Biology subjects

Li, Z.

Publications and source records attributed to Li, Z..

At least 145 records · Page 8Linked to original sources

bioRxiv2026

Structure of full-length APOBEC3B bound to EBV BORF2 reveals coordinated neutralization of a cancer-associated mutator

The double-domain APOBEC3B (A3B) contains an N-terminal non-catalytic and C-terminal active cytidine deaminase domains (NTD and CTD). A3B restricts viral infection yet is also a major endogenous mutator in human cancer, driving tumor evolution and drug resistance. A previous study showed that the Epstein-Barr virus (EBV) ribonucleotide reductase large subunit BORF2 binds the active site of the A3B CTD and neutralizes the activity of the isolated catalytic domain. However, the three-dimensional organization of full-length A3B (fl-A3B) and the contribution of A3B NTD to BORF2-mediated neutralization have remained unclear. Here, we report a 2.77 [A] cryo-electron microscopy structure of fl-A3B in complex with EBV BORF2. The structure reveals an elongated hetero-octamer comprising two A3B2/BORF22 tetramers linked through alternating canonical and non-canonical BORF2 dimer interfaces. Full-length A3B adopts a defined NTD-CTD arrangement distinct from previously characterized APOBEC3G conformations. The A3B CTD binds BORF2 and occludes access to the catalytic site, while the A3B NTD simultaneously contacts a second BORF2 subunit, stabilizing a previously uncharacterized BORF2 canonical dimer interface required for higher-order assembly. Disruption of either BORF2 dimer interface prevents formation of filamentous A3B-BORF2 assemblies. These findings establish the structural architecture of full-length A3B and reveal how dual-domain engagement by A3B promotes higher-order BORF2 assembly, providing a structural framework for understanding EBV-mediated neutralization of an antiviral and cancer-associated mutator.

Cancer Biology↗

bioRxiv2026

Identification of environmental factors and growth stages in the prediction of fibre yield and fibre quality traits in rain-grown cotton

ContextUnderstanding how and when environmental conditions influence overall crop performance is crucial for optimising the development of genotypes to a specific breeding target environment. We focused on economically important traits of Australian rain-grown cotton including fibre yield and quality traits, which have not been investigated comprehensively. The aim of the study was to identify relevant environmental factors, and the timing and extent of their impact on rain-grown cotton production. MethodsWe used a data driven approach to analyse the relationship between ten climate related environmental factors across various plant growth stages and eight fibre yield and quality traits, using a large-scale field dataset of 9,283 records collected over 23 years at 4 locations, with 53 unique year-location combinations. We applied eight complementary statistical models including stepwise, penalised and Bayesian linear regression, regression-tree based ensemble methods and deep learning frameworks to (1) select the most essential environmental covariates affecting rain-grown cotton production, and (2) evaluate the predictive performance of these models. ResultsThe environmental impacts on rain-grown cotton production were trait and growth-stage specific. Number of rainy days and solar radiation were identified as the most influential environmental factors for fibre yield traits, vapour pressure deficit at maximum daily temperature was the most influential factor for majority of fibre quality traits. However, each analysed trait was influenced by multiple environmental factors across multiple growth stages (rather than a single factor or a single growth stage). These influential covariates explained a wide range of variation in the traits, accounting for 5.8% to 68.2%. Using the best-fit random forest model, our findings revealed non-linear relationships between key environmental covariates and the traits. ConclusionsEnvironmental factors at different rain-grown cotton growth stages are key determinants for the performance of end-of-season fibre yield and fibre quality parameters. These findings highlight the need to account for environment conditions when developing cotton varieties optimised for rain-grown production systems. Potential strategies are proposed whereby these key environmental factors can be used to increase the rate of genetic gain in rain-grown cotton production systems. ImplicationsThe results of this study will be crucial for future genetic evaluations and analyses of genotype-by-environment interaction effects in rain-grown cotton, which must account for the influence of the environment on plant performance. Furthermore, these methods can be applied to other species to identify critical growth stages and environmental factors which most influence crop performance.

bioinformatics↗

bioRxiv2026

A data-driven rediscovery of the specificity-conferring code of adenylation domains in nonribosomal peptide synthetases

