Single-molecule peptide fingerprinting

After 75 Years, an Alternative to Edman Degradation: A Mechanistic and Efficiency Study of a Base-Induced Method for N-Terminal Peptide Sequencing

The sequencing of peptides via N-terminal amino acid removal is a classic reaction termed Edman degradation. This method involves repeated treatment of the N-terminal amino group of a peptide with phenyl isothiocyanate (PITC), followed by treatment with trifluoroacetic acid. Spurred by the need for an alternative non-acid-based chemistry for next-generation protein sequencing technologies, we developed a base-induced N-terminal degradation method. Several N-terminal derivatization reagents carrying supernucleophiles were tested. After rounds of iterative designs, compound DR3, with a N-hydroxysuccinimide as a leaving group and hydrazinecarboxamide as the supernucleophile, demonstrated the highest yield for the peptide derivatization step and the most efficient elimination of the N-terminal amino acid in just 1% of a hydroxide salt. The method successfully removed all 20 amino acids at the N-terminus in high yield. The technique demonstrates compatibility with oligonucleic acids, which differs from Edman degradation due to their inherent sensitivity to acidic environments. To demonstrate the practical application of our approach, we sequenced amino acids sequentially from a peptide, effectively determining the sequence of an unknown peptide. Notably, our methodology was successfully applied to mixtures of peptides derived from protein samples, where a significant fraction of the peptides derivatized with DR3 underwent elimination of their N-terminal amino acid upon addition of base. Overall, although our method does not outperform Edman degradation in efficiency, it serves as a valuable alternative in cases where base-induced cleavage is advantageous, particularly for preserving acid-sensitive functionalities.

Ischemic preconditioning attenuates ischemia/reperfusion-induced acute kidney injury dependent on mitochondrial protease CLPP

Ischemic preconditioning (IPC) is a phenomenon in which brief periods of ischemia trigger protective mechanisms that alleviate subsequent ischemia-reperfusion injury (IRI), although the precise protective mechanism remains unclear. This study investigated the mechanism by which IPC protects acute kidney injury (AKI) induced by renal IRI. We found that IPC for 10 min significantly ameliorated IRI-induced AKI, whereas IPC for 5 or 15 min did not have any protective effects. Renal ischemia increased the expression of caseinolytic protease P (CLPP) in tubular epithelial cells. The peak effect was reached after 10 min of renal ischemia, during which no mitochondrial deposition of misfolded/unfolded proteins or signs of AKI were evident. However, after 15 min of renal ischemia, there was no further increase in CLPP levels, which was accompanied by mitochondrial deposition of misfolded/unfolded proteins and signs of AKI. The increase in CLPP levels suggests potential activation of the mitochondrial unfolded protein response (UPRmt), which is a cellular stress response pathway that regulates the expression of mitochondrial chaperones and proteases to maintain protein homeostasis within the mitochondria. Knockdown of Clpp led to the aggregation of mitochondrial unfolded/misfolded proteins and phosphorylation of eukaryotic translation initiation factor 2α (eIF2α), which indicated integrated stress response (ISR) activation. Clpp knockdown in mice antagonized the protective effects induced by IPC for 10 min during renal IRI. Furthermore, the inhibition of ISR activation by an ISR inhibitor (ISRIB) may also impede the protective effects of IPC for 10 min. This study indicates that IPC can ameliorate renal IRI injury and that its effect is dependent on CLPP.

Towards Next Generation Protein Sequencing

Understanding the structure and function of proteins is a critical objective in the life sciences. Protein sequencing, a central aspect of this endeavor, was first accomplished through Edman degradation in the 1950s. Since the late 20th century, mass spectrometry has emerged as a prominent method for protein sequencing. In recent years, single-molecule technologies have increasingly been applied to this field, yielding numerous innovative results. Among these, nanopore sensing has proven to be a reliable single-molecule technology, enabling advancements in amino acid recognition, short peptide differentiation, and peptide sequence reading. These developments are set to elevate protein sequencing technology to new heights. The next generation of protein sequencing technologies is anticipated to revolutionize our understanding of molecular mechanisms in biological processes and significantly enhance clinical diagnostics and treatments.

