Nanopore electric snapshots of an RNA tertiary folding pathway

Molecular sandwich-based DNAzyme catalytic reaction towards transducing efficient nanopore electrical detection of antigen proteins

Despite significant advances in nanopore nucleic acid sequencing and sensing, protein detection remains challenging due to the inherent complexity of protein molecular properties (i.e., net charges, polarity, molecular conformation & dimension) and sophisticated environmental parameters (i.e., biofluids), resulting in unsatisfactory electrical signal resolution for protein detection such as poor accessibility, selectivity and sensitivity. The selection of an appropriate electroanalytical approach is strongly desired which should be capable of offering easily detectable and readable signals regarding proteins particularly depending on the practical application. Herein, a molecular sandwich-based cooperative DNAzyme catalytic reaction nanopore detecting approach was designed. Specifically, this approach uses Mg2+ catalyzed DNAzyme (10-23) toward nucleic acids digestion for efficient antigen protein examination. The proposed strategy operates by initial formation of a molecular sandwich containing capture antibody-antigen-detection antibody for efficient entrapment of target proteins (herein taking the HIV p24 antigen for example) and immobilization on magnetic beads surfaces. After that, the DNAzyme was linked to the detection antibody via a biotin-streptavidin interaction. In the presence of Mg2+, the DNAzyme catalytic reaction was triggered to digest nucleic acid substrates and release unique cleavage fragments as reporters capable of transducing more easily detectable nucleic acids as a substitute for the complicated and hard to yield protein signals, in a nanopore. Notably, experimental validation confirms the detecting stability and sensitivity for the target antigen referenced with other antigen proteins, meanwhile it demonstrates a detection efficacy in a human serum environment at very low concentration (LoD ∼1.24 pM). This cooperative DNAzyme nanopore electroanalytical approach denotes an advance in protein examination, and may benefit in vitro testing of proteinic biomarkers for disease diagnosis and prognosis assessment.

Na+-Mg2+ ion effects on conformation and translocation dynamics of single-stranded RNA: Cooperation and competition

The nanopore-based translocation of a single-stranded RNA (ssRNA) in mixed salt solution has garnered increasing interest for its biological and technological significance. However, it is challenging to comprehensively understand the effects of the mixed ion species on the translocation dynamics due to their cooperation and competition, which can be directly reflected by the ion screening and neutralizing effects, respectively. In this study, Langevin dynamics simulation is employed to investigate the properties of ssRNA conformation and translocation in mixed Na+-Mg2+ ion environments. Simulation results reveal that the ion screening effect dominates the change in the ssRNA conformational size, the ion neutralizing effect controls the capture rate of the ssRNA by the nanopore, and both of them take charge of the different changes in translocation time of the ssRNA under various mixed ion environments. Under high Na+ ion concentration, as Mg2+ concentration increases, the ion neutralizing effect strengthens, weakening the driving force inside the nanopore, leading to longer translocation time. Conversely, at low Na+ concentration, an increase in Mg2+ concentration enhances the ion screening effect, aiding in faster translocation. Furthermore, these simulation results will be explained by quantitative analysis, advancing a deeper understanding of the complicated effects of the mixed Na+-Mg2+ ions.

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.

Oligomer Dynamics of LL-37 Truncated Fragments Probed by α-Hemolysin Pore and Molecular Simulations

Oligomerization of antimicrobial peptides (AMPs) is critical in their effects on pathogens. LL-37 and its truncated fragments are widely investigated regarding their structures, antimicrobial activities, and application, such as developing new antibiotics. Due to the small size and weak intermolecular interactions of LL-37 fragments, it is still elusive to establish the relationship between oligomeric states and antimicrobial activities. Here, an α-hemolysin nanopore, mass spectrometry (MS), and molecular dynamic (MD) simulations are used to characterize the oligomeric states of two LL-37 fragments. Nanopore studies provide evidence of trapping events related to the oligomer formation and provide further details on their stabilities, which are confirmed by MS and MD simulations. Furthermore, simulation results reveal the molecular basis of oligomer dynamics and states of LL-37 fragments. This work provides unique insights into the relationship between the oligomer dynamics of AMPs and their antimicrobial activities at the single-molecule level. The study demonstrates how integrating methods allows deciphering single molecule level understanding from nanopore sensing approaches.

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.

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.

