Biology subjects

Zhang, G.

Publications and source records attributed to Zhang, G..

At least 91 records · Page 5Linked to original sources

bioRxiv2025

Microglial MyD88-dependent signaling influences extracellular matrix development and interneuron maturation in the hippocampus

Parvalbumin interneurons (PVIs) are disrupted across diverse neurodevelopmental disorders, highlighting their vulnerability to developmental perturbations. Inflammation can perturb PVI development and function, and inflammatory mechanisms are often propagated within the brain by microglia. Yet the microglial mechanisms linking inflammatory signals to interneuron development are unclear. To test the role of microglial innate immune signaling in PVI development, we used mice lacking toll-like receptor adaptor MyD88 specifically in microglia. MyD88-deficient microglia showed reduced inflammatory responses but increased early-life phagocytosis of inhibitory synaptic material. In adulthood, males without microglial MyD88 exhibited increased hippocampal PVI density, increased extracellular matrix (ECM) deposition, increased inhibitory signaling, and impaired discrimination behaviors. We determined the cytokine interleukin (IL)-33, which normally drives adult microglial remodeling of the ECM, is developmentally regulated in the hippocampus. MyD88-deficient microglia fail to respond to IL-33, leading to reduced remodeling of the ECM component aggrecan. These results reveal microglial immune signaling via MyD88 regulates hippocampal inhibitory circuit development in a sex-specific manner.

neuroscience↗

bioRxiv2025

Caenorhabditis briggsae ancestral genomic hyper-diversity contrasts with globally distributed genome-wide haplotypes

Comparative genomics provides a powerful framework to uncover the molecular and evolutionary mechanisms that shape genetic diversity within and across species, revealing how shared and lineage-specific processes influence their evolutionary trajectories through time. The nematode Caenorhabditis briggsae is distributed world-wide and is a comparative model to Caenorhabditis elegans in the biology of development, cellular mechanisms, neurobiology, genetic mappings of complex traits, and genome evolution. Following massive collection efforts by the nematode research community, we present the isolation of over 2,000 wild strains and analyses of genome sequences that catalog over six million single-nucleotide and insertion-deletion variants. This genome and strain resource provide a powerful means to interrogate the causal genetic bases of phenotypic variation for diverse traits. Additionally, we describe its global population structure and discover new and genetically distinct groups within this primarily self-fertilizing species, including groups of highly related strains that were sampled across different continents. We leverage expansive genetic variation to decipher the effects of linkage and selection on the distribution of genetic diversity across the genome and across geographic regions. Within the species, we find genomic regions with extremely high levels of genetic variation similar to hyper-divergent regions found in C. elegans and other species. These regions harbor new genes and variation enriched for environmental sensing and pathogen responses. In comparison to the outbreeding sister species Caenorhabditis nigoni, we conclude that long-term balancing selection has maintained substantial functional variation since the divergence from their outbreeding ancestor, likely in response to differences in the ecological niche. Overall, this massive strain resource enables future comparative genetics and genomics studies, including genome-wide association studies between Caenorhabditis species.

genomics↗

bioRxiv2025

Relative contribution of gonads and sex chromosomes to sex differences in cell-type gene expression in the mouse medial septum and sex-biased disease risk

BackgroundWhile sex differences in the brain have traditionally been attributed to gonadal hormones, emerging evidence points to regulation by sex chromosomes. This study aims to differentiate the influence of gonads versus sex chromosomes on cellular gene expression in the mouse medial septum (MS), a critically understudied brain region. MethodsUsing single nucleus RNA-sequencing and the Sex Chromosome Trisomy mouse model, we (1) quantified sex differences in cellular gene expression and (2) isolated sex-biasing effects by identifying perturbed cell types, differentially expressed genes, biological pathways, and gene networks, which were integrated with GWAS data to explore links with sex-biased human phenotypes. ResultsOur analysis revealed that volumetric sex differences in the MS are mirrored by widespread transcriptomic changes across cell types. Critically, genetic effects displayed elevated relevance compared to sex hormones in driving sex-biased gene expression. These effects converge to regulate synaptic/neuronal development, transcriptional regulation, and cellular metabolism. Sex chromosome-associated DEGs were enriched for various human disorders, suggesting a cellular and mechanistic basis for their sex-biased patterns. ConclusionsOur findings challenge the classical gonad-centric views of sexual differentiation, as the MS displays sex-biased transcriptional regulation driven by sex chromosome-associated effects that are highly relevant for human health.

