ACS Nano

The first and critical reaction in magnetic hyperthermia to induce the death of cancer cells is the production of ROS (reactive oxygen species). We previously showed that it is possible to specifically deliver iron oxide magnetic nanoparticles (IONPs) in the lysosomes of cancer cells and eradicate them by targeted magnetic intra-lysosomal hyperthermia (MILH) via the application of a high frequency alternating magnetic field (AMF) without macroscopic temperature elevation. The mechanism involves a local temperature elevation at the IONPs surface which enhances the ROS production through the Fenton reaction; ROS then peroxide the proteins and lipids of the lysosomal membrane, inducing its permeabilization and leading to lysosomal enzymes release and cell death. Fe ions, critical to produce ROS in MILH, were assumed to be released by IONPs. We thus developed PEGylated multi-cores IONPs called NanoFlowers (NF@PEG) presenting or not a SiO2 shell (NF@SiO2@PEG), the later preventing the Fe3+ release from IONPs. NF@PEG released Fe ions and produced ROS production in vitro, in acidic medium mimicking lysosome upon AMF exposure, whereas NF@SiO2@PEG did not. Surprisingly, both nanoparticles increased the ROS production in cells, induced lysosome permeabilization and cell death, and slowed down the proliferation of cancer cells with the same efficacy, upon AMF application, indicating that MILH was efficient in absence of Fe3+ release from IONPs. In contrast, Ferristatin-II, an iron uptake inhibitor, prevented the ROS production and cell death in MILH induced by both IONPs, elucidating the role of endogenous iron cations responsible for the ROS production ROS in MILH to kill cancer cells.

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

Amyloid fibrils are implicated in a wide spectrum of neurodegenerative and systemic disorders, yet their biological consequences are governed not only by total fibril content but also by how fibrillar species are organized, clustered, and amplified within heterogeneous populations. Conventional thioflavin T (ThT)-based assays provide sensitive sample-level readouts of {beta}-sheet-rich material but offer limited access to the local population structure underlying amyloid aggregation and amplification. Here, we introduce the Amyloid Pore Quantification (APQ) chip, a pore-resolved geometric partitioning platform that converts heterogeneous amyloid assembly states into fluorescence intensity distributions across thousands of defined pore-level units. Using hen egg-white lysozyme as a model amyloid-forming protein, we combine length-controlled truncated amyloid nanofibrils with vacuum-assisted ThT infiltration to establish a reproducible pore fluorescence intensity reference. APQ provided quantitative concentration-dependent calibration across a 50-fold concentration range, enabling bulk-comparable quantification while preserving pore-level distribution information. Deviations from this reference resolved pH-dependent fibril clustering near the isoelectric point as pore-signal suppression and accessibility loss, captured pepsin-associated fibrillar amplification as a population-wide increase in pore intensity, and distinguished monomer- and oligomer-driven fibril processing through coupled amplification-aggregation fingerprints. When benchmarked against ensemble fluorescence measurements and AFM morphological analysis, APQ revealed assembly-state changes that were not fully represented by sample-level ThT intensity alone. These results establish APQ as a high-throughput, distribution-aware analytical framework for translating amyloid aggregation and amplification into quantitative pore-resolved fingerprints.

Viral diagnostics during early phases of infection are often limited by target scarcity and the deployment tempo. We significantly advance both quantitative accuracy and diagnostic throughput of viral agglutination assays with Immuno-Janus Particle (IJP) aggregation behavior that "flicker" stochastically with size-dependent statistics. By scrutinizing microscale blinking patterns of time series fluorescent videos, we decipher Brownian dynamics of individual IJP-Virus conjugates and IJP aggregates via windowed Ito stochastic analysis (termed the Culsans method). High-frequency rotational fluctuation is deconvolved from corrupting drifts caused by gravitational sedimentation and Brownian translational motion. This methodology enables a non-linear mapping of angular positions of detected IJPs and IJP aggregates to extract rotational diffusivity (Dr) (and subsequently overall construct size) with superior linearity (R2[≥]0.85). The aggregation behavior exhibits a maximum when the IJP and viral particle concentrations are equal. The virion-bridged IJP-IJP conjugates significantly shift the detectable hydrodynamic diameter in the Poisson limit of reduced virus concentration with respect to IJPs, pushing the limit of detection (LOD) to 103 - 104 virions per mL in untreated human plasma. This tunable platform offers a rapid, low-volume, and scalable alternative to lab-based RT-PCR, bridging the gap between virion sensitivity and field-readiness.

