function, increasing the activation of matrix metalloproteinase and AKT, as well as enhancing the expression of TGF{beta}1 and connective tissue growth factor. Tipiracil is an FDA-approved drug known to inhibit TYMP-enhanced thrombosis. Targeting TYMP with tipiracil could represent a promising new therapeutic strategy for AAA development.

cell biology↗

bioRxiv2024

Increased regional P2X7R expression detected by GSK1482160 PET in a tauopathy mouse model

Neuroinflammation plays an important role in Alzheimers disease and primary tauopathies. The aim of the current study was to map [18F]GSK1482160 for imaging of purinergic P2X7R in Alzheimers disease and primary tauopathy mouse models. MicroPET was performed using [18F]GSK1482160 in widely used mouse models of Alzheimers disease (APP/PS1, 5xFAD and 3xTg), 4-repeat tauopathy (rTg4510) mice and age-matched wild-type mice. Increased uptake of [18F]GSK1482160 was observed in the cortex and basal forebrain of 7-month-old rTg4510 mice compared to age-matched wild-type mice and compared to 3-month-old rTg4510 mice. Nonparametric Spearmans rank analysis revealed a positive correlation between tau [18F]APN-1607 uptake and [18F]GSK1482160 in the hippocampus of rTg4510 mice. No significant differences in the uptake of [18F]GSK1482160 were observed between wild-type mice and APP/PS1 mice (5, 10 months), 5xFAD mice (3, 7 months) or 3xTg mice (10 months). Immunofluorescence staining further indicated the distribution of P2X7Rs in the brains of 7-month-old rTg4510 mice with accumulation of tau inclusion compared to wild-type mice. These findings provide in vivo imaging evidence for increased P2X7R in the brains of tauopathy model mice.

neuroscience↗