Biology subjects

Gao, X.

Publications and source records attributed to Gao, X..

At least 91 records · Page 5Linked to original sources

bioRxiv2025

The Disruption and Normalization of Cortical Language Network Dynamics After Post-Stroke White Matter Disconnection

The human language network undergoes reorganization across different spatiotemporal scales, limited by its fixed structural neurobiological foundations. Although stroke often damages white matter, its effect on temporary language network reorganization is not fully understood. This study examined longitudinal behavioral and resting-state fMRI data from post-stroke patients with exclusive subcortical lesions at three time points: two weeks (n = 38), three months (n = 29), and one year (n = 27). Patients showed mild to moderate language impairments during the acute phase, which improved within three months. The extent of disconnection in several left-hemispheric white matter tracts was negatively associated with language deficits. Healthy controls (HC, n = 25) exhibited domain-segregation dynamics in the cortical language network, limited by the underlying white matter pathways. In patients, severe, state- and track-specific network disruptions were observed in the acute phase, characterized by hypo- and hyper-connectivity and abnormal topological features. As language recovery progressed, connectivity patterns began to return to normal, resembling those of HC, and the domain-segregation dynamics reappeared. These results deepen our understanding of structure-function coupling and indicate significant post-lesional plasticity within the cortical language network.

neuroscience↗

bioRxiv2025

Core gastric microbiota linked to pathogenesis and preserved across age stratified cohorts

Mounting evidences reveal a complex microbial niche in gastric environment. Nevertheless, the phylogenetic stability of gastric microbiota remains undetermined. Here, using full-length 16S rRNA and ITS amplicon sequencing applied to gastric brushes from a pediatric endoscopic cohort (n=243), we identified a core microbiota comprising 11 genera, which clustered into two antagonistic communities (CST1A and CST1B). CST1A was enriched in healthy subjects, while CST1B correlated with gastroduodenal disease. Notably, this bipartite architecture arose through bacterial interactions, with fungal taxa demonstrating minimal integration. Further stratified analyses revealed that H. pylori infection preferentially depleted CST1A taxa. The subclusters exhibited divergent metabolic profiles, with CST1A specializing in motility processes and CST1B in nucleotide/peptidoglycan synthesis. Cross-cohort validation of six datasets (n=1,183) confirmed the persistent relevance of the CST1A-CST1B structure across disease stages. Collectively, our findings define a core gastric microbiota established in early life, linked to gastric disease risk, and persisting into adulthood. HighlightsO_LIIdentification of a gastric bacterial network established in early life. C_LIO_LIDysbiosis in two subclusters within the core microbiota is associated with pediatric peptic ulcers. C_LIO_LIHelicobacter pylori infection reduces the abundance of the core microbiota, with a particularly greater inhibitory effect on CST1A. C_LIO_LIThe core microbiota is preserved across age stratified cohorts and is associated with gastric cancer. C_LI

microbiology↗

bioRxiv2025

Subtype-specific neutralizing antibodies promote antigenic shift during influenza virus co-infection

Reassortment between different influenza strains occurs when they co-infect the same host cell. The emergence of a reassortant virus depends on both its intrinsic fitness and extrinsic factors, including pre-existing humoral immunity. The generation of pandemic strains, such as H2N2 and H3N2, and zoonotic influenza A viruses, like H5N6, H5N8, and H7N9, in birds is suggested to be the result of extensive selection by pre-existing antibodies. To further explore the role of humoral immunity in reassortment, we generated two divergent fluorescent protein-expressing viruses and used strain-specific and cross-reactive monoclonal antibodies (mAbs) to assess the impact of cross-immunity on reassortment. Our results indicate that all mAbs altered the genotypic diversity and significantly reduced the release of progeny virions in co-infected cells both in vitro and in vivo. Moreover, antibody transfer studies in mice revealed protection from challenge with divergent pathogenicity profiles. Notably, selection driven by a strain-specific mAb depended on its neutralizing specificity, whereas the selection driven by broadly reactive mAbs was independent of neutralization specificity. Our findings demonstrate that pre-existing neutralizing antibodies shape reassortment and that strain-specific neutralizing antibodies promote antigenic shift during co-infection, which is not the case for broadly cross-reactive antibodies that recognize influenza viruses from different subtypes.