Nonribosomal peptide synthetases (NRPSs) are large modular enzymes that assemble structurally diverse peptides, many of pharmacological importance, including antibiotics and immunosuppressants. Within each NRPS module, the adenylation (A) domain selects the substrate to be incorporated, a choice governed by a small set of residues lining the binding pocket. For two decades, computational prediction of A-domain substrate specificity has relied on residue sets--most prominently the Stachelhaus code and the 34-residue "8 [A] code"--that were defined by spatial proximity to the substrate rather than by demonstrated predictive value. Here we revisit which residues govern substrate specificity from a purely data-driven perspective. We assembled a non-redundant dataset of 5,366 A-domain sequences (4,693 bacterial and 673 fungal) and used information-theoretic measures to rank alignment positions by their statistical association with substrate identity, without restricting candidate positions to any predefined structural shell. This procedure yielded two compact, kingdom-specific codes: IG15B (15 positions) for bacterial and IG13F (13 positions) for fungal A-domains. Both match or exceed the predictive accuracy of the 34-residue 8 [A] code while using fewer than half its positions, and both independently recover the majority of the classical Stachelhaus positions. Notably, our analysis identifies four positions (242, 280, 281, and 284) that lie outside all conventional codes yet carry non-redundant specificity information and co-localize with classical determinants on two helices flanking the binding pocket. These positions provide new candidate sites for the rational engineering of A-domain specificity. Author summaryMany clinically important drugs--including antibiotics such as vancomycin and immunosuppressants such as cyclosporin--are nonribosomal peptides, assembled by large enzymes known as nonribosomal peptide synthetases. These enzymes contain adenylation domains that act as molecular gatekeepers, each selecting one chemical building block to add to a growing peptide. Identifying which amino acids within a domain determine this choice is central both to predicting what an enzyme produces and to re-engineering it to make new compounds. For over twenty years, researchers have approached this question by selecting the amino acids that sit physically closest to the substrate. However, being close to the substrate does not guarantee that a residue actually influences substrate selection. In this work, we instead let the data decide: using thousands of adenylation domain sequences, we measured which positions are statistically most informative about the substrate, using information gain, mutual information and{chi} 2 statistic. We found that far fewer positions than conventionally used are sufficient to predict specificity, and--importantly--we identified several influential positions that earlier approaches had overlooked because they lie just beyond the conventional distance cutoff. These positions offer promising new targets for engineering these enzymes to produce novel peptide-based drugs.

bioinformatics↗

bioRxiv2026

SOLiD-MaP: A Photoproximity Labeling Platform for Small Molecule Binding Site Mapping on RNA

RNA-targeting small molecules are emerging as promising therapeutic modalities, but their development requires methods that define binding sites and evaluate RNA target selectivity. Existing approaches for detecting ligand-RNA interactions have provided powerful foundations, yet many rely on direct crosslinking or covalent-capture chemistries whose performance depends on ligand-specific probe design, warhead compatibility, and local reaction geometry. Here, we report Singlet Oxygen footprinting on RNA in a Ligand-Directed manner for Mutational Profiling (SOLiD-MaP), a photoproximity labelling platform for small molecule-RNA interaction analysis. Using the Mango-II aptamer and thiazole orange derivatives as a model system, we establish aniline as an efficient nucleophile for singlet oxygen-mediated RNA labelling and demonstrate target-selective labelling driven by ligand-localized photosensitization. We further show that labelling selectivity can be tuned by chemically constraining the singlet oxygen diffusion with a quencher. Finally, we develop a pairwise reverse transcription stop assay and a mutational profiling with next-generation sequencing readouts to infer ligand-proximal regions and unambiguously map binding sites. SOLiD-MaP provides a new, orthogonal strategy for studying small molecule-RNA recognition and should support RNA-focused mechanism-of-action studies.

biochemistry↗

bioRxiv2026

Steller: a high-resolution platform for spatial clonal tracing of mammalian brain development

