Biology subjects

Wu, W.-C.

Publications and source records attributed to Wu, W.-C..

7 recordsLinked to original sources

bioRxiv2026

A Single-cell Spatiotemporal Atlas Encoding Age-dependent Evolution of the Ischemic Penumbra

Aging is the predominant risk factor for stroke and a major driver of poor neurological recovery. Although the ischemic penumbra represents a key therapeutic target, its age-dependent molecular landscape remains poorly understood. Here, we generated a spatiotemporal transcriptomic atlas of the post-stroke penumbra in young (3-4 months) and aged (19-20 months) mice at acute (day 3) and chronic (day 14) stages following transient focal cerebral ischemia. Integrating spatial transcriptomics with dissociated single-cell RNA sequencing revealed a persistent transcriptomic penumbra (TP) that remains detectable for at least 14 days after stroke in both age groups, far beyond the window suggested by conventional imaging modalities. Aging profoundly altered TP organization, resulting in dysregulated energy metabolism, impaired neurovascular repair, diminished pro-reparative cell-cell communication, and extensive remodeling of transcriptional regulatory networks. Using this atlas, we further identified regulatory hub genes whose predicted perturbation could simultaneously counteract multiple age-associated pathological pathways. These data define the molecular architecture of the aging post-stroke penumbra and provide a publicly accessible framework for mechanistic discovery and therapeutic target prioritization aimed at improving recovery after stroke.

neuroscience↗

bioRxiv2026

Multi-kingdom microbial diversity and interaction landscapes in mosquitoes revealed by 5,163 individual meta-transcriptomes

Mosquitoes are pathogen vectors embedded within diverse microbial ecosystems. However, the nature and interactions among their multi-kingdom microbiome remain poorly understood. We conducted a nationwide single-mosquito meta-transcriptomic survey of 5,163 mosquitoes representing 100 species across China, integrating viral discovery with marker-gene profiling of bacteria, archaea, fungi, and other eukaryotic microbes. From this, we identified 1,606 microbial species-level taxa, including extensive novel diversity, and revealed pronounced host species-specific organization of mosquito-associated communities. We detected 34 pathogens or potential pathogens of human or animal relevance, whose prevalence, abundance, host range, and geographic distribution defined distinct epidemiological patterns. Network analysis uncovered pervasive cross-kingdom microbial associations, including candidate antiviral relationships involving Wolbachia and other microbial taxa. Our study establishes a detailed view of the full-spectrum microbiome and provides a resource and conceptual framework for studying vector competence, pathogen emergence, and microbiome-informed mosquito-borne disease control.

microbiology↗

bioRxiv2025

Comprehensive Infectome Analysis Reveals Diverse Infectious Agents with Zoonotic Potential in Wildlife

Understanding wildlife-pathogen interactions is crucial for mitigating zoonotic risk. Through meta-transcriptomic sequencing we profiled the infectomes of 1,922 samples from 67 mammalian species across China, uncovering a remarkable diversity of viral, bacterial, fungal, and parasitic pathogens. Of the 195 pathogens identified, 62 were novel, including a bi- segmented coronavirus in diseased lesser pandas, which we propose represents a new genus - Zetacoronavirus. The orders Carnivora and Rodentia exhibited the highest pathogen diversity and were implicated in numerous host-jumping events. Comparative analysis of diseased versus healthy animals revealed a trend of higher pathogen loads in the former, with possible differences in tissue tropisms. In total, 48 zoonotic and 17 epizootic pathogens were identified, with frequent cross-species transmission, emphasizing the potential for emerging public health threats. This study highlights the urgent need for wildlife pathogen surveillance to inform proactive disease management strategies.

microbiology↗

bioRxiv2024

Scn2a deletion disrupts oligodendroglia function: Implication for myelination, neural circuitry, and auditory hypersensitivity in ASD

Autism spectrum disorder (ASD) is characterized by a complex etiology, with genetic determinants significantly influencing its manifestation. Among these, the Scn2a gene emerges as a pivotal player, crucially involved in both glial and neuronal functionality. This study elucidates the underexplored roles of Scn2a in oligodendrocytes, and its subsequent impact on myelination and auditory neural processes. The results reveal a nuanced interplay between oligodendrocytes and axons, where Scn2a deletion causes alterations in the intricate process of myelination. This disruption, in turn, instigates changes in axonal properties and neuronal activities at the single cell level. Furthermore, oligodendrocyte-specific Scn2a deletion compromises the integrity of neural circuitry within auditory pathways, leading to auditory hypersensitivity--a common sensory abnormality observed in ASD. Through transcriptional profiling, we identified alterations in the expression of myelin-associated genes, highlighting the cellular consequences engendered by Scn2a deletion. In summary, the findings provide unprecedented insights into the pathway from Scn2a deletion in oligodendrocytes to sensory abnormalities in ASD, underscoring the integral role of Scn2a-mediated myelination in auditory responses. This research thereby provides novel insights into the intricate tapestry of genetic and cellular interactions inherent in ASD.