Biomotors, viral assembly, and RNA nanobiotechnology: Current achievements and future directions

The International Society of RNA Nanotechnology and Nanomedicine (ISRNN) serves to further the development of a wide variety of functional nucleic acids and other related nanotechnology platforms. To aid in the dissemination of the most recent advancements, a biennial discussion focused on biomotors, viral assembly, and RNA nanobiotechnology has been established where international experts in interdisciplinary fields such as structural biology, biophysical chemistry, nanotechnology, cell and cancer biology, and pharmacology share their latest accomplishments and future perspectives. The results summarized here highlight advancements in our understanding of viral biology and the structure-function relationship of frame-shifting elements in genomic viral RNA, improvements in the predictions of SHAPE analysis of 3D RNA structures, and the understanding of dynamic RNA structures through a variety of experimental and computational means. Additionally, recent advances in the drug delivery, vaccine design, nanopore technologies, biomotor and biomachine development, DNA packaging, RNA nanotechnology, and drug delivery are included in this critical review. We emphasize some of the novel accomplishments, major discussion topics, and present current challenges and perspectives of these emerging fields.

Ribonucleic Acid Folding Prediction Based on Iterative Multiscale Simulation

RNA folding prediction is a challenge. Currently, many RNA folding models are coarse-grained (CG) with the potential derived from the known RNA structures. However, this potential is not suitable for modified and entirely new RNA. It is also not suitable for the folding simulation of RNA in the real cellular environment, including many kinds of molecular interactions. In contrast, our proposed model has the potential to address these issues, which is a multiscale simulation scheme based on all-atom (AA) force fields. We fit the CG force field using the trajectories generated by the AA force field and then iteratively perform molecular dynamics (MD) simulations of the two scales. The all-atom molecular dynamics (AAMD) simulation is mainly responsible for the correction of RNA structure, and the CGMD simulation is mainly responsible for efficient conformational sampling. On the basis of this scheme, we can successfully fold three RNAs belonging to a hairpin, a pseudoknot, and a four-way junction.

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.

Modeling Noncanonical RNA Base Pairs by a Coarse-Grained IsRNA2 Model

Noncanonical base pairs contribute crucially to the three-dimensional architecture of large RNA molecules; however, how to accurately model them remains an open challenge in RNA 3D structure prediction. Here, we report a promising coarse-grained (CG) IsRNA2 model to predict noncanonical base pairs in large RNAs through molecular dynamics simulations. By introducing a five-bead per nucleotide CG representation to reserve the three interacting edges of nucleobases, IsRNA2 accurately models various base-pairing interactions, including both canonical and noncanonical base pairs. A benchmark test indicated that IsRNA2 achieves a comparable performance to the atomic model in de novo modeling of noncanonical RNA structures. In addition, IsRNA2 was able to refine the 3D structure predictions for large RNAs in RNA-puzzle challenges. Finally, the graphics processing unit acceleration was introduced to speed up the sampling efficiency in IsRNA2 for very large RNA molecules. Therefore, the CG IsRNA2 model reported here offers a reliable approach to predict the structures and dynamics of large RNAs.

Nanopore-Based Single-Molecule Investigation of DNA Sequences with Potential to Form i-Motif Structures

i-Motifs are DNA secondary structures present in cytosine-rich sequences. These structures are formed in regulatory regions of the human genome and play key regulatory roles. The investigation of sequences capable of forming i-motif structures at the single-molecule level is highly important. In this study, we used α-hemolysin nanopores to systematically study a series of DNA sequences at the nanometer scale by providing structure-dependent signature current signals to gain in-sights into the i-motif DNA sequence and structural stability. Increasing the length of the cytosine tract in a range of 3-10 nucleobases resulted in a longer translocation time through the pore, indicating improved stability. Changing the loop sequence and length in the sequences did not affect the formation of the i-motif structure but changed its stability. Importantly, the application of all-atom molecular dynamics simulations revealed the structural morphology of all sequences. Based on these results, we postulated a folding rule for i-motif formation, suggesting that thousands of cytosine-rich sequences in the human genome might fold into i-motif structures. Many of these were found in locations where structure formation is likely to play regulatory roles. These findings provide insights into the application of nanopores as a powerful tool for discovering potential i-motif-forming sequences and lay a foundation for future studies exploring the biological roles of i-motifs.

