ACS Nano

Cell membrane-coated nanoparticles (CNPs) are a potentially transformative biomimetic targeted-delivery platform, which can engage therapeutic targets through source-cell membrane protein functions or homotypic interactions. However, their therapeutic development is limited by the current inability to accurately resolve membrane coating completeness, and CNP particle-to-particle variation. Here, we introduce a STochastic Optical Reconstruction Microscopy (STORM)-based approach that resolves population composition and quantifies membrane coating coverage at the single-particle level. Applying it to dendritic cell membrane- and HeLa cell membrane-coated nanoparticles (DCmPs and HeLamPs), we revealed substantial heterogeneity within both particle types and a cell-type dependence of coating outcomes, corroborated by confocal imaging and flow cytometry. We also quantified membrane protein composition, including peptide major histocompatibility complex class I (pMHC-I) among DCmPs, and confirmed that DCmPs preferentially engaged antigen-specific T cells in coculture. This single-particle framework establishes a quantitative standard for CNP characterization, providing a foundation for quality control and rational design.

Rapid DNA transport limits the temporal resolution of solid-state nanopore sensing. Here we show that breaking pore symmetry through geometric inclination produces exceptionally prolonged DNA residence without surface functionalization or external trapping. For 500-base-pair double-stranded (ds) DNA ,13 nm diameter SiNx pores in tilted membranes exhibit a distinct long-lived population with a mean dwell time of 11.1 seconds at 600 mV bias, exceeding previously reported dsDNA dwell times by at-least 4 orders of magnitude. Controlled pore tilting reproduces the population of prolonged events, whose prevalence and duration depend on ionic strength. TEM-EELS based thickness measurements exclude substantial membrane-thickness differences, while continuum and atomistic simulations support a mechanism coupling electric-field redistribution to off-axis DNA motion, increased pore-wall contact and suppressed axial mobility. These findings establish geometric inclination as a passive design variable for engineering molecular residence in solid-state nanopores and provide a route towards longer observation windows for single-molecule sensing.

Selectively perturbing pathogenic membranes while preserving host-cell integrity is a fundamental challenge in the design of membrane-active biomaterials. This challenge is particularly acute for enveloped viruses because their lipid membranes are derived from host cells and therefore share many of the same molecular constituents. Here, we demonstrate that engineered nanochirality provides a structural parameter for distinguishing virus-organized membrane nanodomains from host-cell membranes. Histidine-functionalized graphene quantum dots (His-GQDs) form enantiomeric nanoscale structures with distinct interfacial topologies despite closely matched size, composition, and surface charge. D-His-GQDs preferentially interact with cholesterol-rich ordered membrane nanodomains associated with S-acylated coronavirus Spike, penetrate more deeply into raft-like lipid bilayers, and induce lipid disordering, membrane leakage, and viral-envelope disruption. Reducing Spike S-acylation or depleting membrane cholesterol attenuated this stereoselective interaction, while molecular simulations revealed asymmetric lipid organization surrounding S-acylated Spike and preferential insertion of D-His-GQDs into the ordered membrane environment. Functionally, D-His-GQDs directly inactivated human coronavirus OC43 (HCoV-OC43), inhibited infection with an EC50 of 0.92 g/mL and exhibited a selectivity index of 361. Stereoselective antiviral activity extended to human cytomegalovirus, demonstrating activity across distinct enveloped-virus families, and intranasal D-His-GQDs protected HCoV-OC43-challenged mice under both prophylactic and early post-exposure regimens. Overall, these findings establish structural nanochirality as a biomaterial design parameter for recognizing higher-order membrane organization and converting virus-associated membrane states into selectively addressable therapeutic vulnerabilities.

