Biology subjects

Zhou, W.

Publications and source records attributed to Zhou, W..

At least 73 records · Page 4Linked to original sources

bioRxiv2025

Computational characterization of decision making during trans-saccadic visual perception

When viewing the environment, humans execute fast sequential saccadic eye movements that disrupt the flow of visual information, yet still preserve stability in their visual percept. At the time of the saccade subjects often experience saccadic suppression of displacement - a failure to notice changes in the location of visual objects slightly shifted during the eye movement. Although well studied, the weighing of sensory information and the extent to which this integration influences visual perceptual judgments is still poorly characterized and understood. Here we used a drift diffusion modeling (DDM) framework to systematically examine the extent to which sensory information biased perceptual judgments when detecting trans-saccadic shifts of visual targets. Healthy human participants (N = 29, 20 female) completed a visual perception task in which a visual target was shifted following a cued saccadic eye movement (4o or 8o). Trans-saccadic target displacements occurred up to +2.5o along the horizontal axis, and participants reported the shift direction with a button press response. We present a version of the DDM that takes the visual error as input to simulate offsets in evidence accumulation during decision-making. The model provides an explanatory framework for the integration of sensory information, capturing the temporal dynamics of evidence accumulation that explain the range of perceptual biasing and response timing effects observed across participants.

neuroscience↗

bioRxiv2025

Multi-platform framework for mapping somatic retrotransposition in human tissues

Mobile element insertions (MEI) shape the human genome in both germline and somatic tissues. While inherited MEIs are well characterized, mapping somatic MEIs (sMEI) in non-cancer tissues remains challenging due to their low allelic fraction and repetitive nature. We established an integrative framework for sMEI analysis leveraging modern sequencing technologies and analytical innovations. We first benchmarked sMEI detection and demonstrated advantages of long-read and MEI-targeted sequencing for ultra-low-frequency events using a mixture of well-established cell lines. We then showed that haplotype phasing and donor-specific assemblies refine sMEI detection, effectively distinguishing from germline and false signals in in-silico tumor-normal mixtures. We further developed a source-tracing strategy based on internal sequence variation, expanding the catalogue of active source elements beyond traditional transduction-based methods. Applying this framework to donor tissues, we identified 18 rare somatic L1 insertions, revealing structural and source diversity. Our work provides a foundational framework and biological insight into sMEIs.

genomics↗

bioRxiv2025

Pocket-based molecule generation with an SE(3)-equivariant language model leads to a potent and selective HPK1 inhibitor with in vivo efficacy

Deep learning shows promise in structure-based drug discovery, yet challenges persist in generating pharmacologically plausible molecules with valid 3D conformation and decent binding mode in the pocket. We introduce SE3-BiLingoMol, an SE(3)-equivariant Transformer for pocket-based 3D molecule generation, addressing two key limitations of existing language-model approaches. First, it uses Geometric Algebra Transformers for SE(3)-equivariant handling of continuous 3D coordinates. Second, a bidirectional attention mechanism mitigates conformational errors accumulated during autoregressive sampling. These innovations enable SE3-BiLingoMol to generate 2D drug-like, 3D geometrically valid molecules with superior binding modes. Validated on DUD-E dataset containing over 100 targets, the model achieved state-of-the-art performance in de novo design and optimization. We applied SE3-BiLingoMol to design potent and selective inhibitors for HPK1, a promising immunotherapy target. Through an iterative human-AI workflow, integrating AI generation with experimental validations (X-ray crystallography, bioassays), we identified Cmpd. 6. This novel tetracyclic compound demonstrates potent HPK1 inhibition, excellent cellular activity, favorable pharmacokinetics, and robust anti-tumor in vivo efficacy as monotherapy and with PD-1 blockade. Our work establishes a sophisticated generative AI framework for 3D molecule design and demonstrates its application in developing cancer immunotherapy. Highlights[bullet] SE(3)-Equivariant Language Model for Molecule Generation: We introduce a dual-channel SE(3)-equivariant language model that supports de novo molecule design and optimization, addressing key challenges in prior language model-based 3D molecule generation approaches. [bullet]Discovery of Potent HPK1 Inhibitors: Application of this model led to the discovery of highly selective HPK1 inhibitors with robust in vivo efficacy, resulting in a promising lead compound. [bullet]AI-Guided Rational Drug Development Paradigm: This work establishes a paradigm for AI-guided rational drug development, showcasing AI as a "co-pilot" that inspires drug designers with novel ideas in an "evidence-based context".

