Biology subjects

Guo, W.

Publications and source records attributed to Guo, W..

At least 91 records · Page 5Linked to original sources

bioRxiv2025

The fetal hydrops-associated single-residue mutation L322P abolishes mechanical but not chemical activation of the PIEZO1 ion channel

The mechanically activated PIEZO1 ion channel is genetically linked to numerous physiological and pathophysiological processes. For example, deleting PIEZO1 in mice leads to defective lymphatic vessel development, while nonsense mutations in humans are associated with autosomal recessive generalized lymphatic dysplasia (GLD) and non-immune hydrops fetalis. However, it remains unclear whether PIEZO1-dependent biological processes are directly mediated by its intrinsic mechanosensitivity. Here we identified a human fetal hydrops-associated single-residue mutation, L322P (corresponding to L329P in mouse PIEZO1), which completely abolishes PIEZO1s response to mechanical stimuli while maintaining normal plasma membrane expression and responsiveness to its chemical activators, Yoda1 and Jedi1. Remarkably, the mechanical response of the mutant can be restored by Yoda1. These findings demonstrate a direct link between the loss of PIEZO1s mechanosensitivity and the pathophysiological phenotype of fetal hydrops, and raise the therapeutic potential of using PIEZO1 chemical activators to restore the mechanosensitivity of PIEZO1 missense mutants that are associated with genetic diseases such as GLD and hydrops fetalis. Significance StatementGenetic deletion studies have revealed the diverse cellular, physiological, and pathophysiological roles of the mechanically activated PIEZO1 ion channel. However, whether these functions are directly mediated by its mechanosensitivity has remained experimentally unaddressed. In this study, we identified a novel fetal hydrops-associated single-residue mutation, hPIEZO1-L322P, which specifically abolishes PIEZO1s mechanical response while retaining its chemical activation. Remarkably, the mechanical response of the mutant can be fully restored by the PIEZO1 chemical activator Yoda1. These findings address the long-standing question of whether PIEZO1 relies on its mechanosensitivity to mediate in vivo functions, provide critical insights into the mechanosensing mechanism of PIEZO1, and highlight the therapeutic potential of using PIEZO1 chemical activators to rescue the loss of mechanosensitivity caused by missense mutations.

physiology↗

bioRxiv2025

Utilising multi-modal data-driven network analysis to identify monotherapy and combinational therapy targets in SOX2-dependent squamous cell lung cancer

Drug discovery requires a deep understanding of disease mechanisms, making the integration and analysis of diverse, multi-modal data types essential. These data types, spanning omics types, disease- associated, and biological pathway information, often originate from disparate sources and must be combined to uncover critical insights. We have developed iPANDDA (in-silico Pipeline for Agnostic Network-based Drug Discovery Analysis), a computational pipeline that integrates multi-modal data through a network-based approach to predict candidate drug target proteins for specific diseases. We applied iPANDDA to lung squamous cell carcinoma (LUSC), a subtype of non-small cell lung cancer (NSCLC) that accounts for approximately 25% of all lung cancer cases globally. Despite advances in cancer therapeutics, targeted therapies specifically approved for LUSC remain lacking, exacerbated by the shortage of robust models for studying LUSC carcinogenesis and therapeutic responses. The SOX2 gene, amplified in about 50% of LUSC patients, plays a critical role in driving and maintaining the cancer phenotype. Using iPANDDA, we identified relevant therapeutic targets for SOX2-dependent LUSC. Selected candidate drug targets were validated in vitro using cell-based models. We conducted target inhibition studies in both SOX2-dependent and non-SOX2-dependent cell lines, evaluating the effects of inhibition and knockout through cell viability assays. Our findings confirmed key monotherapy and combination therapy targets for SOX2-focused models. Specifically, we validated the AKT and mTOR complexes as promising therapeutic targets for LUSC. Additionally, we identified potential pathways for developing novel combination therapies targeting SOX2-dependent LUSC. iPANDDA offers a robust approach to refining and focusing therapeutic strategies for diseases with unmet clinical needs.

