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

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.

Exploring single-molecule interactions: heparin and FGF-1 proteins through solid-state nanopores

Detection and characterization of protein-protein interactions are essential for many cellular processes, such as cell growth, tissue repair, drug delivery, and other physiological functions. In our research, we have utilized emerging solid-state nanopore sensing technology, which is highly sensitive to better understand heparin and fibroblast growth factor 1 (FGF-1) protein interactions at a single-molecule level without any modifications. Understanding the structure and behavior of heparin-FGF-1 complexes at the single-molecule level is very important. An abnormality in their formation can lead to life-threatening conditions like tumor growth, fibrosis, and neurological disorders. Using a controlled dielectric breakdown pore fabrication approach, we have characterized individual heparin and FGF-1 (one of the 22 known FGFs in humans) proteins through the fabrication of 17 ± 1 nm nanopores. Compared to heparin, the positively charged heparin-binding domains of some FGF-1 proteins translocationally react with the pore walls, giving rise to a distinguishable second peak with higher current blockade. Additionally, we have confirmed that the dynamic FGF-1 is stabilized upon binding with heparin-FGF-1 at the single-molecule level. The larger current blockades from the complexes relative to individual heparin and the FGF-1 recorded during the translocation ensure the binding of heparin-FGF-1 proteins, forming binding complexes with higher excluded volumes. Taken together, we demonstrate that solid-state nanopores can be employed to investigate the properties of individual proteins and their complex interactions, potentially paving the way for innovative medical therapies and advancements.

Lithium Chloride Effects Field-Induced Protein Unfolding and the Transport Energetics Inside a Nanopipette

The tapered geometry of nanopipettes offers a unique perspective on protein transport through nanopores since both a gradual and fast confinement are possible depending on the translocation direction. The protein capture rate, unfolding, speed of translocation, and clogging probability are studied by toggling the LiCl concentration between 2 and 4 M. Interestingly, the proteins in this study could be transported with or against electrophoresis and offer vastly different attributes of sensing. Herein, a ruleset for studying proteins is developed that prevents irreversible pore clogging and yields upward of >100,000 events/nanopore. The extended duration of experiments further revealed that the capture rate takes ∼2 h to reach a steady state, emphasizing the importance of reaching equilibrated transport for studying the energetics and kinetics of protein transport (i.e., diffusion vs barrier-limited). Even in the equilibrated transport state, improper lowpass filtering was shown to distort the classification of diffusion-limited vs barrier-limited transport. Finally, electric-field-induced protein unfolding was found to be most prominent in electroosmotic-dominant transport, whereas electrophoretic-dominant events show no evidence of unfolding. Thus, our findings showcase the optimal conditions for protein translocations and the impact on studying protein unfolding, transporting energetics, and acquiring high bandwidth data.

Nanopore Fabrication Made Easy: A Portable, Affordable Microcontroller-Assisted Approach for Tailored Pore Formation via Controlled Breakdown

With growing interest in solid-state nanopore sensing─a single-molecule technique capable of profiling a host of analyte classes─establishing facile and scalable approaches for fabricating molecular-size pores is becoming increasingly important. The introduction of nanopore fabrication by controlled breakdown (CBD) has transformed the economics and accessibility of nanopore fabrication. Here, we introduce the design of an Arduino-based, portable USB-powered CBD device, with an estimated cost of <150 USD, which is ≈10-100× cheaper than most commercial solutions, capable of fabricating single nanopores conducive for single molecule sensing experiments. We demonstrate the facile fabrication of 60 tailored nanopores (∼2.6-12.6 nm) with ∼80% of the pores within 1 nm of the target diameter. Selected pores were then tested with double-stranded DNA, the canonical molecular ruler, demonstrating their performance for single-molecule sensing applications. The device is constructed with off-the-shelf readily available components and controlled using a highly customizable MATLAB application, which has capabilities encompassing pore fabrication, pore enlargement, and current-voltage acquisition for pore size estimation. When combined with a portable amplifier, this device also provides a fully portable sensing platform, an important step toward portable solid-state nanopore sensing applications.

Real-time monitoring of Ti(IV) metal ion binding of transferrin using a solid-state nanopore

Transferrin, a central player in iron transport, has been recognized not only for its role in binding iron but also for its interaction with other metals, including titanium. This study employs solid-state nanopores to investigate the binding of titanium ions [Ti(IV)] to transferrin in a single-molecule and label-free manner. We demonstrate the novel application of solid-state nanopores for single-molecule discrimination between apo-transferrin (metal-free) and Ti(IV)-transferrin. Despite their similar sizes, Ti(IV)-transferrin exhibits a reduced current drop, attributed to differences in translocation times and filter characteristics. Single-molecule analysis reveals Ti(IV)-transferrin's enhanced stability and faster translocations due to its distinct conformational flexibility compared to apo-transferrin. Furthermore, our study showcases solid-state nanopores as real-time monitors of biochemical reactions, tracking the gradual conversion of apo-transferrin to Ti(IV)-transferrin upon the addition of titanium citrate. This work offers insights into Ti(IV) binding to transferrin, promising applications for single-molecule analysis and expanding our comprehension of metal-protein interactions at the molecular level.