Resolving both lineage history and spatial position at single-cell resolution is essential for understanding how tissue assemble, yet simultaneously interrogation of both dimensions remains technically challenging. Here, we present Steller (Spatio-temporal cell lineage tracker), an integrated experimental and computational framework that overcomes the sensitivity bottleneck limiting lineage barcode detection in high-resolution spatial transcriptomics (ST). By co-depositing capture probes alongside conventional poly(T) oligonucleotides on high-density spatial arrays, Steller achieves targeted enrichment of lineage barcodes at spatial single cell resolution. Applied to clonally labeled embryonic day 12.5 (E12.5) mouse forebrain development harvested at postnatal day 4 (P4), Steller increased the proportion of barcode-detectable cells and recovered higher clonal diversity compared with poly(T) chip. Leveraging this enhanced sensitivity, we resolved distinct spatial clonal architectures across three forebrain regions: horizontal or radial-to-horizontal transitions in hippocampal pyramidal neurons, dorsoventrally restricted yet multi-nuclei spread in thalamus, and fate-restricted spiny projection neuron lineages. Steller establishes a generalizable strategy for lineage-enhanced spatial profiling compatible with existing high-resolution spatial transcriptomics platforms and adaptable to diverse biologic process, providing a framewrok for investigating lineage-dependent tissue organization. HighlightsO_LISteller integrates targeted lineage-barcode enrichment with high-resolution spatial transcriptomics C_LIO_LISteller substantially improves clonal detection sensitivity at single-cell resolution C_LIO_LISteller reveals region-specific spatial clonal architectures across the developing mouse forebrain C_LI

Developmental Biology↗

bioRxiv2026

Subregion-Specific Input Organization of Prefrontal-Projecting Basal Forebrain Cholinergic Neurons and Weakened Striatum-to-NBM Inhibitory Transmission in 5xFAD mice

Basal forebrain cholinergic neurons regulate cortical activity and cognition and are vulnerable in Alzheimers disease (AD). However, the upstream circuits controlling projection-defined basal forebrain cholinergic populations remain incompletely understood. Here, we used projection-specific rabies-mediated monosynaptic tracing to map whole-brain inputs to medial prefrontal cortex (mPFC)-projecting cholinergic neurons in the nucleus basalis of Meynert (NBM) and horizontal limb of the diagonal band of Broca (HDB). mPFC-projecting NBM and HDB cholinergic neurons received broad but distinct input patterns. NBM cholinergic neurons received prominent striatal input, including input from D1-expressing medium spiny neurons, whereas HDB cholinergic neurons showed proportionally weaker striatal input and broader non-striatal contributions. Optogenetic electrophysiology confirmed that striatal inputs formed monosynaptic GABAergic inhibitory synapses onto NBM cholinergic neurons. This inhibitory transmission was weakened in 5xFAD mice, indicating impairment of a striatal-NBM inhibitory circuit in an AD mouse model. Together, these findings reveal subregion-specific input organization of mPFC-projecting basal forebrain cholinergic neurons and identify a vulnerable striatal-NBM circuit in AD. HighlightsO_LIWhole-brain rabies tracing reveals input organization of mPFC-projecting BF cholinergic neurons. C_LIO_LINBM and HDB cholinergic neurons projecting to mPFC show distinct monosynaptic input profiles. C_LIO_LIStriatal D1-MSNs are a major input source to mPFC-projecting NBM cholinergic neurons. C_LIO_LIStriatal-NBM inhibitory transmission is functionally impaired in 5xFAD mice. C_LI

