Biology subjects

Zheng, Y.

Publications and source records attributed to Zheng, Y..

At least 91 records · Page 5Linked to original sources

bioRxiv2026

The genetic repertoire of the deep sea: from sequence to structure and function

The deep sea as the largest and maybe most hostile environment on Earth is still underexplored especially regarding its genetic repertoire. Yet, previous work has revealed significant habitat-specific deep-sea biodiversity. Here, we present an integrated deep-sea genetic dataset comprising 502 million nonredundant genes from 2,138 samples and 2.4 million predicted structures, and used it to link specific protein structures with genetic variants associated with life in the deep sea and to assess their biotechnology potential. Combining global sequence analysis with biophysical and biochemical measurements revealed unprecedented sequence diversity, yet substantial structural conservation of proteins. Especially proteins involved in replication, recombination, and repair were identified to be under rapid evolution and with specialized properties. Among these, a structurally divergent helicase exhibited advantages in controlling nanopore sequencing speed. Thus, our work positions the deep sea as a unique evolutionary engine that generates and hosts genetic diversity and bridges genetic knowledge with biotechnology.

bioinformatics↗

bioRxiv2026

PlotGDP: an AI Agent for Bioinformatics Plotting

High-quality bioinformatics plotting is important for biology research, especially when preparing for publications. However, the long learning curve and complex coding environment configuration often appear as inevitable costs towards the creation of publication-ready plots. Here, we present PlotGDP (https://plotgdp.biogdp.com/), an AI agent-based web server for bioinformatics plotting. Built on large language models (LLMs), the intelligent plotting agent is designed to accommodate various types of bioinformatics plots, while offering easy usage with simple natural language commands from users. No coding experience or environment deployment is required, since all the user-uploaded data is processed by LLM-generated codes on our remote high-performance server. Additionally, all plotting sessions are based on curated template scripts to minimize the risk of hallucinations from the LLM. Aided by PlotGDP, we hope to contribute to the global biology research community by constructing an online platform for fast and high-quality bioinformatics visualization. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=78 SRC="FIGDIR/small/702995v3_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@73c77dorg.highwire.dtl.DTLVardef@12ddfc6org.highwire.dtl.DTLVardef@be5963org.highwire.dtl.DTLVardef@de90b6_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstract.C_FLOATNO PlotGDP: an AI Agent for Bioinformatics Plotting C_FIG

bioinformatics↗

bioRxiv2026

Chromid-like secondary replicons as key sites of biosynthetic gene clusters in Ktedonobacteria

Soils harbour immense biosynthetic gene cluster (BGC) diversity that can mediate microbial interactions, yet this potential is still mapped unevenly across the tree of life. Ktedonobacteria--a class of actinomycete-like bacteria within phylum Chloroflexota--are widespread in terrestrial environments and repeatedly dominate pioneer communities in extremely oligotrophic volcanic bare-ground soils; however, their secondary metabolism and genome architecture remain poorly characterised. Here, we integrate targeted cultivation using volcanic soils from Mount Zao with genome-resolved metagenomics and public genomes to analyse 183 ktedonobacterial genomes. Using antiSMASH and BiG-SLiCE, we identified 1,546 BGCs comprising 1,162 non-redundant gene-cluster families (GCFs). In our dataset, nearly one quarter of genomes encode [≥]10 distinct GCFs, and several family-level clades show mean GCF counts comparable to those in genus Streptomyces. Most ktedonobacterial BGCs are highly divergent from reference collections and exhibit unusually low intra-genomic redundancy, suggesting broad, underexplored chemotypes. Long-read assemblies from ten strains reveal recurrent 1.6-3.5 Mb chromid-like secondary replicons with chromosome-like composition but distinct maintenance signatures. These replicons are consistently enriched in BGCs and mobility-associated genes, with mobility loci concentrated near BGC boundaries. Collectively, our results expand the current knowledge of the phylogenetic landscape of soil biosynthetic diversity and highlight chromid-like secondary replicons as major genomic reservoirs for specialised metabolism in Ktedonobacteria.

microbiology↗

bioRxiv2026

SUMO2 Deletion Changes Chromatin Accessibility and Enhances Cytotoxic T Cell Activation and Tumor Infiltration