microbiology↗

bioRxiv2025

GeoGAT-site: A Face-Centered Geometric Graph Attention Network for Protein-Protein Interface Prediction

Protein-protein interactions (PPIs) underpin the intricate machinery of cellular life, orchestrating processes from signal transduction to metabolic regulation, yet their precise interface prediction remains a cornerstone challenge in structural biology, demanding scalable computational paradigms that balance accuracy and efficiency. Herein, we present GeoGAT-site, a pioneering geometric graph attention network that leverages face-centered surface fingerprints extracted from three-dimensional protein architectures to forecast interaction sites. Diverging from conventional vertex-centric approaches, our face-centered methodology achieves a 3.64-fold acceleration in patch generation, mitigating computational bottlenecks while preserving granular surface descriptors. At its core, GeoGAT-site incorporates a bespoke attention mechanism that adaptively modulates inter-facial distances and normal vector orientations, synergistically integrating spatial geometries with physicochemical attributes for nuanced interface delineation. Harnessing a meticulously curated dataset of 150 million face-centered fingerprints from over 20,000 structurally diverse proteins, the model attains robust generalization across heterogeneous interaction motifs. Empirical validation on an independent cohort of 167 protein complexes yields a ROC AUC of 0.89, surpassing established benchmarks including MaSIF-site (0.845), SPPIDER (0.65), and PSIVER (0.63). By furnishing high-fidelity interface annotations, GeoGAT-site augments downstream structural modeling paradigms through targeted constraints, thereby providing a versatile scaffold for unraveling PPI dynamics with profound implications for therapeutic discovery, protein redesign, and molecular epistemology.

bioinformatics↗

bioRxiv2025

Chemerin-CMKLR1 mediated OGD/R induced Mitochondrial Dysfunction, Oxidative Stress, and Autophagy differentially in Microglia and Neurons

IntroductionIschemia-reperfusion (I/R) injury exacerbates tissue damage upon reperfusion after ischemia. The impact of chemerin and its receptor, chemokine-like receptor 1 (CMKLR1) on I/R injury remains poorly understood. We hypothesized that chemerin-CMKLR1 differentially regulates signaling in microglia and neuronal cells oxygen-glucose deprivation/reoxygenation (OGD/R), influencing mitochondrial function, oxidative stress, and autophagy. MethodsUsing BV2 microglia and Neuro-2a (N2a) neuronal cells, we examined OGD/R-induced changes in autophagy associated proteins, chemerin and CMKLR1 expression. We investigated the functional consequences of CMKLR1 overexpression and chemerin treatment on oxidative stress, apoptosis, autophagy, and mitochondrial dynamics in BV2 microglia and N2a neuronal cells. ResultsOGD/R downregulated CMKLR1 while upregulating autophagy in both BV2 microglia and N2a cells; While chemerin expression decreased in BV2 microglia but increased in N2a cells following OGD/R. Treatment with chemerin dose-dependently reduced oxidative stress and apoptosis while enhancing mitochondrial fusion, suppressing fission, and promoting autophagy and mitochondrial function in both cell types under OGD/R. CMKLR1 overexpression exacerbated mitochondrial respiratory dysfunction, mitochondrial fusion, fission, and elevated autophagy (LC3II/LC3I and Pink1 levels), with cell-type-specific differences observed in Parkin and P62 regulation. ConclusionOur study demonstrates cell-type-specific regulation of chemerin-CMKLR1 signaling in I/R injury, and distinct mitophagy activation mechanisms in microglia and neurons. These findings suggest cell-type specific modulation of chemerin-CMKLR1 as a potential therapeutic target in preserving mitochondrial homeostasis, modulating autophagy, mitophagy and reducing oxidative stress, apoptosis in both microglia and neurons for mitigating I/R injury.