neuroscience↗

bioRxiv2026

Robust integration of weakly anchored spatial multi-omics

Spatial multi-omics holds great promise for dissecting complex biological processes, though inherent technical constraints continue to limit its widespread adoption. Currently, most studies therefore measure distinct omics features on separate tissue sections, necessitating spatial diagonal integration. An emerging practical solution is to leverage hematoxylin and eosin (H&E) images as an integration anchor, given their ubiquity, low cost, and compatibility across tissue preparations. However, this anchor is frequently compromised in real-world settings by variations in H&E staining style, absence of reliable histological landmarks, and mismatches in spatial resolutions across omics modalities. To address this, we introduce SpaWeaver, a computational framework that couples a pathology foundation model with a graph Transformer and a latent feature aligner module, providing a highly robust solution for weakly anchored spatial omics data diagonal integration. Extensive experiments demonstrate that SpaWeaver exhibits superior robustness against isolated or synergistic weak-anchoring factors. The spatial multi-omics profiles generated by SpaWeaver link molecular features originally separated on two sections, unlocking diverse downstream analyses once exclusive to co-assayed spatial multi-omics data, including niche-aware cell-cell communication inference and multi-omics resolved cell state. In this study, it unveils tumor-distance-dependent fibroblast-CD4{square}T-cell signaling in human colon adenocarcinoma and identifies a hypoxic glycolytic tumor state with pyknotic nuclei in human ovarian cancer. Overall, our approach bridges readily accessible single-omics measurements across weakly anchored tissue sections, enabling unified spatial multi-omics characterization and system-level tissue analysis.

bioinformatics↗

bioRxiv2026

Cardiomyocytes Undergo a Mesenchymal-Like Fate Transition in Myocardial Fibrosis

BACKGROUNDMyocardial fibrosis, a pathological hallmark of adverse cardiac remodeling and heart failure, has been conventionally attributed to the activation of resident fibroblasts. Although recent studies suggest contributions from non-fibroblast lineages, direct in vivo genetic evidence that cardiomyocytes can undergo a mesenchymal-like fate transition during myocardial fibrosis remains absent. This study aims to investigate whether such a transition occurs and to elucidate the underlying regulatory mechanisms. METHODSHuman myocardial infarction (MI) tissues were analyzed by immunohistochemistry and integrated with public single-nucleus RNA sequencing (snRNA-seq) data to detect mesenchymal-like signatures in cardiomyocytes. Genetic lineage-tracing was performed in MI mice, and in cardiomyocyte-specific Hgs (hepatocyte growth factor-regulated tyrosine kinase substrate) gene knockout mice, to map the fate of cardiomyocyte-derived cells. Mechanistic insights were obtained through proteomic and snRNA-seq analysis of Hgs knockout hearts and validated through gain- and loss-of-function experiments targeting Aldh1a2 (aldehyde dehydrogenase 1 family member A2). RESULTSIn human MI samples, a subset of cardiomyocytes showed reduced expression of cardiomyocyte markers concurrent with acquisition of mesenchymal-associated markers. Genetic lineage tracing demonstrated that adult cardiomyocytes can adopt a mesenchymal-like cell fate during post-MI remodeling. We identify HGS as a factor constraining this transition. Hgs knockout in adult cardiomyocytes upregulated Aldh1a2, triggered the mesenchymal-like fate transition, and gave rise to cells expressing markers of activated fibroblasts or osteoblasts, accompanied by pronounced myocardial fibrosis and calcification. Forced Aldh1a2 overexpression in cardiomyocytes drove the mesenchymal-like fate transition in vitro and in vivo, whereas Aldh1a2 deletion in cardiomyocytes mitigated MI-induced myocardial fibrosis. CONCLUSIONSThis study provides in vivo genetic evidence that adult cardiomyocytes possess the capacity to undergo a mesenchymal-like fate transition under pathological conditions. Our data suggest that HGS and ALDH1A2 serve as regulators of the transition, offering a new basis for understanding cellular and molecular mechanisms of myocardial fibrosis. Novelty and SignificanceO_ST_ABSWhat Is Known?C_ST_ABSO_LIMyocardial fibrosis is primarily driven by resident fibroblast activation, with additional contributions from cardiac CD34+ cells, pericytes, and macrophages. C_LIO_LIAdult cardiomyocytes exhibit phenotypic plasticity and transdifferentiate into epicardial-like or pacemaker cells under specific conditions. C_LI What New Information Does This Article Contribute?O_LIA subset of cardiomyocytes adopts a mesenchymal-like cell fate during myocardial fibrosis, marked by downregulation of cardiomyocyte identity markers and loss of aligned cell-cell contacts. C_LIO_LIThese cells acquire mesenchymal morphology and markers, ECM components, migratory gene signatures, and proliferative capacity. C_LIO_LIHGS and ALDH1A2 act as regulators of this mesenchymal-like fate transition. C_LI Myocardial fibrosis drives heart failure progression, yet the cellular sources of pathological fibroblasts remain incompletely defined. Here, we demonstrate that a subset of cardiomyocytes adopts a mesenchymal-like cell fate during myocardial fibrosis by using an integrated approach combining human MI samples, murine genetic lineage tracing, and snRNA-seq. Mechanistically, we identify HGS and ALDH1A2 as regulators of this transition. Cardiomyocyte-specific Hgs deletion upregulates Aldh1a2, triggering the mesenchymal-like fate transition. Furthermore, Aldh1a2 overexpression drives this transition, while its deletion attenuates MI-induced fibrosis. These findings reveal a previously unrecognized plasticity of adult cardiomyocytes and identify potential therapeutic targets for fibrotic heart disease.

