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Gao, Z.

Publications and source records attributed to Gao, Z..

At least 55 records · Page 3Linked to original sources

Sequence context and methylation interact to shape germline mutation rate variation at CpG sites

A prominent example of sequence context-dependent mutation rate variation is the elevated transition rate at CpG sites, which is largely attributed to cytosine methylation. CpGs with different flanking sequences also exhibit mutation rate variation, but this variation is only partially correlated with context-specific methylation level. Here, we quantify the CpG mutation rate and mutagenic effect of methylation across sequence contexts. Using a regression framework that accounts for recurrent mutations, we analyze human polymorphisms from the gnomAD dataset to estimate mutation rates of unmethylated and methylated CpGs separately in each unique 4-mer or 6-mer context. We find that CpG mutation rate variation in the human genome is shaped by methylation at the focal cytosine, the flanking nucleotides, and interactions between them, suggesting distinct context-dependent mutation patterns for unmethylated and methylated cytosines. Our analysis further reveals that the context effects are driven by largely independent effects of upstream and downstream sequences. Notably, an upstream adenine markedly increases CpG mutation rates regardless of methylation status or downstream sequences. Furthermore, upstream and downstream sequences have similar effects in chimpanzee and rhesus macaque, indicating that some conserved, intrinsic sequence features shape CpG mutability. On the other hand, some inter-species differences, which are especially pronounced at methylated sites on the chimpanzee lineage, point to recent evolutionary changes, possibly in context-specificity of proteins governing DNA demethylation and repair processes. Author SummaryThe DNA sequence surrounding a nucleotide strongly influences how likely it is to mutate. An extreme example is the CpG dinucleotide: cytosines in CpGs mutate far more frequently than other sites in the human genome. This is related to DNA methylation, a chemical modification that occurs almost exclusively at CpGs in vertebrates and makes cytosines more prone to mutations. However, CpGs in different sequence contexts also vary in their mutation rates, and methylation level alone cannot explain this variation. To gain insight into what processes drive this variation, we estimate mutation rates for methylated and unmethylated CpGs in different sequence contexts using human genetic variation data. We find that methylation and neighboring bases interact to influence CpG mutation rates, and that the DNA sequence on either side of the CpG exerts largely independent effects. Extending our analysis to other primates reveals both conserved and species-specific patterns, with differences being especially pronounced at methylated sites on the chimpanzee lineage. Together, our results suggest that while intrinsic DNA sequence features underlie some conserved context effects on CpG mutation rate, inter-species differences may reflect recent evolutionary changes in the mechanisms that regulate DNA demethylation and repair.

genetics↗

A novel allele of Sh1 underlines the conversion of waxy corn to wx-sweet corn

AbstractWaxy corn and sweet corn are two major types of fresh-eating corn. Each has significant market value due to its unique sensory and nutritional profiles. Developing a variety that combines both traits would meet growing consumer demand and create new market opportunities. From a fast neutron-mutagenized population of the waxy corn inbred line HB522, we identified a mutant, wx-sweet, whose kernels exhibit both waxy and sweet properties at the filling stage. Using bulked segregant analysis (BSA) and fine mapping, we localized the causal locus to SHRUNKEN1 (Sh1) on chromosome 9, which was confirmed by an allelic test with a known Mu-insertion mutant. PCR and sequencing indicated a putative large structural variation in the second and third exons of Sh1 in wx-sweet, likely disrupting the reading frame. This novel sh1 allele significantly reduced sucrose synthase activity. The sh1 and waxy1 mutant genes act synergistically to remodel carbohydrate metabolism in wx-sweet endosperms. This remodeling, revealed by integrated transcriptomic and metabolomic analyses, drives transcriptional reprogramming and restructures metabolic flux. These changes thereby enhance sucrose and raffinose accumulation, which underlies the unique waxy-sweet texture in fresh-eating maize endosperm. In summary, our work not provides valuable genetic resources for fresh-eating corn breeding, but also elucidates, for the first time, the molecular mechanism underlying the synergistic formation of waxy and sweet texture. Key messageThe novel allele of Sh1 acts synergistically with waxy1 to regulate carbohydrate metabolism, which elucidates the molecular mechanism for the unique waxy-sweet texture in fresh-eating corn endosperm. Our work provides new strategies for sweet-waxy maize breeding.