neuroscience↗

bioRxiv2025

A high-quality bread wheat genome unravels adaptive evolution of wheat end-use quality

Understanding the genetics of superior dough performance is essential for improving wheat end-use quality. Here, we presented a de novo assembly of the genome of JM44, a Chinese wheat cultivar known for its exceptional end-use quality. The JM44 genome achieved reference-level quality (QV = 66.74), depicting a complete picture of complex regions containing gluten genes. Our microsynteny analysis across the Triticum-Aegilops complex showed that high-molecular-weight glutenin subunits (HMW-GSs) loci are highly conserved, while low-molecular-weight glutenin subunits (LMW-GSs) and -/{beta}-gliadins exhibited greater structural variation. These variable loci appear to have been preferentially selected by humans and contributed substantially to the evolution of wheat quality traits. Moreover, we observed that epistatic interactions between gluten genes are strong in modern cultivars, but markedly weaker in landraces, indicating the importance of epistatic selection during modern breeding. Our findings shed light on the genomics and evolution of wheat quality traits, providing valuable guidance for future breeding efforts.

genomics↗

bioRxiv2025

MICRORNAS REGULATED BY PREGNANCY TARGET THE HIV INTERACTOME

Innate immunity predictors of HIV risk are influenced by reproductive hormone levels, pregnancy, and lactation status. However, the molecular mechanisms underlying these associations remain unclear. MicroRNAs (miRNAs), as post-transcriptional regulators, play key roles in immune regulation and host-virus interactions. We hypothesized that physiological adaptations to pregnancy include the modulation of systemic miRNA expression, which in turn regulates host genes involved in HIV interaction, potentially influencing susceptibility during pregnancy. To test this, we leveraged a large longitudinal cohort from Uganda and Zimbabwe and analyzed 174 serum samples from 88 participants in pre-pregnancy (PP), pregnancy (P), and breastfeeding (BF) states using the HTG EdgeSeq platform. Differentially expressed (DE) miRNAs in pregnancy were identified with false discovery rate (FDR) < 0.1 (29 upregulated and 131 downregulated) by intersecting pairwise comparisons (P vs. PP and P vs. BF). Validated gene targets (2,733) were identified via miRWalk and modular enrichment analysis performed using Cytoscape/ClueGO. Enriched pathways (FDR<0.05) included Adaptive Immune Response, Hippo Signaling, Cellular Senescence, HSV-1 Infection, and two cancer-related pathways. Genes from pregnancy-enriched pathways overlapped with the known HIV-host interactome at the range of 37 to 88%. From this overlap, the Maximal Clique Centrally (MCC) score (cytoHubba) identified 47 unique hub genes acting as essential regulatory nodes of protein-protein interaction (PPI) network. These hub genes were further examined by their expression patterns predicted by DE miRNAs, and explored for their interactions with the HIV interactome, revealing connectivity with 18 HIV proteins - highest with Tat and gp120 - and impact on the HIV replication process. HLA-A was the most connected host gene, followed by BCL2L1, EIF2AK2, PTEN, and CYCS. These findings support the hypothesis that pregnancy-driven systemic miRNAs may shape HIV susceptibility by regulating hub genes with central role in viral evasion of host immunity. GRAPHIC ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=138 HEIGHT=200 SRC="FIGDIR/small/665982v1_ufig1.gif" ALT="Figure 1"> View larger version (17K): org.highwire.dtl.DTLVardef@1cd2007org.highwire.dtl.DTLVardef@1f1b9d3org.highwire.dtl.DTLVardef@dee856org.highwire.dtl.DTLVardef@6796c2_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2025

