Biology subjects

Yang, Z.

Publications and source records attributed to Yang, Z..

At least 91 records · Page 5Linked to original sources

bioRxiv2026

Multivalent adaptor networks generate nanoscale organisation within T cell signalling condensates

Ligand engagement of the T cell receptor (TCR) triggers phosphorylation-dependent assembly of signalling complexes at the plasma membrane, yet how these assemblies are organised to coordinate signal propagation remains unclear. Here, using quantitative super-resolution imaging in primary human T cells, we show that phosphorylated TCR (pTCR) and linker for activation of T cells (pLAT) reside within micrometre-scale signalling condensates that exhibit defined nanoscale organisation. Within these condensates, pTCR and pLAT are spatially interleaved with characteristic spacing of [~]70-100 nm and display short-range dispersion rather than aggregation. Spatial cross-correlation analysis reveals that pLAT is organised around pTCR sites, consistent with a model in which activated TCRs act as local sources of LAT phosphorylation that nucleate condensate assembly. This organisation suggests that multivalent interactions and steric constraints generate structured, yet dynamic, reaction environments that couple receptor activation to downstream signalling. Together, our findings establish that TCR signalling condensates are not amorphous assemblies but possess intrinsic nanoscale architecture and support a general framework in which membrane-proximal signalling is regulated by spatially organised, multivalent assemblies.

immunology↗

bioRxiv2026

Cerebellar Microcircuits and Cortico-Cerebellar Cooperation Enable Robust Decisions

The cerebellum is increasingly implicated in perceptual decision-making, yet how cerebellar circuits-- without prominent recurrent excitation and slow reverberant loops--could support sparse evidence accumulation over behavioral timescales remains unclear. We present a biologically constrained modeling framework showing that cerebellar microcircuits can implement graded accumulation and competition without cortical-like excitatory recurrence. Type-II Purkinje-neuron excitability generates firing-rate hysteresis that prolongs the impact of brief inputs far beyond intrinsic membrane and synaptic time constants, enabling accumulation across long inter-event intervals. Purkinje neuron collateral inhibition produces competitive divergence and tunes temporal evidence weighting, revealing a trade-off between commitment and primacy bias. In a bidirectionally coupled cortico-cerebello-cortical model, cerebellar processing reduces primacy while cortical processing reduces indecision, improving robustness. Together, these results propose a mechanistic division of labor that positions the cerebellum as an active computational partner in perceptual decisions.

neuroscience↗

bioRxiv2026

Hepatocellular Carcinoma Revisited from Single Cell Sequencing: Dynamic Evolution from Epithelial Dedifferentiation to Mesenchymal Remodeling

BackgroundSingle-cell RNA sequencing has provided new insights into hepatocellular carcinoma (HCC); however, a unified understanding of epithelial heterogeneity and immune evasion strategies in HCC remains lacking. MethodsWe re-analyzed publicly available single-cell datasets using conventional bioinformatics pipelines. Cell-type annotation of epithelial and T cell populations was further validated across multiple independent datasets to ensure robustness. ResultsWe systematically examined epithelial, immune, myeloid, and stromal lineages. In addition to recapitulating previously reported findings, we identified several novel observations. Notably, we uncovered a three-step dedifferentiation trajectory in epithelial cells and confirmed a bidirectional differentiation pattern within CD8{square} T cells. We also identified a subset of GZMK{square} CD4{square} T cells, whose transcriptional features resemble but are distinct from T follicular helper (Tfh) cells. Importantly, transcriptional drift within myeloid populations appeared to be closely associated with immune responsiveness. Furthermore, ligand-receptor analysis highlighted a potential cooperative role of LAMP3{square} dendritic cells and Tfh cells in promoting lymphoid follicle formation. ConclusionsIn the era of rapidly evolving single-cell sequencing technologies, we provide a framework for understanding cellular heterogeneity in HCC, which awaits further validation in future studies.

