Biology subjects

Tan, W.

Publications and source records attributed to Tan, W..

At least 19 recordsLinked to original sources

bioRxiv2026

Lipid Imbalance Generates Golgi Whorls that Sequester Small GTPases

Small GTPases are generally viewed as organizers of organelle identity, with different families recruited to specific membranes by compartment-selective targeting mechanisms. Here, we identify a membrane state that reverses this relationship. Excessive peptide S-palmitoylation at Golgi generates multilamellar, filipin-poor whorls that recruit ARF, Rab, and Rho family GTPases normally associated with distinct cellular compartments. The whorls simultaneously excluded Golgi transmembrane residents, coat proteins, ER proteins, a GPI-anchored protein, and other palmitoylated proteins, demonstrating that they were selective membrane compartments rather than nonspecific protein aggregates. Preventing myristoylation of ARF6 or geranylgeranylation of Rab11a strongly reduced recruitment, whereas prenylation alone was insufficient, indicating recognition of a composite membrane-targeting code. Lowering cellular cholesterol promoted whorl formation, whereas cholesterol supplementation suppressed it. Chemically distinct lipid perturbations generated GTPase-positive Golgi whorls, suggesting convergence on a shared membrane-remodeling state. As whorls accumulated, endocytic recycling and anterograde trafficking declined, survival signaling decreased, and viability became poorly reversible. These findings show that lipid imbalance can redirect small GTPases across normal organelle boundaries, converting Golgi-derived membranes into selective sinks for trafficking regulators.

cell biology↗

bioRxiv2026

Super-Resolution Visual ProteomEx for Hard Tissues and Clinical Samples

Correlating nanoscale tissue architecture with unbiased molecular composition within the same specimen remains a fundamental challenge in spatial biology. Current spatial proteomics methods either lack the imaging resolution required to resolve nanoscale tissue architecture or achieve only limited proteome coverage, and untargeted approaches capable of deep protein identification have yet to be integrated with super-resolution imaging within a single workflow. Here, we present microProteomEx, an integrated platform that combines hydrogel-assisted tissue expansion with mass spectrometry-compatible fluorescence imaging, laser capture microdissection, and bottom-up proteomics to achieve simultaneous three-dimensional super-resolution imaging (effective lateral resolution down to [~]47 nm on conventional diffraction-limited microscopes) and spatially resolved proteomics at a scalable lateral resolution of 29-100 {micro}m (0.02-0.28 nL volumetric resolution). By optimizing fixation, protein anchoring, and a secondary re-embedding strategy, we extend the method to mechanically resilient tissues, including mouse kidney and heart, as well as to formalin-fixed, paraffin-embedded clinical specimens. We demonstrate single-glomerulus and single-plaque proteomics (450-1,000 proteins per structure), resolve proteomic differences between malignant melanoma and giant congenital melanocytic nevus in a rare pediatric case, and characterize the morphology-resolved molecular heterogeneity of cored versus diffuse amyloid-beta plaques in a mouse model of Alzheimers disease across two disease stages. microProteomEx establishes a broadly accessible framework for correlating tissue ultrastructure with deep spatial proteomics, with direct implications for disease biology, biomarker discovery, and precision medicine.

biochemistry↗

bioRxiv2026

Architecture of a portal complex embedded in the poxvirus core

Gene transcription within the viral core is a unique feature of poxvirus replication. Following entry into the cytoplasm, the poxvirus core dissociates from the lateral bodies and undergoes expansion, functioning as a compartment for early transcription. However, the mechanisms governing molecular exchange between the viral core and the host cytoplasm remain poorly understood. Here, we determine the structures of the portal complex and its pore on the poxvirus core at 7.1 [A] and 4.9 [A] resolution, respectively, using cryo-electron tomography and sub-tomogram averaging. The pore is assembled from three viral proteins, E8, E6, and L3, for which we constructed an atomic model. Structural and channel analyses reveal that the pore satisfies the geometric and electrostatic requirements for the transport of RNA and smaller negatively charged molecules, while excluding double-stranded DNA and cytosolic DNA sensors. Together, our findings establish a structural framework for understanding the assembly and function of the poxvirus portal complex and identify potential targets for antiviral intervention.

