Biology subjects

Wan, X.

Publications and source records attributed to Wan, X..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

O-Acyltransferase Genes Involved in the Production of Volatile Sex Pheromones in Caenorhabditis elegans

Gene family expansions are critical for functional diversification, yet paralog contributions to metabolic pathways are often unclear. In Caenorhabditis, the expanded O-acyltransferase (OAC) family--enzymes that transfer acyl groups to hydroxylated substrates--remains poorly characterized despite having been implicated in lipid metabolism. Using CRISPR-Cas9 mutagenesis, behavioral assays, gas chromatographic-mass spectral (GC-MS) analyses, and metabolomics, we systematically analyzed 59 OAC-family protein-coding genes to define their roles in regulating signaling molecules. We found that four adjacent paralogs (oac-13, oac-16, oac-25, and oac-28) on chromosome I are required for synthesizing volatile sex pheromones (VSPs)--airborne signals critical for male mate-searching. Specifically, oac-13 and oac-16 are necessary for producing both major pheromone components, while the identical tandem paralogs oac-25 and oac-28 regulate the production of the later-eluting component in gas chromatography. Disruption of these genes reduced production of key pheromone components and impaired male attraction. Metabolomics revealed that oac-16 and other OACs also modulate synthesis and secretion of non-volatile ascaroside pheromones, indicating dual roles in chemical signaling. This work uncovers functional specialization within an expanded gene family, illustrating how redundancy and divergence enable adaptive evolution of communication systems.

biochemistry↗

bioRxiv2025

Study on physiological and ecological responses of alfalfa during the germination stage under drought, bicarbonate, and combined stress conditions

Alfalfa (Medicago sativa L.) is frequently constrained by drought and salinity during cultivation and production. This study aimed to investigate the differential response characteristics and underlying physiological and ecological mechanisms of alfalfa during the germination stage under drought stress, bicarbonate stress, and their combined effects. Twelve alfalfa varieties were subjected to germination tests using PEG-6000 to simulate drought stress (0-20%) and NaHCO{square} to simulate bicarbonate stress (0-30 mM). Based on the semi-inhibitory concentrations and phenotypic indices observed under single-stress conditions, a combined stress treatment was designed. The subordinate function method was employed to comprehensively evaluate the variations in stress responses among the twelve alfalfa varieties during the germination stage. Additionally, this study explored the physiological and ecological response mechanisms of drought-tolerant, salt-tolerant, and drought-salt-sensitive varieties. Among the 12 alfalfa varieties, WL363HQ has the strongest drought and salt tolerance, while WL319HQ is the most sensitive to drought and salt stress. Based on this, the varieties can be classified into drought-tolerant, salt-tolerant, and sensitive categories. At low concentrations, the drought-salt combination shows antagonism (salt alleviates drought inhibition); at high concentrations, it turns into synergy, and the inhibitory effect is amplified.WL363HQ adapts to the combined stress by maintaining stable SOD activity and gradually accumulating soluble sugar; WL319HQ shows sensitivity due to fluctuating SOD, membrane lipid peroxidation, and uncontrolled soluble sugar.

plant biology↗

bioRxiv2025

Activating RET Mutations Promotes Osteoblastic Bone Metastases in Medullary Thyroid Cancer

Development of bone metastases increases mortality in patients with medullary thyroid cancer (MTC), with [~]50% survival at 5 years after diagnosis, but the underlying mechanisms are unknown. We show that patient-derived MTC cells (RETC634W mutant TT cells and RETM918T mutant MZCRC1 cells) promote an osteoblastic phenotype due to reduced bone resorption. Mechanistically, activated RET increases the expression of osteoprotegerin (OPG), an inhibitor of bone resorption, leading to decreased osteoclast differentiation. Furthermore, RET knockdown or pharmacological RET inhibition attenuates tumor burden and osteoblastic lesions in MTC-bearing femurs. Circulating levels of OPG were increased in the plasma of MTC patients who developed bone metastases and this was associated with poor overall survival. Patients who were treated with multi-kinase inhibitors have lower circulating levels of OPG. These novel findings identify a link between the RET signaling pathway and abnormal osteoblastic bone formation and suggest OPG as a potential biomarker of MTC bone metastases. HighlightsO_LIPatient-derived MTC cells promote osteoblastic lesions in a mouse model. C_LIO_LIActivating the RET mutation promotes osteoprotegerin. C_LIO_LIBlocking RET kinase activity inhibits tumor growth and the osteoblastic lesion phenotype. C_LIO_LIHigh levels of circulating osteoprotegerin are associated with poor overall survival. C_LI