genetics↗

bioRxiv2026

Rust fungi secretomes contain structurally diverse effector families including cysteine-rich metal-binding proteins

Rust fungi are significant threats to global food security, causing substantial damage to crops through their ability to adapt and evolve new strains that overcome resistance. These obligate biotrophs infect host plants by secreting effector proteins that manipulate host physiology to promote infection and colonisation. We used AlphaFold2 to investigate structural conservation among effector proteins for the secretomes of Melampsora lini and four Puccinia species. AlphaFold2 yielded high-confidence predictions for 45.7% of the 27,090 secreted proteins, while 19% were poor quality. Comparative analysis revealed extensive structural diversity across the rust secretomes, with all thirteen known rust Avr proteins belonging to different clusters apart from AvrSr13 and AvrSr33. Nevertheless, there were still numerous large clusters of structurally-related proteins, including 59 clusters with over 50 members each, three of which contained known Avr proteins. Of the major structural families defined in other fungi, the rust species studied here only contained FOLD and ToxA-like families. Structural analysis of cysteine-rich proteins revealed over a thousand effector candidates featuring zinc-binding sites, with approximately 75% predicted to be cytoplasmic effectors. In contrast, cysteine-rich apoplastic effector candidates were characterized by a high frequency of disulfide bonds. One family of predicted metal-binding proteins was greatly expanded in P. graminis f. sp. tritici and includes AvrSr13 and AvrSr33. We confirmed that purified AvrSr13 and AvrSr22 proteins bind to zinc in vitro using biochemical assays. Taken together, structural modeling provides new avenues to study sequence-unrelated effectors and highlights the high degree of diversity in the effector repertoires of rust species.

microbiology↗

bioRxiv2026

HoloCell: A Generative Foundation Model for Holistic Cellular Modeling

Single-cell multi-omics technologies have recently advanced to enable the profiling of epigenomic, transcriptomic, and proteomic layers within individual cells, offering new opportunities to characterize cellular states as integrated biological systems. However, developing a unified framework that can seamlessly integrate diverse omics modalities and remain robust to heterogeneous modality missingness remains challenging. Existing methods are often designed for specific modalities or modality pairs, relying on dataset-specific training or paired measurements. Here we present HoloCell, to our knowledge the first generative foundation model for joint representation learning and generative modeling across all three major single-cell omics modalities, i.e., epigenomics, transcriptomics, and proteomics. HoloCell contains over 860 million parameters and is pretrained on the Human-Multi-Omics-Corpus, which comprises approximately 468 million single-cell profiles across these three omics layers, corresponding to over 425 billion tokens. HoloCell introduces a a simple yet biologically motivated hierarchical tokenization strategy that encodes cis-regulatory elements, genes, and proteins as structured tokens within a shared modeling framework. We evaluated HoloCell across single-omics representation learning, paired multi-omics integration, unpaired multi-omics alignment, and cross-modal generation via iterative diffusion and remasking, demonstrating its superior performance and flexibility across diverse omics tasks. From a representation perspective, HoloCell provides a unified digital mapping of cellular states across multiple omics layers, capturing cell heterogeneity as an integrated system. From a generation perspective, its iterative diffusion and remasking frame-work permits flexible generation orders beyond fixed left-to-right causality, enabling in silico simulation of multi-omics information flow. Together, these capabilities position HoloCell as a versatile foundation model toward the emerging concept of a virtual cell, offering both systematic characterization and generative simulation of cellular systems within a unified framework.

