Biology subjects

Li, W.

Publications and source records attributed to Li, W..

At least 235 records · Page 13Linked to original sources

bioRxiv2025

Phosphatidylcholine Metabolism Controls Alveolar Progenitor Renewal and Pulmonary Fibrosis

Idiopathic pulmonary fibrosis (IPF) is a progressive, fatal lung disease marked by alveolar type 2 (AT2) stem cell dysfunction and excessive matrix deposition, with no effective treatments. Recent advances have recognized that AT2 cells act as stem cells, in addition to their role in the production of pulmonary surfactants in the distal alveolar space. We and others have reported a failure of AT2 regeneration and a loss of AT2 cells in IPF. We recently further reported that there is a defect in lipid metabolism in IPF AT2 cells and we discovered a selective loss of lysophosphatidylcholine acyltransferase 1 (LPCAT1) in AT2 cells from IPF, as well as in AT2 cells from bleomycin-injured mice. Pharmacological and genetic experiments confirm that LPCAT1 is required for AT2 cell renewal in 3D organoid assays. AT2 cell-specific Lpcat1 deletion resulted in reduced AT2 renewal, spontaneous lung fibrosis, and heightened susceptibility to bleomycin-induced fibrosis in mice in vivo. Expression-based high-content drug screening with an LPCAT1 knock-in cell line identified several drug families that upregulated LPCAT1 expression. We further confirmed that anti-malarial artesunate and PLA2 inhibitor ONO-RS-082 increased LPCAT1 mRNA expression, promoted AT2 renewal, and attenuated bleomycin-induced lung fibrosis in mice in vivo. Our findings establish LPCAT1 as a critical regulator of AT2 renewal and lipid metabolism in IPF, suggesting that reactivation of LPCAT1 could offer a novel therapeutic strategy for restoring alveolar progenitor function and mitigating lung fibrosis.

cell biology↗

bioRxiv2025

scPhoenix: A Contrastive Learning-based Framework with Aux-Core Feature Disentanglement Enhances Sparse Cellular Multi-omics Translation

Recent advances in single-cell multi-omics co-assays and spatiotemporal sequencing technologies have provided unprecedented opportunities for systematically characterizing cellular heterogeneity. However, severe sparsity and pronounced spatial heterogeneity--hallmark features of complex diseases and tumor microenvironment--remain major obstacles in deciphering cellular multi-omics data. Here, we present scPhoenix, a contrastive learning-based framework for single-cell cross-modality translation. scPhoenix adopts a two-stage Aux-Core strategy to disentangle modality-specific feature extraction from cross-modality feature interaction. Across diverse datasets, it preserves cellular heterogeneity during translation and demonstrates significant advantages for data with high sparsity. In addition, the framework integrates a contrastive learning framework with five effective data augmentation methods tailored to single-cell data. Moreover, scPhoenixs design supports extensions to unpaired data training and spatial multi-omics translation, enabling robust performance in scenarios with high spatial heterogeneity. scPhoenix is freely available at https://github.com/liwz-lab/scPhoenix.

bioinformatics↗

bioRxiv2025

Negative feedback regulation of the hemi-arrestin MAPK scaffold Sms1 prevents untimely mating

Mitogen-activated protein kinases (MAPK) are ancestral kinases that form essential signalling cascades. However, scaffolds that recruit kinases to subcellular locations and promote signal transduction have only been described in few species. Notably, no scaffold was thought necessary for the MAPK cascade promoting sexual differentiation in fission yeast. Here, we identify the hemi-arrestin protein Sms1 as a structurally novel scaffold of this MAPK cascade. Interactions with PIP2 and the pheromone receptor-coupled G subunit target Sms1 to plasma membrane patches, where it assembles the active cascade by binding each MAP kinase. These interactions are essential for signal transduction and local signal interpretation for polarised growth. Phosphorylation, including by the MAPK itself, antagonises Sms1 membrane translocation, establishing a negative feedback that underlies polarity patch turnover and prevents untimely mating attempts. Thus, Sms1 is a MAPK scaffold with canonical functions despite its distinct structural fold, highlighting convergent evolution of MAPK scaffolds across eukaryotes.