Cytotoxic T cells (CTL) are crucial for adaptive immunity that leads to prolonged survival and potential cures for cancer. Recent clinical data has shown that pharmacological inhibition of SUMOylation (SUMOi) profoundly modifies tumor microenvironment (TME) and activates CTL, although the mechanism is not well described. In this study, we found that T cell specific knock out (KO) of the most dominant SUMO paralog, Sumo2/SUMO2, in both mouse and human CD8+ T cells significantly enhanced CD8+ T cell activation that is independent of the known mechanism - inducing type I IFN (IFN-I) expression by myeloid cells. Sumo2/SUMO2 KO in CD8+ T cells increased chromatin accessibility for transcription factors BATF, JunB, ATF3, FRA1, FRA2, and AP1 that are known to promote T cell activation and proliferation. Using antigen-specific T cell models, OT1 and Chimeric Antigen Receptor (CAR)-T cells, we found that Sumo2 KO CD8+ T cells had significantly higher tumor infiltration as revealed by flow cytometry, immuno-fluorescence (IF) staining, and single nuclei RNA-sequencing (snRNA-seq) and conferred greater tumor growth inhibition than wildtype (WT) control T cells. snRNA-seq also revealed Sumo2 KO CD8+ T cells increased the expression of Tumor Necrosis Factor-Related Apoptosis-inducing Ligand (TRAIL), induced apoptosis genes in tumor cells and activated IFN-I and IFN-{gamma} responsive genes in all cell types in the TME. These findings elucidate a novel mechanism regarding how SUMOylation can directly control CTL activation and tumor infiltration that activate anti-tumor immunity in the TME. SUMO2 KO can also be a potential strategy to enhance adoptive T cell therapies of solid tumors by enhancing their activity, tumor infiltration and their ability to after the TME.

immunology↗

bioRxiv2026

Tunable Chemical and Optical Control of ER-Plasma Membrane Contact Site Geometry and Dynamics with High-Fidelity Visualization

Endoplasmic reticulum-plasma membrane (ER-PM) contact sites are essential signaling hubs that regulate lipid transport, calcium homeostasis, and spatially organized signal transduction. Emerging evidence indicates that not only the presence but also the dynamics, stability, and geometry of ER-PM contacts critically shape cellular functions; however, tools that enable simultaneous high-fidelity visualization and reversible, quantitative control of these contacts in living cells remain limited. Here, we introduce a modular toolkit for inducible ER-PM contact-site reconstitution based on complementary chemical and optical dimerization strategies. We develop a nontoxic and reversible abscisic acid (ABA)-inducible system using the plant-derived ABIcs/PYLcs pair, and a rapidly reversible optogenetic system based on the iLID/SspB module, both of which allow robust visualization and dose-dependent control over contact-site formation kinetics, increasing contact-site density and total area fraction per cell without altering the size of individual contacts. In contrast, systematic variation of rigid -helical linker length or inducible tether abundance selectively tunes the lateral growth, stability, and lifetime of individual contact sites, without changing their density. By combining these two orthogonal strategies, we achieve independent control of both individual contact-site size and overall contact-site density, providing complementary mechanisms to adjust total contact area per cell. This versatile platform enables quantitative dissection of ER-PM contact site structure-function relationships and offers broad utility in studies of lipid exchange, calcium signaling, membrane repair, metabolic regulation, and disease-relevant dysregulation.

bioengineering↗

bioRxiv2026

Direct evidence from kinetic D2O-MRI modeling that the choroid plexus is not the major source of cerebrospinal fluid

