Biology subjects

Zeng, W.

Publications and source records attributed to Zeng, W..

At least 19 recordsLinked to original sources

bioRxiv2026

sfate: Schur-free, target-conditioned absorption probabilities for scalable single-cell fate analysis

Motivation: Single-cell fate mapping at atlas scale is constrained by memory: in the tested CellRank 2.3.2 pip environment without the optional PETSc/SLEPc stack, the GPCCA estimator fell back--after a warning--to a dense Brandts Schur routine. Across three measured sizes, its peak memory was consistent with ~72 n^2 bytes, a model that back-calculates to ~405 GB [BACK-CALCULATED] for the 74,984-cell dataset studied here--beyond any consumer workstation. Results: We present scalable-fate (sfate), which computes absorption probabilities to annotation-defined target states--where 'fate probability' denotes absorption probability toward user-defined target states on a latent-space transition graph, conceptually related to Palantir-style diffusion-based Markov-chain fate modeling rather than a velocity-derived lineage probability--from latent-space kNN graphs via column-wise GMRES solves, without any Schur decomposition. Memory scaled linearly with cell number over four measured graph-construction tiers (R^2 = 0.9985; 4.03 GiB at 500,000 synthetic cells in 66.2 s); the 500k absorption solve did not converge under the default configuration, so the largest measured full-pipeline scale is the 75k real-data run (1.76 GiB). Solutions agree with float64 direct references within the prespecified 1e-5 tolerance at every tested configuration (production default L-inf = 1.74e-06; best tested configuration 3.21e-07, 31x below the threshold), and reproduce CellRank's fate probabilities when the transition kernel and terminal representative cells are held identical. On 75k mouse 5xFAD/Cd28-cKO microglia (Ayata et al., 2025; GEO: GSE296768), the full analysis ran at 1.76 GiB peak memory, returning a six-state annotation-defined absorption landscape where the archived CellRank analysis returned three comparable arms; a controlled 2x2 comparison identifies terminal-state selection as an important contributor to the cross-tool discrepancy. Availability: sfate is available at https://github.com/Ericleo-zeng/sfate (release v1.0.0, commit 5472f62; MIT license) and is archived at Zenodo (DOI: 10.5281/zenodo.22851715). The repository includes the source code, the validation suite (32 unit tests, deterministic under fixed seed), all benchmark and figure-generation scripts, the synthetic fixtures, and the records underlying every figure and table. Contact: Wei Zeng (ericleo_zeng@hotmail.com)

bioinformatics↗

bioRxiv2026

Meta-analysis of gut microbiome in largemouth bass (Micropterus salmoides) under different aquaculture systems

The teleost gastrointestinal tract hosts metabolically active microbial assemblages that play critical roles in nutrient use, immune regulation, physiology, behavior, growth, reproduction, and health status. However, the extent to which aquaculture production systems restructure these communities remains poorly defined. In this study, metagenomic sequencing was applied to characterize gut microbiota in largemouth bass (Micropterus salmoides) reared under four representative farming conditions: industrial aquaculture (IA), captive pond-based farming (CA), ordinary pond aquaculture with healthy fish (PH), and ordinary pond aquaculture with diseased fish (PD). Results revealed that the four groups exhibited pronounced differences in microbial diversity, taxonomic composition, functional capacity, carbohydrate-active enzyme profiles, and antibiotic resistance genes (ARGs). Notably, bacterial taxa accounted for more than 95% of the gut microbial communities across all groups. IA fish showed greater microbial richness and diversity than CA and PH fish, consistent with a more complex and potentially more stable intestinal ecosystem under industrialized rearing conditions. Taxonomic profiling at both the phylum and genus levels identified production system-specific microbial signatures. In particular, opportunistic pathogens, including Aeromonas veronii and Aeromonas hydrophila, were disproportionately enriched in CA fish, suggesting a microbiota profile associated with increased disease vulnerability. Functional prediction analysis further indicated distinct metabolic states among groups, with purine and fatty acid metabolism enriched in PD fish, potentially reflecting disease-associated disruption of host-microbiota interactions. Carbohydrate-active enzyme analysis revealed substantial variation in microbial carbohydrate-processing potential, whereas ARG profiling indicated that farming conditions were linked to distinct gut resistome patterns. Collectively, these findings identify aquaculture regimes as a key ecological driver of intestinal microbiome structure in largemouth bass and provide a mechanistic basis for optimizing microbiome-informed health management in aquaculture systems. Keywords: Largemouth bass (Micropterus salmoides); gut microbiota; aquaculture modes

