MOSAIC: A Modular Single-Molecule Analysis Interface for Decoding Multistate Nanopore Data

A Robust Parallel Computing Data Extraction Framework for Nanopore Experiments

The success of a nanopore experiment relies not only on the quality of the experimental design but also on the performance of the analysis program utilized to decipher the ionic perturbations necessary for understanding the fundamental molecular intricacies. An event extraction framework is developed that leverages parallel computing, efficient memory management, and vectorization, yielding significant performance enhancement. The newly developed abf-ultra-simple function extracts key parameters from the header critical for the operation of open-seek-read-close data loading architecture running on multiple cores. This underpins the swift analysis of large files where an ≈ × 18 improvement is found for a 100 min-long file (≈4.5 GB) compared to the more traditional single (cell) array data loading method. The application is benchmarked against five other analysis platforms showcasing significant performance enhancement (>2 ×-1120 ×). The integrated provisions for batch analysis enable concurrently analyzing multiple files (vital for high-bandwidth experiments). Furthermore, the application is equipped with multi-level data fitting based on abrupt changes in the event waveform. The application condenses the extracted events to a single binary file improving data portability (e.g., 16 GB file with 28 182 events reduces to 47.9 MB-343 × size reduction) and enables a multitude of post-analysis extractions to be done efficiently.

Time-domain event detection using single-instruction, multiple-thread gpGPU architectures in single-molecule biophysical data

Discrete amplitude levels in ordered, time-domain data often represent different underlying latent states of the system that is being interrogated. Analysis and feature extraction from these data sets generally require considering the order of each individual point; this approach cannot take advantage of contemporary general-purpose graphics processing units (gpGPU) and single-instruction multiple-data (SIMD) instruction set architectures. Two sources of such data from single-molecule biological measurements are nanopores and single-molecule field effect transistor (smFET) nanotube devices; both generate streams of time-ordered current or voltage data, typically sampled near 1 MS/s, with run times of minutes, yielding terabyte-scale datasets. Here, we present three gpGPU-based algorithms to overcome limitations associated with serial event detection in time series data, resulting in a 250× improvement in the rate with which we can detect salient features in nanopore and smFET datasets. The code is freely available.

Precise Structural Analysis of Neutral Glycans Using Aerolysin Mutant T240R Nanopore

Glycans play vital roles in nearly all life processes of multicellular organisms, and understanding these activities is inseparable from elucidating the biological significance of glycans. However, glycan research has lagged behind that of DNA and protein due to the challenges posed by structural heterogeneity and isomerism (i.e., structures with equal molecular weights) the lack of high-efficiency structural analysis techniques. Nanopore technology has emerged as a sensitive single-molecule biosensor, shining a light on glycan analysis. However, a significant number of glycans are small and uncharged, making it challenging to elicit identifiable nanopore signals. Here we introduce a R-binaphthyl tag into glycans, which enhances the cation-π interaction between the derivatized glycan molecules and the nanopore interface, enabling the detection of neutral glycans with an aerolysin nanopore. This approach allows for the distinction of di-, tri-, and tetrasaccharides with monosaccharide resolution and has the potential for group discrimination, the monitoring of enzymatic transglycosylation reactions. Notably, the aerolysin mutant T240R achieves unambiguous identification of six disaccharide isomers, trisaccharide and tetrasaccharide linkage isomers. Molecular docking simulations reveal that multiple noncovalent interactions occur between residues R282, K238, and R240 and the glycans and R-binaphthyl tag, significantly slowing down their translocation across the nanopore. Importantly, we provide a demonstration of the kinetic translocation process of neutral glycan isomers, establishing a solid theoretical foundation for glycan nanopore analysis. The development of our technology could promote the analysis of glycan structural isomers and has the potential for nanopore-based glycan structural determination and sequencing.

Emerging Data Processing Methods for Single-Entity Electrochemistry

Single-entity electrochemistry is a powerful tool that enables the study of electrochemical processes at interfaces and provides insights into the intrinsic chemical and structural heterogeneities of individual entities. Signal processing is a critical aspect of single-entity electrochemical measurements and can be used for data recognition, classification, and interpretation. In this review, we summarize the recent five-year advances in signal processing techniques for single-entity electrochemistry and highlight their importance in obtaining high-quality data and extracting effective features from electrochemical signals, which are generally applicable in single-entity electrochemistry. Moreover, we shed light on electrochemical noise analysis to obtain single-molecule frequency fingerprint spectra that can provide rich information about the ion networks at the interface. By incorporating advanced data analysis tools and artificial intelligence algorithms, single-entity electrochemical measurements would revolutionize the field of single-entity analysis, leading to new fundamental discoveries.

