Biology subjects

Zhou, J.

Publications and source records attributed to Zhou, J..

At least 73 records · Page 4Linked to original sources

bioRxiv2026

An expansive animal gut microbiome dataset elucidates major compositional shifts across bilaterian evolution

Animal gut microbiomes provide key physiological functions and are critical for host health. They vary dramatically across the animal kingdom, and are shaped by factors including host diet, evolutionary history and environment. However, analyses of gut microbiomes spanning the entire metazoan clade are lacking, limiting our understanding of the fundamental principles governing gut microbiomes. Here we present the Gut Microbiome Tree of Life (GMToL), a curated 16S amplicon dataset of 17,366 samples from 1,553 host species across 26 host classes from 284 studies, enabling analysis of large-scale evolutionary trends. Using ancestral state reconstruction, we provide a critical baseline calculation of major compositional shifts in gut microbiomes throughout animal evolution. We show that the ancestral animal gut was likely dominated by Pseudomonadota. A major shift to Bacteroidota occurred during the evolution of tetrapods, followed by the emergence of Bacillota-dominated guts in mammals and birds. We identify conserved core gut microbes and demonstrate how GMToL can be leveraged to contextualize the evolutionary history of specific microbial taxa. Ultimately, this framework enables the predictive mapping of microbial symbionts across uncharacterized host lineages, and establishes a quantitative baseline for comparative microbiome research at scale.

microbiology↗

bioRxiv2026

CHORD: a framework for cross-species single-cell integration across gene, cell and cell-type levels

Quantifying cross-species relationships among cell types from single-cell transcriptomic data can reveal both conserved and divergent patterns of cell-type hierarchies. However, existing cross-species integration methods can be limited in modeling genes beyond orthologs by leveraging cell-type-resolved transcriptional context, or in learning explicit type-level representations. Here we present CHORD, a cross-species integration framework that jointly learns representations of genes, cells and cell types. We demonstrate that CHORD can integrate cross-species single-cell atlases and support cell-type annotation with unknown cell-type detection. In the frog-zebrafish embryogenesis and mammalian motor cortex atlases, CHORD infers cell-type trees that place conserved cell types from different species in relative proximity and summarize hierarchical relationships among cell types. CHORD also supports cross-species comparison of continuous phenotypic variation by placing embryonic cells along an aligned developmental timeline. CHORD further yields gene embeddings that capture orthologous and functional relationships, and gene importance scores linking genes to cell types.

bioinformatics↗

bioRxiv2026

FOXP-stabilization of the Il2ra super-enhancer structure augments Treg fitness

Gene expression in regulatory T cells (Tregs) is context-dependent and maintains peripheral immune homeostasis. FOXP3 is lineage defining but not sufficient for Treg function or persistence. To define the cell-intrinsic roles of the FOXP3 paralogs FOXP1 and FOXP4, we generated and studied mice with Treg-specific deletion of Foxp1 and/or Foxp4. FOXP1 and FOXP4 are required to maintain the peripheral Treg pool through enhancing Il2ra transcription, thereby promoting sustained high-level expression of IL-2R and thus of the high-affinity IL-2R{beta}{gamma} complex. Integrating RNA-seq and ATAC-seq with previously published ChIA-PET and publicly available data, we propose a model of Il2ra transcriptional regulation in which in which FOXP1 and FOXP4 anchor chromatin looping of the Il2ra locus in mature Tregs, augment super-enhancer activity, and drive sustained CD25 expression. Our results reveal a unique role of FOXP1, and to a lesser extent FOXP4, in controlling Treg homeostasis. One Sentence SummaryFOXP1 and FOXP4 regulate chromatin architecture at the Il2ra locus, promoting sustained CD25 expression and maintaining the peripheral Treg pool.

immunology↗

bioRxiv2026

Structure-based similarity network accelerates the discovery of lysins as oral microbiome modulators targeting periodontal pathogens

