Single molecule analysis by biological nanopore sensors

Detection of Glutamate Decarboxylase Antibodies and Simultaneous Multi-Molecular Translocation Exploration by Glass Nanopores

Glutamic acid decarboxylase antibody (GADAb) has emerged as a significant biomarker for clinical diagnosis and prognosis in type 1 diabetes (T1D). In this study, we investigated the potential utilization of glass capillary solid-state nanopores as a cost-effective and easily preparable platform for the detection of individual antigens, antibodies, and antigen-antibody complexes without necessitating any modifications to the nanopores. Our findings revealed notable characteristic variations in the translocation events of glutamic acid decarboxylase (GAD65) through nanopores under different voltage conditions, discovered that anomalous phenomenon of protein translocation events increasing with voltage may potentially be caused by the crowding of multiple proteins in the nanopores, and demonstrated that there are multiple components in the polyclonal antibodies (GADAb-poly). Furthermore, we achieved successful differentiation between GAD65, GADAb, and GADAb-GAD65 complexes. These results offer promising prospects for the development of a rapid and reliable GADAb detection method, which holds the potential to be applied in patient serum samples, thereby facilitating a label-free, cost-effective, and early diagnosis of type I diabetes.

Characterizing Prion-Like Protein Aggregation: Emerging Nanopore-Based Approaches

Prion-like protein aggregation is characteristic of numerous neurodegenerative diseases, such as Alzheimer's and Parkinson's diseases. This process involves the formation of aggregates ranging from small and potentially neurotoxic oligomers to highly structured self-propagating amyloid fibrils. Various approaches are used to study protein aggregation, but they do not always provide continuous information on the polymorphic, transient, and heterogeneous species formed. This review provides an updated state-of-the-art approach to the detection and characterization of a wide range of protein aggregates using nanopore technology. For each type of nanopore, biological, solid-state polymer, and nanopipette, discuss the main achievements for the detection of protein aggregates as well as the significant contributions to the understanding of protein aggregation and diagnostics.

T-S2Inet: Transformer-based sequence-to-image network for accurate nanopore sequence recognition

MOTIVATION

Nanopore sequencing is a new macromolecular recognition and perception technology that enables high-throughput sequencing of DNA, RNA, even protein molecules. The sequences generated by nanopore sequencing span a large time frame, and the labor and time costs incurred by traditional analysis methods are substantial. Recently, research on nanopore data analysis using machine learning algorithms has gained unceasing momentum, but there is often a significant gap between traditional and deep learning methods in terms of classification results. To analyze nanopore data using deep learning technologies, measures such as sequence completion and sequence transformation can be employed. However, these technologies do not preserve the local features of the sequences. To address this issue, we propose a sequence-to-image (S2I) module that transforms sequences of unequal length into images. Additionally, we propose the Transformer-based T-S2Inet model to capture the important information and improve the classification accuracy.

RESULTS

Quantitative and qualitative analysis shows that the experimental results have an improvement of around 2% in accuracy compared to previous methods. The proposed method is adaptable to other nanopore platforms, such as the Oxford nanopore. It is worth noting that the proposed method not only aims to achieve the most advanced performance, but also provides a general idea for the analysis of nanopore sequences of unequal length.

AVAILABILITY AND IMPLEMENTATION

The main program is available at https://github.com/guanxiaoyu11/S2Inet.

Deep Learning-Assisted Single-Molecule Detection of Protein Post-translational Modifications with a Biological Nanopore

Protein post-translational modifications (PTMs) play a crucial role in countless biological processes, profoundly modulating protein properties on both spatial and temporal scales. Protein PTMs have also emerged as reliable biomarkers for several diseases. However, only a handful of techniques are available to accurately measure their levels, capture their complexity at a single molecule level, and characterize their multifaceted roles in health and disease. Nanopore sensing provides high sensitivity for the detection of low-abundance proteins, holding the potential to impact single-molecule proteomics and PTM detection, in particular. Here, we demonstrate the ability of a biological nanopore, the pore-forming toxin aerolysin, to detect and distinguish α-synuclein-derived peptides bearing single or multiple PTMs, namely, phosphorylation, nitration, and oxidation occurring at different positions and in various combinations. The characteristic current signatures of the α-synuclein peptide and its PTM variants could be confidently identified by using a deep learning model for signal processing. We further demonstrate that this framework can quantify α-synuclein peptides at picomolar concentrations and detect the C-terminal peptides generated by digestion of full-length α-synuclein. Collectively, our work highlights the advantage of using nanopores as a tool for simultaneous detection of multiple PTMs and facilitates their use in biomarker discovery and diagnostics.

Stochastic Sensing of Dynamic Interactions and Chemical Reactions with Nanopores/Nanochannels

Nanopore sensing technology is an emerging analysis method with the advantages of simple operation, high sensitivity, fast output and being label free, and it is widely used in protein analysis, gene sequencing, biomarker detection, and other fields. The confined space of the nanopore provides a place for dynamic interactions and chemical reactions between substances. The use of nanopore sensing technology to track these processes in real time is helpful to understand the interaction/reaction mechanism at the single-molecule level. According to nanopore materials, we summarize the development of biological nanopores and solid-state nanopores/nanochannels in the stochastic sensing of dynamic interactions and chemical reactions. The goal of this paper is to stimulate the interest of researchers and promote the development of this field.