The role of the choroid plexus (CP) as the primary source of cerebrospinal fluid (CSF) remains controversial. Here, we used dynamic indirect D2O magnetic resonance imaging (MRI) at 9.4T to investigate whole-brain CSF dynamics in rats. Spin-echo echo-planar imaging (SE-EPI) was performed during intravenous D2O infusion with a temporal resolution of 10.69 s and an in-plane resolution of 150 x 150 {micro}m. An echo time of 150.0 ms was employed to effectively suppress signals from brain parenchyma, blood, and interstitial fluid, resulting in preferential visualization of CSF. The ambient and supracerebellar cisterns (AC+SC) exhibited the greatest signal attenuation, reaching 47.32 {+/-} 15.70% of baseline, whereas the lateral ventricles (LV1, LV2) showed smaller reductions (68.73 {+/-} 18.72%-72.64 {+/-} 15.07% of baseline). CSF production rates were quantified using a one-compartment perfusion model. Estimated secretion rates were 0.11 and 0.13 {micro}L/min in the lateral ventricles and 1.30 {micro}L/min in the AC+SC region, indicating a 5.42-fold higher CSF production outside the ventricles. These findings provide direct in vivo evidence that the lateral ventricles are not the primary site of CSF production. The proposed D2O-based dynamic SE-EPI approach is safe, non-invasive, cost-effective, and suitable for widespread application.

neuroscience↗

bioRxiv2026

The extent of myeloid skewing in blood is a biomarker of biological aging in mice and humans

Myeloid skewing is a central and therefore often cited hallmark of hematopoietic aging. Myeloid skewing refers to an elevated myeloid-to-lymphoid cell ratio in aged compared to young mice. Interestingly, whether the extent of myeloid skewing might be in itself a quantitative biological marker of aging has not been addressed yet, nor whether this parameter has also relevance for the extent of aging in humans. Aged mice with high level of myeloid skewing (>50% myeloid cells in blood) showed accelerated hematopoietic aging compared to mice with a low level of myeloid skewing (<30% of myeloid cells in blood), as well as an increased level of inflammatory cytokines and elevated levels of diseases. Hematopoietic stem cells (HSCs) from mice with high myeloid skewing showed an impaired repopulation capacity. Epigenetic clock analyses demonstrated that mice with a high level of myeloid skewing present with a biological age that is older than their chronological age. In humans, a high degree of myeloid skewing was associated with elevated levels of inflammatory markers, reduced mobility, a greater burden of comorbidities, and an increased mortality hazard ratio. The data support that, besides overall myeloid skewing being a central hallmark of aging in mice, the extent of the frequency of myeloid cells in blood might serve as a biological marker of aging and disease in both mice and humans. Key PointsThe extent of myeloid skewing in aged mice correlates to an increased hematological and epigenetic age and increased disease burden. The extent of myeloid skewing in older adults is associated with an increased hazard ratio of mortality and correlates with higher frailty and inflammatory markers.

cell biology↗

bioRxiv2026

Single-cell and spatial transcriptomics unveils key regulators governing cell differentiation for Schistosoma sexual development

Schistosomiasis remains a major global health challenge, primarily due to the large number of egg production by sexually mature parasites. However, the cellular basis and regulatory programs governing sexual development and egg production are poorly characterized. Here, we constructed a dynamic single-cell atlas of Schistosoma japonicum (S. japonicum) covering key development stages of sexual maturation and egg production, and integrated it for the first time with spatial transcriptomics to map tissue-resolved cellular niches. Through bioinformatic analysis and experimental validation, we identified several critical cell populations and regulatory networks that drive parasite development and egg laying. By mapping de novo identified transcription factors (TFs) onto these atlases, we generated a comprehensive spatiotemporal expression profile of TFs and define the regulatory programs of several tissue-specific TFs including Zfp, Fbp3, and Lim. Integrated re-clustering further revealed and validated key regulators of germline stem-cell differentiation in S. japonicum. Finally, comparative analyses with S. mansoni single-cell datasets revealed both conserved and species-divergent cellular plasticity, providing unprecedented insights into their distinct biological traits. Collectively, our comprehensive study establishes a foundational resource for understanding schistosome biology, deciphers regulatory programs underlying cell differentiation and pathogenicity, and accelerates the identification of key molecules involved in sexual development against schistosomiasis.

microbiology↗

bioRxiv2026

Covalent Leader Peptide Probes Enable Proteome-Level Mapping of RiPP Enzymes beyond Biosynthetic Gene Clusters

