Biology subjects

Gao, Q.

Publications and source records attributed to Gao, Q..

At least 19 recordsLinked to original sources

bioRxiv2026

PPARγ brakes cytosolic DNA-induced macrophage inflammation by super-enhancer metabolic reprogramming

Cytoplasmic DNA sensing triggers intense innate immune responses that require tight regulation. PPAR{gamma} is a master metabolic regulator in macrophages, but its role in cytoplasmic DNA immunity remains unclear. Using poly(dA:dT) to mimic cytoplasmic DNA stimulation, we combined transcriptomics, epigenomics (PPAR{gamma}/H3K27ac ChIP-seq), and functional assays. Poly(dA:dT) induced a cytokine storm with MAPK activation and apoptosis/necrosis. PPAR{gamma} activation by rosiglitazone (RGZ) antagonized this response, reducing cell death and transcriptionally inhibiting MAPK genes (e.g., DUSP4/10). Mechanistically, PPAR{gamma} bound promoters/enhancers via PPRE motifs and distal intergenic regions, remodeling H3K27ac (reduced at inflammatory loci, increased at metabolic genes). RGZ induced de novo super-enhancers coupling PPAR metabolic programs (e.g., CPT2) with immune suppression by targeting TLR4, CEBPB, and PIM3. Thus, PPAR{gamma} acts as a brake in cytoplasmic DNA immunity, integrating metabolic reprogramming and inflammation suppression through a multi-level genomic/epigenetic program. This study highlights PPAR{gamma} as a key immune-metabolic integrator and therapeutic target for diseases driven by excessive cytoplasmic DNA sensing.

immunology↗

bioRxiv2026

Inferential boundaries of age prediction: why prediction does not establish biological age measurement

Chronological-age clocks reconstruct age from biological measurements, yet their outputs are interpreted as biological age, gaps as ageing acceleration and intervention-associated decreases as rejuvenation. We show that age supervision identifies an age-task statistic, not a biological-age construct, and establish how this distinction changes biomarker construction and validation. Even at the population optimum, the same observable distribution and age-prediction performance admit incompatible biological-age interpretations. Resolving this ambiguity requires assumptions or evidence beyond the age task. Squared-error age loss penalizes within-age output dispersion without defining its biological direction. Given age and background, a gap re-expresses the compressed score; exact age recovery eliminates it even when heterogeneity remains in the measurements. Shared biological covariance permits genuine prognostic value without establishing construct identity. After allogeneic haematopoietic stem-cell transplantation, recipient-blood scores showed excess donor-lineage affiliation under a score-pairing null. In NHANES, age-trained scores improved held-out five-year mortality prediction beyond age and background, yet direct modelling of source measurements and mortality supervision at matched scalar capacity yielded further gains. The intended biological object must therefore guide study design, measurement selection and representation; validation must establish the claimed measurement relation rather than rely on age-prediction success alone.

bioinformatics↗

bioRxiv2026

Systemic tumor-cell reprogramming converts solid tumors into in situ biofactories for immunotherapy

A central challenge in oncology is delivering potent drugs to tumors without harming healthy tissues. We therefore asked whether tumor cells themselves could be genetically programmed to produce therapeutic molecules directly within the tumor. We present LENTRA (LENtiviral Tumor-Reprogramming Activator), an antigen-targeted lentiviral platform that enables selective transduction and genetic modification of tumor cells in vivo. Following intravenous administration, LENTRA achieves tumor restricted expression of immune checkpoint inhibitors, cytokines, or therapeutic enzymes in multiple murine solid tumor models. Local production of anti CTLA 4 or IL 12 triggered potent antitumor responses while avoiding systemic toxicities. Tumor restricted secretion of sialidase enhanced dendritic cell and T cell infiltration, and reprogrammed tumor associated macrophages toward an immunostimulatory phenotype, resulting in tumor regression and durable immune memory, including in tumors with heterogeneous antigen expression. In patient derived tumor explants, LENTRA mediated efficient transduction, immune remodeling, and reduced tumor viability. By engineering tumors to produce therapeutic proteins, LENTRA converts resistant tumors into autonomous therapeutic sources and active immune hubs, achieving local TME reprogramming and systemic antitumor immunity with an improved safety profile.

