Single-molecule spectroscopy of amino acids and peptides by recognition tunnelling

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.

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.

High-bandwidth low-current measurement system for automated and scalable probing of tunnel junctions in liquids

Tunnel junctions have long been used to immobilize and study the electronic transport properties of single molecules. The sensitivity of tunneling currents to entities in the tunneling gap has generated interest in developing electronic biosensors with single molecule resolution. Tunnel junctions can, for example, be used for sensing bound or unbound DNA, RNA, amino acids, and proteins in liquids. However, manufacturing technologies for on-chip integrated arrays of tunnel junction sensors are still in their infancy, and scalable measurement strategies that allow the measurement of large numbers of tunneling junctions are required to facilitate progress. Here, we describe an experimental setup to perform scalable, high-bandwidth (>10 kHz) measurements of low currents (pA-nA) in arrays of on-chip integrated tunnel junctions immersed in various liquid media. Leveraging a commercially available compact 100 kHz bandwidth low-current measurement instrument, we developed a custom two-terminal probe on which the amplifier is directly mounted to decrease parasitic probe capacitances to sub-pF levels. We also integrated a motorized three-axis stage, which could be powered down using software control, inside the Faraday cage of the setup. This enabled automated data acquisition on arrays of tunnel junctions without worsening the noise floor despite being inside the Faraday cage. A deliberately positioned air gap in the fluidic path ensured liquid perfusion to the chip from outside the Faraday cage without coupling in additional noise. We demonstrate the performance of our setup using rapid current switching observed in electromigrated gold tunnel junctions immersed in deionized water.

Amplifiable protein identification via residue-resolved barcoding and composition code counting

Ultrasensitive protein identification is of paramount importance in basic research and clinical diagnostics but remains extremely challenging. A key bottleneck in preventing single-molecule protein sequencing is that, unlike the revolutionary nucleic acid sequencing methods that rely on the polymerase chain reaction (PCR) to amplify DNA and RNA molecules, protein molecules cannot be directly amplified. Decoding the proteins via amplification of certain fingerprints rather than the intact protein sequence thus represents an appealing alternative choice to address this formidable challenge. Herein, we report a proof-of-concept method that relies on residue-resolved DNA barcoding and composition code counting for amplifiable protein fingerprinting (AmproCode). In AmproCode, selective types of residues on peptides or proteins are chemically labeled with a DNA barcode, which can be amplified and quantified via quantitative PCR. The operation generates a relative ratio as the residue-resolved 'composition code' for each target protein that can be utilized as the fingerprint to determine its identity from the proteome database. We developed a database searching algorithm and applied it to assess the coverage of the whole proteome and secretome via computational simulations, proving the theoretical feasibility of AmproCode. We then designed the residue-specific DNA barcoding and amplification workflow, and identified different synthetic model peptides found in the secretome at as low as the fmol/L level for demonstration. These results build the foundation for an unprecedented amplifiable protein fingerprinting method. We believe that, in the future, AmproCode could ultimately realize single-molecule amplifiable identification of trace complex samples without further purification, and it may open a new avenue in the development of next-generation protein sequencing techniques.

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.

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.

Unambiguous discrimination of all 20 proteinogenic amino acids and their modifications by nanopore

Natural proteins are composed of 20 proteinogenic amino acids and their post-translational modifications (PTMs). However, due to the lack of a suitable nanopore sensor that can simultaneously discriminate between all 20 amino acids and their PTMs, direct sequencing of protein with nanopores has not yet been realized. Here, we present an engineered hetero-octameric Mycobacterium smegmatis porin A (MspA) nanopore containing a sole Ni2+ modification. It enables full discrimination of all 20 proteinogenic amino acids and 4 representative modified amino acids, Nω,N'ω-dimethyl-arginine (Me-R), O-acetyl-threonine (Ac-T), N4-(β-N-acetyl-D-glucosaminyl)-asparagine (GlcNAc-N) and O-phosphoserine (P-S). Assisted by machine learning, an accuracy of 98.6% was achieved. Amino acid supplement tablets and peptidase-digested amino acids from peptides were also analyzed using this strategy. This capacity for simultaneous discrimination of all 20 proteinogenic amino acids and their PTMs suggests the potential to achieve protein sequencing using this nanopore-based strategy.

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.