bioinformatics↗

bioRxiv2025

JRSeek: Artificial Intelligence Meets Jelly Roll Fold Classification in Viruses

The jelly roll (JR) fold is the most common structural motif found in the capsid and nucleocapsid of viruses. Its pervasiveness across many different viral families motives developing a tool to predict its presence from a sequence. In the current work, logistic regression (LR) models trained on six different large language model (LLM) embeddings exhibited over 95% accuracy in differentiating JR from non-JR sequences. The dataset used for training and testing included sequences from single JR viruses, non-JR viruses, and non-virus immunoglobulin-like {beta}-sandwich (IGLBS) proteins which closely resemble the JR fold in structure. The high accuracy is particularly remarkable given the low sequence similarity across viral families and the balanced nature of the dataset. Also, the accuracy of the models was independent of LLM embeddings, suggesting that peak accuracy for predicting viral JR folds hinges more on the data quality and quantity rather than on the specific mathematical models used. Given that many viral capsid and nucleocapsid structures have yet to be resolved, using sequence-based LLMs is a promising strategy that can readily be applied to available data. Principal Component Analysis of the Bert-U100 embeddings demonstrates that most IGLBS sequences and a subset of JR and non-JR sequences are distinguishable even before the application of the LR model, but the LR model is necessary to differentiate a subset of more ambiguous sequences. When applied to double JR folds, the Bert-U100 model was able to assign the JR motif for some viral families, providing evidence for the models generalizability. However, for other families, this generalizability was not observed, motivating a future need to develop other models informed by double JR folds. Lastly, the Bert-U100 model was also able to predict whether sequences from a dataset of unclassified viruses produce the JR fold. Two examples are given and the JR predictions are corroborated by AlphaFold3. Altogether, this work demonstrates that JR folds can, in principle, be predicted from their sequences.

bioinformatics↗

bioRxiv2025

Local Microenvironments of capsomer variants in the PBCV-1

PBCV-1, a giant virus classified among the Nucleocytoviricota virus (NCV) whose structure has been determined to near atomic resolution. The majority capsomers forming the capsid of PBCV-1 are Type I capsomers while five other type of variants have been found in recent high resolution structure. Interestingly, some variants, such as Type V capsomers, are found at particular capsid locations whose roles are unclear. To reveal the roles of a Type V capsomer, we replaced the Type V capsomer by a Type I capsomer to compare the interaction among the two types of capsomer variant, especially the interactions between each of the Type V/Type I capsomer and its local capsid microenvironment. Our results revealed significant differences between Type V and Type I capsomers. Notably, the Type V capsomer demonstrated a stronger binding force to the surrounding capsomers than the Type I capsomer. Moreover, the identified salt bridges between Type V/I capsomers and their surrounding capsomers corroborate the results of electrostatic calculations, further highlighting the important residues involved in these interactions. Understanding these local capsid microenvironments will be essential to elucidate the mechanisms governing viral capsid assembly.

biophysics↗

bioRxiv2025

Striatal cell-type specific stability and reorganization underlying agency and habit

Goal-directed behavior is guided by learned action-outcome associations, allowing actions to adapt when outcomes change. With repetition, behavioral control shifts toward habit, enabling more automatic action execution, but reducing flexibility to outcome changes. Here, we used longitudinal, cellular-resolution calcium imaging, chemogenetics, instrumental conditioning, and the outcome devaluation test to ask how dorsomedial striatum D1+ and D2/A2A+ neurons contribute to the formation of goal-directed behavior and habit. DMS D1+ neurons stably encode instrumental actions, carry information about behavioral engagement and organization, and develop and maintain action-reward representational similarity and conjunctive activation with learning. Correspondingly, these neurons are critical for action-outcome learning and goal-directed decision making. In contrast, one ensemble of DMS A2A+ neurons transiently encodes actions during early action-outcome learning and another slowly starts to encode actions as habits form. Similarly, DMS A2A+ neurons transiently mediate action-outcome learning and become dispensable for goal-directed decision making. Thus, action-outcome associations are learned through DMS D1+ and A2A+ neuronal activity but only DMS D1+ neurons maintain support of adaptive, goal-directed decision making. Habit formation is associated with reorganization of A2A+ neuronal encoding. These data reveal a cell-type-specific dissociation between stable v. reorganizing striatal action representations paralleled by persistent v. transient contributions to goal-directed control.

