ACS Nano

Extracellular nanocarriers, such as extracellular vesicles (EVs), lipoproteins, supermeres, and exomeres are diverse lipid-protein-nucleic acid assemblies. Among them, supermeres hold significant diagnostic potential but are challenging to characterize due to limited surface biomarker information and labor-intensive isolation methods. This study introduces an isolation-free Ion Exchange Membrane Sensing method for detection of supermeres within 30 minutes using 50 L of sample, with a sensitivity of 106-107 supermeres/mL. Validation through ultracentrifugation and surface plasmon resonance confirms the detection accuracy and specificity. Supermeres carry key proteins such as HSPA13, ENO2, and DDR1 analogous to tetraspanin in EV. Supermeres outperform sEVs and exomeres across multiple shared and unique surface proteins critical to colorectal cancer diagnosis, highlighting their superior clinical utility and potential as next-generation biomarkers in precision medicine.

Digital assays are in wide development for biomarker quantification at the single-molecule level, but the common use of surface-pulldown steps limits both analytical sensitivity and throughput. Here, we develop surface-free, wash-free, in-solution assays with a sensitivity slope approaching unity for sequence-specific counting of microRNAs (miRs) relevant to metastatic castration-resistant prostate cancer (mCRPC). These assays are enabled by DNA nanoflowers (DNFs) densely encoded with [~]200 fluorescent quantum dots (QDs) that assemble in situ stoichiometrically to miRs. The QD-DNFs are detected as single events in solution by fluorescence microscopy or flow cytometry without washing away unbound labels. A [~]50 aM limit of detection and high agreement with absolute target count (0.95) were achieved by machine learning-guided assay optimization, providing the potential for calibration-free measurements. Multiple miR sequences could be distinguished through ratiometric and colorimetric (5-color) QD signatures with a single excitation source for flexible detection scenarios in static solution or flow streams. The assays were applied for detecting exosomal miRs from small-volume plasma of mCRPC patients and showed strong agreement with RT-qPCR, but with more reliable detection of the trace prognostic biomarker miR-375. Consistent with our prior reports using large volume blood draws, higher plasma levels of miR-375 were associated with poor survival of patients with mCRPC. We anticipate that in-solution absolute counting of clinical biomarkers in plasma will enable robust molecular analysis of trace biomarkers needed for the translation of cancer precision medicine.

In cells, proteins rapidly self-assemble into sophisticated nanomachines. Bio-inspired self-assembly approaches, such as DNA origami, have achieved complex 3D nanostructures and devices. However, current synthetic systems are limited by lack of structural diversity, low yields in hierarchical assembly, and challenges in reconfiguration. Here, we develop a modular system of DNA origami voxels with programmable 3D connections. We demonstrate multifunctional pools of up to 12 unique voxels that can assemble into many shapes, prototyping 50 structures. Multi-step assembly pathways with sequential reduction in conformational freedom were then explored to increase yield. Voxels were first assembled into flexible chains and then folded into rigid structures, increasing yield 100-fold. Furthermore, programmable switching of local connections between flexible and rigid states achieved rapid and reversible reconfiguration of global structures. We envision that foldable chains of DNA origami voxels can be integrated with scalable assembly methods to achieve new levels of complexity in reconfigurable nanomaterials.

When a nanoparticle enters a biological environment, the surface is rapidly coated with proteins to form a "protein corona". Presence of the protein corona surrounding the nanoparticle has significant implications for applying nanotechnologies within biological systems, affecting outcomes such as biodistribution and toxicity. Herein, we measure protein corona formation on single-stranded DNA wrapped single-walled carbon nanotubes (ssDNA-SWCNTs), a high-aspect ratio nanoparticle ideal for sensing and delivery applications, and polystyrene nanoparticles, a model nanoparticle system. The protein corona of each nanoparticle is studied in human blood plasma and cerebrospinal fluid. We characterize corona composition by proteomic mass spectrometry to determine abundant and differentially enriched vs. depleted corona proteins. High-binding corona proteins on ssDNA-SWCNTs include proteins involved in lipid binding and transport (clusterin and apolipoprotein A-I), complement activation (complement C3), and blood coagulation (fibrinogen). Of note, albumin is the most common blood protein (55% w/v), yet exhibits low-binding affinity towards ssDNA-SWCNTs, displaying 1300-fold lower bound concentration relative to native plasma. We investigate the role of electrostatic and entropic interactions driving selective protein corona formation, and find that hydrophobic interactions drive inner corona formation, while shielding of electrostatic interactions allows for outer corona formation. Lastly, we study real-time binding of proteins on ssDNA-SWCNTs and find relative agreement between proteins that are enriched and bind strongly, such as fibrinogen, and proteins that are depleted and bind marginally, such as albumin. Interestingly, certain proteins express contrary behavior in single-protein experiments than within the whole biofluid, highlighting the importance of cooperative mechanisms driving selective corona adsorption on the SWCNT surface. Knowledge of the protein corona composition, dynamics, and structure informs translation of engineered nanoparticles from in vitro design to effective in vivo application.