Slowing Down Peptide Translocation through MoSi2N4 Nanopores for Protein Sequencing

Precise identification and quantification of amino acids are crucial for numerous biological applications. A significant challenge in the development of high-throughput, cost-effective nanopore protein sequencing technology is the rapid translocation of protein through the nanopore, which hinders accurate sequencing. In this study, we explore the potential of nanopore constructed from a novel two-dimensional (2D) material MoSi2N4 in decelerating the velocity of protein translocation using molecular dynamics simulations. The translocation velocity of the peptide through the MoSi2N4 nanopore can be reduced by nearly an order of magnitude compared to the MoS2 nanopore. Systematic analysis reveals that this reduction is due to stronger interaction between the peptide and MoSi2N4 membrane surface, particularly for aromatic residues, as they contain aromatic rings composed of relatively nonpolar C-C and C-H bonds. By adjusting the proportion of aromatic residues in peptides, further control over peptide translocation velocity can be achieved. Additionally, the system validates the feasibility of using an appropriate nanopore diameter for protein sequencing. The theoretical investigations presented herein suggest a potential method for manipulating protein translocation kinetics, promising more effective and economical advancements in nanopore protein sequencing technology.

Emerging protein sequencing technologies: proteomics without mass spectrometry?

INTRODUCTION

Liquid chromatography-tandem mass spectrometry (LC-MS/MS) has been a leading method for proteomics for 30 years. Advantages provided by LC-MS/MS are offset by significant disadvantages, including cost. Recently, several non-mass spectrometric methods have emerged, but little information is available about their capacity to analyze the complex mixtures routine for mass spectrometry.

AREAS COVERED

We review recent non-mass-spectrometric methods for sequencing proteins and peptides, including those using nanopores, sequencing by degradation, reverse translation, and short-epitope mapping, with comments on bioinformatics challenges, fundamental limitations, and areas where new technologies will be more or less competitive with LC-MS/MS. In addition to conventional literature searches, instrument vendor websites, patents, webinars, and preprints were also consulted to give a more up-to-date picture.

EXPERT OPINION

Many new technologies are promising. However, demonstrations that they outperform mass spectrometry in terms of peptides and proteins identified have not yet been published, and astute observers note important disadvantages, especially relating to the dynamic range of single-molecule measurements of complex mixtures. Still, even if the performance of emerging methods proves inferior to LC-MS/MS, their low cost could create a different kind of revolution: a dramatic increase in the number of biology laboratories engaging in new forms of proteomics research.

Nanofluidic Lab-On-A-Chip Systems for Biosensing in Healthcare

Biosensing plays a vital role in healthcare monitoring, disease detection, and treatment planning. In recent years, nanofluidic technology has been increasingly explored to be developed into lab-on-a-chip biosensing systems. Given now the possibility of fabricating geometrically defined nanometric channels that are commensurate with the size of many biomolecules, nanofluidic-based devices are likely to become a key technology for the analysis of various clinical biomarkers, including DNA (deoxyribonucleic acid) and proteins in liquid biopsies. This review summarizes the fundamentals and technological advances of nanofluidics from the purview of single-molecule analysis, detection of low-abundance molecules, and single-cell analysis at the subcellular level. The extreme confinement and dominant surface charge effects in nanochannels provide unique advantages to nanofluidic devices for the manipulation and transport of target biomarkers. When coupled to a microfluidic network to facilitate sample introduction, integrated micro-nanofluidic biosensing devices are proving to be more sensitive and specific in molecular analysis compared to conventional assays in many cases. Based on recent progress in nanofluidics and current clinical trends, the review concludes with a discussion of near-term challenges and future directions for the development of nanofluidic-based biosensing systems toward enabling a new wave of lab-on-a-chip technology for personalized and preventive medicine.

