Nanopore Blockade Sensors for Quantitative Analysis Using an Optical Nanopore Assay.

Nanopore sensing is a popular biosensing strategy that is being explored for the quantitative analysis of biomarkers. With low concentrations of analytes, nanopore sensors face challenges related to slow response times and selectivity. Here, we demonstrate an approach to rapidly detect species at ultralow concentrations using an optical nanopore blockade sensor for quantitative detection of the protein vascular endothelial growth factor (VEGF). This sensor relies on monitoring fluorescent polystyrene nanoparticles blocking nanopores in a nanopore array of 676 nanopores. The fluorescent signal is read out using a wide-field fluorescence microscope. Nonspecific blockade events are then distinguished from specific blockade events based on the ability to pull the particles out of the pore using an applied electric field. This allows the detection of VEGF at sub-picomolar concentration in less than 15 min.

Stochastic Electrochemical Measurement of a Biofouling Layer on Gold.

Adsorption of a biofouling layer on the surface of biosensors decreases the electrochemical activity and hence shortens the service life of biosensors, particularly implantable and wearable biosensors. Real-time quantification of the loss of activity is important for in situ assessment of performance while presenting an opportunity to compensate for the loss of activity and recalibrate the sensor to extend the service life. Here, we introduce an electrochemical noise measurement technique as a tool for the quantification of the formation of a biofouling layer on the surface of gold. The technique uniquely affords thermodynamic and kinetic information without applying an external bias (potential and/or current), hence allowing the system to be appraised in its innate state. The technique relies on the analysis of non-faradaic current and potential fluctuations that are intrinsically generated by the interaction of charged species at the electrode surface, i.e., gold. An analytical model is extended to explain the significance of parameters drawn from statistical analysis of the noise signal. This concept is then examined in buffered media in the presence of albumin, a common protein in the blood and a known source of a fouling layer in biological systems. Results indicate that the statistical analysis of the noise signal can quantify the loss of electrochemical activity, which is also corroborated by impedance spectroscopy as a complementary technique.

A review of electrochemical impedance as a tool for examining cell biology and subcellular mechanisms: merits, limits, and future prospects.

Herein the development of cellular impedance biosensors, electrochemical impedance spectroscopy, and the general principles and terms associated with the cell-electrode interface is reviewed. This family of techniques provides quantitative and sensitive information into cell responses to stimuli in real-time with high temporal resolution. The applications of cell-based impedance biosensors as a readout in cell biology is illustrated with a diverse range of examples. The current state of the field, its limitations, the possible available solutions, and the potential benefits of developing biosensors are discussed.

Machine Learning Color Feature Analysis of a High Throughput Nanoparticle Conjugate Sensing Assay.

Plasmonic nanoparticles are finding applications within the single molecule sensing field in a "dimer" format, where interaction of the target with hairpin DNA causes a decrease in the interparticle distance, leading to a localized surface plasmon resonance shift. While this shift may be detected using spectroscopy, achieving statistical relevance requires the measurement of thousands of nanoparticle dimers and the timescales required for spectroscopic analysis are incompatible with point-of-care devices. However, using dark-field imaging of the dimer structures, simultaneous digital analysis of the plasmonic resonance shift after target interaction of thousands of dimer structures may be achieved in minutes. The main challenge of this digital analysis on the single-molecule scale was the occurrence of false signals caused by non-specifically bound clusters of nanoparticles. This effect may be reduced by digitally separating dimers from other nanoconjugate types. Variation in image intensity was observed to have a discernible impact on the color analysis of the nanoconjugate constructs and thus the accuracy of the digital separation. Color spaces wherein intensity may be uncoupled from the color information (hue, saturation, and value (HSV) and luminance, a* vector, and b* vector (LAB) were contrasted to a color space which cannot uncouple intensity (RGB) to train a classifier algorithm. Each classifier algorithm was validated to determine which color space produced the most accurate digital separation of the nanoconjugate types. The LAB-based learning classifier demonstrated the highest accuracy for digitally separating nanoparticles. Using this classifier, nanoparticle conjugates were monitored for their plasmonic color shift after interaction with a synthetic RNA target, resulting in a platform with a highly accurate yes/no response with a true positive rate of 88% and a true negative rate of 100%. The sensor response of tested single stranded RNA (ssRNA) samples was well above control responses for target concentrations in the range of 10 aM-1 pM.