Programmed -1 ribosomal frameshifting from the perspective of the conformational dynamics of mRNA and ribosomes

Programmed -1 ribosomal frameshifting (-1 PRF) is a translation mechanism that regulates the relative expression level of two proteins encoded on the same messenger RNA (mRNA). This regulation is commonly used by viruses such as coronaviruses and retroviruses but rarely by host human cells, and for this reason, it has long been considered as a therapeutic target for antiviral drug development. Understanding the molecular mechanism of -1 PRF is one step toward this goal. Minus-one PRF occurs with a certain efficiency when translating ribosomes encounter the specialized mRNA signal consisting of the frameshifting site and a downstream stimulatory structure, which impedes translocation of the ribosome. The impeded ribosome can still undergo profound conformational changes to proceed with translocation; however, some of these changes may be unique and essential to frameshifting. In addition, most stimulatory structures exhibit conformational dynamics and sufficient mechanical strength, which, when under the action of ribosomes, may in turn further promote -1 PRF efficiency. In this review, we discuss how the dynamic features of ribosomes and mRNA stimulatory structures may influence the occurrence of -1 PRF and propose a hypothetical frameshifting model that recapitulates the role of conformational dynamics.

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

Folding of RNA can produce elaborate tertiary structures, corresponding to their diverse roles in the regulation of biological activities. Direct observation of RNA structures at high resolution in their native form however remains a challenge. The large vestibule and the narrow constriction of a Mycobacterium smegmatis porin A (MspA) suggests a sensing mode called nanopore trapping/translocation, which clearly distinguishes between microRNA, small interfering RNA (siRNA), transfer RNA (tRNA) and 5 S ribosomal RNA (rRNA). To further profit from the acquired event characteristics, a custom machine learning algorithm is developed. Events from measurements with a mixture of RNA analytes can be automatically classified, reporting a general accuracy of ~93.4%. tRNAs, which possess a unique tertiary structure, report a highly distinguishable sensing feature, different from all other RNA types tested in this study. With this strategy, tRNAs from different sources are measured and a high structural conservation across different species is observed in single molecule.

Translocation of a looped polymer threading through a nanopore

Recent experiments reported that the complicated translocation dynamics of a looped DNA chain through a nanopore can be detected by ionic current blockade profiles. Inspired by the experimental results, we systematically study the translocation dynamics of a looped polymer, formed by three building blocks of a loop in the middle and two tails of the same length connected with the loop, by using Langevin dynamics simulations. Based on two entering modes (tail-leading and loop-leading) and three translocation orders (loop-tail-tail, tail-loop-tail, and tail-tail-loop), the translocation of the looped polymer is classified into six translocation pathways, corresponding to different current blockade profiles. The probabilities of the six translocation pathways are dependent on the loop length, polymer length, and pore radius. Moreover, the translocation times of the entire polymer and the loop are investigated. We find that the two translocation times show different dependencies on the translocation pathways and on the lengths of the loop and the entire polymer.

IsRNA1: De Novo Prediction and Blind Screening of RNA 3D Structures

Modeling structures and functions of large ribonucleic acid (RNAs) especially with complicated topologies is highly challenging due to the inefficiency of large conformational sampling and the presence of complicated tertiary interactions. To address this problem, one highly promising approach is coarse-grained modeling. Here, following an iterative simulated reference state approach to decipher the correlations between different structural parameters, we developed a potent coarse-grained RNA model named as IsRNA1 for RNA studies. Molecular dynamics simulations in the IsRNA1 can predict the native structures of small RNAs from a sequence and fold medium-sized RNAs into near-native tertiary structures with the assistance of secondary structure constraints. A large-scale benchmark test on RNA 3D structure prediction shows that IsRNA1 exhibits improved performance for relatively large RNAs of complicated topologies, such as large stem-loop structures and structures containing long-range tertiary interactions. The advantages of IsRNA1 include the consideration of the correlations between the different structural variables, the appropriate characterization of canonical base-pairing and base-stacking interactions, and the better sampling for the backbone conformations. Moreover, a blind screening protocol was developed based on IsRNA1 to identify good structural models from a pool of candidates without prior knowledge of the native structures.