bioinformatics↗

bioRxiv2026

Validation of MHPC512: A Publicly Available Special-Purpose Supercomputer for Molecular Dynamics Simulations of Biomolecular Systems

MHPC512 is a massively parallel, special-purpose supercomputer designed primarily for atomic-level molecular dynamics (MD) simulations of biomolecular systems. It comprises 512 processor units interconnected by a high-speed three-dimensional torus network and employs a custom chip architecture that uses 35-bit fixed-point arithmetic to accelerate computation while controlling precision loss within an acceptable margin. The preprocessor is compatible with GROMACS and AMBER input formats and supports widely used biomolecular force fields (including CHARMM, AMBER, and OPLS/AA), the Neutral Territory method for short-range nonbonded interactions, the k-space Gaussian Split Ewald method for long-range electrostatics, and multiple thermostats, barostats, and integrators. We present a three-tier validation protocol--comparing static energy and virial components, examining ensemble distributions (NVE, NVT, NPT), and evaluating long-time statistical properties--demonstrating that MHPC512 reproduces results consistent with GROMACS and AmberTools. Application examples, including bulk water, dipeptide conformational sampling, folding of fast-folding peptides, membrane-protein systems, lipid self-assembly, and GPCR conformational transitions, further confirm its reliability. MHPC512 has been deployed at multiple supercomputing centers and is publicly accessible, representing a significant advance in high-throughput, large-scale biomolecular MD simulations.

Molecular Biology↗

bioRxiv2026

The engulfment receptor CED-1/MEGF10 activates the GPCR LAT-1/ADGRL3 for apoptotic cell degradation

Efferocytosis, the clearance of apoptotic cells, is crucial for tissue homeostasis, inflammation suppression, and repair. While several G protein-coupled receptors (GPCRs) are involved, the broader role of GPCRs in efferocytosis remains unexplored. Through a genome-wide RNAi screen in Caenorhabditis elegans, we identified the adhesion GPCR LAT-1 as a key regulator of apoptotic cell degradation through the promotion of phagosome maturation. Our secondary RNAi scrween for transcriptional regulators revealed that the transcription factor AST-1 acts downstream of LAT-1 to mediate apoptotic cell degradation. We show that the engulfment receptor CED-1 functions as a ligand for LAT-1, activating a Gs protein/adenylyl cyclase/PKA/AST-1 signaling cascade and inducing the transcription of vps-34 and piki-1, which encode phosphatidylinositol 3-kinases essential for PtdIns3P generation on phagosomes. This pathway maintains appropriate VPS-34 and PIKI-1 levels for efficient efferocytosis. Notably, LAT-1 is evolutionarily conserved, with homologs in Drosophila (CIRL) and mammals (ADGRL3) performing similar functions. These findings reveal a conserved CED-1/MEGF10-LAT-1/ADGRL3 axis that orchestrates apoptotic cell clearance via a novel transcriptional regulatory pathway, providing new insight into the molecular mechanisms underlying tissue homeostasis and diseases associated with defective efferocytosis, including autoimmunity and neurodegeneration.

cell biology↗

bioRxiv2026

Charting Cervical Spinal Cord Morphometry Across the Lifespan

Spinal cord morphometry provides essential biomarkers of neurological health, but clinical interpretations are confounded by inter-subject variability and a lack of normative references across the full human lifespan. We address this gap by generating the first comprehensive lifespan charts for cervical spinal cord morphometry. We leveraged 30 population-based brain MRI datasets, aggregating 78,269 scans from 41,042 individuals (ages 0-100) whose imaging protocols included cervical cord coverage. To overcome contrast variability, we employed a state-of-the-art contrast-agnostic deep learning segmentation method, extracting cross-sectional area (CSA), anteroposterior (AP) and right-left (RL/transverse), and shape indices (compression ratio, eccentricity, and solidity) from C1 to C7. Normative trajectories were modeled using Generalized Additive Models for Location, Scale, and Shape (GAMLSS). The resulting charts reveal distinct non-linear lifespan changes: rapid growth through childhood and adolescence, peak maturation occurring in early-to-mid adulthood (e.g., mid-30s for CSA), followed by gradual decreases. Significant regional variations along the cervical cord and consistent sex differences (males > females for size metrics) were quantified. Spinal cord trajectories showed strong temporal coupling with brain white matter and brainstem volumes, suggesting integrated CNS development and aging. These lifespan charts provide a robust normative framework, enabling age- and sex-specific centile scoring of individual spinal cord morphometry. This resource offers a critical tool for differentiating typical variation from pathological changes, enhancing the clinical utility of spinal cord MRI in studies of development and neurodegeneration.