cell biology↗

bioRxiv2025

YeastSAM: A Deep Learning Model for Accurate Segmentation of Budding Yeast Cells

An essential step for quantitative image analysis is cell segmentation, which is the process of defining the outline of individual cells in microscopy images. Segmentation of budding yeast is challenging due to their asymmetric cell division and mother-bud morphology. As a result, a dividing cell is frequently misidentified as two separate cells, causing errors in downstream analysis. Here, we overcame this challenge by developing YeastSAM, a deep learning-based segmentation framework derived from {micro}SAM and optimized for budding yeast. YeastSAM achieves more than threefold higher accuracy in segmenting dividing cells compared to existing methods. When combined with single-molecule RNA imaging and organelle imaging, YeastSAM facilitates quantitative analysis of the spatial regulation of gene expression. This study offers an accessible, high-accuracy model for yeast cell segmentation, empowering researchers with minimal programming experience to perform quantitative image analysis.

cell biology↗

bioRxiv2025

Weak SLP-76-PLC-γ1 interaction in the LAT-nucleated multi-protein complex fine-tunes TCR signal strength to optimize T cell responsiveness

Upon TCR engagement several protein tyrosine kinases are recruited and activated, and adapter proteins and enzymes are phosphorylated on tyrosine residues, leading to further events characterizing activated T cells. Phosphorylation of the LAT adapter protein enables binding of the enzyme PLC-{gamma}1 and of a dimer of two additional adapter proteins Gads and SLP-76, forming a tetrameric structure. Within this heterotetramer there is a weak interaction between SLP-76 and PLC-{gamma}1, and the relevant binding sites of SLP-76 and PLC-{gamma}1 are highly conserved in vertebrates. To address the biological relevance of this weak interaction, we introduced a mutation in the SLP-76 that enhanced its affinity for PLC-{gamma}1 and found that this mutation increased PLC-{gamma}1 activity and altered thymocyte development and peripheral T cell responses due to enhanced TCR signal strength. The conserved weak SLP-76-PLC-{gamma}1 interaction is critical for the controlled activation of PLC-{gamma}1, thus fine-tuning TCR signal strength to optimize T cell-mediated immunity.

immunology↗

bioRxiv2025

SpatialFuser: A Unified Deep Learning Framework for Spatial Multi-Omics Data Integrative Analysis

Recent advances in spatial multi-omics technologies provide unprecedented opportunities to interpret molecular features in tissue microenvironments, but integrative analysis across heterogeneous datasets remains challenging. Here we present SpatialFuser, a deep learning framework for integrative analysis of unpaired spatial multi-omics data across epigenomics, transcriptomics, proteomics, and metabolomics. SpatialFuser consists of three coordinated modules: MCGATE, a Multi-head Collaborative Graph Attention auToEncoder that learns multi-scale spatial representations to decipher fine-grained spatial heterogeneity beyond predefined spatial neighbourhoods; an optional geometric pre-matching module that provides coarse initialization under tissue geometry mismatch; and an iterative matching-fusion module that couples geometry-constrained optimal transport matching with contrastive-learning-guided modality fusion for cross-slice alignment and integration. Systematic benchmarks demonstrate superior performance and reliability compared with existing state-of-the-art methods in spatial domain identification, cross-slice alignment, and multi-omics integration. Applications to real datasets illustrate that SpatialFuser resolves precise spatial molecular patterns, reveals developmental dynamics, and recovers complementary signals across modalities. Cross-resolution integration of weakly correlated modalities by our method further uncovers previously obscured biological variation. The generalizability and versatility of our framework enable customized analytical scenarios and potential extension for emerging omics. HighlightsO_LIA unified deep learning framework for spatial multi-omics integrative data analysis C_LIO_LISuperior performance against state-of-the-art methods in spatial identification, alignment, and multi-omics integration C_LIO_LIUnprecedented cross-modality analysis scenarios to offer a holistic view of spatial multi-omics C_LIO_LIComprehensive framework design with generalizability and versatility for customized scenarios and potential extension C_LI

bioinformatics↗

bioRxiv2025

Body temperature drives azole tolerance in Candida albicans by hindering the autophagic degradation of Erg11