Circulating microRNAs (miRNAs) have emerged as promising liquid biopsy markers; however, their clinical translation is restricted by low abundance, biological heterogeneity, and the complexity of multiplex profiling. Herein, we develop a targeted cycling-mediated duplex-specific nuclease (DSN)-nanozyme signal amplification platform (TC-DSN-Nano) that establishes a compartmentalized catalytic transduction strategy for multiplexed miRNA analysis. By encapsulating gold nanozymes within liposomal nanoreactors, this platform spatially separates molecular recognition from catalytic signal generation, preserving nanozyme activity during sensor construction. Upon target miRNA recognition, DSN-mediated recycling induces regenerative release of nanozyme-loaded liposomes from magnetic substrates, converting individual miRNA molecules into amplified catalytic outputs without conventional nucleic acid amplification. The platform enables programmable profiling of six prostate cancer (PCa) associated miRNAs in serum samples. Furthermore, machine learning-assisted integration of multiplexed miRNA signatures enables accurate discrimination among healthy donors, nonmetastatic PCa patients, and metastatic PCa patients, achieving an overall classification accuracy of 90.5%. This work establishes a general compartmentalized nanozyme transduction framework that integrates molecular recycling, catalytic amplification, and computational analysis for liquid biopsy-based cancer stratification.

Phe-Gly-rich nucleoporins (FG-Nups) within the nuclear pore complex (NPC) form a diffusion barrier that controls the exchange of macromolecules between the nucleus and cytoplasm. The behaviors of these intrinsically disordered FG-Nups are fundamental to the NPC function but remain difficult to probe within the dynamic, native nuclear pore. To bridge this knowledge gap, here we build expandable DNA-origami rings with tunable elasticity and study FG-Nups site-specifically tethered in such mechanically responsive NPC mimics. The elastic deformation of DNA rings, measured by single-particle TEM, reveals the type (attraction or repulsion) and strength of FG-Nup interactions that shape the collective morphology of these unstructured proteins. Analyzing homotypic interactions of five FG-Nup species finds diverse FG-Nup behaviors that can be classified as repulsive/extended (Nsp1), moderately cohesive/extended (Nup62, Nup153, and Nup214), and strongly cohesive/compact (Nup98). Furthermore, we examine how FG-Nups' primary sequence, O-glycosylation, grafting density, and binding to nuclear transport receptors (NTRs) impact their biophysical state. For example, O-GlcNAcylation reduced FG-Nup cohesiveness, switching Nup98 from a collapsed state to more extended conformations. Our work thus elucidates spatially confined Nup-Nup and Nup-NTR interactions within an NPC-like nanopore, suggests a previously underappreciated role of FG-Nups in modulating NPC dilation, and establishes a generalizable method for studying multivalent interactions among disordered proteins.

Expansion microscopy (ExM) physically magnifies preserved biological specimens by using a specimen-permeating hydrogel to pull biomolecules, such as proteins, apart from each other. ExM protocols exhibit a tension between the need to initially fix proteins to each other during sample preservation, to retain proteins and their nanoscale organization, and the need to separate proteins from each other isotropically, to achieve physical magnification. We here propose to address this tension by fixing proteins directly to the hydrogel network itself, which then serves as a common substrate for both initial fixation and final separation. We equip proteins with chemical handles, then form a specimen-permeating hydrogel that binds the handles, in a ~15-minute chemical process conducted entirely at -20oC. This network fixation ExM (nfExM) procedure enables excellent epitope retention and nanoscale organization preservation, in cultured cells. nfExM may help support ultrastructural investigations of protein complexes and interactions.

A broad-spectrum antiviral is required to enable rapid intervention against current, newly emerging and mutating viruses. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), influenza A virus (IAV), Sindbis virus (SINV) and chikungunya virus (CHIKV) all engage negatively charged moieties on host cells, such as heparan sulfate (HS) and sialic acid, to facilitate attachment for entry and infection. We designed HS-mimetic nanoparticles in the form of polymer vesicles (polymersomes) by blending membrane-forming and sulfonated copolymers. These biocompatible polymersomes successfully inhibited host cell infection of HS-dependent SARS-CoV-2 and HS-independent IAV in vitro with sub-nanomolar potency. Multivalent interaction of several virus ligands with a single polymersome as quantified by fluorescence correlation spectroscopy likely contributes to their potency. The sulfonated polymersomes also functioned in vivo as demonstrated by a reduction in the spread of SINV, an alphavirus model for CHIKV, in zebrafish embryos, which led to a significantly increased survival. Hence, our polymersomes could form the basis for an urgently required multifunctional broad-spectrum antiviral nanomedicine.