MICRORNAS AS REGULATORS OF DRUG METABOLISM AND TRANSPORT IN PREGNANT AND LACTATING WOMEN

BackgroundPhysiological changes during pregnancy result in altered maternal drug metabolism that impacts efficacy and safety of therapeutics in pregnant women. Pregnancy induced hormonal, immunologic, or metabolic changes may also influence and alter drug disposition. Despite research efforts focused on pharmacokinetics of medications used in pregnant women in the past decade, knowledge gaps exist in understanding how pregnancy influences drug disposition and placental drug transporters. Moreover, there is a scarcity of research in understanding the safety and effectiveness of therapeutics in lactating women. This study aimed to determine the effect of pregnancy on levels of miRNAs regulating drug metabolizing enzymes and transporters (DMET). MethodsWe utilized longitudinal serum specimens collected in 3-month intervals from 88 women who became pregnant during follow-up in a large prospective study of hormonal contraception and HIV acquisition in Uganda and Zimbabwe. We used the HTG EdgeSeq platform coupled with Illumina sequencing to obtain the global miRNA transcriptome in paired specimens collected before, during and after pregnancy. To identify differentially expressed (DE) miRNAs that distinguish pregnancy from pre-conception or breastfeeding we used mixed effect model accounting for multiple samples from the pregnancy event and controlling for fixed effects of batch, country, Nugent score category and sexually transmitted infections. To identify hormonally regulated miRNAs independently associated with Box-Cox-transformed levels of progesterone (P4), {beta}-estradiol (E2), and sex-hormone binding protein (SHBG) we controlled in addition for age, pregnancy and breastfeeding P-values were corrected using the Benjamini-Hochberg false discovery rate (FDR). DMET-targeting miRNAs were identified using miRTarBase focusing on interactions verified by 3-UTR luciferase reporter assay and overlapped with DE miRNAs with FDR < 0.05. ResultsOf 140 DMET-targeting miRNAs among the 2079 miRNAs in the global peripheral blood transcriptome, 41 unique DMET-targeting miRNAs were found to be DE during pregnancy - 38 differentiating pregnancy from preconception and 9 differentiating pregnancy from breastfeeding. The 56 DMETs confirmed as targets of the DE miRNAs included 8 members of the ABC (ATP-binding cassette) transporter family, all abundantly expressed in the placenta, and 4 members of the cytochrome P450 Phase 1 enzyme family with major role in xenobiotics detoxification. The study also revealed a strong (FDR<0.05), predominantly positive association between specific DMET-targeting miRNAs and sex hormone-binding globulin (SHBG) levels, suggesting a miRNA-mediated downregulation of DMETs as SHBG levels rise during pregnancy. ConclusionThis research provides crucial insights into the molecular mechanisms underlying altered drug disposition in pregnant and lactating women, paving the way for improved therapeutic management and personalized medicine in these populations.

molecular biology↗

bioRxiv2025

Abnormal Vaginal Microbiota Associated with miRNA Targeting the HIV-Host Interactome

Understanding the molecular mechanisms underlying the ability of vaginal dysbiosis to alter the mucosal barrier to HIV acquisition is an essential step toward prevention. We hypothesized that micro(mi)-RNAs dysregulated by vaginal pathobiont bacteria epigenetically control host pathways exploited by the virus. The impact of these endogenous non-coding short RNAs on the anti-viral mucosal barrier function in the female reproductive tract is largely unknown. This study utilized cervicovaginal specimens collected during the luteal and follicular phase of the menstrual cycle along with data on age, race, ethnicity, education, and body mass index from 141 healthy reproductive-age women confirmed negative for sexually transmitted infections. Vaginal microbiota was classified by Nugent scoring. Shot-gun vaginal microbiome sequencing and metagenome taxonomic classification was performed on a subset of 21 women. Levels of miRNAs in exosomes isolated from cervicovaginal secretions were quantified using the EdgeSeq-NextGen global transcriptome platform. Differential expression (DE) was determined using R. Epigenetic target prediction was performed using MirTarBase. MiRNA profiles varied by both Nugent score categories (0-3 scores = normal, 4-6 = intermediate, and 7-10 = bacterial vaginosis, BV) and by metagenome classification. Higher microbiome diversity was associated with higher number of significantly dysregulated miRNAs (588 in BV compared to Nugent 0-3 versus 42 in Nugent 4-6 compared to Nugent 0-3, false discovery rate FDR<0.01) affecting over 400 experimentally validated genes targeted for post-transcriptional regulation. The miRNAs dysregulated by G. vaginalis-dominated compared to L. crispatus-dominated metagenomes included 24 DE miRNAs (92% overlap with BV by Nugent score) and 112 validated target genes. BV-dysregulated miRNA mediated the immunosuppressive effects of BV on cytokine levels previously associated with HIV acquisition risk. The gene ontology predictions based on BV-dysregulated miRNAs identified enrichment for 445 downregulated and 50 upregulated genes previously validated as part of the HIV-host interactome. miRNAs mediation revealed a mechanism of suppressed immunity by BV predictive of HIV risk. In conclusion, miRNAs dysregulated by vaginal dysbiosis may facilitate immune imbalance and cellular pathways associated with HIV risk.

