Single-particle Level Research Articles

Highly Sensitive Determination of Copper Ions as MnO2 Etching Inhibitor in Single-Particle Nanoplasmonic Imaging.

Dark-field microscopy (DFM) imaging based on plasmonic metal nanoparticles has garnered significant attention. Here, we exploit the susceptibility of MnO2 to reduction to modulate the local dielectric environment of an Au nanoparticle core through the etching/antietching effects of specific targets on the encapsulated MnO2 shell. The presence of d-penicillamine promotes MnO2 etching, while the chelation of d-penicillamine with Cu2+ effectively inhibits this etching. By recording the Cu2+-induced color shift of scattered light from orange to bright green at the single-particle level and performing the statistical analysis of the green-to-red (G/R) values in DFM images, we achieved quantitative determination of Cu2+ with a wide linear range (0.1-10 μM) and a low limit of detection (4.55 nM). With the facile and reliable Cu2+ assay in real-world samples exemplifying the practicality of the single-particle nanoplasmonic imaging method, this work may inspire future DFM-based investigations of nanoshell etching inhibition processes.

Adaptable Plasmonic Membrane Sensors for Fast and Reliable Detection of Trace Low-Micrometer Microplastics in Lake Water.

In freshwater environments, low-micrometer microplastics (LMMPs) have captured significant attention due to their prevalence and toxicity. Yet, rapid detection of LMMPs (1-10 μm) at the single-particle level within complex freshwater matrices remains a hurdle. We developed an adaptable plasmonic membrane sensor for fast detection of individual LMMPs in eutrophic lake waters. The plasmonic membrane sensor functions both as a membrane filter and as a sensor for LMMP collection and analysis. Among the four types of membrane sensors, polycarbonate track-etch (PCTE) membrane sensors exhibit superior imaging quality for LMMPs due to their flat and homogeneous surfaces. Besides the significantly improved imaging contrast and reduced background interferences, the Raman intensity of LMMPs is enhanced by 48% ± 25% on PCTE membrane sensors compared to unmodified membranes. The increased Raman intensities of a chemical probe with an increasing gold layer thickness and a decreasing membrane pore size suggest a surface-enhanced Raman scattering effect from the membrane sensors. The membrane sensors achieve a detection limit of 1 μg/L and an ultrafast scanning time of 0.01 s for individual LMMPs across natural eutrophic lake water. The developed membrane sensors offer an adaptable tool for the swift and reliable detection of individual LMMPs in complex environmental matrices.

Submillisecond Electric Field Sensing with an Individual Rare-Earth Doped Ferroelectric Nanocrystal.

Understanding the dynamics of electrical signals within neuronal assemblies is crucial to unraveling complex brain functions. Despite recent advances in employing optically active nanostructures in transmembrane potential sensing, there remains room for improvement in terms of response time and sensitivity. Here, we report the development of such a nanosensor capable of detecting electric fields with a submillisecond response time at the single-particle level. We achieve this by using ferroelectric nanocrystals doped with rare-earth ions that produce upconversion (UC). When such a nanocrystal experiences a variation of surrounding electric potential, its surface charge density changes, inducing electric polarization modifications that vary, via a converse piezoelectric effect, the crystal field around the ions. The latter variation is finally converted into UC spectral changes, enabling optical detection of the electric potential. To develop such a sensor, we synthesized erbium and ytterbium-doped barium titanate crystals of ≈160 nm in size. We observed distinct changes in the UC spectrum when individual nanocrystals were subjected to an external field via a conductive atomic force microscope tip, with a response time of 100 μs. Furthermore, our sensor exhibits a remarkable sensitivity of 4.8 kV/cm/, enabling time-resolved detection of a fast-changing electric field of amplitude comparable to that generated during a neuron action potential.

Morphology Determination of Luminescent Carbon Nanotubes by Analytical Super-Resolution Microscopy Approaches.

