ACS Nano

Nosocomial infections, also known as hospital-acquired infections (HAI), appear 48 hours or more after hospital admission and are independent of the original infirmity of the patient. To prevent or to reduce HAI, the central paradigm is to construct protective barriers between the large number of people who are sick and whose immune systems are compromised in the precincts of the hospital. Microbes that result in HAI do so by two routes of infection: touch and aerosol. We describe here ZeBox technology, a voltage induced synergistic killing of the microbe on designed surfaces, as a game-changer in this domain. Its kill rate is hitherto unmatched by any known chemical or non-chemical (viz; UV, ionisation) technology. In an enclosed test chamber, under challenge conditions, ZeBox technology can kill about a billion microbes in 10 minutes. When tested under clinical settings, the device could effectively reduce microbes, both from air and surfaces with more than 90% efficiency. The optimum requirement to reduce HAI would be to construct an online microbicidal device that operates in a continuous trap and kill mode in the background of people and patient movement, and decontaminates air and surfaces. We present unequivocal data to fortify our claims of online, continuous, safe, trap and kill mechanism of ZeBox technology.

Nanoparticles (NPs) have emerged as promising candidates for drug delivery due to their tunable physical and chemical properties. Among these, silica nanoparticles (SiNPs) are particularly valued for their biocompatibility and adaptability in applications like drug delivery and medical imaging. However, predicting SiNP biodistribution and clearance remains a significant challenge. To address this, we developed a minimal physiologically-based pharmacokinetic (mPBPK) model to simulate the systemic disposition of SiNPs, calibrated using in vivo PK data from mice. The model assesses how variations in surface charge, size, porosity, and geometry influence SiNP biodistribution across key organs, including the kidneys, lungs, liver, and spleen. A global sensitivity analysis identified the most influential parameters, with the unbound fraction and elimination rate constants for the kidneys and MPS emerging as critical determinants of SiNP clearance. Non-compartmental analysis (NCA) further revealed that aminated SiNPs exhibit high accumulation in the liver, spleen, and kidneys, while mesoporous SiNPs primarily accumulate in the lungs. Rod-shaped SiNPs showed faster clearance compared to spherical NPs. The mPBPK model was extrapolated to predict SiNP behavior in humans, yielding strong predictive accuracy with Pearson correlation coefficients of 0.98 for mice and 0.92 for humans. This model provides a robust framework for predicting the pharmacokinetics of diverse SiNPs, offering valuable insights for optimizing NP-based drug delivery systems and guiding the translation of these therapies from preclinical models to human applications.

Protein nanopores are emerging as versatile tools to fingerprint biomolecules due to their capability to characterize single molecules without the requirement for labeling. A long-standing challenge with biological nanopores is, however, that large biomolecules in their native state are often too large to enter these pores. Here, we report the self-assembly of approximately 35 {+/-} 5 pneumolysin (PLY) toxins to a stable transmembrane pore with a diameter of 20 {+/-} 3 nm, an effective length of 9.5 nm, and excellent low noise characteristics in the context of nanopore-based resistive pulse recordings. The exceptionally large pore diameter enables the characterization of the size and shape of individual proteins and protein complexes ranging in molecular weight from 50 kDa to 0.8 MDa. Moreover, PLY pores make it possible to follow the time course of the formation of oligomers of tau protein in solution by revealing the size, monomer number, approximate shape, and abundance of these oligomers. At least four characteristics make PLY pores well suited for the characterization of heterogeneous amyloid oligomer samples: First, they are not prone to clogging. Second, they provide label-free single particle analysis. Third, their large diameters make it possible to characterize a wide range of amyloid oligomer sizes with high resolution. And fourth, resistive pulse recordings from these pores provide stable open pore current baselines with low electrical noise.