Reduction of Biosensor False Responses and Time Delay Using Dynamic Response and Theory-Guided Machine Learning

Here, we provide a new methodology for reducing false results and time delay of biosensors, which are barriers to industrial, healthcare, military, and consumer applications. We show that integrating machine learning with domain knowledge in biosensing can complement and improve the biosensor accuracy and speed relative to the performance achieved by traditional regression analysis of a standard curve based on the biosensor steady-state response. The methodology was validated by rapid and accurate quantification of microRNA across the nanomolar to femtomolar range using the dynamic response of cantilever biosensors. Theory-guided feature engineering improved the performance and efficiency of several classification models relative to the performance achieved using traditional feature engineering methods (TSFRESH). In addition to the entire dynamic response, the technique enabled rapid and accurate quantification of the target analyte concentration and false-positive and false-negative results using the initial transient response, thereby reducing the required data acquisition time (i.e., time delay). We show that model explainability can be achieved by combining theory-guided feature engineering and feature importance analysis. The performance of multiple classifiers using both TSFRESH- and theory-based features from the biosensor's initial transient response was similar to that achieved using the entire dynamic response with data augmentation. We also show that the methodology can guide design of experiments for high-performance biosensing applications, specifically, the selection of data acquisition parameters (e.g., time) based on potential application-dependent performance thresholds. This work provides an example of the opportunities for improving biosensor performance, such as reducing biosensor false results and time delay, using explainable machine learning models supervised by domain knowledge in biosensing.

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.

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.

Identifying residues in unfolded whole proteins with a nanopore: a theoretical model based on linear inequalities

A theoretical model is proposed for the identification of individual amino acids (AAs) in an unfolded whole protein's primary sequence. It is based in part on a recent report (Nat. Biotech. 41, 1130-1139, 2023) that describes the unfolding and translocation of whole proteins at constant speed through a biological nanopore (alpha-Hemolysin) of length 5 nm with a residue dwell time inside the pore of ~10 μs. Here current blockade levels in the pore due to the translocating protein are assumed to be measured with a limited precision of 70 nm3 and a bandwidth of 20 KHz for measurement with a low-bandwidth detector. Exclusion volumes in two pores of slightly different lengths are used as a computational proxy for the blockade signal; subsequence exclusion volume differences along the protein sequence are computed from the sampled translocation signals in the two pores relatively shifted multiple times. These are then converted into a system of linear inequalities that can be solved with linear programming and related methods; residues are coarsely identified as belonging to one of 4 subsets of the 20 standard AAs. To obtain the exact identity of a residue an artifice analogous to the use of base-specific tags for DNA sequencing with a nanopore (PNAS 113, 5233-5238, 2016) is used. Conjugates that add volume are attached to a given AA type, this biases the set of inequalities toward the volume of the conjugated AA, from this biased set the position of occurrence of every residue of the AA type in the whole sequence is extracted. By applying this step separately to each of the 20 standard AAs the full sequence can be obtained. The procedure is illustrated with a protein in the human proteome (Uniprot id UP000005640_9606).

Single-molecular protein-based bioelectronics via electronic transport: fundamentals, devices and applications

Biomolecular electronics is a rapidly growing multidisciplinary field that combines biology, nanoscience, and engineering to bridge the two important fields of life sciences and molecular electronics. Proteins are remarkable for their ability to recognize molecules and transport electrons, making the integration of proteins into electronic devices a long sought-after goal and leading to the emergence of the field of protein-based bioelectronics, also known as proteotronics. This field seeks to design and create new biomolecular electronic platforms that allow for the understanding and manipulation of protein-mediated electronic charge transport and related functional applications. In recent decades, there have been numerous reports on protein-based bioelectronics using a variety of nano-gapped electrical devices and techniques at the single molecular level, which are not achievable with conventional ensemble approaches. This review focuses on recent advances in physical electron transport mechanisms, device fabrication methodologies, and various applications in protein-based bioelectronics. We discuss the most recent progress of the single or few protein-bridged electrical junction fabrication strategies, summarise the work on fundamental and functional applications of protein bioelectronics that enable high and dynamic electron transport, and highlight future perspectives and challenges that still need to be addressed. We believe that this specific review will stimulate the interdisciplinary research of topics related to protein-related bioelectronics, and open up new possibilities for single-molecule biophysics and biomedicine.

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.

Chemical Sensors using Single-Molecule Electrical Measurements

Driven by the digitization and informatization of contemporary society, electrical sensors are developing toward minimal structure, intelligent function, and high detection resolution. Single-molecule electrical measurement techniques have been proven to be capable of label-free molecular recognition and detection, which opens a new strategy for the design of efficient single-molecule detection sensors. In this review, we outline the main advances and potentials of single-molecule electronics for qualitative identification and recognition assays at the single-molecule level. Strategies for single-molecule electro-sensing and its main applications are reviewed, mainly in the detection of ions, small molecules, oligomers, genetic materials, and proteins. This review summarizes the remaining challenges in the current development of single-molecule electrical sensing and presents some potential perspectives for this field.