High Sensitivity Extended Nano-Coulter Counter for Detection of Viral Particles and Extracellular Vesicles

We present a chip-based extended nano-Coulter counter (XnCC) that can detect nanoparticles affinity-selected from biological samples with low concentration limit-of-detection that surpasses existing resistive pulse sensors by 2-3 orders of magnitude. The XnCC was engineered to contain 5 in-plane pores each with an effective diameter of 350 nm placed in parallel and can provide high detection efficiency for single particles translocating both hydrodynamically and electrokinetically through these pores. The XnCC was fabricated in cyclic olefin polymer (COP) via nanoinjection molding to allow for high-scale production. The concentration limit-of-detection of the XnCC was 5.5 × 103 particles/mL, which was a 1,100-fold improvement compared to a single in-plane pore device. The application examples of the XnCC included counting affinity selected SARS-CoV-2 viral particles from saliva samples using an aptamer and pillared microchip; the selection/XnCC assay could distinguish the COVID-19(+) saliva samples from those that were COVID-19(-). In the second example, ovarian cancer extracellular vesicles (EVs) were affinity selected using a pillared chip modified with a MUC16 monoclonal antibody. The affinity selection chip coupled with the XnCC was successful in discriminating between patients with high grade serous ovarian cancer and healthy donors using blood plasma as the input sample.

SmartImage: A Machine Learning Method for Nanopore Identifying Chemical Modifications on RNA

RNA modifications modulate essential cellular functions. However, it is challenging to quantitatively identify the differences in RNA modifications. To further improve the single-molecule sensing ability of nanopores, we propose a machine-learning algorithm called SmartImage for identifying and classifying nanopore electrochemical signals based on a combination of improved graph conversion methods and deep neural networks. SmartImage is effective for nearly all ranges of signal duration, which breaks the limitation of the current nanopore algorithm. The overall accuracy (OA) of our proposed recognition strategy exceeded 90% for identifying three types of RNAs. Prediction experiments show that the SmartImage owns the ability to recognize one modified RNA molecule from 1000 normal RNAs with OA >90%. Thus our proposed model and algorithm hold the potential application in clinical applications.

Active learning for efficient analysis of high-throughput nanopore data

MOTIVATION

As the third-generation sequencing technology, nanopore sequencing has been used for high-throughput sequencing of DNA, RNA, and even proteins. Recently, many studies have begun to use machine learning technology to analyze the enormous data generated by nanopores. Unfortunately, the success of this technology is due to the extensive labeled data, which often suffer from enormous labor costs. Therefore, there is an urgent need for a novel technology that can not only rapidly analyze nanopore data with high-throughput, but also significantly reduce the cost of labeling. To achieve the above goals, we introduce active learning to alleviate the enormous labor costs by selecting the samples that need to be labeled. This work applies several advanced active learning technologies to the nanopore data, including the RNA classification dataset (RNA-CD) and the Oxford Nanopore Technologies barcode dataset (ONT-BD). Due to the complexity of the nanopore data (with noise sequence), the bias constraint is introduced to improve the sample selection strategy in active learning. Results: The experimental results show that for the same performance metric, 50% labeling amount can achieve the best baseline performance for ONT-BD, while only 15% labeling amount can achieve the best baseline performance for RNA-CD. Crucially, the experiments show that active learning technology can assist experts in labeling samples, and significantly reduce the labeling cost. Active learning can greatly reduce the dilemma of difficult labeling of high-capacity nanopore data. We hope active learning can be applied to other problems in nanopore sequence analysis.

AVAILABILITY AND IMPLEMENTATION

The main program is available at https://github.com/guanxiaoyu11/AL-for-nanopore.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A Generalized Transformer-Based Pulse Detection Algorithm

Pulse-like signals are ubiquitous in the field of single molecule analysis, e.g., electrical or optical pulses caused by analyte translocations in nanopores. The primary challenge in processing pulse-like signals is to capture the pulses in noisy backgrounds, but current methods are subjectively based on a user-defined threshold for pulse recognition. Here, we propose a generalized machine-learning based method, named pulse detection transformer (PETR), for pulse detection. PETR determines the start and end time points of individual pulses, thereby singling out pulse segments in a time-sequential trace. It is objective without needing to specify any threshold. It provides a generalized interface for downstream algorithms for specific application scenarios. PETR is validated using both simulated and experimental nanopore translocation data. It returns a competitive performance in detecting pulses through assessing them with several standard metrics. Finally, the generalization nature of the PETR output is demonstrated using two representative algorithms for feature extraction.