Affordable, accurate, and rapid point-of-care diagnostic tests remain elusive due to inherent trade-offs between performance and cost. Conventional nucleic acid tests offer high sensitivity but require complex, expensive steps such as amplification and purification, whereas lateral flow assays are simple and low-cost but lack the necessary sensitivity for many applications. To bridge this gap, we present a miniaturized and simplified chip-based platform that combines three components into a single diagnostic pipeline: we use (i) spectrally distinct silver and gold nanoparticles that form analyte-dependent clusters with unique spectral fingerprints, (ii) a one-pot, enzyme- and purification-free assay on a chip integrated with a high-throughput automated low-cost microscope, and (iii) a morphology-guided convolutional Graph Neural Network that embeds morphology information into convolutional kernels and performs graph-based relational learning across particle-level features. This integration captures spectral, spatial, and morphological quantification at the particle level, rather than relying on bulk spectral shifts, thereby overcoming the limitations of contemporary nanoparticle assays and image-level deep learning approaches. Processing up to 5000 particles per image using only <5 GB GPU memory, Mc-GNN achieves femtomolar sensitivity with 98.2% recall for synthetic DNA and 94.8% for SARS-CoV-2 RNA from whole virus, despite variations in nanoparticle selection and sample complexity. By embedding morphological information into the biosensing pipeline, our diagnostic platform is computationally efficient, smartphone-compatible and is readily extensible to new analytes and multiplexing, offering a scalable solution for a fieldable diagnostic tool.

Assessing therapeutic response in glioblastoma (GBM) is a major factor limiting the clinical development of new and effective therapies. The intracranial location limits serial biopsies, and only provides an intermittent view of the tumor molecular profile from the initial resection. Liquid biopsy techniques, specifically small extracellular vesicle (sEV) analysis, have the potential to overcome these limitations by providing a window into the brain using peripheral blood. To address the need for monitoring tumor evolution and therapeutic resistance, we developed a GBM biomarker panel (ATP1B2, EAAT2, CD24, CD44, CD133 and EGFR) for multiplexed profiling of sEVs using an advanced GBM Extracellular vesicle Monitoring Phenotypic Analyzer Chip (GEMPAC). We successfully tracked patient response to treatment by monitoring changes in glioma stem cell markers on circulating sEVs. We propose that these results provide a strong rationale for using GBM sEVs as a serial monitoring tool in the future clinical management of GBM patients.

Single-walled carbon nanotubes (SWCNT) are used in neuroscience for deep-brain imaging, neuron activity recording, measuring brain morphology, and imaging neuromodulation. However, the extent to which SWCNT-based probes impact brain tissue is not well understood. Here, we study the impact of (GT)6-SWCNT dopamine nanosensors on SIM-A9 mouse microglial cells and show SWCNT-induced morphological and transcriptomic changes in these brain immune cells. Next, we introduce a strategy to passivate (GT)6-SWCNT nanosensors with PEGylated phospholipids to improve both biocompatibility and dopamine imaging quality. We apply these passivated dopamine nanosensors to image electrically stimulated striatal dopamine release in acute mouse brain slices, and show that slices labeled with passivated nanosensor exhibit higher fluorescence response to dopamine and measure more putative dopamine release sites. Hence, this facile modification to SWCNT-based dopamine probes provides immediate improvements to both biocompatibility and dopamine imaging functionality with an approach that is readily translatable to other SWCNT-based neurotechnologies.Competing Interest StatementThe authors have declared no competing interest.View Full Text