neuroscience↗

bioRxiv2026

Chaperonin recognition of protein dynamics drives drug resistance

The emergence of drug resistance is typically driven by mutations that alter drug-target affinity, yet the role of host cellular machinery regulating these processes remains unclear. Here, we reveal that the chaperonin GroEL/S promotes drug resistance through recognition of protein dynamics. Using directed evolution of E. coli DHFR under antibiotic stress and varying GroEL/S expression, we identify a well-folded resistance variant whose fitness, despite tight inhibitor binding, is critically potentiated by GroEL/S engagement. X-ray crystallography, NMR, molecular dynamics and kinetic modeling reveal that millisecond-timescale flipping of the M20 loop generates steric accessibility and a kinetic window for chaperonin interaction that forcibly displaces tightly bound inhibitors, thereby overriding thermodynamic equilibrium of inhibitor binding to restore the active enzyme pool and preserve metabolic flux. Our findings not only reveal a novel paradigm of "dynamic recognition" where both conformational kinetics and distribution govern chaperonin recognition but also establish chaperonins as "deligandases" that actively modulate in vivo drug binding, suggesting that chaperone surveillance of the cellular proteome extends beyond quality control to govern native protein function. This mechanism defines a previously unrecognized route for the rapid development of drug resistance, with implications for understanding therapeutics of microbial infections and human malignancies.

biophysics↗

bioRxiv2026

TetraFuse: A Synergistic Four-Dimensional Dynamic Fusion Framework for Efficient and Robust Medical Image Classification

Accurate and robust classification of medical pathology images is pivotal for computer-aided diagnosis. However, the deployment of deep learning models in high-throughput clinical screening faces a fundamental challenge: the trade-off between diagnostic accuracy and computational efficiency. Current lightweight architectures, while reducing parameter complexity through grouped convolutions, often lead to cross-channel information isolation and diminished representational capacity. In this paper, we propose TetraFuse, a novel framework that systematically integrates features from four complementary domains: space, channel, statistics, and frequency. TetraFuse introduces a novel Cross-Channel Dynamic Aggregation (CCDA) paradigm that reconstructs global channel topology with negligible computational overhead, resolving the inter-group isolation issue. To balance perceptual fidelity and efficiency, we design a stage-aware local enhancement mechanism: Local Variance-Guided Enhancer (LVGE) is employed to filter out shallow-stage background noise, while High-Frequency Boundary Injection (HFBI) reinforces deep-stage pathological contours, preventing spatial over-smoothing. Experimental results on the COVID-19, ISIC 2018, and Kvasir datasets confirm that TetraFuse outperforms state-of-the-art (SOTA) methods. Notably, TetraFuse-Tiny achieves a transformative 91.53% reduction in FLOPs compared to ResNet50; on the Kvasir dataset, it achieved an accuracy of 0.926 and an AUC of 0.994 with only 0.345G FLOPs. By combining high representational power with minimal computational demand, TetraFuse offers a scalable solution for large-scale medical image analysis, especially in resource-constrained clinical environments.