Microorganisms significantly influence human health, and dysbiosis of the oral microbiome plays a critical role in the development and progression of both oral and systemic diseases. This highlights the urgent need for novel therapeutics targeting specific pathogens. Here, we presented a structure-based pipeline to efficiently identify potential phage-derived periodontal lysins (LysPds) from nearly one million proteins. We predicted the structures of candidate lysins using AlphaFold2 and developed an innovative structure-based similarity network to classify them into distinct clusters, each with unique functional properties. A systematic characterization of 16 representative LysPds from 11 superfamilies revealed that over 90% demonstrated potent antibacterial activity against key periodontal pathogens. Among these, LysPd078 was identified as a promising preclinical drug candidate, effectively reconfiguring microbiome communities while demonstrating significant efficacy and safety in mouse models of periodontitis and calvarial infection. Our findings highlight the effectiveness of structure-based similarity networks in exploring vast protein spaces and underscore the potential of LysPd078 as a targeted modulating agent for the oral microbiome.

microbiology↗

bioRxiv2026

A nucleolar stress gene signature for quantitative scoring across multi-omics contexts

The nucleolus is essential for ribosome biogenesis and cellular homeostasis, and its dysfunction can induce nucleolar stress, which has been implicated in cancer and other diseases. However, nucleolar stress is commonly inferred from morphological alterations or a limited set of functional assays, and quantitative approaches based on gene expression profiles remain lacking. Here, we integrate literature curation with multi-dataset screening to define a nucleolar stress gene signature and develop a nucleolar stress score (NuS) that is applicable across bulk transcriptomics, single-cell transcriptomics, proteomics, and spatial transcriptomics. Using this framework, we show in colorectal cancer models that oxaliplatin induces nucleolar stress, suppresses nascent rRNA synthesis, and activates p53 signalling, whereas these responses are attenuated in oxaliplatin-resistant cells. In combination with a ribosome biogenesis activity score (RiboSis), NuS captures related yet distinct dimensions of nucleolar function and stratifies tumors into functional states associated with distinct clinical outcomes. Furthermore, NuS-based analysis of perturbational transcriptomes enables prioritization of compounds with putative nucleolar stress-inducing activity. Collectively, this study establishes a quantitative framework for evaluating nucleolar stress and illustrates its applications in disease stratification and drug mechanism discovery.

cell biology↗

bioRxiv2026

Mechanism of GPR84 allosteric modulation at a helix 8-proximate site

Allosteric modulators offer opportunities for pathway-selective GPCR signalling, but the structural mechanisms enabling biased allosteric modulation remain unclear. Here we identify a helix 8-proximate allosteric site in the immune-metabolic receptor GPR84 and define how it achieves Gi -biased signalling. Cryo-EM structures of the GPR84-Gi complexes bound to the orthosteric agonist OX04539 alone or in combination with the positive allosteric modulator (PAM) PSB-16671 reveal that PSB-16671 binds at the interface of TM1, TM7, and helix 8, a location distinct from previously characterized GPCR allosteric pockets. Molecular dynamics simulations and mutagenesis uncover a polar interaction network linking orthosteric and allosteric sites through conserved residues including Asp662.50, Asn1043.36, and Asn3627.45. Unexpectedly, disrupting this network enhances allosteric cooperativity, indicating that conformational flexibility within the network is essential for allosteric communication. PSB-16671 stabilizes a receptor conformation with pronounced TM6 displacement that favours Gi coupling while disfavouring {beta}-arrestin recruitment. This Gi-biased profile sustains macrophage phagocytosis of cancer cells without the desensitization induced by balanced agonists. Sequence analysis suggests that helix 8-proximate allosteric sites may be broadly targetable across class A GPCRs, while receptor-specific contacts enable selective modulation. These findings establish structural and mechanistic principles for biased allosteric modulation applicable beyond GPR84.

biochemistry↗

bioRxiv2026

Reduced precipitation alters microbial availability and redistribution of rhizosphere carbon