Genome-based analyses have enabled widespread discovery and biosynthetic annotation of ribosomally synthesized and post-translationally modified peptides (RiPPs) pathways, yet often fail to capture all participating enzymes, particularly those encoded outside canonical biosynthetic gene clusters. In this study, leveraging the central role of leader peptides (LPs) in RiPP enzyme-substrate recognition, we developed a substrate-guided chemical-proteomic strategy using covalent LP probes to directly identify LP-binding enzymes from native proteomes. Using the LctA-LctM and PatE-LynD systems, we demonstrate that LP probes carrying a photocrosslinker engage enzymes at their authentic LP-recognition sites while preserving full catalytic competence. Application of this strategy to a model strain Streptomyces sparsogenes uncovered lanthipeptide synthetases encoded outside canonical biosynthetic gene clusters and revealed graded cross-cluster activities among multiple RiPP pathways. This work establishes a proof-of-concept model platform for proteome-level discovery of LP-binding RiPP enzymes and highlights cross-cluster enzymatic crosstalk as a latent mechanism for structural diversification.

biochemistry↗

bioRxiv2026

Integrated Multi-omics Analysis Identifies Molecular Signatures of Regular Physical Activity in Human Peripheral Blood

Regular physical activity is well established to protect against metabolic disorders and bolster immunity; yet, the underlying molecular and cellular mechanisms remain incompletely understood. We integrated plasma metabolomics and lipidomics with single-cell transcriptomic and chromatin accessibility profiles to decode the systemic impact of physical activity on human immunity and metabolism. Our data reveal that regular physical activity is linked to a coordinated metabolic signature marked by enhanced fatty acid oxidation and antioxidant defense. In circulating immune cells, regularly active individuals exhibited synchronous enhancement at both the chromatin accessibility and transcriptional levels for antigen presentation-related genes in antigen-presenting cells (APCs), particularly in classical monocytes, naive B cells, and switched memory B cells. Meanwhile, cytotoxic programs in CD8+ cytotoxic T and mature NK cells showed epigenetic pre-activation of effector function regulators. Intercellular communication analysis further revealed that regular exercise enhanced MHC-I/II signaling between APCs and T cells and suppressed inflammatory signaling networks. Together, these findings elucidate molecular mechanisms underlying the health benefits of regular exercise and offer a theoretical basis for enhancing public health and preventing chronic diseases.

bioinformatics↗

bioRxiv2026

Automating the Construction of Contextualized Biomedical Knowledge Graphs for Scientific Inference

Biomedical interactions are inherently dynamic, often shifting or even reversing under specific physiological states. However, existing extraction methods simplify these complex mechanisms into context-agnostic binary associations, resulting in semantic loss and contradictory evidence. Here, we present AutoBioKG, an end-to-end framework that constructs context-aware knowledge graphs by leveraging composite triples to encode environmental conditions and entity attributes alongside core relationships. Powered by an open information extraction model trained on BioOpenIE and further refined through self-training with pseudo-labels from unlabeled literature, the framework exhibits broad generalization. Notably, AutoBioKG achieved the highest zero-shot F1 across DDI, ChemProt, and BioRED, outperforming the best-performing baseline on each benchmark by 3.6-17.8 percentage points. Furthermore, AutoBioKG-derived graphs outperformed existing approaches on yes/no, factoid, and list questions in the BioASQ biomedical question-answering evaluation, particularly for queries requiring fine-grained contextual information. Together, these results support AutoBioKG as a scalable framework for transforming unstructured literature into structured, context-aware biomedical knowledge.