neuroscience↗

bioRxiv2025

Title: Cell-autonomous and non-cell-autonomous effects of TRIM72 on ALS disease progression

Dysfunction of RNA-binding proteins, including TDP-43 and FUS, has been associated with amyotrophic lateral sclerosis (ALS); however, the underlying mechanisms are largely unknown. Here, we reported that a neuronal upregulation of TRIM72 (Tripartite Motif Containing 72) in FUS mutation knockin ALS models slows disease progression. TRIM72 interacts with Commander, a protein complex for recycling of membrane proteins, facilitating membrane repair and antioxidation. Exosomal TRIM72 is detected in ALS patient cerebrospinal fluid (CSF) and extracellular application of exosomal TRIM72 protects cell from membrane damage. In a sporadic ALS cohort, CSF TRIM72 level associates ALS disease progression. AAV-mediated neuronal expression of TRIM72 slows down the disease progressions in ALS models and in an ALS patient without adverse effects over a year treatment course. Taken together, our results suggest a universal neuronal protection of a TRIM family protein in cell-autonomous and non-cell-autonomous manners in ALS.

neuroscience↗

bioRxiv2025

The small genome size ensures adaptive flexibility for an alpine ginger

Understanding the proximate and ultimate causes of genome size (GS) variation is the focus of much research. However, the extent and causes of intraspecific variation in GS is debated and poorly understood. This study aims to test the large-genome constraint hypothesis through the variations of intraspecific GS. GS was measured in 53 Roscoea tibetica populations from the Hengduan Mountains using flow cytometry. Stomatal size and density were collected from the wild populations and common garden populations. Associations between GS and environmental factors, stomatal traits were explored. We found that high GS variability was positively correlated with most environmental factors but negatively correlated with solar radiation during the growing season. The environment, rather than geography, significantly influenced the variations in GS. The stomatal traits measured in the wild were significantly correlated with GS, but no such correlations were detected in the common garden. Populations in the common garden have larger stomatal size and lower stomatal density. Populations with smaller GS present larger degree of stomatal traits variation from wild to common garden. Our findings suggests that intraspecific GS has experienced adaptive evolution driven by environmental stress and the evolution of intraspecific GS can be explained by the large-genome constraint hypothesis. Smaller GS is more advantageous to the alpine ginger to adapt to alpine habitat and thrive in changing habitat.

ecology↗

bioRxiv2025

Single-cell and spatial transcriptomics uncover the role of B chromosomes in driving plant invasiveness

Invasive plants pose a major threat to global biodiversity, yet the molecular and genomic mechanisms underlying their success remain poorly understood. Here, we investigate the common reed (Phragmites australis), a grass species that became invasive in North America after introduction from Europe, to unravel the molecular mechanisms of its invasiveness. By integrating single-cell RNA sequencing, spatial transcriptomics, and comparative genomics, we constructed a single-cell atlas of P. australis and identified 19 transcriptionally distinct cell types, including shoot apical meristem, epidermal, and vascular tissues. Comparative analysis of common garden-grown native (European) and invasive (North American) populations revealed a significant proportion of differentially expressed genes (DEGs) located on B chromosomes, which underwent copy number expansion in invasive genomes. The proportion of B chromosome genes in DEGs varies across cell types, with the highest proportions observed in the epidermis and mesophyll, and lower proportions in the vascular tissues. Gene IMPA-3, a B chromosome gene likely derived from transposable element activity, exhibited an elevated mutation rate compared to its ancestral counterparts, potentially enhancing adaptive evolution in invasive populations. Invasive individuals also displayed molecular regulatory networks related to photosynthetic efficiency, stress tolerance, and growth-defense trade-offs. Together, our findings provide a cell-type-resolved molecular atlas of a non-model invasive plant and offer key insights into the cellular and genomic architecture of plant invasiveness, with implications for ecological management.