bioinformatics↗

bioRxiv2025

Conserved lipid metabolic reprogramming confers hypoxic and aging resilience

The Arctic ground squirrel (AGS, Urocitellus parryii), an extreme hibernator, exhibits remarkable resilience to stressors like hypoxia and hypothermia, making it an ideal model for studying cellular metabolic adaptation. The underlying mechanisms of AGS resilience are largely unknown. Here, we use lipidomic and metabolomic profiling to discover specific downregulation of triglyceride lipids and upregulation of the lipid biosynthetic precursor malonic acid in AGS neural stem cells (NSC) versus murine NSCs. Inhibiting lipid biosynthesis recapitulates hypoxic resilience of squirrel NSCs. Extending this model, we find that acute exposure to hypoxia downregulates key lipid biosynthetic enzymes in C. elegans, while inhibiting lipid biosynthesis reduces mitochondrial fission and facilitates hypoxic survival. Moreover, inhibiting lipid biosynthesis protects against APOE4-induced pathologies and aging trajectories in C. elegans. These findings suggest triglyceride downregulation as a conserved metabolic resilience mechanism, offering insights into protective strategies for neural tissues under hypoxic or ischemic conditions, APOE4-induced pathologies and aging.

physiology↗

bioRxiv2025

An Anterior Cingulate Cortex Neuronal Ensemble Controls Contextual Opioid Analgesic Tolerance

Opioids are first-line treatments for pain; however, tolerance leads to decreased efficacy and escalated dosing, increasing the risk of opioid use disorder and overdose. Despite well-established cellular and molecular adaptations, opioid analgesic tolerance can be rapidly reversed in settings where these drugs are not expected. The specific neuronal populations that orchestrate this expectation-based tolerance are not known. In this study, we used a contextual tolerance training method, whole-brain clearing, and immunostaining to identify brain regions involved in contextual tolerance and to pinpoint a neuronal ensemble in the anterior cingulate cortex (ACC) that is activated by contextual analgesic tolerance. We observed that calcium activity in principal neurons of the ACC is suppressed by fentanyl in opioid-naive mice and during contextual reversal, but not during contextual tolerance. Chemogenetic silencing of the ACC induced analgesic tolerance reversal in the opioid-associated context without affecting thermal nociception in opioid-free mice. Conversely, chemogenetic activation of the ACC contextual tolerance-active neuronal ensemble triggered analgesic tolerance in an unassociated context. This research highlights the role of ACC neuronal ensembles in mediating expectation-driven, contextual opioid analgesic tolerance without affecting basal nociception. Modulating ACC activity could provide a promising strategy to improve pain relief while maintaining the essential ability to detect harmful stimuli.

neuroscience↗

bioRxiv2025

Unveiling the Role of PHF20 in TBC1D4-Mediated Glucose Uptake During Toxoplasma gondii Infection

