Rapid structural analysis of nanomaterials in aqueous solutions

Wearable sensor supports in-situ and continuous monitoring of plant health in precision agriculture era

Plant health is intricately linked to crop quality, food security and agricultural productivity. Obtaining accurate plant health information is of paramount importance in the realm of precision agriculture. Wearable sensors offer an exceptional avenue for investigating plant health status and fundamental plant science, as they enable real-time and continuous in-situ monitoring of physiological biomarkers. However, a comprehensive overview that integrates and critically assesses wearable plant sensors across various facets, including their fundamental elements, classification, design, sensing mechanism, fabrication, characterization and application, remains elusive. In this study, we provide a meticulous description and systematic synthesis of recent research progress in wearable sensor properties, technology and their application in monitoring plant health information. This work endeavours to serve as a guiding resource for the utilization of wearable plant sensors, empowering the advancement of plant health within the precision agriculture paradigm.

Improvement of Sensitivity and Speed of Virus Sensing Technologies Using nm- and μm-Scale Components

Various viral diseases can be widespread and cause severe disruption to global society. Highly sensitive virus detection methods are needed to take effective measures to prevent the spread of viral infection. This required the development of rapid virus detection technology to detect viruses at low concentrations, even in the biological fluid of patients in the early stages of the disease or environmental samples. This review describes an overview of various virus detection technologies and then refers to typical technologies such as beads-based assay, digital assay, and pore-based sensing, which are the three modern approaches to improve the performance of viral sensing in terms of speed and sensitivity.

Combining dynamic Monte Carlo with machine learning to study nanoparticle translocation

Resistive pulse sensing (RPS) measurements of nanoparticle translocation have the ability to provide information on single-particle level characteristics, such as diameter or mobility, as well as ensemble averages. However, interpreting these measurements is complex and requires an understanding of nanoparticle dynamics in confined spaces as well as the ways in which nanoparticles disrupt ion transport while inside a nanopore. Here, we combine Dynamic Monte Carlo (DMC) simulations with Machine Learning (ML) and Poisson-Nernst-Planck calculations to simultaneously simulate nanoparticle dynamics and ion transport during hundreds of independent particle translocations as a function of nanoparticle size, electrophoretic mobility, and nanopore length. The use of DMC simulations allowed us to explicitly investigate the effects of Brownian motion and nanoparticle/nanopore characteristics on the amplitude and duration of translocation signals. Simulation results were verified with experimental RPS measurements and found to be in quantitative agreement.

Methodology to Detect Biological Particles Using a Biosensing Surface Integrated in Resistive Pulse Sensing

Resistive pulse sensing (RPS) is an analytical method that can be used to individually count particles from a small sample. RPS simply monitors the physical characteristics of particles, such as size, shape, and charge density, and the integration of RPS with biosensing is an attractive theme to detect biological particles such as virus and bacteria. In this report, a methodology of biosensing on RPS was investigated. Polydopamine (PD), an adhesive component of mussels, was used as the base material to create a sensing surface. PD adheres to most materials, such as noble metals, metal oxides, semiconductors, and polymers; as a result, PD is a versatile intermediate layer for the fabrication of a biosensing surface. As an example of a biological particle, human influenza A virus (H1N1 subtype) was used to monitor translocation of particles through the pore membrane. When virus-specific ligands (6'-sialyllactose) were immobilized on the pore surface, the translocation time of the virus particles was considerably extended. The detailed translocation data suggest that the viral particles were trapped on the sensing surface by specific interactions. In addition, virus translocation processes on different pore surfaces were distinguished using machine learning. The result shows that the simple and versatile PD-based biosensor surface design was effective. This advanced RPS measurement system could be a promising analytical technique.

Application of Nanopore Sequencing in the Detection of Foodborne Microorganisms

Foodborne pathogens have become the subject of intense interest because of their high incidence and mortality worldwide. In the past few decades, people have developed many methods to solve this challenge. At present, methods such as traditional microbial culture methods, nucleic acid or protein-based pathogen detection methods, and whole-genome analysis are widely used in the detection of pathogenic microorganisms in food. However, these methods are limited by time-consuming, cumbersome operations or high costs. The development of nanopore sequencing technology offers the possibility to address these shortcomings. Nanopore sequencing, a third-generation technology, has the advantages of simple operation, high sensitivity, real-time sequencing, and low turnaround time. It can be widely used in the rapid detection and serotyping of foodborne pathogens. This review article discusses foodborne diseases, the principle of nanopore sequencing technology, the application of nanopore sequencing technology in foodborne pathogens detection, as well as its development prospects.

Fast Fabrication of Solid-State Nanopores for DNA Molecule Analysis

Solid-state nanopores have been developed as a prominent tool for single molecule analysis in versatile applications. Although controlled dielectric breakdown (CDB) is the most accessible method for a single nanopore fabrication, it is still necessary to improve the fabrication efficiency and avoid the generation of multiple nanopores. In this work, we treated the SiNx membranes in the air–plasma before the CDB process, which shortened the time-to-pore-formation by orders of magnitude. λ-DNA translocation experiments validated the functionality of the pore and substantiated the presence of only a single pore on the membrane. Our fabricated pore could also be successfully used to detect short single-stranded DNA (ssDNA) fragments. Using to ionic current signals, ssDNA fragments with different lengths could be clearly distinguished. These results will provide a valuable reference for the nanopore fabrication and DNA analysis.