A generalized protein identification method for novel and diverse sequencing technologies

Protein sequencing is a rapidly evolving field with much progress towards the realization of a new generation of protein sequencers. The early devices, however, may not be able to reliably discriminate all 20 amino acids, resulting in a partial, noisy and possibly error-prone signature of a protein. Rather than achieving de novo sequencing, these devices may aim to identify target proteins by comparing such signatures to databases of known proteins. However, there are no broadly applicable methods for this identification problem. Here, we devise a hidden Markov model method to study the generalized problem of protein identification from noisy signature data. Based on a hypothetical sequencing device that can simulate several novel technologies, we show that on the human protein database (N = 20 181) our method has a good performance under many different operating conditions such as various levels of signal resolvability, different numbers of discriminated amino acids, sequence fragments, and insertion and deletion error rates. Our results demonstrate the possibility of protein identification with high accuracy on many early experimental devices. We anticipate our method to be applicable for a wide range of protein sequencing devices in the future.

Exploring the unmapped cysteine redox proteoform landscape

Cysteine redox proteoforms define the diverse molecular states that proteins with cysteine residues can adopt. A protein with one cysteine residue must adopt one of two binary proteoforms: reduced or oxidized. Their numbers scale: a protein with 10 cysteine residues must assume one of 1,024 proteoforms. Although they play pivotal biological roles, the vast cysteine redox proteoform landscape comprising vast numbers of theoretical proteoforms remains largely uncharted. Progress is hampered by a general underappreciation of cysteine redox proteoforms, their intricate complexity, and the formidable challenges that they pose to existing methods. The present review advances cysteine redox proteoform theory, scrutinizes methodological barriers, and elaborates innovative technologies for detecting unique residue-defined cysteine redox proteoforms. For example, chemistry-enabled hybrid approaches combining the strengths of top-down mass spectrometry (TD-MS) and bottom-up mass spectrometry (BU-MS) for systematically cataloguing cysteine redox proteoforms are delineated. These methods provide the technological means to map uncharted redox terrain. To unravel hidden redox regulatory mechanisms, discover new biomarkers, and pinpoint therapeutic targets by mining the theoretical cysteine redox proteoform space, a community-wide initiative termed the "Human Cysteine Redox Proteoform Project" is proposed. Exploring the cysteine redox proteoform landscape could transform current understanding of redox biology.

Multi-pass, single-molecule nanopore reading of long protein strands

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 goal1,2. Here, we establish a method for the 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 nanopore3,4, we provide single-molecule evidence that ClpX translocates substrates in two-residue steps. This mechanism achieves sensitivity to single amino acids on synthetic protein strands hundreds of amino acids in length, enabling the sequencing of combinations of single-amino-acid substitutions and the mapping of post-translational modifications, such as phosphorylation. To enhance classification accuracy further, we demonstrate the ability to reread individual protein molecules multiple times, and we explore the potential for highly accurate protein barcode sequencing. Furthermore, we develop a biophysical model that can simulate raw nanopore signals a priori on the basis of residue volume and charge, enhancing the interpretation of raw signal data. Finally, we apply these methods to examine full-length, 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.

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.

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.

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.

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.

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.

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.

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.

E. coli outer membrane protein T (OmpT) nanopore for peptide sensing

Peptide detection methods with facility and high sensitivity are essential for diagnosing disease associated with peptide biomarkers. Nanopore sensing technology had emerged as a low cost, high-throughput, and scalable tool for peptide detection. The omptins family proteins which can form β-barrel pores have great potentials to be developed as nanopore biosensor. However, there are no study about the channel properties of E. coli OmpT and the development of OmpT as a nanopore biosensor. In this study, the OmpT biological nanopore channel was constructed with a conductance of 1.49 nS in 500 mM NaCl buffer and a three-step gating phenomenon under negative voltage higher than 100 mV and then was developed as a peptide biosensor which can detect peptide without the interfere of ssDNA and dNTPs. The OmpT constructed in this study has potential application in peptide detection, and also provides a new idea for the detection of peptides using the specific binding ability of protease.