microbiology↗

bioRxiv2026

A gene-augmentation platform for early-stage autosomal recessive retinitis pigmentosa

Most recessive inherited retinal dystrophies are, in principle, amenable to gene augmentation, yet only one such therapy has received regulatory approval. We sought to identify tractable autosomal recessive retinitis pigmentosa (RP) genes that could be treated using existing non-proprietary adeno-associated virus (AAV) components. More than 100 RP-associated genes were prioritized according to cellular expression, coding-sequence size, and the availability of cell type-specific promoters, yielding 19 candidate genes expressed predominantly in rods and/or retinal pigment epithelium (RPE). In rhesus monkey eyes, the human RHO and BEST1 promoters drove rod- and RPE-specific expression, respectively, whereas the GFAP and RLBP1 promoters were limited by absent Muller glial expression or dose-associated RPE toxicity. We selected PDE6B as a proof-of-concept gene and evaluated AAV8-RHO-PDE6B after neonatal subretinal delivery. The vector effectively preserved outer nuclear layer structure, electroretinography responses, and visually guided behaviors in rd1 and rd10 mice for at least 6 months. Dose-ranging studies identified retinal abnormalities at the higher doses, whereas the lower doses were comparatively well tolerated in eyes of mice and rhesus monkeys. Together, these findings define a preclinical framework for developing gene-augmentation vectors for a subset of early-stage autosomal recessive RP patients.

genetics↗

bioRxiv2026

Boosting carbon fixation and microbial dynamics in the coastal sediment ecosystem through large-scale cultivation of Gracilariopsis lemaneiformis

Microorganisms are the key drivers of carbon cycling in coastal marine sediment ecosystems, significantly influencing carbon storage and release during Gracilariopsis lemaneiformis cultivation. This study employed 16S rRNA sequencing, a high-throughput qPCR chip, and carbon isotope labeling to assess the impact of G. lemaneiformis cultivation on carbon cycling processes in coastal sediments. A comparative analysis was conducted between cultivated zones (GZ) of G. lemaneiformis and adjacent control zones (CZ). The results indicated that macroalgae cultivation significantly modified sediment-seawater exchange dynamics and accelerated carbon cycling within coastal marine sediment ecosystems. Furthermore, G. lemaneiformis cultivation increased the abundance of genes linked to polysaccharide degradation and carbon fixation pathways, thereby enhancing carbon cycling efficiency. The ecosystem multifunctional index, calculated based on carbon fixation gene abundance, was significantly higher in GZ compared to CZ. Incubation experiments using 13C-NaHCO3 demonstrated that cultivation markedly elevated the carbon fixation rate of sediment, emphasizing a higher potential for carbon sequestration in sedimentary environments cultivated with macroalgae. Additionally, cultivation significantly altered sediment microbial communities, simplifying their structural complexity. Key microbial taxa identified via k-core species analysis--including Subgroup10 of Desulfobacterota and MBNT15, correlated strongly with carbon fixation rates, indicating their pivotal roles in sediment carbon cycling processes. This study provides critical insights into how large-scale macroalgae cultivation influences coastal carbon dynamics and informs strategies for optimizing carbon management in aquaculture ecosystems. ImportanceGracilariopsis lemaneiformis cultivation is a widely promoted eco-aquaculture model along Southeast Chinas coast. This study finds it can drastically boost carbon sequestration efficiency in coastal sediments. Through field comparison and isotope tracing, we confirm that key carbon-fixing microbes in farmed sediments show significantly higher activity, with far stronger carbon storage potential than non-farmed zones. This research delivers direct scientific evidence for scaling up macroalgae farming to unlock new blue carbon gains, and offers a practical new solution for optimizing carbon management in aquaculture ecosystems.