Solid-state nanopore: chemical modifications, interactions, and functionalities

Nanopore technology is a burgeoning detection technology for single-molecular sensing and ion rectification. Solid-state nanopores have attracted more and more attention because of their higher stability and tunability than biological nanopores. However, solid-state nanopores still suffer the drawbacks of low signal-to-noise ratio and low resolution, which hinders their practical applications. Thus, developing operatical and useful methods to overcome the shortages of solid-state nanopores is urgently needed. Here, we summarize the recent research on nanopore modification to achieve this goal. Modifying solid-state nanopores with different coating molecules can improve the selectivity, sensitivity, and stability of nanopores. The modified molecules can introduce different functions into the nanopores, greatly expanding the applications of this novel detection technology. We hope that this review of nanopore modification will provide new ideas for this field.

Epigenetic tumor heterogeneity in the era of single-cell profiling with nanopore sequencing

Nanopore sequencing has brought the technology to the next generation in the science of sequencing. This is achieved through research advancing on: pore efficiency, creating mechanisms to control DNA translocation, enhancing signal-to-noise ratio, and expanding to long-read ranges. Heterogeneity regarding epigenetics would be broad as mutations in the epigenome are sensitive to cause new challenges in cancer research. Epigenetic enzymes which catalyze DNA methylation and histone modification are dysregulated in cancer cells and cause numerous heterogeneous clones to evolve. Detection of this heterogeneity in these clones plays an indispensable role in the treatment of various cancer types. With single-cell profiling, the nanopore sequencing technology could provide a simple sequence at long reads and is expected to be used soon at the bedside or doctor's office. Here, we review the advancements of nanopore sequencing and its use in the detection of epigenetic heterogeneity in cancer.

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.

S2Snet: deep learning for low molecular weight RNA identification with nanopore

Ribonucleic acid (RNA) is a pivotal nucleic acid that plays a crucial role in regulating many biological activities. Recently, one study utilized a machine learning algorithm to automatically classify RNA structural events generated by a Mycobacterium smegmatis porin A nanopore trap. Although it can achieve desirable classification results, compared with deep learning (DL) methods, this classic machine learning requires domain knowledge to manually extract features, which is sophisticated, labor-intensive and time-consuming. Meanwhile, the generated original RNA structural events are not strictly equal in length, which is incompatible with the input requirements of DL models. To alleviate this issue, we propose a sequence-to-sequence (S2S) module that transforms the unequal length sequence (UELS) to the equal length sequence. Furthermore, to automatically extract features from the RNA structural events, we propose a sequence-to-sequence neural network based on DL. In addition, we add an attention mechanism to capture vital information for classification, such as dwell time and blockage amplitude. Through quantitative and qualitative analysis, the experimental results have achieved about a 2% performance increase (accuracy) compared to the previous method. The proposed method can also be applied to other nanopore platforms, such as the famous Oxford nanopore. It is worth noting that the proposed method is not only aimed at pursuing state-of-the-art performance but also provides an overall idea to process nanopore data with UELS.

Methods for isolating and analyzing physiological hyaluronan: a review

The carbohydrate hyaluronan (or hyaluronic acid, HA) is found in all human tissues and biofluids where it has wide-ranging functions in health and disease that are dictated by both its abundance and size. Consequently, hyaluronan evaluation in physiological samples has significant translational potential. Although the analytical tools and techniques for probing other biomolecules such as proteins and nucleic acids have become standard approaches in biochemistry, those available for investigating hyaluronan are less well established. In this review, we survey methods related to the assessment of native hyaluronan in biological specimens, including protocols for separating it from biological matrices and technologies for determining its concentration and molecular weight.

Detection of small-sized DNA fragments in a glassy nanopore by utilization of CRISPR-Cas12a as a converter system

The fabrication of nanopores with a matched pore size, and the existence of multiple interferents make the reproducible detection of small-sized molecules by means of solid-state nanopores still challenging. A useful method to solve these problems is based on the detection of large DNA nanostructures related to the existence of small-sized targets. In particular, a DNA tetrahedron with a well-defined 3D nanostructure is the ideal candidate for use as a signal transducer. Here, we demonstrate the detection of an L1-encoding gene of HPV18 as a test DNA target sequence in a reaction buffer solution, where long single-stranded DNA linking DNA tetrahedra onto the surface of the magnetic beads is cleaved by a target DNA-activated CRISPR-cas12 system. The DNA tetrahedra are subsequently released and can be detected by the current pulse in a glassy nanopore. This approach has several advantages: (1) one signal transducer can be used to detect different targets; (2) a glassy nanopore with a pore size much larger than the target DNA fragment can boost the tolerance of the contaminants and interferents which often degrade the performance of a nanopore sensor.