neuroscience↗

bioRxiv2025

EMCF ecosystem: Towards pretrained foundation model for electron microscopy image analysis

Volume electron microscopy (vEM) enables nanoscale visualization of three-dimensional (3D) cellular ultrastructure, providing critical insights into physiological processes and pathological alterations. However, its application to large-scale biological tissues remains constrained by two major bottlenecks: prolonged image acquisition and inefficient data processing. Here, we present EMCF ecosystem (EMCFsys), an integrated ecosystem designed to overcome these challenges through three key components: a large-scale benchmark dataset (EMCFD) comprising 4,002,802 high-quality images across 14 EM modalities and 6 biological kingdoms; a foundation image restoration model (EMCellFiner); and a scalable image analysis foundation model (EMCellFound). Together, these modules systematically enhance image quality and substantially improve analysis efficiency. Our results show that EMCellFiner outperforms specialist models in restoring degraded images, even surpassing original ground truth sharpness in certain artifact regions, and reduces imaging time by 16-fold by enabling low-resolution and low dwell time acquisition. EMCellFound exhibits exceptional feature discriminability, outperforms specialist models in classification, semantic segmentation and instance segmentation. It also enables high-precision 3D reconstruction of organelles (e.g., endoplasmic reticulum) with minimal labeled data (0.01% of total volume). We validated the EMCFsys on unseen datasets across diverse biological contexts and imaging platforms. By publicly releasing both the dataset and models, we establish a scalable paradigm for automated, high-throughput vEM data interpretation, accelerating exploration of lifes nanoscale structure and function across biology.

cell biology↗

bioRxiv2025

Enhancer/Enhanceosome/Super-enhancer and the promoter-proximate RNA Polymerase II (Pol II) pausing are coupled

Virus infection triggers the expression of IFN-x{beta}, which requires at least four groups of transcription factors and p300/CBP to form an enhanceosome. The promoter-proximal Pol II pausing regulation in metazoans includes the recruitment of CDK9 by JMJD6 and BRD4, the generation of a unique phosphorylation pattern of CTD of Pol II, the recruitment of JMJD5, and the cleavage of arginine methylated histone tails on the +1 nucleosome. We find that both BRD4 and p300/CBP control the activity of CDK9. It is likely that the BRD4 docking site on nucleosomes is generated by p300/CBP. We conclude that enhancer/enhanceosome/super-enhancer and Pol II pausing regulation are coupled and could be the unique universal mechanism that differentiates animals from unicellular organisms.

biochemistry↗

bioRxiv2025

Amyloid-mediated RNA uptake by sperm for embryonic delivery

Seminal fluid RNA is essential for embryonic development, but the mechanism by which extracellular RNA is transferred from seminal fluid to sperm remains unclear. Here, we identify a role for functional amyloid fibrils in seminal fluid that bind and traffic RNA to mammalian sperm and, upon fertilization, the zygote. We show that highly cationic peptides in seminal fluid phase separate with RNA to form amyloid fibrils. Cryo-electron tomography reveals that these amyloid fibrils are internalized by sperm. Furthermore, biophysical and in vitro fertilization experiments show that amyloid-bound RNA reaches the zygote where molecular chaperones control release of RNA for translation. Our work uncovers a mechanism for RNA trafficking from seminal fluid to the zygote, establishing amyloid fibrils as potential tools for RNA delivery during fertilization.

biophysics↗

bioRxiv2025

Revealing the antibiotic resistome in the global hadal trenches by large-scale cultivation and metagenomics

