Paving the way to single-molecule protein sequencing

Electromigrated Gold Nanogap Tunnel Junction Arrays: Fabrication and Electrical Behavior in Liquid and Gaseous Media

Tunnel junctions have been suggested as high-throughput electronic single molecule sensors in liquids with several seminal experiments conducted using break junctions with reconfigurable gaps. For practical single molecule sensing applications, arrays of on-chip integrated fixed-gap tunnel junctions that can be built into compact systems are preferable. Fabricating nanogaps by electromigration is one of the most promising approaches to realize on-chip integrated tunnel junction sensors. However, the electrical behavior of fixed-gap tunnel junctions immersed in liquid media has not been systematically studied to date, and the formation of electromigrated nanogap tunnel junctions in liquid media has not yet been demonstrated. In this work, we perform a comparative study of the formation and electrical behavior of arrays of gold nanogap tunnel junctions made by feedback-controlled electromigration immersed in various liquid and gaseous media (deionized water, mesitylene, ethanol, nitrogen, and air). We demonstrate that tunnel junctions can be obtained from microfabricated gold nanoconstrictions inside liquid media. Electromigration of junctions in air produces the highest yield (61-67%), electromigration in deionized water and mesitylene results in a lower yield than in air (44-48%), whereas electromigration in ethanol fails to produce viable tunnel junctions due to interfering electrochemical processes. We map out the stability of the conductance characteristics of the resulting tunnel junctions and identify medium-specific operational conditions that have an impact on the yield of forming stable junctions. Furthermore, we highlight the unique challenges associated with working with arrays of large numbers of tunnel junctions in batches. Our findings will inform future efforts to build single molecule sensors using on-chip integrated tunnel junctions.

Site-Specific Integration of Hexagonal Boron Nitride Quantum Emitters on 2D DNA Origami Nanopores

Optical emitters in hexagonal boron nitride (hBN) are promising probes for single-molecule sensing platforms. When engineered in nanoparticle form, they can be integrated as detectors in nanodevices, yet positional control at the nanoscale is lacking. Here we demonstrate the functionalization of DNA origami nanopores with optically active hBN nanoparticles (NPs) with nanometer precision. The NPs are active under three wavelengths of visible illumination and display both stable and blinking emission, enabling their accurate localization by using wide-field optical nanoscopy. Correlative opto-structural characterization reveals deterministic binding of bright, multicolor hBN NPs at the pore rim due to π-π stacking interactions at site-specific locations on the DNA origami. Our work provides a scalable, bottom-up approach toward deterministic assembly of solid-state emitters on arbitrary structural elements based on DNA origami. Such a nanoscale arrangement of optically active components can advance the development of single-molecule platforms, including optical nanopores and nanochannel sensors.

Full-Length Single Protein Molecules Tracking and Counting in Thin Silicon Channels

Emerging single-molecule protein sensing techniques are ushering in a transformative era in biomedical research. Nevertheless, challenges persist in realizing ultra-fast full-length protein sensing, including loss of molecular integrity due to protein fragmentation, biases introduced by antibodies affinity, identification of proteoforms, and low throughputs. Here, a single-molecule method for parallel protein separation and tracking is introduced, yielding multi-dimensional molecular properties used for their identification. Proteins are tagged by chemo-selective dual amino-acid specific labels and are electrophoretically separated by their mass/charge in custom-designed thin silicon channel with subwavelength height. This approach allows analysis of thousands of individual proteins within a few minutes by tracking their motion during the migration. The power of the method is demonstrated by quantifying a cytokine panel for host-response discrimination between viral and bacterial infections. Moreover, it is shown that two clinically-relevant splice isoforms of Vascular endothelial growth factor (VEGF) can be accurately quantified from human serum samples. Being non-destructive and compatible with full-length intact proteins, this method opens up ways for antibody-free single-protein molecule quantification.

Omics-based molecular classifications empowering in precision oncology

BACKGROUND

In the past decades, cancer enigmatical heterogeneity at distinct expression levels could interpret disparities in therapeutic response and prognosis. It built hindrances to precision medicine, a tactic to tailor customized treatment informed by the tumors' molecular profile. Single-omics analysis dissected the biological features associated with carcinogenesis to some extent but still failed to revolutionize cancer treatment as expected. Integrated omics analysis incorporated tumor biological networks from diverse layers and deciphered a holistic overview of cancer behaviors, yielding precise molecular classification to facilitate the evolution and refinement of precision medicine.

CONCLUSION

This review outlined the biomarkers at multiple expression layers to tutor molecular classification and pinpoint tumor diagnosis, and explored the paradigm shift in precision therapy: from single- to multi-omics-based subtyping to optimize therapeutic regimens. Ultimately, we firmly believe that by parsing molecular characteristics, omics-based typing will be a powerful assistant for precision oncology.

GSEA analysis identifies potential drug targets and their interaction networks in coronary microcirculation disorders

Coronary microcirculation dysfunction (CMD) is one of the main causes of cardiovascular disease. Traditional treatment methods lack specificity, making it difficult to fully consider the differences in patient conditions and achieve effective treatment and intervention. The complexity and diversity of CMD require more standardized diagnosis and treatment plans to clarify the best treatment strategy and long-term outcomes. The existing treatment measures mainly focus on symptom management, including medication treatment, lifestyle intervention, and psychological therapy. However, the efficacy of these methods is not consistent for all patients, and the long-term efficacy is not yet clear. GSEA is a bioinformatics method used to interpret gene expression data, particularly for identifying the enrichment of predefined gene sets in gene expression data. In order to achieve personalized treatment and improve the quality and effectiveness of interventions, this article combined GSEA (Gene Set Enrichment Analysis) technology to conduct in-depth research on potential drug targets and their interaction networks in coronary microcirculation dysfunctions. This article first utilized the Coremine medical database, GeneCards, and DrugBank public databases to collect gene data. Then, filtering methods were used to preprocess the data, and GSEA was used to analyze the preprocessed gene expression data to identify and calculate pathways and enrichment scores related to CMD. Finally, protein sequence features were extracted through the calculation of autocorrelation features. To verify the effectiveness of GSEA, this article conducted experimental analysis from four aspects: precision, receiver operating characteristic (ROC) curve, correlation, and potential drug targets, and compared them with Gene Regulatory Networks (GRN) and Random Forest (RF) methods. The results showed that compared to the GRN and RF methods, the average precision of GSEA improved by 0.11. The conclusion indicated that GSEA helped identify and explore potential drug targets and their interaction networks, providing new ideas for personalized quality of CMD.