biophysics↗

bioRxiv2026

Yawning reveals energy-dynamics mismatch and neural inertia across state transitions

Yawning is a highly conserved behavior, yet its neural dynamics across arousal state transitions remain poorly understood. Classical reflex models fail to account for the precise timing of yawns during large-scale changes in brain network organization. Here, we investigated the neural signatures of yawning using simultaneous electroencephalography (EEG), electromyography (EMG), and kinematic recordings in a beagle model during wakefulness and propofol anesthesia. Propofol-associated yawning exhibited marked temporal asymmetry, with 89.2% of events occurring during emergence from anesthesia. To resolve the fast neural dynamics surrounding these events, we applied empirical mode decomposition coupled with the Hilbert-Huang transform (EMD-HHT) analyses. Across induction, recovery, and wakefulness, yawning was consistently associated with a transient decoupling between local and global network dynamics: a brief increase in local {gamma}-band power coincided with a drop in network flexibility, quantified by instantaneous frequency volatility; IFV). We termed this reproducible motif as "Energy-Dynamics Mismatch" (EDM). A machine learning classifier leveraging EDM features reliably decoded the brain state immediately preceding yawning. We further validated the presence of this signature in an independent human cohort during anesthesia induction. These findings indicate that yawning is not a passive reflex, but is tightly linked to moments of network instability during state transitions. From a computational perspective, EDG may reflect a transient "control effort" that preserves information integration in the presence of "neural inertia." This dynamic signature may provide a quantitative biomarker for monitoring arousal transitions brain-computer interface (BCI) interface state-alerting. Significance StatementYawning is a ubiquitous and evolutionarily conserved behavior, yet its neural basis remains elusive. Using high-resolution neural recordings in a cross-species model, we show that yawning is not a passive reflex, but reliably coincides with a distinct, transient brain-state signature. Specifically, yawning occurs when local high-frequency cortical activity briefly increases while global network flexibility decreases - a pattern we term an "Energy-Dynamics Mismatch" (EDM). We propose that EDM reflects a compensatory neural process engaged during moments of network instability, consistent with overcoming neural inertia to preserve information integration. By identifying this conserved neural marker, this work advances the biological understanding of yawning and suggests a potential biomarker for detecting critical brain states in future BCI.

neuroscience↗

bioRxiv2026

Protein structure-informed deep learning enables species-specific codon optimization

Codon usage bias is highly species-specific, posing a major challenge for heterologous protein expression. Existing deep learning approaches to codon optimization rely primarily on DNA or protein sequence information and largely neglect constraints imposed by protein structure and folding. Here, we present Protein structure-Informed Species-specific Codon Optimization (PISCO), a Geometric Vector Perceptron (GVP)-based model that integrates protein sequence, three-dimensional protein structure, and host codon usage statistics to generate optimal, host-specific codon sequences. Compared with protein-structure-agnostic models, PISCO improves codon recovery by 6% and substantially increases similarity to natural coding sequences, reducing divergence by at least 42% in Codon Similarity Index (CSI), 50% in Codon Frequency Distribution (CFD), and 14% in Dynamic Time Warping (DTW) metrics. Ablation analyses demonstrate that incorporating protein folding kinetics and host-specific information is critical to these gains. Moreover, by leveraging host codon usage statistics, PISCO generalizes to optimize codon sequences for species absent from the training data. An autoregressive variant of PISCO further enhances concordance with natural codon usage patterns, at the cost of a modest reduction in codon recovery rate. Wet-lab validation confirms that PISCO-optimized sequences significantly enhance protein solubility and functional expression. Together, these results establish protein structure as a key determinant of species-specific codon optimization and provide a transferable framework for structure-aware gene design.

