Structural-profiling of low molecular weight RNAs by nanopore trapping/translocation using Mycobacterium smegmatis porin A

Impact of MSMEG5257 Deletion on Mycolicibacterium smegmatis Growth

Mycobacterial membrane proteins play a pivotal role in the bacterial invasion of host cells; however, the precise mechanisms underlying certain membrane proteins remain elusive. Mycolicibacterium smegmatis (Ms) msmeg5257 is a hemolysin III family protein that is homologous to Mycobacterium tuberculosis (Mtb) Rv1085c, but it has an unclear function in growth. To address this issue, we utilized the CRISPR/Cas9 gene editor to construct Δmsmeg5257 strains and combined RNA transcription and LC-MS/MS protein profiling to determine the functional role of msmeg5257 in Ms growth. The correlative analysis showed that the deletion of msmeg5257 inhibits ABC transporters in the cytomembrane and inhibits the biosynthesis of amino acids in the cell wall. Corresponding to these results, we confirmed that MSMEG5257 localizes in the cytomembrane via subcellular fractionation and also plays a role in facilitating the transport of iron ions in environments with low iron levels. Our data provide insights that msmeg5257 plays a role in maintaining Ms metabolic homeostasis, and the deletion of msmeg5257 significantly impacts the growth rate of Ms. Furthermore, msmeg5257, a promising drug target, offers a direction for the development of novel therapeutic strategies against mycobacterial diseases.

Nanopore Identification of N-Acetylation by Hydroxylamine Deacetylation (NINAHD)

N-Acetyl modification, a chemical modification commonly found on biomacromolecules, plays a crucial role in the regulation of cell activities and is related to a variety of diseases. However, due to the instability of N-acetyl modification, accurate and rapid identification of N-acetyl modification with a low measurement cost is still technically challenging. Here, based on hydroxylamine deacetylation and nanopore single molecule chemistry, a universal sensing strategy for N-acetyl modification has been developed. Acetohydroxamic acid (AHA), which is produced by the hydroxylamine deacetylation reaction and serves as a reporter for N-acetylation identification, is specifically sensed by a phenylboronic acid (PBA)-modified Mycobacterium smegmatis porin A (MspA). With this strategy, N-acetyl modifications on RNA, DNA, proteins, and glycans were identified, demonstrating its generality. Specifically, histones can be treated with hydroxylamine deacetylation, from which the generated AHA can represent the amount of N-acetyl modification detected by a nanopore sensor. The unique event features of AHA also demonstrate the robustness of sensing against other interfering analytes in the environment.

Recent advances in nanopore-based analysis for carbohydrates and glycoconjugates

Saccharides are not only the basic constituents and nutrients of living organisms, but also participate in various life activities, and play important roles in cell recognition, immune regulation, development, cancer, etc. The analysis of carbohydrates and glycoconjugates is a necessary means to study their transformations and physiological roles in living organisms. Existing detection techniques can hardly meet the requirements for the analysis of carbohydrates and glycoconjugates in complex matrices as they are expensive, involve complex derivatization, and are time-consuming. Nanopore sensing technology, which is amplification-free and label-free, and is a high-throughput process, provides a new solution for the identification and sequencing of carbohydrates and glycoconjugates. This review highlights recent advances in novel nanopore-based single-molecule sensing technologies for the detection of carbohydrates and glycoconjugates and discusses the advantages and challenges of nanopore sensing technologies. Finally, current issues and future perspectives are discussed with the aim of improving the performance of nanopores in complex media diagnostic applications, as well as providing a new direction for the quantification of glycan chains and the study of glycan chain properties and functions.

Nanopore analysis of cis-diols in fruits

Natural fruits contain a large variety of cis-diols. However, due to the lack of a high-resolution sensor that can simultaneously identify all cis-diols without a need of complex sample pretreatment, direct and rapid analysis of fruits in a hand-held device has never been previously reported. Nanopore, a versatile single molecule sensor, can be specially engineered to perform this task. A hetero-octameric Mycobacterium smegmatis porin A (MspA) nanopore modified with a sole phenylboronic acid (PBA) adapter is prepared. This engineered MspA accurately recognizes 1,2-diphenols, alditols, α-hydroxy acids and saccharides in prune, grape, lemon, different varieties of kiwifruits and commercial juice products. Assisted with a custom machine learning program, an accuracy of 99.3% is reported and the sample pretreatment is significantly simplified. Enantiomers such as DL-malic acids can also be directly identified, enabling sensing of synthetic food additives. Though demonstrated with fruits, these results suggest wide applications of nanopore in food and drug administration uses.