Microfluidic Biochips for Single-Cell Isolation and Single-Cell Analysis of Multiomics and Exosomes

Single-cell multiomic and exosome analyses are potent tools in various fields, such as cancer research, immunology, neuroscience, microbiology, and drug development. They facilitate the in-depth exploration of biological systems, providing insights into disease mechanisms and aiding in treatment. Single-cell isolation, which is crucial for single-cell analysis, ensures reliable cell isolation and quality control for further downstream analyses. Microfluidic chips are small lightweight systems that facilitate efficient and high-throughput single-cell isolation and real-time single-cell analysis on- or off-chip. Therefore, most current single-cell isolation and analysis technologies are based on the single-cell microfluidic technology. This review offers comprehensive guidance to researchers across different fields on the selection of appropriate microfluidic chip technologies for single-cell isolation and analysis. This review describes the design principles, separation mechanisms, chip characteristics, and cellular effects of various microfluidic chips available for single-cell isolation. Moreover, this review highlights the implications of using this technology for subsequent analyses, including single-cell multiomic and exosome analyses. Finally, the current challenges and future prospects of microfluidic chip technology are outlined for multiplex single-cell isolation and multiomic and exosome analyses.

Full-length single-molecule protein fingerprinting

Proteins are the primary functional actors of the cell. While proteoform diversity is known to be highly biologically relevant, current protein analysis methods are of limited use for distinguishing proteoforms. Mass spectrometric methods, in particular, often provide only ambiguous information on post-translational modification sites, and sequences of co-existing modifications may not be resolved. Here we demonstrate fluorescence resonance energy transfer (FRET)-based single-molecule protein fingerprinting to map the location of individual amino acids and post-translational modifications within single full-length protein molecules. Our data show that both intrinsically disordered proteins and folded globular proteins can be fingerprinted with a subnanometer resolution, achieved by probing the amino acids one by one using single-molecule FRET via DNA exchange. This capability was demonstrated through the analysis of alpha-synuclein, an intrinsically disordered protein, by accurately quantifying isoforms in mixtures using a machine learning classifier, and by determining the locations of two O-GlcNAc moieties. Furthermore, we demonstrate fingerprinting of the globular proteins Bcl-2-like protein 1, procalcitonin and S100A9. We anticipate that our ability to perform proteoform identification with the ultimate sensitivity may unlock exciting new venues in proteomics research and biomarker-based diagnosis.

Single-Molecule Electrical Profiling of Peptides and Proteins

In recent decades, there has been a significant increase in the application of single-molecule electrical analysis platforms in studying proteins and peptides. These advanced analysis methods have the potential for deep investigation of enzymatic working mechanisms and accurate monitoring of dynamic changes in protein configurations, which are often challenging to achieve in ensemble measurements. In this work, the prominent research progress in peptide and protein-related studies are surveyed using electronic devices with single-molecule/single-event sensitivity, including single-molecule junctions, single-molecule field-effect transistors, and nanopores. In particular, the successful commercial application of nanopores in DNA sequencing has made it one of the most promising techniques in protein sequencing at the single-molecule level. From single peptides to protein complexes, the correlation between their electrical characteristics, structures, and biological functions is gradually being established. This enables to distinguish different molecular configurations of these biomacromolecules through real-time electrical monitoring of their life activities, significantly improving the understanding of the mechanisms underlying various life processes.

Tertiary Amine Coupling by Oxidation for Selective Labeling of Dimethyl Lysine Post-Translational Modifications

Lysine dimethylation (Kme2) is a crucial post-translational modification (PTM) that regulates biological processes and is implicated in diseases. There is significant interest in globally identifying these methylation marks. Unfortunately, this remains challenging due to the lack of robust technologies for selectively labeling Kme2. To address this, we present a chemical method named tertiary amine coupling by oxidation (TACO). This method selectively modifies Kme2 to aldehydes using Selectfluor and a base. The resulting aldehydes from Kme2 were then functionalized using reductive amination, thiolamine, and oxime chemistry. We successfully demonstrated the versatility of TACO in selectively labeling Kme2 peptides and proteins in complex cell lysate mixtures with varying payloads, including affinity tags and fluorophores. We further showed the application of TACO chemistry for the identification of Kme2 sites at a single-molecule level by fluorosequencing. We discovered novel 30 Kme2 sites, in addition to previously known 5 Kme2 sites, by proteomics analysis of TACO-modified nuclear extracts. Our work establishes a unique strategy for covalently modifying Kme2, facilitating the global identification of low-abundance Kme2-PTMs and their sites within complex cell lysate mixtures.

Label-free and amplification-free viral RNA quantification from primate biofluids using a trapping-assisted optofluidic nanopore platform

Viral outbreaks can cause widespread disruption, creating the need for diagnostic tools that provide high performance and sample versatility at the point of use with moderate complexity. Current gold standards such as PCR and rapid antigen tests fall short in one or more of these aspects. Here, we report a label-free and amplification-free nanopore sensor platform that overcomes these challenges via direct detection and quantification of viral RNA in clinical samples from a variety of biological fluids. The assay uses an optofluidic chip that combines optical waveguides with a fluidic channel and integrates a solid-state nanopore for sensing of individual biomolecules upon translocation through the pore. High specificity and low limit of detection are ensured by capturing RNA targets on microbeads and collecting them by optical trapping at the nanopore location where targets are released and rapidly detected. We use this device for longitudinal studies of the viral load progression for Zika and Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) infections in marmoset and baboon animal models, respectively. The up to million-fold trapping-based target concentration enhancement enables amplification-free RNA quantification across the clinically relevant concentration range down to the assay limit of RT-qPCR as well as cases in which PCR failed. The assay operates across all relevant biofluids, including semen, urine, and whole blood for Zika and nasopharyngeal and throat swab, rectal swab, and bronchoalveolar lavage for SARS-CoV-2. The versatility, performance, simplicity, and potential for full microfluidic integration of the amplification-free nanopore assay points toward a unique approach to molecular diagnostics for nucleic acids, proteins, and other targets.