molecular biology↗

bioRxiv2026

Programming Biomolecular Interactions with All-Atom Generative Model

Biomolecular interactions lie at the core of cellular life, spanning diverse molecular modalities from small molecules to nucleic acids and proteins. Nevertheless, design strategies remain separated despite shared physicochemical principles of molecular recognition. Here we present AnewOmni, a unified generative framework trained on more than 5 million biomolecular complexes, that enables transferable molecular design across molecular scales by assembling chemically meaningful building blocks at atomic resolution. We further introduce programmable graph prompts to support user-defined chemical, topological, and geometric steering during generation, exploring hybrid and unconventional chemistries beyond canonical structures. We demonstrate that transferable learning of interaction patterns and physical constraints across molecular modalities is possible, via an atom-to-block latent space capturing both atomic details and structural priors. The framework successfully designed small molecules, peptides, and nanobodies targeting the challenging KRAS G12D switch II pocket, as well as orthosteric peptides and allosteric small-molecule inhibitors for PCSK9 in the absence of known binding site, achieving 23%-75% success with only low-throughput validation, bypassing modality-specific high-throughput screening. AnewOmni is the first to succeed in functional molecular design across all scales, from small chemical entities to large biologics, and represents a stepstone towards general molecular reasoning engines, advocating a generative foundation model for biomolecular interactions to enter regimes where data and human intuition remain limited.

bioengineering↗

bioRxiv2026

Learning the All-Atom Equilibrium Distribution of Biomolecular Interactions at Scale

Biomolecular functions are governed by dynamic conformational ensembles rather than static structures. While models like AlphaFold have revolutionized static structure prediction, accurately capturing the equilibrium distribution of all-atom biomolecular interactions remains a significant challenge due to the high computational cost of molecular dynamics (MD). We present AnewSampling, a transferable generative foundation framework designed for the high-fidelity sampling of all-atom equilibrium distributions, which is the first model to faithfully reproduce MD at the all-atom level. It uses a quotient-space generative framework to ensure mathematical consistency and leverages the largest self-curated database of protein-ligand trajectories to date, with over 15 million conformations. Statistically, AnewSampling consistently outperforms all prior generative methods on the ATLAS monomer benchmark, and the all-atom capabilities of AnewSampling enable close statistical alignment with ground-truth MD for evaluating atomic biomolecular interactions in protein-ligand dynamics. Furthermore, AnewSampling successfully recovers coupled ligand and side-chain motions in CDK2 systems, overcoming a major sampling hurdle inherent to conventional MD. AnewSampling enables rapid exploration of conformational landscapes prior to intensive simulations, elucidating fundamental biophysical mechanisms and accelerating the broader design of functional biomolecules.

bioinformatics↗

bioRxiv2026

Harmonizing Peak Matching Between Multidimensional NMR Spectra

A common task in analysis of multidimensional NMR is the mapping of cross-peaks from one spectrum to another. In some situations, only a subset of coordinates of cross-peaks are to be matched such as in comparing corresponding dimensions of triple resonance assignment spectra. In other cases, the sample is perturbed in some way, and the task is to map corresponding cross-peaks that potentially change in any and all dimensions. This exercise is commonly done "by hand" and is both time-consuming and subjective. It is difficult for an individual to consider all possible interpretations of deviations between two multidimensional NMR spectra. Furthermore, in regions of high degeneracy, cross-peak matchings between spectra can be ambiguous. Ideally, a mapping algorithm should reflect a confidence of its matchings to indicate the reliability of proposed matchings and should do so while harmonizing all potential mappings in the spectrum. Critically, this process should be automated using criteria that are both well-defined, consistent and provide a measure of reliability. Here we develop a novel model describing the distribution of apparent deviations between cross-peaks of two multidimensional NMR spectra to random noise and true deviations to harmonize the cross-peak matching. Bayesian inference is employed to provide confidence estimates. The resulting algorithm (pHarmony) is tested in a variety of ways such as mapping between pairs of triple resonance spectra and between two- and three-dimensional heteronuclear NMR spectra generated by a fragment-based ligand discovery screen.