The C-terminus is essential for the stability of the mycobacterial channel protein MspA

Outer membrane proteins perform essential functions in uptake and secretion processes in bacteria. MspA is an octameric channel protein in the outer membrane of Mycobacterium smegmatis and is structurally distinct from any other known outer membrane protein. MspA is the founding member of a family with more than 3000 homologs and is one of the most widely used proteins in nanotechnological applications due to its advantageous pore structure and extraordinary stability. While a conserved C-terminal signal sequence is essential for folding and protein assembly in the outer membrane of Gram-negative bacteria, the molecular determinants of these processes are unknown for MspA. In this study, we show that mutation and deletion of methionine 183 in the highly conserved C-terminus of MspA and mutation of the conserved tryptophan 40 lead to a complete loss of protein in heat extracts of M. smegmatis. Swapping these residues partially restores the heat stability of MspA indicating that methionine 183 and tryptophan 40 form a conserved sulfur-π electron interaction, which stabilizes the MspA monomer. Flow cytometry showed that all MspA mutants are surface-accessible demonstrating that oligomerization and membrane integration in M. smegmatis are not affected. Thus, the conserved C-terminus of MspA is essential for its thermal stability, but it is not required for protein assembly in its native membrane, indicating that this process is mediated by a mechanism distinct from that in Gram-negative bacteria. These findings will benefit the rational design of MspA-like pores to tailor their properties in current and future applications.

Discrimination of Disaccharide Isomers of Different Glycosidic Linkages Using a Modified MspA Nanopore

Disaccharides are composed of two monosaccharide subunits joined by a glycosidic linkage in an α or β configuration. Different combinations of isomeric monosaccharide subunits and different glycosidic linkages result in different isomeric disaccharide products. Thus, direct discrimination of these disaccharide isomers from a mixture is extremely difficult. In this paper, a hetero-octameric Mycobacterium smegmatis porin A (MspA) nanopore conjugated with a phenylboronic acid (PBA) adapter was applied for disaccharide sensing, with which three most widely known disaccharides in nature, including sucrose, lactose and maltose, were clearly discriminated. Besides, all six isomeric α-D-glucopyranosyl-D-fructoses, differing only in their glycosidic linkages, were also well resolved. Assisted by a custom machine learning algorithm, a 0.99 discrimination accuracy is achieved. Nanopore discrimination of disaccharide isomers with different glycosidic linkages, which has never been previously demonstrated, is inspiring for nanopore saccharide sequencing. This sensing capacity was also applied in direct identification of isomaltulose additives in a commercial sucrose-free yogurt, from which isomaltulose, lactose and L-lactic acid were simultaneously detected.

T-S2Inet: Transformer-based sequence-to-image network for accurate nanopore sequence recognition

MOTIVATION

Nanopore sequencing is a new macromolecular recognition and perception technology that enables high-throughput sequencing of DNA, RNA, even protein molecules. The sequences generated by nanopore sequencing span a large time frame, and the labor and time costs incurred by traditional analysis methods are substantial. Recently, research on nanopore data analysis using machine learning algorithms has gained unceasing momentum, but there is often a significant gap between traditional and deep learning methods in terms of classification results. To analyze nanopore data using deep learning technologies, measures such as sequence completion and sequence transformation can be employed. However, these technologies do not preserve the local features of the sequences. To address this issue, we propose a sequence-to-image (S2I) module that transforms sequences of unequal length into images. Additionally, we propose the Transformer-based T-S2Inet model to capture the important information and improve the classification accuracy.

RESULTS

Quantitative and qualitative analysis shows that the experimental results have an improvement of around 2% in accuracy compared to previous methods. The proposed method is adaptable to other nanopore platforms, such as the Oxford nanopore. It is worth noting that the proposed method not only aims to achieve the most advanced performance, but also provides a general idea for the analysis of nanopore sequences of unequal length.

AVAILABILITY AND IMPLEMENTATION

The main program is available at https://github.com/guanxiaoyu11/S2Inet.

Quantitative analysis of tRNA abundance and modifications by nanopore RNA sequencing

Transfer RNAs (tRNAs) play a central role in protein translation. Studying them has been difficult in part because a simple method to simultaneously quantify their abundance and chemical modifications is lacking. Here we introduce Nano-tRNAseq, a nanopore-based approach to sequence native tRNA populations that provides quantitative estimates of both tRNA abundances and modification dynamics in a single experiment. We show that default nanopore sequencing settings discard the vast majority of tRNA reads, leading to poor sequencing yields and biased representations of tRNA abundances based on their transcript length. Re-processing of raw nanopore current intensity signals leads to a 12-fold increase in the number of recovered tRNA reads and enables recapitulation of accurate tRNA abundances. We then apply Nano-tRNAseq to Saccharomyces cerevisiae tRNA populations, revealing crosstalks and interdependencies between different tRNA modification types within the same molecule and changes in tRNA populations in response to oxidative stress.