Nanomaterials emerged as boundless resource of innovation, but their shape and biopersistence related to respiratory toxicology raise longstanding concerns. The development of predictive safety tests for inhaled nanomaterials, however, is hampered by limited understanding of cell type-specific responses. To advance this knowledge, we used single-cell RNA-sequencing to longitudinally analyze cellular perturbations in mice, caused by three carbonaceous nanomaterials of different shape and toxicity upon pulmonary delivery. Focusing on nanomaterial-specific dynamics of lung inflammation, we found persistent depletion of alveolar macrophages by fiber-shaped nanotubes. While only little involvement was observed for alveolar macrophages during the initiation phase, they emerged, together with infiltrating monocyte-derived macrophages, as decisive factors in shifting inflammation towards resolution for spherical nanomaterials, or chronic inflammation for fibers. Fibroblasts, central for fibrosis, sensed macrophage and epithelial signals and emerged as orchestrators of nanomaterial-induced inflammation. Thus, the mode of actions identified in this study will significantly inspire the precision of future in vitro testing. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/579746v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@1d6f061org.highwire.dtl.DTLVardef@3fabb1org.highwire.dtl.DTLVardef@21040eorg.highwire.dtl.DTLVardef@1915c3b_HPS_FORMAT_FIGEXP M_FIG C_FIG

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.

The co-occurrence of per- and polyfluoroalkyl substances (PFAS) and volatile organic compounds (VOCs) in industrial environments poses complex toxicological risks that standard additive models fail to capture. This study elucidates a novel "metabolic blockade" mechanism wherein PFAS competitively inhibits the renal excretion of VOC metabolites, thereby amplifying neurotoxic burdens. Utilizing a Double Machine Learning (DML) framework on data from National Health and Nutrition Examination Survey (2005-2020), we analyzed a final intersectional cohort of 1,975 participants. We identified a robust inhibition of VOC metabolite clearance by serum PFAS. Specifically, PFNA significantly suppressed the excretion of the benzene metabolite URXPMA (Causal {beta}TMLE = -0.219, p < 0.001), with efficacy dependent on perfluorinated chain length. Molecular docking simulations revealed the biophysical basis of this antagonism: long-chain PFNA exhibited superior binding affinity to the Organic Anion Transporter 1 (OAT1) ({Delta}G = -6.333 kcal/mol) compared to native VOC metabolites ({Delta}G = -4.957 kcal/mol), confirming high-affinity competitive inhibition at the renal interface. In a neurocognitive sub-cohort (N = 1,200), this interference translated into functional synergism; high-PFNA exposure magnified VOC-associated cognitive impairment by 1.5-fold and significantly exacerbated the negative association between VOC burden and processing speed ({beta}int = -0.263, p = 0.004). These findings define PFAS as a "metabolic amplifier" of co-contaminant toxicity, necessitating a paradigm shift toward mixture-based hazardous material regulations that account for transporter-level interactions.

Extracellular vesicles (EVs) provide a protected molecular record of disease activity, but their potential as blood-based biomarkers has been limited by isolation methods that are slow, impure, and poorly scalable. We developed a cleavable DNA-lipid anchor (cDLA) that reframes EV isolation as a modular chemistry platform, enabling rapid, economical bead-based capture and release of intact vesicles. In plasma, cDLA achieved markedly higher purity than size-exclusion chromatography, delivering deeper proteomic coverage. We applied the approach to uncover vesicular tau signals that more faithfully tracked with cerebrospinal fluid, improving diagnostic discrimination over bulk plasma tau. cDLA provides a robust and clinically scalable method for EV isolation, opening a path to liquid biopsy in neurodegenerative diseases and beyond.

Nanoparticles (NPs) coated with pMHCs can reprogram a specific type of CD4+ T cells into diseasesuppressing T regulatory type 1 cells by binding to their TCRs expressed as TCR-nanoclusters (TCRnc). NP size and number of pMHCs coated on them (called valence) can be adjusted to increase their efficacy. Here we explore how this polyvalent interaction is manifested and examine if it can facilitate T cell activation. This is done by developing a multiscale biophysical model that takes into account the complexity of this interaction. Using the model, we quantify pMHC insertion probabilities, dwell time of NP binding, TCRnc carrying capacity, the distribution of covered and bound TCRs by NPs, and cooperativity in the binding of pMHCs within the contact area. Model fitting and parameter sweeping further reveal that moderate jumps between IFN{gamma} dose-response curves at low valences can occur, suggesting that the geometry of NP binding can prime T cells for activation.