biophysics↗

bioRxiv2026

Regulation of CtISWI activity by AutoN and HSS domain

Chromatin remodeler imitation switch (ISWI) plays an important role in regulating chromatin structure through sliding and spacing nucleosomes. Despite the enormous progress in regulatory elements and mechanisms of the activity of ISWI in recent years, there are still some unclear structures and mechanisms in different species. Here, we studied the ATPase activity and nucleosome binding affinity of Chaetomium thermophilum ISWI (hereafter referred to as CtISWIWT) and several mutants, further proving the importance of these mutated residues in the inhibition of AutoN. We also analyzed the effects of dsDNA and ssDNA on ATPase activity of CtISWI, suggesting the potential interaction between HSS and ATPase domain. Notably, we provided a predicted structural model based on the sequence of CtISWIWT, proposing a two-step activating mechanism of conformation change and activity regulation. Taken together, our findings elucidate a different model of ISWI self-maintenance and action, providing a new mechanism of regulation supporting chromatin remodeling. HighlightsO_LIStructural modeling of ISWI: a chromatin remodeler that couples to ATP hydrolysis to slide and space composition of nucleosome. C_LIO_LIThe ATPase activity of ISWI can be stimulated by exogenous DNA, with opposite promoting effects by dsDNA and ssDNA. C_LIO_LIThe mechanism by which ISWI is activated upon binding with nucleosome has been the subject of debate, and a more comprehensive mechanism for regulation of ISWI activity. C_LI SignificanceIn the past decades, a variety of regulatory mechanisms of the activity of chromatin remodeling factor ISWI have been proposed. Based on the hypothesis of nucleosome complex structure analysis, these studies attempted to explore the mechanism of chromatin remodeling, a gene expression regulation activity. However, previous studies have basically focused on the binding and regulation mechanism of ISWI ATPase domain and nucleosomes, without mentioning the activity mode of full-length ISWI. Therefore, our study mainly focuses on the nearly full-length ISWI containing HSS domain, exploring the mechanism of the active state transition of ISWI in remodeling activities from this perspective. It enriches and supplements the research on chromatin remodeling, an important physiological activity.

biochemistry↗

bioRxiv2026

PartiNet is a dynamic adaptive neural network for high-performance particle picking in cryo-electron microscopy

Accurate, efficient and autonomous particle picking is a major bottleneck in high-resolution cryo-electron microscopy (cryo-EM). We introduce PartiNet, an Artificial Intelligence (AI)-based particle picker with size-agnostic detection and pre-trained models that eliminate manual parameter specification and dataset-specific training, pioneering dynamic neural network inference for single particle cryo-EM pipeline. Unlike static architectures, PartiNet employs a dynamic framework that adjusts network complexity in real-time based on perceived micrograph quality. This adaptive approach accelerates inference up to 7-fold compared to existing tools without sacrificing particle selection quality. Training on diverse protein datasets showed that PartiNet improves particle yields, enhances sampling of rare orientations, and is compatible with on-the-fly workflows. Comprehensive evaluation on benchmark datasets and validation on a new dataset of the chromatin remodeler MORC2 demonstrates superior precision and recall, with the ability to detect heterogeneous protein species, leading to more complete structural models and consistently higher-resolution reconstructions.

molecular biology↗

bioRxiv2026

INTS12 Bridges Integrator and NELF to Prevent the Release of Non-processive RNA Polymerase II Complexes