cancer biology↗

bioRxiv2025

Mechanism-Aware Protein-Protein Interaction Prediction via Contact-Guided Dual Attention on Protein Language Models

Robust prediction of protein-protein interactions (PPIs) requires models that generalize beyond the training distribution. Here, we present PLMDA-PPI, a mechanism-aware framework that incorporates biophysical inductive biases into a dual-attention architecture with residue-level contact supervision applied to protein language model embedded geometric representations. This design enables the model to jointly learn global interaction likelihoods and the residue pairs mediating interactions, producing interpretable, mechanism-grounded predictions. PLMDA-PPI demonstrates strong out-of-distribution generalization, substantially outperforming lightweight deep learning models (D-SCRIPT, Topsy-Turvy, TT3D, and TUnA) and achieving comparable or even superior performance to computationally intensive methods (AF2Complex, RF2-Lite, and RF2-PPI) derived from AlphaFold2 and RoseTTAFold2, while requiring orders of magnitude fewer computational resources. These results show that incorporating mechanistic priors as architectural inductive biases enhances generalization, interpretability, and computational efficiency, providing a principled foundation for AI-driven prediction of complex biological interactions.

bioinformatics↗

bioRxiv2025

Human meibomian gland organoids to study epithelial homeostasis and dysfunction

Meibomian glands (MGs) are holocrine glands that secrete lipids to maintain the homeostasis of ocular surface, and their dysfunction leads to dry eye disease. Herein, we established long-term 3D organoid culture for murine and human MGs, which retained the cell lineages and lipid-producing ability. The organoids mimicked the drug treatment responses and generated functional MGs after orthotopic transplantation. Inspired by organoid cultures, we found FGF10 eye drops could rescue all-trans retinoic acid-induced MG dysfunction in mice. Besides, nicotinamide uniquely hampered the human MG organoid expansion by inhibiting FGF10 signaling. Single-cell atlas and lipidome not only aligned the delineated cell types and featured lipids between human MGs and organoids, but highlighting MAPK signaling inhibition enhanced acinar cell differentiation and functional maturation of MG organoids. In summary, this study established an organoid platform to explore epithelial homeostasis and dysfunction of MGs, facilitating drug development and regenerative medicine for dry eye disease.

cell biology↗

bioRxiv2025

Identification of locally activated spindle-associated proteins in oocytes uncovers a phosphatase-driven mechanism

The meiotic spindle forms only around the chromosomes in oocytes, despite the exceptionally large volume of the cytoplasm. This spatial restriction is likely to be governed by local activation of key microtubule regulators around the chromosomes in oocytes, but the identities of these microtubule regulators and the mechanisms remain unclear. To address this, we developed a novel assay to visualise spatial regulation of spindle-associated proteins in Drosophila oocytes by inducing ectopic microtubule clusters. This assay identified several proteins including the TPX2 homologue Mei-38 that localise more strongly to microtubules near the chromosomes than away from them. We identified a microtubule-binding domain containing a region highly conserved also in humans. The domain itself is regulated spatially, and contains a conserved serine and a nearby PP2A-B56 docking motif. A non-phosphorylatable mutation of this serine allows the domain to localise to ectopic microtubules as well as spindle microtubules, while mutations in a PP2A-B56 docking motif greatly reduced the spindle localisation. As this phosphatase is concentrated at the kinetochores, it may act as a novel chromosomal signal spatially regulating spindle proteins within oocytes.

cell biology↗

bioRxiv2025

Pangenome analyses of tea plant reveal structural variations driven gene expression alterations and agronomic trait diversification