Pre-existing clusters of the adaptor Lat do not participate in early T cell signaling events.

Engaged T cell antigen receptors (TCRs) initiate signaling through the adaptor protein Lat. In quiescent T cells, Lat is segregated into clusters on the cell surface, which raises the question of how TCR triggering initiates signaling. Using super-resolution fluorescence microscopy, we found that pre-existing Lat domains were neither phosphorylated nor laterally transported to TCR activation sites, which suggested that these clusters do not participate in TCR signaling. Instead, TCR activation resulted in the recruitment and phosphorylation of Lat from subsynaptic vesicles. Studies of Lat mutants confirmed that recruitment preceded and was essential for phosphorylation and that both processes were independent of surface clustering of Lat. Our data suggest that TCR ligation preconditions the membrane for vesicle recruitment and bulk activation of the Lat signaling network.

Synthetic Strategies to Enhance the Electrocatalytic Properties of Branched Metal Nanoparticles.

Branched metal nanoparticles have unique catalytic properties because of their high surface area with multiple branches arranged in an open 3D structure that can interact with reacting species and tailorable branch surfaces that can maximize the exposure of desired catalytically active crystal facets. These exceptional properties have led to the exploration of the roles of branch structural features ranging from the number and dimensions of branches at the larger scales to the atomic-scale arrangement of atoms on precise crystal facets. The fundamental significance of how larger-scale branch structural features and atomic-scale surface faceting influence and control the catalytic properties has been at the forefront of the design of branched nanoparticles for catalysis. Current synthetic advances have enabled the formation of branched nanoparticles with an unprecedented degree of control over structural features down to the atomic scale, which have unlocked opportunities to make improved nanoparticle catalysts. These catalysts have high surface areas with controlled size and surface facets for achieving exceedingly high activity and stability. The synthetic advancement has recently led to the use of branched nanoparticles as ideal substrates that can be decorated with a second active metal in the form of islands and single atoms. These decorated branched nanoparticles have new and highly effective catalytic active sites where both branch metal and decorating metal play essential roles during catalysis.In the opening half of this Account, we critically assess the important structural features of branched nanoparticles that control catalytic properties. We first discuss the role of branch dimensions and the number of branches that can improve the surface area but can also trap gas bubbles. We then investigate the atomic-scale structural features of exposed surface facets, which are critical for enhancing catalytic activity and stability. Well-defined branched nanoparticles have led to a fundamental understanding of how the branch structural features influence the catalytic activity and stability, which we highlight for the oxygen evolution reaction (OER) and biomass oxidation. In discussing recent breakthroughs for branched nanoparticles, we explore the opportunities created by decorated branched nanoparticles and the unique bifunctional active sites that are exposed on the branched nanoparticle surfaces. This class of catalysts is of rapidly growing importance for reactions including the hydrogen evolution reaction (HER) and methanol oxidation reaction (MOR), where two exposed metals are required for efficient catalysis. In the second half of this Account, we explore recent advances in the synthesis of branched nanoparticles and highlight the cubic-core hexagonal-branch growth mechanism that has achieved excellent control of all of the important structural features, including branch dimensions, number of branches, and surface facets. We discuss the slow precursor reduction as an effective strategy for decorating metal islands with controlled loadings on the branched nanoparticle surfaces and the spread of these metal islands to form single-atom active sites. We envisage that the key synthetic and structural advances identified in this Account will guide the development of the next-generation electrocatalysts.

Tuning the Mechanical Properties of Multiarm RAFT-Based Block Copolyelectrolyte Hydrogels via Ionic Cross-Linking for 3D Cell Cultures.

Hydrogels that serve as native extracellular matrix (ECM) mimics are typically naturally derived hydrogels that are physically cross-linked via ionic interactions. This means rapid gelation of synthetic polymers, which give control over the chemical and physical cues in hydrogel formation. Herein, we combine the best of both systems by developing a synthetic hydrogel with ionic cross-linking of block copolyelectrolytes to rapidly create hydrogels. Reversible addition-fragmentation chain-transfer (RAFT) polymerization was used to synthesize oppositely charged polyelectrolyte molecules and, in turn, modulate the mechanical property of stiffness. The mechanical stiffness of a range of 900-3500 Pa was tuned by varying the number of charged ionic groups, the length of the polymer arms, and the polymer concentration. We demonstrate the synthetic polyelectrolyte hydrogel as an ECM mimic for three-dimensional (3D) in vitro cell models using MCF-7 breast cancer cells.