evolutionary biology↗

bioRxiv2024

Reshaping epigenomic landscapes in facilitating the speciation of bread wheat

Polyploidization is a driving force of wheat evolution and speciation, yet its impact on epigenetic regulation and gene expression remains unclear. Here, we constructed a high-resolution epigenetic landscape across leaves, spikes, and roots of hexaploidy wheat and its tetraploid and diploid relatives. Inter-species stable-expression genes exhibited conserved amino acid sequences under strong purifying selection, while dynamic-expression genes were linked to species-specific adaptation. During hexaploidization, dominant D-subgenome homoeolog expression was suppressed via reduced activating epigenetic signals, converging expression with the A and B subgenomes. Proximal chromatin regions near genes were more stable, whereas distal regions, particularly enhancer-like elements mediated by H3K27ac and H3K4me3, exhibit higher dynamism. Sequence variations in these enhancers lead to differential gene regulation, influencing traits such as spike development. For instance, the two haplotypes of dCRE region of TaDEP-B1 resulted in significant differences in its expression and spikelet numbers. We also observed a coevolution of transcription factors and their binding sites, particularly within the expanded ERF family, which regulates spike morphology. This study highlights the interplay between sequence variation and epigenetic modifications in shaping transcriptional regulation during wheat speciation, offering valuable insights for genetic improvement.

plant biology↗

bioRxiv2024

BSReadSim: a versatile and efficient simulator to generate realistic bisulfite sequencing reads

Realistic bisulfite sequencing simulators are crucial for advancing method development in computational epigenetics. However, existing tools often fall short due to oversimplified generative models that fail to capture the complexity of real data. We present BSReadSim, an efficient and versatile simulator that generatesrealistic bisulfite sequencing reads. BSReadSim excels in integrating reference genetic variants and methylation profiles, offering unmatched versatility across multiple sequencing technologies, including WGBS, RRBS, and TBS. By accurately modeling methylation patterns, sampling biases, sequencing errors, and leveraging optimized implementation, BSReadSim efficiently generates realistic synthetic datasets tailored to specific experimental needs while maintaining computational feasibility. By enhancing the realism and flexibility of bisulfite sequencing simulations, BSReadSim supports improved experiment design, method development, and benchmarking of computational tools, ultimately advancing the reliability and rigor of DNA methylation analysis tools.

bioinformatics↗

bioRxiv2024

Unraveling Honey Bee's Waggle Dances in Natural Conditions with Video-Based Deep Learning

O_LIWild and managed honey bees, crucial pollinators for both agriculture and natural ecosystems, face challenges due to industrial agriculture and urbanization. Understanding how bee colonies utilize the landscape for foraging is essential for managing human-bee conflicts and protecting these pollinators to sustain their vital pollination services. To understand how the bees utilize their surroundings, researchers often decode bee waggle dances, which honey bee workers use to communicate navigational information of desirable food and nesting sites to their nest mates. This process is carried out manually, which is time-consuming, prone to human error and requires specialized skills. C_LIO_LIWe address this problem by introducing a novel deep learning-based pipeline that automatically detects and measures waggle runs, the core movement of the waggle dance, under natural recording conditions for the first time. We combined the capabilities of the action detector YOWOv2 and the DeepSORT tracking method, with the Principal Component Analysis to extract dancing bee bounding boxes and the angles and durations within waggle runs. C_LIO_LIThe presented pipeline works fully automatically with videos taken from wild Apis dorsata colonies in its natural environment, and can be used for any honey bee species. Comparison of our pipeline with analyses made by human experts revealed that our procedure was able to detect 93% of waggle runs on the testing dataset, with a run duration Root Mean Squared Error (RMSE) of less than a second, and a run angle RMSE of 0.14 radians. We also assessed the generalizability of our pipeline to previously unseen recording conditions, successfully detecting 50% of waggle runs performed by Apis mellifera bees from a colony managed in Tokyo, Japan. In parallel, we discovered the most appropriate values of the models hyperparameters for this task. C_LIO_LIOur study demonstrates that a deep learning-based pipeline can successfully and automatically analyze the waggle runs of Apis dorsata in natural conditions and generalize to other bee species. This approach enables precise measurement of direction and duration, enabling the study of bee foraging behavior on an unprecedented scale compared to traditional manual methods contributing to preserving biodiversity and ecosystem services. C_LI

ecology↗

bioRxiv2024

Rapid riparian ecosystem recovery in low-latitudinal North China following the end-Permian mass extinction