RNA Pore Translocation with Static and Periodic Forces: Effect of Secondary and Tertiary Elements on Process Activation and Duration

We use MD simulations to study the pore translocation properties of a pseudoknotted viral RNA. We consider the 71-nucleotide-long xrRNA from the Zika virus and establish how it responds when driven through a narrow pore by static or periodic forces applied to either of the two termini. Unlike the case of fluctuating homopolymers, the onset of translocation is significantly delayed with respect to the application of static driving forces. Because of the peculiar xrRNA architecture, activation times can differ by orders of magnitude at the two ends. Instead, translocation duration is much smaller than activation times and occurs on time scales comparable at the two ends. Periodic forces amplify significantly the differences at the two ends, for both activation times and translocation duration. Finally, we use a waiting-times analysis to examine the systematic slowing downs in xrRNA translocations and associate them to the hindrance of specific secondary and tertiary elements of xrRNA. The findings provide a useful reference to interpret and design future theoretical and experimental studies of RNA translocation.

Tertiary RNA Folding-Targeted Drug Screening Strategy Using a Protein Nanopore

Bacterial riboswitch RNAs are attractive targets for novel antibiotics against antibiotic-resistant superbacteria. Their binding to cognate metabolites is essential for the regulation of bacterial gene expression. Despite the importance of RNAs as therapeutic targets, the development of RNA-targeted, small-molecule drugs is limited by current biophysical methods. Here, we monitored the specific interaction between the adenine-sensing riboswitch aptamer domain (ARS) and adenine at the single-molecule level using α-hemolysin (αHL) nanopores. During adenine-induced tertiary folding, adenine-bound ARS intermediates exhibited characteristic nanopore events, including a two-level ionic current blockade and a ∼ 5.6-fold longer dwell time than that of free RNA. In a proof-of-concept experiment, tertiary RNA folding-targeted drug screening was performed using a protein nanopore, which resulted in the discovery of three new ARS-targeting hit compounds from a natural compound library. Taken together, these results reveal that αHL nanopores are a valuable platform for ultrasensitive, label-free, and single-molecule-based drug screening against therapeutic RNA targets.

Reversible photo-regulation on the folding/unfolding of telomere G-quadruplexes with solid-state nanopores

The formation of G-quadruplexes (G4) in human telomere and other important biological regions inhibits the replication and transcription of DNA, thereby influencing further cell proliferation. The investigation of G4 formation and unfolding is vital for understanding their modulation in biological processes and life science. Photo regulation is a facile and sensitive approach for monitoring the structures of biomacromolecules and material surface properties. The nanopore-based technique is also prevalent for label-free single-molecule characterization with high accuracy. This study provides a combination of solid-state nanopore technology with light-switch as a platform for the modulation of human telomere G4 formation and splitting under switchable light exposure. The introduction of molecular switch, namely azobenzene moiety at different positions of the DNA sequence influences the formation and stability of G4. Three azobenzenes immobilized on each of the G-quartet plane (hTelo-3azo-p) or four azobenzenes on the same plane (hTelo-4azo-4p) of the human telomere G4 sequence realized the reversible control of G4 folding/unfolding at the temporal scale upon photo regulation, and the formation and splitting of G4 with hTelo-4azo-4p is slower and not thorough compared to that with hTelo-3azo-p due to the coplanar steric hindrance. Moreover, the G4 formation recorded with the combined nanopore and photo-responsive approach was also characterized with fluorescence, and the variation in the fluorescence intensity of the NMM and G4 complex exhibited a different tendency under reverse light irradiation due to the distinct interactions of NMM with the azobenzene-modified G4. Our study demonstrated a controllable and sensitive way for the manipulation of G4 structures, which will be inspiring for the intervention of G4-related cell senescence, cancer diagnosis and drug exploration.

A Bayes-inspired theory for optimally building an efficient coarse-grained folding force field

Because of their potential utility in predicting conformational changes and assessing folding dynamics, coarse-grained (CG) RNA folding models are appealing for rapid characterization of RNA molecules. Previously, we reported the iterative simulated RNA reference state (IsRNA) method for parameterizing a CG force field for RNA folding, which consecutively updates the simulation force field to reflect marginal distributions of folding coordinates in the structure database and extract various energy terms. While the IsRNA model was validated by showing close agreement between the IsRNA-simulated and experimentally observed distributions, here, we expand our theoretical understanding of the model and, in doing so, improve the parameterization process to optimize the subset of included folding coordinates, which leads to accelerated simulations. Using statistical mechanical theory, we analyze the underlying, Bayesian concept that drives parameterization of the energy function, providing a general method for developing predictive, knowledge-based, polymer force fields on the basis of limited data. Furthermore, we propose an optimal parameterization procedure, based on the principal of maximum entropy.