Recent methodological advances towards single-cell proteomics

Studying the central dogma at the single-cell level has gained increasing attention to reveal hidden cell lineages and functions that cannot be studied using traditional bulk analyses. Nonetheless, most single-cell studies exploiting genomic and transcriptomic levels fail to address information on proteins that are central to many important biological processes. Single-cell proteomics enables understanding of the functional status of individual cells and is particularly crucial when the specimen is composed of heterogeneous entities of cells. With the growing importance of this field, significant methodological advancements have emerged recently. These include miniaturized and automated sample preparation, multi-omics analyses, and combined analyses of multiple techniques such as mass spectrometry and microscopy. Moreover, artificial intelligence and single-molecule detection technologies have advanced throughput and improved sensitivity limitations, respectively, over conventional methods. In this review, we summarize cutting-edge methodologies for single-cell proteomics and relevant emerging technologies that have been reported in the last 5 years, and provide an outlook on this research field.

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.

Trends in Single-Molecule Total Internal Reflection Fluorescence Imaging and Their Biological Applications with Lab-on-a-Chip Technology

Single-molecule imaging technologies, especially those based on fluorescence, have been developed to probe both the equilibrium and dynamic properties of biomolecules at the single-molecular and quantitative levels. In this review, we provide an overview of the state-of-the-art advancements in single-molecule fluorescence imaging techniques. We systematically explore the advanced implementations of in vitro single-molecule imaging techniques using total internal reflection fluorescence (TIRF) microscopy, which is widely accessible. This includes discussions on sample preparation, passivation techniques, data collection and analysis, and biological applications. Furthermore, we delve into the compatibility of microfluidic technology for single-molecule fluorescence imaging, highlighting its potential benefits and challenges. Finally, we summarize the current challenges and prospects of fluorescence-based single-molecule imaging techniques, paving the way for further advancements in this rapidly evolving field.

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.

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.

Mitochondrial quality control proteases and their modulation for cancer therapy

Mitochondria, the main provider of energy in eukaryotic cells, contains more than 1000 different proteins and is closely related to the development of cells. However, damaged proteins impair mitochondrial function, further contributing to several human diseases. Evidence shows mitochondrial proteases are critically important for protein maintenance. Most importantly, quality control enzymes exert a crucial role in the modulation of mitochondrial functions by degrading misfolded, aged, or superfluous proteins. Interestingly, cancer cells thrive under stress conditions that damage proteins, so targeting mitochondrial quality control proteases serves as a novel regulator for cancer cells. Not only that, mitochondrial quality control proteases have been shown to affect mitochondrial dynamics by regulating the morphology of optic atrophy 1 (OPA1), which is closely related to the occurrence and progression of cancer. In this review, we introduce mitochondrial quality control proteases as promising targets and related modulators in cancer therapy with a focus on caseinolytic protease P (ClpP), Lon protease (LonP1), high-temperature requirement protein A2 (HrtA2), and OMA-1. Further, we summarize our current knowledge of the advances in clinical trials for modulators of mitochondrial quality control proteases. Overall, the content proposed above serves to suggest directions for the development of novel antitumor drugs.

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.

Phosphonium-Based Ionic Liquid Significantly Enhances SERS of Cytochrome c on TiO2 Nanotube Arrays

Surface-enhanced Raman scattering (SERS) is an attractive technique for studying trace detection. It is of utmost importance to further improve the performance and understand the underlying mechanisms. An ionic liquid (IL), the anion of which is derived from biomass, [P6,6,6,14][FuA] was synthesized and used as a trace additive to improve the SERS performance of cytochrome c (Cyt c) on TiO2 nanotube arrays (TNAs). An increased and better enhancement factor (EF) by four to five times as compared to the system without an IL was obtained, which is better than that from using the choline-based amino acid IL previously reported by us. Dissociation of the ILs improved the ionic conductivity of the system, and the long hydrophobic tails of the [P6,6,6,14]+ cation contributed to a strong electrostatic interaction between Cyt c and the TNA surface, thereby enhancing the SERS performance. Atomic force microscopy did verify strong electrostatic interactions between the Cyt c molecules and TNAs after the addition of the IL. This work demonstrates the importance of introducing the phosphonium-based IL to enhance the SERS performance, which will stimulate further development of more effective ILs on SERS detection and other relevant applications in biology.