The greatest mass extinction at the end of the Permian, ca. 252 million years ago, led to a tropical dead zone on land and sea. The speed of recovery of life has been debated, whether fast or slow, and terrestrial ecosystems are much less understood than marine. Here, we show fast reestablishment of riparian ecosystems in low-latitude North China as little as [~]2 million years after the end-Permian mass extinction. The initial ichnoassemblages in shallow lacustrine and fluvial facies of late Smithian age are monospecific, devoid of infaunalization, with apparent size reduction. In the following Spathian, relatively complex, multi-level, structured riverain ecosystems had been rebuilt including medium-sized carnivores, plant stems, root traces, increased ichnological complexity, and significantly increased infaunalization. Specifically, burrowing behavior had re-emerged as a key life strategy not only to minimize stressful climatic conditions, but possibly to escape predation.

paleontology↗

bioRxiv2024

scTrace+: enhance the cell fate inference by integrating the lineage-tracing and multi-faceted transcriptomic similarity information

Deciphering the cell state dynamics is crucial for understanding biological processes. Single-cell lineage tracing technologies provide an effective way to track the single-cell lineages by heritable DNA barcodes, but the high missing rates of lineage barcodes and the intra-clonal heterogeneity bring great challenges for dissecting the mechanisms of cell fate decision. Here, we systematically evaluate the feature of single-cell lineage tracing data, and then develop an algorithm scTrace+ to enhance the cell dynamic traces by incorporating multi-faceted transcriptomic similarities into lineage relationships via a Kernelized Probabilistic Matrix Factorization model. We assess its feasibility and performance by conducting ablation and benchmarking experiments on multiple real datasets, and show scTrace+ can accurately predict the fates of cells. Further, scTrace+ effectively identifies some important driver genes implicated in cellular fate decision of diverse biological processes, such as the cell differentiation or the tumor drug responses.

bioinformatics↗

bioRxiv2024

High-throughput, multiplexed quantification, and sorting of single EVs at single-molecule level

We have developed a platform for the high-throughput, multiplexed, and ultra-sensitive profiling of individual extracellular vesicles (EVs) directly in plasma, which we call BDEVS - Agarose Bead-based Digital Single Molecule-Single EV Sorting. Unlike conventional approaches, BDEVS achieves single molecule sensitivity and moderate multiplexing (demonstrated 3-plex) without sacrificing the throughput (processing ten thousand of EVs per minute) necessary to resolve EVs directly in human plasma. Our platform integrates rolling circle amplification (RCA) of EV surface proteins, which are cleaved from single EVs, and amplified within agarose droplets, followed by flow cytometry-based readout and sorting, overcoming steric hindrance, non-specific binding, and the lack of quantitation of multiple proteins on EVs that have plagued earlier approaches. We evaluated the analytical capabilities of BDEVS through head-to-head comparison with gold-standard technologies, and demonstrated a [~]100x improvement in the limit of detection of EV subpopulations. We demonstrate the high throughput ([~]100k beads / minute) profiling of individual EVs for key immune markers PD-L1, CD155, and the melanoma tumor marker TYRP-1, and showed that BDEVS can precisely quantify and sort EVs, offering unprecedented resolution for analyzing tumor-immune interactions and detecting rare EV subpopulations in complex clinical specimens. We demonstrate BDEVSs potential as a transformative tool for EV-based diagnostics and therapeutic monitoring in the context of cancer immunology by analyzing plasma samples from patients with melanoma, where EV heterogeneity plays a critical role in disease progression and response to therapy. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=93 SRC="FIGDIR/small/621423v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@1a8a542org.highwire.dtl.DTLVardef@f9b9f0org.highwire.dtl.DTLVardef@11e4758org.highwire.dtl.DTLVardef@de1645_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2024

Systematic dissection of epigenetic age acceleration in normal breast tissue reveals its link to estrogen signaling and cancer risk