microbiology↗

bioRxiv2026

DNA-binding specificity recognition from predicted homologous protein-DNA structures

Predicting protein DNA-binding specificity is essential for understanding gene regulation and disease mechanisms. Existing deep learning methods typically infer specificity from a single protein-DNA complex structure, which limits their ability to capture the diverse geometric patterns underlying protein-DNA recognition. Homologous protein-DNA interfaces provide complementary structural evidence and richer geometric features related to interatomic interactions. To address the limited diversity and coverage of experimentally determined complexes, we constructed a large-scale library of predicted homologous protein-DNA complex structures. Building on this resource, we propose HomoDSP, a template-retrieval-based framework for accurate DNA-binding specificity prediction. Benchmark evaluations and validation on newly released JASPAR 2026 samples indicate that HomoDSP outperforms existing methods in both accuracy and generalization, with particularly substantial gains on high-error samples. Moreover, this performance is largely retained when AlphaFold3-predicted complex structures are used as input. Template- and residue-level interpretability analyses suggest that HomoDSP improves prediction by focusing on DNA-affinity residues across multiple homologous templates. Finally, universal Protein Binding Microarrays evaluations on AI-designed DNA-binding proteins show that HomoDSP rescues a baseline failure mode in which the baseline method produces incorrect predictions because of training-set bias. Together, these results support the use of homologous template interfaces as informative structural priors for decoding protein DNA-binding specificity.

bioinformatics↗

bioRxiv2026

ArchaicSeeker 3.0: A deep-learning framework for scalable, haplotype-resolved inference of archaic introgression

Archaic introgression has left a significant mark on human genetic diversity, but reliably identifying introgressed segments remains a major challenge, especially with complex demographic histories and limited sample sizes. Existing methods often rely on demographic assumptions or cohort-specific parameter fitting, which compromises robustness and scalability. We introduce ArchaicSeeker 3.0 (AS3), a deep-learning framework designed for haplotype-resolved detection of archaic introgression. AS3 integrates a tract-scale sequence model with an overlap-aware reassembly approach and boundary refinement, enabling accurate, boundary-coherent reconstruction of introgressed segments across diverse genomic contexts. By leveraging a simulation-trained model, AS3 avoids inference-time recalibration, offering stable performance across unrepresented demographic scenarios and small cohorts. In extensive simulations, AS3 outperforms existing methods in precision, recall, and F1 score, while providing more continuous segments with accurate boundary localization. It demonstrates robustness in small-target regimes and varying marker densities. Applied to 3,453 genomes from 209 populations, AS3 shows strong concordance with existing introgression callers and identifies additional introgressed regions, including high-frequency AS3-specific introgressed segments supported by locus-level haplotype and phylogenetic analyses. AS3 provides a scalable, robust solution for detecting archaic introgression from single individuals to large biobank datasets, marking a significant advancement in the field of local ancestry inference and opening new possibilities for the study of human evolutionary genetics. ArchaicSeeker 3.0 is available at https://github.com/Shuhua-Group/ArchaicSeeker3.0.

bioinformatics↗

bioRxiv2026

An Isoform-Centric, Structure-Aware Framework for Protein Function Prediction and Evaluation, Instantiated in 3DisoDeepPF