The ability to determine the precise structure of nano-objects is essential for a multitude of applications. This is particularly true of single-walled carbon nanotubes (SWCNTs), which are produced as heterogeneous samples. Current techniques used for their characterization require sophisticated instrumentation, such as atomic force microscopy (AFM), or compromise on accuracy. In this paper, we propose to use super-resolution microscopy (SRM) to accurately determine the morphology (orientation, length, and shape) of individual luminescent SWCNTs. We generate super-resolved images using three recently published SRM analytical software packages (DPR, eSRRF, and MSSR) and metrologically compare their performances to determine the morphological properties of SWCNTs. For this, ground-truth information on nanotube morphologies was obtained using polarization measurements and AFM to directly correlate the results from SRM at the single particle level. We show a more than 4-fold improvement in resolution over standard photoluminescence imaging, revealing hidden morphologies as efficiently as AFM. We finally demonstrate that DPR, and eventually eSRRF, can effectively assess SWCNT length distribution in a much faster and more accessible way than AFM. We believe that this approach can be generalized to other types of luminescent nanostructures and thus become a standard for rapid and accurate characterization of samples.

The Countoscope: Measuring Self and Collective Dynamics without Trajectories

Driven by physical questions pertaining to quantifying particle dynamics, microscopy can now resolve complex systems at the single-particle level, from cellular organisms to individual ions. Yet, available analysis techniques face challenges reconstructing trajectories in dense and heterogeneous systems where accurately labeling particles is difficult. Furthermore, the inescapable finite field of view of experiments hinders the measurement of collective effects. Inspired by Smoluchowski, we introduce a broadly applicable analysis technique that probes dynamics of interacting particle suspensions based on a remarkably simple principle: counting particles in finite observation boxes. Using colloidal experiments, advanced simulations, and theory, we first demonstrate that statistical properties of fluctuating counts can be used to determine self-diffusion coefficients, so alleviating the hurdles associated with trajectory reconstruction. We also provide a recipe for practically extracting the diffusion coefficient from experimental data at variable particle densities, which is sensitive to steric and hydrodynamic interactions. Remarkably, by increasing the observation box size, counting naturally enables the study of collective dynamics in dense suspensions. Using our novel analysis of particle counts, we uncover a surprising enhancement of collective behavior due to hydrodynamics as well as a new length scale which can be connected with hyperuniform structure. Our counting framework, the “countoscope,” thus enables efficient measurements of self and collective dynamics in dense suspensions and opens the way to quantifying dynamics and identifying novel physical mechanisms in diverse complex systems where single particles can be resolved. Published by the American Physical Society 2024

Unlocking Intracellular Protein Delivery by Harnessing Polymersomes Synthesized at Microliter Volumes using Photo-PISA.

Efficient delivery of therapeutic proteins and vaccine antigens to intracellular targets is challenging due to generally poor cell membrane permeation and endolysosomal entrapment causing degradation. Herein, these challenges are addressed by developing an oxygen-tolerant photoinitiated polymerization-induced self-assembly (Photo-PISA) process, allowing for the microliter-scale (10µL) synthesis of protein-loaded polymersomes directly in 1536-well plates. High-resolution techniques capable of analysis at a single particle level are employed to analyze protein encapsulation and release mechanisms. Using confocal microscopy and super-resolution stochastic optical reconstruction microscopy (STORM) imaging, their ability to deliver proteins into the cytosol following endosomal escape is subsequently visualized. Lastly, the adaptability of these polymersomes is exploited to encapsulate and deliver a prototype vaccine antigen, demonstrating its ability to activate antigen-presenting cells and support antigen cross-presentation for applications in subunit vaccines and cancer immunotherapy. This combination of ultralow volume synthesis and efficient intracellular delivery holds significant promise for unlocking the high throughput screening of a broad range of otherwise cost-prohibitive or early-stage therapeutic protein and vaccine antigen candidates that can be difficult to obtain in large quantities. The versatility of this platform for rapid screening of intracellular protein delivery can result in significant advancements across the fields of nanomedicine and biomedical engineering.

Shear rheology of confined double rings of dust particles in a dusty plasma

Abstract Shear rheology is a fundamental property of soft matter, which can be deformed. Although the shear rheology of fluids has been well studied at the macroscopic scale, understanding the microscopic processes of rheology at the single-particle level remains a challenging issue. Dusty plasma serves as an ideal platform for exploring microscopic dynamics of system at the individual particle level. Here, we study the shear rheology of confined double rings of strongly coupled dust particles in a dusty plasma. The outer ring is actively driven to rotate using laser illumination. Depending on the particle number, the inner ring may passively rotate following the outer ring at different angular speeds, resulting in shear rheology. The number of dust particles influences particle arrangement, which is characterized by the pair correlation function, bond-orientational order parameter, and triangle skewness. That further alters structural stability, significantly affecting the shear rheology.