A novel design of DNA duplex containing programmable sensing sites for nanopore-based length-resolution reading and applications for Pb2+ and cfDNA analysis

Glass nanopore is an ideal candidate for biosensors due to its unique advantages such as label-free analysis, single-molecule sensitivity, and easy operation. Previous studies have shown that glass nanopores can distinguish different lengths of double-stranded DNA (dsDNA) at the same time with the length-resolution ability. Based on this, we proposed a novel design of a dsDNA block containing a programmable sensing site inside, which can be programmed to respond to different target molecules and cleaved into two smaller DNA blocks. When programming the sensing site with different sequences, for example, programming it as the substrate of GR-5 DNAzyme and CRISPR-Cas12a system, the DNA block could realize Pb2+ and cfDNA detection with the length-resolution ability of the glass nanopore. This strategy achieved a Pb2+ detection range from 0.5 nM to 100 nM, with a detection limit of 0.4 nM, and a BRCA-1 detection range from 1 pM to 10 pM, with a detection limit of 1 pM. The programable sensing site is easy to design and has strong expandability, which gives full play to the advantages of glass nanopore in length-resolution ability for dsDNA, and is expected to become an optional design for biosensing strategy for the glass nanopore as a biosensing platform.

Machine learning for small interfering RNAs: a concise review of recent developments

The advent of machine learning and its subsequent integration into small interfering RNA (siRNA) research heralds a new epoch in the field of RNA interference (RNAi). This review emphasizes the urgency and relevance of assimilating the plethora of contributions and advancements in this domain, particularly focusing on the period of 2019-2023. Given the rapid progression of deep learning technologies, our synthesis of recent research is paramount to staying apprised of the state-of-the-art methods being utilized. It not only offers a comprehensive insight into the confluence of machine learning and siRNA but also serves as a beacon, guiding future explorations in this intersectional research field. Our rigorous examination of studies promises a discerning perspective on the contemporary landscape of machine learning applications in siRNA design and function. This review is an effort to foster further discourse and propel academic inquiry in this multifaceted domain.

Real-time label-free detection of dynamic aptamer-small molecule interactions using a nanopore nucleic acid conformational sensor

Nucleic acids can undergo conformational changes upon binding small molecules. These conformational changes can be exploited to develop new therapeutic strategies through control of gene expression or triggering of cellular responses and can also be used to develop sensors for small molecules such as neurotransmitters. Many analytical approaches can detect dynamic conformational change of nucleic acids, but they need labeling, are expensive, and have limited time resolution. The nanopore approach can provide a conformational snapshot for each nucleic acid molecule detected, but has not been reported to detect dynamic nucleic acid conformational change in response to small -molecule binding. Here we demonstrate a modular, label-free, nucleic acid-docked nanopore capable of revealing time-resolved, small molecule-induced, single nucleic acid molecule conformational transitions with millisecond resolution. By using the dopamine-, serotonin-, and theophylline-binding aptamers as testbeds, we found that these nucleic acids scaffolds can be noncovalently docked inside the MspA protein pore by a cluster of site-specific charged residues. This docking mechanism enables the ion current through the pore to characteristically vary as the aptamer undergoes conformational changes, resulting in a sequence of current fluctuations that report binding and release of single ligand molecules from the aptamer. This nanopore tool can quantify specific ligands such as neurotransmitters, elucidate nucleic acid-ligand interactions, and pinpoint the nucleic acid motifs for ligand binding, showing the potential for small molecule biosensing, drug discovery assayed via RNA and DNA conformational changes, and the design of artificial riboswitch effectors in synthetic biology.

A nanopore counter for highly sensitive evaluation of DNA methylation and its application in in vitro diagnostics

DNA methylation has been considered an essential epigenetic biomarker for diagnosing various diseases, such as cancer. A simple and sensitive way for DNA methylation level detection is necessary. Inspired by the label-free and ultra-high sensitivity of solid-state nanopores to double-stranded DNA (dsDNA), we proposed a nanopore counter for evaluating DNA methylation by integrating a dual-restriction endonuclease digestion strategy coupled with polymerase chain reaction (PCR) amplification. Simultaneous application of BstUI/HhaI endonucleases can ensure the full digestion of the unmethylated target DNA but shows no effect on the methylated ones. Therefore, only the methylated DNA remains intact and can trigger the subsequent PCR reaction, producing a large quantity of fixed-length PCR amplicons, which can be directly detected through glassy nanopores. By simply counting the event rate of the translocation signals, the concentration of methylated DNA can be determined to range from 1 aM to 0.1 nM, with the detection limit as low as 0.61 aM. Moreover, a 0.01% DNA methylation level was successfully distinguished. The strategy of using the nanopore counter for highly sensitive DNA methylation evaluation would be a low-cost but reliable alternative in the analysis of DNA methylation.