The application of single molecule nanopore sensing for quantitative analysis.

Nanopore-based sensors typically work by monitoring transient pulses in conductance via current-time traces as molecules translocate through the nanopore. The unique property of being able to monitor single molecules gives nanopore sensors the potential as quantitative sensors based on the counting of single molecules. This review provides an overview of the concepts and fabrication of nanopore sensors as well as nanopore sensing with a view toward using nanopore sensors for quantitative analysis. We first introduce the classification of nanopores and highlight their applications in molecular identification with some pioneering studies. The review then shifts focus to recent strategies to extend nanopore sensors to devices that can rapidly and accurately quantify the amount of an analyte of interest. Finally, future prospects are provided and briefly discussed. The aim of this review is to aid in understanding recent advances, challenges, and prospects for nanopore sensors for quantitative analysis.

Understanding and modelling the magnitude of the change in current of nanopore sensors.

Nanopores are promising sensing devices that can be used for the detection of analytes at the single molecule level. It is of importance to understand and model the current response of a nanopore sensor for improving the sensitivity of the sensor, a better interpretation of the behaviours of different analytes in confined nanoscale spaces, and quantitative analysis of the properties of the targets. The current response of a nanopore sensor, usually called a resistive pulse, results from the change in nanopore resistance when an analyte translocates through the nanopore. This article reviews the theoretical models used for the calculation of the resistance of the nanopore, and the corresponding change in nanopore resistance due to a translocation event. Models focus on the resistance of the pore cavity region and the access region of the nanopore. The influence of the sizes, shapes and surface charges of the translocating species and the nanopore, as well as the trajectory that the analyte follows are also discussed. This review aims to give a general guidance to the audience for understanding the current response of a nanopore sensor and the application of this class of sensor to a broad range of species with the theoretical models.

How can we use the endocytosis pathways to design nanoparticle drug-delivery vehicles to target cancer cells over healthy cells?

Targeted drug delivery in cancer typically focuses on maximising the endocytosis of drugs into the diseased cells. However, there has been less focus on exploiting the differences in the endocytosis pathways of cancer cells versus non-cancer cells. An understanding of the endocytosis pathways in both cancer and non-cancer cells allows for the design of nanoparticles to deliver drugs to cancer cells whilst restricting healthy cells from taking up anticancer drugs, thus efficiently killing the cancer cells. Herein we compare the differences in the endocytosis pathways of cancer and healthy cells. Second, we highlight the importance of the physicochemical properties of nanoparticles (size, shape, stiffness, and surface chemistry) on cellular uptake and how they can be adjusted to selectively target the dominated endocytosis pathway of cancer cells over healthy cells and to deliver anticancer drug to the target cells. The review generates new thought in the design of cancer-selective nanoparticles based on the endocytosis pathways.

Optical Nanopore Sensors for Quantitative Analysis.

Nanopore sensors have received significant interest for the detection of clinically important biomarkers with single-molecule resolution. These sensors typically operate by detecting changes in the ionic current through a nanopore due to the translocation of an analyte. Recently, there has been interest in developing optical readout strategies for nanopore sensors for quantitative analysis. This is because they can utilize wide-field microscopy to independently monitor many nanopores within a high-density array. This significantly increases the amount of statistics that can be obtained, thus enabling the analysis of analytes present at ultralow concentrations. Here, we review the use of optical nanopore sensing strategies for quantitative analysis. We discuss optical nanopore sensing assays that have been developed to detect clinically relevant biomarkers, the potential for multiplexing such measurements, and techniques to fabricate high density arrays of nanopores with a view toward the use of these devices for clinical applications.

Introducing Stacking Faults into Three-Dimensional Branched Nickel Nanoparticles for Improved Catalytic Activity.

Creating high surface area nanocatalysts that contain stacking faults is a promising strategy to improve catalytic activity. Stacking faults can tune the reactivity of the active sites, leading to improved catalytic performance. The formation of branched metal nanoparticles with control of the stacking fault density is synthetically challenging. In this work, we demonstrate that varying the branch width by altering the size of the seed that the branch grows off is an effective method to precisely tune the stacking fault density in branched Ni nanoparticles. A high density of stacking faults across the Ni branches was found to lower the energy barrier for Ni2+/Ni3+ oxidation and result in enhanced activity for electrocatalytic oxidation of 5-hydroxylmethylfurfural. These results show the ability to synthetically control the stacking fault density in branched nanoparticles as a basis for enhanced catalytic activity.