molecular biology↗

bioRxiv2025

Rapid Identification of Metal Resistance Genes Using an Enhanced ResNet Deep Learning Model Trained on a largely Expanded BacMet-Based Database

Heavy metal pollution poses significant risks to both the environment and public health. Effective management requires not only reducing contaminants but also understanding microbial adaptation, which could be achieved through the comprehensive identification and classification of metal resistance genes. This study expanded the existing BacMet database by incorporating 1,219,137 unique amino acid sequences through BLASTp analysis, thereby increasing the number of metal resistance-related acid sequences by more than 1,600-fold compared to the 753 sequences included in the previous version. We employed various deep learning models for our proposed multi-label framework which could effectively overcome the well-recognized challenging issue of strict classification among metal translocating proteins such as CopA, ZntA, SilA, CadA, and CzcA due to their high sequence similarity and overlapping metal specificities, including AlexNet, VGG, GoogleNet, ResNet, BERT, ViT, and Mamba2, with ResNet demonstrating superior performance in terms of accuracy, robustness, and computational efficiency. The ResNet model achieved a Jaccard score of 98.91%, significantly higher than BLASTp (98.19%) and DIAMOND (98.16%), and was approximately 6,500 times faster in inference speed than these traditional alignment-based methods. Furthermore, the predictive performance of the model and the reliability of the expanded gene library were experimentally validated through overexpression and metal resistance assays of selected genes. Additionally, we developed the Predicting Metal Resistance Amino Acid Sequences (PMRAAS, https://s3.v100.vip:16165) website, facilitating online predictions of gene metal resistance. Our findings provided deeper insights into microbial adaptation mechanisms in metal-polluted environments and offered a robust tool for advancing heavy metal pollution management through enhanced bioremediation strategies.

genomics↗

bioRxiv2025

Effects of matric versus osmotic potential changes on Variovorax beijingensis transcription

Soil microbes must continuously adapt to changes in water availability, which dynamically fluctuates with weather and irrigation, and these adaptations are closely linked to soil CO2 emissions. Soil water potential, which regulates microbe-available water, is controlled by both osmotic and matric potential, which both increase as soils dry. While both parameters can independently increase water potential, the genetic mechanisms underlying microbial responses to both are unknown, with potentially different mechanisms available for soil microbes to respond to these hydrologic parameters. To explore microbial responses to matric versus osmotic potential shifts, we evaluated the growth and transcription of Variovorax beijingensis in soils and liquid cultures of varying water potential. We find this microbe respires in dilute minimal medium (-240 {+/-}104 kPa), in liquid medium supplemented with sucrose (-1323 {+/-}20.8 kPa), and in a pair of matrices that span a similar range of pressures (-183 {+/-}55 and -1393 kPa {+/-}200 kPa). We show that the global gene expression patterns vary significantly across all four conditions, even when the matric potential and osmotic pressure are set to similar values. However, the direction of gene expression changes correlated for 68% of the transcripts arising from an increase in osmotic pressure within liquid medium and an increase in matric potential within the different soils. While a large overlap was observed in the Variovorax transcriptional response to shifts in both osmotic and matric potential, the responses were not identical, with matric potential shifts leading to 2.55-fold more genes exhibiting differential expression. IMPORTANCEIt remains hard to establish how changes in soil water properties affect microbial behaviors that regulate soil health, and the energy with which soil water is held is likely a holistic control on at least some of those microbial behaviors. This energy is controlled by parameters associated with soil saltiness (osmotic potential) and texture (matric potential), which both alter bioavailable water by contributing to total soil water potential. To investigate how the global transcriptional profile of a soil microbe changes when the microbe-available water is altered either by changing soil texture or by changing osmolyte concentrations, we varied osmotic and matric potential individually and performed RNA sequencing. We observe differences in the transcriptome across all conditions analyzed. A larger number of genes are differentially expressed as matric potential increases; however, many of the transcripts differentially expressed as osmotic pressure increases covary with those observed as the matrix potential increases.