genetics↗

Structural and functional insights into QueC-family protein in QatABCD anti-phage system

QatABCD is a widespread prokaryotic anti-phage defense system comprising four protein components, out of which QatC, a QueC-family protein is the signature component. QueC family proteins are nucleoside biosynthesis enzymes involved in the biosynthesis of queuosine, a 7-deazaguanine derivative. Recently, QueC-family proteins were shown to catalyze a deazaguanylation protein-nucleobase conjugation reaction in type IV CBASS antiphage defense. However, the mechanism of QatABCD, even the function of QatC in this system, remains unknown. Here, we demonstrate that QatBCD forms a complex in which QatD is highly flexible. Crystal structures of the QatBC complex in apo and ATP-bound form support a shared role for QueC-family proteins in targeting protein substrates for N-terminal modification as in type IV CBASS. We show that the QatB N-terminal loop, its binding with QatC and QatC catalytic site are essential for QatABCD defense in vivo, suggesting a modification might occur analogous to CBASS. These findings provide structural and functional insights into QueC-family protein in QatABCD system, suggesting the conserved mechanisms and critical roles of QueC-family in prokaryotic immunity.

biochemistry↗

Tryptoline Stereoprobe Elaboration Identifies Inhibitors of the GRPEL1-HSPA9 Chaperone Complex

Activity-based protein profiling has identified hundreds of proteins from diverse classes that react at specific cysteine residues with stereochemically defined electrophilic compounds (stereoprobes) in human cells. The structure-activity relationships underlying these stereoprobe-protein interactions, however, remain poorly understood. Here we show that the protein interaction landscape of tryptoline acrylamide stereoprobes can be profoundly altered by structural modifications distal to the acrylamide reactive group. The majority of stereoprobe liganding events occurred at non-orthosteric sites and mostly evaded assignment by the machine learning-based co-folding model Boltz-2, which instead tended to misplace the stereoprobes in orthosteric pockets (an outcome we term "orthostery burnout"). We found that stereoprobes reacting with C124 in the nucleotide exchange factor GRPEL1 disrupt interactions with the mitochondrial HSP70 chaperone HSPA9/mortalin, leading to impairments in mitochondrial protein import and induction of mitophagy. Our results highlight tryptoline acrylamides as a versatile source of covalent ligands targeting non-orthosteric sites on proteins, including tool compounds that perturb the mitochondrial HSP70 chaperone system.

biochemistry↗

Shared and distinct neural signatures of inhibitory control deficits in attention-deficit/hyperactivity disorder and autism

BackgroundAttention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) share deficits in inhibitory control, yet direct comparisons of their neurobiological underpinnings remain sparse and are often confounded by comorbidity. We examined shared and distinct abnormalities in brain activation and circuit connectivity associated with inhibitory control in non-comorbid ADHD and ASD. MethodsBrain activity and hyperdirect pathway connectivity during inhibitory control were examined in children with non-comorbid ADHD (age: 11.1{+/-}0.24y) and children with non-comorbid ASD (age: 11.1{+/-}0.39y), compared with typically developing (TD) children (age: 10.9{+/-}0.09y), and benchmarked against healthy adults (age: 24.1{+/-}1.26y), using fMRI stop-signal task data. ResultsBoth ADHD and ASD groups showed reduced activation in salience and frontoparietal network regions alongside increased activation in default mode network (DMN) regions, consistent with triple-network dysfunction. These activation deficits were more pronounced in ASD, whose activation profile also diverged most from adults. At the circuit level, only ASD showed abnormal hyperdirect connectivity, involving insula-STN and preSMA-STN pathways and further reflected in a composite insula/IFG-STN connectivity measure, indicating broader cortical-STN disruption. Importantly, across all children, reduced salience/frontoparietal relative to DMN engagement correlated with greater parent-reported inhibitory control deficits, and in ASD, individual differences in insula/IFG-STN connectivity showed the same association, highlighting the behavioral relevance of both network- and circuit-level abnormalities. ConclusionsADHD and ASD share network-level but differ in circuit-level abnormalities underlying inhibitory control deficits. Together, these insights advance the neurobiology of inhibitory control in ADHD and ASD and provide potential targets for neuroscience-informed interventions addressing both shared and disorder-specific mechanisms.