Efficient intracellular delivery of neoantigen-encoded mRNAs is central to the development of effective cancer vaccines and immunotherapies. However, how the nanoscale geometry of delivery carriers impacts mRNA delivery remains poorly understood, largely because conventional delivery platforms do not readily permit systematic variation of carrier architecture while maintaining comparable chemical composition. Here, we develop a modular RNA-DNA hybrid nanoplatform that enables controlled investigation of geometry-dependent mRNA delivery. Guided by a unified design principle, we construct a series of two- and three-dimensional nanostructures with programmable architectures and systematically compare their delivery performance using consistent functional readouts. We further investigate how mRNA embedding strategies and aptamer-mediated functionalization influence intracellular delivery efficiency. By providing precise control over carrier geometry, this platform establishes a framework for elucidating structure-function relationships in mRNA delivery and offers a versatile strategy for engineering targeted nucleic acid delivery systems.

Perovskite quantum dots (PQDs) are exceptionally promising next-generation optical materials for bioimaging applications. This paper presents an optical PQDs nanocomposite method to identify bacterial species associated with breast cancer, employing a LSTM deep learning model. The results indicate that the developed PQD-based nano-sensor offers impressive sensitivity, selectivity, and practical application. The four bacterial species identified in the study, Pseudomonas aeruginosa, Vibrio parvula, Acinetobacter baumannii, and Streptococcus vestibularis, were considered the most relevant indicators of breast cancer. With rapid detection, an intuitive design, and improved reliability, the PQD sensor could be an excellent breast cancer diagnostic tool for a point-of-care application. Furthermore, it has the potential to be integrated into healthcare systems, specifically in resource-limited settings, thereby improving the accessibility and efficiency of early breast cancer detection.

Therapeutic siRNAs are a major clinical modality for hepatic gene silencing, but efficient extrahepatic delivery and multi-gene modulation remain significant barriers. Nucleic acid nanotechnology offers programmable assembly, but conventional structures suffer from enzymatic instability in vivo . Here we report fully chemically modified RNA nanostructures (FMRNs): a vehicle-free platform entirely composed of stabilized therapeutic nucleic acids that integrate structural precision with metabolic durability. Following systemic administration, FMRNs exhibit enhanced pharmacokinetics and extrahepatic accumulation, with in vivo behavior influenced greatly by hydrodynamic size rather than molecular weight. Using triangular and square geometries, we demonstrate programmable control over siRNA stoichiometry to achieve sustained, simultaneous silencing of up to four genes from a single entity. Nanostructure assembly alone drives productive delivery, especially to heart and muscle, matching lipophilic conjugation. Furthermore, cerebrospinal fluid administration reveals that larger FMRNs improve central nervous system distribution and retention revealing physicochemical parameters that impact brain exposure. FMRNs establish a modular and effective platform combining improved pharmacokinetics, extrahepatic delivery, and multi-gene silencing for complex diseases.

Macromolecular release from synthetic cells often relies on membrane pores or channels. We explored whether internally generated osmotic stress could increase membrane permeability and promote release. Using double-emulsion microfluidics, we encapsulated an Escherichia coli cell-free expression system in Pluronic L121 polymersomes to co-express the fluorescent protein mScarlet3 and the dextranase PsDex1711 in the presence of dextran. PsDex1711-mediated dextran hydrolysis produced a greater increase in bulk osmolality than reactions without PsDex1711 DNA. Tracking hundreds of individual polymersomes showed that PsDex1711-containing populations expanded, whereas control populations contracted. The distribution of normalized fluorescence revealed a subset with lower residual fluorescence than the main population. In selected expanded polymersomes, integrated internal mScarlet3 fluorescence declined to 18-22% of peak levels, without visible membrane disruption, consistent with protein release. These findings support a proof of concept for using internal gene expression to promote macromolecular release through osmotic actuation without introducing dedicated membrane pores.