Climate change intensifies grassland drying, which is predicted to decrease soil organic carbon (SOC) storage. Yet how reduced soil water affects the transport and processing of carbon in the rhizosphere -- a major source of SOC supporting microbial activities -- remains poorly resolved under field conditions. We traced living root-derived carbon (rhizodeposit C) into soils and microbes using {superscript 1}3CO2 labeling in a multi-year precipitation manipulation experiment in a California Mediterranean annual grassland dominated by Avena barbata. Under halved precipitation, season-averaged soil water content was 20% lower and soil matric potential more than threefold lower, without inducing detectable signs of plant stress. Quantitative stable isotope probing (qSIP) of rhizosphere microbial DNA revealed that up to 68% more bacterial and 13% more fungal taxa incorporated rhizodeposit C, and that microbial uptake of rhizodeposit C increased more over time under reduced precipitation, even as total microbial biomass and community composition were unchanged. {superscript 1}3C-informed co-occurrence networks of these consumers were larger and more connected under reduced precipitation. The surrounding soils contained less 13C, and modeled solute transport by soil water was 32-40% lower, implying that rhizodeposit C was retained and intensively processed nearer to roots rather than transported to the wider soil matrix. Our evidence supports that reduced precipitation concentrates rhizodeposit C near roots, increasing the number of distinct consumers and intensifying associations among them. This represents an overlooked mechanism linking precipitation reduction to rhizodeposit C cycling. These findings show that precipitation reduction may reshape rhizosphere C processing before apparent plant stress response, with potential consequences for the fate of rhizodeposit C in grassland soils.

microbiology↗

bioRxiv2026

Detecting context-dependent selection on cancer driver genes with DiffDriver

Positive selection on somatic mutations is the driving force for cancer progression. Growing evidence shows that the emergence of a driver mutation in a tumor sample depends on individual-specific factors, for example environmental exposures or the individuals germline genetic background. We term these individual-level factors as the "contexts" of a tumor. Our hypothesis is that mutations in a driver gene can bring different growth advantages in different contexts, resulting in "differential selection" on these genes in varying contexts. Identifying which contexts modulate selection strength provides critical insights into the selection forces driving tumorigenesis. However, due to the sparsity of somatic mutations and heterogeneous background mutational process across positions and individuals, identification of differential selection has limited power with current statistical tools and is prone to false positives. To address this, we developed a powerful statistical method, DiffDriver, that identifies associations between "contexts" and selection strength on a driver gene across individuals. DiffDriver accounts for variations of mutation rates across bases and individuals, while taking advantage of functional information of sequences to improve the power. Through simulations, we show DiffDriver reduces false positives and boosts power compared to current methods. Our results highlight that multiple individual-level factors create significant heterogeneity in the strength of selection acting on driver genes and 33% of driver genes showed differential selection in at least one of the contexts studied, including tumor clinical traits and tumor immune microenvironment subtypes. These results provided new insights into the context-dependent forces driving cancer evolution.

genomics↗

bioRxiv2026

PI(4,5)P2-dependence of GABAA receptor channel function revealed by optogenetic manipulation of a binding site

ABSTRACT/SUMMARYIonotropic GABAA receptors (GABAARs) mediate fast inhibitory neurotransmission in mammalian brains. While recent structural studies have identified that phosphatidylinositol 4,5-bisphosphate [PI(4,5)P2], a well-established regulator of numerous ion channels, binds to the 1 subunits of GABAARs, the functional relevance of this binding has remained elusive. Here, we combine electrophysiology, molecular dynamics simulations, and a recently developed caged lysine technology to define the role of PI(4,5)P2 in GABAARs. We show that GABAARs are insensitive to acute PI(4,5)P2 depletions by voltage-sensing phosphatase, but sensitivity is conferred by neutralizing the K311 binding site, indicating high-affinity binding. Caging of K311 by use of genetic code expansion recapitulated phenotypes of K311 mutant, conferring sensitivity to PI(4,5)P2 depletion, whereas uncaging restored insensitivity. Furthermore, caging K311 revealed decelerated activation, which then can be accelerated by uncaging. Additionally, PI(4,5)P2-dependence extends to glycine receptors, suggesting PI(4,5)P2 is an important endogenous phospholipid modulator of inhibitory receptor channels.

biophysics↗

bioRxiv2026

Genetic background shapes AI-predicted variant effects

Predicting the consequences of genetic variants remains a major goal in biomedicine. Conventional approaches typically assess single-nucleotide variants in the context of a single reference genome, without accounting for genetic diversity that can modulate variant effects. Here we introduce the personalized variant effect predictor (pVEP) framework, which quantifies how genetic background across thousands of human genomes from globally diverse populations shapes computational predictions of clinical variant effects. Across deep learning models spanning protein structure, splicing, and noncoding regulation, pVEP reveals that many clinical variants exhibit heterogeneous predicted effects across haplotypes, with the same variant predicted to be pathogenic in some genetic backgrounds and benign in others. We find support for underlying molecular mechanisms, including shifts in predicted protein contacts and changes in splice-site recognition. Overall, personalized genomic context emerges as a systematically underappreciated variable in variant annotation and clinical interpretation, with particular implications for genetically diverse populations.