Direct biomolecule discrimination in mixed samples using nanogap-based single-molecule electrical measurement

In single-molecule measurements, metal nanogap electrodes directly measure the current of a single molecule. This technique has been actively investigated as a new detection method for a variety of samples. Machine learning has been applied to analyze signals derived from single molecules to improve the identification accuracy. However, conventional identification methods have drawbacks, such as the requirement of data to be measured for each target molecule and the electronic structure variation of the nanogap electrode. In this study, we report a technique for identifying molecules based on single-molecule measurement data measured only in mixed sample solutions. Compared with conventional methods that require training classifiers on measurement data from individual samples, our proposed method successfully predicts the mixing ratio from the measurement data in mixed solutions. This demonstrates the possibility of identifying single molecules using only data from mixed solutions, without prior training. This method is anticipated to be particularly useful for the analysis of biological samples in which chemical separation methods are not applicable, thereby increasing the potential for single-molecule measurements to be widely adopted as an analytical technique.

Molecular Electronics: Creating and Bridging Molecular Junctions and Promoting Its Commercialization

Molecular electronics is driven by the dream of expanding Moore's law to the molecular level for next-generation electronics through incorporating individual or ensemble molecules into electronic circuits. For nearly 50 years, numerous efforts have been made to explore the intrinsic properties of molecules and develop diverse fascinating molecular electronic devices with the desired functionalities. The flourishing of molecular electronics is inseparable from the development of various elegant methodologies for creating nanogap electrodes and bridging the nanogap with molecules. This review first focuses on the techniques for making lateral and vertical nanogap electrodes by breaking, narrowing, and fixed modes, and highlights their capabilities, applications, merits, and shortcomings. After summarizing the approaches of growing single molecules or molecular layers on the electrodes, the methods of constructing a complete molecular circuit are comprehensively grouped into three categories: 1) directly bridging one-molecule-electrode component with another electrode, 2) physically bridging two-molecule-electrode components, and 3) chemically bridging two-molecule-electrode components. Finally, the current state of molecular circuit integration and commercialization is discussed and perspectives are provided, hoping to encourage the community to accelerate the realization of fully scalable molecular electronics for a new era of integrated microsystems and applications.

MoS2 nanopore identifies single amino acids with sub-1 Dalton resolution

The sequencing of single protein molecules using nanopores is faced with a huge challenge due to the lack of resolution needed to resolve single amino acids. Here we report the direct experimental identification of single amino acids in nanopores. With atomically engineered regions of sensitivity comparable to the size of single amino acids, MoS₂ nanopores provide a sub-1 Dalton resolution for discriminating the chemical group difference of single amino acids, including recognizing the amino acid isomers. This ultra-confined nanopore system is further used to detect the phosphorylation of individual amino acids, demonstrating its capability for reading post-translational modifications. Our study suggests that a sub-nanometer engineered pore has the potential to be applied in future chemical recognition and de novo protein sequencing at the single-molecule level.

Advances in single-molecule junctions as tools for chemical and biochemical analysis

The development of miniaturized electronics has led to the design and construction of powerful experimental platforms capable of measuring electronic properties to the level of single molecules, along with new theoretical concepts to aid in the interpretation of the data. A new area of activity is now emerging concerned with repurposing the tools of molecular electronics for applications in chemical and biological analysis. Single-molecule junction techniques, such as the scanning tunnelling microscope break junction and related single-molecule circuit approaches have a remarkable capacity to transduce chemical information from individual molecules, sampled in real time, to electrical signals. In this Review, we discuss single-molecule junction approaches as emerging analytical tools for the chemical and biological sciences. We demonstrate how these analytical techniques are being extended to systems capable of probing chemical reaction mechanisms. We also examine how molecular junctions enable the detection of RNA, DNA, and traces of proteins in solution with limits of detection at the zeptomole level.

Graphene-molecule-graphene single-molecule junctions to detect electronic reactions at the molecular scale

The ability to measure the behavior of a single molecule during a reaction implies the detection of inherent dynamic and static disordered states, which may not be represented when measuring ensemble averages. Here, we describe the building of devices with graphene-molecule-graphene single-molecule junctions integrated into an electrical circuit. These devices are simple to build and are stable, showing tolerance to mechanical changes, solution environment and voltage stimulation. The design of a conductive channel based on a single molecule enables single-molecule detection and is sensitive to variations in physical properties and chemical structures of the detected molecules. The on-chip setup of single-molecule junctions further offers complementary metal-oxide-semiconductor (CMOS) compatibility, enabling logic functions in circuit elements, as well as deciphering of reaction intermediates. We detail the experimental procedure to prepare graphene transistor arrays as a basis for single-molecule junctions and the preparation of nanogapped carboxyl-terminal graphene electrodes by using electron-beam lithography and oxygen plasma etching. We describe the basic design of a molecular bridge with desired functions and terminals to form covalent bonds with electrode arrays, via a chemical reaction, to construct stably integrated single-molecule devices with a yield of 30-50% per chip. The immobilization of the single molecules is then characterized by using inelastic electron tunneling spectra, single-molecule imaging and fluorescent spectra. The whole protocol can be implemented within 2 weeks and requires users trained in using ultra-clean laboratory facilities and the aforementioned instrumentation.