systems biology↗

bioRxiv2025

Super-giga and tiny orchid genomes illuminate evolution of Orchidaceae

Orchidaceae (orchids) is commonly known as one of the largest families of seed plants, and grow in an extensive range of habitats worldwide. In the present study, we generated chromosome-level reference genomes for two orchids using a combination of PacBio, Illumina, and Hi-C sequencing, Cypripedium singchii has the largest genome and chromosomes among the sequenced species so far, with a genome size of 43.19 Gb (1C) with ten chromosomes, and Apostasia fujianica has the smallest known genome and chromosomes in Orchidaceae, with a genome size of 340.90 Mb (1C) with 35 chromosomes. We predicted a total of 32,412 and 21,724 protein-coding genes for C. singchii and A. fujianica, respectively. The overall BUSCO score was 85.01% for C. singchii and 91.80% in A. fujianica. Based on protein-coding sequences from 55 conserved single-copy families across 21 plant species, we constructed a high-confidence phylogenetic tree and estimated the divergence times. The high-quality genomes of super-giga and tiny orchids offer key insight for future evolutionary researches.

genomics↗

bioRxiv2025

A comparison shopper's guide to forest datasets

Recent advances in remote sensing, data availability, and cloud-based computing have led to a rapid expansion of publicly accessible datasets characterizing forest cover and land use. These datasets are widely used in ecological research, natural resource management, and policymaking. However, the sheer number of available products--and the often-subtle differences among them--pose significant challenges for users seeking the most appropriate dataset for their specific objectives. Here, we evaluate 27 derived products from 12 publicly available sources that quantify tree or forest cover and use across the conterminous United States (CONUS), with temporal coverage ranging from 5 to 30 years. The products include both satellite-based remote sensing data and ground-based national forest inventory data. We ask: How, why, and where do these datasets differ in their estimates of forest extent and change over time? Our analysis reveals that estimates of total forest area at the CONUS scale differ by over 2,000,000 km{superscript 2}, and correlations among forest change estimates vary widely in both direction and statistical significance. To support dataset selection and interpretation, we developed an open-access map comparison tool using Google Earth Engine. Our findings highlight the substantial implications of dataset choice for understanding forest dynamics and underscore the need for careful selection and transparent reporting in forest-related analyses.

ecology↗

bioRxiv2025

Structural and temporal dynamics analysis on PANoptosis in sepsis: a bibliometric analysis