The global hadal trenches that reside more than 6000 meters below the sea level, represent one of Earths most remote ecosystems, potentially harboring a microbial reservoir for antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs). However, the global hadal environments remain the least investigated ecosystem for ARB/ARG compositions and distribution. This study took three-fold approaches to investigate the ARB/ARGs in the global hadal trench sediments, i.e., large-scale cultivation to isolate and verify ARB/ARGs from Challenger Deep sediments, metagenomic analysis of sediment samples from Challenger Deep over a six-year period, and comparative study of resistomes across six hadal trenches through metagenomic analysis. The Challenger Deep sediments had a consistent average ARG abundance of 0.02 copy/cell over a six-year period, whereas some ARG subtypes fluctuated and showed distinct temporal dynamics. Large-scale screening of ARB via microbial cultivation using 13 classes of antibiotics led to enriching distinct ARB, for which eleven genera were identified by metagenomic sequencing as major host for ARGs. The global hadal trench sediments showed a variable ARG abundance, which was significantly lower than those from environments in proximity to human activities, representing a relatively pristine reservoir. Phylogenetic analysis suggested the hadal ARGs underwent niche-specific selections and formed hadal trench-specific clusters that diverged from human-associated lineages, which can be outward transported when disturbed. The study established the hadal trench sediments, as a relatively pristine reservoir of natural ARGs, providing a crucial environmental baseline for assessing their impacts on the ecosystems and public health risks.

microbiology↗

bioRxiv2025

Rapid robust high-fidelity 3D neuronal extraction from multi-view projections

Recent developments in imaging facilitate large-scale three-dimensional (3D) neuronal recording. While these huge amounts of data shed new light on population-level neural coding, it is much harder to extract neuronal calcium dynamics from 3D volumes than 2D images with the existence of noise and scattering. Here, we presented DeepWonder3D, a general end-to- end pipeline for rapid and robust 3D neuronal extraction with high fidelity. Instead of processing voxel by voxel, DeepWonder3D works on the multi-view projections of 3D imaging data obtained either digitally or optically through specific point spread functions (PSFs) for general applicability to diverse techniques, including point-scanning microscopy, light- field microscopy, and two-photon synthetic aperture microscopy. Integrating denoising, resolution registration, background removal, neuronal extraction, and multi-view fusion into a unified pipeline tailored for large-scale high-resolution datasets contaminated by noise and scattering, DeepWonder3D outperforms state-of-the-art methods in 3D localization accuracy with a 10-fold reduction in computational costs, validated by numerical simulations and a hybrid two-photon/light-field imaging system. With the RUSH3D mesoscope, DeepWonder3D achieves rapid high-fidelity 3D calcium extraction of tens of thousands of neurons across the mouse cortex within hours.

neuroscience↗

bioRxiv2025

Cell State Chaos Underpins the Evolution of SMARCA4-Deficient Dedifferentiated Endometrial Cancer

Dedifferentiated endometrial carcinoma (DDEC) is a histologically unique cancer type, wherein well-differentiated regions lie adjacent to morphologically distinct, high-grade lesions that are histologically undifferentiated. Previous studies have determined that in nearly half of the cases dedifferentiation is associated with the genomic inactivation of SMARCA4, a catalytic subunit belonging to the SWI/SNF chromatin remodelling complex (SWI/SNF CRC), suggesting that SMARCA4 loss causes dedifferentiation. Herein, using gene editing, we reveal that when serially passaged in mice, SMARCA4-deficient endometrial cancer cells repeatably and predictably generate heterogeneous admixtures of differentiated and undifferentiated cells, resembling human DDEC. Surprisingly, despite this metamorphosis, SMARCA4 loss does not induce lineage plasticity nor reprogramming to a less differentiated fate. Rather, single-cell sequencing combined with barcoding demonstrated that SMARCA4 loss induces a dysregulated epigenome that allows cells to randomly move through cellular states that are otherwise shared with SMARCA4-expressing well-differentiated cancer cells. This finding was validated using a cohort of patient samples, such that epithelial fate markers (E-CADHERIN) can be detected in morphologically undifferentiated cells. Collectively, this work constitutes the first repeatable model of human dedifferentiated cancer and suggests that histological dedifferentiation is not due to the acquisition of a stem cell-like fate. Rather, undifferentiated tissue emerges due to epigenomic dysfunction concomitant with the arbitrary movement of cancer cells between cellular states.