Nanoconfined Electrokinetic Chromatography (NEC): Gradient Separation and Sensing of Short DNA Fragments at the Single-Molecule Level

Glass nanopipets have been demonstrated to be a powerful tool for the sensing and discrimination of biomolecules, such as DNA strands with different lengths or configurations. Despite progress made in nanopipet-based sensors, it remains challenging to develop effective strategies that separate and sense in one operation. In this study, we demonstrate an agarose gel-filled nanopipet that enables hyphenated length-dependent separation and electrochemical sensing of short DNA fragments based on the electrokinetic flow of DNA molecules in the nanoconfined channel at the tip of the nanopipet. This nanoconfined electrokinetic chromatography (NEC) method is used to distinguish the mixture of DNA strands without labels, and the ionic current signals measured in real time show that the mixed DNA strands pass through the tip hole in order according to the molecular weight. With NEC, gradient separation and electrochemical measurement of biomolecules can be achieved simultaneously at the single-molecule level, which is further applied for programmable gene delivery into single living cells. Overall, NEC provides a multipurpose platform integrating separation, sensing, single-cell delivery, and manipulation, which may bring new insights into advanced bioapplication.

Protein Deceleration and Sequencing Using Si3N4-CNT Hybrid Nanopores

Protein sequencing is crucial for understanding the complex mechanisms driving biological functions and is of utmost importance in molecular diagnostics and medication development. Nanopores have become an effective tool for single molecule sensing, however, the weak charge and non-uniform charge distribution of protein make capturing and sensing very challenging, which poses a significant obstacle to the development of nanopore-based protein sequencing. In this study, to facilitate capturing of the unfolded protein, highly charged peptide was employed in our simulations, we found that the velocity of unfolded peptide translocating through a hybrid nanopore composed of silicon nitride membrane and carbon nanotube is much slower compared to bare silicon nitride nanopore, it is due to the significant interaction between amino acids and the surface of carbon nanotube. Moreover, by introducing variations in the charge states at the boundaries of carbon nanotube nanopores, the competition and combination of the electrophoretic and electroosmotic flows through the nanopores could be controlled, we then successfully regulated the translocation velocity of unfolded proteins through the hybrid nanopores. The proposed hybrid nanopore effectively retards the translocation velocity of protein through it, facilitates the acquisition of ample information for accurate amino acid identification.

Real-time detection of 20 amino acids and discrimination of pathologically relevant peptides with functionalized nanopore

Precise identification and quantification of amino acids is crucial for many biological applications. Here we report a copper(II)-functionalized Mycobacterium smegmatis porin A (MspA) nanopore with the N91H substitution, which enables direct identification of all 20 proteinogenic amino acids when combined with a machine-learning algorithm. The validation accuracy reaches 99.1%, with 30.9% signal recovery. The feasibility of ultrasensitive quantification of amino acids was also demonstrated at the nanomolar range. Furthermore, the capability of this system for real-time analyses of two representative post-translational modifications (PTMs), one unnatural amino acid and ten synthetic peptides using exopeptidases, including clinically relevant peptides associated with Alzheimer's disease and cancer neoantigens, was demonstrated. Notably, our strategy successfully distinguishes peptides with only one amino acid difference from the hydrolysate and provides the possibility to infer the peptide sequence.

Nanopore DNA sequencing technologies and their applications towards single-molecule proteomics

Sequencing of nucleic acids with nanopores has emerged as a powerful tool offering rapid readout, high accuracy, low cost and portability. This label-free method for sequencing at the single-molecule level is an achievement on its own. However, nanopores also show promise for the technologically even more challenging sequencing of polypeptides, something that could considerably benefit biological discovery, clinical diagnostics and homeland security, as current techniques lack portability and speed. Here we survey the biochemical innovations underpinning commercial and academic nanopore DNA/RNA sequencing techniques, and explore how these advances can fuel developments in future protein sequencing with nanopores.

Lipid vesicle-based molecular robots

A molecular robot, which is a system comprised of one or more molecular machines and computers, can execute sophisticated tasks in many fields that span from nanomedicine to green nanotechnology. The core parts of molecular robots are fairly consistent from system to system and always include (i) a body to encapsulate molecular machines, (ii) sensors to capture signals, (iii) computers to make decisions, and (iv) actuators to perform tasks. This review aims to provide an overview of approaches and considerations to develop molecular robots. We first introduce the basic technologies required for constructing the core parts of molecular robots, describe the recent progress towards achieving higher functionality, and subsequently discuss the current challenges and outlook. We also highlight the applications of molecular robots in sensing biomarkers, signal communications with living cells, and conversion of energy. Although molecular robots are still in their infancy, they will unquestionably initiate massive change in biomedical and environmental technology in the not too distant future.

Aptamer-Functionalized Interface Nanopores Enable Amino Acid-Specific Peptide Detection

Single-molecule proteomics based on nanopore technology has made significant advances in recent years. However, to achieve nanopore sensing with single amino acid resolution, several bottlenecks must be tackled: controlling nanopore sizes with nanoscale precision and slowing molecular translocation events. Herein, we address these challenges by integrating amino acid-specific DNA aptamers into interface nanopores with dynamically tunable pore sizes. A phenylalanine aptamer was used as a proof-of-concept: aptamer recognition of phenylalanine moieties led to the retention of specific peptides, slowing translocation speeds. Importantly, while phenylalanine aptamers were isolated against the free amino acid, the aptamers were determined to recognize the combination of the benzyl or phenyl and the carbonyl group in the peptide backbone, enabling binding to specific phenylalanine-containing peptides. We decoupled specific binding between aptamers and phenylalanine-containing peptides from nonspecific interactions (e.g., electrostatics and hydrophobic interactions) using optical waveguide lightmode spectroscopy. Aptamer-modified interface nanopores differentiated peptides containing phenylalanine vs. control peptides with structurally similar amino acids (i.e., tyrosine and tryptophan). When the duration of aptamer-target interactions inside the nanopore were prolonged by lowering the applied voltage, discrete ionic current levels with repetitive motifs were observed. Such reoccurring signatures in the measured signal suggest that the proposed method has the possibility to resolve amino acid-specific aptamer recognition, a step toward single-molecule proteomics.

Multivariate analysis of nanoparticle translocation through a nanopore to improve the accuracy of resistive pulse sensing

The advent of nanopore-based sensors based on resistive pulse sensing gave rise to a remarkable breakthrough in the detection and characterization of nanoscale species. Some strong correlations have been reported between the resistive pulse characteristics and the particle's geometrical and physical properties. These correlations are commonly used to obtain information about the particles in commercial devices and research setups. The correlations, however, do not consider the simultaneous effect of influential factors such as particle shape and off-axis translocation, which complicates the extraction of accurate information from the resistive pulses. In this paper, we numerically studied the impact of the shape and position of particles on pulse characteristics in order to estimate the errors that arise from neglecting the influence of multiple factors on resistive pulses. We considered the sphere, oblate, and prolate particles to investigate the nanoparticle shape effect. Moreover, the trajectory dependency was examined by considering the translocation of nanoparticles away from the nanopore axis. Meanwhile, the shape effect was studied for different trajectories. We observed that the simultaneous effects of influential parameters could lead to significant errors in estimating particle properties if the coupled effects are neglected. Based on the results, we introduce the "pulse waveshape" as a novel characteristic of the resistive pulse that can be utilized as a decoupling parameter in the analysis of resistive pulses.