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.

Label-Free Optical Analysis of Biomolecules in Solid-State Nanopores: Toward Single-Molecule Protein Sequencing

Sequence identification of peptides and proteins is central to proteomics. Protein sequencing is mainly conducted by insensitive mass spectroscopy because proteins cannot be amplified, which hampers applications such as single-cell proteomics and precision medicine. The commercial success of portable nanopore sequencers for single DNA molecules has inspired extensive research and development of single-molecule techniques for protein sequencing. Among them, three challenges remain: (1) discrimination of the 20 amino acids as building blocks of proteins; (2) unfolding proteins; and (3) controlling the motion of proteins with nonuniformly charged sequences. In this context, the emergence of label-free optical analysis techniques for single amino acids and peptides by solid-state nanopores shows promise for addressing the first challenge. In this Perspective, we first discuss the current challenges of single-molecule fluorescence detection and nanopore resistive pulse sensing in a protein sequencing. Then, label-free optical methods are described to show how they address the single-amino-acid identification within single peptides. They include localized surface plasmon resonance detection and surface-enhanced Raman spectroscopy on plasmonic nanopores. Notably, we report new data to show the ability of plasmon-enhanced Raman scattering to record and discriminate the 20 amino acids at a single-molecule level. In addition, we discuss briefly the manipulation of molecule translocation and liquid flow in plasmonic nanopores for controlling molecule movement to allow high-resolution reading of protein sequences. We envision that a combination of Raman spectroscopy with plasmonic nanopores can succeed in single-molecule protein sequencing in a label-free way.

Proteomics for Early Detection of Non-Muscle-Invasive Bladder Cancer: Clinically Useful Urine Protein Biomarkers

Bladder cancer is the fourth most common cancer in men, and most cases are non-muscle-invasive. A high recurrence rate is a critical problem in non-muscle-invasive bladder cancer. The availability of few urine tests hinders the effective detection of superficial and small bladder tumors. Cystoscopy is the gold standard for diagnosis; however, it is associated with urinary tract infections, hematuria, and pain. Early detection is imperative, as intervention influences recurrence. Therefore, urinary biomarkers need to be developed to detect these bladder cancers. Recently, several protein candidates in the urine have been identified as biomarkers. In the present narrative review, the current status of the development of urinary protein biomarkers, including FDA-approved biomarkers, is summarized. Additionally, contemporary proteomic technologies, such as antibody-based methods, mass-spectrometry-based methods, and machine-learning-based diagnosis, are reported. Furthermore, new strategies for the rapid and correct profiling of potential biomarkers of bladder cancer in urine are introduced, along with their limitations. The advantages of urinary protein biomarkers and the development of several related technologies are highlighted in this review. Moreover, an in-depth understanding of the scientific background and available protocols in research and clinical applications of the surveillance of non-muscle bladder cancer is provided.

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.

Making the cut with protease engineering

Proteases cut with enviable precision and regulate diverse molecular events in biology. Such qualities drive a seemingly inexhaustible appetite for proteases with new activities and capabilities. Comprising 25% of the total industrial enzyme market, proteases appear in consumer goods, such as detergents, textile processing, and numerous foods; additionally, proteases include 25 US Food and Drug Administration-approved medicines and various research tools. Recent advances in protease engineering strategies address target specificity, catalytic efficiency, and stability. This guide to protease engineering surveys best practices and emerging strategies. We further highlight gaps and flexibilities inherent to each system that suggest opportunities for new technology development along with engineered proteases to solve challenges in proteomics, protein sequencing, and synthetic gene circuits.

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.