Membrane tension, defined as the energy cost to expand the membrane surface area, is a fundamental mechanical property of the lipid bilayer and an important modulator of various cellular processes. Liposomes provide model systems to study protein-mediated membrane dynamics, where membrane tension can be controlled by osmotic pressure and micropipette aspiration. However, it is challenging to individually control membrane tension of nanometer-sized liposomes, such as small unilamellar vesicles (SUVs), that are widely used for modeling subcellular membrane structures and drug delivery. To bridge this technological gap, we present reconfigurable DNA origami rings for dynamically controlling membrane tension of sub-100 nm liposomes. The DNA nanorings template the formation of uniformly sized SUVs and undergo trigger-responsive dilation and contraction, thus applying controlled and reversible mechanical stress to the SUV membranes. Electron microscopy analyses show deformed liposomes with ~2.5% expanded membrane area following ring dilation. The corresponding increase in membrane tension opens a mechanosensitive ion channel MscL with gating tension of ~10 mN/m. Selectively manipulating a mixture of SUV populations enables timed release of their distinct molecular cargos, either concurrently or one at a time. Furthermore, vesicles with expanded membranes are more conducive to SNARE-mediated fusion. The nanomechanical device thus provides a programmable platform for engineering the mechanics of synthetic nano-vesicles and studying membrane tension modulated processes at the molecular level.

Clinical studies have revealed that glioblastoma (GBM) is refractory to immunotherapy, such as immune checkpoint inhibitors (ICIs), due to the immunosuppressive tumor microenvironment (TME) primarily intensified by intratumoral upregulation of transforming growth factor-{beta} (TGF{beta}). Primary GBM tumor bulks are surgically removed in clinic, but invasive tumor cells infiltrated into surrounding normal brain tissue cannot be eradicated by systemic therapy due to the integral blood-brain barrier (BBB), leading to near-inevitable tumor recurrence. To address these translational challenges, we have engineered a TGF{beta}-inhibiting protein nanocage comprising human heavy-chain ferritin protein and TGF{beta} receptor II ectodomain that enables BBB penetration and multivalent TGF{beta} entrapment, respectively. We demonstrate that the nanocage platform, denoted T{beta}R2-HFt, following systemic administration, traverses the BBB, and extensively modulates immunosuppressive TME, both stromal and immune components, thereby potentiating the therapeutic efficacy of a clinically used ICI in multiple mouse glioma models. Notably, a majority of the glioma-bearing animals that received surgical tumor resection, followed by treatment with T{beta}R2-HFt and the ICI, survived the tumor and resisted tumor rechallenge, providing a potential means to control GBM in a durable manner.

Unlike nucleic acids, proteins cannot be directly amplified. Ultrasensitive detection must therefore couple efficient analyte-to-signal conversion with strong suppression of target-independent background. Consistently detecting ~100 molecules (below which Poisson sampling noise alone causes CV to exceed 10%) across protein targets in a format as scalable and accessible as PCR remains unsolved. Separation-based ultrasensitive immunoassays require target binding stable enough to survive stringent washing and are therefore constrained by wash-induced signal loss and, more fundamentally, the relative scarcity of exceptionally tight binders. Performance consequently varies across targets; detection limits below 1,000 molecules remain rare. Conventional separation-free proximity assays avoid washing but incur background from random probe collisions, with reported detection limits frequently exceeding 100,000 molecules. Here we introduce Successive Proximity Extension Amplification Reaction (SPEAR), a separation-free architecture in which autonomous engineered DNA nanodevices emulate biological kinetic proofreading. Two successive irreversible proximity-extension steps compound discrimination between analyte-dependent and background reactions, suppressing spurious signals while preserving efficient analyte-to-signal conversion. This design reduces reliance on high-affinity binders and enables sub-fM detection from 1 uL samples through simple 3-step mixing followed by standard qPCR readout. Across 11 biomarkers tested, SPEAR consistently achieved sub-100-molecule detection limits. Where compared, it outperformed ultrasensitive separation-based platforms, analytically and clinically, including for low-abundance Alzheimer's disease biomarkers. SPEAR also precisely quantified SARS-CoV-2 neutralizing antibody titers from finger-prick dried blood spots, concordant with the cell-based reference assay on venous blood. It detected a distinct mixed phosphorylation state of Tau, and targeting this state resolved previously observed capillary-venous discordance and improved amyloid-status discrimination. These results establish engineered autonomous successive molecular discrimination as a practical strategy for near-single-molecule protein detection, extending the sensitivity, scalability and accessibility of PCR-based testing to non-amplifiable analytes.