Understanding and accurately predicting function across protein isoforms has been a long-standing challenge with profound implications for both biological and translational research. However, most functional annotations and benchmarks remain tied to genes or reference protein sequences, leaving limited support for distinguishing protein isoforms from the same gene whose sequence, structure and domain composition may lead to different functions. To address this gap, we developed an isoform-centric framework for protein function and domain annotation that integrates a dense graph of sequence and structure similarity with protein features. We implemented this framework as 3DisoDeepPF, a graph-based multimodal model, and applied it to a breast cancer isoform atlas. Across canonical benchmarks and evaluations at isoform resolution, 3DisoDeepPF showed strong performance in predicting GO terms and Pfam domains and remained robust in tests with homology control. It further captured changes in Pfam domain composition among isoforms from the same gene, including reference-relative domain gain and loss. An evidence tracing module links predicted labels to supporting proteins in the graph, as illustrated by the calcium and integrin binding protein 1 (CIB1). Together, this study provides a framework informed by protein structure for function and domain annotation at isoform resolution, converting human protein isoform diversity into traceable functional evidence for cancer atlas interpretation.

cancer biology↗

bioRxiv2026

Symmetric Self-play Online Preference Optimization for Protein Inverse Folding

Multi-objective reinforcement learning based on predicted structure feedback has been introduced into protein inverse folding. However, existing methods typically rely on a single model to optimize multiple structural objectives via a scalarized reward, which can bias the optimization toward dominant objectives and limit the exploration of diverse solutions. Here, we propose a online Symmetric Self-play Preference Optimization (SSP) framework that decouples the optimization of multiple structural objectives by training separate preference models with distinct reward signals, while enabling interaction through a shared sampling pool. This design allows the models to explore diverse optimization trajectories without enforcing a single dominant direction. Extensive experiments on both natural and de novo binder backbone inverse folding tasks demonstrate that SSP consistently improves sequence design self-consistency compared to single-model and existing baselines. Further analysis shows that different structural objectives are only partially aligned and induce distinct optimization directions, as evidenced by metric correlation and white-box analyses. This supports the effectiveness of decoupling objectives to enable higher design quality in protein design.

bioinformatics↗

bioRxiv2026

Nonanticoagulated Heparin Derivatives Mediate Goblet Cell Differentiation to Restore the Mucosal Barrier for Ulcerative Colitis Therapy

Epithelial mucus barrier dysfunction is a pathological hallmark of ulcerative colitis (UC), yet current clinical therapeutic strategies primarily suppress inflammation, lacking reliable approaches for restoration of the mucosal layer. Here, through a systematic screen of our established library of deanticoagulated heparins, we identified NALHP, a non-anticoagulant low-molecular-weight heparin derivative, and its representative fraction S6 as orally active epithelial repair-promoting glycans. NALHP/S6 restored crypt architecture, mucus production and epithelial barrier integrity in experimental colitis. In UC patient-derived colonic organoids, NALHP/S6 reduced aberrant stem/proliferative programs while promoting secretory, absorptive and junctional maturation. Single-cell transcriptomics and temporal validation identified a transient repair-secretory transitional state (RSTS) positioned between classical Wnt-associated stemness and mature barrier-forming epithelial states. Transcriptomic analysis revealed coordinated attenuation of Wnt and Notch signaling, whereas pharmacological reactivation of these pathways opposed NALHP/S6-induced epithelial state progression. These findings define mucosal repair as a regulated epithelial-state transition and identify NALHP/S6 as glycan-based modulators capable of restoring this progression in UC epithelium.