Lifetime-based analysis of binary fluorophores mixtures in the low photon count limit

Single biomolecule sensing often requires the quantification of multiple fluorescent species. Here, we theoretically and experimentally use time-resolved fluorescence via Time Correlated Single Photon Counting (TCSPC) to accurately quantify fluorescent species with similar chromatic signatures. A modified maximum likelihood estimator is introduced to include two fluorophore species, with compensation of the instrument response function. We apply this algorithm to simulated data of a simplified two-fluorescent species model, as well as to experimental data of fluorophores' mixtures and to a model protein, doubly labeled with different fluorophores' ratio. We show that 100 to 200 photons per fluorophore, in a 10-ms timescale, are sufficient to provide an accurate estimation of the dyes' ratio on the model protein. Our results provide estimation for the desired photon integration time toward implementation of TCSPC in systems with fast occurring events, such as translocation of biomolecules through nanopores or single-molecule burst analyses experiments.

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Exact ratios of emission-similar dyes in binary mixtures were quantified by TCSPC

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MLE-based analysis with IRF compensation was implemented for two fluorescent dyes

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Dual dye bioconjugation on a model protein was quantified at limited photon counts

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.

Evaluation of FRET X for single-molecule protein fingerprinting

Single-molecule protein identification is an unrealized concept with potentially ground-breaking applications in biological research. We propose a method called FRET X (Förster Resonance Energy Transfer via DNA eXchange) fingerprinting, in which the FRET efficiency is read out between exchangeable dyes on protein-bound DNA docking strands and accumulated FRET efficiencies constitute the fingerprint for a protein. To evaluate the feasibility of this approach, we simulated fingerprints for hundreds of proteins using a coarse-grained lattice model and experimentally demonstrated FRET X fingerprinting on model peptides. Measured fingerprints are in agreement with our simulations, corroborating the validity of our modeling approach. In a simulated complex mixture of >300 human proteins of which only cysteines, lysines, and arginines were labeled, a support vector machine was able to identify constituents with 95% accuracy. We anticipate that our FRET X fingerprinting approach will form the basis of an analysis tool for targeted proteomics.

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We propose a FRET-based single-molecule protein identification method

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Peptides are experimentally distinguishable by their fingerprints

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Our approach can classify the constituents of complex samples with 95% accuracy

Nanopore electro-osmotic trap for the label-free study of single proteins and their conformations

Many strategies have been pursued to trap and monitor single proteins over time to detect the molecular mechanisms of these essential nanomachines. Single-protein sensing with nanopores is particularly attractive because it allows label-free high-bandwidth detection on the basis of ion currents. Here we present the nanopore electro-osmotic trap (NEOtrap) that allows trapping and observing single proteins for hours with submillisecond time resolution. The NEOtrap is formed by docking a DNA-origami sphere onto a passivated solid-state nanopore, which seals off a nanocavity of a user-defined size and creates an electro-osmotic flow that traps nearby particles irrespective of their charge. We demonstrate the NEOtrap's ability to sensitively distinguish proteins on the basis of size and shape, and discriminate between nucleotide-dependent protein conformations, as exemplified by the chaperone protein Hsp90. Given the experimental simplicity and capacity for label-free single-protein detection over the broad bio-relevant time range, the NEOtrap opens new avenues to study the molecular kinetics underlying protein function.

Probing Orientations and Conformations of Peptides and Proteins at Buried Interfaces

Molecular structures of peptides/proteins at interfaces determine their interfacial properties, which play important roles in many applications. It is difficult to probe interfacial peptide/protein structures because of the lack of appropriate tools. Sum frequency generation (SFG) vibrational spectroscopy has been developed into a powerful technique to elucidate molecular structures of peptides/proteins at buried solid/liquid and liquid/liquid interfaces. SFG has been successfully applied to study molecular interactions between model cell membranes and antimicrobial peptides/membrane proteins, surface-immobilized peptides/enzymes, and physically adsorbed peptides/proteins on polymers and 2D materials. A variety of other analytical techniques and computational simulations provide supporting information to SFG studies, leading to more complete understanding of structure-function relationships of interfacial peptides/proteins. With the advance of SFG techniques and data analysis methods, along with newly developed supplemental tools and simulation methodology, SFG research on interfacial peptides/proteins will further impact research in fields like chemistry, biology, biophysics, engineering, and beyond.

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.