genomics↗

bioRxiv2026

OpenAc4C: A gateway to decode the landscape, regulation and pathogenesis of N4-acetylcytidine (ac4C) epitranscriptome

N4-acetylcytidine (ac4C) is an ancient and highly conserved chemical marker found in all domains of life. Recent advancements in sequencing techniques have enabled the functional analysis of ac4C occurrence by accurately capturing its locations and levels, shedding light on its significant regulatory potential and emerging role in diseases. The OpenAc4C, the first comprehensive knowledgebase exclusively designed for unraveling the ac4C epitranscriptome across diverse species, spanning vertebrates, mammals, insects, fungi, plants, bacteria, archaea, and viruses. By mining a large array of ac4C epitranscriptome datasets with deep learning-based pipelines, OpenAc4C features a collection of 536,745 ac4C sites identified from four distinct next-generation sequencing (NGS)-based techniques, alongside novel insights from Oxford Nanopore direct RNA sequencing (ONT)-based samples, encompassing a total of 33 species. Beyond the ac4C landscape, a total of 536,986 ac4C-affecting variants were identified in seven species. Among them, 4,766 pathogenic ac4C-SNPs may drive ac4C dysregulation with implications for disease pathogenesis. In addition, OpenAc4C offers a user-friendly graphical interface and a web-based analysis platform for comprehensive querying and interactive exploration of the database collections. Together, OpenAc4C will serve as a valuable integrated resource to facilitate studies of ac4C modification. It is freely accessible at: www.rnamd.org/ac4cportal.

bioinformatics↗

bioRxiv2026

The antipsychotic drug clozapine suppresses autoimmunity driving psychosis-like behavior in mice

Antipsychotic drugs are the first-line treatment for psychosis yet their mechanism of action remains poorly understood, largely due to the challenge to faithfully model psychosis preclinically. Here, we focus on the emerging concept that psychosis can be caused by brain autoimmunity and present a novel mouse model of anti-N-methyl-D-aspartate-receptor (anti-NMDAR) encephalitis, a condition that manifests with psychosis and autoanti-bodies against the NMDAR. We devised a new mRNA-based approach to immunize mice against the NMDAR. Immunized mice developed psychosis-like behaviors that were caused by anti-NMDAR autoantibodies leading to phagocytosis of NMDARs by brain microglia. The antipsychotic drug clozapine rescued psychosis-like behaviors and, remarkably, reduced anti-NMDAR autoantibody levels and antibody-mediated phagocytosis of NMDARs. The immunomodulatory effects of clozapine were confirmed in a mouse model of systemic lupus erythematosus. Our results demonstrate that clozapine suppresses autoimmunity driving psychosis-like behaviors, raising the possibility that immunomodulation contributes to antipsychotic drug action. HIGHLIGHTSO_LImRNA immunization against the NMDAR induces psychosis-like behavior in mice C_LIO_LIAnti-NMDAR autoantibodies are sufficient for psychosis-like behavior C_LIO_LIMicroglial phagocytosis of NMDARs mediates psychosis-like behavior induced by anti-NMDAR autoanti-bodies. C_LIO_LIClozapine reduces anti-NMDAR autoantibodies, microglial phagocytosis and psychosis-like behavior, consistent with immunomodulation as a potential mechanism of antipsychotic drug action. C_LI