Computational evaluation of transport parameters and logic circuit designing of L-Lysine amino acid stringed to Au, Ag, Cu, Pt, and Pd electrodes

The integrants of proteins, i.e., amino acids, have grossed exceptional recognition for their applications towards designing imminent switching devices. Among 20 amino acids, L-Lysine (i.e., positively charged) has the highest number of CH₂ chains, and such chains affect the rectification ratio in several biomolecules. Towards molecular rectification, we investigate the transport parameters of L-Lysine in conjunction with five different coinage metal electrodes, i.e., Au, Ag, Cu, Pt and Pd to form five distinct devices. We deputize the NEGF-DFT formulism for computing conductance, frontier molecular orbitals, current-voltage, and molecular projected self-Hamiltonian calculations using a self-consistent function. We focus on the most widely used electron exchange correlation combination, i.e., the PBE version of GGA with DZDP basis set. The molecular devices under inquisition exhibit phenomenal rectification ratios (RR) in conjunction with negative differential resistance (NDR) regimes. The nominated molecular device offers a substantial rectification ratio of 45.6 with platinum electrodes and a prominent peak to valley current ratio of 1.78 with copper electrodes. We deduce from these findings that L-Lysine based molecular devices would implicit in future bio-nanoelectronic devices. The OR and AND logic gates are also proposed hinged on highest rectification ratio of L-Lysine-based devices.

Single-exonuclease nanocircuits reveal the RNA degradation dynamics of PNPase and demonstrate potential for RNA sequencing

The degradation process of RNA is decisive in guaranteeing high-fidelity translation of genetic information in living organisms. However, visualizing the single-base degradation process in real time and deciphering the degradation mechanism at the single-enzyme level remain formidable challenges. Here, we present a reliable in-situ single-PNPase-molecule dynamic electrical detector based on silicon nanowire field-effect transistors with ultra-high temporal resolution. These devices are capable of realizing real-time and label-free monitoring of RNA analog degradation with single-base resolution, including RNA analog binding, single-nucleotide hydrolysis, and single-base movement. We discover a binding event of the enzyme (near the active site) with the nucleoside, offering a further understanding of the RNA degradation mechanism. Relying on systematic analyses of independent reads, approximately 80% accuracy in RNA nucleoside sequencing is achieved in a single testing process. This proof-of-concept sets up a Complementary Metal Oxide Semiconductor (CMOS)-compatible playground for the development of high-throughput detection technologies toward mechanistic exploration and single-molecule sequencing.

Quantitative Microscopic Observation of Base-Ligand Interactions via Hydrogen Bonds by Single-Molecule Counting

Chemical properties have been based on statistical averages since the introduction of Avogadro's number. The lack of suitable methods for counting identified single molecules has posed challenges to counting statistics. The selectivity, affinity, and mode of hydrogen bonding between base and small molecules that make up DNA, which is vital for living organisms, have not yet been revealed at the single molecule level. Here, we show the quantitation of the above-mentioned parameters via single-molecule counting based on the combination of single-molecule electrical measurements and AI. The binding selectivity values of five ligands to four different base molecules were evaluated quantitatively by determining the ratio of the number of aggregates in a solution mixture of base molecules and a ligand. In addition, we show the ligand dependence of the mode and number of microscopic hydrogen bonds via single-molecule counting and quantum chemical calculations.

Single-Molecule Peptide Identification Using Fluorescence Blinking Fingerprints

The ability to identify peptides with single-molecule sensitivity would lead to next-generation proteomics methods for basic research and clinical applications. Existing single-molecule peptide sequencing methods can read some amino acid sequences, but they are limited in their ability to distinguish between similar amino acids or post-translational modifications. Here, we demonstrate that the fluorescence intermittency of a peptide labeled with a spontaneously blinking fluorophore contains information about the structure of the peptide. Using a deep learning algorithm, this single-molecule blinking pattern can be used to identify the peptide. This method can distinguish between peptides with different sequences, peptides with the same sequence but different phosphorylation patterns, and even peptides that differ only by the presence of epimerized residues. This study builds the foundation for a targeted proteomics method with single-molecule sensitivity.

Functionalized electrodes embedded in nanopores: read-out enhancement?

In this review, functionalized nanogaps embedded in nanopores are discussed in view of their high biosensitivity in detecting biomolecules, their length, type, and sequence. Specific focus is given on nanoelectrodes functionalized with tiny nanometer-sized diamond-like particles offering vast functionalization possibilities for gold junction electrodes. This choice of the functionalization, in turn, offers nucleotide-specific binding possibilities improving the detection signals arising from such functionalized electrodes potentially embedded in a nanopore. The review sheds light onto the use and enhancement of the tunnelling recognition in functionalized nanogaps towards sensing DNA nucleotides and mutation detection, providing important input for a practical realization.