Narrowing Signal Distribution by Adamantane Derivatization for Amino Acid Identification Using an α-Hemolysin Nanopore

The rapid progress in nanopore sensing has sparked interest in protein sequencing. Despite recent notable advancements in amino acid recognition using nanopores, chemical modifications usually employed in this process still need further refinements. One of the challenges is to enhance the chemical specificity to avoid downstream misidentification of amino acids. By employing adamantane to label proteinogenic amino acids, we developed an approach to fingerprint individual amino acids using the wild-type α-hemolysin nanopore. The unique structure of adamantane-labeled amino acids (ALAAs) improved the spatial resolution, resulting in distinctive current signals. Various nanopore parameters were explored using a machine-learning algorithm and achieved a validation accuracy of 81.3% for distinguishing nine selected amino acids. Our results not only advance the effort in single-molecule protein characterization using nanopores but also offer a potential platform for studying intrinsic and variant structures of individual molecules.

Optical sequencing of single synthetic polymers

Microscopic sequences of synthetic polymers play crucial roles in the polymer properties, but are generally unknown and inaccessible to traditional measurements. Here we report real-time optical sequencing of single synthetic copolymer chains under living polymerization conditions. We achieve this by carrying out multi-colour imaging of polymer growth by single catalysts at single-monomer resolution using CREATS (coupled reaction approach toward super-resolution imaging). CREATS makes a reaction effectively fluorogenic, enabling single-molecule localization microscopy of chemical reactions at higher reactant concentrations. Our data demonstrate that the chain propagation kinetics of surface-grafted polymerization contains temporal fluctuations with a defined memory time (which can be attributed to neighbouring monomer interactions) and chain-length dependence (due to surface electrostatic effects). Furthermore, the microscopic sequences of individual copolymers reveal their tendency to form block copolymers, and, more importantly, quantify the size distribution of individual blocks for comparison with theoretically random copolymers. Such sequencing capability paves the way for single-chain-level structure-function correlation studies of synthetic polymers.

Nanoscale electrohydrodynamic ion transport: Influences of channel geometry and polarization-induced surface charges

Electrohydrodynamic ion transport has been studied in nanotubes, nanoslits, and nanopores to mimic the advanced functionalities of biological ion channels. However, probing how the intricate interplay between the electrical and mechanical interactions affects ion conduction in asymmetric nanoconduits presents further obstacles. Here, ion transport across a conical nanopore embedded in a polarizable membrane under an electric field and pressure is analyzed by numerically solving a continuum model based on the Poisson, Nernst-Planck, and Navier-Stokes equations. We report an anomalous ionic current depletion, of up to 75%, and an unexpected rise in current rectification when pressure is exerted along the external electric field. Membrane polarization is revealed as the prerequisite to obtain this previously undetected electrohydrodynamic coupling. The electric field induces large surface charges at the pore tip due to its conical shape, creating nonuniform electrical double layers (EDL) with a massive accumulation of electrolyte ions near the orifice. Once applied, the pressure distorts the quasiequilibrium distribution of the EDL ions to influence the nanopore conductivity. Our fundamental approach to inspect the effect of pressure on the channel EDL (and thus ionic conductance) in contrast to its effect on the current arising from the hydrodynamic streaming of ions further explains the pressure-sensitive ion transport in different nanochannels and physical regimes manifested in past experiments, including the hitherto inexplicit mechanism behind the mechanically activated ion transport in carbon nanotubes. This enhances our broad understanding of nanoscale electrohydrodynamic ion transport, yielding a platform to build nanofluidic devices and ionic circuits with more robust and tunable responses to electrical and mechanical stimuli.

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.

Unfolding of protein using MoS2/SnS2heterostructure for nanopore-based sequencing

Protein sequencing is crucial for understanding the complex mechanisms driving biological functions. However, proteins are usually folded in their native state and the mechanism of fast protein conformation transitions still remains unclear, which make protein sequencing challenging. Molecular dynamics simulations with accurate force field are now able to observe the entire folding/unfolding process, providing valuable insights into protein folding mechanisms. Given that proteins can be unfolded, nanopore technology shows great potential for protein sequencing. In this study, we proposed to use MoS2/SnS2heterostructures to firstly unfold proteins and then detect them by a nanopore in the heterostructural membrane. All-atom molecular dynamics simulations performed in this work provided rich atomic-level information for a comprehensive understanding of protein unfolding process and mechanism on the MoS2/SnS2heterostructure, it was found that the strong binding of protein to SnS2nanostripe and hydrogen bond breaking were the main reasons for unfolding the protein on the heterostructure. After the protein was fully unfolded, it was restrained on the nanostripe because of the affinity of protein to the SnS2nanostripe. Thus by integrating the proposed unfolding technique with nanopore technology, detection of linear unfolded peptide was realized in this work, allowing for the identification of protein components, which is essential for sequencing proteins in the near future.

Peptide sequencing based on host-guest interaction-assisted nanopore sensing

Direct protein sequencing technologies with improved sensitivity and throughput are still needed. Here, we propose an alternative method for peptide sequencing based on enzymatic cleavage and host-guest interaction-assisted nanopore sensing. We serendipitously discovered that the identity of any proteinogenic amino acid in a particular position of a phenylalanine-containing peptide could be determined via current blockage during translocation of the peptide through α-hemolysin nanopores in the presence of cucurbit[7]uril. Building upon this, we further present a proof-of-concept demonstration of peptide sequencing by sequentially cleaving off amino acids from C terminus of a peptide with carboxypeptidases, and then determining their identities and sequence with a peptide probe in nanopore. With future optimization, our results point to a different way of nanopore-based protein sequencing.

Solid-State Nanopores for Biomolecular Analysis and Detection

Advances in nanopore technology and data processing have rendered DNA sequencing highly accessible, unlocking a new realm of biotechnological opportunities. Commercially available nanopores for DNA sequencing are of biological origin and have certain disadvantages such as having specific environmental requirements to retain functionality. Solid-state nanopores have received increased attention as modular systems with controllable characteristics that enable deployment in non-physiological milieu. Thus, we focus our review on summarizing recent innovations in the field of solid-state nanopores to envision the future of this technology for biomolecular analysis and detection. We begin by introducing the physical aspects of nanopore measurements ranging from interfacial interactions at pore and electrode surfaces to mass transport of analytes and data analysis of recorded signals. Then, developments in nanopore fabrication and post-processing techniques with the pros and cons of different methodologies are examined. Subsequently, progress to facilitate DNA sequencing using solid-state nanopores is described to assess how this platform is evolving to tackle the more complex challenge of protein sequencing. Beyond sequencing, we highlight the recent developments in biosensing of nucleic acids, proteins, and sugars and conclude with an outlook on the frontiers of nanopore technologies.