neuroscience↗

bioRxiv2026

Imaging Intrinsic Stochastic Magnetic Fluctuations in Living Cells

SignificanceThis work establishes a probabilistic magnetometry framework for detecting weak stochastic magnetic fluctuations at the nanoscale, which provides the first quantitative access to intrinsic magnetic activity in living cells. Weak stochastic magnetic fluctuations at nanoscale are difficult to quantify. In living cells, ionic transport and molecular currents generate electromagnetic activity whose magnetic component is likewise nanoscale, weak, stochastic, and rapidly varying and has therefore remained experimentally inaccessible. Here we introduce Bio-Spin Probabilistic Inference (BISPIN), a digital statistical framework that can quantify weak, stochastic magnetic fluctuations at the nanoscale. Using threshold-resolved signals from enhanced nitrogen-vacancy quantum sensors, BISPIN converts unstable analog magnetic readouts into statistically convergent digital observables and infers fluctuation strength through probabilistic modeling, enabling robust quantification under random sensor orientations and biological heterogeneity within the experimental bandwidth. Applied to living cells, this approach distinguishes live from fixed cells, resolves agonist-induced activation, and maps subcellular variations in magnetic fluctuation strength. By providing the first quantitative access to intrinsic stochastic magnetic fluctuations in living cells, this work establishes a probabilistic magnetometry framework for cellular electrodynamics and opens a new magnetic dimension of cellular phenotyping for bio-spin omics.

biophysics↗

bioRxiv2026

Ca2+ influx through ER-plasma membrane contacts is required for brown fat thermogenesis and metabolic health

Brown adipose tissue (BAT) exhibits exceptional metabolic plasticity, rapidly increasing energy expenditure to sustain thermogenesis during cold exposure. This high metabolic activity imposes substantial demands on cellular systems, requiring robust adaptive mechanisms to maintain homeostasis and prevent cellular stress. Yet, the pathways that support and coordinate these adaptive responses in brown adipocytes remain incompletely understood. Here, we identify a cold-induced adaptive program in BAT characterized by the formation of endoplasmic reticulum-plasma membrane (ER-PM) contact sites and the activation of store-operated calcium entry (SOCE), which is essential for maintaining brown adipocyte health during thermogenic activation. Cold exposure enhances ER-PM contacts and upregulates the expression of STIM and Orai proteins, key mediators of SOCE. Loss of STIM in brown adipocytes disrupts intracellular Ca{superscript 2} homeostasis and induces aberrant aggregation of ER membranes. STIM deficiency also impairs cold-induced mitochondrial fission resulting in hyperfused mitochondria with reduced oxidative capacity, independently of UCP1 abundance. Importantly, mice lacking STIM in BAT exhibit impaired lipid oxidation, are cold intolerant and develop exacerbated peripheral insulin resistance when challenged with a high-fat diet. Together, these findings identify ER-PM remodeling and STIM-mediated SOCE as a central regulator that links organelle architecture to brown adipocyte function and contributes to whole-body metabolic homeostasis.

cell biology↗

bioRxiv2026

Telomere-to-telomere gap-free genome assembly integrated with multi-omics uncovers shading mediated regulation of leaf aroma biosynthesis in aromatic crop Pandanus amaryllifolius

Pandanus amaryllifolius is a valuable aromatic crop widely cultivated in tropical forest understories. Here, A telomere-to-telomere, gap-free genome assembly of the Chinese cultivar Taishan Banlan was generated, and the molecular basis underlying shading-mediated regulation of leaf aroma biosynthesis was elucidated for the first time through integrated genomic, transcriptomic, and metabolomic analyses. Volatile metabolomics identified 1599 volatile organic compounds in leaf tissue, with terpenoids as the primary contributors to leaf aroma. Shading modulated the aroma quality of P. amaryllifolius primarily via terpenoid biosynthesis, yielding aroma profiles dominated by sweet, fruity, green, and woody notes. Integrated transcriptomic profiling revealed that terpenoid biosynthesis is co-regulated by structural genes in the MVA/MEP pathways, TPS family members, and key transcription factors, which collectively modulate the biosynthesis and accumulation of the three core differential terpenoids. Our findings provide valuable resources for the targeted genetic improvement and efficient cultivation optimization of P. amaryllifolius.

genomics↗

bioRxiv2026

Cellular transcriptomics reveals evolutionary adaptation and rumination of vertebrate stomachs