Unveiling the Dynamic Mechanism of SARS-CoV-2 Entry Host Cells at the Single-Particle Level.

Understanding the dynamic features of severe acute respiratory coronavirus 2 (SARS-CoV-2) binding to the cell membrane and entry cells is crucial for comprehending viral pathogenesis and transmission and facilitating the development of effective drugs against COVID-19. Herein, we employed atomic force microscopy (AFM)-based single-molecule force spectroscopy (SMFS) to study the binding dynamics between the virus and cell membrane. Our findings revealed that the Omicron variant of SARS-CoV-2 virus-like particles (VLPs) exhibited a slightly stronger affinity for the angiotensin-converting enzyme-2 (ACE2) receptor compared with the Delta variant and was significantly higher than the wild-type (WT). Using a real-time force-tracing technique, we quantified the dynamic parameters for a single SARS-CoV-2 VLP entry into cells, showing that approximately 200 ms and 60 pN are required. The parameters aligned with the analysis obtained from coarse-grained molecular dynamics (CGMD) simulations. Additionally, the Omicron variant invades cells at a higher entry cell speed, smaller force, and higher probability. Furthermore, single-particle fluorescence tracking visually demonstrated clathrin-dependent endocytosis for SARS-CoV-2 entry into A549 cells. The dynamic features of endocytosis provide valuable insights into the SARS-CoV-2 entry mechanism and possible intervention strategies targeting the viral infection process.

Measurement report: The Fifth International Workshop on Ice Nucleation phase 1 (FIN-01): intercomparison of single-particle mass spectrometers

Abstract. Knowledge of the chemical composition and mixing state of aerosols at a single-particle level is critical for gaining insights into atmospheric processes. One common tool to make these measurements is single-particle mass spectrometry. There remains a need to compare the performance of different single-particle mass spectrometers (SPMSs). An intercomparison of SPMSs was conducted at the Aerosol Interaction and Dynamics in the Atmosphere (AIDA) chamber at the Karlsruhe Institute of Technology (KIT) in November 2014, as part of the first phase of the Fifth International Workshop on Ice Nucleation (FIN-01). In this paper we compare size distributions and mass spectra of atmospherically relevant particle types measured by five SPMSs. These include different minerals, desert and soil dusts, soot, bioaerosol (Snomax; protein granule), secondary organic aerosol (SOA), and SOA-coated mineral particles. Most SPMSs reported similar vacuum aerodynamic diameter (dva) within typical instrumental ranges from ∼100–200 nm (lower limit) to ∼2–3 µm (upper limit). In general, all SPMSs exhibited a wide dynamic range (up to ∼103) and high signal-to-noise ratio (up to ∼104) in mass spectra. Common spectral features with small diversities in mass spectra were found with high average Pearson's correlation coefficients, i.e., for average positive spectra ravg-pos=0.74 ± 0.12 and average negative spectra ravg-neg=0.67 ± 0.22. We found that instrument-specific detection efficiency (DE) was more dependent on particle size than particle type, and particle identification favored the use of bipolar, rather than monopolar, instruments. Particle classification from “blind experiments” showed that all instruments differentiated SOA, soot, and soil dust and detected subtle changes in the particle internal mixing but had difficulties differentiating among specific mineral types and dusts. This study helps to further understand the capabilities and limitations of the single-particle mass spectrometry technique in general and the specific performance of the instrument in characterizing atmospheric aerosol particles.

Quantum Spin Probe of Single Charge Dynamics.

Electronic defects in semiconductors form the basis for emerging quantum technologies, but many defect centers are difficult to access at the single-particle level. A method for probing optically inactive spin defects would reveal semiconductor physics at the atomic scale and advance the study of new quantum systems. We exploit the intrinsic correlation between the charge and spin states of defect centers to measure the charge populations and dynamics of single substitutional nitrogen spin defects in diamond. By probing their steady-state spin population, read out at the single-defect level with a nearby nitrogen vacancy center, we directly measure the defect ionization-corroborated by first-principles calculations-an effect we do not have access to with traditional coherence-based quantum sensing.