Molecular sensitised probe for amino acid recognition within peptide sequences

The combination of low-temperature scanning tunnelling microscopy with a mass-selective electro-spray ion-beam deposition established the investigation of large biomolecules at nanometer and sub-nanometer scale. Due to complex architecture and conformational freedom, however, the chemical identification of building blocks of these biopolymers often relies on the presence of markers, extensive simulations, or is not possible at all. Here, we present a molecular probe-sensitisation approach addressing the identification of a specific amino acid within different peptides. A selective intermolecular interaction between the sensitiser attached at the tip-apex and the target amino acid on the surface induces an enhanced tunnelling conductance of one specific spectral feature, which can be mapped in spectroscopic imaging. Density functional theory calculations suggest a mechanism that relies on conformational changes of the sensitiser that are accompanied by local charge redistributions in the tunnelling junction, which, in turn, lower the tunnelling barrier at that specific part of the peptide.

Nano/microfluidic device for high-throughput passive trapping of nanoparticles

We present a design and a fabrication method for devices designed for rapid collection of nanoparticles in a fluid. The design uses nanofluidic channels as a passive size-based barrier trap to isolate particles near a central point in the channel, which is also covered by a thin membrane. Particles that enter the collection region are trapped with 100% efficiency within a 6-12 μ m radius from a central point. Flow rates for particle-free fluid range from 1.88 to 3.69 nl/s for the pressure and geometries tested. Particle trapping tests show that high trapped particle counts significantly impact flow rates. For suspensions as dilute as 30-300 aM (20-200 particles/μ l), 8-80 particles are captured within 500 s.

NanoDeep: a deep learning framework for nanopore adaptive sampling on microbial sequencing

Nanopore sequencers can enrich or deplete the targeted DNA molecules in a library by reversing the voltage across individual nanopores. However, it requires substantial computational resources to achieve rapid operations in parallel at read-time sequencing. We present a deep learning framework, NanoDeep, to overcome these limitations by incorporating convolutional neural network and squeeze and excitation. We first showed that the raw squiggle derived from native DNA sequences determines the origin of microbial and human genomes. Then, we demonstrated that NanoDeep successfully classified bacterial reads from the pooled library with human sequence and showed enrichment for bacterial sequence compared with routine nanopore sequencing setting. Further, we showed that NanoDeep improves the sequencing efficiency and preserves the fidelity of bacterial genomes in the mock sample. In addition, NanoDeep performs well in the enrichment of metagenome sequences of gut samples, showing its potential applications in the enrichment of unknown microbiota. Our toolkit is available at https://github.com/lysovosyl/NanoDeep.

Beam search decoder for enhancing sequence decoding speed in single-molecule peptide sequencing data

Next-generation single-molecule protein sequencing technologies have the potential to significantly accelerate biomedical research. These technologies offer sensitivity and scalability for proteomic analysis. One auspicious method is fluorosequencing, which involves: cutting naturalized proteins into peptides, attaching fluorophores to specific amino acids, and observing variations in light intensity as one amino acid is removed at a time. The original peptide is classified from the sequence of light-intensity reads, and proteins can subsequently be recognized with this information. The amino acid step removal is achieved by attaching the peptides to a wall on the C-terminal and using a process called Edman Degradation to remove an amino acid from the N-Terminal. Even though a framework (Whatprot) has been proposed for the peptide classification task, processing times remain restrictive due to the massively parallel data acquisicion system. In this paper, we propose a new beam search decoder with a novel state formulation that obtains considerably lower processing times at the expense of only a slight accuracy drop compared to Whatprot. Furthermore, we explore how our novel state formulation may lead to even faster decoders in the future.

Enzyme-less nanopore detection of post-translational modifications within long polypeptides

Means to analyse cellular proteins and their millions of variants at the single-molecule level would uncover substantial information previously unknown to biology. Nanopore technology, which underpins long-read DNA and RNA sequencing, holds potential for full-length proteoform identification. We use electro-osmosis in an engineered charge-selective nanopore for the non-enzymatic capture, unfolding and translocation of individual polypeptides of more than 1,200 residues. Unlabelled thioredoxin polyproteins undergo transport through the nanopore, with directional co-translocational unfolding occurring unit by unit from either the C or N terminus. Chaotropic reagents at non-denaturing concentrations accelerate the analysis. By monitoring the ionic current flowing through the nanopore, we locate post-translational modifications deep within the polypeptide chains, laying the groundwork for compiling inventories of the proteoforms in cells and tissues.

Recent progress in analytical strategies of arsenic-binding proteomes in living systems

Arsenic (As) is one of the most concerning elements due to its high exposure risks to organisms and ecosystems. The interaction between arsenicals and proteins plays a pivotal role in inducing their biological effects on living systems, e.g., arsenicosis. In this review article, the recent advances in analytical techniques and methods of As-binding proteomes were well summarized and discussed, including chromatographic separation and purification, biotin-streptavidin pull-down probes, in situ imaging using novel fluorescent probes, and protein identification. These analytical technologies could provide a growing body of knowledge regarding the composition, level, and distribution of As-binding proteomes in both cells and biological samples, even at the organellar level. The perspectives on analysis of As-binding proteomes are also proposed, e.g., isolation and identification of minor proteins, in vivo targeted protein degradation (TPD) technologies, and spatial As-binding proteomics. The application and development of sensitive, accurate, and high-throughput methodologies of As-binding proteomics would enable us to address the key molecular mechanisms underlying the adverse health effects of arsenicals.

Protein Sequencing with Artificial Intelligence: Machine Learning Integrated Phosphorene Nanoslit

Achieving high throughput protein sequencing at single molecule resolution remains a daunting challenge. Herein, relying on a solid-state 2D phosphorene nanoslit device, an extraordinary biosensor to rapidly identify the key signatures of all twenty amino acids using an interpretable machine learning (ML) model is reported. The XGBoost regression algorithm allows the determination of the transmission function of all twenty amino acids with high accuracy. The resultant ML and DFT studies reveal that it is possible to identify individual amino acids through transmission and current signals readouts with high sensitivity and selectivity. Moreover, we thoroughly compared our results to those from graphene nanoslit and found that the phosphorene nanoslit device can be an ideal candidate for protein sequencing up to a 20-fold increase in transmission sensitivity. The present study facilitates high throughput screening of all twenty amino acids and can be further extended to other biomolecules for disease diagnosis and therapeutic decision making.