cancer biology↗

bioRxiv2025

Integron-associated structures underlie the accumulation of antibiotic resistance genes on plasmids beyond cassette arrays

Rising multidrug-resistant (MDR) bacteria threatens global public health. While antibiotic selection preserves MDR plasmids, how mobile genetic elements (MGEs) drive the antibiotic resistance gene (ARG) accumulation to form complex plasmid architectures remain elusive. Here, we demonstrate that MDR plasmid evolution follows a hierarchical scheme, where progressive combinations of integrons, IS26, and ISCR elements drive stepwise increases in ARG load. The combination of all these three MGEs were significantly linked to the highest ARG load on plasmids. In the presence of integrons or ISCR elements, ARG numbers in plasmids are strongly and positively correlated with IS26 copy numbers. Such correlations were further validated by Escherichia coli plasmids collected from human and pig wastewater. We propose an integron-IS26-ISCR (3I) framework with four MDR plasmid evolutionary stages of increasing ARG accumulation potential. The "3I" framework refines predictions of MDR plasmid emergence and spread, providing universal genetic markers for cost-effective surveillance.

microbiology↗

bioRxiv2025

High-throughput phenomics of global ant biodiversity

The big data era in biology is underway, but the study of organismal form has been slow to capitalize on advances in imaging and computation. Modern imaging can digitize whole organisms, but low throughput has limited the effort to document morphological diversity. Within the open science initiative Antscan, we applied high-throughput synchrotron X-ray microtomography to capture phenotypes across a diverse and ecologically dominant insect group -- ants. We provide 2193 whole-body 3D ant datasets from 792 species to broadly cover the ant phylogeny with a global scope, also pairing phenomic data with genome sequencing projects. Scans acquired with standardized parameters facilitate automated analysis and free access to data can broaden the audience and incentivize methods development. Antscan presents a scalable approach to create libraries of diverse anatomies, heralding a new era of studies on the evolution, structure, and function of organismal phenotypes.

zoology↗

bioRxiv2025

Sequence-aware Prediction of Point Mutation-induced Effects on Protein-Protein Binding Affinity using Deep Learning

Amino acid mutations may lead to significant changes in the binding affinity of protein complexes, thereby causing a series of cellular dysfunctions. Therefore, accurate prediction of protein-protein binding affinity changes ({Delta}{Delta}G) induced by amino acid mutations is of great importance for understanding protein-protein interactions (PPIs). In this study, we propose SAMAffinity, a protein sequence-aware deep learning architecture for predicting changes in protein-protein binding affinity caused by amino acid mutations. SAMAffinity predicts mutation-induced {Delta}{Delta}G by integrating multi-source sequence features, leveraging a Mutation-Site Identification (MSI) module to highlight local semantic shifts and a Binding-Interface Awareness (BIA) module to capture interaction changes. Benchmark evaluations on public datasets show that under the mutation-level data splitting strategy, SAMAffinity outperforms the state-of-the-art sequence-based method AttABseq by 33.3%, 72.3%, 31.8%, and 30.5% on S1131, S4169, S645, and M1101 datasets, respectively. Moreover, under the complex-level data splitting strategy, SAMAffinity surpasses the structure-based method MpbPPI by 22.9%, 22.7%, 5.0%, and 11.4% on the corresponding datasets. Beyond predictive accuracy, the strong consistency between the models predicted distribution and natural amino-acid mutation tendencies indicates that SAMAffinity effectively captures the underlying mutational landscape shaped by intrinsic biochemical and evolutionary factors. Based on this capability, SAMAffinity demonstrated strong generalization in a study of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cases, suggesting its potential for optimizing therapeutic antibody design.

bioinformatics↗

bioRxiv2025

Context-specific configuration of orthogonal integrator dynamics for flexible foraging decisions