cancer biology↗

bioRxiv2026

Tracking a major evolutionary transition to superorganismality

Major transitions in evolution are associated with the loss of independent reproduction by formerly autonomous units. Termites provide a powerful system for studying this process because they exhibit diverse social systems in which worker developmental and reproductive potential declines with increasing colony-level organismality. However, the evolutionary sequence and developmental genetic basis of these transitions remain unresolved. Here, using comparative developmental transcriptomics across seven termite species that differ in workers' reproductive potential, we reconstructed the evolutionary history of termite social systems. We found that linear caste development, in which workers retain full reproductive potential, represents the ancestral state of termites. Bifurcated caste development, in which workers partially lose reproductive potential early in development, evolved independently multiple times, with two origins subsequently giving rise to superorganisms with unipotent, sterile workers. Ancestral gene regulatory network (GRN) reconstruction revealed that linear caste development evolved through retention of a juvenile-like worker state and co-option of a conserved developmental GRN characterizing hemimetabolous insect nymphal development, in which juvenile hormone, ecdysone and TGF-{beta} signaling pathways play central roles. The convergent evolution of bifurcated caste development repeatedly co-opted the GRN underlying linear caste development, heterochronically shifting its activity to earlier developmental stages. Finally, we found that the evolution of termite superorganisms involved somatization of the worker caste and co-option of a conserved endocrine GRN for terminal differentiation. Together, these findings uncovered repeated routes to reduced workers' reproductive potential through GRN co-option and highlight striking parallels between superorganism evolution in social insects and organismal evolution in metazoans.

evolutionary biology↗

bioRxiv2026

The evolutionary processes of bacterial aromatic polyketide ketosynthases

BackgroundThe biosynthesis of bacterial aromatic polyketide polyketides (type II polyketides, T2PKs) employs a single set of catalysts (ketosynthases, KSs or KS, with chain length factors, CLFs or KS{beta}) and iteratively assembles a carbon backbone with precise chain length control. Considering the increasing number of T2PKs discovered in laboratory settings, it is necessary to understand the evolution trajectories of KSs and CLFs. ResultsWe employed our recently developed algorithm, MAAPE, based on large protein language model (PLM) to glean insights into the evolution process of KSs and CLFs. Our findings indicated the evolutionary history of KS and CLF domains from bacterial T2PKSs and identified a shared ancestral cluster (Cluster A), supporting a common origin. Despite structural homology, KSs and CLFs followed distinct evolutionary paths, shaped by coevolution and early horizontal gene transfer. ConclusionsUnderstanding the evolutionary lineage of these enzymes will illuminate the natural optimization processes of their functions and present opportunities for the rational design of novel polyketides with enhanced efficacy.

evolutionary biology↗

bioRxiv2026

GALILEO: Embodied AI scientist for autonomous therapeutic discovery in dynamic membrane systems

Generalizable Agentic Laboratory Intelligence for Learning, Experimentation, and Optimization (GALILEO) closes the prediction-to-intervention gap in therapeutic peptide discovery. Unlike prior AI-scientist systems, GALILEO couples an Observation-Thought-Action-Summary (OTAS) reasoning loop with robotic peptide synthesis and multimodal phenotyping. Candidate peptides are retrieved from a clinically informed peptide prior (CPP) and locally edited through auditable operations. GALILEO autonomously prioritized LRRC8C and SLC25A1 branches and used wet-lab feedback to update target beliefs, sequence policies, assay choices, and mechanism hypotheses. Peptides generated under this framework blocked LRRC8C currents, perturbed osmolyte/redox homeostasis, and promoted tumor-dependent T-cell activation, while SLC25A1 peptides disrupted citrate-export metabolism, reduced extracellular acidosis, and enhanced CD8+ T-cell function. These results establish retrieval-and-editing-based physical learning as a route for auditable, experimentally grounded interventions and transferable membrane-blocker rules.