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.

Over One Million DNA and Protein Events Through Ultra-Stable Chemically-Tuned Solid-State Nanopores

Stability, long lifetime, resilience against clogging, low noise, and low cost are five critical cornerstones of solid-state nanopore technology. Here, a fabrication protocol is described wherein >1 million events are obtained from a single solid-state nanopore with both DNA and protein at the highest available lowpass filter (LPF, 100 kHz) of the Axopatch 200B-the highest event count mentioned in literature. Moreover, a total of ≈8.1 million events are reported in this work encompassing the two analyte classes. With the 100 kHz LPF, the temporally attenuated population is negligible while with the more ubiquitous 10 kHz, ≈91% of the events are attenuated. With DNA experiments, the pores are operational for hours (typically >7 h) while the average pore growth is merely ≈0.16 ± 0.1 nm h-1 . The current noise is exceptionally stable with traces typically showing <10 pA h-1 increase in noise. Furthermore, a real-time method to clean and revive pores clogged with analyte with the added benefit of minimal pore growth during cleaning (< 5% of the original diameter) is showcased. The enormity of the data collected herein presents a significant advancement to solid-state pore performance and will be useful for future ventures such as machine learning where large amounts of pristine data are a prerequisite.

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.

Portable nanopore-sequencing technology: Trends in development and applications

Sequencing technology is the most commonly used technology in molecular biology research and an essential pillar for the development and applications of molecular biology. Since 1977, when the first generation of sequencing technology opened the door to interpreting the genetic code, sequencing technology has been developing for three generations. It has applications in all aspects of life and scientific research, such as disease diagnosis, drug target discovery, pathological research, species protection, and SARS-CoV-2 detection. However, the first- and second-generation sequencing technology relied on fluorescence detection systems and DNA polymerization enzyme systems, which increased the cost of sequencing technology and limited its scope of applications. The third-generation sequencing technology performs PCR-free and single-molecule sequencing, but it still depends on the fluorescence detection device. To break through these limitations, researchers have made arduous efforts to develop a new advanced portable sequencing technology represented by nanopore sequencing. Nanopore technology has the advantages of small size and convenient portability, independent of biochemical reagents, and direct reading using physical methods. This paper reviews the research and development process of nanopore sequencing technology (NST) from the laboratory to commercially viable tools; discusses the main types of nanopore sequencing technologies and their various applications in solving a wide range of real-world problems. In addition, the paper collates the analysis tools necessary for performing different processing tasks in nanopore sequencing. Finally, we highlight the challenges of NST and its future research and application directions.

Use of a solid-state nanopore for profiling the transferrin receptor protein and distinguishing between transferrin receptor and its ligand protein

A nanopore device is capable of providing single-molecule level information of an analyte as they translocate through the sensing aperture-a nanometer-sized through-hole-under the influence of an applied electric field. In this study, a silicon nitride (Six Ny )-based nanopore was used to characterize the human serum transferrin receptor protein (TfR) under various applied voltages. The presence of dimeric forms of TfR was found to decrease exponentially as the applied electric field increased. Further analysis of monomeric TfR also revealed that its unfolding behaviors were positively dependent on the applied voltage. Furthermore, a comparison between the data of monomeric TfR and its ligand protein, human serum transferrin (hSTf), showed that these two protein populations, despite their nearly identical molecular weights, could be distinguished from each other by means of a solid-state nanopore (SSN). Lastly, the excluded volumes of TfR were experimentally determined at each voltage and were found to be within error of their theoretical values. The results herein demonstrate the successful application of an SSN for accurately classifying monomeric and dimeric molecules while the two populations coexist in a heterogeneous mixture.

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.