neuroscience↗

bioRxiv2024

Meta-transcriptomic analysis of companion animal infectomes reveals their diversity and potential roles in animal and human disease

Companion animals such as cats and dogs harbor diverse microbial communities that can potentially impact human health due to close and frequent contact. To better characterize their total infectomes and assess zoonotic risks, we performed meta-transcriptomic profiling on 239 samples from cats and dogs collected across China, comparing the similarities and differences between animal species (cats or dogs), sampling sites (rectal or oropharyngeal), and health status (healthy or diseased). We identified 24 viral species, 270 bacterial genera, and two fungal genera, including many known pathogens such as canine parvovirus, Clostridium difficile, and Candida albicans, as well as opportunistic pathogens such as canine vesivirus. Microbial compositions differed mainly according to sampling site (i.e., rectal and oropharyngeal swabs), and less so between host species and health status. Notably, we detected 27 potential zoonotic pathogens, such as alphacoronavirus 1, among all sampling sites, hosts, and health status, underscoring substantial zoonotic risks requiring surveillance. Overall, our meta-transcriptomic analysis reveals a landscape of actively transcribing microorganisms in major companion animals, including key pathogens, those with the potential for cross-species transmission, and possible zoonotic threats.

microbiology↗

bioRxiv2023

Artificial intelligence redefines RNA virus discovery

Current metagenomic tools can fail to identify highly divergent RNA viruses. We developed a deep learning algorithm, termed LucaProt, to discover highly divergent RNA-dependent RNA polymerase (RdRP) sequences in 10,487 metatranscriptomes generated from diverse global ecosystems. LucaProt integrates both sequence and predicted structural information, enabling the accurate detection of RdRP sequences. Using this approach we identified 161,979 potential RNA virus species and 180 RNA virus supergroups, including many previously poorly studied groups, as well as RNA virus genomes of exceptional length (up to 47,250 nucleotides) and genomic complexity. A subset of these novel RNA viruses were confirmed by RT-PCR and RNA/DNA sequencing. Newly discovered RNA viruses were present in diverse environments, including air, hot springs and hydrothermal vents, and both virus diversity and abundance varied substantially among ecosystems. This study advances virus discovery, highlights the scale of the virosphere, and provides computational tools to better document the global RNA virome. In briefA deep learning algorithm (LucaProt) that integrates both sequence and predicted structural information was employed to identify highly divergent RNA viral "dark matter" in 10,487 metatranscriptomes from diverse global ecosystems. A total of 161,979 potential RNA virus species and 180 RNA virus supergroups was unveiled using this AI approach, including many understudied groups.

microbiology↗

bioRxiv2019

Biological Pathways and Gene Networks Link Inflammation and Vascular Remodeling to Both Heart Failure with Preserved and Reduced Ejection Fraction in Women across Ethnicities

IntroductionHeart failure (HF) is understudied among women; especially, genomic evidence implicating shared or unique mechanisms of HF with respect to reduced or preserved ejection fraction (HFrEF, HFpEF) is lacking across ethnic populations of women. Prior genome-wide association studies (GWAS) have identified approximately 30 suggestive genetic variants for HF, although none have been specifically linked to HFrEF or HFpEF.\n\nObjectivesWe aimed to define, replicate, and annotate genetic variants to HFrEF, HFpEF, or both, as well as to investigate potential biological mechanisms underlying HFrEF and HFpEF among African American (AA) and European American (EA) women in three well-characterized, high-quality prospective cohorts, the Womens Health Initiative (WHI) study, the Jackson Heart Study (JHS), and the Framingham Heart Study (FHS).\n\nMethodsGWAS analysis on HFrEF and HFpEF were first performed among 7,982 AA and 4,133 EA in the WHI, followed by pathway analysis employing two independent methodological platforms (GSA-SNP and Mergeomics) curating KEGG, Reactome, and BioCarta pathway databases. GWAS signals and biological pathways identified using the WHI were replicated in the JHS and FHS. For all replicated pathways, we performed cross-phenotype and cross-ethnicity validation analyses to examine shared pathways between HFrEF and HFpEF, and phenotype-specific pathways, across ethnicities. We further prioritized key driver genes for HF according to specific pathways identified.\n\nResultsWe validated one previously reported genetic locus and identified six new ones, among which one locus was allocated to HFrEF and five to HFpEF. Additionally, we defined five biological pathways shared between HFrEF and HFpEF and discovered six HFpEF-specific pathways. These pathways overlapped in two main domains for molecular signaling: 1) inflammation and 2) vascular remodeling (including angiogenesis and vascular patterning), involving key driver genes from collagen and HLA gene families.\n\nConclusionsOur network analysis of three large prospective cohorts of women in the United States defined several novel loci for HF and its subtypes. In particular, several key driver genes reinforce the mechanistic role of inflammation and vascular remodeling in the development of HF, especially HFpEF. Given that therapeutic strategies developed for left ventricular dysfunction have had limited success for HFpEF, several new targets and pathways identified and validated in this study should be further assessed in risk stratification as well as the design of potential new HF interventions.

genetics↗