Identification of Conformational Variants for Bradykinin Biomarker Peptides from a Biofluid Using a Nanopore and Machine Learning

There is a current need to develop methods for the sensitive detection of peptide biomarkers in complex mixtures of molecules, such as biofluids, to enable early disease detection. Moreover, to our knowledge, there is currently no detection method capable of identifying the different conformations of a peptide biomarker differing by a single amino acid. Single-molecule nanopore sensing promises to provide this level of resolution. In order to be able to identify these differences in a biofluid such as serum, it is necessary to carefully characterize electrical parameters to obtain specific signatures of each biomarker population observed. We are interested here in a family of peptide biomarkers, kinins such as bradykinin and des-Arg9 bradykinin, that are involved in many disabling pathologies (allergy, asthma, angioedema, sepsis, or cancer). We show the proof of concept for direct identification of these biomarkers in serum at the single-molecule level using a protein nanopore. Each peptide exhibits two unique electrical signatures attributed to specific conformations in bulk. The same signatures are found in serum, allowing their discrimination and identification in a complex mixture such as biofluid. To extend the utility of our experimental results, we developed a principal component analysis approach to define the most relevant electrical parameters for their identification. Finally, we used semisupervised classification to assign each event type to a specific biomarker at physiological serum concentration. In the future, single-molecule scale analysis of peptide biomarkers using a powerful nanopore coupled with machine learning will facilitate the identification and quantification of other clinically relevant biomarkers from biofluids.

An aptamer-assisted nanopore strategy with a salt gradient for direct protein sensing

Nanopore sensing is at the forefront of the technological revolution of the protein research field and has been widely used in molecular diagnosis and molecular dynamics, as well as for various sequencing applications. However, direct protein sensing with biological nanopores is still challenging owing to the large molecular size. Here, we propose an aptamer-assisted nanopore strategy for direct protein sensing and demonstrate its proof-of-concept utilities by experiments with SARS-Cov-2 nucleocapsid protein (NP), the most abundantly expressed viral protein, that is widely used in clinical diagnosis for COVID-19. NP binds with an oligonucleotide-tailed aptamer to form a protein-DNA complex which induces a discriminative two-level pattern of current blockades. We reveal the potential molecular interaction mechanism for the characteristic blockades and identify the salt gradient condition as the dominant factor of the phenomenon. Furthermore, we achieve a high sensitivity of 10 pM for NP detection within one hour and make a preliminary exploration on clinical diagnosis. This work promises a new platform for rapid and label-free protein detection.

Multiplexed detection of viral antigen and RNA using nanopore sensing and encoded molecular probes

We report on single-molecule nanopore sensing combined with position-encoded DNA molecular probes, with chemistry tuned to simultaneously identify various antigen proteins and multiple RNA gene fragments of SARS-CoV-2 with high sensitivity and selectivity. We show that this sensing strategy can directly detect spike (S) and nucleocapsid (N) proteins in unprocessed human saliva. Moreover, our approach enables the identification of RNA fragments from patient samples using nasal/throat swabs, enabling the identification of critical mutations such as D614G, G446S, or Y144del among viral variants. In particular, it can detect and discriminate between SARS-CoV-2 lineages of wild-type B.1.1.7 (Alpha), B.1.617.2 (Delta), and B.1.1.539 (Omicron) within a single measurement without the need for nucleic acid sequencing. The sensing strategy of the molecular probes is easily adaptable to other viral targets and diseases and can be expanded depending on the application required.

Synthesis of length-tunable DNA carriers for nanopore sensing

Molecular carriers represent an increasingly common strategy in the field of nanopore sensing to use secondary molecules to selectively report on the presence of target analytes in solution, allowing for sensitive assays of otherwise hard-to-detect molecules such as small, weakly-charged proteins. However, existing carrier designs can often introduce drawbacks to nanopore experiments including higher levels of cost/complexity and carrier-pore interactions that lead to ambiguous signals and elevated clogging rates. In this work, we present a simple method of carrier production based on sticky-ended DNA molecules that emphasizes ease-of-synthesis and compatibility with nanopore sensing and analysis. In particular, our method incorporates the ability to flexibly control the length of the DNA carriers produced, enhancing the multiplexing potential of this carrier system through the separable nanopore signals they could generate for distinct targets. A proof-of-concept nanopore experiment is also presented, involving carriers produced by our method with multiple lengths and attached to DNA nanostructure targets, in order to validate the capabilities of the system. As the breadth of applications for nanopore sensors continues to expand, the availability of tools such as those presented here to help translate the outcomes of these applications into robust nanopore signals will be of major importance.

Analysis of Nanopore Data: Classification Strategies for an Unbiased Curation of Single-Molecule Events from DNA Nanostructures

Nanopores are versatile single-molecule sensors that are being used to sense increasingly complex mixtures of structured molecules with applications in molecular data storage and disease biomarker detection. However, increased molecular complexity presents additional challenges to the analysis of nanopore data, including more translocation events being rejected for not matching an expected signal structure and a greater risk of selection bias entering this event curation process. To highlight these challenges, here, we present the analysis of a model molecular system consisting of a nanostructured DNA molecule attached to a linear DNA carrier. We make use of recent advances in the event segmentation capabilities of Nanolyzer, a graphical analysis tool provided for nanopore event fitting, and describe approaches to the event substructure analysis. In the process, we identify and discuss important sources of selection bias that emerge in the analysis of this molecular system and consider the complicating effects of molecular conformation and variable experimental conditions (e.g., pore diameter). We then present additional refinements to existing analysis techniques, allowing for improved separation of multiplexed samples, fewer translocation events rejected as false negatives, and a wider range of experimental conditions for which accurate molecular information can be extracted. Increasing the coverage of analyzed events within nanopore data is not only important for characterizing complex molecular samples with high fidelity but is also becoming essential to the generation of accurate, unbiased training data as machine-learning approaches to data analysis and event identification continue to increase in prevalence.