Tea plants, one of the worlds most economically significant beverage crops, exhibit extensive genetic diversity and a rich array of secondary metabolites. While structural variations (SVs) are key drivers of phenotypic innovation, their regulatory roles in transcriptional networks and agronomic trait diversification remain underexplored in this perennial crop. We constructed a pangenome from 21 representative tea accessions and their wild relatives. Comparative analysis revealed that wild relatives harbor a greater abundance of gibberellin-related genes, whereas cultivated accessions exhibit an expansion of defense-related genes. We identified 522,428 non-redundant SVs, primarily insertions/deletions (73.56%), which were enriched in promoter regions. These SVs influenced the expression of genes governing flavor compounds, including those involved in flavonoid, amino acid, and terpenoid biosynthesis. Population SV analysis of 275 tea accessions uncovered three haplotypes in the ANS3 gene promoter region, with Hap1, containing a 192 bp insertion, predominantly found in wild relatives but largely lost in modern cultivars. This insertion enhanced CtANS3 expression, increasing anthocyanin accumulation. Additionally, a 159 bp insertion in the CtLRR1 promoter reduced resistance to Colletotrichum gloeosporioides in wild relatives. Our findings underscore SVs as pivotal regulators of genomic diversity, flavor differentiation, and adaptive evolution in tea plant domestication.

genomics↗

bioRxiv2025

Closing The Loop: A Dynamic Neural Network Model Integrating Decision making and Metacognition

Decision making under uncertainty entails selecting optimal actions from noisy evidence. Currently influential models, such as drift-diffusion and attractor frameworks, posit decisions as bottom-up stochastic evidence accumulation from sensory inputs but ignore critical interactions between decision, commitment, and metacognition. While these models explain basic choice behaviors and accompanying confidence, they fail to reconcile many empirical findings, including motor-area encoding of decision variables and time-dependent urgency signals. We present a closed-loop neural network model unifying three modules: decision module accumulating evidence, a motor module implementing action thresholds, and a metacognition module regulating deliberation through dual feedback pathways to suppress noise-driven errors and accelerate decision commitment under time constraints, respectively. This architecture can account for crucial characteristics of decision-making and metacognition that were empirically observed. By integrating decision, motor, and metacognitive dynamics, our model provides a biologically grounded framework for optimal decision making, offering testable predictions for neural and behavioral studies.

neuroscience↗

bioRxiv2024

Efficient pheromone navigation via antagonistic detectors

Chemotaxis to a moving potential mate that emits a volatile sex pheromone poses a navigation challenge requiring rapid, precise responses to maximize reproductive success. Volatile chemicals form gradients that differ from soluble compounds, potentially making navigation based on comparisons between spatially separated sensors unreliable for small-bodied animals. Here we show that, rather than a simple spatial comparison, Caenorhabditis elegans males employ an antagonistic strategy, comparing inputs from sex-shared head (AWA) and male-specific tail (PHD) sensory neurons with distinct response properties. Despite sharing a receptor, SRD-1, these detectors play different roles: AWAs promote forward movement and acceleration, while PHDs induce reversals and deceleration. In rising pheromone gradients, AWA activity dominates; in falling gradients, AWA inactivates, allowing PHD to correct trajectories. AWAs are essential for mate-searching, while PHDs are crucial for complex tasks. A minimal computational model reproduces these behaviors and infers how head-tail signals are combined. Thus, a sexually dimorphic, antagonistic sensory system enables adaptive navigation in dynamic environments

neuroscience↗

bioRxiv2024

A post-translational cysteine-to-serine conversion in human and mouse insulin generates a diabetogenic neoepitope