The accurate quantification of biological nanoparticles, such as small extracellular vesicles (sEVs), is fundamentally hindered by a resolution-coincidence trade-off in digital assays. While physical confinement can isolate single particles, conventional optical readouts remain diffraction-limited, causing multi-particle occupancy to be miscounted as single events and thereby restricting the analytical dynamic range. Here, we report a nanoplasmonic platform that overcomes this limit by introducing a geometry-defined interface that uniquely unifies nanoscale compartmentalisation and near-field-assisted super-resolution imaging. Utilising a gold plasmonic nanohole array, the strict geometric periodicity of the lattice simultaneously serves as a template for single-vesicle confinement and a deterministic grid that generates an array of localised surface plasmon resonance near-field hotspots. This position-deterministic illumination pattern imposes known geometric priors on the excitation field, shifting high-spatial-frequency information into the detectable bandwidth to achieve sub-100 nm lateral resolution. This dual-purpose geometric determinism enables high-fidelity digital readout of individual vesicles with significantly fewer sub-images than stochastic, speckle-based metasurface structured illumination microscopy approaches. The assay achieves an analytical limit of detection of 143 sEVs/{micro}L, matching the performance of state-of-the-art single-EV counting technologies. It successfully differentiates distinct sEV subpopulations based on surface biomarker expression, establishing a clear pathway for future clinical liquid biopsy applications. By replacing stochastic loading and illumination with geometric design, this work establishes a robust framework for precise vesicle interrogation with broad implications for emerging translational applications and fundamental biology.

Solid-state nanopores offer a versatile platform for single-molecule sensing owing to their mechanical robustness, tuneable geometry, and compatibility with scalable fabrication. Here, we present a pyramidal silicon nanopore with a 40 nm sensing aperture for label-free characterisation of protein molecules by resistive pulse sensing. The nanopore operates stably over transmembrane voltages ranging from -2 to +2 V and across a broad range of electrolyte concentrations, enabling analysis under diverse experimental conditions. As molecules traverse the confined sensing region, transient ionic current modulations are generated that reflect their excluded volume and molecular geometry. Using this approach, we characterise unlabelled Tau species spanning monomeric proteins, intermediate aggregates, and mature fibrillar assemblies. Analysis of the resulting current signatures, together with simplified geometrical models, enables reconstruction of molecular dimensions and discrimination of distinct Tau populations based on their electrical fingerprints. These results demonstrate that pyramidal silicon nanopores provide a sensitive and scalable platform for label-free monitoring of structurally heterogeneous protein aggregation and establish a framework for investigating protein aggregation using solid-state nanopore sensing.

The early detection of breast cancer currently relies on expensive mammography, followed by pathology that uses biopsied, fixed, and immunohistochemically stained tissues. A live-cell detection approach could be highly beneficial as a supportive diagnostic and research tool to better understand and resolve the dynamic nature of breast cancer cells and their response to treatment in real time. Here, we present a single-walled carbon nanotube (SWCNT) near-infrared fluorescence spectral fingerprinting approach combined with machine learning to precisely detect the heterogeneity of breast cancer cells in live culture. We introduced DNA-functionalized SWCNTs to MCF-10A (a non-tumorigenic healthy control) and cancer cell lines spanning known extrinsic disease subtypes: MCF-7 (luminal A), HCC1954 (HER2+), MDA-MB-231, and MDA-MB-468 (both triple-negative). The NIR fluorescence spectra of DNA-SWCNTs across 600 individual cells within each type showed significant differences in emission peak intensities, center wavelengths, and peak intensity ratios, attributable to variations in cellular uptake and biomolecular interactions. These spectral changes likely arise from complex SWCNT cellular interaction fingerprint that includes redox-mediated modulation of the local nanotube environment, rather than from a single biomarker response. The extracted spectral features were used to train an ensemble machine learning model. The model achieved 98% classification accuracy for breast cancer detection and 95% classification accuracy for breast cancer cell subtyping. Moreover, Raman microscopy further showed that MDA-MB-468 cells exhibited the highest SWCNT uptake, whereas MCF-10A cells showed greater SWCNT aggregation, consistent with their lower broadband NIR fluorescence intensity. These results demonstrate that SWCNT NIR fluorescence fingerprints can capture cell line-specific optical signatures. This platform provides a foundation for nanomaterial-enabled biosensing strategies aimed at real-time monitoring of cancer-associated cellular states.