Ribosome Fingerprinting with a Solid-State Nanopore

Nanopores hold great potential for the analysis of complex biological molecules at the single-entity level. One particularly interesting macromolecular machine is the ribosome, responsible for translating mRNAs into proteins. In this study, we use a solid-state nanopore to fingerprint 80S ribosomes and polysomes from a human neuronal cell line andDrosophila melanogaster cultured cells and ovaries. Specifically, we show that the peak amplitude and dwell time characteristics of 80S ribosomes are distinct from polysomes and can be used to discriminate ribosomes from polysomes in mixed samples. Moreover, we are able to distinguish large polysomes, containing more than seven ribosomes, from those containing two to three ribosomes, and demonstrate a correlation between polysome size and peak amplitude. This study highlights the application of solid-state nanopores as a rapid analytical tool for the detection and characterization of ribosomal complexes.

Molecular mechanisms underlying the extreme mechanical anisotropy of the flaviviral exoribonuclease-resistant RNAs (xrRNAs)

Mechanical anisotropy is an essential property for many biomolecules to assume their structures, functions and applications, however, the mechanisms for their direction-dependent mechanical responses remain elusive. Herein, by using a single-molecule nanopore sensing technique, we explore the mechanisms of directional mechanical stability of the xrRNA1 RNA from ZIKA virus (ZIKV), which forms a complex ring-like architecture. We reveal extreme mechanical anisotropy in ZIKV xrRNA1 which highly depends on Mg²⁺ and the key tertiary interactions. The absence of Mg²⁺ and disruption of the key tertiary interactions strongly affect the structural integrity and attenuate mechanical anisotropy. The significance of ring structures in RNA mechanical anisotropy is further supported by steered molecular dynamics simulations in combination with force distribution analysis. We anticipate the ring structures can be used as key elements to build RNA-based nanostructures with controllable mechanical anisotropy for biomaterial and biomedical applications.

Modeling Loop Composition and Ion Concentration Effects in RNA Hairpin Folding Stability

The ability to accurately predict RNA hairpin structure and stability for different loop sequences and salt conditions is important for understanding, modeling, and designing larger RNA folds. However, traditional RNA secondary structure models cannot treat loop-sequence and ionic effects on RNA hairpin folding. Here, we describe a general, three-dimensional (3D) conformation-based computational method for modeling salt concentration-dependent conformational distributions and the detailed 3D structures for a set of three RNA hairpins that contain a variable, 15-nucleotide loop sequence. For a given RNA sequence, the new, to our knowledge, method integrates a Vfold2D two-dimensional structure folding model with IsRNA coarse-grained molecular dynamics 3D folding simulations and Monte Carlo tightly bound ion estimations of ion-mediated electrostatic interactions. The model predicts free-energy landscapes for the different RNA hairpin-forming sequences with variable salt conditions. The theoretically predicted results agree with the experimental fluorescence measurements, validating the strategy. Furthermore, the theoretical model goes beyond the experimental results by enabling in-depth 3D structural analysis, revealing energetic mechanisms for the sequence- and salt-dependent folding stability. Although the computational framework presented here is developed for RNA hairpin systems, the general method may be applied to investigate other RNA systems, such as multiway junctions or pseudoknots in mixed metal ion solutions.

Measuring temperature effects on nanobubble nucleation via a solid-state nanopore

In this study, we designed SiN_X solid-state nanopores to detect the temperature effect on the hydrogen nanobubble formation. Here, we integrated a temperature controller with the highly sensitive nanopore. As the temperature decreases from 25 °C to 5 °C, the occurrence of the nanobubble nucleation inside a 12.3 nm SiN_X nanopore confined space decreased from 102 s^-1 to 23 s^-1, and the life-time of nanobubbles increased from 1.16 ms to 4.78 ms. The results further gave the activation energy for nanobubble nucleation which was 8.1 × 10^-20 J with a 12.3 nm SiN_X nanopore. Our method provides an efficient analytical tool for revealing the temperature-dependent nanobubble nucleation, which further benefits the fundamental understanding of nanobubble nucleation.