Promoter-proximal RNA Polymerase II (RNAPII) pausing and the processivity are controlled by distinct modules of the Integrator complex, which together fine-tune transcription and protect against the accumulation of defective RNAPII complexes. Compromised activity of individual Integrator modules has been linked to human disease including cancer and developmental disorders, caused by defective transcription of protein-coding or small-nuclear RNAs. Despite extensive characterisation of the Integrator complex both genetically and structurally, the role of smallest member of the complex, INTS12, has remained enigmatic. Here, we uncover that INTS12 loss acts to stabilise the association between NELF and Integrator via its PHD domain and N-terminus, respectively, thus safeguarding against the release of defective RNAPII complexes. Acute degradation of INTS12 results in the selective dissociation of Integrator from the NELF-RNAPII complex which subsequently convert to their canonical paused form from which they can be released by CDK9. In the absence of INTS12 excess release of defective RNAPII via P-TEFb/SEC, loss of the ARMC5 salvage pathway and deletion of the catalytic and core Integrator subunits is toxic to cells. These findings demonstrate that there is interconversion between canonical paused RNAPII and paused-Integrator, and highlight the critical interplay between these processes and P-TEFb mediated pause-release to ensure that only transcription competent complexes are released into elongation. O_LIINTS12 degradation confers CDK9 inhibitor resistance and triggers cellular stress through a phosphatase module-independent mechanism. C_LIO_LIINTS12 stabilizes the Integrator-NELF complex through its N-terminus and PHD domain. C_LIO_LIAcute INTS12 degradation promotes aberrant release of promoter-proximal RNA polymerase II complexes. C_LIO_LIRNA polymerase II complexes released upon INTS12 loss exhibit defective elongation and reduced processivity. C_LIO_LIINTS12 loss removes Integrator from RNAPII resulting in aberrant paused-state from which it can be released by CDK9. C_LIO_LIExcess CDK9 activity and ARMC5 loss are synthetically lethal with INTS12 deficiency. C_LI

molecular biology↗

bioRxiv2025

Structural insights into the specific recognition of H2A.Z-H2B dimer by the catalytic subunit of SRCAP chromatin remodeling complex

Chromatin remodeling complexes (SRCAP-C) mediate the exchange of H2A.Z with H2A, leading to the incorporation of H2A.Z-H2B dimers into chromatin through a step-by-step manner. Here, we determined the crystal structure of the N-terminal region (531-560) of the catalytic subunit of SRCAP-C, termed SRCAP-Z domain, in complex with the engineered single-chain H2B-H2A.Z (scH2B-H2A.Z) at 2.53 [A] resolution. In the crystal structure, two molecules of scH2B-H2A.Z and one molecule of SRCAP-Z form a sandwich-like architecture. Histones form typical histone fold and SRCAP-Z domain adopts a short 310 helix. In details, Val551, Leu554, and Leu555 of the SRCAP-Z 310 helix specifically recognize the C helix of H2A.Z through hydrophobic interactions. The particular recognition has been validated in vitro by MBP-pulldown and isothermal titration calorimetry (ITC) experiments, and the MBP-pulldown assay results demonstrated that mutations in specific amino acids of SRCAP-Z attenuated its interaction with H2A.Z-H2B dimer. Finally, we demonstrated that SRCAP-Z recognizes H2A.Z-H2B dimer with a conservative structural basis and facilitates the nucleosome assembly by its chaperone activity. HighlightsFirstly, we determined the structure of the SRCAP-Z domain/scH2A.Z-H2B complex at 2.53 [A] resolution. Second, our results support a mechanism of H2A.Z-H2B/H2A-H2B exchange model in which YL1 enriches H2A.Z/H2B around nucleosomes, presenting them to SRCAP, which mediates the exchange of H2A.Z/H2B with H2A/H2B. Third, SRCAP-Z recognition of H2A.Z-H2B dimer is structurally conserved. Fourth, a distinct sandwich-like architecture: SRCAP-Z adopts a 310 helix that inserts precisely between H2A.Z and H2B, forming a stable, unexpected structural module.

biochemistry↗

bioRxiv2025

Engineered Transdermal Peptide-Recombinant Type III Collagen Hydrogel with Biological Efficacy in Cell Proliferation and Wound Healing