Human body temperature has been shown to limit the antifungal efficacy of azoles; however, the precise mechanisms underlying this limitation remain insufficiently understood. In this study, we observed that short-term exposure (24 h) to human body temperature (37{square}{degrees}C), in contrast to 30{square}{degrees}C, significantly enhances the tolerance of Candida albicans to azoles without inducing resistance. Our findings suggest that this increased tolerance is due to a reduction in the degradation of C. albicans Erg11 at 37{square}{degrees}C compared to 30{square}{degrees}C, thereby promoting azole tolerance. This phenomenon occurs because Erg11 degradation is mediated by autophagy, which is inhibited in C. albicans at 37{square}{degrees}C. The suppression of autophagy at this temperature may be associated with elevated mitochondrial production of reactive oxygen species, leading to mitochondrial dysfunction. In response to heat stress-induced mitochondrial dysfunction, autophagy-related proteins such as Atg8 accumulate around the mitochondria, while their levels in the endoplasmic reticulum decrease, consequently inhibiting autophagy in C. albicans. These findings suggest that promoting the degradation of Erg11 in C. albicans may serve as a viable strategy to augment the fungicidal efficacy of azoles in the human host.

microbiology↗

bioRxiv2025

Transfer RNA modifications during rhizome development in Oryza longistaminata

The rhizome organ endows many clonal plants with the ability to reproduce under stressful climates. Such rhizome-mediated perenniality also underlies the recent success of perennial rice breeding. Despite the importance of this organ, its developmental regulation is poorly understood. Here, using Oryza longistaminata, an emerging model for rhizome biology, we explored the involvement of tRNA modification in rhizome development. Through comparative profiling of modified nucleotides in rhizome samples at different developmental stages and/or subjected to various treatments, we identified a number of key rhizome-related tRNA modifications and revealed that, akin to the observations in many non-plant organisms, tRNA modifications are associated with hormonal signalling to regulate rhizomes responses to environmental cues. Furthermore, genome-wide analysis of tRNA-modifying genes was performed to facilitate future functional studies. These results and analyses not only deepen our understanding of rhizome development but also underscore the regulatory roles of tRNA modification in plant organ development.

plant biology↗

bioRxiv2025

DNA Data Storage Architecture via Ligation of Dynamic DNA Bytes

The explosive growth of digital data is overwhelming conventional storage media, creating an urgent need for more efficient solutions. DNA offers immense potential for digital data storage, yet most systems remain static and archival. Here, we present a modular DNA storage architecture based on dynamic DNA bytes (DynaBytes)-- pre-fabricated DNA segments that can be ligated into reconfigurable information units. Utilizing core, functional and control DynaBytes, we stored 210,776 bits (26,347 bytes) of digital information organized within a file-system, and demonstrated CRUD (Create-Read-Update-Delete)-like operations, hierarchical access and nanopore-based realtime retrieval. Robust data recovery was achieved under [~]100x error-prone sequencing using streamlined error correction and fuzzy decoding. By relying on in vitro ligation of standardized components, DynaBytes reduces cost, scales efficiently, and allows interactive, rewritable storage. These features advance DNA storage beyond passive archiving toward a reconfigurable framework, opening new possibilities for dynamic, practical and large-scale DNA-based data systems.

synthetic biology↗

bioRxiv2025

Characterizing intra- and inter-tumor heterogeneity in ovarian high-grade serous carcinoma subtypes using single-cell and spatial transcriptomics