Multi-pass, single-molecule nanopore reading of long protein strands with single-amino acid sensitivity

The ability to sequence single protein molecules in their native, full-length form would enable a more comprehensive understanding of proteomic diversity. Current technologies, however, are limited in achieving this goal. Here, we establish a method for long-range, single-molecule reading of intact protein strands on a commercial nanopore sensor array. By using the ClpX unfoldase to ratchet proteins through a CsgG nanopore, we achieve single-amino acid level sensitivity, enabling sequencing of combinations of amino acid substitutions across long protein strands. For greater sequencing accuracy, we demonstrate the ability to reread individual protein molecules, spanning hundreds of amino acids in length, multiple times, and explore the potential for high accuracy protein barcode sequencing. Further, we develop a biophysical model that can simulate raw nanopore signals a priori, based on amino acid volume and charge, enhancing the interpretation of raw signal data. Finally, we apply these methods to examine intact, folded protein domains for complete end-to-end analysis. These results provide proof-of-concept for a platform that has the potential to identify and characterize full-length proteoforms at single-molecule resolution.

Common Post-translational Modifications (PTMs) of Proteins: Analysis by Up-to-Date Analytical Techniques with an Emphasis on Barley

Post-translational modifications (PTMs) of biomacromolecules can be useful for understanding the processes by which a relatively small number of individual genes in a particular genome can generate enormous biological complexity in different organisms. The proteomes of barley and the brewing process were investigated by different techniques. However, their diverse and complex PTMs remain understudied. As standard analytical approaches have limitations, innovative analytical approaches need to be developed and applied in PTM studies. To make further progress in this field, it is necessary to specify the sites of modification, as well as to characterize individual isoforms with increased selectivity and sensitivity. This review summarizes advances in the PTM analysis of barley proteins, particularly those involving mass spectrometric detection. Our focus is on monitoring phosphorylation, glycation, and glycosylation, which critically influence functional behavior in metabolism and regulation in organisms.

Robust and scalable single-molecule protein sequencing with fluorosequencing

The need to accurately survey proteins and their modifications with ever higher sensitivities, particularly in clinical settings with limited samples, is spurring development of new single molecule proteomics technologies. Fluorosequencing is one such highly parallelized single molecule peptide sequencing platform, based on determining the sequence positions of select amino acid types within peptides to enable their identification and quantification from a reference database. Here, we describe substantial improvements to fluorosequencing, including identifying fluorophores compatible with the sequencing chemistry, mitigating dye-dye interactions through the use of extended polyproline linkers, and developing an end-to-end workflow for sample preparation and sequencing. We demonstrate by fluorosequencing peptides in mixtures and identifying a target neoantigen from a database of decoy MHC peptides, highlighting the potential of the technology for high sensitivity clinical applications.

Engineering Biological Nanopore Approaches toward Protein Sequencing

Biotechnological innovations have vastly improved the capacity to perform large-scale protein studies, while the methods we have for identifying and quantifying individual proteins are still inadequate to perform protein sequencing at the single-molecule level. Nanopore-inspired systems devoted to understanding how single molecules behave have been extensively developed for applications in genome sequencing. These nanopore systems are emerging as prominent tools for protein identification, detection, and analysis, suggesting realistic prospects for novel protein sequencing. This review summarizes recent advances in biological nanopore sensors toward protein sequencing, from the identification of individual amino acids to the controlled translocation of peptides and proteins, with attention focused on device and algorithm development and the delineation of molecular mechanisms with the aid of simulations. Specifically, the review aims to offer recommendations for the advancement of nanopore-based protein sequencing from an engineering perspective, highlighting the need for collaborative efforts across multiple disciplines. These efforts should include chemical conjugation, protein engineering, molecular simulation, machine-learning-assisted identification, and electronic device fabrication to enable practical implementation in real-world scenarios.

Protein engineering of pores for separation, sensing, and sequencing

Proteins are critical to cellular function and survival. They are complex molecules with precise structures and chemistries, which allow them to serve diverse functions for maintaining overall cell homeostasis. Since the discovery of the first enzyme in 1833, a gamut of advanced experimental and computational tools has been developed and deployed for understanding protein structure and function. Recent studies have demonstrated the ability to redesign/alter natural proteins for applications in industrial processes of interest and to make customized, novel synthetic proteins in the laboratory through protein engineering. We comprehensively review the successes in engineering pore-forming proteins and correlate the amino acid-level biochemistry of different pore modification strategies to the intended applications limited to nucleotide/peptide sequencing, single-molecule sensing, and precise molecular separations.

Unidirectional single-file transport of full-length proteins through a nanopore

The electrical current blockade of a peptide or protein threading through a nanopore can be used as a fingerprint of the molecule in biosensor applications. However, threading of full-length proteins has only been achieved using enzymatic unfolding and translocation. Here we describe an enzyme-free approach for unidirectional, slow transport of full-length proteins through nanopores. We show that the combination of a chemically resistant biological nanopore, α-hemolysin (narrowest part is ~1.4 nm in diameter), and a high concentration guanidinium chloride buffer enables unidirectional, single-file protein transport propelled by an electroosmotic effect. We show that the mean protein translocation velocity depends linearly on the applied voltage and translocation times depend linearly on length, resembling the translocation dynamics of ssDNA. Using a supervised machine-learning classifier, we demonstrate that single-translocation events contain sufficient information to distinguish their threading orientation and identity with accuracies larger than 90%. Capture rates of protein are increased substantially when either a genetically encoded charged peptide tail or a DNA tag is added to a protein.

Gating of β-Barrel Protein Pores, Porins, and Channels: An Old Problem with New Facets

β barrels are ubiquitous proteins in the outer membranes of mitochondria, chloroplasts, and Gram-negative bacteria. These transmembrane proteins (TMPs) execute a wide variety of tasks. For example, they can serve as transporters, receptors, membrane-bound enzymes, as well as adhesion, structural, and signaling elements. In addition, multimeric β barrels are common structural scaffolds among many pore-forming toxins. Significant progress has been made in understanding the functional, structural, biochemical, and biophysical features of these robust and versatile proteins. One frequently encountered fundamental trait of all β barrels is their voltage-dependent gating. This process consists of reversible or permanent conformational transitions between a large-conductance, highly permeable open state and a low-conductance, solute-restrictive closed state. Several intrinsic molecular mechanisms and environmental factors modulate this universal property of β barrels. This review article outlines the typical signatures of voltage-dependent gating. Moreover, we discuss recent developments leading to a better qualitative understanding of the closure dynamics of these TMPs.