Nanoparticle delivery to tumors remains inefficient, with current nanomedicines achieving only 0.7% injected dose per gram (ID/g) of tumor tissue due to uncontrolled protein corona formation that redirects nanoparticles away from target sites. We engineered biomimetic protein coronas to control nanoparticle-protein interactions and enhance tumor targeting. Competitive binding studies using NMR spectroscopy revealed that transferrin (Tf) and fibronectin (Fn) outcompete albumin (BSA) and immunoglobulin G (IgG) for 15 nm gold nanoparticle surfaces, establishing a binding hierarchy that enables predictable corona composition. Pre-coating nanoparticles with a four-protein combination (BSA+Tf+Fn+IgG) created coronas that selectively enhanced cancer cell uptake while reducing macrophage recognition in vitro. When administered to tumor-bearing mice, these engineered coronas achieved 13 ppm/g tumor accumulation--equivalent to 4% ID/g--representing 6.5-fold improvement over bare nanoparticles and 2.6-fold improvement over PEGylated formulations. Proteomics analysis of secondary coronas formed in human serum revealed that engineered nanoparticles selectively recruit transport and adhesion proteins while limiting immune recognition signatures. The pre-formed coronas maintained targeting protein retention and reduced complement binding compared to controls. Circular dichroism confirmed minimal protein structural perturbation, preserving receptor-binding functionality for active targeting. The strategy harnesses natural protein adsorption processes to create "smart" biological interfaces that simultaneously evade immune clearance and promote tumor cell recognition through multiple receptor pathways. This approach demonstrates the feasibility of treating the coron as a programmable interface, addressing delivery limitations that have hindered clinical translation of cancer nanomedicines. For Table of Contents Only O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=109 SRC="FIGDIR/small/693224v1_ufig1.gif" ALT="Figure 1"> View larger version (61K): org.highwire.dtl.DTLVardef@5dd106org.highwire.dtl.DTLVardef@1460e3corg.highwire.dtl.DTLVardef@50c251org.highwire.dtl.DTLVardef@5604f_HPS_FORMAT_FIGEXP M_FIG C_FIG

Acute lung inflammation has severe morbidity, as seen in COVID-19 patients. Lung inflammation is accompanied or led by massive accumulation of neutrophils in pulmonary capillaries ("margination"). We sought to identify nanostructural properties that predispose nanoparticles to accumulate in pulmonary marginated neutrophils, and therefore to target severely inflamed lungs. We designed a library of nanoparticles and conducted an in vivo screen of biodistributions in naive mice and mice treated with lipopolysaccharides. We found that supramolecular organization of protein in nanoparticles predicts uptake in inflamed lungs. Specifically, nanoparticles with agglutinated protein (NAPs) efficiently home to pulmonary neutrophils, while protein nanoparticles with symmetric structure (e.g. viral capsids) are ignored by pulmonary neutrophils. We validated this finding by engineering protein-conjugated liposomes that recapitulate NAP targeting to neutrophils in inflamed lungs. We show that NAPs can diagnose acute lung injury in SPECT imaging and that NAP-like liposomes can mitigate neutrophil extravasation and pulmonary edema arising in lung inflammation. Finally, we demonstrate that ischemic ex vivo human lungs selectively take up NAPs, illustrating translational potential. This work demonstrates that structure-dependent interactions with neutrophils can dramatically alter the biodistribution of nanoparticles, and NAPs have significant potential in detecting and treating respiratory conditions arising from injury or infections.

When a material enters the body, it is immediately attacked by hundreds of proteins, organized into complex networks of binding interactions and reactions. How do such complex systems interact with a material, "deciding" whether to attack? We focus on the "complement" system of [~]40 blood proteins that bind microbes, nanoparticles, and medical devices, initiating inflammation. We show a sharp threshold for complement activation upon varying a fundamental material parameter, the surface density of potential complement attachment points. This sharp threshold manifests at scales spanning single nanoparticles to macroscale pathologies, shown here for diverse engineered and living materials. Computational models show these behaviors arise from a minimal subnetwork of complement, manifesting percolation-type critical transitions in the complement response. This criticality switch explains the "decision" of a complex signaling network to interact with a material, and elucidates the evolution and engineering of materials interacting with the body.

Tissue barriers must be rapidly restored after injury to promote regeneration. However, the mechanism behind this process is unclear, particularly in cases where the underlying extracellular matrix is still compromised. Here, we report the discovery of matrimeres as constitutive nanoscale mediators of tissue integrity and function. We define matrimeres as non-vesicular nanoparticles secreted by cells, distinguished by a primary composition comprising at least one matrix protein and DNA molecules serving as scaffolds. Mesenchymal stromal cells assemble matrimeres from fibronectin and DNA within acidic intracellular compartments. Drawing inspiration from this biological process, we have achieved the successful reconstitution of matrimeres without cells. This was accomplished by using purified matrix proteins, including fibronectin and vitronectin, and DNA molecules under optimal acidic pH conditions, guided by the heparin-binding domain and phosphate backbone, respectively. Plasma fibronectin matrimeres circulate in the blood at homeostasis but exhibit a 10-fold decrease during systemic inflammatory injury in vivo. Exogenous matrimeres rapidly restore vascular integrity by actively reannealing endothelial cells post-injury and remain persistent in the host tissue matrix. The scalable production of matrimeres holds promise as a biologically inspired platform for regenerative nanomedicine.