Collagen, as a major structural protein in the extracellular matrix, plays a crucial role in tissue regeneration; however, traditional collagen sources often suffer from immunogenicity, poor stability, and batch-to-batch variability. In this study, a novel transdermal peptide-recombinant type III collagen hydrogel was developed, which has excellent biocompatibility, thermal stability, and skin repair effects. Transdermal peptide-recombinant type III collagen was expressed and purified by genetic engineering methods, and its potential for biomedical applications was further evaluated. The experimental results showed that the prepared collagen had a high purity (95%) and retained the unique secondary structure of collagen, showing good structural stability at different pH values. Through cell proliferation experiments and mouse wound healing experiments, we verified the superior effect of the collagen hydrogel in promoting wound healing and significantly accelerating wound healing at concentrations as low as 0.2 mg/mL. This achievement provides strong experimental support for its application in clinical skin wound repair.

biochemistry↗

bioRxiv2025

Cycling Molecular Assemblies (CyMA) for Ultrasensitive Golgi Imaging

The Golgi apparatus is central to intracellular trafficking, yet its dynamic visualization remains constrained by probes that require high concentrations and long incubations. Here we present cycling molecular assemblies (CyMA), a design concept that harnesses endogenous dynamic enzymatic futile cycle to drive ultrasensitive imaging. The BODIPY-CyMA probe operates through reversible palmitoylation-depalmitoylation mediated by palmitoyl acyltransferases and thioesterases, establishing a nonequilibrium steady-state that actively concentrates the probe at the Golgi. This enzymatic cycling converts diffusion-limited localization into self-amplifying signal generation, enabling morphology imaging at concentrations as low as 100 pM and real-time tracking of Golgi dynamics within minutes at nanomolar levels. This probe requires minimal incubation time, exhibits negligible cytotoxicity, faithfully reports pharmacological Golgi disassembly, and functions in vivo in Drosophila larvae. BODIPY-CyMA exemplifies how coupling molecular self-assembly to endogenous enzymatic cycles affords a general strategy for constructing dynamic, non-perturbative probes for live cell and in vivo imaging.

biochemistry↗

bioRxiv2025

Deep Learning Enables Automated Segmentation and Quantification of Ultrastructure from Transmission Electron Microscopy Images

Transmission electron microscopy (TEM) has become an essential technique for observing subcellular ultrastructure, and is widely used in both clinical diagnosis and biomedical research. However, analysis of TEM data remains extremely labor-intensive and often inconsistent across operators due to the lack of dedicated computational methods. Here, we present TEAMKidney, a deep learning framework for accurate and scalable measurement of ultrastructures in TEM images across species, magnifications, and instrument platforms. We collected 12,991 TEM images from patients with multiple kidney diseases and from different animal models. By combining a self-training-based semantic segmentation stage with a TEM-tailored panoptic segmentation model, we address two major challenges in TEM data analysis: the lack of accurately labeled training data and the difficulty of achieving high segmentation accuracy for complex ultrastructure. Application of TEAMKidney to both human and animal images successfully reveals disease-associated changes in two critical glomerular ultrastructures: the glomerular basement membrane and podocyte foot processes. In addition to significantly outperforming existing tools, TEAMKidney shows close agreement with pathological expert measurements used in clinical assessment protocols. By reducing dependence on manual tracing while preserving expert-level accuracy, TEAMKidney demonstrates that deep learning can substantially reduce the burden of image analysis in both clinical pathology and biomedical research settings.

bioinformatics↗

bioRxiv2025

LRP8 is a Receptor for Yellow Fever Virus

Yellow fever virus (YFV), an arbovirus causing substantial human morbidity and mortality, was the first human virus discovered over a century ago. The live-attenuated 17D vaccine is among the most successful vaccines in medicine. Despite the importance of YFV, its receptor has remained unknown. Here, we performed a barcoded, genome-wide human ORF library screen and identified LRP8 (also named APOER2) as a receptor for YFV. We show that LRP8 expression specifically boosts YFV infection in cell lines by promoting entry. AAV-mediated expression of human LRP8 in mouse liver aggravates infection and pathology. LRP8 knockdown abolishes YFV infection in brain cells, primary human hepatocytes, and notably in mosquitoes. Biochemically, LRP8 directly interacts with YFV particles via the viral envelope protein. This function of LRP8 is conserved across species, particularly in mosquitoes and primates. A soluble LRP8 decoy protein can block YFV infection in vitro and in mice, providing a potential therapeutic or prophylactic strategy. Our findings provide groundwork for understanding YFV entry, tropism, and pathogenesis, and may enable development of novel therapeutics to treat YFV infection.