Nanodevices for Biological and Medical Applications: Development of Single-Molecule Electrical Measurement Method

A comprehensive detection of a wide variety of diagnostic markers is required for the realization of personalized medicine. As a sensor to realize such personalized medicine, a single molecule electrical measurement method using nanodevices is currently attracting interest for its comprehensive simultaneous detection of various target markers for use in biological and medical application. Single-molecule electrical measurement using nanodevices, such as nanopore, nanogap, or nanopipette devices, has the following features:; high sensitivity, low-cost, high-throughput detection, easy-portability, low-cost availability by mass production technologies, and the possibility of integration of various functions and multiple sensors. In this review, I focus on the medical applications of single- molecule electrical measurement using nanodevices. This review provides information on the current status and future prospects of nanodevice-based single-molecule electrical measurement technology, which is making a full-scale contribution to realizing personalized medicine in the future. Future prospects include some discussion on of the current issues on the expansion of the application requirements for single-mole-cule measurement.

Full Width at Half Maximum of Nanopore Current Blockage Controlled by a Single-Biomolecule Interface

A biological nanopore is one of the predominant single-molecule approaches as a result of its controllable single-biomolecule interface, which could reflect the "intrinsic" information on an individual molecule in a label-free way. Because the current blockage is normally treated as the most important parameter for nanopore identification of every single molecule, the fluctuation of current blockage for certain types of molecules, defined as full width at half maximum (fwhm) of current blockage, actually owns a dominant influence on nanopore resolution. Therefore, controlling the fwhm of current blockage of molecules is critical for the sensing capability of the nanopore. Here, taking an aerolysin nanopore as a model, by precisely controlling the functional group in this single-biomolecule interface, we could narrow the fwhm of nanopore current blockage for DNA identification and prolong the duration inside the nanopore. Moreover, a substantial correlation between fwhm of current blockage and duration is established, showing a non-monotonic variation. Besides, the mechanism is also clarified with studying the detailed current blockage events. This proposed correlation is further demonstrated to be applied uniformly across different mutant aerolysins for a certain DNA. This study proposes a new strategy for regulating molecular sensing from the duration of the analyte, which could guide the resolution of heterogeneity analysis using nanopores.

Recent Progress on Single-Molecule Detection Technologies for Food Safety

Rapid and sensitive detection technologies for food contaminants play vital roles in food safety. Due to the complexity of the food matrix and the trace amount distribution, traditional methods often suffer from unsatisfying accuracy, sensitivity, or specificity. In past decades, single-molecule detection (SMD) has emerged as a way to realize the rapid and ultrasensitive measurement with low sample consumption, showing a great potential in food contaminants detection. For instance, based on the nanopore technique, simple and effective methods for single-molecule analysis of food contaminants have been developed. To our knowledge, there has been a rare review that focuses on SMD techniques for food safety. The present review attempts to cover some typical SMD methods in food safety, including electrochemistry, optical spectrum, and atom force microscopy. Then, recent applications of these techniques for detecting food contaminants such as biotoxins, pesticides, heavy metals, and illegal additives are reviewed. Finally, existing research challenges and future trends of SMD in food safety are also tentatively proposed.

Functionalised nanopores: chemical and biological modifications

Nanopore technology has established itself as a powerful tool for single-molecule studies. By analysing changes in the ion current flowing through a single transmembrane channel, a wealth of molecular information can be elucidated. Early studies utilised nanopore technology for sensing applications, and subsequent developments have diversified its remit. Nanopores can be synthetic, solid-state, or biological in origin, but recent work has seen these boundaries blurred as hybrid functionalised pores emerge. The modification of existing pores and the construction of novel synthetic pores has been an enticing goal for creating systems with tailored properties and functionality. Here, we explore chemically functionalised biological pores and the bio-inspired functionalisation of solid-state pores, highlighting how the convergence of these domains provides enhanced functionality.

The convergence of chemistry, biology, and solid-state approaches enables the construction hybrid nanopores with enhanced single-molecule applications.

Nanopore sensors for viral particle quantification: current progress and future prospects

Rapid, inexpensive, and laboratory-free diagnostic of viral pathogens is highly critical in controlling viral pandemics. In recent years, nanopore-based sensors have been employed to detect, identify, and classify virus particles. By tracing ionic current containing target molecules across nano-scale pores, nanopore sensors can recognize the target molecules at the single-molecule level. In the case of viruses, they enable discrimination of individual viruses and obtaining important information on the physical and chemical properties of viral particles. Despite classical benchtop virus detection methods, such as amplification techniques (e.g., PCR) or immunological assays (e.g., ELISA), that are mainly laboratory-based, expensive and time-consuming, nanopore-based sensing methods can enable low-cost and real-time point-of-care (PoC) and point-of-need (PoN) monitoring of target viruses. This review discusses the limitations of classical virus detection methods in PoN virus monitoring and then provides a comprehensive overview of nanopore sensing technology and its emerging applications in quantifying virus particles and classifying virus sub-types. Afterward, it discusses the recent progress in the field of nanopore sensing, including integrating nanopore sensors with microfabrication technology, microfluidics and artificial intelligence, which have been demonstrated to be promising in developing the next generation of low-cost and portable biosensors for the sensitive recognition of viruses and emerging pathogens.