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.

DNA origami nanostructures offer substantial potential as programmable, biocompatible platforms for drug delivery and diagnostics. However, their structural stability under physiological conditions remains a major barrier to practical applications. Stability assessment of DNA origami nanostructures has traditionally relied on image-based and empirical approaches, which are time-consuming and difficult to generalize across conditions. To address these limitations, we developed a machine learning approach for DNA origami stability prediction, based on measurable physicochemical parameters. Using dynamic light scattering (DLS) to quantify diffusion coefficients as a proxy for structural integrity, we characterized over 1400 DNA origami samples under varying physiologically relevant variables: temperature, incubation time, MgCl2 concentration, pH, and DNase I concentrations. The predictive performance of the model was confirmed using an independent set of samples under previously untested conditions. This data-driven approach offers a scalable and generalizable framework to guide the design of robust DNA nanostructures for biomedical applications.

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.

Amyloid diseases are frequently associated with the appearance of an aberrant form of a protein, whose detection enables early diagnosis. In the case of transthyretin amyloidosis, the aberrant protein - the monomers - constitute the smallest species of the amyloid cascade, which creates engineering opportunities for sensing that remain virtually unexplored. Here, a two-step assay is devised, combining molecular sieving and immunodetection, for quantification of circulating monomeric transthyretin in the plasma. It is shown that mesoporous crystals built from biomolecules can selectively uptake transthyretin monomers up to measurable quantities. Furthermore, it was found that the use of endogenous molecules to produce the host framework drastically reduces unspecific adsorption of plasma proteins at the crystal surface, a feature that was observed with metal-organic frameworks. The assay was used to analyse plasma microsamples of patients and healthy controls. It shows a significant increase in the levels of monomeric transthyretin in the patients, proving its usefulness to establish the monomers as soluble and non-invasive marker of the disease. In addition, the assay can evaluate transthyretin stabilizers, an emergent strategy that broadened the treatment approach to the disease. Sensing the initial event of the transthyretin amyloid cascade with the proposed assay can make the difference for early diagnosis and eliminate the currently adopted invasive biopsies modalities for detection of the final products of the aggregation pathway.

Virus-like particles (VLPs) are non-infections viral-derived nanomaterials poised for biotechnological applications due to their well-defined, modular self-assembling architecture. Although progress has been made in understanding the complex effects that mutations may have on VLPs, nuanced understanding of the influence particle mutability has on quaternary structure has yet to be achieved. Here, we generate and compare the apparent fitness landscapes of two capsid geometries (T=3 and T=1 icosahedral) of the bacteriophage MS2 VLP. We find significant shifts in mutability at the symmetry interfaces of the T=1 capsid when compared to the wildtype T=3 assembly. Furthermore, we use the generated landscapes to benchmark the performance of in silico mutational scanning tools in capturing the effect of missense mutation on complex particle assembly. Finding that predicted stability effects correlated relatively poorly with assembly phenotype, we used a combination of de novo features in tandem with in silico results to train machine learning algorithms for the classification of variant effects on assembly. Our findings not only reveal ways that assembly geometry affects the mutable landscape of a self-assembled particle, but also establish a template for the generation of predictive mutational models of self-assembled capsids using minimal empirical training data.

The impact on human health of the increasing use of silver nanoparticles (AgNPs) in medical devices remains understudied, even though AgNP-containing dressings are known to release silver in the bloodstream leading to accumulation and slow clearance in the liver. Cellular studies have shown the intracellular dissolution of AgNPs within endo-lysosomes followed by Ag(I) binding to biomolecular thiolate-containing molecules. However, the precise subcellular distribution of Ag(I) and the nature of the disrupted physiological pathways remained unknown. Novel imaging approaches enabled us to visualize the trafficking of AgNP-containing lysosomes towards a perinuclear location and a direct nuclear transfer of Ag(I) species with accumulation in the nucleoli. These Ag(I) species impaired nuclear receptor activity, disrupting critical mechanisms of liver physiology in very low dose exposure scenarios, thus justifying further research into defining a framework for the safe use of AgNPs.