Artificial intelligence-based multi-omics analysis fuels cancer precision medicine

With biotechnological advancements, innovative omics technologies are constantly emerging that have enabled researchers to access multi-layer information from the genome, epigenome, transcriptome, proteome, metabolome, and more. A wealth of omics technologies, including bulk and single-cell omics approaches, have empowered to characterize different molecular layers at unprecedented scale and resolution, providing a holistic view of tumor behavior. Multi-omics analysis allows systematic interrogation of various molecular information at each biological layer while posing tricky challenges regarding how to extract valuable insights from the exponentially increasing amount of multi-omics data. Therefore, efficient algorithms are needed to reduce the dimensionality of the data while simultaneously dissecting the mysteries behind the complex biological processes of cancer. Artificial intelligence has demonstrated the ability to analyze complementary multi-modal data streams within the oncology realm. The coincident development of multi-omics technologies and artificial intelligence algorithms has fuelled the development of cancer precision medicine. Here, we present state-of-the-art omics technologies and outline a roadmap of multi-omics integration analysis using an artificial intelligence strategy. The advances made using artificial intelligence-based multi-omics approaches are described, especially concerning early cancer screening, diagnosis, response assessment, and prognosis prediction. Finally, we discuss the challenges faced in multi-omics analysis, along with tentative future trends in this field. With the increasing application of artificial intelligence in multi-omics analysis, we anticipate a shifting paradigm in precision medicine becoming driven by artificial intelligence-based multi-omics technologies.

A binary/digital approach to amino acid identification and its application to peptide sequencing and protein identification

A binary/digital method is proposed in theory for the identification of single amino acids (AAs) in the bulk or with a few molecules from a single binary measurement. Combined with Edman degradation (or other cleaving method), it can be used to sequence a peptide or identify the parent protein from a partial sequence. The approach is centered on the superspecificity property of transfer RNAs (tRNAs). Markedly different from conventional and recent single molecule (SM) sequencing methods based on analog measurements, it changes the analytical question 'Which AA is it?' to the much simpler one 'Is there an AA in the detection space?'. Each of 20 terminal residues cleaved from 20 copies of a peptide enters a different cavity with a unique tRNA; tRNA charging (or binding with AA) occurs only in the cavity with the cognate AA. The bound AA or the AA separated from the tRNA is detected with a single binary measurement; its identity is known from the position of the single high bit in the resulting 20-bit output. Alternatively, a 20-stage pipeline can be used with sparse samples. Detection of the bound AA can be done optically by tagging the AAs with a fluorescent dye, or of the freed AA electrically with a nanopore. Necessary conditions for accurate AA identification are satisfied in principle; related computations and simulation results are presented. A modified version that can be used for de novo sequencing in parallel of large numbers of peptides immobilized on a glass slide with the tRNAs carrying a fluorescent tag is also proposed. Both methods can be used for protein identification from partial sequences containing 2 or 3 AA types by using only the corresponding tRNAs. Experiments may be performed to validate them, followed by translation into practice with existing technology; potential implementation issues are discussed. Binary/digital amino acid identification for peptide sequencing.

Selective Detection and Characterization of Small Cysteine-Containing Peptides with Cluster-Modified Nanopore Sensing

It was recently demonstrated that one can monitor ligand-induced structure fluctuations of individual thiolate-capped gold nanoclusters using resistive-pulse nanopore sensing. The magnitude of the fluctuations scales with the size of the capping ligand, and it was later shown one can observe ligand exchange in this nanopore setup. We expand on these results by exploring the different types of current fluctuations associated with peptide ligands attaching to tiopronin-capped gold nanoclusters. We show here that the fluctuations can be used to identify the attaching peptide through either the magnitude of the peptide-induced current jumps or the onset of high-frequency current fluctuations. Importantly, the peptide attachment process requires that the peptide contains a cysteine residue. This suggests that nanopore-based monitoring of peptide attachments with thiolate-capped clusters could provide a means for selective detection of cysteine-containing peptides. Finally, we demonstrate the cluster-based protocol with various peptide mixtures to show that one can identify more than one cysteine-containing peptide in a mixture.

A Critical Review on the Sensing, Control, and Manipulation of Single Molecules on Optofluidic Devices

Single-molecule techniques have shifted the paradigm of biological measurements from ensemble measurements to probing individual molecules and propelled a rapid revolution in related fields. Compared to ensemble measurements of biomolecules, single-molecule techniques provide a breadth of information with a high spatial and temporal resolution at the molecular level. Usually, optical and electrical methods are two commonly employed methods for probing single molecules, and some platforms even offer the integration of these two methods such as optofluidics. The recent spark in technological advancement and the tremendous leap in fabrication techniques, microfluidics, and integrated optofluidics are paving the way toward low cost, chip-scale, portable, and point-of-care diagnostic and single-molecule analysis tools. This review provides the fundamentals and overview of commonly employed single-molecule methods including optical methods, electrical methods, force-based methods, combinatorial integrated methods, etc. In most single-molecule experiments, the ability to manipulate and exercise precise control over individual molecules plays a vital role, which sometimes defines the capabilities and limits of the operation. This review discusses different manipulation techniques including sorting and trapping individual particles. An insight into the control of single molecules is provided that mainly discusses the recent development of electrical control over single molecules. Overall, this review is designed to provide the fundamentals and recent advancements in different single-molecule techniques and their applications, with a special focus on the detection, manipulation, and control of single molecules on chip-scale devices.