Molecular Biology↗

bioRxiv2026

EnzOracle: Mechanism-aware prediction of enzyme environmental adaptation via a classification-guided mixture-of-experts framework

Industrial biocatalysis increasingly requires enzymes capable of operating under extreme physicochemical conditions, yet most natural sequence data reflect adaptation to mild environments, leading conventional predictive models to suffer from regression-to-the-mean effects in extremophilic regimes. Here we present EnzOracle, a classification-guided mixture-of-experts framework that enables distribution-aware prediction of enzyme melting temperature (Tm), optimal catalytic temperature (Topt), and optimal pH (pHopt) directly from sequence. EnzOracle demonstrated robust predictive accuracy across diverse benchmarks, achieving RMSE of 5.245{degrees}C for Tm, 11.458{degrees}C for Topt, and 0.781 for pHopt. Beyond predictive accuracy, we introduce a trait-resolved molecular simulation strategy to evaluate whether EnzOracle-derived attribution patterns correspond to independent physical mechanisms. Across representative systems, attention hotspots mapped onto rigidity-conferring interaction networks for Tm, dynamically preorganized active-site ensembles for Topt, and pH-dependent electrostatic and hydration networks for pHopt. These orthogonal validations indicate that EnzOracle captures transferable biophysical principles of enzyme environmental adaptation rather than merely exploiting dataset-specific correlations, positioning sequence-based learning as a mechanism-aware framework for discovering stability and activity determinants across diverse catalytic landscapes.

bioinformatics↗

bioRxiv2026

Tumor-derived mitochondria enhance CD8+ T cell cytotoxicity through SPHK2-dependent S1P signaling

Intercellular organelle exchange is increasingly recognized as a feature of the tumor microenvironment, but whether tumor-derived mitochondria functionally shape anti-tumor T cell immunity remains unclear. Here we show that tumor-infiltrating CD8+ T cells acquire functional mitochondria from tumor cells through a contact-dependent, TCR-independent mechanism requiring the mitochondrial trafficking machinery Trak1-Miro1. Transferred tumor mitochondria enhanced CD8+ T cell effector activity, increasing cytotoxic molecule expression and tumor-cell killing. Mechanistically, tumor-derived mitochondria carried sphingosine-1-phosphate (S1P), which engaged S1PR1 signaling in recipient T cells. Tumor-specific deletion of Sphk2 diminished mitochondrial transfer-associated T cell activation, impaired CD8+ T cell effector function, and accelerated tumor progression in vivo. These findings reveal tumor-to-T cell mitochondrial transfer as an unexpected immunostimulatory circuit in the TME and identify mitochondrial SPHK2-S1P signaling as a regulator of CD8+ T cell anti-tumor function.

cell biology↗

bioRxiv2026

The stability of fatty acid composition in sunflower oil is dependent on environment and affected by structural variation

In sunflower (Helianthus annuus L.), the composition of fatty acids in the seeds, primarily oleic, linoleic, stearic and palmitic acid, is of utmost importance for oil quality. Despite this, the genetic basis of this trait and its interaction with the environment is poorly understood. Understanding this interaction is critical to improvement of sunflower within the context of climate change. In this work, we incorporated fatty acid composition measurements from the sunflower SAM population and eight environments across an extensive geographic cline into GWAS. The SAM panel consists of 287 varieties representing approximately 90% of sunflower diversity, for which 2.2 million high-quality SNPs with a MAF > 5% are available. For increased power, multivariate GWAS was performed with four different inputs: (i) mean fatty acid composition within each environment, (ii) mean fatty acid composition within each environment omitting high oleic varieties, (iii) trait stability within environments quantified by standard errors among replicate samples ( stability) and (iv) Eberhart and Russells {beta} which quantifies trait stabilities across environments ({beta} stability). All four analyses yielded highly significantly associated SNPs. We found that high oleic varieties exhibited high {beta} trait stability, resulting in substantial overlap in markers between analyses (i) and (iv), with signals being fairly consistent between environments in analysis (i). For analyses (ii) and (iii), significant markers tended to vary between trials. For significant SNPs across all analyses, 147 candidate genes were identified, including promising candidates such as 15 fatty acid metabolism genes, 6 heat shock proteins and 22 transcription factors. Lastly, a large introgression consisting of two flanking inverted sequences on Chromosome 5 was found to coincide with stability in the Georgia trial, suggesting a role in FA composition stability under high heat conditions.