pathology↗

bioRxiv2026

Metabolic Perturbation Exacerbates Sinoatrial Node Dysfunction in Heart Failure

Heart failure (HF) affects approximately 6.2 million people in the United States, with a 5-year mortality exceeding 50%. Bradyarrhythmia, a known complication in HF due to sinoatrial node (SAN) dysfunction (SAND), increases the morbidity and mortality of HF patients. Insights into the mechanistic underpinnings of SAND in HF could therefore uncover vital therapeutic targets to improve clinical outcomes. The SAN cells are endowed with a dense mitochondrial network crucial for sustaining their pacemaking function on a beat-to-beat basis. We have previously demonstrated significant disruptions in the mitochondrial-sarcoplasmic reticulum connectomics, resulting in abnormal mitochondrial Ca2+ handling and impaired mitochondrial function in HF. Here, we hypothesize that the metabolic perturbation is one of the critical mechanisms underlying SAND. To this end, we took advantage of a multi-omics approach combined with ultra-resolution imaging and functional analyses to decipher the metabolic shift that transpires in the HF SAN. Our findings revealed significant metabolic remodeling within the SAN mitochondria in HF, with a diminished reliance on fatty acid {beta}-oxidation, enhanced utilization of ketone bodies, and heightened dependence on carbohydrate catabolism. Notably, metabolomics analyses identified the pronounced increase of glucosylceramides and ceramides as one of the mechanisms leading to mitochondrial dysfunction. We directly test this hypothesis and demonstrate that ceramides induce a dose-dependent metabolic shift from oxidative phosphorylation to glycolysis. Importantly, these alterations lead to a significant impairment in SAN automaticity in a dose-dependent manner. Collectively, the findings support the notion that ceramides are not only markers of metabolic derangement, but also active mediators of mitochondrial and metabolic dysfunction in the SAN. Overall, the study provides evidence that ceramides may be a potential therapeutic target for mitigating SAND in HF.

physiology↗

bioRxiv2026

Molecular mechanisms of mitochondrial Ca2+ exchanger NCLX

Mitochondrial Ca2+ homeostasis is maintained through coordinated influx and efflux processes, with NCLX long recognized as the primary Ca2+ extruder operating via Na+/Ca2+ exchange. Here, we report cryo-EM structures of rat NCLX in cytosolic-facing occluded and open states. The central transmembrane (TM) domain of NCLX comprises ten helices arranged in two inverted, structurally similar halves, with two -repeats forming a central ion-binding pocket. Peripheral TMs 1 and 6 are loosely associated with the core and likely mediate alternative access to this site. These structural features closely resemble those of NCXs, indicating a conserved ion exchange mechanism. While NCLX retains the canonical Ca2+-binding site, it lacks several key Na+-binding residues found in NCXs, suggesting broader ion selectivity. Consistently, cell-based Ca2+ uptake assays show that NCLX mediates Ca2+ exchange using Na+, K+, Li+, and potentially protons as counterions. Based on the structural symmetry of NCLX and its bidirectional exchange capability, we propose a matrix-facing model and an alternating-access mechanism in which TMs 1 and 6 undergo sliding motions to enable ion exchange between cytosolic and matrix sides, analogous to NCX. These findings provide a structural and mechanistic framework for understanding NCLX-mediated Ca2+ transport in mitochondria.

biophysics↗

bioRxiv2026

A genetically encoded ionic-stress sensor reveals protons as a sleep driver

Dynamic ionic changes are hallmarks of physiological and behavioral state transitions, including sleep in animals. Although biosensors for specific cellular ions are widely available, real-time monitoring of overall ionic strength in living organisms remains challenging. Here, we present a genetically encoded nuclear translocation ionic sensor (GENTIS) that enables direct visualization of ionic stress in vivo. Using GENTIS in C. elegans, we uncover rhythmic elevations in ionic strength during larval molting transitions that coincide with the lethargus sleep. Cytosolic proton ionic increase through inhibition of v-ATPase is sufficient to induce GENTIS nuclear translocation and evoke behavioral quiescence, characterized by reduced feeding and activation of sleep-active neurons. Apical membrane v-ATPases undergo disassembly during lethargus and under sleep-inducing stress conditions, leading to proton accumulation. Notably, this proton-mediated sleep is suppressed by proton buffering with ammonium. Together, these findings establish GENTIS as a powerful tool for tracking ionic strength dynamics in living organisms and support protons as a physiological driver of sleep.

animal behavior and cognition↗

bioRxiv2026

Asymmetric partition of the O-GlcNAcome in mitosis ensures binary cell fate decision