Recent advances in integrated solid-state nanopore sensors

The advent of single-molecule probing techniques has revolutionized the biomedical and life science fields and has spurred the development of a new class of labs-on-chip based on powerful biosensors. Nanopores represent one of the most recent and most promising single molecule sensing paradigms that is seeing increased chip-scale integration for improved convenience and performance. Due to their physical structure, nanopores are highly sensitive, require low sample volume, and offer label-free, amplification-free, high-throughput real-time detection and identification of biomolecules. Over the last 25 years, nanopores have been extensively employed to detect a variety of biomolecules with a growing range of applicatons ranging from nucleic acid sequencing to ultrasensitive diagnostics to single-molecule biophysics. Nanopores, in particular those in solid-state membranes, also have the potential for integration with other technologies such as optics, plasmonics, microfluidics, and optofluidics to perform more complex tasks for an ever-expanding demand. A number of breakthrough results using integrated nanopore platforms have already been reported, and more can be expected as nanopores remain the focus of innovative research and are finding their way into commercial instruments. This review provides an overview of different aspects and challenges of nanopore technology with a focus on chip-scale integration of solid-state nanopores for biosensing and bioanalytical applications.

Detection of single peptide with only one amino acid modification via electronic fingerprinting using reengineered durable channel of Phi29 DNA packaging motor

Protein post-translational modification (PTM) is crucial to modulate protein interactions and activity in various biological processes. Emerging evidence has revealed PTM patterns participate in the pathology onset and progression of various diseases. Current PTM identification relies mainly on mass spectrometry-based approaches that limit the assessment to the entire protein population in question. Here we report a label-free method for the detection of the single peptide with only one amino acid modification via electronic fingerprinting using reengineered durable channel of phi29 DNA packaging motor, which bears the deletion of 25-amino acids (AA) at the C-terminus or 17-AA at the internal loop of the channel. The mutant channels were used to detect propionylation modification via single-molecule fingerprinting in either the traditional patch-clamp or the portable MinION™ platform of Oxford Nanopore Technologies. Up to 2000 channels are available in the MinION™ Flow Cells. The current signatures and dwell time of individual channels were identified. Peptides with only one propionylation were differentiated. Excitingly, identification of single or multiple modifications on the MinION™ system was achieved. The successful application of PTM differentiation on the MinION™ system represents a significant advance towards developing a label-free and high-throughput detection platform utilizing nanopores for clinical diagnosis based on PTM.

Structural-profiling of low molecular weight RNAs by nanopore trapping/translocation using Mycobacterium smegmatis porin A

Folding of RNA can produce elaborate tertiary structures, corresponding to their diverse roles in the regulation of biological activities. Direct observation of RNA structures at high resolution in their native form however remains a challenge. The large vestibule and the narrow constriction of a Mycobacterium smegmatis porin A (MspA) suggests a sensing mode called nanopore trapping/translocation, which clearly distinguishes between microRNA, small interfering RNA (siRNA), transfer RNA (tRNA) and 5 S ribosomal RNA (rRNA). To further profit from the acquired event characteristics, a custom machine learning algorithm is developed. Events from measurements with a mixture of RNA analytes can be automatically classified, reporting a general accuracy of ~93.4%. tRNAs, which possess a unique tertiary structure, report a highly distinguishable sensing feature, different from all other RNA types tested in this study. With this strategy, tRNAs from different sources are measured and a high structural conservation across different species is observed in single molecule.

Directing a rational design of aptamer-based fluorescence anisotropy assay for sensitive detection of immunoglobulin E by site-specific binding study

Mapping aptamer-protein interactions is important for characterization and applications of aptamers against proteins. We describe here probing affinity interactions between aptamer and immunoglobulin E (IgE) with a fluorescence anisotropy (FA) approach using a series of aptamer probes having single fluorescein (FAM) label at individual nucleotide (A, C, T). Studies of binding between IgE and aptamer probes revealed several possible close-contact sites, e.g., T9, T10, T11, T13, C15, and T17 of a 37-nt aptamer with a stem-loop secondary structure. FAM labeling on these sites resulted in much higher FA values (higher than 0.230 for T10, T11, T13 and C15) of aptamer-IgE complexes than the distant sites (e.g., terminals) of aptamer probably because the bound IgE close to these sites significantly restricted local rotation of FAM. Close-contact site labeled aptamer probes with high affinity allowed to develop a more sensitive FA assay for IgE than distant site labeled aptamers. The FA assay using T10-labeled aptamer with a dissociation constant (K_d) about 0.8 nM enabled selective detection of IgE at 20 pM and large FA increase upon IgE addition. We also found A12, C14, A25, and T27 were important for IgE-aptamer binding as FAM labeling at these sites significantly reduced aptamer affinity. FA study showed the loop region of this stem-loop aptamer was crucial for affinity binding, and IgE bound to the loop. This FA method will be helpful for understanding aptamer-protein binding and making a rational design of aptamer affinity assays for proteins.