Fluorescence-based super-resolution optical microscopy (SRM) techniques allow the visualization of biological structures beyond the diffraction limit of conventional microscopes. Despite its successful adoption in cell biology, the integration of SRM into the field of histology has been deferred due to several obstacles. These include limited imaging throughput, high cost, and the need for complex sample preparation. Additionally, the refractive index heterogeneity and high labeling density of commonly available formalin-fixed paraffin-embedded (FFPE) tissue samples pose major challenges to applying existing super-resolution microscopy methods. Here, we demonstrate that photonic chip-based microscopy alleviates several of these challenges and opens avenues for super-resolution imaging of FFPE tissue sections. By illuminating samples through a high refractive-index waveguide material, the photonic chip-based platform enables ultra-thin optical sectioning via evanescent field excitation, which reduces signal scattering and enhances both the signal-to-noise ratio and the contrast. Furthermore, the photonic chip provides decoupled illumination and collection light paths, allowing for total internal reflection fluorescence (TIRF) imaging over large and scalable fields of view. By exploiting the spatiotemporal signal emission via MUSICAL, a fluorescence fluctuation-based super-resolution microscopy (FF-SRM) algorithm, we demonstrate the versatility of this novel microscopy method in achieving superior contrast super-resolution images of diverse FFPE tissue sections derived from human colon, prostate, and placenta. The photonic chip is compatible with routine histological workflows and allows multimodal analysis such as correlative light-electron microscopy (CLEM), offering a promising tool for the adoption of super-resolution imaging of FFPE sections in both research and clinical settings.

-synuclein is an intrinsically disordered protein composed of 140 amino acids that adopts multiple conformations and is prone to aggregate into {beta}-sheet-rich structures, which are hallmarks of Parkinsons disease. Moreover, missense mutations in -synuclein are related to familial forms of this neurodegenerative disorder, making their detection at the single-molecule level essential. Recently, protein sequencing using solid-state nanopores has emerged as a powerful, label-free approach for single-molecule sensing with high sensitivity. Atomically thin two-dimensional materials, such as MoS2, provide ideal platforms for sequencing applications due to their ultimate thinness and enhanced spatial resolution. However, protein sequencing using 2D materials remains challenging because of rapid translocation speeds, which limit the observation time per molecule. Here, we present extensive all-atom classical molecular dynamics simulations in explicit solvent of the full translocation of the wild-type -synuclein protein and two pathogenic mutants, i.e. A30P and E46K, through single-layer MoS2 nanopores, for a total duration of more than 22 {micro}s. To the best of our knowledge, this work represents the first atomistic simulation of a full-length protein sequencing through a 2D solid-state nanopore. From the ionic current traces recorded during simulations, we characterized distinct blockade levels and bumps, as well as their dwell time along the protein sequence at multiple time and sequence length scales. For instance, we provided the sequence motifs that show some particular patterns in the data. Furthermore, we analyzed the volume properties of amino acids inside the pore and identified characteristic blockade fingerprints differentiating the wild-type from the mutant proteins. These pioneering results pave the way for future experimental studies, offering a roadmap for validating 2D nanopore-based protein sequencing and biomarker detection with single-molecule resolution.

Reactive oxygen and nitrogen species (RONS) are implicated in neurodegeneration, but their specific pathogenic roles remain unclear. Here, we developed a pair of iridium-based nanozymes with opposing functionalities to dissect these pathways. We show that a copper-tuned iridium nanozyme (Ir{square}Cu), despite being a superior ROS scavenger, paradoxically and dramatically exacerbated -synuclein (Syn) pathology in vivo. This pathology was causally linked to its ability to amplify RNS, as pharmacological inhibition of nitric oxide synthase (NOS) with L-NAME completely abrogated the pathology and reversed a human Parkinsons disease (PD)-like transcriptomic signature. In contrast, a copper-free, broad-spectrum RONS-scavenging iridium (Ir) nanozyme demonstrated substantial therapeutic efficacy across diverse brain-first, body-first, and Alzheimers disease with Lewy body co-pathology models. Our findings uncover the importance of the RNS pathway in driving -synucleinopathies and establish a critical design principle for nanomedicine, mandating caution in the use of redox-active copper for neuroprotective applications.