cancer biology↗

bioRxiv2026

CCZ1 is a modulator of TPC2 activity and melanoma cell migration

The small GTPase RAB7a is a key regulator of melanoma progression by enhancing the activity of the endolysosomal two-pore cation channel TPC2. In this study, we demonstrate that CCZ1--a core component of the RAB7a guanine nucleotide exchange factor (GEF) complex--is essential for mediating this RAB7a-dependent enhancement of TPC2. Unexpectedly, we find that constitutively active (GTP-locked) RAB7a fails to bind and regulate TPC2 in the absence of CCZ1, indicating that CCZ1 contributes to the RAB7a-TPC2 interaction through mechanisms beyond its GEF activity. Furthermore, the CCZ1 facilitated GTPase-activating function on RAB5 is dispensable for modulating TPC2. Notably, in the absence of CCZ1, TPC2 exhibits increased affinity for its agonist, PI(3,5)P2, along with markedly upregulated channel activity. In melanoma cell lines, this upregulation enhances migratory capacity. Our findings identify CCZ1 as a functional inhibitor of TPC2 and highlight its critical role in regulating cancer cell migration.

physiology↗

bioRxiv2026

A High-Throughput Platform for Rapidly Adapting DNA Aptamers to SARS-CoV-2 Evolution

Rapid pathogen evolution threatens public health by eroding the effectiveness of vaccines, therapeutics, and diagnostic tools. Although spike protein targeting monoclonal antibodies (mAbs) were developed within 10-12 months of the initial outbreak to serve as key theranostic agents, their redesign has struggled to keep pace with viral evolution, rendering many neutralizing antibodies ineffective. Here we demonstrate a novel platform that combines a random-rational hybrid library diversification with high-throughput MiSeq screening to rapidly reprogram aptamers against emerging SARS-CoV-2 spike variants. Interactions between 3 different spike proteins and 11,806 unique aptamer variant designs were profiled within a few days. Starting from a 40-nt aptamer originally selected against wild-type (WT) spike protein, our screen identified a Delta-binding mutant with a 4-fold affinity improvement and an Omicron-binding mutant that converted undetectable binding into nanomolar affinity. We also identified a WT-selective mutant with substantially reduced affinity for Delta, as well as previously unrecognized bases that critically contribute to spike recognition. Integrating high-throughput binding data with molecular dynamics simulations further revealed sequence-dependent structural features underlying variant-specific aptamer-spike interactions. Finally, we developed a sensor based on the identified WT-selective aptamer mutant, enabling highly specific detection of the WT spike protein with robust performance. Together, this work establishes a rapid and adaptable aptamer engineering platform for rapid adaptation of aptamers to evolving pathogens in future pandemics.

bioengineering↗

bioRxiv2026

CXCL-CXCR2 signaling drives cancer-endothelium interactions in SCLC metastatic seeding

Small cell lung cancer (SCLC) is a highly metastatic malignancy with tropism to the liver, yet the signals that enable organ-specific metastatic colonization remain largely undefined. During metastasis, disseminated cancer cells first encounter endothelial cells (ECs) at the vascular-tissue interface, positioning cancer-endothelium crosstalk as a key determinant of metastatic success. Defining the signaling pathways underlying this reciprocal communication may uncover actionable vulnerabilities for preventing and treating this lethal disease. Here, we uncover an EC-derived CXCL chemokine program that activates cancer-intrinsic CXCR2-RAC1 signaling as a critical mediator of SCLC liver metastasis. By integrating in vitro and in vivo models, we show that SCLC cells induce robust CXCL chemokine expression from liver ECs, which in turn enhances SCLC migration and reinforces cancer cell-EC interactions. We applied highly quantitative metastatic colony barcode sequencing coupled with individual gene inactivation to demonstrate that CXCR2 is essential for SCLC migration and liver metastatic seeding. Mechanistically, CXCL-CXCR2 signaling activates RAC1-dependent F-actin assembling to drive SCLC motility during CXCL-induced metastatic seeding. Pharmacologic inhibition of CXCR2 or RAC1 suppresses SCLC migration and prevents SCLC liver metastasis. Together, our research defined a chemokine-driven signaling circuit that governs cancer-endothelium communication during the metastatic cascade and nominate the CXCL-CXCR2-RAC1 axis as a promising therapeutic vulnerability for preventing and treating metastatic SCLC.

cancer biology↗

bioRxiv2026

Bacteria-mimetic bioadhesives with multivalent mucoadhesion and drug-compatible delivery