Rapid and accurate identification of bacterial infections and their resistance to antibiotics is critical to effective clinical decision-making and combating antimicrobial resistance. However, current diagnostic approaches are typically segmented: techniques such as MALDI-TOF provide species identification, but cannot assess antibiotic susceptibility, while standard antimicrobial susceptibility (AST) tests are time-consuming and lack concurrent identification capability. In this study, we overcome these limitations by integrating single-cell nanomotion detection using graphene drums with machine learning (ML) algorithms to perform both tasks simultaneously within a single measurement. Nanomotion signals, nanoscale vibrations from single living cells, are recorded in real-time and transformed into time-frequency spectrograms, which serve as inputs to ML models trained for robust pattern recognition. Our framework enables the differentiation of Escherichia coli, Staphylococcus aureus, and Klebsiella pneumoniae, while simultaneously distinguishing resistant and susceptible strains with 98% precision. By coupling highly-sensitive graphene nanomotion sensors with advanced ML tools, our approach delivers a label-free bacterial diagnostics, offering both identification and susceptibility profiling at the single-cell level within a couple of hours.

Optical and non-optical techniques propelled the field of single extracellular particle (EP) research through phenotypic and morphological analyses, revealing the similarities, differences, and co-isolation of EP subpopulations. Overcoming the challenges of optical and non-optical techniques motivates the use of orthogonal techniques while analyzing extracellular particles (EPs), which require varying concentrations and preparations. Herein, we introduce the nano-positioning matrix (NPMx) technique capable of superimposing optical and non-optical modalities for a single-EP orthogonal analysis. The NPMx technique is realized by ultraviolet-mediated micropatterning to reduce the stochasticity of Brownian motion. While providing a systematic orthogonal measurement of a single EP via total internal reflection fluorescence microscopy and transmission electron microscopy, the NPMx technique is compatible with low-yield samples and can be utilized for non-biased electrostatic capture and enhanced positive immunogold sorting. The success of the NPMx technique thus provides a novel platform by marrying already trusted optical and non-optical techniques at a single-EP resolution.

Nanopore sensing is a technique based on the Coulter principle to analyze and characterize nanoscale materials with single entity resolution. However, its use in nanoparticle characterization has been constrained by the need to tailor the nanopore aperture size to the size of the analyte, precluding the analysis of heterogenous samples. Additionally, nanopore sensors often require the use of high salt concentrations to improve the signal-to-noise ratio, which further limits their ability to study a wide range of nanoparticles that are unstable at high ionic strength. Here, we report the development of nanopore sensors enhanced by a polymer electrolyte system, enabling the analysis of heterogenous nanoparticle mixtures at low ionic strength. We present a finite element model to explain the anomalous conductive/resistive pulse signals observed and compare these results with experiments. Furthermore, we demonstrate the wide applicability of the method by characterizing metallic nanospheres of varied sizes, plasmonic nanostars with various degrees of branching, and protein-based spherical nucleic acids with different oligonucleotide loadings. Our system will complement the toolbox of nanomaterials characterization techniques and will enable real-time optimization workflow for engineering a wide range of nanomaterials.

Plasmonic nanoparticles are key components in nanophotonics1-11 and have applications in molecular detection and diagnostic platforms. 12-14 Coupling of dipoles to plasmonic antennas has allowed engineering of qualitatively altered behavior in isolated quantum systems, 8,15 but this promise has not been fulfilled in living systems, where the use of plasmonics is limited to tissue level applications of plasmonic particles as contrast agents16 or heat sources.17 Here we show that coupling to designed plasmonic nanoparticles can control the electrophysiological function of proteins in living cells. We designed nanostar geometries and achieved robust near-field coupling of these optimized nanoparticles to plasma membrane-localized Archaerhodopsin proteins. We enhanced the fluorescence of the coupled rhodopsins and increased their response speed to membrane voltage. We incorporated this plasmonic enhancement into a Markov chain photocycle model of the Archaerhodopsin mutant QuasAr6a, showing an increased fluorescence emission rate and manipulation of the protein dynamics through a combination of photocycle transition rate enhancements. These results represent the first scalable near-field coupling between plasmonic particles and fluorescent proteins in living cells. They show enhancement of protein function beyond what has been achievable through genetic engineering. This opens up a range of possibilities for engineering biological functionality through plasmonics.