neuroscience↗

Proteoform-Resolved Phosphorylation Dynamics in Kinase Complexes by Hybrid Precision Mass Spectrometry

Protein kinases integrate cellular signals through complex phosphorylation cascades, yet resolving how chemical perturbations trigger and modulate these cascades in therapeutic targets remains a major challenge. Here, we dissect AMP-activated protein kinase (AMPK) proteoforms during activation through controlled biochemical reactions with a hybrid mass spectrometry (MS) approach integrating bottom-up MS for site-specific kinetics with top-down proteoform characterization. We reveal that AMPK phosphorylation proceeds through hierarchical cascades rather than binary switching, with dual entry points: canonical CaMKK2-mediated phosphorylation or allosteric activator PF-739 both triggering extensive autophosphorylation with 1-S496 showing highest kinetic priority. Proteoform-resolved analysis uncovers channeled {beta}1-S24/25+S108 co-phosphorylation linking subcellular localization with allosteric responsiveness. Site-directed mutagenesis demonstrates CaMKK2 targets only 1-T183, with all other modifications arising through autophosphorylation. Phosphatase competition reveals asymmetric control where PP1A selectively removes activation-loop phosphorylation while autophosphorylation sites remain protected, establishing persistent regulatory states. Resolving AMPKs temporal kinetics and proteoform architecture during activation enables a proteoform-centric understanding on kinase regulation.

biochemistry↗

Robustness and fidelity of voltage imaging analysis pipelines

Tracking neuronal voltage changes using fluorescent voltage indicators is rapidly reshaping neuroscientific research. Voltage imaging enables direct visualization of electrical signals from subcellular compartments to large-scale networks, yet requires sophisticated image-analysis procedures. Here, we present a comprehensive study of current voltage imaging analysis pipelines and discuss the experimental conditions for which they are most suitable. We compare strengths and limitations of these pipelines in motion correction, denoising and segmentation routines, and discuss how different signal processing strategies can influence data integrity and interpretation. Our results show that most real-time analyses require GPU-accelerated algorithms and that denoising prior to signal processing is needed for analysis of subcellular dynamics. We conclude that voltage imaging analyses needs to be tailored to different experimental settings: we propose a decision-tree to determine analysis strategies for diverse experimental conditions. Together, these insights pave the way for reproducible, high-fidelity voltage imaging studies.

neuroscience↗

A deep reinforcement learning platform for antibiotic discovery

Antimicrobial resistance (AMR) is projected to cause up to 10 million deaths annually by 2050, underscoring the urgent need for new antibiotics. Here we present ApexAmphion, a deep-learning framework for de novo design of antibiotics that couples a 6.4-billion-parameter protein language model with reinforcement learning. The model is first fine-tuned on curated peptide data to capture antimicrobial sequence regularities, then optimised with proximal policy optimization against a composite reward that combines predictions from a learned minimum inhibitory concentration (MIC) classifier with differentiable physicochemical objectives. In vitro evaluation of 100 designed peptides showed low MIC values (nanomolar range in some cases) for all candidates (100% hit rate). Moreover, 99 our of 100 compounds exhibited broad-spectrum antimicrobial activity against at least two clinically relevant bacteria. The lead molecules killed bacteria primarily by potently targeting the cytoplasmic membrane. By unifying generation, scoring and multi-objective optimization with deep reinforcement learning in a single pipeline, our approach rapidly produces diverse, potent candidates, offering a scalable route to peptide antibiotics and a platform for iterative steering toward potency and developability within hours.