Discriminating Single Nucleotide Variations in Solid-State Nanopores by Evaluating the Combination Efficiency between DNA Polymerase and Its Substrate

A single nucleotide variant present between two otherwise identical nucleic acids will have unexpected functional consequences frequently. Here, a neoteric single nucleotide variation (SNV) detection assay that integrates two complementary nanotechnology systems, nanoassembly technology and an ingenious nanopore biosensing platform, has been applied to this research. Specifically, we set up a detection system to reflect the binding efficiency of the polymerase and nanoprobe through the difference of nanopore signals and then explore the effect of base mutation at the binding site. In addition, machine learning based on support vector machines is used to automatically classify characteristic events mapped by nanopore signals. Our system reliably discriminates single nucleotide variants at binding sites, even possessing the recognition among transitions, transversions, and hypoxanthine (base I). Our results demonstrate the potential of solid-state nanopore detection for SNV and provide some ideas for expanding solid-state nanopore detection platforms.

Identification of tagged glycans with a protein nanopore

Structural complexity of glycans derived from the diversities in composition, linage, configuration, and branching considerably complicates structural analysis. Nanopore-based single-molecule sensing offers the potential to elucidate glycan structure and even sequence glycan. However, the small molecular size and low charge density of glycans have restricted direct nanopore detection of glycan. Here we show that glycan sensing can be achieved using a wild-type aerolysin nanopore by introducing a facile glycan derivatization strategy. The glycan molecule can induce impressive current blockages when moving through the nanopore after being connected with an aromatic group-containing tag (plus a carrier group for the neutral glycan). The obtained nanopore data permit the identification of glycan regio- and stereoisomers, glycans with variable monosaccharide numbers, and distinct branched glycans, either independently or with the use of machine learning methods. The presented nanopore sensing strategy for glycans paves the way towards nanopore glycan profiling and potentially sequencing.

Ultrathin, High-Lifetime Silicon Nitride Membranes for Nanopore Sensing

Thin membranes are highly sought-after for nanopore-based single-molecule sensing, and fabrication of such membranes becomes challenging in the ≲10 nm thickness regime where a plethora of useful molecule information can be acquired by nanopore sensing. In this work, we present a scalable and controllable method to fabricate silicon nitride (Si_xN_y) membranes with effective thickness down to ∼1.5 nm using standard silicon processing and chemical etching using hydrofluoric acid (HF). Nanopores were fabricated using the controlled breakdown method with estimated pore diameters down to ∼1.8 nm yielding events >500,000 and >1,800,000 from dsDNA and bovine serum albumin (BSA) protein, respectively, demonstrating the high-performance and extended lifetime of the pores fabricated through our membranes. We used two different compositions of Si_xN_y for membrane fabrication (near-stoichiometric and silicon-rich Si_xN_y) and compared them against commercial membranes. The final thicknesses of the membranes were measured using ellipsometry and were in good agreement with the values calculated from the bulk etch rates and DNA translocation characteristics. The stoichiometry and the density of the membrane layers were characterized with Rutherford backscattering spectrometry while the nanopores were characterized using pH-conductance, conductivity-conductance, and power spectral density (PSD) graphs.

Nanopore Discrimination of Coagulation Biomarker Derivatives and Characterization of a Post-Translational Modification

One of the most important health challenges is the early and ongoing detection of disease for prevention, as well as personalized treatment management. Development of new sensitive analytical point-of-care tests are, therefore, necessary for direct biomarker detection from biofluids as critical tools to address the healthcare needs of an aging global population. Coagulation disorders associated with stroke, heart attack, or cancer are defined by an increased level of the fibrinopeptide A (FPA) biomarker, among others. This biomarker exists in more than one form: it can be post-translationally modified with a phosphate and also cleaved to form shorter peptides. Current assays are long and have difficulties in discriminating between these derivatives; hence, this is an underutilized biomarker for routine clinical practice. We use nanopore sensing to identify FPA, the phosphorylated FPA, and two derivatives. Each of these peptides is characterized by unique electrical signals for both dwell time and blockade level. We also show that the phosphorylated form of FPA can adopt two different conformations, each of which have different values for each electrical parameter. We were able to use these parameters to discriminate these peptides from a mix, thereby opening the way for the potential development of new point-of-care tests.

Procedural Data Processing for Single-Molecule Identification by Nanopore Sensors

Nanopores are promising single-molecule sensing devices that have been successfully used for DNA sequencing, protein identification, as well as virus/particles detection. It is important to understand and characterize the current pulses collected by nanopore sensors, which imply the associated information of the analytes, including the size, structure, and surface charge. Therefore, a signal processing program, based on the MATLAB platform, was designed to characterize the ionic current signals of nanopore measurements. In a movable data window, the selected current segment was analyzed by the adaptive thresholds and corrected by multi-functions to reduce the noise obstruction of pulse signals. Accordingly, a set of single molecular events was identified, and the abundant information of current signals with the dwell time, amplitude, and current pulse area was exported for quantitative analysis. The program contributes to the efficient and fast processing of nanopore signals with a high signal-to-noise ratio, which promotes the development of the nanopore sensing devices in various fields of diagnosis systems and precision medicine.