Many cellular components undergo biased segregation during stem cell division, but whether such order extends to the proteome has remained unknown. Using our real-time O-GlycoTracer, we find that O-GlcNAcylated proteins (the O-GlcNAcome) segregate asymmetrically during Drosophila neuroblast mitosis, predisposing the two daughters to distinct fates. The daughter that preserves stem cell identity inherits most of the O-GlcNAcome. This asymmetric partition requires putative O-GlcNAc readers, notably 14-3-3 proteins. We further identify the nuclear pore complex (NPC) as a major O-GlcNAc substrate in neuroblasts; Nup153, located in the nuclear basket, shows O-GlcNAc-dependent biased inheritance. Perturbing multiple steps in this segregation pathway disrupts neuroblast differentiation, reduces brain size, and causes adult learning deficits. These findings reveal a coordinated O-GlcNAc-driven mechanism for proteome-level asymmetric inheritance during neural stem cell division, with implications for neurodevelopmental disorders linked to OGT or 14-3-3 mutations.

cell biology↗

bioRxiv2025

A mouse model for cerebral/cortical visual impairment (CVI) impairs vision and disrupts the spatial frequency tuning of neurons in visual cortex

Cerebral/cortical visual impairment (CVI) is a visual disorder associated with perinatal hypoxic injury. The pathophysiology of CVI is poorly understood in part because of the lack of an animal model. Here we developed a murine model of CVI from existing rodent early postnatal hypoxia models for periventricular leukomalacia. Exposure to hypoxia during the equivalent to the human third trimester did not perturb motor function but caused severe impairments in binocular depth perception and visual acuity. Impaired vision was associated with normal retinal function, but reduced size of the visual thalamus, and aberrant tuning for spatial frequency by populations of excitatory neurons in primary visual cortex. This murine model of CVI provides a framework for triangulating circuit deficits with specific visual impairments and testing potential therapeutic interventions.

neuroscience↗

bioRxiv2025

Improved multimodal protein language model-driven universal biomolecules-binding protein design with EiRA

The interactions between proteins and biomolecules form a complex system that supports life activities. Designing proteins capable of targeted biomolecular binding is therefore critical for protein engineering and gene therapy. Here, we propose a new generative model, EiRA, specifically designed for universal biomolecular-binding protein design, which undergoes two-stage post-training, i.e., domain-adaptive masking training and binding site-informed preference optimization, based on a general multimodal protein language model. A systemic evaluation reveals the SOTA performance of EiRA, including structural confidence, diversity, novelty, and designability on 8 test sets across 6 biomolecule types. Meanwhile, EiRA provides a better characterization for biomolecular-binding proteins than generic model, thereby improving the predictive performance of various downstream tasks. We also mitigate severe repetition generation in the original language model by optimizing training strategies and loss. Additionally, we introduced DNA information into EiRA to support DNA-conditioned binder design, further expanding the boundaries of the design paradigm. Purification experiments and molecular dynamics simulations verified the manufacturability and DNA-binding ability of the designed highly differentiated protein. Remarkably, EiRA achieved the "one-shot" design of a Glucagon peptide binder with SPR-confirmed micromolar affinity.

bioinformatics↗

bioRxiv2025

Multi-omic dereplication of antibiotic production by diffusion chamber isolated bacteria from Australian soils