plant biology↗

bioRxiv2026

Holomycin from Yersinia ruckeri mediates fish infection at low temperature

Why microbes invest energy in producing structurally complex natural products at extremely low concentrations within hosts remains an important topic of interest in microbial ecology. This is because such compounds with potential "biomolecular activities" can reflect molecule-target interactions, thereby providing conceptual and mechanistic insights that inform the rational design of essential clinical agents. Here, we uncover the in situ ecological function of the dithiolopyrrolone antibiotic holomycin produced by the fish pathogen Yersinia ruckeri. We show that holomycins biosynthesis is strictly gated by low temperature and that trace amounts of holomycin accumulate in vivo during infection in rainbow trout. In addition, the holomycin-deficient mutant leads to markedly reduced virulence. Integrated multiomics, phenotypic analyses, and in vivo bioassay test reveal that holomycin is not a direct lethal factor but instead remodels host-associated microbiota and enhances Y. ruckeri biofilm formation. These coordinated effects promote pathogen colonization and infection progression. Our findings establish holomycin as a host-associated effector and illustrate how its existence and ecological function are mechanistically intertwined in the evolution of pathogenic bacterial chemical arsenals.

microbiology↗

bioRxiv2026

Targeting ALA3 with propiconazole regulates plant growth and enables discovery of promising inhibitor leads

Propiconazole (PCZ) is widely misused growth regulator in leafy Brassica vegetables. Developing green strategies for managing plant architecture has become an urgent agricultural priority. Here, we identified from a membrane-protein-defective yeast library a P4-ATP phospholipid flippase, aminophospholipid ATPase 3 (ALA3), as a target sensitive to PCZ. ALA3 exhibits high binding affinity for PCZ, which inhibits its ATPase activity. Knockdown of ALA3 rendered yeast, Arabidopsis, and Brassica rapa less sensitive to PCZ and conferred a growth-inhibited phenotype. This dwarfing phenotype is mediated through the interaction between ALA3 and CYP51G1 that jointly acts within the brassinosteroid regulatory pathway. Furthermore, we identified lead compounds A01 and A15 as ALA3-targeting agents, and compared to PCZ, they display superior binding affinity and reduced toxicity. Our work establishes ALA3 as a key mediator of PCZ-induced dwarfism and provides dual strategies--creating promising varieties through gene editing and developing targeted green pesticides--to reduce PCZ use. TeaserTargeting ALA3 reduces PCZ use through gene-edited varieties and green pesticides.

plant biology↗

bioRxiv2026

The BraALA3 Homologs Mediate Propiconazole-Modulated Plant Growth in flowering Chinese cabbage

In agriculture, propiconazole (PCZ) controls excessive growth in flowering Chinese cabbage but poses dietary safety risks due to residue accumulation. Therefore, identifying novel PCZ targets and breeding PCZ-free cultivars is critical for the safe production of flowering Chinese cabbage. Here, we identified three P4-ATPase flippase homologs aminophospholipid ATPase 3 (BraALA3a/b/c) in flowering Chinese cabbage that function as sensitive targets for PCZ. These proteins exhibit high binding affinity for PCZ, which directly inhibits their ATPase activity. Overexpression of the BraALA3 homologs enhanced plant growth and increased sensitivity to PCZ, whereas knockdown led to dwarfism and reduced sensitivity. Based on these findings, we identified editable active sites via protoplast-based screening. Genetic transformation of one such site yielded BraALA3a/braala3aK200T mutant lines, which displayed a dwarf and compact architecture. These findings provide a precise molecular target for developing PCZ-free germplasm in flowering Chinese cabbage through gene editing.

plant biology↗

bioRxiv2026

Spikes meet Spins: Quantum-Native Neural Decoding for Ultra_Low-Latency Brain-Computer Interfaces