Modulation of immune cells as therapeutic tools has gained significant clinical relevance in the treatment of cancer. Among them, macrophages represent a promising immunotherapeutic platform not only because they can internalize tumor material, but also because they profoundly shape the tumor microenvironment through cytokine production, antigen presentation, metabolic regulation, and modulation of other immune and stromal populations. Lipid Nanoparticles (LNPs) have enabled RNA therapies to the bedside and are thus considered the gold standard for gene delivery. However, optimizing LNPs for RNA delivery to macrophages remains an active area of investigation. Here, we propose the surface modification of unPEGylated LNPs using the Layer-by-Layer (LbL) approach for enhanced RNA delivery to macrophages. Specifically, we show that fucoidan, a sulfated polysaccharide, when at the outermost layer in the LbL process provides two physicochemical advantages to unPEGylated LNPs: (1) stability in PBS and (2) resistance to lyophilization in the presence of cryoprotectant. Additionally, fucoidan improves macrophage targeting and RNA transfection efficiency compared to previously synthesized hyaluronan-decorated LbL LNPs. Fucoidan LbL LNPs (Fuc-LNPs) preferentially accumulated in CD11b+ macrophages when co-cultured with U87 glioblastoma cells, which was not observed for control PEGylated LNPs. Furthermore, Fuc-LNPs induced a higher transfection of mRNA in primary human macrophages when compared to PEGylated control LNPs. Using the model mRNA encoding CAR@CD19, Fuc-LNPs generated CAR macrophages which mediated CD19 cell ablation in vitro. Altogether, these findings highlight the potential of the LbL strategy to modulate the targeting properties of LNPs, improving RNA delivery to human macrophages and encouraging further studies using LbL LNPs for the generation of CAR-Macrophages in the context of solid tumors.

Although microplastics and nanoplastics (MP/NP) are pervasive environmental contaminants, our understanding of cellular toxicity remains incomplete, as adverse effects are often attributed to long-term intracellular accumulation, while the spatiotemporal onset of cellular damage remains poorly defined. Here, we employ chemical-bond-selective stimulated Raman scattering (SRS) microscopy and cell models that decouple continuous exposure from intracellular retention to directly visualize clinically derived MP/NP-cell interactions. Cellular stress occurs primarily during MP/NP exposure, accompanied by alterations in lipid droplet (LD) composition. In contrast, following extracellular removal, intracellularly retained MP/NP become largely inert, with recovery of lipid metabolism and cellular functions. Lipidomics identifies arachidonic acid (AA) as a key dysregulated metabolite, and SRS imaging further reveals transient, spatially confined AA enrichment in MP/NP-proximal LDs during uptake. Importantly, phospholipid coating of MP/NP attenuates LD alterations and cytotoxicity while preserving particle internalization, establishing uptake-driven metabolic stress, rather than long-term intracellular retention, as primary source of MP/NP-induced damage.