Cell-Free Expression of De Novo Designed Peptides That Form β-Barrel Nanopores

Nanopore sensing has attracted much attention as a rapid, simple, and label-free single-molecule detection technology. To apply nanopore sensing to extensive targets including polypeptides, nanopores are required to have a size and structure suitable for the target. We recently designed a de novo β-barrel peptide nanopore (SVG28) that constructs a stable and monodispersely sized nanopore. To develop the sizes and functionality of peptide nanopores, systematic exploration is required. Here we attempt to use a cell-free synthesis system that can readily express peptides using transcription and translation. Hydrophilic variants of SVG28 were designed and expressed by the PURE system. The peptides form a monodispersely sized nanopore, with a diameter 1.1 or 1.5 nm smaller than that of SVG28. Such cell-free synthesizable peptide nanopores have the potential to enable the systematic custom design of nanopores and comprehensive sequence screening of nanopore-forming peptides.

Single-Molecule Interconversion between Chiral Configurations of Boronate Esters Observed in a Nanoreactor

Isomers of some chemical compounds may be dynamically interconvertible. Due to a lack of sensing methods with a sufficient resolution, however, direct monitoring of such processes can be difficult. Engineered Mycobacterium smegmatis porin A (MspA) nanopores can be applied as nanoreactors so that chemical reactions can be directly monitored. Here, an MspA modified with a phenylboronic acid (PBA) adapter was prepared and was used to observe dynamic interconversion between chiral configurations of boronate esters, which appears as telegraphic switching on top of nanopore events. The mechanism of this behavior was further confirmed by trials with different halogenated catechols, dopamine, adenosine, 1,2-propanediol, and (2R,3R)-2,3-butanediol, and its generality has been demonstrated. These results suggest that an engineered MspA possesses an exceptional resolution in its monitoring of chemical reaction processes and may inspire the future design of nanopore small-molecule sensors.

Discrimination of Ribonucleoside Mono-, Di-, and Triphosphates Using an Engineered Nanopore

Ribonucleotides, which widely exist in all living organisms and are essential to both physiological and pathological processes, can naturally appear as ribonucleoside mono-, di-, and triphosphates. Natural ribonucleotides can also dynamically switch between different phosphorylated forms, posing a great challenge for sensing. A specially engineered nanopore sensor is promising for full discrimination of all canonical ribonucleoside mono-, di-, and triphosphates. However, such a demonstration has never been reported, due to the lack of a suitable nanopore sensor that has a sufficient resolution. In this work, we utilized a phenylboronic acid (PBA) modified Mycobacterium smegmatis porin A (MspA) hetero-octamer for ribonucleotide sensing. Twelve types of ribonucleotides, including mono-, di-, and triphosphates of cytidine (CMP, CDP, CTP), uridine (UMP, UDP, UTP), adenosine (AMP, ADP, ATP), and guanosine (GMP, GDP, GTP) were simultaneously discriminated. A machine-learning algorithm was also developed, which achieved a general accuracy of 99.9% for ribonucleotide sensing. This strategy was also further applied to identify ribonucleotide components in ATP tablets and injections. This sensing strategy provides a direct, accurate, easy, and rapid solution to characterize ribonucleotide components in different phosphorylated forms.

Active learning for efficient analysis of high-throughput nanopore data

MOTIVATION

As the third-generation sequencing technology, nanopore sequencing has been used for high-throughput sequencing of DNA, RNA, and even proteins. Recently, many studies have begun to use machine learning technology to analyze the enormous data generated by nanopores. Unfortunately, the success of this technology is due to the extensive labeled data, which often suffer from enormous labor costs. Therefore, there is an urgent need for a novel technology that can not only rapidly analyze nanopore data with high-throughput, but also significantly reduce the cost of labeling. To achieve the above goals, we introduce active learning to alleviate the enormous labor costs by selecting the samples that need to be labeled. This work applies several advanced active learning technologies to the nanopore data, including the RNA classification dataset (RNA-CD) and the Oxford Nanopore Technologies barcode dataset (ONT-BD). Due to the complexity of the nanopore data (with noise sequence), the bias constraint is introduced to improve the sample selection strategy in active learning. Results: The experimental results show that for the same performance metric, 50% labeling amount can achieve the best baseline performance for ONT-BD, while only 15% labeling amount can achieve the best baseline performance for RNA-CD. Crucially, the experiments show that active learning technology can assist experts in labeling samples, and significantly reduce the labeling cost. Active learning can greatly reduce the dilemma of difficult labeling of high-capacity nanopore data. We hope active learning can be applied to other problems in nanopore sequence analysis.