Stomach, an essential digestive organ in vertebrates, has undergone significant changes in its morphology, chamber numbers, and physiology, in response to dietary diversity. However, its cellular and molecular basis underlying evolutionary adaptation remains largely uncharacterized. Here we report a single-cell and spatial transcriptomic atlas of stomachs from 23 vertebrate species with diverse feeding habits (e.g., omnivores, carnivores, and herbivores) and gastric architectures, including monogastric (e.g., primates), two- (e.g., aves), three- (e.g., camel) and four-chambered stomachs (e.g., sheep). We reveal conservation and divergence in cell-type composition, developmental trajectory, evolutionary origins and forces, spatial distribution, gene regulatory network and effect, metabolic signature and disease susceptibility associated with the feeding habits and stomach chamber. The diversification of plant based diets, particularly the expansion of coarse fibrous plants that required enhanced mechanical processing, driving the rapid evolution of specific cells and associated genes. Ruminants have evolved chamber-specific cell types with enhanced expressions of relevant functional genes (e.g., KRT6A in spinous cells of forestomach, LUC7L in SMCs of abomasum, and TSPYL4 in abomasal enteroendocrine cells), which were validated by fluorescence in situ hybridization and spatial transcriptomic profiling. The three cell-specific expressed genes showed significant effects on cell proliferation and migration by RNA interference to knock down their expressions. In particular, the knockdown of LUC7L in SMCs promotes a transition from a contractile to a synthetic phenotype, and Luc7l knock-out in mice delays gastric emptying and impairs gastric motility, demonstrating that this gene is essential for the coordinated multi-chambered gastric motility that underlies rumination in ruminants. These findings elucidate the cellular and molecular adaptations underlying the evolution of stomach coupled with the emergence of diet land plants. Our results provide potential cellular and gene targets for engineering monogastric animals to acquire functional rumination digestive capabilities as well as for medication of gastric mobility.

evolutionary biology↗

bioRxiv2026

Distinct cellular DNA methylation mechanisms underlie common and rare genetic risk for brain disorders

Noncoding genetic variation contributes to brain disorder risk, but the mechanisms through which it acts in specific brain cell types remain unclear. DNA methylation (DNAm), a highly cell type-specific regulatory layer in the brain, may mediate noncoding genetic risk, yet whether methylation at CG (mCG) and neuron-enriched non-CG (mCH) dinucleotides contribute differently to that risk remains unknown. Here we develop a deep learning framework that predicts DNAm from DNA sequence and estimates variant effects across 186 brain cell subtypes in both mCG and mCH, leveraging single-nucleus DNAm profiles from 46 brain regions. The models reveal distinct transcription factor (TF) programs underlying the two methylation contexts, with mCH-associated TFs showing stronger evolutionary constraint. Predicted variant effects agree closely with cell type-matched mQTLs in both direction and magnitude. Common variants predicted to affect mCG, particularly in excitatory neurons, show substantially greater heritability enrichment for brain-related traits than variants affecting mCH. By contrast, noncoding de novo mutations in autism preferentially perturb mCH, but not mCG, at conserved neuronal regulatory regions. This pattern is replicated across two independent cohorts totaling 5,782 probands and 4,053 unaffected siblings. Together, these findings indicate that common and rare noncoding variants contribute to brain disorders through distinct DNA methylation mechanisms.

genetics↗

bioRxiv2026

Bacterial proteome foundation model enhances functional prediction from enzymes to ecological interactions

Bacteria play fundamental roles in ecosystems, human health, and biotechnology. Although bacterial genome sequencing data have accumulated rapidly over the past decade, the metabolic and ecological functions carried out by most sequenced bacteria remain poorly understood, apart from a few well-studied taxa and traits. Establishing a general framework that comprehensively captures the relationship between bacterial genomes and the diverse biological functions they encode remains a major challenge, as it requires embedding individual genes within their broader genomic context and modeling their combined effects across complex biological pathways and networks. The difficulty is further compounded by the limited functional annotations available for most bacterial genomes. Here, we introduce BacPT, a proteome foundation model trained on tens of thousands of complete genomes spanning diverse bacterial taxa. BacPT captures both local and genome-wide information, enabling the generation of contextualized gene embeddings and functionally rich representations of the whole genome. We demonstrate the utility of BacPT across diverse prediction tasks spanning multiple biological scales. BacPT embeddings improve the prediction of enzyme activities, biosynthetic gene clusters, metabolic traits, and ecological interaction outcomes. Our results highlight that unsupervised deep learning applied at the scale of entire proteomes provides a powerful approach for characterizing gene interactions and mapping functional landscapes for bacteria.

genomics↗