Sub-5 nm nanogap electrodes towards single-molecular biosensing

Nanogap electrodes (NGEs) with sub-5 nm gap has been widely used in single-molecule sensing and sequencing, with the characteristics of label-free, high sensitivity, rapid detection and low-cost. However, the fabrication of sub-5 nm gap electrodes with high controllability and reproducibility still remains a great challenge that impedes the experimental research and the commercialization of the nanogap device. Here, we review the common currently used fabrication methods of nanogap electrodes, such as gap narrowing deposition, mechanical controllable break junctions and the fabrication methods combined with nanopore or nanochannel. We then highlight the typical applications of nanogap electrodes in biological/chemical sensing fields, including single molecule recognition, single molecule sequencing and chemical kinetics analysis. Finally, the challenges of nanogap electrodes in single molecule sensing/sequencing are outlined and the future directions for sensing perspectives are suggested.

Protein Sequencing, One Molecule at a Time

Despite tremendous gains over the past decade, methods for characterizing proteins have generally lagged behind those for nucleic acids, which are characterized by extremely high sensitivity, dynamic range, and throughput. However, the ability to directly characterize proteins at nucleic acid levels would address critical biological challenges such as more sensitive medical diagnostics, deeper protein quantification, large-scale measurement, and discovery of alternate protein isoforms and modifications and would open new paths to single-cell proteomics. In response to this need, there has been a push to radically improve protein sequencing technologies by taking inspiration from high-throughput nucleic acid sequencing, with a particular focus on developing practical methods for single-molecule protein sequencing (SMPS). SMPS technologies fall generally into three categories: sequencing by degradation (e.g., mass spectrometry or fluorosequencing), sequencing by transit (e.g., nanopores or quantum tunneling), and sequencing by affinity (as in DNA hybridization-based approaches). We describe these diverse approaches, which range from those that are already experimentally well-supported to the merely speculative, in this nascent field striving to reformulate proteomics.

Distinguishing between Similar Miniproteins with Single-Molecule Nanopore Sensing: A Computational Study

A nanopore is a tool in single-molecule sensing biotechnology that offers label-free identification with high throughput. Nanopores have been successfully applied to sequence DNA and show potential in the study of proteins. Nevertheless, the task remains challenging due to the large variability in size, charges, and folds of proteins. Miniproteins have a small number of residues, limited secondary structure, and stable tertiary structure, which can offer a systematic way to reduce complexity. In this computational work, we theoretically evaluated sensing two miniproteins found in the human body using a silicon nitride nanopore. We employed molecular dynamics methods to compute occupied-pore ionic current magnitudes and electronic structure calculations to obtain interaction strengths between pore wall and miniprotein. From the interaction strength, we derived dwell times using a mix of combinatorics and numerical solutions. This latter approach circumvents typical computational demands needed to simulate translocation events using molecular dynamics. We focused on two miniproteins potentially difficult to distinguish owing to their isotropic geometry, similar number of residues, and overall comparable structure. We found that the occupied-pore current magnitudes not to vary significantly, but their dwell times differ by 1 order of magnitude. Together, these results suggest a successful identification protocol for similar miniproteins.

Single-Molecule Classification of Aspartic Acid and Leucine by Molecular Recognition through Hydrogen Bonding and Time-Series Analysis

Amino acid detection/identification methods are important for understanding biological systems. In this study, we developed the single-molecule measurement for investigated quantum tunneling enhancement by chemical modification and machine learning based time series analysis for develop accurate amino acid discrimination. We performed single-molecule measurement of L-aspartic Acid (Asp) and L-leucine (Leu) with mercaptoacetic acid (MAA) chemical modified nano-gap. The measured current was investigated by machine learning based time series analysis method for accurate amino acid discrimination. Compared to measurements using bare nano-gap, it is found that MAA modification improves the difference in the conductance-time profiles between Asp and Leu through the hydrogen bonding facilitated tunneling phenomena. It is also found that this method enables determination of relative concentration. even in the mixture of Asp and Leu. It improves selective analysis for amino acids, and therefore would be applicable in medicine, diagnosis, and single-molecule peptide sequencing.