AVAILABILITY AND IMPLEMENTATION

The main program is available at https://github.com/guanxiaoyu11/AL-for-nanopore.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Nanopore Detection Assisted DNA Information Processing

The deoxyribonucleotide (DNA) molecule is a stable carrier for large amounts of genetic information and provides an ideal storage medium for next-generation information processing technologies. Technologies that process DNA information, representing a cross-disciplinary integration of biology and computer techniques, have become attractive substitutes for technologies that process electronic information alone. The detailed applications of DNA technologies can be divided into three components: storage, computing, and self-assembly. The quality of DNA information processing relies on the accuracy of DNA reading. Nanopore detection allows researchers to accurately sequence nucleotides and is thus widely used to read DNA. In this paper, we introduce the principles and development history of nanopore detection and conduct a systematic review of recent developments and specific applications in DNA information processing involving nanopore detection and nanopore-based storage. We also discuss the potential of artificial intelligence in nanopore detection and DNA information processing. This work not only provides new avenues for future nanopore detection development, but also offers a foundation for the construction of more advanced DNA information processing technologies.

Identification of nucleoside monophosphates and their epigenetic modifications using an engineered nanopore

RNA modifications play critical roles in the regulation of various biological processes and are associated with many human diseases. Direct identification of RNA modifications by sequencing remains challenging, however. Nanopore sequencing is promising, but the current strategy is complicated by sequence decoding. Sequential nanopore identification of enzymatically cleaved nucleoside monophosphates may simultaneously provide accurate sequence and modification information. Here we show a phenylboronic acid-modified hetero-octameric Mycobacterium smegmatis porin A nanopore, with which direct distinguishing between monophosphates of canonical nucleosides, 5-methylcytidine, N⁶-methyladenosine, N⁷-methylguanosine, N¹-methyladenosine, inosine, pseudouridine and dihydrouridine was achieved. A custom machine learning algorithm, which reports an accuracy of 0.996, was also applied to the quantitative analysis of modifications in microRNA and natural transfer RNA. It is generally suitable for sensing of a variety of other nucleoside or nucleotide derivatives and may bring new insights to epigenetic RNA sequencing.

Application of nanopore sensors for biomolecular interactions and drug discovery

Biomolecular interactions, including protein-protein, protein-nucleic acid, and protein/nucleic acid-ligand interactions, play crucial roles in various cellular signaling and biological processes, and offer attractive therapeutic targets in numerous human diseases. Currently, drug discovery is limited by the low efficiency and high cost of conventional ensemble-averaging-based techniques for biomolecular interaction analysis and high-throughput drug screening. Nanopores are an emerging technology for single-molecule sensing of biomolecules. Owing to the robust advantages of single-molecule sensing, nanopore sensors have contributed tremendously to nucleic acid sequencing and disease diagnostics. In this minireview, we summarize the recent developments and outlooks in single-molecule sensing of various biomolecular interactions for drug discovery applications using biological and solid-state nanopore sensors.

Nanopore Identification of Alditol Epimers and Their Application in Rapid Analysis of Alditol-Containing Drinks and Healthcare Products

Alditols, which have a sweet taste but produce much lower calories than natural sugars, are widely used as artificial sweeteners. Alditols are the reduced forms of monosaccharide aldoses, and different alditols are diastereomers or epimers of each other and direct and rapid identification by conventional methods is difficult. Nanopores, which are emerging single-molecule sensors with exceptional resolution when engineered appropriately, are useful for the recognition of diastereomers and epimers. In this work, direct distinguishing of alditols corresponding to all 15 monosaccharide aldoses was achieved by a boronic acid-appended hetero-octameric Mycobacterium smegmatis porin A (MspA) nanopore (MspA-PBA). Thirteen alditols including glycerol, erythritol, threitol, adonitol, arabitol, xylitol, mannitol, sorbitol, allitol, dulcitol, iditol, talitol, and gulitol (l-sorbitol) could be fully distinguished, and their sensing features constitute a complete nanopore alditol database. To automate event classification, a custom machine-learning algorithm was developed and delivered a 99.9% validation accuracy. This strategy was also used to identify alditol components in commercially available "zero-sugar" drinks and healthcare products, suggesting their use in rapid and sensitive quality control for the food and medical industry.

A Nanopore-Based Saccharide Sensor

Saccharides play critical roles in many forms of cellular activities. Saccharide structures are however complicated and similar, setting a technical hurdle for direct identification. Nanopores, which are emerging single molecule tools sensitive to minor structural differences between analytes, can be engineered to identity saccharides. A hetero-octameric Mycobacterium smegmatis porin A nanopore containing a phenylboronic acid was prepared, and was able to clearly identify nine monosaccharide types, including D-fructose, D-galactose, D-mannose, D-glucose, L-sorbose, D-ribose, D-xylose, L-rhamnose and N-acetyl-D-galactosamine. Minor structural differences between saccharide epimers can also be distinguished. To assist automatic event classification, a machine learning algorithm was developed, with which a general accuracy score of 0.96 was achieved. This sensing strategy is generally suitable for other saccharide types and may bring new insights to nanopore saccharide sequencing.