The ability to adhere to mucus-lined tissues underpins a range of biomedical devices and therapies. However, many existing strategies rely on covalent bonding chemistries and can be unstable, cytotoxic, or incompatible with therapeutics. Here, we present a bacteria-mimetic bioadhesion strategy inspired by Vibrio cholerae. A short Bap1-derived adhesion peptide is grafted onto chitosan to strengthen mucus interactions through multivalent, cooperative secondary bonding, while preserving pH-triggered interfacial bridging behavior. Bacterial peptide grafting significantly increases adhesion energy on porcine intestine, and when paired with a tough hydrogel matrix achieves adhesion energies >400 J/m2 without forming covalent bonds to tissue. Confocal imaging reveals deep tissue penetration ([~]80 m) with markedly enhanced mucin binding and no loss of cytocompatibility. Ex vivo intestinal delivery and in vitro drug release tests demonstrate improved drug transport and tissue exposure compared to carbodiimide-mediated covalent bonding strategy. These findings establish a bacteria-mimetic bioadhesion strategy for tissue repair and drug delivery. Novelty StatementBioadhesive designs have drawn inspiration from nature such as mussel-inspired catechol chemistry and gecko-inspired dry adhesion. In contrast, bacterial adhesion mechanisms, despite enabling robust colonization of mucus-lined tissues under demanding conditions, remain largely overlooked. This work introduces a bacteria-mimetic bioadhesion strategy that selectively repurposes a short, non-pathogenic peptide derived from a Vibrio cholerae adhesin to enhance bioadhesion through multivalent, cooperative physical interactions rather than covalent bonding. This strategy significantly toughens adhesion even on chitosan, a polymer already rich in adhesive functional groups. By decoupling bacterial adhesion function from pathogenic risk, this study establishes bacterial adhesion peptides as a safe, modular, and mechanistically distinct foundation for next generation bioadhesives with improved drug compatibility.

bioengineering↗

bioRxiv2026

Lifetime-based multiplexed detection of viral RNA using fluorogenic aptamers

Fluorogenic aptamers (FAPs) are emerging molecular probes for viral RNA and DNA sensing. However, their use in multiplexed nucleic acid sensing has been hindered by cross-reactivity and overlapping emission spectra. Here we address these limitations by introducing a fluorescence-lifetime-based multiplexed detection strategy using variants of the DNA fluorogenic aptamer Lettuce that exhibits distinct fluorescence lifetimes when complexed with the fluorogen TO1-biotin. To effectively evolve Lettuce for diverse lifetimes, we developed a large-scale screening platform, termed FAP-FLIM-NGS (fluorogenic aptamer-based fluorescence lifetime imaging microscopy on next-generation sequencing chips), which measures the fluorescence lifetimes of [~]104 Lettuce/TO1-biotin complexes directly on an Illumina MiSeq flow cell. Using this approach, three variants with markedly different lifetimes were identified: a single mutant (smC14T, 6.0 ns) and two double mutants (dmA5T/C14T, 5.2 ns, and dmA5T/T22A, 4.4 ns). To demonstrate the utility of these Lettuce variants in multiplexed detection, a set of split Lettuce probes targeting viral RNA fragments derived from SARS-CoV-2, MERS-CoV, and influenza A were designed and tested. Phasor plot analysis confirmed that these probes can robustly distinguish individual targets as well as mixtures containing any two or all three targets purely based on distinct fluorescence lifetimes of probes, thereby overcoming the challenges of cross-reactivity and spectral overlap. Beyond this proof of concept, our findings establish a generalizable strategy for engineering FAPs with customized photophysical properties, opening new avenues for next-generation diagnostics and molecular sensing technologies.