Fabrication of Si Micropore and Graphene Nanohole Structures by Focused Ion Beam

A biosensor formed by a combination of silicon (Si) micropore and graphene nanohole technology is expected to act as a promising device structure to interrogate single molecule biopolymers, such as deoxyribonucleic acid (DNA). This paper reports a novel technique of using a focused ion beam (FIB) as a tool for direct fabrication of both conical-shaped micropore in Si₃N₄/Si and a nanohole in graphene to act as a fluidic channel and sensing membrane, respectively. The thinning of thick Si substrate down to 50 µm has been performed prior to a multi-step milling of the conical-shaped micropore with final pore size of 3 µm. A transfer of graphene onto the fabricated conical-shaped micropore with little or no defect was successfully achieved using a newly developed all-dry transfer method. A circular shape graphene nanohole with diameter of about 30 nm was successfully obtained at beam exposure time of 0.1 s. This study opens a breakthrough in fabricating an integrated graphene nanohole and conical-shaped Si micropore structure for biosensor applications.

Nanopore Fabrication and Application as Biosensors in Neurodegenerative Diseases

Since its conception as an applied biomedical technology nearly 30 years ago, nanopore is emerging as a promising, high-throughput, biomarker-targeted diagnostic tool for clinicians. The attraction of a nanopore-based detection system is its simple, inexpensive, robust, user-friendly, high-throughput blueprint with minimal sample preparation needed prior to analysis. The goal of clinical-based nanopore biosensing is to go from sample acquisition to a meaningful readout quickly. The most extensive work in nanopore applications has been targeted at DNA, RNA, and peptide identification. Although, biosensing of pathological biomarkers, which is covered in this review, is on the rise. This review is broken into two major sections: (i) the current state of existing biological, solid state, and hybrid nanopore systems and (ii) the applications of nanopore biosensors toward detecting neurodegenerative biomarkers.

Single molecule observation of hard-soft-acid-base (HSAB) interaction in engineered Mycobacterium smegmatis porin A (MspA) nanopores

In the formation of coordination interactions between metal ions and amino acids in natural metalloproteins, the bound metal ion is critical either for the stabilization of the protein structure or as an enzyme co-factor. Though extremely small in size, metal ions, when bound to the restricted environment of an engineered biological nanopore, result in detectable perturbations during single channel recordings. All reported work of this kind was performed with engineered α-hemolysin nanopores and the observed events appear to be extremely small in amplitude (∼1–3 pA). We speculate that the cylindrical pore restriction of α-hemolysin may not be optimal for probing extremely small analytes. Mycobacterium smegmatis porin A (MspA), a conical shaped nanopore, was engineered to interact with Ca²⁺, Mn²⁺, Co²⁺, Ni²⁺, Zn²⁺, Pb²⁺ and Cd²⁺ and a systematically larger event amplitude (up to 10 pA) was observed. The measured rate constant suggests that the coordination of a single ion with an amino acid follows hard–soft-acid–base theory, which has never been systematically validated in the case of a single molecule. By adjusting the measurement pH from 6.8 to 8.0, the duration of a single ion binding event could be modified with a ∼46-fold time extension. The phenomena reported suggest MspA to be a superior engineering template for probing a variety of extremely small analytes, such as monatomic and polyatomic ions, small molecules or chemical intermediates, and the principle of hard–soft-acid–base interaction may be instructive in the pore design.

The principle of hard–soft-acid–base (HSAB) theory was first validated in single molecule by measurements with engineered Mycobacterium smegmatis porin A (MspA) nanopore reactors.

Surface coatings for solid-state nanopores

Since their introduction in 2001, solid-state nanopores have been increasingly exploited for the detection and characterization of biomolecules ranging from single DNA strands to protein complexes. A major factor that enables the application of nanopores to the analysis and characterization of a broad range of macromolecules is the preparation of coatings on the pore wall to either prevent non-specific adhesion of molecules or to facilitate specific interactions of molecules of interest within the pore. Surface coatings can therefore be useful to minimize clogging of nanopores or to increase the residence time of target analytes in the pore. This review article describes various coatings and their utility for changing pore diameters, increasing the stability of nanopores, reducing non-specific interactions, manipulating surface charges, enabling interactions with specific target molecules, and reducing the noise of current recordings through nanopores. We compare the coating methods with respect to the ease of preparing the coating, the stability of the coating and the requirement for specialized equipment to prepare the coating.