Protein Sizing with 15 nm Conical Biological Nanopore YaxAB

Nanopores are promising single-molecule tools for the electrical identification and sequencing of biomolecules. However, the characterization of proteins, especially in real-time and in complex biological samples, is complicated by the sheer variety of sizes and shapes in the proteome. Here, we introduce a large biological nanopore, YaxAB for folded protein analysis. The 15 nm cis-opening and a 3.5 nm trans-constriction describe a conical shape that allows the characterization of a wide range of proteins. Molecular dynamics showed proteins are captured by the electroosmotic flow, and the overall resistance is largely dominated by the narrow trans constriction region of the nanopore. Conveniently, proteins in the 35-125 kDa range remain trapped within the conical lumen of the nanopore for a time that can be tuned by the external bias. Contrary to cylindrical nanopores, in YaxAB, the current blockade decreases with the size of the trapped protein, as smaller proteins penetrate deeper into the constriction region than larger proteins do. These characteristics are especially useful for characterizing large proteins, as shown for pentameric C-reactive protein (125 kDa), a widely used health indicator, which showed a signal that could be identified in the background of other serum proteins.

Estimating error rates for single molecule protein sequencing experiments

The practical application of new single molecule protein sequencing (SMPS) technologies requires accurate estimates of their associated sequencing error rates. Here, we describe the development and application of two distinct parameter estimation methods for analyzing SMPS reads produced by fluorosequencing. A Hidden Markov Model (HMM) based approach, extends whatprot, where we previously used HMMs for SMPS peptide-read matching. This extension offers a principled approach for estimating key parameters for fluorosequencing experiments, including missed amino acid cleavages, dye loss, and peptide detachment. Specifically, we adapted the Baum-Welch algorithm, a standard technique to estimate transition probabilities for an HMM using expectation maximization, but modified here to estimate a small number of parameter values directly rather than estimating every transition probability independently, which should help prevent overfitting. We demonstrate a high degree of accuracy on simulated data, but on experimental datasets, we observed that the model needed to be augmented with an additional error type, N-terminal blocking. This, in combination with data pre-processing, results in reasonable parameterizations of experimental datasets that agree with controlled experimental perturbations. A second independent implementation using a hybrid of DIRECT and Powell's method to reduce the root mean squared error (RMSE) between simulations and the real dataset was also developed. We compare these methods on both simulated and real data, finding that our Baum-Welch based approach outperforms DIRECT and Powell's method by most, but not all, criteria. Although some discrepancies between the results exist, we also find that both approaches provide similar error rate estimates from experimental single molecule fluorosequencing datasets.

Detection of Biological Molecules Using Nanopore Sensing Techniques

Modern biomedical sensing techniques have significantly increased in precision and accuracy due to new technologies that enable speed and that can be tailored to be highly specific for markers of a particular disease. Diagnosing early-stage conditions is paramount to treating serious diseases. Usually, in the early stages of the disease, the number of specific biomarkers is very low and sometimes difficult to detect using classical diagnostic methods. Among detection methods, biosensors are currently attracting significant interest in medicine, for advantages such as easy operation, speed, and portability, with additional benefits of low costs and repeated reliable results. Single-molecule sensors such as nanopores that can detect biomolecules at low concentrations have the potential to become clinically relevant. As such, several applications have been introduced in this field for the detection of blood markers, nucleic acids, or proteins. The use of nanopores has yet to reach maturity for standardization as diagnostic techniques, however, they promise enormous potential, as progress is made into stabilizing nanopore structures, enhancing chemistries, and improving data collection and bioinformatic analysis. This review offers a new perspective on current biomolecule sensing techniques, based on various types of nanopores, challenges, and approaches toward implementation in clinical settings.

Unlocking the Power of Nanopores: Recent Advances in Biosensing Applications and Analog Front-End

The biomedical field has always fostered innovation and the development of various new technologies. Beginning in the last century, demand for picoampere-level current detection in biomedicine has increased, leading to continuous breakthroughs in biosensor technology. Among emerging biomedical sensing technologies, nanopore sensing has shown great potential. This paper reviews nanopore sensing applications, such as chiral molecules, DNA sequencing, and protein sequencing. However, the ionic current for different molecules differs significantly, and the detection bandwidths vary as well. Therefore, this article focuses on current sensing circuits, and introduces the latest design schemes and circuit structures of different feedback components of transimpedance amplifiers mainly used in nanopore DNA sequencing.

Substantial Slowing of Electrophoretic Translocation of DNA through a Nanopore Using Coherent Multiple Entropic Traps

One of the major challenges in the technology of sequencing DNA using single-molecule electrophoresis through a nanopore is to control the translocation of the macromolecule across the pore in order to allow sufficient time for accurate sequence reading at limited recording bandwidths. If the translocation speed is too fast, the signatures of the bases passing through the sensing region of the nanopore overlap in time, presenting difficulties in accurately identifying the bases in a sequential manner. Even though several strategies, such as enzyme ratcheting, have been implemented to reduce the translocation speed, the challenge to achieve a substantial reduction in the translocation speed continues to be of paramount significance. Toward achieving this goal, we have fabricated a nonenzymatic hybrid device that can reduce the translocation speed of long DNAs by more than 2 orders of magnitude, in comparison with the current status of the art. This device is made of a tetra-PEG hydrogel that is chemically anchored to the donor side of a solid-state nanopore. The idea behind this device is based on the recent discovery of the topologically frustrated dynamical state of confined polymers, whereby the front hydrogel matter of the hybrid device provides multiple entropic traps for a single DNA molecule holding it back against the electrophoretic driving force that pulls the DNA through the solid-state nanopore portion of the device. As a demonstration of slowing DNA translocation by a factor of about 500, we find the average translocation time realized in the present hybrid device for 3 kbp DNA as 23.4 ms, whereas the corresponding time for the bare solid-state nanopore under otherwise identical conditions is 0.047 ms. Our measurements on 1 kbp DNA and λ-DNA show that such a slowing down of DNA translocation with our hybrid device is general. An additional feature of our hybrid device is its incorporation of all features of the conventional gel electrophoresis to separate different DNA sizes in a clump of DNAs and to streamline them in an orderly and slow manner into the nanopore. Our results suggest the high potential of our hydrogel-nanopore hybrid device in further advancing the single-molecule electrophoresis technology to accurately sequence very large biological polymers.