Cataloguing the proteome: Current developments in single-molecule protein sequencing

The cellular proteome is complex and dynamic, with proteins playing a critical role in cell-level biological processes that contribute to homeostasis, stimuli response, and disease pathology, among others. As such, protein analysis and characterization are of extreme importance in both research and clinical settings. In the last few decades, most proteomics analysis has relied on mass spectrometry, affinity reagents, or some combination thereof. However, these techniques are limited by their requirements for large sample amounts, low resolution, and insufficient dynamic range, making them largely insufficient for the characterization of proteins in low-abundance or single-cell proteomic analysis. Despite unique technical challenges, several single-molecule protein sequencing (SMPS) technologies have been proposed in recent years to address these issues. In this review, we outline several approaches to SMPS technologies and discuss their advantages, limitations, and potential contributions toward an accurate, sensitive, and high-throughput platform.

Nanopore-Based Protein Identification

The implementation of a reliable, rapid, inexpensive, and simple method for whole-proteome identification would greatly benefit cell biology research and clinical medicine. Proteins are currently identified by cleaving them with proteases, detecting the polypeptide fragments with mass spectrometry, and mapping the latter to sequences in genomic/proteomic databases. Here, we demonstrate that the polypeptide fragments can instead be detected and classified at the single-molecule limit using a nanometer-scale pore formed by the protein aerolysin. Specifically, three different water-soluble proteins treated with the same protease, trypsin, produce different polypeptide fragments defined by the degree by which the latter reduce the nanopore's ionic current. The fragments identified with the aerolysin nanopore are consistent with the predicted fragments that trypsin could produce.

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

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

Single-molecule mechanical fingerprinting with DNA nanoswitch calipers

Decoding the identity of biomolecules from trace samples is a longstanding goal in the field of biotechnology. Advances in DNA analysis have substantially affected clinical practice and basic research, but corresponding developments for proteins face challenges due to their relative complexity and our inability to amplify them. Despite progress in methods such as mass spectrometry and mass cytometry, single-molecule protein identification remains a highly challenging objective. Towards this end, we combine DNA nanotechnology with single-molecule force spectroscopy to create a mechanically reconfigurable DNA nanoswitch caliper capable of measuring multiple coordinates on single biomolecules with atomic resolution. Using optical tweezers, we demonstrate absolute distance measurements with ångström-level precision for both DNA and peptides, and using multiplexed magnetic tweezers, we demonstrate quantification of relative abundance in mixed samples. Measuring distances between DNA-labelled residues, we perform single-molecule fingerprinting of synthetic and natural peptides, and show discrimination, within a heterogeneous population, between different posttranslational modifications. DNA nanoswitch calipers are a powerful and accessible tool for characterizing distances within nanoscale complexes that will enable new applications in fields such as single-molecule proteomics.

Molecular electronics behaviour of L-aspartic acid using symmetrical metal electrodes

Protein-based electronics is one of the growing areas of bio-nanoelectronics, where novel electronic devices possessing distinctive properties are being fabricated using specific proteins. Furthermore, if the bio-molecule is analysed amidst different electrodes, intriguing properties are elucidated. This research article investigates the electron transport properties of L-aspartic acid (i.e. L-amino acid) bound to symmetrical electrodes of gold, silver, copper, platinum and palladium employing NEGF-DFT approach using self-consistent function. The theoretical work function of different electrodes is calculated using local density approximation and generalized gradient approximation approach. The calculated work function correlates well with the hole tunneling barrier and conductance of the molecular device, which further authenticate the coupling strength between molecule and electrode. Molecule under consideration also exhibits negative differential resistance region and rectification ratio with all the different electrodes, due to its asymmetrical structure. The molecular device using platinum electrodes exhibits the highest peak to valley ratio of 1.38 and rectification ratio of 3.20, at finite bias. The switching characteristics of different molecular device are justified with detailed transmission spectra and MPSH. These results indicate that L-aspartic acid and similar biomolecule can be vital to the growth of Proteotronics.

A Guide to Signal Processing Algorithms for Nanopore Sensors

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

Herding cats: Label-based approaches in protein translocation through nanopore sensors for single-molecule protein sequence analysis

Proteins carry out life's essential functions. Comprehensive proteome analysis technologies are thus required for a full understanding of the operating principles of biological systems. While current proteomics techniques suffer from limitations in sensitivity and/or throughput, nanopore technology has the potential to enable de novo protein identification through single-molecule sequencing. However, a significant barrier to achieving this goal is controlling protein/peptide translocation through the nanopore sensor for processive strand analysis. Here, we review recent approaches that use a range of techniques, from oligonucleotide conjugation to molecular motors, aimed at driving protein strands and peptides through protein nanopores. We further discuss site-specific protein conjugation chemistry that could be combined with these translocation approaches as future directions to achieve single-molecule protein detection and sequencing of native proteins.