Understanding the intracellular fate of nanoparticles is essential for designing safer and more effective nanomedicines, yet most studies rely on static observations and lack high-resolution, near-native volumetric information. Here, we establish a synchrotron-based correlative X-ray microscopy framework to investigate how fluorescent silica nanoparticles (SiNPs) redistribute within macrophages as a function of concentration and successive cell-division cycles. SiNPs were internalized by RAW 264.7 macrophages at different concentrations and analyzed using a synchrotron-based correlative X-ray microscopy workflow integrating cryogenic soft X-ray tomography (cryo-SXT), cryogenic structured illumination microscopy (cryo-SIM), and coherent X-ray ptychography, with confocal fluorescence microscopy used to establish population-level uptake tendencies. Cryo-SXT reveals a concentration-dependent redistribution of nanoparticle-containing vesicles from peripheral endosomes toward the perinuclear region, while correlative cryo-SIM confirms strict vesicular confinement, with no evidence of free nanoparticle diffusion into the nucleoplasm. At higher doses, nanoparticles approach the nuclear region via vesicles extending into nuclear-envelope invaginations, rather than by true nuclear entry. Successive cell divisions redistribute the intracellular nanoparticle load and promote stable perinuclear clustering, identifying a long-term sequestration route in macrophages. Coherent X-ray ptychography further reveals nanoscale deformations of the nuclear envelope associated with dense perinuclear vesicles. Together, these results establish synchrotron-based correlative X-ray microscopy as a mechanistic, multiscale platform for unveiling the dynamic intracellular fate of nanoparticles and providing mechanistic insight into their apparent nuclear localization.

Accurate characterization of the nanoparticle (NP) protein corona is essential for predicting biological fate, safety, and therapeutic efficacy, and for enabling robust biomarker discovery. Standard isolation techniques, most commonly centrifugation and magnetic separation, are widely used, yet they rarely account for co-isolating endogenous biological NPs such as extracellular vesicles (EVs). This oversight can distort the apparent "biological identity" of the NP. Here, we quantitatively demonstrate the magnitude and impact of EVs on the perceived protein corona composition. We incubated highly monodisperse polystyrene NPs (50-1000 nm) and superparamagnetic beads in either standard human plasma or plasma depleted of EVs by immunoaffinity capture targeting 37 EV surface epitopes. Mass spectrometry revealed that EV depletion reduced the number of proteins identified on polystyrene NPs by 60-75% and on magnetic beads by 45-50%. Importantly, EV depletion also altered the apparent abundance hierarchy; it restored the expected relative abundance and rank of major plasma proteins such as albumin and shifted the top-ranked proteins from intracellular cytoskeletal component, consistent with EV carryover, to genuine soluble plasma adsorbates (e.g., apolipoproteins, complement factors). These results highlight that standard corona workflows can inadvertently co-isolate a vast array of EV-associated proteins, yielding inaccurate proteomic profiles. Discriminating genuine corona proteins and EV-associated contaminants is critical for advancing nanomedicine, ensuring predictive safety and efficacy profiles, and enhancing the precision of NP-based biomarker discovery.