Innate immune agonists are promising therapeutic agents to induce immune responses against cancer. However, these agents have been limited by toxicity associated with systemic accumulation and activity in off-target cells. In this work, a targeted nanoparticle (NP) platform to encapsulate and protect the Toll-like receptor 3 (TLR3) agonist polyinosinic-polycytidylic acid (poly(I:C)) and promote its specific delivery to antigen presenting cells (APCs), macrophages and dendritic cells, for activation of this cell population was designed. To determine NP physiochemical properties that promote APC delivery, we developed a library of NP surface chemistries formed by electrostatic adsorption of polyanion coatings onto liposomes using layer-by-layer (LbL) assembly and screened the particles on APCs and off-target cells. Dextran sulfate was identified as a promising coating to enhance specific APC delivery. We applied these design parameters to develop a poly(I:C)-loaded NP for an APC-targeted immunotherapy. In a model of metastatic ovarian cancer, the LbL NP prolonged poly(I:C) retention in the peritoneal space--with 2-fold remaining 24-48hr after administration compared to free poly(I:C)--ultimately reducing systemic accumulation and associated toxicities. Compared to free drug, the NP reduced the increase in serum levels of TNF, IL-6, and CXCL10 by 9-, 4-, and 31-fold respectively. NP-treated mice experienced lower weight loss and recovered more quickly at a higher poly(I:C) dose, indicating a widening of the therapeutic window. The NP formulation enhanced accumulation of poly(I:C) in the tumor 2-fold and activation of the target APC population compared to free drug, and ultimately slowed tumor growth and extended survival in combination with doxorubicin chemotherapy. Overall, this work demonstrates a modular NP delivery strategy to improve the delivery, safety, and therapeutic window of a TLR3 agonist.

Solid-state nanopores offer label-free, real-time single-molecule sensing. However, resolving fast biomolecular transport requires high-bandwidth data acquisition while the intrinsic high-frequency noise limits recovery of informative events. Here we present a hardware-software co-designed nanopore sensing platform that combines wafer-scale low-noise device engineering with deep learning-based signal reconstruction. A low-dielectric SU8 coating on silicon nitride nanopores reduces device capacitance to the pF range and suppresses high-frequency noise by up to 5-fold while maintaining facile, controllable and reproducible fabrication. This extends usable acquisition to 40 MHz and enables capture of fast molecular features. Coupled with a reconstruction model trained on synthetic translocation events embedded in experimentally measured noise, the platform recovers transient sublevels while preserving blockage edges and temporal fidelity. Using engineered DNA molecules carrying dumbbell-like barcodes, we resolve nanometer-scale structural spacings on sub-microsecond timescales, and experimentally quantify translocation dynamics within the sub-10 nanometer regime. Dual-channel measurement on a single nanopore device further demonstrates transferability of the platform by showing robust cross-channel signal reconstruction across distinct baseline noise levels. Our approach provides a general route for reliable recovery of fast event features and may enable more information-rich single-molecule sensing across diverse biomolecular targets.

High-quality cellular imaging, especially in live cells, remains constrained by the trade-off among signal-to-noise ratio, phototoxicity, and instrumentation complexity. Here, we report a scalable plasmonic metasurface that generates a spatially ordered array of fluorescence-enhancing near-field hotspots and enables self-supervised denoised, cellular imaging with improved feature readability on a conventional wide-field microscope. The registered hotspot lattice serves as a physics-derived functional prior that identifies where fluorescence amplification is physically grounded and steers neural-network training accordingly, reducing reliance on paired ground truth, large external pretrained models, or extensive supervised datasets. We demonstrate two labeling-density-dependent operating regimes: dense labeling for cytoskeleton structural imaging and sparse labeling for multiplexed sensing of plasma-membrane-associated dynamics across the hotspot array. Our work unites scalable nanophotonic hardware and self-supervised computational imaging into a practical platform for structural bioimaging and on-chip live-cell biosensing under simple wide-field imaging conditions.

Biomarker analysis requires detecting analyte classes that span nucleic acids, proteins, small molecules, and metabolites, yet testing remains fragmented across target-specific assays and instruments. Here we report a molecular information-transduction strategy that converts target recognition across molecular classes into a common, error-tolerant DNA code readable by nanopore sequencing. Target recognition triggers a hybridization chain reaction that generates concatemers containing periodically repeated 10-nucleotide target-specific barcodes. A matched-filter decoder exploits this periodicity and the linear scaling of read length with match count to reject spurious matches by two to three orders of magnitude. Multi-class detection is demonstrated for a small molecule (ATP), two cardiovascular-associated microRNAs and thrombin in singleplex and multiplexed assays. By separating molecular recognition from sequence readout, this architecture provides a modular framework for converting heterogeneous analytes into a shared, redundancy-encoded signal for high-fidelity molecular sensing.