AutoNanopore: An Automated Adaptive and Robust Method to Locate Translocation Events in Solid-State Nanopore Current Traces

Solid-state nanopore sequencing has shown impressive performances in several research scenarios but is still challenging, mainly due to the ultrafast speed of DNA translocation and significant noises embedded in raw signals. Hence, event detection, aiming to locate precisely these translocation events, is the fundamental step of data analysis. However, existing event detection methods use either a user-defined global threshold or an adaptive threshold determined by the data, assuming the baseline current to be stable over time. These disadvantages limit their applications in real-world application scenarios, especially considering that the results of different methods are often inconsistent. In this study, we develop an automated adaptive method called AutoNanopore, for fast and accurate event detection in current traces. The method consists of three consecutive steps: current trace segmentation, current amplitude outlier identification by straightforward statistical analyses, and event characterization. Then we propose ideas/metrics on how to quantitatively evaluate the performance of an event detection method, followed by comparing the performance of AutoNanopore against two state-of-the-art methods, OpenNanopore and EventPro. Finally, we examine if one method can detect the overlapping events detected by the other two, demonstrating that AutoNanopore has the highest coverage ratio. Moreover, AutoNanopore also performs well in detecting challenging events: e.g., those with significantly varying baselines.

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.

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.

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.

An advanced optical-electrochemical nanopore measurement system for single-molecule analysis

Nanopore measurement has advanced in single-molecule analysis by providing a transient time and confined space window that only allows one interested molecule to exist. By optimization and integration of the electrical and optical analysis strategies in this transient window, the acquisition of comprehensive information could be achieved to resolve the intrinsic properties and heterogeneity of a single molecule. In this work, we present a roadmap to build a unified optical and electrochemical synchronous measurement platform for the research of a single molecule. We design a low-cost ultralow-current amplifier with low noise and high-bandwidth to measure the ionic current events as a single molecule translocates through a nanopore and combine a multi-functional optical system to implement the acquisition of the fluorescence, scattering spectrum, and photocurrent intensity of single molecule events in a nanopore confined space. Our system is a unified and unique platform for the protein nanopore, the solid-state nanopore, and the glass capillary nanopore, which has advantages in the comprehensive research of nanopore single-molecule techniques.

Mapping shifts in nanopore signal to changes in protein and protein-DNA conformation

Solid-state nanopores have been used extensively in biomolecular studies involving DNA and proteins. However, the interpretation of signals generated by the translocation of proteins or protein-DNA complexes remains challenging. Here, we investigate the behavior of monovalent streptavidin and the complex it forms with short biotinylated DNA over a range of nanopore sizes, salts, and voltages. We describe a simple geometric model that is broadly applicable and employ it to explain observed variations in conductance blockage and dwell time with experimental conditions. The general approach developed here underscores the value of nanopore-based protein analysis and represents progress toward the interpretation of complex translocation signals.

A Guide to Signal Processing Algorithms for Nanopore Sensors

Nanopore technology holds great promise for a wide range of applications such as biomedical sensing, chemical detection, desalination, and energy conversion. For sensing performed in electrolytes in particular, abundant information about the translocating analytes is hidden in the fluctuating monitoring ionic current contributed from interactions between the analytes and the nanopore. Such ionic currents are inevitably affected by noise; hence, signal processing is an inseparable component of sensing in order to identify the hidden features in the signals and to analyze them. This Guide starts from untangling the signal processing flow and categorizing the various algorithms developed to extracting the useful information. By sorting the algorithms under Machine Learning (ML)-based versus non-ML-based, their underlying architectures and properties are systematically evaluated. For each category, the development tactics and features of the algorithms with implementation examples are discussed by referring to their common signal processing flow graphically summarized in a chart and by highlighting their key issues tabulated for clear comparison. How to get started with building up an ML-based algorithm is subsequently presented. The specific properties of the ML-based algorithms are then discussed in terms of learning strategy, performance evaluation, experimental repeatability and reliability, data preparation, and data utilization strategy. This Guide is concluded by outlining strategies and considerations for prospect algorithms.

Protein identification by nanopore peptide profiling

Nanopores are single-molecule sensors used in nucleic acid analysis, whereas their applicability towards full protein identification has yet to be demonstrated. Here, we show that an engineered Fragaceatoxin C nanopore is capable of identifying individual proteins by measuring peptide spectra that are produced from hydrolyzed proteins. Using model proteins, we show that the spectra resulting from nanopore experiments and mass spectrometry share similar profiles, hence allowing protein fingerprinting. The intensity of individual peaks provides information on the concentration of individual peptides, indicating that this approach is quantitative. Our work shows the potential of a low-cost, portable nanopore-based analyzer for protein identification.

Peptide mass fingerprinting is a traditional approach for protein identification by mass spectrometry. Here, the authors provide evidence that peptide mass fingerprinting is also feasible using FraC nanopores, demonstrating protein identification based on nanopore measurements of digested peptides.