Technological development of multidimensional liquid chromatography-mass spectrometry in proteome research

Liquid chromatography-mass spectrometry (LC-MS) is the method of choice for high-throughput proteomic research. Limited by the peak capacity, the separation performance of conventional single-dimensional LC hampers the development of proteomics. Combining different separation modes orthogonally, multidimensional liquid chromatography (MDLC) with high peak capacity was developed to address this challenge. MDLC has evolved rapidly since its establishment, and the progress of proteomics has been greatly facilitated by the advent of novel MDLC-MS-based methods. In this paper, we will review the advances of MDLC-MS-based methodologies and technologies in proteomics studies, from different perspectives including novel application scenarios and proteomic targets, automation, miniaturization, and the improvement of the classic methods in recent years. In addition, attempts regarding new MDLC-MS models are also mentioned together with the outlook of MDLC-MS-based proteomics methods.

Amino acid sequence assignment from single molecule peptide sequencing data using a two-stage classifier

We present a machine learning-based interpretive framework (whatprot) for analyzing single molecule protein sequencing data produced by fluorosequencing, a recently developed proteomics technology that determines sparse amino acid sequences for many individual peptide molecules in a highly parallelized fashion. Whatprot uses Hidden Markov Models (HMMs) to represent the states of each peptide undergoing the various chemical processes during fluorosequencing, and applies these in a Bayesian classifier, in combination with pre-filtering by a k-Nearest Neighbors (kNN) classifier trained on large volumes of simulated fluorosequencing data. We have found that by combining the HMM based Bayesian classifier with the kNN pre-filter, we are able to retain the benefits of both, achieving both tractable runtimes and acceptable precision and recall for identifying peptides and their parent proteins from complex mixtures, outperforming the capabilities of either classifier on its own. Whatprot's hybrid kNN-HMM approach enables the efficient interpretation of fluorosequencing data using a full proteome reference database and should now also enable improved sequencing error rate estimates.

Mechanistic Study of the Conductance and Enhanced Single-Molecule Detection in a Polymer-Electrolyte Nanopore

Solid-state nanopores have been widely employed in the detection of biomolecules, but low signal-to-noise ratios still represent a major obstacle in the discrimination of nucleic acid and protein sequences substantially smaller than the nanopore diameter. The addition of 50% poly(ethylene) glycol (PEG) to the external solution is a simple way to enhance the detection of such biomolecules. Here, we demonstrate with finite-element modeling and experiments that the addition of PEG to the external solution introduces a strong imbalance in the transport properties of cations and anions, drastically affecting the current response of the nanopore. We further show that the strong asymmetric current response is due to a polarity-dependent ion distribution and transport at the nanopipette tip region, leading to either ion depletion or enrichment for few tens of nanometers across its aperture. We provide evidence that a combination of the decreased/increased diffusion coefficients of cations/anions in the bath outside the nanopore and the interaction between a translocating molecule and the nanopore-bath interface is responsible for the increase in the translocation signals. We expect this new mechanism to contribute to further developments in nanopore sensing by suggesting that tuning the diffusion coefficients of ions could enhance the sensitivity of the system.

First-passage time analysis of diffusion-controlled reactions in single-molecule detection

Single-molecule detection (SMD) aims to achieve the ultimate limit-of-detection (LOD) in biosensing. This method detects a countable number of targeted analyte molecules in solution, where the dynamics of molecule diffusion, capturing, identification and delivery greatly impact the SMD's efficiency and accuracy. In this study, we adopt the first-passage time method to investigate the diffusion-controlled reaction process in SMD. We analyze the influence of detection conditions on incubation time and the expected coefficient of variation (CV) under three SMD molecule capturing strategies, including solid-phase capturing (one-dimensional solid-liquid interface fixation), liquid-phase magnetic bead (MB) capturing, and liquid-phase direct fluorescence pair labeling. We find that inside a finite-sized reaction chamber, a finite average reaction time exists in all three capturing strategies, while the liquid-phase strategies are in general more efficient than the solid-phase approaches. CV can be estimated by averaging first-passage time solely in all three strategies, and the CV reduction is achievable given an extended reaction time. To further enable zeptomolar detection, extra treatments, such as adopting liquid-phase fluorescence pairs with high diffusion rates to label the molecule, or designing specific sensing devices with large effective sensing areas would be required. This framework provides solid theoretical support to guide the design of SMD sensing strategies and sensor structures to achieve desired measurement time and CV.

Single Molecule Protein Segments Sequencing by a Plasmonic Nanopore

Obtaining sequential and conformational information on proteins is vital to understand their functions. Although the nanopore-based electrical detection can sense single molecule (SM) protein and distinguish among different amino acids, this approach still faces difficulties in slowing down protein translocation and improving ionic current signal-to-noise ratio. Here, we observe the unfolding and multistep sequential translocation of SM cytochrome c (cyt c) through a surface enhanced Raman scattering (SERS) active conical gold nanopore. High bias voltage unfolds SM protein causing more exposure of amino acid residues to the nanopore, which slows down the protein translocation. Specific SERS traces of different SM cyt c segments are then recorded sequentially when they pass through the hotspot inside the gold nanopore. This study shows that the combination of SM SERS with a nanopore can provide a direct insight into protein segments and expedite the development of nanopore toward SM protein sequencing.

Multi-Stimuli-Responsive and Mechano-Actuated Biomimetic Membrane Nanopores Self-Assembled from DNA

In bioinspired design, biological templates are mimicked in structure and function by highly controllable synthetic means. Of interest are static barrel-like nanopores that enable molecular transport across membranes for use in biosensing, sequencing, and biotechnology. However, biological ion channels offer additional functions such as dynamic changes of the entire pore shape between open and closed states, and triggering of dynamic processes with biochemical and physical stimuli. To better capture this complexity, this report presents multi-stimuli and mechano-responsive biomimetic nanopores which are created with DNA nanotechnology. The nanopores switch between open and closed states, whereby specific binding of DNA and protein molecules as stimuli locks the pores in the open state. Furthermore, the physical stimulus of high transmembrane voltage switches the pores into a closed state. In addition, the pore diameters are larger and more tunable than those of natural templates. These multi-stimuli-responsive and mechanically actuated nanopores mimic several aspects of complex biological channels yet offer easier control over pore size, shape and stimulus response. The designer pores are expected to be applied in biosensing and synthetic biology.