bioengineering↗

bioRxiv2026

Balancing Inhibition and Sparsity for Stable, Accurate Cerebellar Learning

The cerebellums structured circuitry supports learning across motor and cognitive domains, yet the coding strategies in granule cells that enable this versatility remain unclear. Using a theoretical cerebellar model, we examined how feedforward inhibition (FFI) and feedback inhibition (FBI) shape granule cell activation patterns to optimize learning in two tasks: complex trace learning and pattern identification. For trace learning, performance depends on spatiotemporally ordered granule cell activity shaped by FBI, with temporal sparsity emerging as the key determinant of accuracy. For pattern identification, both pathways support high accuracy, with only slight sensitivity to pathway choice. In both tasks, spatial sparsity becomes critical in incremental learning to prevent memory interference, a role reinforced by advanced synaptic plasticity strategies. These findings identify sparse granule cell activation as a unifying principle for cerebellar learning and reveal task-dependent roles of inhibitory pathways, providing a mechanistic framework for understanding stability-plasticity trade-offs in cerebellar learning.

neuroscience↗

bioRxiv2026

End-to-end bimodal anti-counterfeiting by informational DNA nanoparticles

The superior stealth properties and high information density make DNA a sought-after candidate in the field of molecular steganography. Here, we developed the InfinMark end-to-end DNA steganography framework for anti-counterfeiting applications by combining the characteristics of both the Internet of Things (IoT) and DNA-of-Things (DoT). InfinMark includes five modules: Information Transcoding, Fingerprint Writing, Nano-encapsulation, Invisible Marking, and Multi-level Rapid Authentication. It ensures precise anti-counterfeiting information reading and writing through a dynamic DNA-compatible transcoding algorithm, achieves seamless embedding by developing scalable nanoparticle manufacture methods, and supports cross-scenario on-site verification, ultimately granting it comprehensive anti-counterfeiting capabilities spanning from source labeling to terminal tracing. By addressing the bottlenecks in IoT and DoT integration, lifecycle tracking, as well on-site product authentication, this research constructs a full-chain bimodal anti-counterfeiting system, thereby showcasing the practical application of informational DNA nanoparticles in various aspects of production and daily life.

synthetic biology↗

bioRxiv2026

PRISM: A High-Throughput Simulation Infrastructure for CADD Agents

Despite rapid progress in AI agents for computer-aided drug design (CADD), protein-ligand simulation workflows remain fragmented across disparate tools, creating a major bottleneck for scalable candidate evaluation. Here, we present PRISM (Protein-Receptor Interaction Simulation Modeler), a Python platform built on GROMACS that unifies ligand parameterization across multiple force fields, automated system construction, enhanced sampling, multi-tier binding free energy estimation, and trajectory analysis within a single workflow. Through the Model Context Protocol (MCP), PRISM further serves as the computational infrastructure for CADD-Agent, an expert-workflow-driven AI agent designed to orchestrate hierarchical drug screening pipelines. As a pilot application, we applied PRISM to riboflavin synthase and demonstrated end-to-end automation from candidate library assembly to binding pocket characterization, identifying a potential allosteric inhibition site at the oligomerization interface. Together, these results establish PRISM as a high-throughput simulation infrastructure for agent-enabled CADD.

biophysics↗

bioRxiv2026

Structure-guided discovery and engineering of miniature CRISPR-Cas12m for epigenome editing

CRISPR-based epigenome editing represents a programmable strategy to precisely modulate gene expression, holding immense promise for therapeutic applications. However, the large size of the dCas proteins substantially impedes the delivery via adeno-associated virus (AAV) vectors. Here, through iterative bioinformatics analysis, structure-guided predictions, and functional assays, we identified and characterized PmCas12m, a novel miniature subtype V-M CRISPR-Cas12m. PmCas12m exhibited flexible 5-YTN-3 PAM-dependent recognition and robust double-stranded DNA binding properties, while lacking DNA cleavage activity, thus positioning it as an ideal tool for epigenome editing. Cryogenic electron microscopy (cryo-EM) structures of PmCas12m unveiled its unique molecular mechanism of DNA binding facilitating interference. Guided by these structural insights, we employed deep mutational scanning (DMS) and protein engineering to develop xCas12m, a hypercompact variant with highly potent and specific epigenome editing capabilities in human cells. We further constructed the xCas12m-CRISPRoff platform in a single AAV vector, which achieved durable epigenetic silencing and effective inhibition of hepatitis B virus (HBV) infection in a mouse model. Collectively, these findings establish xCas12m as a versatile epigenome editing platform with transformative potential for treating diseases, paving the way for clinical translation of epigenetic therapies.