Ovarian high-grade serous carcinoma (HGSC) is an aggressive ovarian cancer with a heterogeneous tumor microenvironment (TME). Advances in single-cell RNA sequencing (scRNA-seq) and spatially-resolved transcriptomics have enabled the study of complex TME. This study explores connections between molecular subtypes described from bulk transcriptomes and spatial domains characterized by distinct gene expression in HGSC and their variability between patients. We explored both intraand inter-tumor heterogeneity across 2D space and identified differing spatial patterns of gene expression pertaining to immune pathways and vasculature development. Functional characterization of tumor spaces revealed potentially shared cell states across molecular subtypes, while correlation analysis underscored subtype-specific spatial anti-colocalization between spots exhibiting antigen-presenting functions and B cell-mediated immunity. Lastly, we performed spatially-aware cell-cell communication analysis on the spatial samples and identified a molecular subtype specific difference in total signaling activity and heterogeneity in Midikine signaling between the differentiated subtype. Our results suggest that generating multiple tissue slices per patient might be necessary to enable comprehensive characterization of HGSC spatial transcriptomes.

genomics↗

bioRxiv2025

A simplified and highly efficient cell-free protein synthesis system for prokaryotes

Cell-free protein synthesis (CFPS) systems are a powerful platform with immense potential in fundamental research, biotechnology, and synthetic biology. Conventional prokaryotic CFPS systems, particularly those derived from Escherichia coli (E. coli), often rely on complex reaction buffers containing up to thirty-five components, limiting their widespread adoption and systematic optimization. Here, we present an optimized E. coli cell-free protein synthesis (eCFPS) system, which is significantly streamlined for high efficiency. Through systematic screening, we successfully reduced the essential core reaction components from 35 to a core set of 7. The thorough optimization of these seven key components ensured that protein expression levels were not only maintained but even substantially improved. Furthermore, we developed a much simpler procedure for preparing the bacterial cytosolic extracts, a "fast lysate" protocol that eliminates the traditional time-consuming runoff and dialysis steps, thereby enhancing the overall accessibility and robustness of eCFPS. This optimized and user-friendly eCFPS efficiently synthesizes challenging proteins, including functional, self-assembling vimentin, and active restriction endonuclease BsaI despite its strong cytotoxicity, and serves as a powerful tool that will facilitate diverse applications in basic life science research and beyond.

biochemistry↗

bioRxiv2025

Non-synaptic Mechanism of Ocular Dominance Plasticity

Classic experiments showing that monocular visual disruption alters synaptic connections to binocular neurons established the fundamental concept of synaptic plasticity. Synaptic inputs that are activated coincidently with postsynaptic action potential firing are strengthened, and inputs from cells firing before or after the postsynaptic action potential are weakened. An implicit assumption, however, is that the speed of impulse transmission is not altered by visual deprivation. If so, spike time arrival at binocular neurons would be affected, thereby inducing synaptic plasticity. This possibility is tested here in adult mice by monocular eyelid suture and monocular action potential inhibition in retinal axons. The results show that spike time arrival in visual cortex is altered by monocular visual disruption in association with morphological changes in myelin (nodes of Ranvier) on axons in optic nerve and optic tract. This non-synaptic mechanism of ocular dominance plasticity, mediated by myelin-forming cells, supplements and may drive synaptic plasticity.

neuroscience↗

bioRxiv2025

Instruction-tuned extraction of virus-host interactions from integrated scientific evidence