Fluorescence microscopy is routinely used in the quantitative analysis of Giant Unilamellar Vesicles (GUVs) because it makes GUVs visible and easy to detect. Nonetheless, it requires fluorescence-equipped microscopes and, especially, the addition of tagged molecules that may introduce undesired and unaccounted variations compared to the pristine formulation. Alternatively, phase-contrast microscopy can be used to observe GUVs without labelling, yet the automatic detection of GUVs in phase-contrast images by standard image processing techniques is difficult. To overcome this limitation, we developed a framework for the automated detection and size characterization of label-free GUVs based on YOLOv11 model, a state-of-art lightweight Convolutional Neural Network (CNN) for object detection. Trained on 164 phase-contrast microscope images containing 4666 manually annotated vesicles, the model enables robust detection under low contrast-to-noise ratio and heterogeneous illumination. The trained model is implemented in a stand-alone desktop application supporting multiple analysis in a single run, pixel-to-micrometer calibration, and automated size distribution analysis. This approach achieves high detection accuracy and competitive cross-microscope generalization using YOLOv11 nano on greyscale image. Retraining scripts compatible with standard hardware are also provided to enhance adaptability. This tool enables fast and reliable analysis of GUVs without altering their composition, supporting experimental reproducibility.

Biomolecular condensates formed via phase separation play critical roles in regulating cellular processes, and their dysregulation is increasingly associated with neurodegeneration. A key challenge in understanding condensate pathology lies in distinguishing dynamic condensates from neurotoxic solid aggregates, the formation of which can, in some systems, occur within existing condensates. Yet current detection techniques often lack the sensitivity and resolution to directly monitor these assemblies and their transitions in dynamic and complex environments. Here, we combined fluorescent probes, based on molecular rotors, with fluorescence lifetime imaging microscopy to quantify changes in protein dynamics during phase separation-associated aggregate formation. Molecular rotors respond to local viscosity changes, which in our study allowed discrimination between fluid condensates and rigid amyloids based on rotors' fluorescence lifetime. Using -synuclein, a hallmark protein in Parkinson's disease, as a model system, we demonstrate real-time visualization of phase separation and condensate maturation within a unified experimental framework. Our method preserves protein integrity and provides quantitative, spatially resolved insights into structural transitions. This technology bridges a critical gap in the study of pathological protein aggregation and offers a powerful platform for mechanistic studies, biomarker discovery, and drug discovery in neurodegenerative disease research.

Extracellular vesicles (EV) are cell-secreted, nanosized biological particles that are involved in most physiological and pathophysiological processes. Their composition and properties reflect the pathophysiological state of the producing cell, tissue, and organ. Released into biological fluids, they may be used as a potential source of non-invasive biomarkers for diagnosis, prognosis or therapeutic follow-up in several diseases such as cancer. However, despite the development of single-EV analysis technologies, the sorting of EV subpopulations for downstream analysis remains a major challenge. Here, we describe a novel instrument that combines a highly sensitive optical detection system with an advanced lab-on-a-chip device. Using engineered fluorescent small extracellular vesicles (sEV), we demonstrate that the Hekat NanoSorter enables sensitive, scalable, and reproducible detection and sorting of individual sEVs for downstream analysis by cryo-EM. Furthermore, detailed characterization of the sorted EV populations, together with the detection of sEVs labeled with an in vitro pathophysiological marker, demonstrates the ability of the NanoSorter to monitor and enrich clinically relevant EV-associated biomarkers. These findings highlight the clinical potential of extracellular vesicle sorting for their use as biomarkers for therapeutic monitoring and treatment outcome assessment.