Label-free single-molecule identification of telomere G-quadruplexes with a solid-state nanopore sensor

Telomere sequences can spontaneously form G-quadruplexes (G4) in the presence of some cations. In view of their relevance to genetic processes and potential as therapeutic-targets, hitherto, a wealth of conventional techniques have been reported for interrogation of G4 conformation diversity and corresponding folding kinetics, most of which are limited in precision and sensitivity. This work introduces a label-free solid-state nanopore (SSN) approach for the determination of inter-, intra- and tandem molecular G4 with distinct base permutation in various cation buffers with a tailored aperture and meanwhile captures the single-molecule G4 folding process. SSN translocation properties elucidated that both inter- and intramolecular G4 generated higher current blockage with longer duration than flexible homopolymer nucleotide, and intramolecular G4 are structurally more stable with higher event frequency and longer blockage time than intermolecular ones; base arrangement played weak role in translocation behaviors; the same sequences with one, two and three G4 skeletons displayed an increase in current blockage and a gradual extension in dwell time with the increase of molecule size recorded in the same nanopore. We observed the conformation change of single-molecule G4 which indicated the existence of folding/unfolding equilibration in nanopore, and real-time test suggested a gradual formation of G4 with time. Our results could provide a continued and improved understanding of the underlying relevance of structural stability and G4 folding process by utilizing SSN platform which exhibits strategic potential advances over the other methods with high spatial and temporal resolution.

Nanopore detection of single-molecule G-quadruplexes.

A Nanopore Phosphorylation Sensor for Single Oligonucleotides and Peptides

The phosphorylation of oligonucleotides and peptides plays a critical role in regulating virtually all cellular processes. To fully understand these complex and fundamental regulatory pathways, the cellular phosphorylate changes of both oligonucleotides and peptides should be simultaneously identified and characterized. Here, we demonstrated a single-molecule, high-throughput, label-free, general, and one-step aerolysin nanopore method to comprehensively evaluate the phosphorylation of both oligonucleotide and peptide substrates. By virtue of electrochemically confined effects in aerolysin, our results show that the phosphorylation accelerates the traversing speed of a negatively charged substrate for about hundreds of time while significantly enhances the translocation frequency of a positively charged substrate. Thereby, the kinase/phosphatase activity could be directly measured with the aerolysin nanopore from the characteristically dose-dependent event frequency of the substrates. By using this straightforward approach, a model T₄ oligonucleotide kinase (PNK) further achieved the nanopore evaluation of its phosphatase activity and real-time monitoring of its phosphatase-catalyzed dephosphorylation at a single-molecule level. Our study provides a step forward to nanopore enzymology for analyzing the phosphorylation of both oligonucleotides and peptides with significant feasibility in fundamental biochemical researches, clinical diagnosis, and kinase/phosphatase-targeted drug discovery.

Single Locked Nucleic Acid-enhanced nanopore genetic discrimination of pathogenic serotypes and cancer driver mutations

Rapid and accurate detection of single-nucleotide polymorphism (SNP) in pathogenic mutants is crucial for broad fields from food safety monitoring to disease diagnostics and prognosis. Here, we developed a nanopore single-molecule sensor, coupled with the locked nucleic acid (LNA) technique, to accurately discriminate SNPs for detection of Shiga toxin producing Escherichia coli (STEC) O157:H7 pathogen serotype, and cancer-derived driver mutations EGFR L858R and KRAS G12D. This sensitive method, with a simplified, low cost, easy-to-operate LNA design, can be applied in food science and medical detection that need rapid and accurate determination of genetic variations.

Normal expression of KCNJ11 is maintained by the G-quadruplex

MicroRNAs affect various pathological pathways by binding to multiple target mRNAs. Recently, it was reported that eukaryotic RNA G-quadruplexes were enriched in mRNA 3'-UTR, where microRNAs can also bind. To determine the roles of the G-quadruplex within mRNA 3'-UTR in microRNA binding sites, a bioinformatics approach was utilized to identify candidate microRNA target mRNAs with potential G-quadruplex formation. Circular dichroism spectrometry demonstrated the formation of RNA G-quadruplexes in vitro in candidate G-rich sequences. Mutated guanosines that are critical for G-quadruplex formation significantly decreased luciferase activities. Moreover, a G-quadruplex ligand TMPyP4 was used to destabilize the KCNJ11 RNA G-quadruplex in cardiomyocytes, resulting in binding of the microRNA to mRNA and subsequent suppression of KCNJ11 expression. In conclusion, our study showed that the G-quadruplex structure affects microRNA binding to its target mRNA. Thus, our study reveals a novel mechanism for G-quadruplex-dependent regulation of microRNA-mRNA interaction, which is essential to maintain normal gene expression.