The capacity to adapt behavior and cognition across contexts is fundamental to intelligence. Context-dependent decision making is an exemplar of flexible cognition in animals, yet its biological basis remains poorly understood. At the neural level, a critical mechanistic question is whether context largely alters the inputs to a common decision process or reconfigures decision activity itself to create context-specific functional modes. To study this problem, we developed a patch foraging task in which mice forage in two environment contexts defined by distinct reward dynamics. Mice made patch leaving decisions across environments using different context-specific parameterizations of a drift-diffusion integrator process. Using high-density acute and chronic neural recordings, we find that foraging environments recruit separate activity subspaces which organize orthogonal coding of context-specific decision variables. Unlike the context-invariant decision coding used for perceptual choice problems, foraging decision variables were encoded in orthogonal population vectors within largely separate neural subpopulations - a subspace configuration mechanism which can support modular learning, independent readout, and flexible toggling of decision strategies across environments. In the dorsal frontal cortex, orthogonal integrators emerge with experience, are preserved across three distinct task settings, and are required for rapid and volitional strategy switching. Our findings establish orthogonal integrator dynamics as a general solution for context-dependent decision making and open a new avenue to investigate the cell- and circuit-level basis of flexible cognition in the mammalian brain.

neuroscience↗

bioRxiv2025

High-throughput imaging of GABA fluorescence as a functional assay for variants in the neurodevelopmental gene, SLC6A1

Pathogenic variants in SLC6A1, which encodes GABA Transporter 1 (GAT-1), are associated with developmental delay, autism, epilepsy (e.g., epilepsy with myoclonic astatic seizures [EMAS]), and possibly schizophrenia. Functional assays to establish pathogenicity of human variants is a key limiting factor in the clinical interpretation of genetic findings. Methods based on radioactive [3H]-GABA uptake come with significant regulatory concerns, cost, and workflow complexity, which could be resolved by an alternate assay. To address this issue, we developed a high-content fluorescence imaging assay of GAT-1-mediated GABA uptake using a genetically encoded GABA sensor, iGABA-Snfr. We demonstrated that pathogenic variants strongly reduced uptake (mean, -89.4% [95% CI, -71.5% to -107.3%]). Some variants of uncertain significance (VUS) were associated with reduced GABA uptake (G111R, S459R, V511M; mean, -101.2% [95% CI -81.1% to -121.3%]), whereas others showed only mild reduction (R211C, R566H, F242V, R419C; mean, -33.6% [95% CI -17.2% to -50.1%]), supporting variant reclassification. Variant-specific effects on iGABA were highly correlated with the results of the radioactive [3H]-GABA assay (R2=0.8095, p<0.0001). The molecular chaperone 4-phenylbutyric acid (4PBA) was associated with [~]35% increase in iGABA. This non-radioactive assay is suitable for functional validation and high-throughput screening to identify positive modulators of GAT-1.

neuroscience↗

bioRxiv2025

A multi-tissue atlas of genetic regulatory effects in sheep

Characterizing the impact of genomic variants on genome function and ultimately complex traits in livestock is essential for the development of sustainable precision agriculture and comparative genomics. Here, as part of the Farm animal Genotype-Tissue Expression (FarmGTEx) project, we present the pilot phase of the SheepGTEx resource through analyzing 6,761 RNA-sequencing samples of 51 primary tissues in a multi-breed population of sheep. We identify millions of regulatory variants associated with seven types of molecular phenotypes, and fine-map 322,468 primary and 114,017 non-primary effects, revealing a high degree of regulatory allelic heterogeneity. We systematically characterize the pleiotropic effects of these variants on molecular phenotypes, assess their context-specific regulatory patterns across tissues, breeds, sexes, and developmental stages, as well as explore their evolutionary constraints across mammals. Finally, we demonstrate the substantial potential of the SheepGTEx resource (https://sheepgtex.farmgtex.org), by providing examples of regulatory mechanisms underpinning 34 complex traits, population divergence between European and Asian breeds, and adaptive evolution in sheep over the past ten millennia.