bioinformatics↗

bioRxiv2026

Single-Cell Multi-Omics Insights into BMI-Mediated Immune-Related Disease Risk

This study is based on the Chinese Immune Multi-Omics Atlas (CIMA) cohort and performs an integrated single-cell multi-omics analysis of peripheral blood mononuclear cells (PBMCs) from 210 individuals aged 20-29, comprising 3,311,699 scRNA-seq cells and 1,839,860 scATAC-seq cells, to decipher immune characteristics across different body mass index (BMI) categories. By integrating gene regulatory network (GRN) and cell type-level molecular quantitative trait loci (xQTL) data, and conducting summary-data-based Mendelian randomization (SMR) analysis in conjunction with genome-wide association studies (GWAS) of BMI-mediated immune-related diseases, we identified key disease-associated cell types and molecular features. Using rheumatoid arthritis (RA) as an example, multi-omics evidence revealed that in MAIT-SLC4A10 cells of underweight individuals, increased chromatin accessibility at the CCR6 locus (chr6:167119627-167120128) and enhanced transcriptional activity of RORC/RORA collectively drive elevated CCR6 expression, which may represent a potential molecular mechanism underlying the higher risk of RA in underweight populations. Our study leverages single-cell multi-omics data to systematically dissect the molecular mechanisms by which different BMI categories mediate susceptibility to immune-related diseases through coordinated regulation of immune cell chromatin accessibility, transcription factor activity, and downstream gene expression.

bioinformatics↗

bioRxiv2026

Unifying constraints linking protein folding and native dynamics decoded from AlphaFold

The interplay between protein folding and native dynamics remains a central question in biophysics. Analyzing an extensive set of AlphaFold-predicted structures, we uncover a robust relationship between folding topology (contact order) and native dynamics (fluctuation entropy), showing that long-range contacts that slow folding also restrict conformational flexibility across protein sizes and taxonomic groups. Scaling analysis reveals that this relationship, together with its chain-length dependence, is consistent with power-law-like trends, reflecting common organizing constraints of protein architecture. Across species, increasing organismal complexity is associated with proteome-wide shifts toward lower contact order and higher fluctuation entropy. Together, evidence from folding, stability, and functional dynamics converges on unifying constraints, revealing an intrinsic physical organizing principle captured by AI models.

bioinformatics↗

bioRxiv2026

TRPV4 Inhibition by a Natural Product Mediates Analgesia

The transient receptor potential vanilloid 4 (TRPV4) channel, a polymodal calcium-permeable cation channel, is activated by diverse stimuli, including hyposmolarity, moderate heat, mechanical stress, and acidic pH. TRPV4 plays a critical role in the onset and progression of pain and is implicated in multiple pathological conditions, positioning it as an attractive therapeutic target. However, the development of TRPV4-targeted therapeutics has been hindered by limited mechanistic understanding of its inhibition. Here, the natural product (R)-1-(3-ethylphenyl)ethane-1,2-diol (AH001) is identified as a potent, subtype-selective TRPV4 inhibitor. A potential gating mechanism of TRPV4 inhibition is proposed through a combination of structural analyses and site-directed mutagenesis. Electrophysiological studies and cryo-electron microscopy (cryo-EM) further reveal that AH001s glucuronide metabolite, AHP, retains robust TRPV4 inhibitory activity, providing a critical structural basis for rational optimization of AH001 as a lead compound. Notably, AH001 demonstrated significant efficacy in reducing neuronal hyperexcitability in dorsal root ganglia (DRGs) and produced pronounced analgesic effects across multiple pain models, highlighting its therapeutic potential in pain relief. This study offers critical structural and mechanistic insights into TRPV4 inhibition and lays the groundwork for the structure-based design of TRPV4-targeted therapeutics.

biochemistry↗

bioRxiv2026

Single-cell Tree-based Model for Genomic-Disease Association

The rapid maturation of single-cell multi-omics technologies has enabled unprecedented resolution for mapping disease states and identifying disease-associated biomarkers. In practice, biomarkers are often discovered through differential detection that treat genomic features as independent contributors to phenotypes, while the combinatorial interactions that drive clinical outcomes remain a practical challenge. We present scanCT (single-cell analysis of Clinical Tree), a tree-based framework that identifies groups of genomic features associated with distinct disease phenotypes in a highly interpretable manner. scanCT uses an unbiased, model-based variable-selection procedure for data-driven split selection, which is important for handling the diverse distributional properties of single-cell data across modalities. The tree architecture captures feature interaction effects, and the association modeling enables adjustment for confounding factors. We apply scanCT to longitudinal single-cell multi-omics COVID-19 datasets spanning diverse clinical outcomes and multiple time points per patient. scanCT identifies phenotype-specific gene and protein markers while accounting for age and sex, and it reveals interpretable synergistic marker combinations that help explain differences in patient clinical phenotypes.