An investigation of solid-state nanopores on label-free metal-ion signalling via the transition of RNA-cleavage DNAzyme and the hybridization chain reaction

Recent advances have proven solid-state nanopores as a powerful analysis platform that enables label-free and separation-free single-molecule analysis. However, the relatively low resolution still limits its application because many chemicals or targets with small sizes could not be recognized in a label-free condition. In this paper, we provide a possible solution that uses solid-state nanopores for small species signaling via the transition of huge DNA assembly products. DNAzyme responding to metal ions and the hybridization chain reaction (HCR) generating nanopore-detectable dsDNA concatamers are used as the transition model set. By the two-step DNAzyme-HCR transition, Pb2+ that was too tiny to be sensed was successfully recognized by the nanopore. The whole process happened in a completely homogeneous solution without any chemical modification. During condition optimization, we also discussed one possible application challenge that may affect the HCR signal-background distinction. Solid-state nanopores provide a potential solution to this challenge due to its ability to profile product length or even 3D structure information.

Translocation intermediates of ubiquitin through an α-hemolysin nanopore: implications for detection of post-translational modifications

Nanopore based sensors constitute a promising approach to single molecule protein characterization being able, in principle, to detect sequences, structural elements and folding states of proteins and polypeptide chains. In narrow nanopores, one of the open issues concerns the coupling between unfolding and translocation. Here, we studied the ubiquitin translocation in an α-hemolysin nanopore, the most widely used pore for nanopore sensing, via all-atom molecular dynamics simulations. We completely characterize the co-translocational unfolding pathway finding that robust translocation intermediates are associated with the rearrangement of secondary structural elements, as also confirmed by coarse grained simulations. An interesting recurrent pattern is the clogging of the α-hemolysin constriction by an N-terminal β-hairpin. This region of ubiquitin is the target of several post-translational modifications. We propose a strategy to detect post-translational modifications at the N-terminal using the α-hemolysin nanopore based on the comparison of the co-translocational unfolding signals associated with modified and unmodified proteins.

Exploration of solid-state nanopores in characterizing reaction mixtures generated from a catalytic DNA assembly circuit

Recent advances have proven that using solid-state nanopores is a promising single molecular technique to enrich the DNA assembly signaling library. Other than using them for distinguishing structures, here we innovatively adapt solid-state nanopores for use in analyzing assembly mixtures, which is usually a tougher task for either traditional characterization techniques or nanopores themselves. A trigger induced DNA step polymerization (SP-CHA), producing three-way-DNA concatemers, is designed as a model. Through counting and integrating the translocation-induced current block when each concatemer passes through a glass conical glass nanopore, we propose an electrophoresis-gel like, but homogeneous, quantitative method that can comprehensively profile the "base-pair distribution" of SP-CHA concatemer mixtures. Due to the higher sensitivity, a number of super long concatemers that were previously difficult to detect via gel electrophoresis are also revealed. These ultra-concatemers, longer than 2 kbp, could provide a much enhanced signal-to-noise ratio for nanopores and are thus believed to be more accurate indicators for the existence of a trigger, which may be of benefit for further applications, such as molecular machines or biosensors.

Trapped and non-trapped polymer translocations through a spherical pore

The polymer translocation through a spherical pore is studied using the Langevin dynamics simulation. The translocation events are classified into two types: one is the trapped translocation in which the entire polymer is trapped in the pore and the other is the non-trapped translocation where the pore cannot hold the whole polymer. We find that the trapped translocation is favored at large spheres and small external voltages. However, the monomer-pore attraction would lead to the non-monotonic behavior of the trapped translocation possibility out of all translocation events. Moreover, both the trapped and non-trapped translocation times are dependent on the polymer length, pore size, external voltage, and the monomer-pore attraction. There exist two pathways for the polymer in the trapped translocation: an actively trapped pathway for the polymer trapped in the pore before the head monomer arrives at the pore exit, and a passively trapped pathway for the polymer trapped in the pore while the head monomer is struggling to move out of the pore. The studies of trapped pathways can provide a deep understanding of the polymer translocation behavior.