BackgroundToxoplasma gondii relies on host cell nutrients, especially glucose, to support its intracellular growth. However, the mechanisms by which it enhances host glucose metabolism remain incompletely understood. MethodsWe used fluorescence-based glucose uptake assays, flow cytometry, metabolic flux analysis, and gene silencing in ARPE-19 cells, along with transgenic mouse models, to explore how T. gondii manipulates host glucose utilization and whether this promotes parasite proliferation. ResultsT. gondii infection significantly enhanced host glucose uptake in a dose-dependent manner and promoted GLUT4 translocation to the plasma membrane. Notably, extracellular acidification rate (ECAR) assays demonstrated a marked increase in glycolytic activity following infection. Mechanistically, we identified that the PI3K/AKT signaling pathway mediates the phosphorylation and transcriptional upregulation of TBC1D4, a Rab-GAP protein essential for GLUT4 trafficking. Genetic silencing of TBC1D4 impaired both glucose uptake and parasite replication. Furthermore, we uncovered a regulatory mechanism involving AKT-dependent nuclear signaling that modulates TBC1D4 transcription. In vivo experiments using Phf20 transgenic mice confirmed increased susceptibility to T. gondii and elevated glucose metabolic responses. ConclusionsOur study reveals that T. gondii hijacks a host PI3K/AKT-TBC1D4 axis to enhance glucose uptake and glycolysis, thereby ensuring metabolic support for its proliferation. These findings highlight host glucose metabolism as a potential therapeutic target for controlling toxoplasmosis.

cell biology↗

bioRxiv2025

Construction of an engineered Escherichia coli with enhanced intestinal colonization and anti-inflammatory efficacy in colitis

Engineered probiotics are considered as effective and safe therapeutic strategies for the treatment of various diseases. Escherichia coli Nissle 1917 (EcN) has been widely used as a chassis strain for its safety and well-established genetic manipulation system. The limited intestinal colonization ability of EcN hampers its potential as a chassis for constructing synthetic probiotics in therapeutic applications. Here, an engineered EcN strain with high gastric acid and bile salts tolerance as well as enhanced intestinal adhesion ability was constructed by improving the expression of gastric acid and bile salts tolerance-associated genes and strengthening the expression of curli fiber formation genes, respectively. Meanwhile, oral administration of this engineered strain to colitis mice alleviated the disease severity and restored the disordered gut microbiome by decreasing the abundance of Escherichia-Shigella, whereas increasing norank_f_Muribaculaceae. We engineered EcN to improve its probiotic properties and anti-colitis efficacy, thereby establishing a platform for precision-designed synthetic probiotics.

microbiology↗

bioRxiv2025

SimSpace: a comprehensive in-silico spatial omics data simulation framework

Spatial omics technologies provide rich measurements of molecular states in their native tissue context, but the development and benchmarking of computational methods remain constrained by limited access to datasets with known ground truth. We present SimSpace, a flexible framework for simulating spatial omics data for method development, stress-testing, and controlled in silico experiments. SimSpace uses a hierarchical generative model that couples tissue-scale spatial organization, local cell-type interactions, and modular omics-profile generation. Its Markov random field-based spatial model enables controllable simulation of niche structure, cell-type co-localization, phenotype-dependent density, and spatially mediated molecular interactions. SimSpace supports both reference-free simulations under user-defined generative assumptions and reference-guided simulations that calibrate spatial parameters to real datasets while generating new spatial realizations. Across Xenium, MERFISH, and CODEX examples, SimSpace reproduced multiple evaluated spatial statistics, preserved key domain-level structure in reference-guided settings, and supported benchmarking of cell-type deconvolution and spatially variable gene detection methods. We further show that inferred interaction parameters can be perturbed to generate interpretable counterfactual spatial proteomics scenarios. SimSpace is implemented as an open-source Python package with reproducible workflows for rigorous benchmarking and methodological development in spatial omics.