Advances of nanopore-based sensing techniques for contaminants evaluation of food and agricultural products

Food safety assurance systems are becoming more stringent in response to the growing food safety problems. Rapid, sensitive, and reliable detection technology is a prerequisite for the establishment of food safety assurance systems. Nanopore technology has been taken as one of the emerging technology capable of dealing with the detection of harmful contaminants as efficiently as possible due to the advantage of label-free, high-throughput, amplification-free, and rapid detection features. Start with the history of nanopore techniques, this review introduced the underlying knowledge of detection mechanism of nanopore-based sensing techniques. Meanwhile, sensing interfaces for the construction of nanopore sensors are comprehensively summarized. Moreover, this review covers the current advances of nanopore techniques in the application of food safety screening. Currently, the establishment of nanopore sensing devices is mainly based on the blocking current phenomenon. Sensing interfaces including biological nanopores, solid-state nanopores, DNA origami, and de novo designed nanopores can be used in the manufacture of sensing devices. Food harmful substances, including heavy metals, veterinary drugs, pesticide residues, food toxins, and other harmful substances can be quickly determined by nanopore-based sensors. Moreover, the combination of nanopore techniques with advanced materials has become one of the most effective methods to improve sensing properties.

Translocation Behaviors of Synthetic Polyelectrolytes through Alpha-Hemolysin (α-HL) and Mycobacterium smegmatis Porin A (MspA) Nanopores

DNAs have been used as probes for nanopore sensing of noncharged biomacromolecules due to its negative phosphate backbone. Inspired by this, we explored the potential of diblock synthetic polyelectrolytes as more flexible and inexpensive nanopore sensing probes by investigating translocation behaviors of PEO-b-PSS and PEO-b-PVBTMA through commonly used alpha-hemolysin (α-HL) and Mycobacterium smegmatis porin A (MspA) nanopores. Translocation recordings in different configurations of pore orientation and testing voltage indicated efficient PEO-b-PSS translocations through α-HL and PEO-b-PVBTMA translocations through MspA. This work provides insight into synthetic polyelectrolyte-based probes to expand probe selection and flexibility for nanopore sensing.

Identification of Single-Molecule Catecholamine Enantiomers Using a Programmable Nanopore

Enantiomers, chiral isomers with opposite chirality, typically demonstrate differences in their pharmacological activity, metabolism, and toxicity. However, direct discrimination between enantiomers is challenging due to their similar physiochemical properties. Following the strategy of programmable nanoreactors for stochastic sensing (PNRSS), introduction of phenylboronic acid (PBA) to a Mycobacterium smegmatis porin A (MspA) assists in the identification of the enantiomers of norepinephrine and epinephrine. Using a machine learning algorithm, identification of the enantiomers has been achieved with an accuracy of 98.2%. The enantiomeric excess (ee) of a mixture of enantiomeric catecholamines was measured to determine the enantiomeric purity. This sensing strategy is a faster method for the determination of ee values than liquid chromatography-mass spectrometry and is useful as a quality control in the industrial production of enantiomeric drugs.

S2Snet: deep learning for low molecular weight RNA identification with nanopore

Ribonucleic acid (RNA) is a pivotal nucleic acid that plays a crucial role in regulating many biological activities. Recently, one study utilized a machine learning algorithm to automatically classify RNA structural events generated by a Mycobacterium smegmatis porin A nanopore trap. Although it can achieve desirable classification results, compared with deep learning (DL) methods, this classic machine learning requires domain knowledge to manually extract features, which is sophisticated, labor-intensive and time-consuming. Meanwhile, the generated original RNA structural events are not strictly equal in length, which is incompatible with the input requirements of DL models. To alleviate this issue, we propose a sequence-to-sequence (S2S) module that transforms the unequal length sequence (UELS) to the equal length sequence. Furthermore, to automatically extract features from the RNA structural events, we propose a sequence-to-sequence neural network based on DL. In addition, we add an attention mechanism to capture vital information for classification, such as dwell time and blockage amplitude. Through quantitative and qualitative analysis, the experimental results have achieved about a 2% performance increase (accuracy) compared to the previous method. The proposed method can also be applied to other nanopore platforms, such as the famous Oxford nanopore. It is worth noting that the proposed method is not only aimed at pursuing state-of-the-art performance but also provides an overall idea to process nanopore data with UELS.