MotivationViral infectious diseases continue to pose a major threat to global health. Understanding protein-protein interactions (PPIs) and RNA-protein interactions (RPIs) between viruses and hosts is essential for elucidating infection mechanisms. However, manual curation of these interactions from biomedical literature is inefficient, creating a pressing need for automated and scalable extraction methods. Large language models (LLMs), such as the generative pre-trained transformer (GPT) and bidirectional encoder representations from transformers (BERT), offer promising solutions. Yet, most existing datasets focus on abstracts, overlooking other information-rich sections. We aim to develop a data-efficient approach to extract virus-host interaction (VHI) entities from full-text biomedical articles, including Results, Methods and tables. To our knowledge, this is the first study to apply instruction tuning to full-text VHI extraction ResultsWe curated a dataset containing 3, 395 PPI and 674 RPI entities from the Results, Materials and Methods sections, along with 566 PPIs and 793 RPIs from tables. Under low-resource conditions (<500 training examples), our instruction-tuned ChatMed-VHI model achieves the best overall performance (F1: 89.7%, Precision: 95.3%), outperforming PubMedBERT (F1: 74.6%, Precision: 75.1%). When scaled to the full dataset (>4, 000 training examples), ChatMed-VHI maintained the highest overall performance, while PubMedBERT achieved slightly higher precision (92.3% vs. 91.3%). Notably, ChatMed-VHI improved F1 and recall by 2.79% but precision dropped by 4.20% with more training data, whereas PubMedBERT improved consistently across all metrics. These results demonstrate the effectiveness of instruction-tuned LLMs for full-text biomedical extraction tasks, and position ChatMed-VHI as a scalable, domain-adaptable solution for VHI mining.

bioinformatics↗

bioRxiv2025

Mating-Type Imputation (MTI) provides an efficient tool for the mating-type inference of tetrapolar fungi

Mating-type identification is fundamental for the genetic diversity and genetic breeding study in fungi, especially for tetrapolar basidiomycetes, whose mating-types are determined by two multiallelic loci A and B. Traditional mating-type identification of monokaryons relies on manual inference based on their hybridization experiments; however, the process is rather complex, time-consuming and error-prone for large-scale hybridization experiments. In this study, we developed the Mating-Type Imputation (MTI) software for automatic, rapid and accurate monokaryon mating-type inference for tetrapolar fungi using a combinatorial pruning traversal algorithm. Taking the compatibility matrix from 435 hybridization experiments of 30 Flammulina velutipes monokaryons as an example, MTI takes a few minutes to infer the accurate mating-types of all monokaryons, which might take several days for manual inference by experienced investigators. Furthermore, MTI enables us to investigate how false-positives and false-negatives influence mating-type inference results. Using simulated compatibility matrix, we found that MTI could accurately detect potential false-negatives in compatibility and successfully infer the true mating-type combination with limited false-negatives, but the tool could be misled by any false-positives to result in a wrong mating-type combination, indicating that false-positives records in hybridization experiments should be strictly obviated for mating-type inferences. In summary, MTI provides an efficient tool for mating-type inference of tetrapolar fungi, offering technical support for the research paradigm in mating-type studies of edible and medicinal fungi and holding significant theoretical value and broad application prospects in the fields of fungal genetic diversity and breeding studies.

genetics↗

bioRxiv2025

Vcam1 in endothelial and stromal cells regulates hematopoietic stem cell contact with the niche

Hematopoietic stem and progenitor cells (HSPCs) are essential for differentiation into all blood cell types. In mammals, the interaction between HSPCs and the fetal liver niche during development is critical for stem cell maturation. Integrin alpha 4 (Itga4) on HSPCs and vascular cell adhesion molecule (Vcam1) on niche cells are critical for HSPC colonization of the fetal liver (FL). Itga4 and Vcam1 also function in the zebrafish equivalent of the FL, the caudal hematopoietic tissue (CHT), however, the specific niche cells that express Vcam1 remain unclear. Using multiple approaches, including fluorescent in situ hybridization, we found Vcam1 is expressed in endothelial cells (ECs) and mesenchymal stromal cells (MSCs), but not macrophages. Time-lapse live imaging of itga4 mutants showed the Itga4-Vcam1 axis is required for HSPC retention in the CHT niche, but not homing or lodgment. Our results show that Itga4 on HSPCs and Vcam1 on ECs and MSCs are involved in retention in the CHT niche. SummaryBlood stem cell interaction with the niche microenvironment during development is critical for establishing a robust stem cell pool into adulthood. This study determines the niche cell types that present Vcam1 in the embryo and allow interaction with blood stem cells.