Localized measurements of electric fields offer a promising route to expand the information content of nanopore-based single-molecule sensing beyond conventional ionic-current blockade. Here, using all-atom molecular dynamics simulations with virtual electric-field probes placed around a graphene nanopore, we show that the local electric-field captures the presence, and distribution of charged amino acids as the peptides translocate through the pore. These field signatures create reproducible peptide-specific fingerprints across independent translocation events and enable substantially improved discrimination between peptides compared with ionic-current traces obtained under the same simulation conditions. Our results suggest that localized nanopore electrometry can provide a complementary, information-rich readout of peptide charge order that is largely inaccessible to conventional current blockade-based measurement. This study establishes a simulation-guided framework for integrating nanoscale electrometry with nanopore platforms for future peptide and protein analysis.

While natural infections expose the immune system for days to weeks of inflammation and antigen presentation, immunizations with conventional bolus vaccines often lead to rapid clearance of antigens and adjuvants. Prolonged exposure to vaccines using controlled delivery devices or repeated dosing regimens has been shown to enhance germinal center reactions, leading to improved humoral responses, including increased magnitude of antibody titers and enhanced neutralizing activity. Herein, we report the use of injectable polymer-nanoparticle (PNP) hydrogels as a vaccine depot technology for sustained delivery of the clinically relevant SARS-CoV-2 Hexapro subunit antigen and a toll-like receptor agonist adjuvant. In mice, we demonstrated that PNP hydrogel vaccines enhanced germinal center responses and antibody responses relative to bolus vaccination. In nonhuman primates, hydrogel vaccines induced enhanced and durable antibody responses against wildtype and variants of concern such as Omicron BA.5 compared to bolus vaccination. We report the first use of a biomaterials-based approach for sustained delivery of vaccines in nonhuman primates, further advancing toward clinical translation.

Mechanotransduction plays a fundamental role in regulating immune cell function, yet how engineered virus-like nanospikes engage mechanosensitive signaling pathways to modulate innate immunity remains poorly understood. Here, we report virus-like nanotopography as a previously unrecognized regulator of Piezo1-mediated mechanotransduction in macrophages using virus-like mesoporous silica nanoparticles (VLPSi) with tunable rigid nanospike lengths. We demonstrate a direct structure-activity relationship between nanospike geometry and Piezo1-dependent Ca{superscript 2}+ influx, with longer nanospikes inducing significantly greater intracellular Ca{superscript 2}+ signaling. Building on this mechanistic insight, we developed biomimetic cancer cell membrane (CM)-coated, MSA-2-loaded VLPSi nanoparticle (CM/MSA-2@VLPSi) and investigate the combination of nanospikes-activated Piezo1 with STING signaling and CM antigens presentation in macrophage immune reprogramming. The resulting biomimetic nanoparticles robustly activate the STING-TBK1-IRF3/NF-{kappa}B axis, increase IFN-{beta} and pro-inflammatory cytokine production, and promote macrophage polarization toward M1 phenotype in a spike-length-dependent manner. Collectively, the present study provides a biomimetic strategy for enhancing the M1 polarization of macrophage through the coordinated regulation of mechanical, inflammatory, and antigenic signals.

Antimicrobial resistance motivates the development of approaches capable of probing nanoparticle-bacterium interactions with nanoscale sensitivity. Here, synchrotron infrared nano-spectroscopy (SINS) is applied to investigate interactions between carbohydrate-coated silica nanoparticles and the Gram-negative model bacterium Escherichia coli at the single-cell level. Silica nanoparticles (SiO2) were coated with mannose, maltose, or trehalose to evaluate how surface carbohydrate chemistry influences their interactions with the bacterial envelope. Correlative electron microscopy revealed pronounced association of carbohydrate-SiO2 with the bacterial envelope, with features consistent with localization within the periplasmic region, whereas bare-SiO2 showed no detectable association. SINS measurements acquired directly on bacterial cells and at bacterium-nanoparticle interfaces revealed distinct, carbohydrate-dependent spectral signatures. Quantitative analysis of the amide I band used the I/I{beta} ; ratio, which describes the relative contributions of -helical and {beta}-sheet protein secondary-structure components, together with interface-dependent band-position analysis to characterize local spectral perturbations. Carbohydrate-SiO2 produced systematic changes in the I/I{beta} ; ratio, including at locations where nanoparticles were not directly observed, indicating that their effects extend beyond the sites of nanoparticle association. Comparison of measurements acquired on bacterial surfaces and at bacterium-nanoparticle interfaces further revealed that carbohydrate chemistry modulates both the magnitude and spatial extent of these spectral perturbations. Trehalose-SiO2 produced the largest interface-dependent amide I band shifts and a spectral component consistent with random-coil structures. Overall, these results demonstrate that carbohydrate surface chemistry modulates nanoscale protein conformational perturbations at the nano-bio interface and highlight SINS as a powerful approach for resolving chemically localized molecular responses at single-cell interfaces.