Application of Micropore Device for Accurate, Easy, and Rapid Discrimination of Saccharomyces pastorianus from Dekkera spp

Traceability analysis, such as identification and discrimination of yeasts used for fermentation, is important for ensuring manufacturing efficiency and product safety during brewing. However, conventional methods based on morphological and physiological properties have disadvantages such as time consumption and low sensitivity. In this study, the resistive pulse method (RPM) was employed to discriminate between Saccharomyces pastorianus and Dekkera anomala and S. pastorianus and D. bruxellensis by measuring the ionic current response of cells flowing through a microsized pore. The height and shape of the pulse signal were used for the simultaneous measurement of the size, shape, and surface charge of individual cells. Accurate discrimination of S. pastorianus from Dekkera spp. was observed with a recall rate of 96.3 ± 0.8%. Furthermore, budding S. pastorianus was quantitatively detected by evaluating the shape of the waveform of the current ionic blockade. We showed a proof-of-concept demonstration of RPM for the detection of contamination of Dekkera spp. in S. pastorianus and for monitoring the fermentation of S. pastorianus through the quantitative detection of budding cells.

Microfluidic Assessment of Drug Effects on Physical Properties of Androgen Sensitive and Non-Sensitive Prostate Cancer Cells

The identification and treatment of androgen-independent prostate cancer are both challenging and significant. In this work, high-throughput deformability cytometry was employed to assess the effects of two anti-cancer drugs, docetaxel and enzalutamide, on androgen-sensitive prostate cancer cells (LNCaP) and androgen-independent prostate cancer cells (PC-3), respectively. The quantified results show that PC-3 and LNCaP present not only different intrinsic physical properties but also different physical responses to the same anti-cancer drug. PC-3 cells possess greater stiffness and a smaller size than LNCaP cells. As the docetaxel concentration increases, PC-3 cells present an increase in stiffness and size, but LNCaP cells only present an increase in stiffness. As the enzalutamide concentration increases, PC-3 cells present no physical changes but LNCaP cells present changes in both cell size and deformation. These results demonstrated that cellular physical properties quantified by the deformability cytometry are effective indicators for identifying the androgen-independent prostate cancer cells from androgen-sensitive prostate cancer cells and evaluating drug effects on these two types of prostate cancer.

Rapid Discrimination of Extracellular Vesicles by Shape Distribution Analysis

A rapid and simple cancer detection method independent of cancer type is an important technology for cancer diagnosis. Although the expression profiles of biological molecules contained in cancer cell-derived extracellular vesicles (EVs) are considered candidates for discrimination indexes to identify any cancerous cells in the body, it takes a certain amount of time to examine these expression profiles. Here, we report the shape distributions of EVs suspended in a solution and the potential of these distributions as a discrimination index to discriminate cancer cells. Distribution analysis is achieved by low-aspect-ratio nanopore devices that enable us to rapidly analyze EV shapes individually in solution, and the present results reveal a dependence of EV shape distribution on the type of cells (cultured liver, breast, and colorectal cancer cells and cultured normal breast cells) secreting EVs. The findings in this study provide realizability and experimental basis for a simple method to discriminate several types of cancerous cells based on rapid analyses of EV shape distributions.

Effect of Electrolyte Concentration on Cell Sensing by Measuring Ionic Current Waveform through Micropores

Immunostaining has been widely used in cancer prognosis for the quantitative detection of cancer cells present in the bloodstream. However, conventional detection methods based on the target membrane protein expression exhibit the risk of missing cancer cells owing to variable protein expressions. In this study, the resistive pulse method (RPM) was employed to discriminate between cultured cancer cells (NCI-H1650) and T lymphoblastoid leukemia cells (CCRF-CEM) by measuring the ionic current response of cells flowing through a micro-space. The height and shape of a pulse signal were used for the simultaneous measurement of size, deformability, and surface charge of individual cells. An accurate discrimination of cancer cells could not be obtained using 1.0 × phosphate-buffered saline (PBS) as an electrolyte solution to compare the size measurements by a microscopic observation. However, an accurate discrimination of cancer cells with a discrimination error rate of 4.5 ± 0.5% was achieved using 0.5 × PBS containing 2.77% glucose as the electrolyte solution. The potential application of RPM for the accurate discrimination of cancer cells from leukocytes was demonstrated through the measurement of the individual cell size, deformability, and surface charge in a solution with a low electrolyte concentration.