bioinformatics↗

bioRxiv2026

Tracking multi-site somatic voltage dynamics via high-speed fiber photometry

Investigating neural circuit dynamics across distributed brain regions in awake, behaving animals is crucial for understanding complex behavior. Genetically encoded voltage indicators (GEVIs) offer a powerful approach to tracking transmembrane voltage with high temporal and cellular specificity. However, scaling high-sensitivity GEVI recordings across multiple brain regions and multiple animals simultaneously remains a major technical challenge. Furthermore, it is unclear whether soma-targeted GEVIs - typically used for single-cell resolution imaging - can be effectively adapted for fiber photometry. Here, we show that a sCMOS-based widefield imaging system achieves sensitive dual-color multi-site fiber photometry using soma-targeted GEVI indicators with high temporal resolution. We validated this approach in the mouse hippocampal CA1, capturing theta (3-10Hz) and gamma (30-80Hz) rhythms and theta-gamma cross-frequency coupling. Additionally, we recorded high-frequency neural entrainment (>100 Hz) and somatic depolarization induced by electrical stimulation in CA1. Lastly, we tracked synchronized neural activity between the bilateral CA1s as well as multi-site dual-color imaging across CA1 and cortex simultaneously in three freely running mice. This work provides a scalable, accessible platform for high-speed optical electrophysiology in distributed neural circuits. Key points- Implementation of a sCMOS-based widefield imaging setup for sensitive and scalable fiber photometry and cellular imaging. - Demonstration of population multi-site and inter-animal voltage imaging with soma-targeted genetically encoded voltage indicators. - Tracking of high-frequency gamma and high-gamma (>100Hz) neural entrainment

neuroscience↗

bioRxiv2026

Nature-inspired Nanoparticle Adiposomes Enable Targeted Delivery of Hydrophobic Drug for Anti-Cancer Treatment

The predominance of hydrophobic molecules in drug pipelines poses a fundamental delivery challenge in the aqueous physiological environment. Inspired by the endogenous lipid-transport machinery of lipid droplets and lipoproteins, adiposome was developed as a biocompatible platform for hydrophobic drug delivery. Here, docetaxel (DTX) was selected as a model hydrophobic chemotherapeutic agent to evaluate the therapeutic versatility of adiposome. Non-targeted DTX-loaded adiposomes (DTX-Ad) reduced systemic toxicity by avoiding the allergenic excipients Tween 80 and ethanol used in commercial DTX formulations. The cytotoxic mechanism and intracellular responses of DTX-Ad were comprehensively characterized. To boost antitumor efficacy, three tumor-targeting DTX-Ad formulations were subsequently engineered. Lung-targeting DTX-adiposomes (Lung@DTX-Ad), mediated by AAM-B1-28-CRGDK fusion peptide/NRP1 axis, enhanced antitumor efficacy in a lung metastasis model. BCMA-targeting DTX-adiposomes (BCMA@DTX-Ad), conferred by biotin-avidin-mediated antibody conjugation, achieved sustained suppression in a multiple myeloma model. Liver-targeting DTX-adiposomes (Liver@DTX-Ad), enabled by the ApoE/LDLR axis, outperformed both commercial DTX injection and sorafenib in hepatocellular carcinoma models. Taken together, these results demonstrate adiposome as a promising and broadly applicable drug delivery platform, with considerable potential for clinical translation across diverse malignancies.

cancer biology↗

bioRxiv2026

Dietary fiber intake associates with improved survival and microbiomecomposition in allogeneic hematopoietic cell transplantation

Diet is linked to changes in gut microbiota and metabolite production with clinical relevance in several disease settings, although these effects remain poorly defined. We performed prospective, real-time diet monitoring (37,929 food items, 3,837 patient days) and longitudinal microbiome and metabolite profiling (1,230 fecal samples) in a clinical cohort of 173 patients undergoing allogeneic hematopoietic cell transplantation. Patients with pre-transplant fiber intake above the cohort average had significantly improved overall survival (p=0.014) and reduced incidence of grades 2-4 acute graft-versus-host disease (GVHD) (p=0.032) post-transplant. Those consuming insoluble fiber had increased microbial diversity, enriched butyrate-producing taxa, and depleted Enterococcus. Those who developed lower gastrointestinal GVHD had reduced fecal butyrate levels. In a GVHD preclinical model, we confirmed that a fiber-enriched diet increased survival, cecal butyrate, and regulatory-to-conventional T cell ratio. Thus, we demonstrated that dietary fiber has clinical significance as a modifiable factor with microbiome-mediated effects.

cancer biology↗