Promising Assays for Examining a Putative Role of Ribosomal Heterogeneity in COVID-19 Susceptibility and Severity

The heterogeneity of ribosomes, characterized by structural variations, arises from differences in types, numbers, and/or post-translational modifications of participating ribosomal proteins (RPs), ribosomal RNAs (rRNAs) sequence variants plus post-transcriptional modifications, and additional molecules essential for forming a translational machinery. The ribosomal heterogeneity within an individual organism or a single cell leads to preferential translations of selected messenger RNA (mRNA) transcripts over others, especially in response to environmental cues. The role of ribosomal heterogeneity in SARS-CoV-2 coronavirus infection, propagation, related symptoms, or vaccine responses is not known, and a technique to examine these has not yet been developed. Tools to detect ribosomal heterogeneity or to profile translating mRNAs independently cannot identify unique or specialized ribosome(s) along with corresponding mRNA substrate(s). Concurrent characterizations of RPs and/or rRNAs with mRNA substrate from a single ribosome would be critical to decipher the putative role of ribosomal heterogeneity in the COVID-19 disease, caused by the SARS-CoV-2, which hijacks the host ribosome to preferentially translate its RNA genome. Such a protocol should be able to provide a high-throughput screening of clinical samples in a large population that would reach a statistical power for determining the impact of a specialized ribosome to specific characteristics of the disease. These characteristics may include host susceptibility, viral infectivity and transmissibility, severity of symptoms, antiviral treatment responses, and vaccine immunogenicity including its side effect and efficacy. In this study, several state-of-the-art techniques, in particular, chemical probing of ribosomal components or rRNA structures, proximity ligation to generate rRNA-mRNA chimeras for sequencing, nanopore gating of individual ribosomes, nanopore RNA sequencing and/or structural analyses, single-ribosome mass spectrometry, and microfluidic droplets for separating ribosomes or indexing rRNAs/mRNAs, are discussed. The key elements for further improvement and proper integration of the above techniques to potentially arrive at a high-throughput protocol for examining individual ribosomes and their mRNA substrates in a clinical setting are also presented.

Machine Learning Assisted Simultaneous Structural Profiling of Differently Charged Proteins in a Mycobacterium smegmatis Porin A (MspA) Electroosmotic Trap

The nanopore is emerging as a means of single-molecule protein sensing. However, proteins demonstrate different charge properties, which complicates the design of a sensor that can achieve simultaneous sensing of differently charged proteins. In this work, we introduce an asymmetric electrolyte buffer combined with the Mycobacterium smegmatis porin A (MspA) nanopore to form an electroosmotic flow (EOF) trap. Apo- and holo-myoglobin, which differ in only a single heme, can be fully distinguished by this method. Direct discrimination of lysozyme, apo/holo-myoglobin, and the ACTR/NCBD protein complex, which are basic, neutral, and acidic proteins, respectively, was simultaneously achieved by the MspA EOF trap. To automate event classification, multiple event features were extracted to build a machine learning model, with which a 99.9% accuracy is achieved. The demonstrated method was also applied to identify single molecules of α-lactalbumin and β-lactoglobulin directly from whey protein powder. This protein-sensing strategy is useful in direct recognition of a protein from a mixture, suggesting its prospective use in rapid and sensitive detection of biomarkers or real-time protein structural analysis.

Nanopores in Graphene and Other 2D Materials: A Decade's Journey toward Sequencing

Nanopore techniques offer a low-cost, label-free, and high-throughput platform that could be used in single-molecule biosensing and in particular DNA sequencing. Since 2010, graphene and other two-dimensional (2D) materials have attracted considerable attention as membranes for producing nanopore devices, owing to their subnanometer thickness that can in theory provide the highest possible spatial resolution of detection. Moreover, 2D materials can be electrically conductive, which potentially enables alternative measurement schemes relying on the transverse current across the membrane material itself and thereby extends the technical capability of traditional ionic current-based nanopore devices. In this review, we discuss key advances in experimental and computational research into DNA sensing with nanopores built from 2D materials, focusing on both the ionic current and transverse current measurement schemes. Challenges associated with the development of 2D material nanopores toward DNA sequencing are further analyzed, concentrating on lowering the noise levels, slowing down DNA translocation, and inhibiting DNA fluctuations inside the pores. Finally, we overview future directions of research that may expedite the emergence of proof-of-concept DNA sequencing with 2D material nanopores.