bioengineering↗

bioRxiv2026

Complete genome-derived metabolic interactions reveal impact of gut ecology on human health

Metabolic interactions govern gut microbiome assembly, yet functional rules remain obscured by genomic incompleteness and fragmentation. Here, we leverage 1,150 complete genomes to construct genome-scale metabolic models, demonstrating that draft genomes introduce systemic artifacts missing critical transport functions. We observe that metabolic interactions are intrinsically driven by genomic traits and niche specialization rather than random association. We stratifies strains into four ecological groups, including active players, resource predators, utilizers, and contributors, each of which exhibits distinct metabolite exchange/competition signatures. This functional architecture is strongly coupled to secondary metabolism. Applying this framework to inflammatory bowel disease revealed distinct temporal dynamics of ecological groups across disease subtypes, where group-specific dysbiosis predicted clinical phenotypes better than whole community profiles. Furthermore, integrating metabolic and co-occurrence networks to identify keystone for classifiers as features significantly improved disease diagnosis. Our study provides novel insights into gut metabolic interaction landscape, bridging the gap between genomic potential and clinical utility for precision microbiome therapeutics.

microbiology↗

bioRxiv2026

Complete Genomes of Cultivated Gut Bacteria Reveal Mobile Genetic Element-Driven Functional Diversity with Therapeutic Implications

Cultivated bacterial isolates are essential for elucidating gut microbiota functions, yet reliance on fragmented draft genomes and limited mobile genetic element (MGE) annotation has constrained high-resolution analyses. Here, we present the Cultivated Complete Genome Reference (CCGR), a comprehensive compendium of 1,150 fully circularized human gut bacterial genomes. Overcoming draft limitations, CCGR achieves chromosome-scale resolution and reveals distinct evolutionary strategies shaping gene topological organization in response to bacterial growth. Furthermore, we decode the dynamic landscape of MGEs, demonstrating that broad-host-range phages follow strict positional patterns by integrating at conserved chromosomal hotspots flanked by nutrient transporter loci. Importantly, we provide mechanistic in vivo evidence that accessory genomic elements drive strain-level functional heterogeneity. Specifically, the plasmid-encoded scrK gene in Levilactobacillus brevis involved in fructose catabolism is required to mitigate fructose-diet-exacerbated colitis. Collectively, CCGR establishes a framework linking chromosomal architecture and MGEs to bacterial evolution and host health, enabling precise, strain-resolved functional investigations.

microbiology↗

bioRxiv2026

The enhanced multi-tissue atlas of regulatory effects in cattle

Cattle are integral to global food security, yet the molecular architecture of their complex traits remains poorly understood. Here, we present the Cattle Genotype-Tissue Expression (CattleGTEx) Phase 1 resource (https://cattlegtex.farmgtex.org/), a substantial expansion of the pilot study. By leveraging 12,422 RNA-seq profiles across 43 tissues and 82 breeds, we characterized 433,972 primary and 161,428 non-primary regulatory effects spanning seven molecular phenotypes. This high-resolution atlas resolves 75% of GWAS signals for 44 complex traits, significantly addressing the "missing regulation" in livestock. We propose a genetic regulatory model demonstrating how variants across multiple biological layers interact with specific biological contexts to shape phenotypic variation. Furthermore, CattleGTEx elucidates mechanisms underlying adaptive evolution between Bos taurus and Bos indicus, as well as artificial selection in dairy and beef breeds. Finally, by mapping evolutionary constraints on these regulatory effects, we demonstrate the translational value of this resource for prioritizing causal variants in human complex diseases. Together, Phase 1 of CattleGTEx provides a transformative framework for functional genomics, precision breeding, and comparative genetics.