bioinformatics↗

bioRxiv2026

'Zipper' Grammar of CTD Governs the Spatial Programing of the Transcription Cycle of RNA Polymerase II

RNA polymerase II transcribes all protein-coding genes in eukaryotes, with its C-terminal domain (CTD) acting as a regulatory platform throughout the transcription cycle. Despite its simple sequence, the conserved heptad repeats encode a regulatory grammar critical for transcription initiation, elongation, and termination. Using structural analysis, single-molecule imaging, and synthetic CTD-engineered Pol II constructs, we defined the minimal sequence requirements across transcriptional stages. We show that while SP motifs are essential phosphorylation sites, flanking residues tolerate variability. In contrast, the periodic positioning of tyrosine residues is indispensable for pre-initiation complex (PIC) assembly through interactions with the Mediator, which are disrupted upon Ser5 phosphorylation triggering promoter escape. This supports a "zipper" model where sequential tyrosine engagement stabilizes PIC assembly and progressive phosphorylation propels Pol II escape. Site-specific Ser2/5 phosphorylation orchestrates 3-end processing factor recruitment. These findings redefine the functional grammar of the Pol II CTD and explain how a low-complexity sequence achieves regulatory specificity.

cell biology↗

bioRxiv2025

Cross-species insights into placental evolution and diseases at the single-cell resolution

The placenta is a highly specialized organ in mammals, mediating the exchange of nutrients, gases, and waste between the mother and the fetus while orchestrating intricate immunological interactions to sustain a successful pregnancy. Despite its essential roles, the molecular evolution underlying the diversity of placentas across mammalian species remains largely elusive. Here, we constructed a comprehensive mammalian placental single-cell transcriptomic atlas from approximately 300,000 cells spanning ten species that could well represent the four primary placental types: (discoid, cotyledonary, diffuse, and zonary. Our cross-species analysis highlights trophoblast lineages as key drivers for placental evolution. By reconstructing differentiation trajectories, we elucidate the gene expression dynamics and regulatory networks shaping trophoblast development across diverse placental architectures. Besides, we propose that the association of human trophoblasts with conditions such as pre-eclampsia and miscarriage arises from their unique gene expression profile, which distinguishes them from trophoblasts of other species. The functional experiments further demonstrate that TGIF1 acts as an upstream regulator of key functional genes in extravillous trophoblast cells, modulating their growth, invasion, and migration. Additionally, TGIF1, along with its target genes, such as ADAM12, WNT3A, and ZNF831, is associated with preeclampsia and pregnancy loss. Collectively, these findings provide a high-resolution framework to understand the molecular evolution of the placenta and its role in reproductive success and diseases.

evolutionary biology↗

bioRxiv2025

Ultrahigh-Throughput Forster Resonance Energy Transfer-Activated Droplet Sorting for Terminator Polymerase Engineering

Droplet microfluidic screening systems enable high-throughput, labor-saving enzyme directed evolution by employing fluorescence, absorbance, and Raman-activated sorting strategies for library screening. Forster resonance energy transfer (FRET) - a nanoscale technique for monitoring intramolecular/intermolecular conformational changes - is yet to be integrated into this process. We upgraded a single-channel sorter to a dual-channel one without redesigning the microscopy setup, which can monitor FRET signals during enzyme reactions in droplets at kilohertz rates. We applied this upgraded sorter to improve the incorporation efficiency of KOD DNA polymerase towards reversible terminator deoxyribonucleotides, a property crucial for its application in next-generation sequencing (NGS). Our data show that a single-round sorting can achieve 30-fold enrichment of active variants. Five KOD variants enabling 100-cycle single-end runs of DNA sequencing were identified using a novel cyclic reversible termination (CRT) substrate featuring a terminator group {approx} 5-fold bulkier than the classical azidomethyl moiety. We also engineered a metagenome-derived novel polymerase, and a variant achieving 90% terminator incorporation efficiency within 2 minutes was identified after two rounds of enrichment. In sum, we provide a practical setup for dual-channel FRET-based droplet sorting, and demonstrate its ability in terminator polymerases engineering, thereby broaden the scope of microfluidic applications.

biochemistry↗