Mechanical Profiling of Biopolymer Condensates through Acoustic Trapping.

Characterizing the mechanical properties of single colloids is a central problem in soft matter physics. It also plays a key role in cell biology through biopolymer condensates, which function as membraneless compartments. Such systems can also malfunction, leading to the onset of a number of diseases, including many neurodegenerative diseases; the functional and pathological condensates are commonly differentiated by their mechanical signature. Probing the mechanical properties of biopolymer condensates at the single particle level has, however, remained challenging. In this study, we demonstrate that acoustic trapping can be used to profile the mechanical properties of single condensates in a contactless manner. We find that acoustic fields exert the acoustic radiation force on condensates, leading to their migration to a trapping point where acoustic potential energy is minimized. Furthermore, our results show that the Brownian motion fluctuation of condensates in an acoustic potential well is an accurate probe for their bulk modulus. We demonstrate that this framework can detect the change in the bulk modulus of polyadenylic acid condensates in response to changes in environmental conditions. Our results show that acoustic trapping opens up a novel path to profile the mechanical properties of soft colloids at the single particle level in a non-invasive manner with applications in biology, materials science, and beyond.

Nanomotor-Driven Targeting Chimeras as Accelerators for the Degradation of Extracellular Proteins.

Targeted protein degradation (TPD) is emerging as a therapeutic paradigm and a serviceable research tool in chemical biology and disease treatment. However, without driving sources, most targeting chimeras (TACs) lack the capability of self-diffusion and active searching in biological environments, which significantly impedes degradation efficiency. Herein, nanomotor-driven targeting chimeras (MotorTACs) are ingeniously designed to achieve effective internalization and degradation of extracellular platelet-derived growth factor (PDGF), a driver to cancer invasion and metastasis. Catalyzed by endogenous H2O2, MotorTACs diffused rapidly and searched actively in living cells, as visualized at the single-particle level under the dark-field mode. Hydrolysis efficiency is significantly enhanced as target protein degradation is complete in only 4h. Furthermore, MotorTACs-mediated degradation of PDGF is found to be via the lysosome and ubiquitin-proteasome dual-degradation pathways. Taking advantage of the properties, it is anticipated that MotorTACs provide a unique strategy against extracellular undruggable proteins, thus advancing the development of therapeutic interventions in chemical biology and disease treatment.

Boundary-localized many-body bound states in the continuum

Bound states in the continuum (BICs), referring to spatially localized bound states with energies falling within the range of extended modes, have been extensively investigated in single-particle systems, leading to diverse applications in photonics, acoustics, and other classical-wave systems. Recently, there has been theoretical interest in exploring many-body BICs in interacting quantum systems, which necessitate the careful design of impurity potentials or spatial profiles of interaction. Here, we propose a type of many-body BICs localized at boundaries, which can be purely induced by the uniform onsite interaction without requiring any specific design of impurity potential or nonlocal interaction. We numerically show that three or more interacting bosons can concentrate on the boundary of a homogeneous one-dimensional lattice, which is absent at single- and two-particle counterparts. Moreover, the eigenenergy of multi-boson bound states can embed within the continuous energy spectra of extended scattering states, thereby giving rise to interaction-induced boundary many-body BICs. Furthermore, by mapping Fock states of three and four bosons to nonlinear circuit networks, we experimentally simulate boundary many-body BICs. Our findings enrich the comprehension of correlated BICs beyond the single-particle level, and have the potential to inspire future investigations on exploring many-body BICs.

Single-Particle Imaging Photoinduced Charge Transfer of Ferroelectric Polarized Heterostructures for Photocatalysis.