Brain - computer interfaces (BCIs) require rapid and accurate decoding of neural activity, yet conventional computing architectures face growing latency as neural recording scales. We demonstrate a quantum computing - enabled neural decoding approach using a physical 1000-qubit coherent photonic Ising machine, in which inference is performed through hardware energy relaxation rather than numerical computation. By mapping sparse neural spike patterns onto Ising Hamiltonians, our hardware-native Quantum Semi-Restricted Boltzmann Machine achieves up to 96.2% accuracy across public in vivo datasets spanning multiple species and modalities. We report hardware-verified median latencies of 0.075 ms-- a tenfold speedup over GPUs--with complexity-invariant scaling. These results establish quantum computing as a viable pathway toward ultra-low-latency neural decoding for future BCI systems.

neuroscience↗

bioRxiv2026

Patient-derived organoid xenografts reveal the multifaceted role of the lncRNA MALAT1 in breast cancer progression

Long non-coding RNAs (lncRNAs) have emerged as key regulators of tumor biology, however, thus far none have translated to cancer therapies. The lncRNA MALAT1 is overexpressed in more than 20 cancers, including breast cancer and has been shown to function via various mechanisms in a context-dependent manner, in 2D cell lines and mouse models. However, its functional role and therapeutic potential have not been evaluated in clinically relevant patient-derived models. We investigated the therapeutic potential of MALAT1-targeting antisense oligonucleotides (ASOs) for breast cancer, using clinically relevant 3D human patient-derived organoids (PDOs) and PDO-xenograft (PDO-X) models. We systematically evaluated the efficiency of MALAT1-targeting ASOs using a biobank of 28 PDO models. Across three independent PDO-X models of triple negative breast cancer (TNBC), MALAT1 depletion reproducibly drove widespread alternative splicing changes across all event types, with an enrichment of intron retention. Differentially spliced transcripts were enriched for targets of shared cancer-associated transcription factors, and MALAT1 knockdown specifically altered the relative abundance of previously unannotated splicing isoforms. Beyond tumor-intrinsic effects, tumor-specific MALAT1 depletion induced a consistent reduction in macrophage-associated gene signatures and reduced lung metastatic burden. Our data defines MALAT1s multifaceted role in TNBC, coordinating alternative splicing, tumor-stroma crosstalk, and metastatic progression. Our study provides strong preclinical evidence supporting MALAT1-targeted ASO therapy and establishes PDO-X models as a clinically relevant platform for functional interrogation of TNBC therapies. SignificanceUsing clinically relevant human PDO-X models, we show that MALAT1 influences alternative splicing, metastatic potential and the tumor microenvironment. These data support the potential of oncogenic lncRNA MALAT1 as a therapeutic target.

cancer biology↗

bioRxiv2026

Large-scale quantum computing framework enhances drug discovery in multiple stages

Coherent Ising machines (CIMs) excel at solving large-scale combinational optimization problems (COPs), but their insufficient long-term stability has hindered their applications in compute-intensive tasks like computer-aided drug discovery (CADD). By improving fiber vibration isolation and temperature control system, we have implemented a 2000-node CIM named QBoson-CPQC-3Gen achieving stable solutions over one hour on large-scale COPs. Graph-based encoding schemes were further introduced to realize a CIM-based CADD workflow including allosteric site detection, protein-peptide docking and intermolecular similarity calculation. CIM-based methods demonstrated superior speed and accuracy than heuristic algorithms. Especially, QBoson-CPQC-3Gen identified 2 novel druggable sites and bioactive compounds for 6 targets, which were further validated in vitro, in-cell and by crystal structures. Our contributions established a quantum-computing framework for multi-stage drug discovery, representing a significant advancement in both quantum computing applications and pharmaceutical research.