Soil bacteria are a major source of clinically useful antibiotics, yet the majority of soil-dwelling microorganisms remain uncultivable by standard laboratory methods. To access this untapped microbial diversity, we employed microbial diffusion chambers to isolate bacteria from ten Australian soil samples. A total of 1,218 bacterial isolates were recovered, representing a diverse collection spanning 61 genera from 32 families, covering the major known phyla of soil bacteria. Antibiotic activity screening revealed that 16% of isolates inhibited the growth of at least one of E. coli or S. aureus, with 120 isolates displaying activity against multidrug-resistant pathogens including methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococcus faecium (VRE). Mass spectrometry-based dereplication using GNPS identified known antibiotics in 33% of bioactive strains, including actinomycin D, nonactins, and valinomycin. Genomic analysis confirmed the presence of corresponding biosynthetic gene clusters (BGCs), while targeted analysis of selected strains uncovered production of additional antibiotics such as nigericin and streptothricin that were not initially detected by mass spectrometry. Our results demonstrate that diffusion chambers enhance bacterial recovery from soil and show the benefits of a combined pipeline including bioactivity screening, mass spectrometry, and genomics for effective antibiotic dereplication and discovery. Impact StatementThis study delivers a significant advance in natural product discovery by demonstrating that microbial diffusion chambers can dramatically improve the recovery of diverse soil bacteria with antibiotic-producing potential from Australian soil samples. By integrating in situ cultivation with high-throughput screening, mass spectrometry-based dereplication and genome mining, this study yielded more than 1,200 bacterial isolates--including many with activity against multidrug-resistant pathogens--and confirms the production of both known and previously undetected antibiotics. The discovery of streptothricin production via genomics, despite its absence from mass spectrometry data, underscores the power of a multi-layered dereplication strategy. This work not only validates the utility of diffusion chambers for unlocking the "rare biosphere" of uncultivable microbes but also highlights critical methodological refinements to diversify antibiotic-producing strains beyond Streptomyces. The findings will inform and accelerate future efforts to discover urgently needed antibiotics from environmental microbiomes. Data SummaryThe whole-genome sequences were deposited in the National Center for Biotechnology Information National Library of Medicine under BioProject accession number PRJNA1272227.

microbiology↗

bioRxiv2025

Optimized large-scale longitudinal biorepository of gastroesophageal adenocarcinoma patient-derived organoids: High-fidelity models for personalized treatment to overcome resistance.

A major limitation in studying gastroesophageal adenocarcinoma (GEA) has been the lack of reliable models that represent the diseases complexity. We present lessons learned from a comprehensive large-scale biobanking effort combining traditional sample collection with several in vitro models including 3-dimensional patient-derived organoids (PDOs), 2-dimensional cancer-associated fibroblasts (CAFs), tumor-infiltrating lymphocytes (TILs) and/or in vivo xenografts. This initiative started in 2018, integrating multiple advanced ex-vivo models such as PDOs, patient-derived xenografts (PDXs) and organoids (PDXOs). This unique resource now includes tumor avatars from over 380 consented patients, making it the largest living GEA biobank in the world. We achieved > 90% success rate in creating per-patient models, including 227 tumor-derived and 203 neighboring normal PDOs. These organoids accurately mirror key features of the original tumors, such as their histology (e.g. microsatellite instability), mutations, and drug response, across treatment points. Notably, PDOs can predict individual patient responses to chemotherapy within five weeks, underscoring their clinical relevance. Furthermore, high-throughput drug screening on PDO subsets generates personalized chemosensitivity profiles for 22 drugs. Through a process of continued refinement of culture techniques and tumor sampling approach, our large-scale comprehensive collection of GEA avatars represents a unique and valuable preclinical experimental resource for precision oncology. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=76 SRC="FIGDIR/small/663874v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@f8a032org.highwire.dtl.DTLVardef@dd6fa3org.highwire.dtl.DTLVardef@1cc558corg.highwire.dtl.DTLVardef@492a5_HPS_FORMAT_FIGEXP M_FIG Schematic depiction of GEA live-banking workflow C_FIG

cancer biology↗

bioRxiv2025

Light-up nanostructures with allosteric DNA mimics of GFP

In this study, we present a systematic approach for the rational design of synthetic allosteric DNA aptamers. This methodology enables precise control over the allosteric ON-OFF transition in fluorescent DNA aptamers, allowing for the engineering of aptamers with highly tunable fluorescent properties. When combined with toehold-mediated strand displacement, we have developed a series of allosteric aptamers in which the target sequence functions as a specific allosteric modulator. Furthermore, these aptamers have been applied in synthetic DNA computing and in the construction of responsive nanostructures that light up upon activation.

synthetic biology↗