The protein corona (PC), a layer of biomolecules that adsorbs onto nanoparticles (NPs) surfaces upon exposure to biological fluids, plays a key role in defining the biological identity and performance of nanomaterials. However, most current analytical approaches rely on pooled measurements of PC-coated NPs and therefore lack the resolution needed to detect subtle heterogeneity in PC composition, potentially masking important differences in NPs biological identity. Here, we used a high-sensitivity magnetic levitation (MagLev) platform capable of resolving extremely small density differences among nominally identical PC-coated NPs, enabling fractionation of particles based on subtle variations in PC composition. Compared with conventional standard MagLev systems (density resolution [~]10-3 g/cm3), the high-sensitivity MagLev improves density sensitivity by up to three orders of magnitude, allowing discrimination of density differences as small as 10-5 g/cm3. Using this approach, PC-coated NPs were separated along the MagLev column into multiple fractions corresponding to distinct density populations. Subsequent proteomic analysis across the extracted fractions identified more than 500 proteins and revealed a structured but continuous redistribution of protein composition across the column, including fraction-dependent differences in protein abundance, overlap, and biological identity. In particular, the fraction series captured hidden heterogeneity among nominally identical PC-coated NPs, with upper fractions retaining relatively stronger extracellular/plasma-associated signatures and lower fractions showing increasing representation of structural, membrane-associated, cytoskeletal, and metabolic proteins. These findings demonstrate that PC formation is intrinsically heterogeneous even on identical NPs and this heterogeneity is largely missed by conventional pooled analysis. High-sensitivity MagLev provides a simple, label-free framework for resolving PC heterogeneity and offers a new analytical approach for studying NP-biomolecule interactions, with important implications for nanomedicine design, biomarker discovery, and the clinical translation of NP-based systems. TOC O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=96 SRC="FIGDIR/small/727410v1_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@155ad62org.highwire.dtl.DTLVardef@1ea3e3dorg.highwire.dtl.DTLVardef@19c40ceorg.highwire.dtl.DTLVardef@162ca8d_HPS_FORMAT_FIGEXP M_FIG C_FIG

The protein corona, a dynamic biomolecular layer that forms on nanoparticle (NP) surfaces upon exposure to biological fluids is emerging as a valuable diagnostic tool for improving plasma proteome coverage analyzed by liquid chromatography-mass spectrometry (LC-MS/MS). Here, we show that spiking small molecules, including metabolites, lipids, vitamins, and nutrients (namely, glucose, triglyceride, diglycerol, phosphatidylcholine, phosphatidylethanolamine, L--phosphatidylinositol, inosine 5'-monophosphate, and B complex), into plasma can induce diverse protein corona patterns on otherwise identical NPs, significantly enhancing the depth of plasma proteome profiling. The protein coronas on polystyrene NPs when exposed to plasma treated with an array of small molecules (n=10) allowed for detection of 1793 proteins marking an 8.25-fold increase in the number of quantified proteins compared to plasma alone (218 proteins) and a 2.63-fold increase relative to the untreated protein corona (681 proteins). Furthermore, we discovered that adding 1000 {micro}g/ml phosphatidylcholine could singularly enable the detection of 897 proteins. At this specific concentration, phosphatidylcholine selectively depleted the four most abundant plasma proteins, including albumin, thus reducing the dynamic range of plasma proteome and enabling the detection of proteins with lower abundance. By employing an optimized data-independent acquisition (DIA) approach, the inclusion of phosphatidylcholine led to the detection of 1436 proteins in a single plasma sample. Our molecular dynamic results revealed that phosphatidylcholine interacts with albumin via hydrophobic interactions, h-bonds, and water-bridges. Addition of phosphatidylcholine also enabled the detection of 337 additional proteoforms compared to untreated protein corona using a top-down proteomics approach. These significant achievements are made utilizing only a single NP type and one small molecule to analyze a single plasma sample, setting a new standard in plasma proteome profiling. Given the critical role of plasma proteomics in biomarker discovery and disease monitoring, we anticipate widespread adoption of this methodology for identification and clinical translation of proteomic biomarkers into FDA approved diagnostics.

The protein corona influences the in vivo biodistribution of ionizable lipid nanoparticles (LNPs) in nucleic acid delivery, yet its structural architecture remains poorly defined. Using cryo-transmission electron microscopy, we visualized LNP-protein interactions in their native state. We show that, unlike the discrete "fuzzy" shells observed on hard nanoparticles, LNPs displayed no peripheral protein shell. Instead, controlled incubation and competitive "dual-particle" assays, supported by molecular dynamics simulations, indicate that LNP membranes undergo localized thickening and electron-dense remodeling consistent with lipoprotein integration rather than surface adsorption. Similar features were observed in extracellular vesicles, suggesting this behavior is shared among lipid-based carriers, and proteomic analysis identified apolipoproteins as the dominant associated proteins. Together, these findings support a model in which the biological identity of LNPs arises through membrane remodeling rather than shell-like adsorption, and provide a framework for the rational design of targeted nanomedicines. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=138 SRC="FIGDIR/small/695162v2_ufig1.gif" ALT="Figure 1"> View larger version (79K): org.highwire.dtl.DTLVardef@5275d3org.highwire.dtl.DTLVardef@1b59ae4org.highwire.dtl.DTLVardef@1cc290eorg.highwire.dtl.DTLVardef@9b7bfb_HPS_FORMAT_FIGEXP M_FIG C_FIG