Direct visualization of superselective colloid-surface binding mediated by multivalent interactions

Reliably distinguishing between cells based on minute differences in receptor density is crucial for cell-cell or virus-cell recognition, the initiation of signal transduction, and selective targeting in directed drug delivery. Such sharp differentiation between different surfaces based on their receptor density can only be achieved by multivalent interactions. Several theoretical and experimental works have contributed to our understanding of this "superselectivity." However, a versatile, controlled experimental model system that allows quantitative measurements on the ligand-receptor level is still missing. Here, we present a multivalent model system based on colloidal particles equipped with surface-mobile DNA linkers that can superselectively target a surface functionalized with the complementary mobile DNA-linkers. Using a combined approach of light microscopy and Foerster resonance energy transfer (FRET), we can directly observe the binding and recruitment of the ligand-receptor pairs in the contact area. We find a nonlinear transition in colloid-surface binding probability with increasing ligand or receptor concentration. In addition, we observe an increased sensitivity with weaker ligand-receptor interactions, and we confirm that the timescale of binding reversibility of individual linkers has a strong influence on superselectivity. These unprecedented insights on the ligand-receptor level provide dynamic information into the multivalent interaction between two fluidic membranes mediated by both mobile receptors and ligands and will enable future work on the role of spatial-temporal ligand-receptor dynamics on colloid-surface binding.

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.

Single-particle diffusional fingerprinting: A machine-learning framework for quantitative analysis of heterogeneous diffusion

Single-particle tracking (SPT) analysis of individual biomolecules is an indispensable tool for extracting quantitative information from dynamic biological processes, but often requires some a priori knowledge of the system. Here we present “single-particle diffusional fingerprinting,” a more general approach for extraction of diffusional patterns in SPT independently of the biological system. This method extracts a set of descriptive features for each SPT trajectory, which are ranked upon classification to yield mechanistic insights for the species under comparison. We demonstrate its capacity to yield a dictionary of diffusional traits across multiple systems (e.g., lipases hydrolyzing fat, transcription factors diffusing in cells, and nanoparticles in mucus), supporting its use on multiple biological phenomena (e.g., drug delivery, receptor dynamics, and virology).

Single-particle tracking (SPT) is a key tool for quantitative analysis of dynamic biological processes and has provided unprecedented insights into a wide range of systems such as receptor localization, enzyme propulsion, bacteria motility, and drug nanocarrier delivery. The inherently complex diffusion in such biological systems can vary drastically both in time and across systems, consequently imposing considerable analytical challenges, and currently requires an a priori knowledge of the system. Here we introduce a method for SPT data analysis, processing, and classification, which we term “diffusional fingerprinting.” This method allows for dissecting the features that underlie diffusional behavior and establishing molecular identity, regardless of the underlying diffusion type. The method operates by isolating 17 descriptive features for each observed motion trajectory and generating a diffusional map of all features for each type of particle. Precise classification of the diffusing particle identity is then obtained by training a simple logistic regression model. A linear discriminant analysis generates a feature ranking that outputs the main differences among diffusional features, providing key mechanistic insights. Fingerprinting operates by both training on and predicting experimental data, without the need for pretraining on simulated data. We found this approach to work across a wide range of simulated and experimentally diverse systems, such as tracked lipases on fat substrates, transcription factors diffusing in cells, and nanoparticles diffusing in mucus. This flexibility ultimately supports diffusional fingerprinting’s utility as a universal paradigm for SPT diffusional analysis and prediction.

Proteomics, Personalized Medicine and Cancer

As of 2020 the human genome and proteome are both at >90% completion based on high stringency analyses. This has been largely achieved by major technological advances over the last 20 years and has enlarged our understanding of human health and disease, including cancer, and is supporting the current trend towards personalized/precision medicine. This is due to improved screening, novel therapeutic approaches and an increased understanding of underlying cancer biology. However, cancer is a complex, heterogeneous disease modulated by genetic, molecular, cellular, tissue, population, environmental and socioeconomic factors, which evolve with time. In spite of recent advances in treatment that have resulted in improved patient outcomes, prognosis is still poor for many patients with certain cancers (e.g., mesothelioma, pancreatic and brain cancer) with a high death rate associated with late diagnosis. In this review we overview key hallmarks of cancer (e.g., autophagy, the role of redox signaling), current unmet clinical needs, the requirement for sensitive and specific biomarkers for early detection, surveillance, prognosis and drug monitoring, the role of the microbiome and the goals of personalized/precision medicine, discussing how emerging omics technologies can further inform on these areas. Exemplars from recent onco-proteogenomic-related publications will be given. Finally, we will address future perspectives, not only from the standpoint of perceived advances in treatment, but also from the hurdles that have to be overcome.

