How low can you go? Short-read polishing of Oxford Nanopore bacterial genome assemblies.

It is now possible to assemble near-perfect bacterial genomes using Oxford Nanopore Technologies (ONT) long reads, but short-read polishing is usually required for perfection. However, the effect of short-read depth on polishing performance is not well understood. Here, we introduce Pypolca (with default and careful parameters) and Polypolish v0.6.0 (with a new careful parameter). We then show that: (1) all polishers other than Pypolca-careful, Polypolish-default and Polypolish-careful commonly introduce false-positive errors at low read depth; (2) most of the benefit of short-read polishing occurs by 25× depth; (3) Polypolish-careful almost never introduces false-positive errors at any depth; and (4) Pypolca-careful is the single most effective polisher. Overall, we recommend the following polishing strategies: Polypolish-careful alone when depth is very low (<5×), Polypolish-careful and Pypolca-careful when depth is low (5-25×), and Polypolish-default and Pypolca-careful when depth is sufficient (>25×).

Specific Small-Molecule Detection Using Designed Nucleic Acid Nanostructure Carriers and Nanopores.

In the realm of nanopore sensor technology, an enduring challenge lies in achieving the discerning detection of small biomolecules with a sufficiently high signal-to-noise ratio. This study introduces a method for reliably quantifying the concentration of target small molecules, utilizing tetrahedral DNA nanostructures as surrogates for the captured molecules through a magnetic-bead-based competition substitution mechanism. Magnetic Fe3O4-DNA tetrahedron nanoparticles (MNPs) are incorporated into a nanopore electrochemical system for small-molecule sensing. In the presence of the target, the DNA tetrahedron, featuring an aptamer tail acting as a molecular carrier, detaches from the MNPs due to aptamer deformation. Following removal of the MNPs, the DNA tetrahedron bound to the target traversed the nanopore by applying a positive potential. This approach exhibits various advantages, including heightened sensitivity, selectivity, an improved signal-to-noise ratio (SNR), and robust anti-interference capabilities. Our findings demonstrate that this innovative methodology has the potential to significantly enhance the sensing of various small-molecule targets by nanopores, thereby advancing the sensitivity and dynamic range. This progress holds promise for the development of precise clinical diagnostic tools.

Determination of Acetylamantadine by γ-Cyclodextrin-Assisted α-HL Nanopore for Potential Cancer Prediagnosis.

The high expression of Spermidine/spermine N1-acetyltransferase (SSAT-1) is an important indicator in early cancer diagnosis. Here, we developed a nanopore-based methodology with γ-cyclodextrin as an adaptor to detect and quantify acetylamantadine, the specific SSAT-1-catalyzed product from amantadine, to accordingly reflect the activity of SSAT-1. We employ γ-cyclodextrin and report that amantadine cannot cause any secondary signals in γ-cyclodextrin-assisted α-HL nanopore, while its acetylation product, acetylamantadine, does. This allows γ-cyclodextrin to practically detect acetylamantadine in the interference of excessive amantadine, superior to the previously reported ß-cyclodextrin. The quantification of acetylamantadine was not interfered with even a 50-fold amantadine and displayed no interference in artificial urine sample analysis, which indicates the good feasibility of this nanopore-based methodology in painless cancer prediagnosis. In addition, the discrimination mechanism is also explored by 2-D nuclear magnetic resonance (NMR) and nanopore experiments with a series of adamantane derivatives with different hydrophilic and hydrophobic groups. We found that both the hydrophobic region matching effect and hydrophilic interactions play a synergistic effect in forming a host-guest complex to further generate the characteristic signals, which may provide insights for the subsequent design and study of drug-cyclodextrin complexes.

The Applications of Nanopore Sequencing Technology in Animal and Human Virus Research.

In recent years, an increasing number of viruses have triggered outbreaks that pose a severe threat to both human and animal life, as well as caused substantial economic losses. It is crucial to understand the genomic structure and epidemiology of these viruses to guide effective clinical prevention and treatment strategies. Nanopore sequencing, a third-generation sequencing technology, has been widely used in genomic research since 2014. This technology offers several advantages over traditional methods and next-generation sequencing (NGS), such as the ability to generate ultra-long reads, high efficiency, real-time monitoring and analysis, portability, and the ability to directly sequence RNA or DNA molecules. As a result, it exhibits excellent applicability and flexibility in virus research, including viral detection and surveillance, genome assembly, the discovery of new variants and novel viruses, and the identification of chemical modifications. In this paper, we provide a comprehensive review of the development, principles, advantages, and applications of nanopore sequencing technology in animal and human virus research, aiming to offer fresh perspectives for future studies in this field.

Evaluation of the accuracy of bacterial genome reconstruction with Oxford Nanopore R10.4.1 long-read-only sequencing.

Whole-genome reconstruction of bacterial pathogens has become an important tool for tracking transmission and antimicrobial resistance gene spread, but highly accurate and complete assemblies have largely only historically been achievable using hybrid long- and short-read sequencing. We previously found the Oxford Nanopore Technologies (ONT) R10.4/kit12 flowcell/chemistry produced improved assemblies over the R9.4.1/kit10 combination, however long-read only assemblies contained more errors compared to Illumina-ONT hybrid assemblies. ONT have since released an R10.4.1/kit14 flowcell/chemistry upgrade and recommended the use of Bovine Serum Albumin (BSA) during library preparation, both of which reportedly increase accuracy and yield. They have also released updated basecallers trained using native bacterial DNA containing methylation sites intended to fix systematic basecalling errors, including common adenosine (A) to guanine (G) and cytosine (C) to thymine (T) substitutions. To evaluate these improvements, we successfully sequenced four bacterial reference strains, namely Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa and Staphylococcus aureus, and nine genetically diverse E. coli bloodstream infection-associated isolates from different phylogroups and sequence types, both with and without BSA. These sequences were de novo assembled and compared against Illumina-corrected reference genomes. In this small evaluation of 13 isolates we found that nanopore long-read-only R10.4.1/kit 14 assemblies with updated basecallers trained using bacterial methylated DNA produce accurate assemblies with ≥40×depth, sufficient to be cost-effective compared with hybrid ONT/Illumina sequencing in our setting.