Digital immunoassay for biomarker concentration quantification using solid-state nanopores

Single-molecule counting is the most accurate and precise method for determining the concentration of a biomarker in solution and is leading to the emergence of digital diagnostic platforms enabling precision medicine. In principle, solid-state nanopores—fully electronic sensors with single-molecule sensitivity—are well suited to the task. Here we present a digital immunoassay scheme capable of reliably quantifying the concentration of a target protein in complex biofluids that overcomes specificity, sensitivity, and consistency challenges associated with the use of solid-state nanopores for protein sensing. This is achieved by employing easily-identifiable DNA nanostructures as proxies for the presence (“1”) or absence (“0”) of the target protein captured via a magnetic bead-based sandwich immunoassay. As a proof-of-concept, we demonstrate quantification of the concentration of thyroid-stimulating hormone from human serum samples down to the high femtomolar range. Further optimization to the method will push sensitivity and dynamic range, allowing for development of precision diagnostic tools compatible with point-of-care format.

The concentration of a biomarker in solution can be determined by counting single molecules. Here the authors report a digital immunoassay scheme with solid-state nanopore readout to quantify a target protein and use this to measure thyroid-stimulating hormone from human serum.

Real-Time and Label-Free Measurement of Deubiquitinase Activity with a MspA Nanopore

Covalently attaching ubiquitin (Ub) to cellular proteins as a post-translational modification can result in altered function of modified proteins. Enzymes regulating Ub as a post-translational modification, such as ligases and deubiquitinases, are challenging to characterize in part due to the low throughput of in-vitro assays. Single-molecule nanopore based assays have the advantage of detecting proteins with high specificity and resolution, and in a label-free, real-time fashion. Here we demonstrate the use of a MspA nanopore for discriminating and quantifying Ub proteins. We further applied the MspA pore to measure the Ub-chain disassembly activity of UCH37, a proteasome associated deubiquitinase. The implementation of this MspA system into nanopore arrays could enable high throughput characterizations of unknown deubiquitinases as well as drug screening against disease related enzymes.

Nanopore sensing: A physical-chemical approach

Protein nanopores have emerged as an important class of sensors for the understanding of biophysical processes, such as molecular transport across membranes, and for the detection and characterization of biopolymers. Here, we trace the development of these sensors from the Coulter counter and squid axon studies to the modern applications including exquisite detection of small volume changes and molecular reactions at the single molecule (or reactant) scale. This review focuses on the chemistry of biological pores, and how that influences the physical chemistry of molecular detection.

Nanopore Data Analysis: Baseline Construction and Abrupt Change-Based Multilevel Fitting

Solid-state nanopore technology delivers single-molecule resolution information, and the quality of the deliverables hinges on the capability of the analysis platform to extract maximum possible events and fit them appropriately. In this work, we present an analysis platform with four baseline fitting methods adaptive to a wide range of nanopore traces (including those with a step or abrupt changes where pre-existing platforms fail) to maximize extractable events (2× improvement in some cases) and multilevel event fitting capability. The baseline fitting methods, in the increasing order of robustness and computational cost, include arithmetic mean, linear fit, Gaussian smoothing, and Gaussian smoothing and regressed mixing. The performance was tested with ultra-stable to vigorously fluctuating current profiles, and the event count increased with increasing fitting robustness prominently for vigorously fluctuating profiles. Turning points of events were clustered using the dbscan method, followed by segmentation into preliminary levels based on abrupt changes in the signal level, which were then iteratively refined to deduce the final levels of the event. Finally, we show the utility of clustering for multilevel DNA data analysis, followed by the assessment of protein translocation profiles.

EasyNanopore: A Ready-to-Use Processing Software for Translocation Events in Nanopore Translocation Experiments

We developed EasyNanopore which is a ready-to-use software to select the events of a nanopore molecular translocation experiment. The software is released as an executable file with a graphical user interface and provides several versions suitable for different operating systems without installing any running environment to execute it. We use the adaptive threshold which adapts to the low-frequency variation of the baseline to detect events and uses a multiprocess method to accelerate the process of event detection. After the event is identified, its duration and amplitude information will be extracted and a resulting txt file will be generated for further analysis. Our software runs fast and can effectively extract the data from data of large-scale nanopore molecular translocation experiments.

Revisiting the Origin of Nanopore Current Blockage for Volume Difference Sensing at the Atomic Level

Changes in the nanopore ionic current during entry of a target molecule underlie the sensing capability and dominate the intensity and extent of applications of the nanopore approach. The volume exclusion model has been proposed and corrected to describe the nanopore current blockage. However, increasing evidence shows nonconformity with this model, suggesting that the ionic current within a nanopore should be entirely reconsidered. Here, we revisit the origin of nanopore current blockage from a theoretical perspective and propose that the noncovalent interactions between a nanopore and a target molecule affect the conductance of the solution inside the nanopore, leading to enhanced current blockage. Moreover, by considering the example of an aerolysin nanopore discriminating the cytosine DNA and methylcytosine DNA that differ by a single methyl group, we completely demonstrate, by nanopore experiments and molecular dynamics simulations, the essential nature of this noncovalent interaction for discrimination. Our conductance model suggests multiplicative effects of both volume exclusion and noncovalent interaction on the current blockage and provides a new strategy to achieve volume difference sensing at the atomic level with highly specific current events, which would promote the nanopore protein sequencing and its applications in real-life systems.