bioinformatics↗

bioRxiv2025

The Inaugural Flatiron Institute Cryo-EM Conformational Heterogeneity Challenge

Despite the rise of single particle cryo-electron microscopy (cryo-EM) as a premier method for resolving macromolecular structures at atomic resolution, methods to address molecular heterogeneity in vitrified samples have yet to reach maturity. With an increasing number of new methods to analyze the multitude of heterogeneous states captured in single particle images, a systematic approach to validation in this field is needed. With this motivation, we issued a challenge to the community to analyze two cryo-EM particle image sets of thyroglobulin that exhibit continuous conformational heterogeneity. The first dataset was experimental and the second was generated with a simulator, allowing control over the distribution of molecular structures and enabled direct comparison between participants submissions and the ground truth molecular structures and distributions. Participants were asked to submit 80 volumes representing the heterogeneous ensemble and estimate their respective populations in the image sets provided. Participation of the research community in the challenge was strong, with submissions from nearly all developers of heterogeneity methods, resulting in 41 submissions across both datasets. Submissions qualitatively exceeded expectations, with the molecular motions identified by methods resembling both each other and the ground truth motion. However, quantitatively assessing these similarities was a challenge in and of itself. In the process of assessing the submissions, we developed several validation metrics, most of which require reference to the underlying ground truth volumes. However, we have also explored the use of metrics that do not necessarily reference ground truth. This is particularly apt for experimental datasets where ground truth is inaccessible. These approaches allowed us to assess the similarity and accuracy in volume quality, molecular motions, and conformational distribution of di!erent submissions. These metrics and the e!orts of all participants help chart a path forward for the improvements of heterogeneity methods for cryo-EM and for future challenges to validate these new methods as they continue to be developed by the community.

biophysics↗

bioRxiv2025

Correlation Analysis of Breast Cancer Molecular Characteristics and Epithelial-Mesenchymal Transition in Circulating Tumor Cells: Based on Clinical Cases

BackgroundThis study aimed to investigate the correlation between epithelial-mesenchymal transition (EMT) in circulating tumor cells (CTCs) from peripheral blood and molecular characteristics of breast cancer. MethodsWe enrolled 48 breast cancer patients who underwent CTC testing at Shenzhen Peoples Hospitals Breast Surgery Department between September 2022 and May 2024. Intraoperative tissue samples underwent routine pathological and immunohistochemical examination. CTCs were detected using Canpatrol technology. Clinical data were analyzed statistically using SPSS 27.0. Categorical data were presented as percentages/frequencies. Comparisons used chi-square tests, with Yates correction for expected frequencies <5 but [≥]1. Statistical significance was set at P<0.05 (=0.05). ResultsEMT status showed no significant differences between ER-positive/negative, PR-positive/negative, HER2-positive/negative, Ki-67 [≥]14%/<14%, tumor size, or lymph node metastasis groups (P>0.05). Luminal-type tumors exhibited lower EMT grades than other subtypes, while triple-negative breast cancer (TNBC) showed higher EMT grades (P<0.05). ConclusionEMT grade correlates with luminal-type and TNBC subtypes, suggesting predictive value for these breast cancer classifications.

cancer biology↗

bioRxiv2025

Revisiting the Fungal ITS2 Sequencing Data from the Human Microbiome Project

While the Human Microbiome Project (HMP) significantly advanced our understanding of the human microbiome, our revisiting of its fecal ITS2 sequencing data reveals two significant issues. First, technical variations in sequencing or data processing introduce batch effects in downstream analyses. Second, we discovered a mismatch between the reported and actual amplification primers, which requires careful consideration when interpreting, reusing, or referencing HMP ITS2 data and methodology.

bioinformatics↗

bioRxiv2025

Spatial joint profiling of DNA methylome and transcriptome in mammalian tissues

The spatial resolution of omics dynamics is fundamental to understanding tissue biology. Spatial profiling of DNA methylation, which is a canonical epigenetic mark extensively implicated in transcriptional regulation, remains an unmet demand. Here, we introduce a method for whole genome spatial co-profiling of DNA methylation and transcriptome of the same tissue section at near single-cell resolution. Applying this technology to mouse embryogenesis and postnatal brain resulted in rich DNA-RNA bimodal tissue maps. These maps revealed the spatial context of known methylation biology and its interplay with gene expression. The two modalities concordance and distinction in spatial patterns highlighted a synergistic molecular definition of cell identity in spatial programming of mammalian development and brain function. By integrating spatial maps of mouse embryos at two different developmental stages, we reconstructed the dynamics of both epigenome and transcriptome underlying mammalian embryogenesis, revealing details in sequence, cell type, and region-specific methylation-mediated transcriptional regulation. This method extends the scope of spatial omics to DNA cytosine methylation for a more comprehensive understanding of tissue biology over development and disease.