Learning Shapelets for Improving Single-Molecule Nanopore Sensing

The nanopore technique employs a nanoscale cavity to electrochemically confine individual molecules, achieving ultrasensitive single-molecule analysis based on evaluating the amplitude and duration of the ionic current. However, each nanopore sensing interface has its own intrinsic sensing ability, which does not always efficiently generate distinctive blockade currents for multiple analytes. Therefore, analytes that differ at only a single site often exhibit similar blockade currents or durations in nanopore experiments, which often produces serious overlap in the resulting statistical graphs. To improve the sensing ability of nanopores, herein we propose a novel shapelet-based machine learning approach to discriminate mixed analytes that exhibit nearly identical blockade current amplitudes and durations. DNA oligomers with a single-nucleotide difference, 5'-AAAA-3' and 5'-GAAA-3', are employed as model analytes that are difficult to identify in aerolysin nanopores at 100 mV. First, a set of the most informative and discriminative segments are learned from the time-series data set of blockade current signals using the learning time-series shapelets (LTS) algorithm. Then, the shapelet-transformed representation of the signals is obtained by calculating the minimum distance between the shapelets and the original signals. A simple logistic classifier is used to identify the two types of DNA oligomers in accordance with the corresponding shapelet-transformed representation. Finally, an evaluation is performed on the validation data set to show that our approach can achieve a high F₁ score of 0.933. In comparison with the conventional statistical methods for the analysis of duration and residual current, the shapelet-transformed representation provides clearly discriminated distributions for multiple analytes. Taking advantage of the robust LTS algorithm, one could anticipate the real-time analysis of nanopore events for the direct identification and quantification of multiple biomolecules in a complex real sample (e.g., serum) without labels and time-consuming mutagenesis.

Enhanced Bipolar Electrochemistry at Solid-State Micropores: Demonstration by Wireless Electrochemiluminescence Imaging

Bipolar electrochemistry (BPE) is a powerful method based on the wireless polarization of a conductive object that induces the asymmetric electroactivity at its two extremities. A key physical limitation of BPE is the size of the conductive object because the shorter the object, the larger is the potential necessary for sufficient polarization. Micrometric and nanometric objects are thus extremely difficult to address by BPE due to the very high potentials required, in the order of tens of kV or more. Herein, the synergetic actions of BPE and of planar micropores integrated in a microfluidic device lead to the spatial confinement of the potential drop at the level of the solid-state micropore, and thus to a locally enhanced polarization of a bipolar electrode. Electrochemiluminescence (ECL) is emitted in half of the electroactive micropore and reveals the asymmetric polarization in this spatial restriction. Micrometric deoxidized silicon electrodes located in the micropore are polarized at a very low potential (7 V), which is more than 2 orders of magnitude lower compared to the classic bipolar configurations. This behavior is intrinsically associated with the unique properties of the micropores, where the sharp potential drop is focused. The presented approach offers exciting perspectives for BPE of micro/nano-objects, such as dynamic BPE with objects passing through the pores or wireless ECL-emitting micropores.

A simple fluorescent aptamer based assay coupled with fluorescence scanning capillary array for aflatoxin B1

We developed a simple aptamer fluorescence assay for aflatoxin B1 (AFB1) detection by using an array of capillaries. The 34-nt aptamer having a single fluorescein (FAM) label on the 24th T nucleotide generated a remarkable fluorescence increase upon AFB1 binding. The use of fluorescence scanning capillary array allowed for the analysis of multiple samples with low sample consumption, showing advantages of simplicity, rapidity and high throughput analysis. The detection limit of AFB1 reached 0.5 nM. This assay has great potential for analysis in food safety and environmental monitoring.

Rapid and Accurate Determination of Nanopore Ionic Current Using a Steric Exclusion Model

Nanopore sensing has emerged as a versatile approach to detection and identification of biomolecules. Presently, researchers rely on experience and intuition for choosing or modifying the nanopores to detect a target analyte. The field would greatly benefit from a computational method that could relate the atomic-scale geometry of the nanopores and analytes to the blockade nanopore currents they produce. Existing computational methods are either computationally too expensive to be used routinely in experimental laboratories or not sensitive enough to account for the atomic structure of the pore and the analytes. Here, we demonstrate a robust and inexpensive computational approach-the steric exclusion model (SEM) of nanopore conductance-that is orders of magnitude more efficient than all-atom MD and yet is sensitive enough to account for the atomic structure of the nanopore and the analyte. The method combines the computational efficiency of a finite element solver with the atomic precision of a nanopore conductance map to yield unprecedented speed and accuracy of ionic current prediction. We validate our SEM approach through comparison with the current blockades computed using the all-atom molecular dynamics method for a range of proteins confined to a solid-state nanopore, biological channels embedded in a lipid bilayer membranes, and blockade currents produced by DNA homopolymers in MspA. We illustrate potential applications of SEM by computing blockade currents produced by nucleosome proteins in a solid-state nanopore, individual amino acids in MspA, and by testing the effect of point mutations on amino acid distinguishability. We expect our SEM approach to become an integral part of future development of the nanopore sensing field.

Biomimetic Membranes with Transmembrane Proteins: State-of-the-Art in Transmembrane Protein Applications

In biological cells, membrane proteins are the most crucial component for the maintenance of cell physiology and processes, including ion transportation, cell signaling, cell adhesion, and recognition of signal molecules. Therefore, researchers have proposed a number of membrane platforms to mimic the biological cell environment for transmembrane protein incorporation. The performance and selectivity of these transmembrane proteins based biomimetic platforms are far superior to those of traditional material platforms, but their lack of stability and scalability rule out their commercial presence. This review highlights the development of transmembrane protein-based biomimetic platforms for four major applications, which are biosensors, molecular interaction studies, energy harvesting, and water purification. We summarize the fundamental principles and recent progress in transmembrane protein biomimetic platforms for each application, discuss their limitations, and present future outlooks for industrial implementation.