Rapid and Accurate Data Processing for Silver Nanoparticle Oxidation in Nano-Impact Electrochemistry

In recent years, nano-impact electrochemistry (NIE) has attracted widespread attention as a new electroanalytical approach for the analysis and characterization of single nanoparticles in solution. The accurate analysis of the large volume of the experimental data is of great significance in improving the reliability of this method. Unfortunately, the commonly used data analysis approaches, mainly based on manual processing, are often time-consuming and subjective. Herein, we propose a spike detection algorithm for automatically processing the data from the direct oxidation of sliver nanoparticles (AgNPs) in NIE experiments, including baseline extraction, spike identification and spike area integration. The resulting size distribution of AgNPs is found to agree very well with that from transmission electron microscopy (TEM), showing that the current algorithm is promising for automated analysis of NIE data with high efficiency and accuracy.

Instrumentational implementation for parallelized nanopore electrochemical measurements

Nanopore electrochemistry, as one of the promising tools for single molecule sensing, has proved its capability in DNA sequencing and protein analysis. To achieve a high resolution for obtaining molecular information, the nanopore electrochemical technique not only urgently requires an appropriate nanopore sensing interface with atomic resolution but also requires advanced instrumentation and its related data processing methods. In order to reveal the fundamental biological process and process the point-of-care diagnosis, it is necessary to use a nanopore sensing instrument with a high amperometric and temporal resolution as well as high throughput. The development of the instrumentation requires multi-disciplinary collaboration involving preparing a sensitive nanopore interface, low-noise circuit design, and intelligent data analysis. In this review, we have summarized the recent improvements in the nanopore sensing interface as well as discussed the higher throughput achieved by nanopore arrays and intelligent nanopore data analysis methods. The parallelized nanopore instrumentation could be popularized to all ranges of single-molecule applications.

Length-Dependent, Single-Molecule Analysis of Short Double-Stranded DNA Fragments through Hydrogel-Filled Nanopores: A Potential Tool for Size Profiling Cell-Free DNA

Fast sampling followed by sequence-independent sensing and length-dependent detection of short double-stranded DNA fragments, the size of those found in blood and other bodily fluids, is achieved using engineered molecular sensors, dubbed hydrogel-filled nanopores (HFNs). Fragments as short as 100 base pairs were blindly sampled and concentrated at the tip of an HFN before reversing the applied potential to detect and distinguish individual molecules based on fragment length as they translocate out of the nanopore. A remarkable 16-fold increase in the signal-to-noise ratio was observed in the eject configuration compared to the load configuration, enabling the resolution of fragments with a size difference of 50 nucleotides in length. This fast and versatile technology offers great tunability for both sampling and detection. While increasing sampling time leads to an increase in the local DNA concentration at the tip prior to detection, a linear correlation between the peak current and DNA fragment size enables good resolution of fragments up to 250 bp long.

Laser-based temperature control to study the roles of entropy and enthalpy in polymer-nanopore interactions

Single-molecule approaches for probing the free energy of confinement for polymers in a nanopore environment are critical for the development of nanopore biosensors. We developed a laser-based nanopore heating approach to monitor the free energy profiles of such a single-molecule sensor. Using this approach, we measure the free energy profiles of two distinct polymers, polyethylene glycol and water-soluble peptides, as they interact with the nanopore sensor. Polyethylene glycol demonstrates a retention mechanism dominated by entropy with little sign of interaction with the pore, while peptides show an enthalpic mechanism, which can be attributed to physisorption to the nanopore (e.g., hydrogen bonding). To manipulate the energetics, we introduced thiolate-capped gold clusters [Au25(SG)18] into the pore, which increases the charge and leads to additional electrostatic interactions that help dissect the contribution that enthalpy and entropy make in this modified environment. These observations provide a benchmark for optimization of single-molecule nanopore sensors.

Electrophysiology on Channel-Forming Proteins in Artificial Lipid Bilayers: Next-Generation Instrumentation for Multiple Recordings in Parallel

Artificial lipid bilayers have been used for several decades to study channel-forming pores and ion channels in membranes. Until recently, the classical two-chamber setups have been primarily used for studying the biophysical properties of pore forming proteins. Within the last 10 years, instruments for automated lipid bilayer measurements have been developed and are now commercially available. This chapter focuses on protein purification and reconstitution of channel-forming proteins into lipid bilayers using a classic setup and on the commercially available systems, the Orbit mini and Orbit 16.

Mechanisms of solid-state nanopore enlargement under electrical stress

We present a thorough exploration of nanopore growth under electrical stress in electrolyte solution, and demonstrate that despite their superficial similarities, nanopore formation by controlled breakdown (CBD) and nanopore growth under moderate voltage stress are fundamentally different processes. In particular, we demonstrate that unlike the CBD process, nanopore growth is primarily driven by the level of ionic current passing through the nanopore, rather than the strength of the electric field generating the current, and that enlargement has a much weaker pH dependence than does CBD pore formation. In combination with other works in the field, our results suggest that despite clear current-dependence, Joule heating is unlikely to be the main driver of pore growth during electrical stress, pointing instead toward electrochemical dissolution of membrane material along the pore walls. While the chemistry underlying the growth process remains unclear, the dependence of growth rate on current allows decoupling of the pore enlargement mechanism from the possibility of forming additional nanopores during the growth process, providing a practical method by which to rapidly enlarge a nanopore without risking opening a second nanopore.