genomics↗

bioRxiv2025

Evolutionary implications of stipule occurrence in Permo-Carboniferous wetland forests dominated by Psaroniaceae

Stipules are specialized appendages borne at the leaf base with roles as diverse as sheltering of delicate growing tissues from environmental exposure, vegetative propagation and dispersal, and modification into climbing hooks or protective spines. Stipules are widely present in extant vascular plants, but their origins in geological history remain obscure and must have involved convergent evolution more than once, perhaps as early as the late Paleozoic emergence of forested terrestrial ecosystems. Based on extraordinary collections from the early Permian Wuda Tuff Flora, the earliest known stipule structure in the plant kingdom has been identified in marattialean tree ferns Psaroniaceae, the dominant element of Permo-Carboniferous wetland forests. Psaroniaceous stipules are consistent with protection of juvenile fronds and the stem apex as well as retention of a functional role in mature and withered fronds. Furthermore, the continued and perhaps indeterminate growth and the fully laminated stipules invite speculation of a potential role in vegetative propagation following detachment from the parent frond. However, no direct fossil evidence of stipules acting as vegetative propagules is currently available.

paleontology↗

bioRxiv2025

MultiAlloDriver: a multi-model method to predict and identify cancer driver mutations

A minority of driver mutations in cancer significantly alter protein structure and key functionalities, thereby driving cancer progression. Consequently, the prediction and identification of driver mutations hold critical implications for targeted cancer therapy. This study introduces MultiAlloDriver, a novel multi-modal machine learning model based on an attention mechanism, which for the first time, incorporates protein surface information. By integrating information from three dimensions-protein sequence, structure, and surface-the model achieves high-accuracy driver target prediction with an accuracy exceeding 93%. Notably, we utilized this tool to predict and identify the driver effect of the F90S mutation in the PTEN tumor suppressor gene, uncovering mutations associated with cancer signaling mechanisms. Overall, MultiAlloDriver contributes to elucidating the underlying mechanisms of cancer development and progression, providing a robust framework for the identification of driver targets.

bioinformatics↗

bioRxiv2025

CRISPR RiPCA for Investigating eIF4E-m7GpppX Capped mRNA Interactions

Post-transcriptional modifications expand the information encoded by an mRNA. These dynamic and reversible modifications are specifically recognized by reader RNA-binding proteins (RBPs), which mediate the regulation of gene expression, RNA processing, localization, stability, and translation. Given their crucial functions, any disruptions in the normal activity of these readers can have significant implications for cellular health. Consequently, the dysregulation of these RBPs has been associated with neurodegenerative disorders, cancers, and viral infections. Therefore, there has been growing interest in targeting reader RBPs as a potential therapeutic strategy since developing molecules that restore proper RNA processing and function may offer a promising avenue for treating diseases. In this work, we coupled our previously established live-cell RNA-protein interaction (RPI) assay, RNA interaction with Protein-mediated Complementation Assay (RiPCA), with CRISPR technology to build a new platform, CRISPR RiPCA. As a model for development, we utilized the interaction of eukaryotic translation initiation factor 4E (eIF4E), a reader RBP that binds to the m7GpppX cap present at the 5' terminus of coding mRNAs, with an m7G capped RNA substrate. Using eIF4E CRISPR RiPCA, we demonstrate our technologys potential for measuring on-target activity of inhibitors of the eIF4E RPI of relevance to cancer drug discovery.

cell biology↗

bioRxiv2025

Multimodal Validation of the Existence of Transitional Cerebellar Progenitors in the Human Fetal Cerebellum