molecular biology↗

Human-scATAC-Corpus: a comprehensive database of scATAC-seq data

Single-cell Assay for Transposase-Accessible Chromatin using sequencing (scATAC-seq) profiles chromatin accessibility at cellular resolution, making it possible to reveal epigenomic landscapes that govern gene regulation in a variety of cells. Nevertheless, heterogeneous feature spaces and complex processing pipelines have impeded the construction of an ensemble resource capable of supporting diverse downstream analytical scenarios. To address this gap, we present Human-scATAC-Corpus (https://health.tsinghua.edu.cn/human-scatac-corpus/), a comprehensive database of human scATAC-seq comprising 5,407,621 cells from 35 datasets across 37 tissues or cell lines. To support complementary use cases, each dataset is distributed in three aligned formats: cell-by-candidate cis-regulatory element matrices for cross-dataset integration, raw fragment files for flexible processing, and cell-by-peak matrices for within-dataset analyses. This resource spans diverse biological contexts and includes rich metadata, enabling method benchmarking and development, as well as pretraining of foundation models. The website offers searchable browsing, detailed dataset pages, on-demand downloads, and tutorials. EpiAgent, a foundation model pretrained on Human-scATAC-Corpus, is further integrated to provide online analyses, including reference mapping, embedding extraction, and cell type annotation. Human-scATAC-Corpus establishes a unified and scalable substrate for single-cell epigenomics and is intended to accelerate discovery while standardizing evaluation across tasks. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=79 SRC="FIGDIR/small/674505v1_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@e2c4c3org.highwire.dtl.DTLVardef@1e3eaf8org.highwire.dtl.DTLVardef@5768c1org.highwire.dtl.DTLVardef@9e96ad_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

Structural insights and engineering of deep-sea halophilic PET hydrolytic enzymes

Pervasive use of polyethylene terephthalate (PET) poses tremendous challenges for global waste management and environmental sustainability, fueling growing interests in enzymatic degradation as an eco-friendly solution. While PET hydrolases hold significant promise, their industrial deployment is hindered by insufficient performance, particularly under high-salinity conditions raised from high substrate loads. Building on our previous discovery of three deep-sea PET hydrolases (dsPETase01, dsPETase05 and dsPETase06) with exceptional halophilicity and PET-degrading activity, we here present their three-dimensional structures and mechanistic characterization. Structural comparison, site-directed mutagenesis, and domain swapping reveal key structural features and the essential role of C-terminal acidic residues in salt tolerance. Integrating semi-rational protein design, Transformer-based modeling, and disulfide bond engineering, we synergistically enhance the thermostability and catalytic efficiency of dsPETase05. These findings elucidate the unique structural features and salt adaptation mechanisms of deep-sea halophilic PET hydrolases, and inform the future engineering of biocatalysts for application in harsh industrial environments.

molecular biology↗

UHRF1 restricts HCoV-229E infection through epigenetic silencing of the viral receptor APN

The emergence of SARS-CoV-2 has posed significant threats to global health, particularly for the older population. Similarly, common human coronaviruses, such as HCoV-229E, which typically cause mild cold-like symptoms, have also been linked to severe diseases, underscoring the need to understand virus-host interactions and identify host factors contributing to viral pathogenesis and disease progression. In this study, we performed a genome-wide CRISPR knockout screen using HCoV-229E and identified Ubiquitin-like with PHD and RING finger domain 1 (UHRF1) as a potent restriction factor. Mechanistically, UHRF1 suppressed HCoV-229E infection by downregulating the expression of its cell entry receptor, aminopeptidase N (APN), through promoter hypermethylation. Focused CRISPR activation screens of UHRF1-downregulated genes confirmed the critical role of APN in HCoV-229E infection and identified additional genes (e.g., SIGLEC1, PLAC8, and heparan sulfate biosynthesis genes) contributing to the restrictive functions of UHRF1. Transcriptomic and single-cell RNA sequencing analysis revealed that UHRF1 expression decreases with age, negatively correlating with increased APN expression. This age-related decline in UHRF1 was further validated in primary alveolar macrophages isolated from elderly individuals, which exhibited heightened susceptibility to HCoV-229E infection compared to those from younger individuals. Our findings highlight UHRF1 as a key age-related host defense factor against coronavirus infection and provide novel insights into the epigenetic regulation of viral entry receptors.

microbiology↗

Modeling structural variations sequencing information to address missing heritability and enhance risk prediction