Programmable DNA Nanoswitch Sensing with Solid-State Nanopores

Sensing performance of solid-state nanopores is limited by the fast kinetics of small molecular targets. To address this challenge, we translate the presence of a small target to a large conformational change of a long polymer. In this work, we explore the performance of solid-state nanopores for sensing the conformational states of molecular nanoswitches assembled using the principles of DNA origami. These programmable single-molecule switches show great potential in molecular diagnostics and long-term information storage. We investigate the translocation properties of linear and looped nanoswitch topologies using nanopores fabricated in thin membranes, ultimately comparing the performance of our nanopore platform for detecting the presence of a DNA analogue to a sequence found in a Zika virus biomarker gene with that of conventional gel electrophoresis. We found that our system provides a high-throughput method for quantifying several target concentrations within an order of magnitude by sensing only several hundred molecules using electronics of moderate bandwidth that are conventionally used in nanopore sensing systems.

Fast capture and multiplexed detection of short multi-arm DNA stars in solid-state nanopores

Fast and multiplexed detection of low-abundance disease biomarkers at the point-of-need would transform medicine. Nanopores have gained attention as single-molecule counters to electrically detect a range of biological molecules in a handheld format, but challenges remain before diagnostic applications can emerge. For solid-state nanopore sensors, the specificity of the ionic current signatures and the rate of target capture required to simultaneously recognize and rapidly count a mixture of molecular targets in a complex sample are active areas of research. Herein, we study the capture and translocation characteristics of short N-arm star shaped DNA nanostructures to evaluate their potential as a family of surrogate label molecules for biomarkers of interest, designed for fast and reliable multiplexed detection based on conductance blockages. Simple hybridization of a varying number of short, easily synthesized 50 bp ssDNA strands allows the number of arms in the star shape DNA to be controlled from N = 3 to 12. By introducing more arms to the nanostructures, we show that we can controllably increase the nanopore signal-to-noise ratio for a range of pore sizes, producing conductance blockages which increase linearly with the number of arms, and we demonstrate conductance-based multiplexing through simultaneous detection of three such nanostructures. Moreover, the increased molecular signal strength facilitates detection under salt concentration asymmetries, allowing for a capture rate enhancement of two orders of magnitude without compromising the nanopore temporal and ionic signals. Together, these attributes (strong signal, multiplexing potential and increased counting rate) make the N-arm star DNA-based nanostructures promising candidates as proxy labels for the detection of multiple biomarkers of interest in future high sensitivity single-molecule solid-state nanopore-based assays.

Entropic Trapping of DNA with a Nanofiltered Nanopore

Elucidating the kinetics of DNA passage through a solid-state nanopore is a fertile field of research, and mechanisms for controlling capture, passage, and trapping of biopolymers are likely to find numerous technological applications. Here we present a nanofiltered nanopore device, which forms an entropic cage for DNA following first passage through the nanopore, trapping the translocated DNA and permitting recapture for subsequent reanalysis and investigation of kinetics of passage under confinement. We characterize the trapping properties of this nanodevice by driving individual DNA polymers into the nanoscale gap separating the nanofilter and the pore, forming an entropic cage similar to a "two pores in series" device, leaving polymers to diffuse in the cage for various time lengths, and attempting to recapture the same molecule. We show that the cage results in effectively permanent trapping when the radius of gyration of the target polymer is significantly larger than the radii of the pores in the nanofilter. We also compare translocation dynamics as a function of translocation direction in order to study the effects of confinement on DNA just prior to translocation, providing further insight into the nanopore translocation process. This nanofiltered nanopore device realizes simple fabrication of a femtoliter nanoreactor in which to study fundamental biophysics and biomolecular reactions on the single-molecule level. The device provides an electrically-permeable single-molecule trap with a higher entropic barrier to escape than previous attempts to fabricate similar structures.

Single Molecule Study of Hydrogen Bond Interactions Between Single Oligonucleotide and Aerolysin Sensing Interface

The aerolysin nanopore displays a charming sensing capability for single oligonucleotide discrimination. When reading from the electrochemical signal, stronger interaction between the aerolysin nanopore and oligonucleotide represent prolonged duration time, thereby amplifying the hidden but intrinsic signal thus improving the sensitivity. In order to further understand and optimize the performance of the aerolysin nanopore, we focus on the investigation of the hydrogen bond interaction between nanopore, and analytes. Taking advantage of site-direct mutagenesis, single residue is replaced. According to whole protein sequence screening, the region near K238 is one of the key sensing regions. Such a positively charged amino acid is then mutagenized into cysteine and tyrosine denoted as K238C, and K238Y. As (dA)₄ traverses the pores, K238C dramatically produces a six times longer duration time than the WT aerolysin nanopore at the voltage of +120 mV. However, K238Y shortens the dwell time which suggests the acceleration of the translocation causing poor sensitivity. Referring to our previous findings in K238G, and K238F, our results suggest that the hydrogen bond does not dominate the dynamic translocation process, but enhances the interaction between pores and analytes confined in such nanopore space. These insights give detailed information for the rational design of the sensing mechanism of the aerolysin nanopore, thereby providing further understanding for the weak interactions between biomolecules and the confined space for nanopore sensing.