Breast aging encompasses intricate molecular and cellular changes that elevate cancer risk. Our study profiled DNA methylation and gene expression of 181 normal breast samples and systematically evaluated eight epigenetic clocks. We found that clocks trained using breast tissues demonstrate improved age prediction in normal breast tissue, and bias universally exists in epigenetic clocks, necessitating a proper definition of age acceleration. Cell composition analysis revealed significant age-related alterations and highlighted its distinct associations with age acceleration, including increased luminal epithelial and myoepithelial cells and reduced adipocytes and immune cells, connecting age acceleration to carcinogenesis from a cell compositional perspective. Additionally, CpG sites associated with age acceleration were enriched for estrogen receptor binding sites, providing a mechanistic link between estrogen exposure, accelerated aging, and cancer. These findings highlight the importance of cellular heterogeneity in epigenetic age estimates and the potential of age acceleration to guide for risk stratification and prevention strategies.

bioinformatics↗

bioRxiv2024

Structure elucidation, biosynthetic gene cluster distribution, and biological activities of ketomemicin analogs in Salinispora

We report three new ketomemicin pseudopeptides (1-3) from extracts of the marine actinomycete Salinispora pacifica strain CNY-498. Their constitution and relative configuration were elucidated using NMR, mass spectrometry, and quantum chemical calculations. Using GNPS molecular networking and publicly available Salinispora LCMS datasets, five additional ketomemicin analogs (4-8) were identified with ketomemicin production detected broadly across Salinispora species. The ketomemicin biosynthetic gene cluster (ktm) is highly conserved in Salinispora, occurring in 79 of 118 public genome sequences including eight of the nine named species. Outside Salinispora, ktm homologs were detected in various genera of the phylum Actinomycetota that might encode novel ketomemicin analogs. Ketomemicins 1-3 were tested against a panel of eleven proteases, with 2 displaying moderate inhibitory activity. This study describes the first report of ketomemicin production by Salinispora cultures, the distribution of the corresponding biosynthetic gene cluster, and the protease inhibitory activity of new ketomemicin derivatives. Table of Content/Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=64 SRC="FIGDIR/small/620863v1_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@481b56org.highwire.dtl.DTLVardef@1fad340org.highwire.dtl.DTLVardef@433ffaorg.highwire.dtl.DTLVardef@11d5d33_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2024

GERMIN3 plays a role in plasmodesmatal gating to regulate meristem activation related to tuberisation, tuber dormancy release and stem branching in potato

O_LIGERMIN3 has previously been identified as a target of the tuberigen activation complex suggesting a function in potato tuberisation but its role is presently unknown. C_LIO_LITo understand the role of GERMIN3 we analysed morphological, agronomic and molecular phenotypes in transgenic lines. C_LIO_LIGERMIN3 over-expressing lines of Solanum tuberosum ssp. andigena exhibited increased tuber yields under permissive conditions and enhanced tuber numbers. Post-harvest tuber sprouting exhibited reduced apical dominance with increased numbers of sprouts. Apical dominance was reduced in aerial tissues of mature plants where stem growth from axillary buds was activated. Similar results were observed in the commercial cultivar Desiree. Over-expression of GERMIN3 had no impact on the expression of SP6A, a positive regulator of tuberisation or TFL1B, a negative regulator. The GERMIN3 protein localised to the endoplasmic reticulum and transient expression in N. benthamiana leaves resulted in plasmodesmatal gating allowing intercellular transport of GFP-tagged sporamin independent of GERMIN3 oxalate oxidase activity. C_LIO_LIGERMIN3 affects tuberisation and other developmental processes by facilitating meristem activation. This identifies GERMIN3 as a novel protein associated with control of plasmodesmatal transport and supports the importance of plasmodesmatal gating in the regulation of key potato developmental processes. C_LI

plant biology↗

bioRxiv2024

MdLRR-RLK1-MdATG3 module enhances the resistance of apples to abiotic stress via autophagy

LRR-RLKs play a key role in plant responses to stress, although their physiological functions under abiotic stress are not yet fully understood. MdLRR-RLK1 was found to regulate plant growth and development and to increase tolerance to salt and drought stress. MdLRR-RLK1 interacts with MdATG3, which ubiquitinates and degrades MdLRR-RLK1. MdATG3 enhances salt and drought tolerance through autophagy, interacting with MdATG8F/I-like in apple. These findings reveal the interaction between MdLRR-RLK1 and MdATG3, suggesting mechanisms that regulate apple growth and resistance to abiotic stress.

molecular biology↗