Biomolecular Binding under Confinement: Statistical Predictions of Steric Influence in Absence of Long-Distance Interactions.

We propose a theoretical model for the influence of confinement on biomolecular binding at the single-molecule scale at equilibrium, based on the change of the number of microstates (localization and orientation) upon reaction. Three cases are discussed: DNA sequences shorter and longer than the single strain DNA Kuhn length and spherical proteins, confined into a spherical container (liposome, droplet, etc.). The influence of confinement is found to be highly dependent on the molecular structure and significant for large molecules (relative to container size).

Spiers Memorial Lecture. Next generation nanoelectrochemistry: the fundamental advances needed for applications.

Nanoelectrochemistry, where electrochemical processes are controlled and investigated with nanoscale resolution, is gaining more and more attention because of the many potential applications in energy and sensing and the fact that there is much to learn about fundamental electrochemical processes when we explore them at the nanoscale. The development of instrumental methods that can explore the heterogeneity of electrochemistry occurring across an electrode surface, monitoring single molecules or many single nanoparticles on a surface simultaneously, have been pivotal in giving us new insights into nanoscale electrochemistry. Equally important has been the ability to synthesise or fabricate nanoscale entities with a high degree of control that allows us to develop nanoscale devices. Central to the latter has been the incredible advances in nanomaterial synthesis where electrode materials with atomic control over electrochemically active sites can be achieved. After introducing nanoelectrochemistry, this paper focuses on recent developments in two major application areas of nanoelectrochemistry; electrocatalysis and using single entities in sensing. Discussion of the developments in these two application fields highlights some of the advances in the fundamental understanding of nanoelectrochemical systems really driving these applications forward. Looking into our nanocrystal ball, this paper then highlights: the need to understand the impact of nanoconfinement on electrochemical processes, the need to measure many single entities, the need to develop more sophisticated ways of treating the potentially large data sets from measuring such many single entities, the need for more new methods for characterising nanoelectrochemical systems as they operate and the need for material synthesis to become more reproducible as well as possess more nanoscale control.

Statistical predictions on the encapsulation of single molecule binding pairs into sized-dispersed nanocontainers.

Single molecule experiments have recently attracted enormous interest. Many of these studies involve the encapsulation of a single molecule into nanoscale containers (such as vesicles, droplets and nanowells). In such cases, the single molecule encapsulation efficiency is a key parameter to consider in order to get a statistically significant quantitative information. It has been shown that such encapsulation typically follows a Poisson distribution and such theory of encapsulation has only been applied to the encapsulation of single molecules into perfectly sized monodispersed containers. However, experimentally nanocontainers are usually characterized by a size distribution, and often just a single binding pair (rather than a single molecule) is required to be encapsulated. Here the use of Poisson distribution is extended to predict the encapsulation efficiency of two different molecules in an association equilibrium. The Poisson distribution is coupled with a log-normal distribution in order to consider the effect of the container size distribution, and the effect of adsorption to the container is also considered. This theory will allow experimentalists to determine what single molecule encapsulation efficiency can be expected as a function of the experimental conditions. Two case studies, based on experimental data, are given to support the theoretical predictions.

Key Parameters That Determine the Magnitude of the Decrease in Current in Nanopore Blockade Sensors.

Nanopore blockade sensors were developed to address the challenges of sensitivity and selectivity for conventional nanopore sensors. To date, the parameters affecting the current of the sensor have not been elucidated. Herein, the impacts of nanopore size and charge and the shape, size, surface charge, and aggregation state of magnetic nanoparticles were assessed. The sensor was tolerant to all parameters contrary to predictions from electronic or geometric arguments on the current change. Theoretical models showed the greater importance of the polymers around nanoparticles and the access resistance of nanopores to the current, when compared with translocation-based nanopore sensors. The signal magnitude was dominated by the change in access resistance of ∼4.25 MΩ for all parameters, resulting in a robust system. The findings provide understandings of changes in current when nanopores are blocked, like in RNA trapping or nanopore blockade sensors, and are important for designing sensors based on nanopore blockades.