The Utility of Nanopore Technology for Protein and Peptide Sensing

Resistive pulse nanopore sensing enables label-free single-molecule analysis of a wide range of analytes. An increasing number of studies have demonstrated the feasibility and usefulness of nanopore sensing for protein and peptide characterization. Nanopores offer the potential to study a variety of protein-related phenomena that includes unfolding kinetics, differences in unfolding pathways, protein structure stability, and free-energy profiles of DNA-protein and RNA-protein binding. In addition to providing a tool for fundamental protein characterization, nanopores have also been used as highly selective protein detectors in various solution mixtures and conditions. This review highlights these and other developments in the area of nanopore-based protein and peptide detection.

Nanopore Decoding of Oligonucleotides in DNA Computing

In conventional DNA-computation methods involving logic gate operations, the output molecules are detected and decoded mainly by gel electrophoresis or fluorescence measurements. To employ rapid and label-free decoding, nanopore technology, an emerging methodology for single-molecule detection or DNA sequencing, is proposed as a candidate for electrical and simple decoding of DNA computations. This review describes recent approaches to decoding DNA computation using label-free and electrical nanopore measurements. Several attempts have been successful in DNA decoding with the nanopore either through enzymatic reactions or in water-in-oil droplets. Additionally, DNA computing combined with nanopore decoding has clinical applications, including microRNA detection for early diagnosis of cancers. Because this decoding methodology is still in development and not yet widely accepted, this review aims to inform the scientific community regarding usefulness.

Computation-Assisted Nanopore Detection of Thorium Ions

Thorium is a well-known radioactive and chemically toxic contaminant in the environment. The continuous exposure to thorium may cause an increased risk of developing lung and liver diseases as well as lung, pancreas, and bone cancer. Due to its use in nuclear industry and other industrial applications, thorium may be accidentally released to the environment from its mining and processing plants. In this work, we developed a rapid, real-time, and label-free nanopore sensor for Th⁴⁺ detection by using an aspartic acid containing peptide as a chelating agent and tuning the electrolyte solution pH to control the net charges of the peptide ligand and its metal ion complex. The method is highly sensitive with a detection limit of 0.45 nM. Furthermore, the sensor is selective: other metal ions (e.g., UO₂²⁺, Pb²⁺, Cu²⁺, Ni²⁺, Hg²⁺, Zn²⁺, As³⁺, Mg²⁺, and Ca²⁺) with concentrations of up to 3 orders of magnitude greater than that of Th⁴⁺ would not interfere with Th⁴⁺detection. In addition, simulated water samples were successfully analyzed. Our developed computation-assisted sensing strategy should find useful applications in the development of nanopore sensors for other metal ions.

Fabrication of multiple nanopores in a SiNx membrane via controlled breakdown

This paper reports a controlled breakdown (CBD) method to fabricate multiple nanopores in a silicon nitride (SiN_x) membrane with control over both nanopore count and nanopore diameter. Despite the stochastic process of the breakdown, we found that the nanopores created via CBD, tend to be of the same diameter. We propose a membrane resistance model to explain and control the multiple nanopores forming in the membrane. We prove that the membrane resistance can reflect the number of nanopores in the membrane and that the diameter of the nanopores is controlled by the exposure time and strength of the electric field. This controllable multiple nanopore formation via CBD avoids the utilization of complicated instruments and time-intensive manufacturing. We anticipate CBD has the potential to become a nanopore fabrication technique which, integrated into an optical setup, could be used as a high-throughput and multichannel characterization technique.

Biomimetic ion channels formation by emulsion based on chemically modified cyclodextrin nanotubes

We present short cyclodextrin nanotubes that form ion channels in lipid bilayers.

A thumb-size electrochemical system for portable sensors

A thumb-size and precise electrochemical system is designed for sensors in size and cost sensitive applications.

Simulation of a model nanopore sensor: Ion competition underlies device behavior

We study a model nanopore sensor with which a very low concentration of analyte molecules can be detected on the basis of the selective binding of the analyte molecules to the binding sites on the pore wall. The bound analyte ions partially replace the current-carrier cations in a thermodynamic competition. This competition depends both on the properties of the nanopore and the concentrations of the competing ions (through their chemical potentials). The output signal given by the device is the current reduction caused by the presence of the analyte ions. The concentration of the analyte ions can be determined through calibration curves. We model the binding site with the square-well potential and the electrolyte as charged hard spheres in an implicit background solvent. We study the system with a hybrid method in which we compute the ion flux with the Nernst-Planck (NP) equation coupled with the Local Equilibrium Monte Carlo (LEMC) simulation technique. The resulting NP+LEMC method is able to handle both strong ionic correlations inside the pore (including finite size of ions) and bulk concentrations as low as micromolar. We analyze the effect of bulk ion concentrations, pore parameters, binding site parameters, electrolyte properties, and voltage on the behavior of the device.