bioinformatics↗

bioRxiv2026

PRDM16 is necessary for sensory neuronal development in the Trigeminal Ganglion

BackgroundCranial neural crest cells (cNCC) generate craniofacial cartilage, bone, and peripheral neurons and glia, and birth defects arise when the cartilage/neuronal/glial progenitor fail to differentiate. PRDM16 is a transcriptional regulator containing both zinc-finger and SET domains, implicated in craniofacial development and orofacial clefting, but its role in cranial sensory ganglion formation has not been defined. ResultsHere, we demonstrate that prdm16 is required for trigeminal ganglion (TG) assembly and sensory neurogenesis from cranial neural crest lineages. In zebrafish, prdm16 is expressed in TG beginning by 18 hours post fertilization (hpf) and persists through the later developmental stage at 48 hpf. In the prdm16 loss-of-function zebrafish, fewer HuC+ TG neurons are present at 24 hpf and 48 hpf, along with reduced overall ganglion size. Live imaging in Tg(sox10:mRFP; elavl3:GFP) embryos demonstrates similar numbers of sox10+ cNCCs migrating to the TG region and reduced cell numbers and overall smaller size of TG in prdm16-/-. Acetylated {beta}-tubulin immunostaining shows fewer trigeminal axon projections early and an altered projection pattern by 48 hpf. A reduction in a defined sensory neuron population, p2rx3b+ cells displayed a weaker signal and decreased cell number in prdm16-/- TG. Transcriptomic analysis of FACS-isolated sox10+ cranial neural crest cells supported reduced expression of key neurogenic and sensory lineage genes. Finally, in mouse embryos, PRDM16 is expressed in TG neurons, and Prdm16csp1/csp1 embryos exhibited reduced TG volume, area and fewer HuC+ neurons at E18.5. ConclusionTogether, these data identify Prdm16 as a conserved regulator of trigeminal ganglion growth and sensory neuron differentiation, linking PRDM-family chromatin regulators to the development of the peripheral sensory nervous system.

developmental biology↗

bioRxiv2026

IDH-mutant inhibitors enhance the sensitivity of IDH1-mutant gliomas to cysteine-methionine deprivation and ferroptosis

Cysteine is essential for synthesizing glutathione, the brains main antioxidant, and cysteine deprivation can trigger ferroptosis. Here, using a new mouse model of IDH1-mutant glioma that recapitulates the characteristics of human IDH1-mutant low-grade gliomas, we demonstrate that IDH1-mutant glioma cells are significantly more vulnerable to cysteine deprivation alone or in combination with the ferroptosis inducer RSL3, compared to IDH1-wildtype glioma cells. In addition, treatments with the IDH-mutant inhibitors vorasidenib and ivosidenib further sensitize the cells to ferroptosis. Metabolomics analysis reveals that IDH1-mutant cells have altered cysteine and methionine metabolism with deficiency in transsulfuration, which is further exacerbated by cysteine-methionine deprivation and IDH-mutant inhibitors. Furthermore, dietary cysteine-methionine deprivation alone or in combination with convection-enhanced delivery of RSL3 or ivosidenib in vivo significantly prolongs survival of IDH1-mutant tumor-bearing mice. Our findings suggest that targeting cysteine and methionine metabolism in combination with IDH-mutant inhibition provides promising therapeutic strategies for IDH1-mutant gliomas.

cancer biology↗

bioRxiv2026

Coronavirus Nucleocapsid Proteins Hijack Host Protein Kinase A Catalytic Subunit α into Nucleus to Evade from STAT1 Signaling

The role of the cAMP/PKA pathway in antiviral innate immunity, including during coronavirus infections, remains unclear. We discovered coronavirus N proteins initiate cAMP-ADCY10-PKA cascade. Cytoplasmic PKA activates STAT1 independently of canonical JAK/TYR2 signaling. Coronavirus N proteins, via a conserved arginine (e.g., PEDV R58, SARS-CoV-2 R92), directly bind and sequester PKA C into the nucleus to evade STAT1 activation. Using PEDV as a model, mutant viruses with NmutNLS and NR58A were generated. Wildtype PEDV infection suppressed STAT1 activation in cells expressing PKA C/PKA CS339A deficient in STAT1 phosphorylation. However, in rXS0101mutNLS- or rXS0101R58A-infected cells, only PKA CS339A expression inhibited STAT1 activation. Downregulation of STAT1 activation is accompanied with increased viral replication. This study first elaborates that PKA C activates STAT1 in the cytoplasm of infected cells distinctly from canonical JAK/STAT1 signaling, while coronaviruses evade this antiviral response by sequestering PKA C into the nucleus via direct N protein interaction.

microbiology↗