Challenges and approaches to predicting RNA with multiple functional structures

The revolution in sequencing technology demands new tools to interpret the genetic code. As in vivo transcriptome-wide chemical probing techniques advance, new challenges emerge in the RNA folding problem. The emphasis on one sequence folding into a single minimum free energy structure is fading as a new focus develops on generating RNA structural ensembles and identifying functional structural features in ensembles. This review describes an efficient combinatorially complete method and three free energy minimization approaches to predicting RNA structures with more than one functional fold, as well as two methods for analysis of a thermodynamics-based Boltzmann ensemble of structures. The review then highlights two examples of viral RNA 3'-UTR regions that fold into more than one conformation and have been characterized by single molecule fluorescence energy resonance transfer or NMR spectroscopy. These examples highlight the different approaches and challenges in predicting structure and function from sequence for RNA with multiple biological roles and folds. More well-defined examples and new metrics for measuring differences in RNA structures will guide future improvements in prediction of RNA structure and function from sequence.

Predicting 3D structure and stability of RNA pseudoknots in monovalent and divalent ion solutions

RNA pseudoknots are a kind of minimal RNA tertiary structural motifs, and their three-dimensional (3D) structures and stability play essential roles in a variety of biological functions. Therefore, to predict 3D structures and stability of RNA pseudoknots is essential for understanding their functions. In the work, we employed our previously developed coarse-grained model with implicit salt to make extensive predictions and comprehensive analyses on the 3D structures and stability for RNA pseudoknots in monovalent/divalent ion solutions. The comparisons with available experimental data show that our model can successfully predict the 3D structures of RNA pseudoknots from their sequences, and can also make reliable predictions for the stability of RNA pseudoknots with different lengths and sequences over a wide range of monovalent/divalent ion concentrations. Furthermore, we made comprehensive analyses on the unfolding pathway for various RNA pseudoknots in ion solutions. Our analyses for extensive pseudokonts and the wide range of monovalent/divalent ion concentrations verify that the unfolding pathway of RNA pseudoknots is mainly dependent on the relative stability of unfolded intermediate states, and show that the unfolding pathway of RNA pseudoknots can be significantly modulated by their sequences and solution ion conditions.

Single Locked Nucleic Acid-Enhanced Nanopore Genetic Discrimination of Pathogenic Serotypes and Cancer Driver Mutations

Accurate and rapid detection of single-nucleotide polymorphism (SNP) in pathogenic mutants is crucial for many fields such as food safety regulation and disease diagnostics. Current detection methods involve laborious sample preparations and expensive characterizations. Here, we investigated a single locked nucleic acid (LNA) approach, facilitated by a nanopore single-molecule sensor, to accurately determine SNPs for detection of Shiga toxin producing Escherichia coli (STEC) serotype O157:H7, and cancer-derived EGFR L858R and KRAS G12D driver mutations. Current LNA applications that require incorporation and optimization of multiple LNA nucleotides. But we found that in the nanopore system, a single LNA introduced in the probe is sufficient to enhance the SNP discrimination capability by over 10-fold, allowing accurate detection of the pathogenic mutant DNA mixed in a large amount of the wild-type DNA. Importantly, the molecular mechanistic study suggests that such a significant improvement is due to the effect of the single-LNA that both stabilizes the fully matched base-pair and destabilizes the mismatched base-pair. This sensitive method, with a simplified, low cost, easy-to-operate LNA design, could be generalized for various applications that need rapid and accurate identification of single-nucleotide variations.

Remote Activation of a Nanopore for High-Performance Genetic Detection Using a pH Taxis-Mimicking Mechanism

Aerolysin protein pore has been widely used for sensing peptides and proteins. However, only a few groups explored this nanopore for nucleic acids detection. The challenge is the extremely low capture efficiency for nucleic acids (>10 bases), which severely lowers the sensitivity of an aerolysin-based genetic biosensor. Here we reported a simple and easy-to-operate approach to noncovalently transform aerolysin into a highly nucleic acids-sensitive nanopore. Through a remote pH-modulation mechanism, we simply lower the pH on one side of the pore, then aerolysin is immediately "activated" and enabled to capture target DNA/RNA efficiently from the opposite side of the pore. This mechanism also decelerates DNA translocation, a desired property for sequencing and gene detection, allowing temporal separation of DNAs in different lengths. This method provides insight into the nanopore engineering for biosensing, making aerolysin applicable in genetic and epigenetic detections of long nucleic acids.