Piezoelectric-assisted photocatalysis has a huge potential in solving the energy shortage and environmental pollution problems, and imaging their detailed charge-transfer process can provide in-depth understanding for the development of high-active piezo-photocatalysts; however, it is still challenging. Herein, topotactic heterostructures of TiO2@BaTiO3 (TO@BTO-S) were constructed by the epitaxial growth of ferroelectric BaTiO3 mesocrystals on TiO2-{001} facets, resulting in a ferroelectric photocatalyst with a polarization orientation on the surface. Notably, the photoinduced charge transfer in ferroelectric TiO2@BaTiO3 was accurately monitored and directly visualized at the single-particle level by the advanced photoluminescence (PL) imaging microscopy systems. The longer PL lifetime of TO@BTO-S demonstrated the efficient charge separation caused by a built-in electric field, which is constructed by the polarization orientation of BaTiO3 mesocrystals. Therefore, the TO@BTO-S heterostructure exhibits efficient piezoelectric-assisted photocatalytic pure water splitting, which is 290 times higher than photocatalysis. This work revealed time/spatial-resolved photoinduced charge transfer in piezoelectric assistance photocatalysts at the single-particle level and demonstrated the great role of polarization orientation in promoting charge transfer for photocatalysis.

Visualization of Biomolecular Radiation Damage at the Single-Particle Level Using Lanthanide-Sensitized DNA Origami.

Precise monitoring of biomolecular radiation damage is crucial for understanding X-ray-induced cell injury and improving the accuracy of clinical radiotherapy. We present the design and performance of lanthanide-DNA-origami nanodosimeters for directly visualizing radiation damage at the single-particle level. Lanthanide ions (Tb3+ or Eu3+) coordinated with DNA origami nanosensors enhance the sensitivity of X-ray irradiation. Atomic force microscopy (AFM) revealed morphological changes in Eu3+-sensitized DNA origami upon X-ray irradiation, indicating damage caused by ionization-generated electrons and free radicals. We further demonstrated the practical applicability of Eu3+-DNA-origami integrated chips in precisely monitoring radiation-mediated cancer radiotherapy. Quantitative results showed consistent trends with flow cytometry and histological examination under comparable X-ray irradiation doses, providing an affordable and user-friendly visualization tool for preclinical applications. These findings provide new insights into the impact of heavy metals on radiation-induced biomolecular damage and pave the way for future research in developing nanoscale radiation sensors for precise clinical radiography.

C2-domain abscisic acid-related proteins regulate the dynamics of a plasma membrane H+-ATPase in response to alkali stress.

Arabidopsis (Arabidopsis thaliana) H+-ATPase1 (AHA1), a plasma membrane (PM)-localized H+-ATPase, plays a key role in plant alkali stress tolerance by pumping protons from the cytoplasm to the apoplast. However, its molecular dynamics are poorly understood. We report that many C2-domain ABA-related (CAR) protein family members interact with AHA1 in Arabidopsis. Single or double mutants of CAR1, CAR6, and CAR10 had no obvious phenotype of alkali stress tolerance, while their triple mutants showed significantly higher tolerance to this stress. The disruption of AHA1 largely compromised the increased alkali stress tolerance of the car1car6car10 mutant, revealing a key role of CARs in AHA1 regulation during the plant's response to a high alkali pH. Furthermore, variable angle total internal reflection fluorescence microscopy was used to observe AHA1-mGFP5 in intact Arabidopsis seedlings, revealing the presence of heterogeneous diffusion coefficients and oligomerization states in the AHA1 spots. In the aha1 complementation lines, alkali stress curtailed the residence time of AHA1 at the PM and increased the diffusion coefficient and particle velocity of AHA1. In contrast, the absence of CAR proteins decreased the restriction of the dynamic behavior of AHA1. Our results suggest that CARs play a negative role in plant alkali stress tolerance by interacting with AHA1 and provide a perspective to investigate the regulatory mechanism of PM H+-ATPase activity at the single-particle level.

A simple guideline for designing droplet microfluidic chips to achieve an improved single (bio)particle encapsulation rate using a stratified flow-assisted particle ordering method