The Influence of Nanoconfinement on Electrocatalysis.

The use of nanoparticles and nanostructured electrodes are abundant in electrocatalysis. These nanometric systems contain elements of nanoconfinement in different degrees, depending on the geometry, which can have a much greater effect on the activity and selectivity than often considered. In this Review, we firstly identify the systems containing different degrees of nanoconfinement and how they can affect the activity and selectivity of electrocatalytic reactions. Then we follow with a fundamental understanding of how electrochemistry and electrocatalysis are affected by nanoconfinement, which is beginning to be uncovered, thanks to the development of new, atomically precise manufacturing and fabrication techniques as well as advances in theoretical modeling. The aim of this Review is to help us look beyond using nanostructuring as just a way to increase surface area, but also as a way to break the scaling relations imposed on electrocatalysis by thermodynamics.

Self-Propelled Initiative Collision at Microelectrodes with Vertically Mobile Micromotors.

Impact experiments enable single particle analysis for many applications. However, the effect of the trajectory of a particle to an electrode on impact signals still requires further exploration. Here, we investigate the particle impact measurements versus motion using micromotors with controllable vertical motion. With biocatalytic cascade reactions, the micromotor system utilizes buoyancy as the driving force, thus enabling more regulated interactions with the electrode. With the aid of numerical simulations, the dynamic interactions between the electrode and micromotors are categorized into four representative patterns: approaching, departing, approaching-and-departing, and departing-and-reapproaching, which correspond well with the experimentally observed impact signals. This study offers a possibility of exploring the dynamic interactions between the electrode and particles, shedding light on the design of new electrochemical sensors.

Functionalized Gold Nanorod Probes: A Sophisticated Design of SERS Immunoassay for Biodetection in Complex Media.

Surface-enhanced Raman scattering (SERS) probes offer considerable opportunities in label-based biosensing and analysis. However, achieving specific and reproducible performance, where low detection limits are needed in complex media, remains a challenge. Herein, we present a general strategy employing gold nanorod SERS probes and rationally designed surface chemistry involving protein resistant layers and antibodies to allow for the selective detection of species in complex media. By utilizing the ability of gold nanorods for selective surface modification, Raman reporters (4-mercaptobenzoic acid) were attached to the tips. Importantly, the sides of the nanorods were modified using a mixed layer of two different length stabilizing ligands (carboxyl-terminated oligo ethylene glycols) to ensure colloidal stability, while antibodies were attached to the stabilizing ligands. The nanoparticle interfacial design improves the colloidal stability, unlocks the capability of the probes for targeting biomolecules in complex matrices, and gives the probes the high SERS efficiency. The utility of this probe is demonstrated herein via the detection of Salmonella bacteria at the single bacterium level in complex food matrices using an anti-Salmonella IgG antibody-conjugated probe. The modular nature of the surface chemistry enables the SERS probes to be employed with a molecularly diverse range of biorecognition species (e.g., antibodies and peptides) for many different analytes, thus opening up new opportunities for efficient biosensing applications.

Investigating Spatial Heterogeneity of Nanoparticles Movement in Live Cells with Pair-Correlation Microscopy and Phasor Analysis.

How nanoparticles distribute in living cells and overcome cellular barriers are important criteria in the design of drug carriers. Pair-correlation microscopy is a correlation analysis of fluctuation in the fluorescence intensity obtained by a confocal line scan that can quantify the dynamic properties of nanoparticle diffusion including the number of mobile nanoparticles, diffusion coefficient, and transit time across a spatial distance. Due to the potential heterogeneities in nanoparticle properties and the complexity within the cellular environment, quantification of averaged auto- and pair-correlation profiles may obscure important insights into the ability of nanoparticles to deliver drugs. To overcome this issue, we used phasor analysis to develop a data standardizing method, which can segment the scanned line into several subregions according to diffusion and address the spatial heterogeneity of nanoparticles moving inside cells. The phasor analysis is a fit-free method that represents autocorrelation profiles for each pixel relative to free diffusion on the so-called phasor plots. Phasor plots can then be used to select subpopulations for which the auto- and pair-correlation analysis can be performed separately. We demonstrate the phasor analysis for pair-correlation microscopy for investigating 16 nm, Cy5-labeled silica nanoparticles diffusing across the plasma membrane and green fluorescent proteins (GFP) diffusing across nuclear envelope in MCF-7 cells.