Temperature regulation in the brain is essential for maintaining neuronal function and preventing thermally induced damage. Here, we report the development and in vivo application of quantum dots (QDs) to high-resolution thermometry in the mouse brain using two-photon excitation microscopy. These QDs, via the red-to-green photoluminescence (PL) intensity ratios, enabled stable temperature measurements in both normal and chronically hypo-perfused cerebral tissue. Our findings show that localized neuronal activity leads to transient heat generation, which is rapidly dissipated by cerebrovascular responses. In a chronic hypoperfusion model, impaired vascular function resulted in exaggerated and prolonged brain temperature elevations. This thermometry system provides unprecedented insight into the mechanisms of cerebral thermoregulation and highlights the importance of vascular cooling in protecting the brain from heat-induced stress, particularly in pathological conditions such as stroke.

All-gold electron microscopy (EM) grids reduce beam-induced motion relative to conventional holey carbon supports and provide biocompatible substrates for cellular cryo-EM. However, placing customizable all-gold grid fabrication in the hands of researchers requires accessible processes based on standard microfabrication tools. We report a wafer-scale process using microfabrication techniques available in most academic cleanrooms such as lift-off metallization, electroplating, and sacrificial layer release to fabricate 594 all-gold grids per 4-inch wafer without individual grid handling. A numerical electroplating model provides a quantitative framework to relate gold deposition, grid-bar thickness, and tilt-compatible grid geometry. We show that oval 2 {micro}m x 6 {micro}m foil holes bias on-grid actin organization by substrate geometry alone, without chemical micropatterning. The EM grids supported a 2.15 [A] apoferritin single-particle reconstruction on a 200 kV cryo-TEM and are compatible with protein micropatterning and cell culture. This platform establishes an accessible route to programmable, application-specific all-gold cryo-EM supports that couple high-resolution structural imaging with engineered control of cellular organization.

The multivalent display of surface glycoprotein hemagglutinin (HA) on Influenza A viruses (IAVs) enhances the overall binding avidity to sialylated glycans on host cell surfaces. While precomplexing HA trimers with antibodies increases multivalency and avidity, this method does not replicate the virions geometry and limits insights into the multivalent binding process. Here, we use perfectly controllable icosahedral protein nanoparticles to examine the multivalent HA receptor-binding properties. We compare three HA presentation systems with varying degrees of multivalency: single HA trimers, antibody-precomplexed HA trimers, and HA trimers on nanoparticles. Our results indicate that increasing HA valency enhances binding avidity across various glycan surfaces, including erythrocytes, cells, and lipid bilayers with varying glycan densities, while maintaining receptor specificity. By combining functional and non-functional HA trimers during nanoparticle formation, we create statistical mixtures of nanoparticles with varying valencies. At high receptor densities, nanoparticles with few functional trimers still bind strongly, whereas at low receptor densities, a patch of five HA trimers appears necessary for binding. As a key finding, we observe that such a statistical mixture of nanoparticles with functional and nonfunctional HAs binds to glycan surfaces in a stronger density-dependent manner than fully functional particles. We also observe differences in binding modes that correlate with the number of functional trimers, the glycan structure (linear vs branched), and the densities achievable with these glycans. Overall, our findings demonstrate that the presentation of multivalent HA plays an enormous role in the response to glycan receptor type and density, with implications for the future design of virus monitoring, viral inhibitors, and targeting vectors.