PANoptosis, as a new type of programmed cell death, is characterized by pyroptosis, apoptosis and necroptosis, and is a key mechanism causing a variety of inflammatory diseases. Despite the growing number of studies indicating the crucial role of PANoptosis in sepsis, there has been no bibliometric analysis of the research hotspots and trends in this field. Therefore, this study aims to explore the history, research hotspots and emerging trends of PANoptosis in sepsis related research in the past 20 years from the perspective of structure and temporal dynamics. The articles related to PANoptosis in sepsis were retrieved from the Web of Science Core Collection (WoSCC) database from 2000 to 2024. CiteSpace and HistCite were used to analyse the historical features, the evolution of active topics, and emerging trends about PANoptosis in sepsis. 6165 original articles and reviews on PANoptosis in sepsis were included in the bibliometric analysis. In the last 20 years, the number of published documents is increasing year by year and reaches a peak in 2022. At the same time, many activation themes have emerged at different times, as evidenced by a total of 96 categories, 865 keywords and 629 reference bursts. Keyword clustering anchored eight emerging research subfields, namely 0# oxidative stress, 1#pyroptosis, 2#sepsis-associated encephalopathy, 3#acute kidney injury, 4#immunosuppression, 5#necroptosis, 7#lung injury and 8#extracellular vesicles. The keyword alluvial map shows that the most persistent research concepts in this field are phosphatase. And the emerging keywords are toll_like_receptors, regulatory T cells, recognition, etc. In a timeline visualization based on the time span of the citations, we find five relevant emerging topics, namely 1# immunosuppression, 2# sepsis-induced cardiomyopathy, 3# pyroptosis, 4# acute kidney injury, and 13# COVID-19. Our study provides a comprehensive bibliometric analysis and summary about the current status and trends on PANoptosis in sepsis, which will aid researchers in conducting further scientific research in this field.

bioinformatics↗

bioRxiv2025

Genome-wide CRISPR/Cas9 knockout screen identifies host factors essential for Bovine Parainfluenza Virus Type 3 replication

Bovine Parainfluenza Virus Type 3 (BPIV3) is a leading cause of respiratory illness in cattle and a primary component of Bovine Respiratory Disease Complex (BRDC), resulting in significant economic losses. Understanding the mechanisms of BPIV3 infection, particularly the entry process, is essential for developing effective control measures. Identifying specific host factors that viruses exploit during their life cycle can reveal critical vulnerabilities for potential antiviral targets. We established a genome-wide CRISPR/Cas9 knockout screen in bovine cells to identify host factors involved in viral infections. Our screen identified several key host factors required for BPIV3 infection, including the sialic acid transporter SLC35A1 and the protein LSM12. Further mechanistic analysis revealed that these factors play critical roles at distinct stages of the BPIV3 entry process. These findings not only advance our understanding of how BPIV3 infects host cells, but also identify potential host targets for inhibiting infection and developing novel antiviral strategies.

microbiology↗

bioRxiv2025

Neural hierarchy for coding articulatory dynamics in speech imagery and production

Mental imagery is a hallmark of human cognition, yet the neural mechanisms underlying these internal states remain poorly understood. Speech imagery--the internal simulation of speech without overt articulation--has been proposed to partially share neural substrates with actual speech articulation. However, the precise feature encoding and spatiotemporal dynamics of this neural architecture remain controversial, constraining the understanding of mental states and the development of reliable speech imagery decoders. Here, we leveraged high-resolution electrocorticography recordings to investigate the shared and modality-specific cortical coding of articulatory kinematic trajectories (AKTs) during speech imagery and articulation. Applying a linear model, we identified robust neural dynamics in frontoparietal cortex that encoded AKTs across both modalities. Shared neural populations across the middle premotor cortex, subcentral gyrus, and postcentral-supramarginal junction exhibited consistent spatiotemporal stability during the integrative articulatory planning. In contrast, modality-specific populations for speech imagery and articulation were somatotopically interleaved along the primary sensorimotor cortex, revealing a hierarchical spatiotemporal organization distinct from shared encoding regions. We further developed a generalized neural network to decode multi-population neural dynamics. The model achieved high syllable prediction accuracy for speech imagery (79% median accuracy), closely matching the performance of speech articulation (81%). This model robustly extrapolated AKT decoding to untrained syllables within each modality while demonstrating cross-modal generalization across shared populations. These findings uncover a somato-cognitive hierarchy linking high-level supramodal planning with modality-specific neural manifestation, revolutionizing an imagery-based brain-computer interface that directly decodes thoughts for synthetic telepathy.

neuroscience↗

bioRxiv2025

The potential of 4-Methylumbelliferone to be repurposed for treating liver fibrosis