The evolving antigenic landscape of autoimmune diabetes reflects a dynamic failure to preserve self-tolerance. Yet, how novel neoantigens emerge in humans remains incompletely understood. Here, we designed an immunopeptidomics-based approach to probe HLA-II-bound, islet-derived neoepitopes in patients with type 1 diabetes (T1D). We uncovered a microenvironment-driven Cys[->]Ser transformation, conserved between mice and humans, that reshapes autoreactivity to insulin, the core {beta}-cell antigen, at the single-residue level. This transformation, which we call "C19S," arises from oxidative remodeling of insulin in stressed pancreatic islets and can also occur in inflammatory antigen-presenting cells, contributing to a feed-forward loop of neoepitope formation and presentation as diabetes progresses. Despite involving just one amino acid, C19S is specifically recognized by HLA-DQ8-restricted, register-specific CD4+ T cells that expand in individuals with T1D. These C19S-specific CD4+ T cells lack regulatory potential but acquire a poised central memory phenotype that persists at different disease stages. These findings reveal a distinct, microenvironment-driven route of neoantigen formation that fuels sustained autoreactivity in diabetes.

immunology↗

bioRxiv2024

Retrospective Attention Can Trigger Visual Perception Without Dependence on Either Cue Awareness or Target Reporting

Whether retrospective attention changes a target representation relevant to conscious perception, rather than only later report processes, remains unresolved. Across three experiments, we traced a progression from retroperception to attentional selection and to a consciousness-linked target representation. Experiments 1 and 2 showed that post-target cues altered orientation discrimination despite strongly reduced cue-location discrimination; Experiment 2 additionally revealed an N2pc modulation, a lateralized event-related potential (ERP) signature consistent with attentional selection. Experiment 3 combined parallel Report and No-report sessions with cue-controlled EEG and validity-neutral decoding. During Report, stronger target evidence predicted visibility and orientation discrimination, and Valid cues enhanced this evidence at medium contrast. Under No-report, Valid cues enhanced high-contrast target evidence. Crucially, target evidence learned entirely under No-report predicted visibility and orientation discrimination in an independent Report session, and target-present codes generalized between Report and No-report in both directions. In contrast, validity transfer was reliable only from Report to No-report. These results support the conclusion that retrospective attention can strengthen a target representation linked to conscious visibility and discrimination without requiring an explicit target report.

neuroscience↗

bioRxiv2024

Bio-medical Big Data Operating System (Bio-OS): An Integrated Data Mining Environment for Data Intensive Scientific Research

The advent of high throughput sequencing has ushered life science and clinical research into the era of big data, posing significant challenges for reproducibility due to the complexity of data integration and analysis. Although the FAIR principles advocate for the transparent and reliable sharing of scientific data, their implementation remains hampered by technical barriers. The Global Alliance for Genomics and Health (GA4GH) has made strides in standardizing data and tools, yet a comprehensive solution for reproducibility is lacking. In response, we present BioOS, an open source, cloud native Biomedical big data Operating System. This system encapsulates study components data, code, tools, and environments into workspaces, enhancing reproducibility and validation. BioOS employs JSON Schema for machine readability and includes a Hierarchy Hash Mechanism to ensure data integrity. Adhering to GA4GH protocols, BioOS simplifies complex technological implementations, making advanced research tools accessible. Demonstrated through representative workspaces, BioOS fosters seamless research replication, peer review, and editorial evaluation. Its cloud native infrastructure supports dynamic resource allocation, enabling efficient handling of large scale analyses. By integrating AI driven Large Language Models, BioOS enhances user interaction and operational flexibility. As an evolving open source platform, BioOS exemplifies a transformative approach to biomedical research, aligning with FAIR principles and advancing the AI for Science paradigm, thus promoting a more connected, efficient, and impactful research environment.

bioinformatics↗

bioRxiv2024

SciMind: A Multimodal Mixture-of-Experts Model for Advancing Pharmaceutical Sciences

Large language models (LLMs) have made substantial strides, but their use in reliably tackling issues within specialized domains, particularly in interdisciplinary areas like pharmaceutical sciences, is hindered by data heterogeneity, knowledge complexity, unique objectives, and a spectrum of constraint conditions. In this area, diverse modalities such as nucleic acids, proteins, molecular structures, and natural language are often involved. We designed a specialized token set and introduced a new Mixture-of-Experts (MoEs) pre-training and fine-tuning strategy to unify these modalities in one model. With this strategy, weve created a multi-modal mixture-of-experts foundational model for pharmaceutical sciences, named SciMind. This model has undergone extensive pre-training on publicly accessible datasets including nucleic acid sequences, protein sequences, molecular structure strings, and biomedical texts, and delivers good performance on biomedical text comprehension, promoter prediction, protein function prediction, molecular description, and molecular generation.