genomics↗

bioRxiv2025

High-accuracy structure modeling for antibody-antigen complexes

Accurate modeling of antibody-antigen complexes is crucial for advancing therapeutics and diagnostics, yet predicting their binding interface remains a formidable challenge. To address this, we introduce DeepAAAssembly, a protocol that enhances static structural information from AlphaFold3 by integrating dynamic interaction patterns to guide complex assembly. Our approach leverages predicted inter-chain residue distances to construct a flexibility-aware energy function, which drives a two-stage conformational sampling process for global exploration and local exploitation. On a benchmark set of 67 representative antibody-antigen complexes, by incorporating a built-in confidence selection mechanism, DeepAAAssembly outperforms AlphaFold3, achieving not only a 12.9% higher average DockQ score and more medium- and high-quality models, but also reliably elevating the most challenging cases from incorrect to acceptable accuracy. These results demonstrate that DeepAAAssembly effectively captures conserved interaction motifs and conformational flexibility, offering a robust framework for high-accuracy antibody-antigen modeling.

bioinformatics↗

bioRxiv2025

Structure-based Predictions of Conformational B Cell Epitopes by Protein Language Model and Deep Learning

Mapping conformational B-cell epitopes remains a central challenge for antibody discovery: experiments are costly and most computational tools trained on generic protein-protein interfaces transfer poorly to antibody-antigen recognition. We introduce a patch-centric framework that predicts epitopes directly on antigen structures. Each surface "patch" is defined as a triad of neighboring residues, capturing the smallest local unit that encodes both shape and chemistry. We evaluate two classifiers: (i) a protein language model (PLM) approach that averages ESM-2 embeddings over each triad and scores them with a small multilayer perceptron [1], and (ii) a convolutional baseline that consumes a hand-crafted 15x20 feature matrix summarizing amino-acid identity, secondary structure, solvent accessibility, and shape index. Trained with five-fold cross-validation on 1,151 AbDb antibody-antigen complexes, the PLM model markedly outperforms the CNN at the patch level (e.g., F1{approx} 0.986, ROC-AUC{approx} 0.998). Aggregating patch scores to residues with an ensemble over all folds yields robust residue-wise performance, surpassing the CNN (ROC-AUC 0.689{+/-}0.072 vs. 0.548{+/-}0.018). Against widely used sequence- and structure-based tools on AbDb, our PLM achieves the best summary metrics (ROC-AUC 0.67, PR- AUC 0.56) with full coverage of all antigens. On five external complexes unseen during development, the model generalizes well (ROC-AUC 0.663) and accurately localizes binding regions qualitatively. The method converts PLM representations into interpretable epitope likelihood maps, offering a practical aid for antigen prioritization, antibody engineering, and vaccine design.

bioinformatics↗

bioRxiv2025

Structure and function of the nairovirus cap-snatching endonuclease

Nairoviruses include several human pathogens such as Crimean-Congo hemorrhagic fever virus (CCHFV) and Kasokero virus (KASV). The cap-snatching endonuclease (EN) domain of the viral polymerase is essential for transcription and represents a promising antiviral target. However, the structural and functional mechanisms of nairovirus ENs remain poorly understood. Here, we describe biochemical and structural studies of the ENs from CCHFV and KASV. Biochemical assays demonstrate that the RNA endonuclease activity of both ENs is activated by manganese ions and exhibits a preference for uridine-rich RNA substrates. This activity is inhibited by three metal-chelating inhibitors (DPBA, L-742,001, and BXA), with BXA displaying the highest binding affinity and inhibitory potency. We further determine nine crystal structures of CCHFV and KASV ENs in apo, metal ion-bound, and inhibitor-bound states. Comparative structural analysis uncovers a two-metal-ion binding mode unique to nairovirus ENs, in which conserved residues coordinate two manganese ions via bridging water molecules. In the inhibitor-bound structures of KASV EN, BXA forms additional stabilizing interactions with the enzyme, explaining its superior inhibitory effect. Functional assays further confirm that the two-metal-ion mechanism is critical for viral transcription. These findings provide a structural foundation for the rational design of antivirals against CCHFV and related pathogens.

microbiology↗