4-Methylumbelliferone (4-MU) is the active component of hymecromone, a choleretic and antispasmodic drug with an excellent safety profile. In rodent studies, high doses of 4-MU are also used to inhibit the production of hyaluronan (HA), a biomarker of liver fibrosis. Further, 4-MU shows excellent efficacy in inhibiting liver fibrosis of different etiologies in animal studies, eliciting interest in its repurposing for this condition. However, 4-MUs mechanism of action, and whether it inhibits liver fibrosis by impeding HA synthesis, remains unclear. Using several transgenic mouse models with HA overproduction or degradation in different types of liver cells, we found that both directions of perturbation reduced liver fibrosis levels. In addition, degrading HA via hyaluronidase PH20 overexpression impaired liver function manifested by increased serum aminotransferase (ALT) activity levels. These findings challenge both the role of HA modulation in 4-MUs action and the strategy of targeting HA to treat liver fibrosis. Additional mouse models also excluded the possibility that 4-MU modulates intestinal farnesoid X receptor (FXR) to inhibit liver fibrosis. Ablation of gut microbiota partially abolishes 4-MUs anti-liver fibrosis effect. However, the anti-liver fibrosis effect of 4-MU was lost in the lower-dose group, and the high doses effect in reducing ALT disappeared over time despite its liver fibrosis-reducing effect. Based on these findings, we argue that the lack of efficacy of 4-MU at a translatable dose and lack of a clear mechanism that allows further improvement of 4-MUs efficacy make 4-MU impractical for development as an anti-liver fibrosis treatment. HighlightsO_LI4-MU inhibits MASH fibrosis. C_LIO_LIBoth HA overproduction and digestion in the liver reduce liver fibrosis. C_LIO_LIIntestinal epithelial cell FXR is not required for 4-MU to reduce liver fibrosis. C_LIO_LIThe gut microbiota is partially responsible for 4-MUs antifibrotic effect in the liver. C_LIO_LI4-MU lacks the potential to be further developed into anti-liver fibrosis treatment. C_LI

molecular biology↗

bioRxiv2025

Coronary Artery Disease Risk Variant rs6903956 Links to Endothelial Dysfunction via PHACTR1 Regulation

Ischemic heart disease, particularly coronary artery disease (CAD), remain leading causes of mortality worldwide. The single nucleotide polymorphism rs6903956 on chromosome 6p24.1 has been identified as a susceptibility locus for CAD in East Asian populations through genome-wide association studies. However, its functional role has not been fully elucidated. This study investigates the mechanistic basis of rs6903956 and its contribution to CAD pathogenesis, focusing on endothelial cell dysfunction. We first conducted cohort studies, revealing an association between the rs6903956 A risk allele and blood pressure phenotypes, along with impaired endothelial responsiveness indicated by reduced flow-mediated dilation. Single-base editing of induced pluripotent stem cell-derived endothelial cells obtained from patients with CAD and expression quantitative trait loci analysis highlighted a cisacting impact of the A allele on PHACTR1 and EDN1 expression, suggesting allelespecific regulatory effects. Using in silico modeling by AlphaFold 3 platform, the A allele exhibited enhanced binding affinity for HOXA4 and MEIS1 transcription factors, forming a stable ternary complex that promoted transcriptional activation of PHACTR1. Functional assays demonstrated the enhancer role of rs6903956 A in PHACTR1 promoter activity, supporting its locus-specific regulatory function in endothelial cells. Under pathological flow conditions, endothelial cells harboring the A allele display elevated ICAM-1 expression and increased monocyte adhesion compared to the G allele, indicating allele-specific endothelial inflammatory activation. These findings propose a model in which rs6903956 influences PHACTR1 expression via HOX-MEIS cooperative binding, thereby modulating endothelial function and contributing to CAD susceptibility. This study provides mechanistic insights into the role of rs6903956 in endothelial dysfunction and CAD, informing potential therapeutic targets arising from genetic determinants in cardiovascular pathogenesis.

molecular biology↗