Enhanced identification of Tau acetylation and phosphorylation with an engineered aerolysin nanopore

Posttranslational modifications (PTMs) affect protein function/dysfunction, playing important roles in the occurrence and development of tauopathies including Alzheimer's disease. PTM detection is significant and still challenging due to the requirements of high sensitivity to identify the subtle structural differences between modifications. Herein, in terms of the unique geometry of the aerolysin (AeL) nanopore, we elaborately engineered a T232K AeL nanopore to detect the acetylation and phosphorylation of Tau segment (Pep). By replacing neutral threonine (T) with positively charged lysine (K) at the 232 sites, the T232K and K238 rings of this engineered T232K AeL nanopore corporately work together to enhance electrostatic trapping of the acetylated and phosphorylated Tau peptides. Translocation speed of the monophosphorylated Pep-P was decelerated by up to 46 folds compared to the wild-type (WT) AeL nanopore. The prolonged residences within the T232K AeL nanopore enabled to simultaneously identify the monoacetylated Pep-Ac, monophosphorylated Pep-P, di-modified Pep-P-Ac and non-modified Pep. The tremendous potential is demonstrated for PTM sensing by manipulating non-covalent interactions between nanopores and single analytes.

Single Molecule Ratcheting Motion of Peptides in a Mycobacterium smegmatis Porin A (MspA) Nanopore

Diverse functions of proteins, including synthesis, catalysis, and signaling, result from their highly variable amino acid sequences. The technology allowing for direct analysis of protein sequences, however, is still unsatisfactory. Recent developments of nanopore sequencing of DNA or RNA have motivated attempts to realize nanopore sequencing of peptides in a similar manner. The core challenge has been to achieve a controlled ratcheting motion of the target peptide, which is currently restricted to a limited choice of compatible enzymes. By constructing peptide-oligonucleotide conjugates (POCs) and measurements with nanopore-induced phase-shift sequencing (NIPSS), direct observation of the ratcheting motion of peptides has been successfully achieved. The generated events show a clear sequence dependence on the peptide that is being tested. The method is compatible with peptides with either a conjugated N- or C-terminus. The demonstrated results suggest a proof of concept of nanopore sequencing of peptide and can be useful for peptide fingerprinting.

The emerging landscape of single-molecule protein sequencing technologies

Single-cell profiling methods have had a profound impact on the understanding of cellular heterogeneity. While genomes and transcriptomes can be explored at the single-cell level, single-cell profiling of proteomes is not yet established. Here we describe new single-molecule protein sequencing and identification technologies alongside innovations in mass spectrometry that will eventually enable broad sequence coverage in single-cell profiling. These technologies will in turn facilitate biological discovery and open new avenues for ultrasensitive disease diagnostics.

The Characterization of Electronic Noise in the Charge Transport through Single-Molecule Junctions

With the goal of creating single-molecule devices and integrating them into circuits, the emergence of single-molecule electronics provides various techniques for the fabrication of single-molecule junctions and the investigation of charge transport through such junctions. Among the techniques for characterization of charge transport through molecular junctions, electronic noise characterization is an effective strategy with which issues from molecule-electrode interfaces, mechanisms of charge transport, and changes in junction configurations are studied. Electronic noise analysis in single-molecule junctions can be used to identify molecular conformations and even monitor reaction kinetics. This review summarizes the various types of electronic noise that have been characterized during single-molecule electrical detection, including the functions of random telegraph signal (RTS) noise, flicker noise, shot noise, and their corresponding applications, which provide some guidelines for the future application of these techniques to problems of charge transport through single-molecule junctions.

Micro-scale technologies propel biology and medicine

Historically, technology has been central to new discoveries in biology and progress in medicine. Among various technologies, microtechnologies, in particular, have had a prominent role in the revolution experienced by the life sciences in the last few decades, which will surely continue in the years to come. In this Perspective, we illustrate how microtechnologies, with a focus on microfluidics, have evolved in trends/waves to tackle the boundary of knowledge in the life sciences. We provide illustrative examples of technology-enabled biological breakthroughs and their current and future use in clinics. Finally, we take a closer look at the translational process to understand why the incorporation of new micro-scale technologies in medicine has been comparatively slow so far.

A single-molecule electrical approach for amino acid detection and chirality recognition

One of the ultimate goals of analytic chemistry is to efficiently discriminate between amino acids. Here we demonstrate this ability using a single-molecule electrical methodology based on molecular nanocircuits formed from stable graphene-molecule-graphene single-molecule junctions. These molecular junctions are fabricated by covalently bonding a molecular machine featuring a permethylated-β-cyclodextrin between a pair of graphene point contacts. Using pH to vary the type and charge of the amino acids, we find distinct multimodal current fluctuations originating from the different host-guest interactions, consistent with theoretical calculations. These conductance data produce characteristic dwell times and shuttling rates for each amino acid, and allow accurate, statistical real-time, in situ measurements. Testing four amino acids and their enantiomers shows the ability to distinguish between them within a few microseconds, thus paving a facile and precise way to amino acid identification and even single-molecule protein sequencing.