genetics↗

bioRxiv2026

Dual targeting of PDPK1 and BRAF V600E is synthetically lethal

PDPK1 functions downstream of PI3K and is essential for activating AKT and other AGC kinases. Although PDPK1 has a central role in the PI3K/AKT/mTOR signaling pathway, there has been limited evaluation of it as a target for cancer therapy. Anaplastic thyroid cancer (ATC) has one of the highest mortality rates of all human malignancies. Although combined BRAF and MEK inhibition in BRAF V600E mutant ATC (present in 45% of cases) results in response, resistance is common, and there is no curative treatment for ATC. The majority (up to 95.8%) of ATC cases have activation in the PI3K/AKT/mTOR and RAS/RAF/MEK/MAPK pathways due to genetic alterations involved in these pathways. In this study, we investigated PDPK1 as a therapeutic target for ATC. We used in vitro, ex vivo, and in vivo ATC models to evaluate the effect of targeting PDPK1 (BX795) alone and in combination with BRAF V600E inhibition (dabrafenib), and the mechanism of action that resulted in ATC cell death. BX795 monotherapy significantly reduced ATC cell proliferation, invasion, colony formation, and spheroid size. Combination BX795 and dabrafenib treatment had strong synergistic anticancer activity in BRAF V600E-mutant ATC models and led to simultaneous and sustained suppression of PDPK1/AKT and MAPK signaling, preventing the compensatory pathway reactivation observed with single-agent treatment. Mechanistically, combined inhibition induced pronounced oxidative stress, DNA damage, and G2-phase cell-cycle arrest, accompanied by mitochondrial dysfunction and robust activation of apoptosis in ATC cells. These effects resulted in marked tumor regression in in vitro, ex vivo, and in vivo ATC models. Our findings identify PDPK1 as a critical therapeutic vulnerability in ATC. Co-targeting PDPK1 and BRAF V600E produces potent synergistic anticancer activity by shutting down convergent oncogenic signaling pathways and amplifying apoptotic stress responses. These data support PDPK1 inhibition alone and in combination with BRAF blockade as a promising therapeutic strategy in BRAF V600E-mutant cancers.

cancer biology↗

bioRxiv2026

GCN-Mamba: Graph Convolutional Network with Mamba for Antibacterial Synergy Prediction

The escalating crisis of antimicrobial resistance necessitates novel therapeutic strategies, among which drug combination therapy shows great promise by enhancing efficacy and reducing toxicity. However, identifying effective synergistic pairs from the vast combinatorial space remains experimentally challenging and resource-intensive. To address this, we introduce GCN-Mamba, a deep learning framework that integrates Graph Convolutional Networks (GCN) with the Mamba State Space Model. This architecture captures both local molecular topological structures and global implicit interactions by leveraging Extended 3-Dimensional Fingerprints (E3FP) and bacterial gene expression profiles. Evaluation on a comprehensive dataset demonstrated that GCN-Mamba significantly outperforms classical machine learning models in predictive accuracy. In a targeted case study against Methicillin-resistant Staphylococcus aureus (MRSA), the model successfully rediscovered known synergistic pairs, such as Quercetin and Curcumin, consistent with recent literature. Furthermore, prospective in vitro validation confirmed a novel synergistic combination of Shikimic acid and Oxacillin, validating the models practical utility. By efficiently prioritizing potential candidates, GCN-Mamba serves as a powerful and reliable tool for accelerating the discovery of synergistic antimicrobial combinations, effectively bridging the gap between computational prediction and experimental validation.

bioinformatics↗

bioRxiv2026

IL12-engineered human PSMA-CAR T cells for the treatment of advanced prostate cancer

Adoptive cell therapies used to treat advanced prostate cancer are being developed to target several tumor-associated antigens, including prostate-specific membrane antigen (PSMA). Chimeric antigen receptor (CAR) T cell therapy using the single chain variable fragment (scFv) derived from the humanized murine mAb clone, J591, as the antigen-binding domain has shown promising anti-tumor activity. However, it has also been associated with macrophage activation syndrome and other unwanted toxicities, highlighting the need for more specific and human-derived antigen-binders with optimized construct designs for improved safety and efficacy. Here, we optimize a human scFv-based PSMA-targeted CAR (hPSMA-CAR) with highly selective PSMA targeting. We further introduce a membrane-bound IL-12 (mbIL12) molecule, which enhances potency with increased T cell expansion, IFNy production and anti-tumor cell activity in vitro. Using two clinically-relevant bone-metastatic prostate cancer models, we show that mbIL12-engineered hPSMA-CAR T cells drive potent in vivo anti-tumor responses. In summary, we have developed a promising therapeutic that has potential to promote safe and effective treatment of advanced PSMA+ prostate cancer.

bioengineering↗