Missing heritability remains a significant challenge in genome-wide studies focused on single nucleotide polymorphisms (SNPs) when analyzing the genetic basis of complex traits. Structural variations (SVs), which span broader genomic regions and often exert larger functional impacts than SNPs, hold promise for capturing this heritability. Although graph-based pangenomes have advanced SV detection and association analysis, traditional SNP-centric frameworks typically overlook detailed SV sequence information, treating overlapping SVs as independent variants and leading to reduced statistical power. To overcome this limitation, we developed SVrefiner, an algorithm that aligns overlapping SVs and partitions them into non-overlapping refined SVs (rSVs) based on sequence congruence. By generating precise genotype matrices, SVrefiner enables more accurate association studies. When applied to human, tomato, and pig genomes, SVrefiner delineated 48,712 rSVs from 77,696 human SVs, 6,607 rSVs from 51,561 tomato SVs, and 5,237 rSVs from 142,784 pig SVs. Incorporating rSVs alongside SNPs, indels, and unrefined SVs enhanced heritability estimates by up to 24.47%. Further, refined analysis revealed that gene expression traits are often influenced by specific SV subregions rather than entire SVs. Notably, integration of rSVs in human datasets increased total eQTLs by 71.56%, with cis- and trans-eQTLs rising by 21.3% and 94.4%, respectively. Mean risk prediction accuracy across over 16,000 traits improved by as much as 16.8%. These findings deepen the understanding of complex trait heritability and demonstrate the utility of rSVs for genetic improvement and disease risk assessment.

genetics↗

Nanopore-Based Glycan Sequencing via Fragmentation-Reassembly Strategy

Glycan sequencing remains a major analytical challenge due to the high structural complexity, extensive branching, and isomeric diversity of glycans. Nanopore sensing has emerged as a promising single-molecule platform for glycan analysis, but existing strategies--such as hydrolysis and strand sequencing, face significant limitations when applied to highly branched or non-linear glycans. Here we report the first experimental realization of glycan assembly sequencing, a nanopore-based strategy that reconstructs full glycan structures from individually analyzed fragments. Using a biantennary complex-type N-glycan as a model, we performed controlled enzymatic digestion to generate structurally defined oligosaccharide fragments. An engineered -HL nanopore was developed for enhanced glycan recognition, enabling the construction of a multidimensional electrical fingerprinting library. Fragment signals from unknown samples were matched to this reference dataset, and full-sequence reconstruction was achieved via fragment reassembly based on set-theoretic integration of structural candidates. This study establishes glycan assembly sequencing as a viable and modular approach to resolve complex glycoforms using nanopore technologies. The method expands the accessible sequence space beyond what is achievable with conventional strategies and provides a foundation for scalable, high-resolution glycomic analysis.

bioengineering↗

Approaching an Error-Free Diploid Human Genome

Complete human genomes now resolve regions long inaccessible to genetic analysis, yet repetitive and structurally complex sequences remain prone to assembly errors because of limitations in current assembly algorithms. We introduce a support-based framework founded on the principle that each sequencing read provides independent evidence for the underlying genome sequence. Implemented through Sufficient Alignment Support (SAS), the framework identifies regions lacking concordant read support, localizes residual errors, and guides correction. Applying SAS to T2T-YAO, a haplotype-resolved Han Chinese genome, produced a support-validated assembly in which nearly all sequences outside unresolved rDNA arrays and long homopolymer tracts are supported by independent sequencing evidence. This work establishes a scalable framework for genome validation and provides a support-validated East Asian diploid reference for investigating human genomic diversity.

genomics↗

Uranium mining fuels evolution in deep groundwater microbiomes

Deep-biosphere microbes have been underpinning global biogeochemical cycles throughout Earth history, yet their evolutionary responses to long-term anthropogenic disturbance remain poorly understood. Neutral-pH in-situ leaching (ISL), the dominant uranium-mining strategy, imposes persistent radiochemical and redox stress offering rare natural experiments across decades for observing subsurface microbial evolution. Here, by exploiting metagenomics and metatranscriptomics in examining microbial responses through various mining stages, we show that neutral U ISL causes substantial changes in microbial communities spanning 2,294 strains accompanied by diversification and selection of active microbial species. These changes occurred during elevated dissolved uranium and radiological activity which correlated with a substantial transcriptional change in energy metabolism, and with an overexpression of specific genes for oxidative-stress defence and DNA-repair pathways. Increased nucleotide diversity in 101 out of 392 species clusters and nonsynonymous/synonymous polymorphism ratios greater than one in 139 species clusters were predominantly observed in metatranscriptomes with elevated radiation, highlighting positive selection of transcriptionally active populations. These findings demonstrate that neutral U ISL drives functional and genetic diversification of subsurface microbiomes, revealing a dynamic and evolutionarily responsive deep biosphere.