Hydrated Ionic Liquids Boost the Trace Detection Capacity of Proteins on TiO2 Support

Trace detection based on surface-enhanced Raman scattering (SERS) has attracted considerable attention, and exploiting efficient strategies to stretch the limit of detection and understanding the mechanisms on molecular level are of utmost importance. In this work, we use ionic liquids (ILs) as trace additives in a protein-TiO2 system, allowing us to obtain an exceptionally low limit of detection down to 10-9 M. The enhancement factors (EFs) were determined to 2.30 × 104, 6.17 × 104, and 1.19 × 105, for the three systems: one without ILs, one with ILs in solutions, and one with ILs immobilized on the TiO2 substrate, respectively, corresponding to the molecular forces of 1.65, 1.32, and 1.16 nN quantified by the atomic force microscopy. The dissociation and following hydration of ILs, occurring in the SERS system, weakened the molecular forces but instead improved the electron transfer ability of ILs, which is the major contribution for the observed excellent detection. The weaker diffusion of the hydrated IL ions immobilized on the TiO2 substrate did provide a considerably greater EF value, compared to the ILs in the solution. This work clearly demonstrates the importance of the hydration of ions, causing an improved electron transfer ability of ILs and leading to an exceptional SERS performance in the field of trace detection. Our results should stimulate further development to use ILs in SERS and related applications in bioanalysis, medical diagnosis, and environmental science.

Oriented Soft DNA Curtains for Single-Molecule Imaging

Over the past 20 years, single-molecule methods have become extremely important for biophysical studies. These methods, in combination with new nanotechnological platforms, can significantly facilitate experimental design and enable faster data acquisition. A nanotechnological platform, which utilizes a flow-stretch of immobilized DNA molecules, called DNA Curtains, is one of the best examples of such combinations. Here, we employed new strategies to fabricate a flow-stretch assay of stably immobilized and oriented DNA molecules using a protein template-directed assembly. In our assay, a protein template patterned on a glass coverslip served for directional assembly of biotinylated DNA molecules. In these arrays, DNA molecules were oriented to one another and maintained extended by either single- or both-end immobilization to the protein templates. For oriented both-end DNA immobilization, we employed heterologous DNA labeling and protein template coverage with the antidigoxigenin antibody. In contrast to single-end immobilization, both-end immobilization does not require constant buffer flow for keeping DNAs in an extended configuration, allowing us to study protein-DNA interactions at more controllable reaction conditions. Additionally, we increased the immobilization stability of the biotinylated DNA molecules using protein templates fabricated from traptavidin. Finally, we demonstrated that double-tethered Soft DNA Curtains can be used in nucleic acid-interacting protein (e.g., CRISPR-Cas9) binding assay that monitors the binding location and position of individual fluorescently labeled proteins on DNA.

From proteomic landscape to single-cell oncoproteomics

Introduction: Proteomic profiling plays an important role in the exploration of cancer from molecular mechanisms to clinical diagnosis and treatment. In recent years, the advent of new technologies has promoted oncoproteomics from the initial global style to a refined single-cell level.Areas Covered: Among them, the development of microfluidic devices, the improvement of liquid mass spectrometry in accuracy and trace sample handling processes, and the emergence of protein sequencing have contributed to the oncoproteomic analysis at the single-cell level.Expert Opinion: The proteomic analysis at the global level and the single-cell level gives different perspectives while combining them can reveal more comprehensive oncoproteomics and help cancer research and treatment strategies.