Encapsulation of a single (bio)particle into individual droplets (referred to as single encapsulation) presents tremendous potential for precise biological and chemical reactions at the single (bio)particle level. Previously demonstrated successful strategies often rely on the use of high flow rates, gel, or viscoelastic materials for initial cell ordering prior to encapsulation into droplets, which could potentially challenge the system's operation. We propose to enhance the single encapsulation rate by using a stratified flow structure to focus and pre-order the (bio)particles before encapsulation. The stratified flow structure is formed using two simple aqueous Newtonian fluids with a viscosity contrast, which together serve as the dispersed phase. The single encapsulation rate is influenced by many parameters, including fluid viscosity contrast, geometric conditions, flow conditions and flow rate ratios, and dimensionless numbers such as the capillary number. This study focuses on investigating the influences of these parameters on the focused stream of the stratified flow, which is key for single encapsulation. The results allow the proposal of a simple guideline that can be adopted to design droplet microfluidic chips with an improved single encapsulation rate demanded by a wide range of applications. The guideline was validated by performing the single encapsulation of mouse embryonic stem cells suspended in a gelatin-methacryloyl solution in individual droplets of phosphate buffer saline, achieving a single encapsulation efficiency of up to 70%.

Training Machine-Learned Density Functionals on Band Gaps.

The systematic underestimation of band gaps is one of the most fundamental challenges in semilocal density functional theory (DFT). In addition to hindering the application of DFT to predicting electronic properties, the band gap problem is intimately related to self-interaction and delocalization errors, which make the study of charge transfer mechanisms with DFT difficult. To expand the range of available tools for addressing the band gap problem, we design an approach for machine learning density functionals based on Gaussian processes to explicitly fit single-particle energy levels. We also introduce nonlocal features of the density matrix that are expressive enough to fit these single-particle levels. Combining these developments, we train a machine-learned functional for the exact exchange energy that predicts molecular energy gaps and reaction energies of a wide range of molecules in excellent agreement with reference hybrid DFT calculations. In addition, while being trained solely on molecular data, our model predicts reasonable formation energies of polarons in solids, showcasing its transferability and robustness. We discuss how this approach can be generalized to full exchange-correlation functionals, thus paving the way to the design of state-of-the-art functionals for the prediction of electronic properties of molecules and materials.

The Effects of the Carrier and Ligand Spatial Conformation on RNA Nanodrug Cell Delivery.

Small interfering RNA (siRNA) highlights the immense therapeutic potential for cancer treatment. The major challenge in siRNA therapy is the effective RNA nanodrug delivery system, which is facilitated by the ligand and the carrier. In this study, we analyzed the binding specificity of linear RGD and circular RGD to αVβ3 integrins by mapping the morphology using super-resolution direct stochastic optical reconstruction microscopy. Meanwhile, the binding dynamics was investigated using single-molecule force spectroscopy. Then, the effects of the ligand and carrier on RNA nanodrug cell entry dynamic parameters were evaluated at the single particle level by the force tracing technique. Furthermore, the delivery efficiency of RNA nanodrugs was assessed using AFM-based nanoindentation at the single cell level. This report will provide valuable insights for rational design strategies aiming to achieve improved efficiency for nanodrug delivery systems.

A Fluorogenic Pseudoinfection Assay to Probe Transfer and Distribution of Influenza Viral Contents to Target Vesicles.

Fusion of enveloped viruses with endosomal membranes and subsequent release of the viral genome into the cytoplasm are crucial to the viral infection cycle. It is often modeled by performing fusion between virus particles and target lipid vesicles. We utilized fluorescence microscopy to characterize the kinetic aspects of the transfer of influenza viral ribonucleoprotein (vRNP) complexes to target vesicles and their spatial distribution within the fused volumes to gain deeper insight into the mechanistic aspects of endosomal escape. The fluorogenic RNA-binding dye QuantiFluor (Promega) was found to be well-suited for direct and sensitive microscopic observation of vRNPs which facilitated background-free detection and kinetic analysis of fusion events on a single particle level. To determine the extent to which the viral contents are transferred to the target vesicles through the fusion pore, we carried out virus-vesicle fusion in a side-by-side fashion. Measurement of the Euclidean distances between the centroids of superlocalized membrane and content dye signals within the fused volumes allowed determination of any symmetry (or the lack thereof) between them as expected in the event of transfer (or the lack thereof) of vRNPs, respectively. We found that, in the case of fusion between viruses and 100 nm target vesicles, ∼39% of the events led to transfer of viral contents to the target vesicles. This methodology provides a rapid, generic, and cell-free way to assess the inhibitory effects of antiviral drugs and therapeutics on the endosomal escape behavior of enveloped viruses.