microbiology↗

bioRxiv2025

Identification of key host genes for influenza A virus in avian cells using a genome-wide CRISPR-Cas9 screen

Influenza A virus (IAV) causes major economic losses to the poultry industry and poses a zoonotic threat to human health. Potential pandemic outbreaks are underpinned by the ability of the virus to jump from one species to another. Host-virus interactions can dictate the success of such events and while systematic studies have successfully mapped host virus interactions in human cells, few studies have been performed in relevant animal host cell lines. Here, we conducted two independent genome-wide CRISPR/Cas9 knockout screens in chicken lung epithelial cells infected with either the human-adapted PR8 vaccine strain or the avian UDL 3:5 reassortant virus encoding PR8 HA, NA and M segments. Rather than selecting solely for cell survival, we used anti-M2 antibody staining and fluorescence-activated cell sorting to capture host factors influencing multiple stages of the IAV life cycle. Across both screens, we identified 104 genes required for efficient replication in chicken cells, including 16 with strong effects (log2 fold change > 2). Comparative analysis with published human screens revealed 17 conserved host factors, 19 human-specific factors, and 42 chicken-specific factors, highlighting potential species-specific interactions. Top hits included genes involved in sialic acid biosynthesis and N-linked glycosylation--SLC35A1, SLC35A2, and the avian-specific influenza polymerase cofactor ANP32A. Functional validation demonstrated that MOGS, MGAT1, DENR, DMXL1, ENO1, IPO9, KLF6, PTAR1, and TSG101 contribute to multiple stages of the IAV life cycle. In particular, MOGS and MGAT1 were essential for N-glycan processing and modulated cell-surface sialic acid abundance, with strain- and species-specific effects. These findings define a genetic landscape of IAV dependency factors in chicken cells and suggest shared and species-specific host requirements that could impact cross-species transmission.

cell biology↗

bioRxiv2025

Programmable Aptamer-Embedded Circular RNAs for Targeted Antigen-Presenting Cells Immunotherapy

The targeted delivery of mRNA to specific cell types in vivo remains a major unmet need in mRNA-based therapeutics. Conventional strategies rely on nanocarriers engineered with various modifications. However, these exogenous materials could cause adverse reactions, and their complex manufacturing processes often hinder clinical application. By leveraging the innate programmability of RNA sequences, we herein report a carrier-free, scalable, and programmable aptamer-embedded circular RNAs (Apt-circRNAs) design that confers targeting capability through the strategic incorporation of different aptamers at varying densities, while retaining circular RNA stability and protein production capability. Experimental results show that antigen-loaded Apt-circRNAs enable targeted delivery to antigen-presenting cells (APCs), drive endogenous antigen expression, activate antigen-specific T cells, and elicit potent immune responses that mediate clearance of both early-and late-stage tumors in mouse models. In humanized models of colorectal cancer, the combination of Apt-circRNA and PD-1 blockade produced synergistic antitumor effects and significantly reshaped the tumor microenvironment. In a first-in-human (FIH) clinical trial, Apt-circRNA vaccine encoding KRAS G12D/G12V neoantigens exhibited a favorable safety profile and induced robust immune activation, T cell mobilization, and neoantigen-specific immune responses. With this study, we have established a new paradigm in carrier-free, APC-targeted RNA vaccine design, offering a safe and effective platform for next-generation cancer immunotherapy.

bioengineering↗