Glial cells play essential roles in maintaining neural tissue homeostasis and limiting the spread of injury-induced neuroinflammation, yet their dysfunction can also exacerbate neurodegenerative, neuroimmune, and neurodevelopmental disorders. Therapeutic targeting of specific glial cell populations would open up new treatment possibilities, but currently available viral and non-viral delivery vehicles are limited by carrier toxicity as well as poor delivery efficiency and specificity. To work towards new glia-targeted, non-viral delivery vehicles, we performed an in silico analysis on neural cell specific RNA-Seq datasets in mice to identify surface molecules differentially enriched on neurons, astrocytes, and microglia. We identified Slc2a5 (Glut5) as a microglia-enriched transporter and validated its microglia specific expression in healthy murine neural tissue using RNA in situ hybridization. By employing a sequential thiol-ene and enzymatic catalyzed reaction scheme, we synthesized polyelectrolytic dendrimers with multivalent presentation of fructose, the natural ligand for Glut5, and formulated nano-sized polyionic complexes (PICs) loaded with protein or nucleic acid cargo by mixing oppositely charged dendrimers. Fructose functionalized PICs lacking cationic surface charge enabled fructose-dependent intracellular protein delivery to Glut5-expressing human breast cancer cells (MCF-7) and mouse fibroblasts, while restricting uptake by Glut5-negative mouse astrocytes, confirming transporter-dependent selectivity in vitro. Fructose functionalized PICs resulted in minimal neuroinflammation when injected into mouse striatum at 1 mg/ml but elicited concentration-dependent neural tissue toxicity at higher doses. Fructose-PICs failed to achieve microglia specific intracellular delivery of functional proteins when injected into healthy neural tissue but aided in directing protein delivery to microglia and astrocytes at ischemic stroke lesions. Together, our findings demonstrate proof-of-principle for using in silico RNA-seq screening workflows to identify cell specific surfaceome targets and incorporating that insight into a modular biomaterial platform for targeted drug delivery.

CRISPR gene editing offers unprecedented genomic and transcriptomic control, positioning it as a powerful tool for cell therapies. Non-viral CRISPR delivery avoids the immunogenicity, genomic integration, and packaging limits of viral vectors, but local or systemic injections of non-viral nanoparticles suffers from transient action and poor biodistribution. Alternatively, biomaterial-based delivery improves nanoparticle localization and sustains delivery, yet current approaches rely on non-specific adsorption of nanoparticles to scaffolds, risking aggregation, destabilization, and unreliable release kinetics. This work establishes a novel strategy to covalently tether nanoparticles to biomaterial substrates through SnoopTag and SpyTag bioconjugation systems for spatiotemporal control of non-viral CRISPR delivery. The RALA cell-penetrating peptide, an efficient and low-cytotoxicity CRISPR delivery system, was functionalized with SnoopTag without altering nanoparticle formation or transfection capacity. SnoopTag-functionalized nanoparticles were then covalently tethered to SpyTag-decorated zwitterionic microgels via a SnoopCatcher-SpyCatcher fusion protein. This platform achieves sustained RALA-mRNA nanoparticle delivery and prolonged CRISPR activation in human mesenchymal stem cells seeded within CRISPR-loaded microgel scaffolds. This work establishes a defined biorthogonal conjugation system that tethers non-viral nanoparticles to biomaterial platforms for sustained and localized CRISPR gene editing.

Immunoassays are critical for clinical diagnostics, yet their performance is restricted by the physical constraints of flat surfaces used to immobilize capture molecules which limit loading capacity and induce protein denaturation. Hydrogels provide immense volumetric molecular loading capacity but translating them across diverse assay formats and readout modalities without compromising analyte permeability remains challenging. Here, we present a universal strategy for hydrogel integration into immunoassay platforms for enhanced optical and electronic biosensing. Utilizing bio-orthogonal photo-click chemistry, we developed a modular and tuneable poly(ethylene glycol) (PEG) matrix that achieves a 6,000-fold increase in molecular loading and a large mesh size for analyte diffusion. This 3D architecture demonstrates broad multimodal utility with easy integration into a range of binding-based assays enabling higher sensitivity, repeatability and multiplexability. It achieves high sensitivity enhancement for fluorescence detection in microarrays (38-fold) and microtiter plates (25-fold) and enables multiplexed readout in single wells, including from clinical serum samples. In silver metallization-based assays it boosts densitometric optical detection sensitivity (18-fold) and enables inexpensive electronic detection. In lateral flow assays, it generates 20-fold signal enhancement while enabling multiplexability and higher repeatability. By standardizing high-capacity volumetric biosensing, this scalable, plug-and-play technology empowers next generation highly sensitive, field-deployable point-of-care diagnostics.