bioinformatics↗

bioRxiv2024

UCS: a unified approach to cell segmentation for subcellular spatial transcriptomics

Subcellular Spatial Transcriptomics (SST) represents an innovative technology enabling researchers to investigate gene expression at the subcellular level within tissues. To comprehend the spatial architecture of a given tissue, cell segmentation plays a crucial role in attributing the measured transcripts to individual cells. However, existing cell segmentation methods for SST datasets still face challenges in accurately distinguishing cell boundaries due to the varying characteristics of SST technologies. In this study, we propose a unified approach to cell segmentation (UCS) specifically designed for SST data obtained from diverse platforms, including 10X Xenium, NanoString CosMx, MERSCOPE, and Stereo-seq. UCS leverages deep learning techniques to achieve high accuracy in cell segmentation by integrating nuclei segmentation from nuclei staining and transcript data. Compared to current methods, UCS not only provides more precise transcript assignment to individual cells but also offers computational advantages for large-scale SST data analysis. The analysis output of UCS further supports versatile downstream analyses, such as subcellular gene classification and missing cell detection. By employing UCS, researchers gain the ability to characterize gene expression patterns at both the cellular and subcellular levels, leading to a deeper understanding of tissue architecture and function.

bioinformatics↗

bioRxiv2024

MitoStructSeg: A Comprehensive Platform for Mitochondrial Structure Segmentation and Analysis

Mitochondrial morphology and structural changes are closely associated with metabolic dysfunction and disease progression. However, the structural complexity of mitochondria presents a major challenge for accurate segmentation and analysis. Most existing methods focus on delineating entire mitochondria but lack the capability to resolve fine internal features, particularly cristae. In this study, we introduce MitoStructSeg, a deep learning-based framework for mitochondrial structure segmentation and quantitative analysis. The core of MitoStructSeg is AMM-Seg, a novel model that integrates domain adaptation to improve cross-sample generalization, dual-channel feature fusion to enhance structural detail extraction, and continuity learning to preserve spatial coherence. This architecture enables accurate segmentation of both mitochondrial membranes and intricately folded cristae. MitoStructSeg further incorporates a quantitative analysis module that extracts key morphological metrics, including surface area, volume, and cristae density, allowing comprehensive and scalable assessment of mitochondrial morphology. The effectiveness of our approach has been validated on both human myocardial tissue and mouse kidney tissue, demonstrating its robustness in accurately segmenting mitochondria with diverse morphologies. In addition, we provide an open source, user-friendly tool to ensure practical usability.

bioinformatics↗

bioRxiv2024

Perineuronal nets in motor circuitry regulate the performance of learned vocalizations in songbirds

The accurate and reliable production of learned behaviors can be important for survival and reproduction; for example, the performance of learned vocalizations (e.g., speech and birdsong) modulates the efficacy of social communication in humans and songbirds. Consequently, it is critical to understand the factors that regulate the performance of learned behaviors. Across various taxa, neural circuits that regulate motor learning are replete with perineuronal nets (PNNs), extracellular matrices that surround neurons and shape neural dynamics and plasticity. Perineuronal nets in circuits for sensory and cognitive processes have been found to affect sensory processing and behavioral plasticity. However, the function of PNNs in motor circuits remains largely unknown. Here, we analyzed the causal contribution of PNNs in motor circuitry to the performance of learned vocalizations in songbirds. Songbirds like the zebra finch are powerful models for this endeavor because the performance of their learned songs is regulated by activity within discrete and specialized circuits (i.e., song system) that are dense with PNNs. We first report that developmental increases in the density and intensity of PNNs throughout the song system [including in the motor nucleus HVC (acronym used as proper name)] are associated with developmental increases in song performance. We next discovered that enzymatically degrading PNNs in HVC acutely affected song performance. In particular, PNN degradation caused song structure to deviate from pre-surgery song due to changes in syllable sequencing and production. Collectively, our data provide compelling evidence for a causal contribution of PNNs to the performance of learned behaviors. SIGNIFICANCE STATEMENTMotor circuits are replete with perineuronal nets (PNNs) but little is known about their contribution to motor performance. Here, we analyzed how PNNs within vocal motor circuits modulate the ability of songbirds to consistently produce their learned songs. We report that developmental increases in PNN expression in vocal circuitry were associated with developmental increases in the ability to consistently perform their learned song. Moreover, degrading PNNs in the vocal motor nucleus HVC reduced the ability of adult birds to accurately produce their learned song. Our findings indicate a causal contribution of PNNs in motor circuitry to the performance of learned behaviors and, because PNNs are expressed in brain areas regulating speech, suggest that PNNs could modulate speech production in humans.