Biological Nanopores: Engineering on Demand

Nanopore-based sensing is a powerful technique for the detection of diverse organic and inorganic molecules, long-read sequencing of nucleic acids, and single-molecule analyses of enzymatic reactions. Selected from natural sources, protein-based nanopores enable rapid, label-free detection of analytes. Furthermore, these proteins are easy to produce, form pores with defined sizes, and can be easily manipulated with standard molecular biology techniques. The range of possible analytes can be extended by using externally added adapter molecules. Here, we provide an overview of current nanopore applications with a focus on engineering strategies and solutions.

Pore Structures for High-Throughput Nanopore Devices

Nanopore devices are expected to advance the next-generation of nanobiodevices because of their strong sensing and analyzing capabilities for single molecules and bioparticles. However, the device throughputs are not sufficiently high. Although analytes pass through a nanopore by electrophoresis, the electric field gradient is localized inside and around a nanopore structure. Thus, analytes located far from a nanopore cannot be driven by electrophoresis. Here, we report nanopore structures for high-throughput sensing, namely, inverted pyramid (IP)-shaped nanopore structures. Silicon-based IP-shaped nanopore structures create a homogeneous electric field gradient within a nanopore device, indicating that most of the analytes can pass through a nanopore by electrophoresis, even though the analytes are suspended far from the nanopore entrance. In addition, the nanostructures can be fabricated only by photolithography. The present study suggests a high potential for inverted pyramid shapes to serve as nanopore devices for high-throughput sensing.

Analysis Method of the Ion Current-Time Waveform Obtained from Low Aspect Ratio Solid-state Nanopores

Low aspect ratio nanopores are expected to be applied to the detection of viruses and bacteria because of their high spatial resolution. Multiphysics simulations have revealed that the ion current-time waveform obtained from low aspect ratio nanopores contains information on not only the volume of viruses and bacteria, but also the structure, surface charge, and flow dynamics. Analysis using machine learning extracts information about these analytes from the ion current-time waveform. The combination of low aspect ratio nanopores, multiphysics simulation, and machine learning has made it possible to distinguish different types of viruses and bacteria with high accuracy.

Volume discrimination of nanoparticles via electrical trapping using nanopores

Electrophoretic capture of an oversized object on a solid-state nanopore is a useful approach for single-particle analyses via post electrical and optical measurements. Here we report on nanoparticle discriminations by the volume through combining this nanopore trap method with the cross-membrane ionic current measurements. We investigated ion transport through a pore channel being partially occluded by an electrophoretically-drawn nanoparticle at the orifice. We found distinct difference in the amount of current blockage by particles of different sizes. Multiphysics simulations revealed dominant contribution of particle volume over the other properties. We also demonstrated single-particle discriminations of two different sizes in a mixture solution. The present results demonstrate that this electrical capturing is a promising technique to immobilize a target at a single particle level that concomitantly offer wealth of information concerning their volume.

Gold Nanoparticles with Ligand/Zwitterion Hybrid Layer for Individual Counting of Influenza A H1N1 Subtype Using Resistive Pulse Sensing

Resistive pulse sensing (RPS) is an analytical technique for detecting particles with nano- to micrometer diameters, such as proteins, viruses, and bacteria. RPS is a promising tool for diagnosis as it can analyze the characteristics of target particles individually from ion current blockades as pulse waveforms. However, it is difficult to discriminate analog targets because RPS merely provides physical information such as size, shape, concentration, and charge density of the analyte. Influenza A virus, which is 80-120 nm in diameter, has various subtypes, demonstrating the diversity of virus characteristics. For example, highly pathogenic avian influenza infections in humans are recognized as an emerging infectious disease with high mortality rates compared with human influenza viruses. Distinguishing human from avian influenza using their differing biological characteristics would be challenging using RPS. To develop a highly selective diagnostic system for infectious diseases, we combined RPS with molecular recognition. Gold nanoparticles (GNPs) that have human influenza A (H1N1 subtype) virus-specific sialic acid receptors on the surface were prepared as a virus label for RPS analysis. A sulfobetaine and sialic acid (ligand) hybrid surface was formed on the GNPs for the suppression of nonspecific interaction. The results show a size change of viruses derived from specific interactions with GNPs. In contrast, no size shift was observed when nonspecific sialic acid receptor-immobilized GNPs were used. Detection of viruses by individual particle counting could be a new facet of diagnosis.

Clog and Release, and Reverse Motions of DNA in a Nanopore

Motions of circular and linear DNA molecules of various lengths near a nanopore of 100 or 200 nm diameter were experimentally observed and investigated by fluorescence microscopy. The movement of DNA molecules through nanopores, known as translocation, is mainly driven by electric fields near and inside the pores. We found significant clogging of nanopores by DNA molecules, particularly by circular DNA and linear T4 DNA (165.65 kbp). Here, the probabilities of DNA clogging events, depending on the DNA length and shape—linear or circular—were determined. Furthermore, two distinct DNA motions were observed: clog and release by linear T4 DNA, and a reverse direction motion at the pore entrance by circular DNA, after which both molecules moved away from the pore. Finite element method-based numerical simulations were performed. The results indicated that DNA molecules with pores 100–200 nm in diameter were strongly influenced by opposing hydrodynamic streaming flow, which was further enhanced by bulky DNA configurations.