developmental biology↗

bioRxiv2025

Separately prestored proteasome components to prevent polyspermy

To ensure genome stability across generations, an egg must be fertilized by only a single sperm. However, how sperm actively contribute to preventing polyspermy has remained unknown. Here, we demonstrate that testis-specific 20S proteasome core particles (CPs) are pre-stored within the sperm heads of both mice and humans. Upon fertilization, these testis-specific 20S CPs assemble with oocyte-derived 19S regulatory particles (RPs), forming chimeric proteasomes that efficiently degrade Fetuin B, which is ubiquitinated by the E3 ligase MARCH3. The clearance of Fetuin B triggers ZP2 cleavage and subsequent zona pellucida hardening, thereby blocking additional sperm entry. The newly assembled chimeric proteasome in the zygote represents a novel strategy to prevent polyspermy during fertilization in mammals.

developmental biology↗

bioRxiv2025

Therapeutic Salmonella induces long-term protective trained immunity in NK cells against cancer metastasis

Trained immunity, a form of innate immune memory initially recognized in pathogen defense, has recently been reported to aid in combating cancer. Although trained immunity has been well-characterized in myeloid lineage cells, its presence in innate lymphoid cells, particularly natural killer (NK) cells, remains largely unexplored. Here, we report that a single dose of Salmonella YB1, an attenuated candidate anticancer vaccine strain, provides long-lasting protection against cancer metastasis in mice by inducing trained natural killer (NK) cells. Functional assays coupled with multiomics analysis revealed that Salmonella-trained NK (stNK) cells establish an enduring reprogrammed epigenome characterized by enhanced pro-survival signaling and immune effector functions, resulting in more potent IFN-{gamma} release and cytotoxicity upon secondary stimulation. We further revealed that IL-12 and IL-18 are essential but insufficient for this NK cell training effect. Crucially, stNK cells far outperform the common immune checkpoint therapies, including PD-1 and TIGIT blockade, in suppressing metastasis, underscoring the unique immunological mechanisms in combating metastasis. These findings uncover a novel long-term anti-metastatic function of trained immunity in NK cells, highlighting its potential as an effective antitumor strategy.

immunology↗

bioRxiv2025

Lineage-Specific Epigenomic Mapping of Proximal and Distal Fallopian Tube Epithelium Reveals Mesenchymal/Wnt-Driven Tumor Phenotype Diversification

High-grade serous ovarian cancer (HGSC) typically originates from the distal fallopian tube epithelium (disFTE), while the proximal epithelium (proFTE) remains less explored. Here, Using isogenic murine organoid models with common oncogenic drivers (Tp53-/-; Krasmut; Pten-/-), we show that disFTE and proFTE generate distinct tumor subtypes driven by region-specific transcriptional programs. Unlike disFTE, proFTE demonstrates continuous activation of epithelial-mesenchymal transition (EMT) across wild-type, mutant organoids, and derived tumors. Additionally, mutated proFTE organoids and their tumors exhibit persistent WNT signaling activation and grow independently of WNT signals. Chromatin profiling shows that mutant proFTE maintains a distinctive epigenetic profile with promoters associated with EMT and WNT pathways. Human proFTE with BRCAmut also shows epigenetic activation of EMT- and WNT-related genes. Tumors near the uterotubal junction (UTJ)--anatomically akin to proFTE--exhibit a pronounced EMT signature, increased Vimentin+E-cadherin+ and nuclear {beta}-catenin expression. These findings suggest proFTE-derived tumors may occupy a unique niche in gynecological malignancies, with regional identity shaping tumor phenotypes.

cancer biology↗