neuroscience↗

bioRxiv2024

The microtubule regulator EFA-6 forms spatially restricted cortical foci dependent on its intrinsically disordered region and interactions with tubulins

Microtubules (MTs) are dynamic components of the cytoskeleton and play essential roles in morphogenesis and maintenance of tissue and cell integrity. Despite recent advances in understanding MT ultrastructure, organization, and growth control, how cells regulate MT organization at the cell cortex remains poorly understood. The EFA-6/EFA6 proteins are recently identified membrane-associated proteins that inhibit cortical MT dynamics. Here, combining visualization of endogenously tagged C. elegans EFA-6 with genetic screening, we uncovered tubulin-dependent regulation of EFA-6 patterning. In the mature epidermal epithelium, EFA-6 forms punctate foci in specific regions of the apical cortex, dependent on its intrinsically disordered region (IDR). We further show the EFA-6 IDR is sufficient to form biomolecular condensates in vitro. In screens for mutants with altered GFP::EFA-6 localization, we identified a novel gain-of-function (gf) mutation in an -tubulin tba-1 that induces ectopic EFA-6 foci in multiple cell types. tba-1(gf) animals exhibit temperature-sensitive embryonic lethality, which is partially suppressed by efa-6(lf), indicating the interaction between tubulins and EFA-6 is important for normal development. TBA-1(gf) shows reduced incorporation into filamentous MTs but has otherwise mild effects on cellular MT organization. The ability of TBA-1(gf) to trigger ectopic EFA-6 foci formation requires {beta}-tubulin TBB-2 and the chaperon EVL-20/Arl2. The tba-1(gf)-induced EFA-6 foci display slower turnover, contain the MT-associated protein TAC-1/TACC, and require the EFA-6 MTED. Our results reveal a novel crosstalk between cellular tubulins and cortical MT regulators in vivo. HighlightsO_LIThe MT regulator EFA-6 forms spatially restricted punctate cortical foci C_LIO_LIThe EFA-6 N-terminal intrinsically disordered region (IDR) is essential for the formation of cortical foci in vivo and is sufficient for droplet formation in vitro C_LIO_LITubulins regulate formation of EFA-6 foci via the EFA-6 MT elimination domain C_LIO_LIEFA-6 foci induced by altered tubulin heterodimer function display reduced turnover and recruit TAC-1/TACC C_LI

cell biology↗

bioRxiv2024

Root-specific secondary metabolism at the single-cell level: a case study of theanine metabolism and regulation in the roots of tea plants (Camellia sinensis)

Root-synthesized secondary metabolites are critical quality-conferring compounds of foods, plant-derived medicines, and beverages. However, information at a single-cell level on root-specific secondary metabolism remains largely unexplored. L-theanine, an important quality component of tea, is primarily synthesized in roots, from which it is then transported to new shoots of tea plant. In this study, we present a single-cell RNA sequencing (scRNA-seq)-derived map for the tea plant root, which enabled cell-type-specific analysis of glutamate and ethylamine (two precursors of theanine biosynthesis) metabolism, and theanine biosynthesis, storage, and transport. Our findings support a model in which the theanine biosynthesis pathway occurs via multicellular compartmentation and does not require high co-expression levels of transcription factors and their target genes within the same cell cluster. This study provides novel insights into theanine metabolism and regulation, at the single-cell level, and offers an example for studying root-specific secondary metabolism in other plant systems.

plant biology↗