The developing human cerebellum comprises a series of transient progenitor states that are essential for generating diverse neural subtypes, yet the identity and validation of intermediate cell populations bridging stem-like and lineage-committed neuronal precursors remain limited. In our previous single-cell transcriptomic study, we identified a distinct transitional cerebellar progenitor (TCP) population enriched in specific progenitor zones such as the rhombic lip during human fetal cerebellar development. To address the concerns raised in the Matters Arising regarding the existence of the TCP cells, we provide additional multimodal validations of this population. Rigorous reanalysis of our single-cell transcriptomic data, applying stringent quality control measures, validated the quality of TCP cells and their classification as a transcriptionally distinct population. Multiple orthogonal validations of TCP signature genes (SOX11 and HNRNPH1) using RNAscope in situ hybridization, Xenium-based spatial transcriptomics, and immunohistochemistry on additional fetal cerebellar samples across different stages demonstrated the consistent presence of TCPs in the rhombic lip, transitioning from PRTG+ stem-like zones in the ventricular zone at early developmental stages to the subventricular zone overlapping with EOMES+ unipolar brush cell precursors at later stages. TCP-like populations were also independently identified in two fetal cerebellar single-nucleus transcriptomic atlases, and their gene signature was enriched in a cell population associated with aggressive medulloblastomas. Collectively, these multimodal validations confirm the existence of a transitional progenitor population in the human fetal cerebellum, with implications for cerebellar lineage progression and medulloblastoma origin.

developmental biology↗

bioRxiv2025

Functional analysis of gene family evolution demonstrates expansion of digestive, immunity and olfactory functions in the black soldier fly (Hermetia illucens) lineage

Structural variants such as chromosomal rearrangements and gene duplications can play an important role in the adaptation and diversification of organisms. Here, we used comparative genomics to study the functional implications of structural variants across two families of flies. We compared the reference genomes of eight Asilidae species and six Stratiomyidae species, including the black soldier fly (Hermetia illucens), a species with an ability to convert organic waste into biomass and a recently expanded global range. The genomes of Stratiomyidae are generally larger than Asilidae and contain a higher proportion of transposable elements, many of which are recently expanded. Gene families showing more gene duplications are enriched for life history related functions such as metabolism in Stratiomyidae and proteolysis and longevity in Asilidae. Gene families showing more gene duplications that are specific to H. illucens are mostly related to olfactory and immune responses, while across the Stratiomyidae there is enrichment of digestive and metabolic functions such as proteolysis. Together, our results shed light on gene family expansions that have likely played a role in the ecological success of the black soldier fly.

genomics↗

bioRxiv2025

Mechanism of age-related accumulation of mitochondrial DNA mutations in human blood

One of the strongest signatures of aging is an accumulation of mutant mitochondrial DNA (mtDNA) heteroplasmy. Here we investigate the mechanism underlying this phenomenon by calling mtDNA sequence, abundance, and heteroplasmic variation in human blood using whole genome sequences from [~]750,000 individuals. Our analyses reveal a simple, two-step mechanism: first, individual cells randomly accumulate low levels of "cryptic" mtDNA mutations; then, when a cell clone proliferates, the cryptic mtDNA variants are carried as passenger mutations and become detectable in whole blood. Four lines of evidence support this model: (1) the mutational spectrum of age-accumulating mtDNA variants is consistent with a well-established model of mtDNA replication errors, (2) these mutations are found primarily at low levels of heteroplasmy and do not show evidence of positive selection, (3) high mtDNA mutation burden tends to co-occur in samples harboring somatic driver mutations for clonal hematopoiesis (CH), and (4) nuclear GWAS reveals that germline variants predisposing to CH (such as those near TERT, TCL1A, and SMC4) also increase mtDNA mutation burden. We propose that the high copy number and high mutation rate of mtDNA make it a particularly sensitive blood-based marker of CH. Importantly, our work helps to mechanistically unify three prominent signatures of aging: common germline variants in TERT, clonal hematopoiesis, and observed mtDNA mutation accrual.

genetics↗