Key Parameters That Determine the Magnitude of the Decrease in Current in Nanopore Blockade Sensors

Nanopore blockade sensors were developed to address the challenges of sensitivity and selectivity for conventional nanopore sensors. To date, the parameters affecting the current of the sensor have not been elucidated. Herein, the impacts of nanopore size and charge and the shape, size, surface charge, and aggregation state of magnetic nanoparticles were assessed. The sensor was tolerant to all parameters contrary to predictions from electronic or geometric arguments on the current change. Theoretical models showed the greater importance of the polymers around nanoparticles and the access resistance of nanopores to the current, when compared with translocation-based nanopore sensors. The signal magnitude was dominated by the change in access resistance of ∼4.25 MΩ for all parameters, resulting in a robust system. The findings provide understandings of changes in current when nanopores are blocked, like in RNA trapping or nanopore blockade sensors, and are important for designing sensors based on nanopore blockades.

Direct Nanopore Sequencing of Individual Full Length tRNA Strands

We describe a method for direct tRNA sequencing using the Oxford Nanopore MinION. The principal technical advance is custom adapters that facilitate end-to-end sequencing of individual transfer RNA (tRNA) molecules at subnanometer precision. A second advance is a nanopore sequencing pipeline optimized for tRNA. We tested this method using purified E. coli tRNA^fMet, tRNA^Lys, and tRNA^Phe samples. 76-92% of individual aligned tRNA sequence reads were full length. As a proof of concept, we showed that nanopore sequencing detected all 43 expected isoacceptors in total E. coli MRE600 tRNA as well as isodecoders that further define that tRNA population. Alignment-based comparisons between the three purified tRNAs and their synthetic controls revealed systematic nucleotide miscalls that were diagnostic of known modifications. Systematic miscalls were also observed proximal to known modifications in total E. coli tRNA alignments, including a highly conserved pseudouridine in the T loop. This work highlights the potential of nanopore direct tRNA sequencing as well as improvements needed to implement tRNA sequencing for human healthcare applications.

Microscopic Screening of Cyclodextrin Channel Blockers by DiffusiOptoPhysiology

Blockers of pore-forming toxins (PFTs) limit bacterial virulence by blocking relevant channel proteins. However, screening of desired blockers from a large pool of candidate molecules is not a trivial task. Acknowledging its advantages of low cost, high throughput, and multiplicity, DiffusiOptoPhysiology (DOP), an emerging nanopore technique that visually monitors the states of individual channel proteins without using any electrodes, has shown its potential use in the screening of channel blockers. By taking different α-hemolysin (α-HL) mutants as model PFTs and different cyclodextrins as model blockers, we report direct screening of pore blockers solely by using fluorescence microscopy. Different combinations of pores and blockers were simultaneously evaluated on the same DOP chip and a single-molecule resolution is directly achieved. The entire chip is composed of low-cost and biocompatible materials, which is fully disposable after each use. Though only demonstrated with cyclodextrin derivatives and α-HL mutants, this proof of concept has also suggested its generality to investigate other pore-forming proteins.

Direct Nanopore Sequencing of Individual Full Length tRNA Strands

We describe a method for direct tRNA sequencing using the Oxford Nanopore MinION. The principal technical advance is custom adapters that facilitate end-to-end sequencing of individual transfer RNA (tRNA) molecules at subnanometer precision. A second advance is a nanopore sequencing pipeline optimized for tRNA. We tested this method using purified E. coli tRNA^fMet, tRNA^Lys, and tRNA^Phe samples. 76-92% of individual aligned tRNA sequence reads were full length. As a proof of concept, we showed that nanopore sequencing detected all 43 expected isoacceptors in total E. coli MRE600 tRNA as well as isodecoders that further define that tRNA population. Alignment-based comparisons between the three purified tRNAs and their synthetic controls revealed systematic nucleotide miscalls that were diagnostic of known modifications. Systematic miscalls were also observed proximal to known modifications in total E. coli tRNA alignments, including a highly conserved pseudouridine in the T loop. This work highlights the potential of nanopore direct tRNA sequencing as well as improvements needed to implement tRNA sequencing for human healthcare applications.

Nanopore Technology for the Application of Protein Detection

Protein is an important component of all the cells and tissues of the human body and is the material basis of life. Its content, sequence, and spatial structure have a great impact on proteomics and human biology. It can reflect the important information of normal or pathophysiological processes and promote the development of new diagnoses and treatment methods. However, the current techniques of proteomics for protein analysis are limited by chemical modifications, large sample sizes, or cumbersome operations. Solving this problem requires overcoming huge challenges. Nanopore single molecule detection technology overcomes this shortcoming. As a new sensing technology, it has the advantages of no labeling, high sensitivity, fast detection speed, real-time monitoring, and simple operation. It is widely used in gene sequencing, detection of peptides and proteins, markers and microorganisms, and other biomolecules and metal ions. Therefore, based on the advantages of novel nanopore single-molecule detection technology, its application to protein sequence detection and structure recognition has also been proposed and developed. In this paper, the application of nanopore single-molecule detection technology in protein detection in recent years is reviewed, and its development prospect is investigated.