Enhanced Signal to Noise Ratio Enables High Bandwidth Nanopore Recordings and Molecular Weight Profiling of Proteins

Fast protein translocations often lead to bandwidth-limited amplitude-attenuated event signatures. In this study, we developed a protein- and electrolyte chemistry-centric pathway to construct a readily executable decision tree for the detection of non-attenuated protein translocations using conventional electronics. Each optimization encompasses increasing capture rate (C_R), signal-to-noise ratio (SNR), and minimizing irreversible analyte clogging to collect >10⁴ events/pipette spanning a host of electric fields. This was demonstrated using 11 proteins ranging from ∼12 kDa to ∼720 kDa. Moreover, both symmetric and asymmetric electrolyte conditions (cis and trans chamber electrolyte concentration ratios _<^> 1) were explored. As a result, asymmetric electrolyte conditions were favorable on the extreme ends of the size spectrum (i.e., larger, and smaller proteins) and while the remainder of proteins were best sensed under symmetric electrolyte conditions. Under these optimal conditions, only ≲10% of events were attenuated at 500 mV (≲ 5% for most proteins at 500 mV with only ≲1-5% of the population faster than ∼7 μs, which is the theoretical attenuation threshold for 100 kHz bandwidth). Finally, applied voltage (V_app), peak current drop (ΔI_p), electrolyte conductivity (K), and open-pore conductance (G₀) were used to generate a linear relationship to evaluate the molecular weight of the protein (M_w) using plots of (dΔI_p)/(dV_app) vs M_w/(G₀/K).

Combining dynamic Monte Carlo with machine learning to study nanoparticle translocation

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

Stochastic Collision Electrochemistry from Single Pt Nanoparticles: Electrocatalytic Amplification and MicroRNA Sensing

Single-particle collisions have made many achievements in basic research, but challenges still exist due to their low collision frequency and selectivity in complex samples. In this work, we developed an "on-off-on" strategy based on Pt nanoparticles (PtNPs) that catalyze N₂H₄ collision signals on the surface of carbon ultramicroelectrodes and established a new method for the detection of miRNA21 with high selectivity and sensitivity. PtNPs catalyze the reduction of N₂H₄ on the surface of carbon ultramicroelectrodes to generate a stepped collision signal, which is in the "on" state. The single-stranded DNA paired with miRNA21 is coupled with PtNPs to form the complex DNA/PtNPs. Because PtNPs are covered by DNA, the electrocatalytic collision of N₂H₄ oxidation is inhibited. At this time, the signal is in the "off" state. When miRNA21 is added, the strong complementary pairing between miRNA21 and DNA destroys the electrostatic adsorption of DNA/PtNP conjugates and restores the electrocatalytic performance of PtNPs, and the signal is in the "on" state again. Based on this, a new method for detecting miRNA21 was established. It provides a new way for small-molecule sensing and has a wide range of applications in electroanalysis, electrocatalysis, and biosensing.

Investigating protein translocation in the presence of an electrolyte concentration gradient across a solid-state nanopore

Electrolyte chemistry plays an important role in the transport properties of analytes through nanopores. Here, we report the translocation properties of the protein human serum transferrin (hSTf) in asymmetric LiCl salt concentrations with either positive (C_trans /C_cis < 1) or negative chemical gradients (C_trans /C_cis > 1). The cis side concentration was fixed at 4 M for positive chemical gradients and at 0.5 M LiCl for negative chemical gradients, while the trans side concentration varied between 0.5 to 4 M which resulted in six different configurations, respectively, for both positive and negative gradient types. For positive chemical gradient conditions, translocations were observed in all six configurations for at least one voltage polarity whereas with negative gradient conditions, dead concentrations where no events at either polarity were observed. The flux of Li⁺ and Cl^- ions and their resultant cation or anion enrichment zones, as well as the interplay of electrophoretic and electroosmotic transport directions, would determine whether hSTf can traverse across the pore.

Nanopore Current Enhancements Lack Protein Charge Dependence and Elucidate Maximum Unfolding at Protein's Isoelectric Point

Protein sequencing, as well as protein fingerprinting, has gained tremendous attention in the electrical sensing realm of solid-state nanopores and is challenging due to fast translocations and the use of high molar electrolytes. Despite providing an appreciable signal-to-noise ratio, high electrolyte concentrations can have adverse effects on the native protein structure. Herein, we present a thorough investigation of low electrolyte sensing conditions across a broad pH and voltage range generating conductive pulses (CPs) irrespective of protein net charge. We used Cas9 as the model protein and demonstrated that unfolding is noncooperative, represented by the gradual elongation or stretching of the protein, and sensitive to both the applied voltage and pH (i.e., charge state). The magnitude of unfolding and the isoelectric point (pI) of Cas9 was found to be correlated and a critical factor in our experiments. Electroosmotic flow (EOF) was always aligned with the transit direction, whereas electrophoretic force (EPF) was either reinforcing (pH < pI) or opposing (pH > pI) the protein's movement, which led to slower translocations at higher pH values. Further exploration of higher pH values led to slowing down of protein with > 30% of the population being slower than 0.5 ms. Our results would be critical for protein sensing at very low electrolytes and to retard their translocation speed without resorting to high-bandwidth equipment.