A defining pathological feature of most neurodegenerative diseases is the assembly of proteins into amyloid that form disease-specific structures. In Alzheimers disease (AD) this is characterised by the deposition of amyloid-{beta} (A{beta}) and tau with AD-specific conformations. The in situ structure of amyloid in the human brain is unknown. Here, using cryogenic fluorescence microscopy (cryoFM)-targeted cryo-sectioning, cryo-focused ion beam scanning electron microscopy (cryoFIB-SEM) liftout and cryo-electron tomography (cryoET), we determined the in-tissue structure of {beta}-amyloid and tau pathology in fresh post-mortem AD donor brain. {beta}-amyloid plaques contained a mixture of fibrils and protofilaments arranged in parallel arrays and lattice-like structures, some of which were branched. Extracellular vesicles, extracellular droplets and open lipid bilayer sheets defined non-amyloid constituents of amyloid plaques. In contrast, tau inclusions were characterised by clusters of unbranched filaments. Subtomogram averaging of filaments within each cluster revealed distinct structures including variably twisted paired helical filaments (PHF) and chronic traumatic encephalopathy (CTE)-like tau filaments that were situated [~]1 m apart within two microscopic regions of pathology. Filaments within a cluster were similar to each other, but different between clusters, showing that fibril heterogeneity is spatially organised and influenced by the subcellular tissue environment. The in situ structural approaches outlined here for targeting specific proteins within human donor tissues have applications to a broad range of neurodegenerative diseases.

Multiplex electronic antigen sensors for detection of SARS-Cov-2 spike glycoproteins or hemagglutinin from Influenza A in liquid samples with characteristics resembling extracted saliva were fabricated using scalable processes with potential for economical mass-production. The sensors utilize the sensitivity and surface chemistry of a two-dimensional MoS2 transducer for attachment of antibody fragments in a conformation favorable for antigen binding. Ultra-thin layers (3 nm) of amorphous MoS2 were directly sputtered over the entire sensor chip at room temperature and laser annealed to create an array of semiconducting 2H-MoS2 active sensor regions between metal contacts. The semiconducting region was functionalized with monoclonal antibody Fab (fragment antigen binding) fragments derived from whole antibodies complementary to either SARS-CoV-2 S1 spike protein or Influenza A hemagglutinin using a papain digestion to cleave the antibodies at the disulfide hinges. The high affinity for the MoS2 transducer surface with some density of sulfur vacancies for the antibody fragment base promoted chemisorption with antigen binding regions oriented for interaction with the sample. The angiostatin converting enzyme 2 (ACE2) receptor protein for the SARS-CoV-2 spike glycoprotein, was tethered to a hexa-histidine (his6) tag at its c-terminus both for purification purposes, as well as a motif for binding to MoS2. This modified protein was also investigated as a bio-recognition element. Electrical resistance measurements of sensors functionalized with antibody fragments and exposed to antigen concentrations ranging from 2-20,000 picograms per milliliter revealed selective responses in the presence of complementary antigens with sensitivity to SARS-CoV-2 or influenza A on the order of pg/mL and comparable to gold-standard diagnostics such as Polymerase Chain Reaction (PCR) analysis. Lack of antigen sensitivity for the larger ACE2 BRE further demonstrates the utility of the engineered antibody fragment/transducer interface in bringing the target antigen closer to the transducer surface for sensitivity required for early detection viral diagnostics.

The electroosmotic-driven transport of unravelled proteins across nanopores is an important biological process that is now under investigation for the rapid analysis and sequencing of proteins. For this approach to work, however, it is crucial that the polymer is threaded in single file. Here we found that, contrary to the electrophoretic transport of charged polymers such as DNA, during polypeptide translocation blob-like structures typically form inside nanopores. Comparisons between different nanopore sizes, shapes and surface chemistries showed that under electroosmotic-dominated regimes single-file transport of polypeptides can be achieved using nanopores that simultaneously have an entry and an internal diameter that is smaller than the persistence length of the polymer, have a uniform non-sticky (i.e. non-aromatic) nanopore inner surface, and using moderate translocation velocities.