Monolithic Fabrication of NPN/SiNx Dual Membrane Cavity for Nanopore-based DNA Sensing

Nanoscale preconfinement of DNA has been shown to reduce the variation of passage times through solid-state nanopores. Preconfinement has been previously achieved by forming a femtoliter-sized cavity capped with a highly porous layer of nanoporous silicon nitride (NPN). This cavity was formed by sealing a NPN nanofilter membrane against a substrate chip using water vapor delamination. Ultimately, this method of fabrication cannot keep a consistent spacing between the filter and solid-state nanopore due to thermal fluctuations and wrinkles in the membrane, nor can it be fabricated on thousands of individual devices reliably. To overcome these issues, we present a method to fabricate the femtoliter cavity monolithically, using a selective XeF2 etch to hollow out a polysilicon spacer sandwiched between silicon nitride layers. These monolithically fabricated cavities behave identically to their counterparts formed by vapor delamination, exhibiting similar translocation passage time variation reduction and folding suppression of DNA without requiring extensive manual assembly. The ability to form nanocavity sensors with nanometer-scale precision and to reliably manufacture them at scale using batch wafer processing techniques will find numerous applications, including motion control of polymers for single-molecule detection applications, filtering of dirty samples prior to nanopore detection, and simple fabrication of single-molecule nanobioreactors.

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.

Channel from bacterial virus T7 DNA packaging motor for the differentiation of peptides composed of a mixture of acidic and basic amino acids

Protein mutations can result in dysfunctional cell signaling pathways; therefore it is of significance to develop a robust platform for the detection of protein mutations. Here, we report that the channel of bacterial virus T7 DNA packaging motor is able to discriminate peptides containing a mixture of acidic (negatively charged) and basic (positively charged) amino acids. Peptides were differentiated based on their current signatures created by their unique charge compositions. In combination with protease digestion, peptides with the locational differences of single amino acid were also identified. The results suggest that the T7 motor channel has the potential for peptide differentiation, mutation verification, and analysis of protein sequence.

Fabrication and practical applications of molybdenum disulfide nanopores

Among the different developed solid-state nanopores, nanopores constructed in a monolayer of molybdenum disulfide (MoS₂) stand out as powerful devices for single-molecule analysis or osmotic power generation. Because the ionic current through a nanopore is inversely proportional to the thickness of the pore, ultrathin membranes have the advantage of providing relatively high ionic currents at very small pore sizes. This increases the signal generated during translocation of biomolecules and improves the nanopores' efficiency when used for desalination or reverse electrodialysis applications. The atomic thickness of MoS₂ nanopores approaches the inter-base distance of DNA, creating a potential candidate for DNA sequencing. In terms of geometry, MoS₂ nanopores have a well-defined vertical profile due to their atomic thickness, which eliminates any unwanted effects associated with uneven pore profiles observed in other materials. This protocol details all the necessary procedures for the fabrication of solid-state devices. We discuss different methods for transfer of monolayer MoS₂, different approaches for the creation of nanopores, their applicability in detecting DNA translocations and the analysis of translocation data through open-source programming packages. We present anticipated results through the application of our nanopores in DNA translocations and osmotic power generation. The procedure comprises four parts: fabrication of devices (2-3 d), transfer of MoS₂ and cleaning procedure (24 h), the creation of nanopores within MoS₂ (30 min) and performing DNA translocations (2-3 h). We anticipate that our protocol will enable large-scale manufacturing of single-molecule-analysis devices as well as next-generation DNA sequencing.

Nanopore-Based Confined Spaces for Single-Molecular Analysis

The field of nanopore sensing at the single-molecular level is in a "boom" period. Such nanopores, which are either composed of biological materials or are fabricated from solid-state substrates, offer a unique confined space that is compatible with the single-molecular scale. Under the influence of an electrical field, such single-biomolecular interfaces can read single-molecular information and, if appropriately fine-tuned, each molecule plays its individual ionic rhythm to compose a "molecular symphony". Over the past few decades, many research groups have worked on nanopore-based single-molecular sensors for a range of thrilling chemical and clinical applications. Furthermore, for the past decade, we have also focused on nanopore-based sensors. In this Minireview, we summarize the recent developments in fundamental research and applications in this area, along with data algorithms and advances in hardware, which act as infrastructure for the electrochemical analysis.

Direct Sensing of Single Native RNA with a Single-Biomolecule Interface of Aerolysin Nanopore

RNA sensing is of vital significance to advance our comprehension of gene expression and to further benefit medical diagnostics. Taking advantage of the excellent sensing capability of the aerolysin nanopore as a single-biomolecule interface, we for the first time achieved the direct characterization of single native RNA of Poly(A)₄ and Poly(U)₄. Poly(A)₄ induces ∼10% larger blockade current amplitude than Poly(U)₄. The statistical duration of Poly(A)₄ is 18.83 ± 1.08 ms, which is 100 times longer than that of Poly(U)₄. Our results demonstrated that the capture of RNA homopolymers is restricted by the biased diffusion. The translocation of RNA needs to overcome a lower free-energy barrier than that of DNA. Moreover, the strong RNA-aerolysin interaction is attributed to the hydroxyl in pentose, which prolongs the translocation time. This study opens an avenue for aerolysin nanopores to directly achieve RNA sensing, including discrimination of RNA epigenetic modification and selective detection of miRNA.