genomics↗

ProteinReasoner: A Multi-Modal Protein Language Model with Chain-of-Thought Reasoning for Efficient Protein Design

Reasoning has emerged as a central capability of large language models, yet how it should be formulated for scientific foundation models remains unclear because scientific knowledge is distributed across interdependent, domain-specific representations. Here we introduce modality-chain reasoning, which organizes representations into ordered computational chains, each conditioning prediction or generation of the next. Based on this principle, we develop ProteinReasoner, a multimodal generative protein foundation model that sequentially connects amino acid sequence, evolutionary constraints and three-dimensional structure within a shared autoregressive architecture. Across zero-shot structure prediction, inverse folding and fitness prediction, ProteinReasoner outperformed two multimodal protein foundation models, while controlled comparisons supported the functional contribution of the modality chain. We further extended this principle beyond pretraining: reorganizing the chain across successive structural states enabled multiple-conformation prediction, while introducing experimental feedback as an additional modality enabled an in-context learning paradigm for protein optimization without target-specific parameter updates. In particular, across thermostability and affinity-maturation evaluations, this paradigm improved over matched fine-tuned models and showed stronger mean performance than target-specific active-learning baselines. These results establish modality-chain reasoning as a unified and effective foundation-modelling strategy in protein science. More broadly, they suggest a general route towards reasoning across interdependent representations in other scientific domains.

bioinformatics↗

Off-target effects of PLX5622 revealed: mixing microglial function in anesthesia and addiction withdrawal

Microglia have gained increasing attention as important regulators in the brain. Acute microglial depletion using the colony-stimulating factor 1 receptor (CSF1R) inhibitor, PLX5622, has become a popular approach to uncover microglial function. PLX5622 treatment has been recently shown to significantly promote anesthetic emergence. In characterizing underlying mechanisms, we found that PLX5622 treatment did not change the global neuronal activity during anesthesia, but robustly enhanced anesthetic metabolism. Moreover, PLX5622 dramatically induced the expression of hepatic enzymes that extensively modify xenobiotic and endobiotic metabolism. Blocking increased enzymatic activity significantly reduced the arousal-promoting effects of PLX5622 in anesthesia, irrespective of microglial elimination. In addition, we demonstrate that enhanced drug metabolism also contributed to PLX5622-induced attenuation in nicotine-withdrawal anxiety. By revealing previously unrecognized effects of PLX5622, our findings raise caution in interpreting data generated from PLX5622 treatment and bring forward the need for designing more specific CSF1R inhibitors.

neuroscience↗

A Photo-regulatable Intein Based Trans-Splicing tool for Protein and Organelle Relocalization to Different Subcellular Compartments

The dynamics of protein subcellular localization are intricately regulated, requiring new tools for controlling protein translocation to uncover the biological significance of post-translational regulation of protein localization. Here, we developed a new method, Protein Rerouting via INtein-mediated Trans-Splicing (PRINTS), which enables precise control of protein translocation across diverse subcellular compartments. By reconstituting functional signaling peptides, PRINTS can efficiently relocalize fluorescent proteins to the 26S proteasome, nucleus, mitochondria, plasma membrane, endomembrane organelles, and liquid-liquid phase separation (LLPS) condensates. Furthermore, we incorporated the optically regulated dimerization domain CRY2clust into the PRINTS system, achieving light-mediated control of protein entry into the cell membrane and LLPS membraneless compartments. Strikingly, we observed that HNRNPA1 promiscuously recruit CRY2- or intein-containing proteins into LLPS condensate, whereas FXR1, another LLPS protein showed minimal non-specific activity. PRINTS also allow organelle relocalization, such as LLPS condensates or mitochondria to cell membrane in a light-controllable manner. Overall, PRINTS provides a versatile and robust platform for manipulating protein and organelle subcellular translocations, offering a powerful tool to investigate the regulatory coordination and crosstalk between membranous and membraneless compartments in response to physiological needs.

cell biology↗