Chemical Annealing Restructures RNA for Nanopore Detection.

RNA is a key biochemical marker, yet its chemical instability and complex secondary structure hamper its integration into DNA nanotechnology-based sensing platforms. Relying on the denaturation of the native RNA structure using urea, we show that restructured DNA/RNA hybrids can readily be prepared at room temperature. Using solid-state nanopore sensing, we demonstrate that the structures of our DNA/RNA hybrids conform to the design at the single-molecule level. Employing this chemical annealing procedure, we mitigate RNA self-cleavage, enabling the direct detection of restructured RNA molecules for biosensing applications.

Transfer learning enables identification of multiple types of RNA modifications using nanopore direct RNA sequencing.

Nanopore direct RNA sequencing (DRS) has emerged as a powerful tool for RNA modification identification. However, concurrently detecting multiple types of modifications in a single DRS sample remains a challenge. Here, we develop TandemMod, a transferable deep learning framework capable of detecting multiple types of RNA modifications in single DRS data. To train high-performance TandemMod models, we generate in vitro epitranscriptome datasets from cDNA libraries, containing thousands of transcripts labeled with various types of RNA modifications. We validate the performance of TandemMod on both in vitro transcripts and in vivo human cell lines, confirming its high accuracy for profiling m6A and m5C modification sites. Furthermore, we perform transfer learning for identifying other modifications such as m7G, Ψ, and inosine, significantly reducing training data size and running time without compromising performance. Finally, we apply TandemMod to identify 3 types of RNA modifications in rice grown in different environments, demonstrating its applicability across species and conditions. In summary, we provide a resource with ground-truth labels that can serve as benchmark datasets for nanopore-based modification identification methods, and TandemMod for identifying diverse RNA modifications using a single DRS sample.

Detection of Glutamate Decarboxylase Antibodies and Simultaneous Multi-Molecular Translocation Exploration by Glass Nanopores.

Glutamic acid decarboxylase antibody (GADAb) has emerged as a significant biomarker for clinical diagnosis and prognosis in type 1 diabetes (T1D). In this study, we investigated the potential utilization of glass capillary solid-state nanopores as a cost-effective and easily preparable platform for the detection of individual antigens, antibodies, and antigen-antibody complexes without necessitating any modifications to the nanopores. Our findings revealed notable characteristic variations in the translocation events of glutamic acid decarboxylase (GAD65) through nanopores under different voltage conditions, discovered that anomalous phenomenon of protein translocation events increasing with voltage may potentially be caused by the crowding of multiple proteins in the nanopores, and demonstrated that there are multiple components in the polyclonal antibodies (GADAb-poly). Furthermore, we achieved successful differentiation between GAD65, GADAb, and GADAb-GAD65 complexes. These results offer promising prospects for the development of a rapid and reliable GADAb detection method, which holds the potential to be applied in patient serum samples, thereby facilitating a label-free, cost-effective, and early diagnosis of type I diabetes.

Nm-Nano: a machine learning framework for transcriptome-wide single-molecule mapping of 2´-O-methylation (Nm) sites in nanopore direct RNA sequencing datasets.

2´-O-methylation (Nm) is one of the most abundant modifications found in both mRNAs and noncoding RNAs. It contributes to many biological processes, such as the normal functioning of tRNA, the protection of mRNA against degradation by the decapping and exoribonuclease (DXO) protein, and the biogenesis and specificity of rRNA. Recent advancements in single-molecule sequencing techniques for long read RNA sequencing data offered by Oxford Nanopore technologies have enabled the direct detection of RNA modifications from sequencing data. In this study, we propose a bio-computational framework, Nm-Nano, for predicting the presence of Nm sites in direct RNA sequencing data generated from two human cell lines. The Nm-Nano framework integrates two supervised machine learning (ML) models for predicting Nm sites: Extreme Gradient Boosting (XGBoost) and Random Forest (RF) with K-mer embedding. Evaluation on benchmark datasets from direct RNA sequecing of HeLa and HEK293 cell lines, demonstrates high accuracy (99% with XGBoost and 92% with RF) in identifying Nm sites. Deploying Nm-Nano on HeLa and HEK293 cell lines reveals genes that are frequently modified with Nm. In HeLa cell lines, 125 genes are identified as frequently Nm-modified, showing enrichment in 30 ontologies related to immune response and cellular processes. In HEK293 cell lines, 61 genes are identified as frequently Nm-modified, with enrichment in processes like glycolysis and protein localization. These findings underscore the diverse regulatory roles of Nm modifications in metabolic pathways, protein degradation, and cellular processes. The source code of Nm-Nano can be freely accessed at https://github.com/Janga-Lab/Nm-Nano.

High-Resolution and Low-Noise Single-Molecule Sensing with Bio-Inspired Solid-State Nanopores.

Solid-state nanopores have been extensively explored as single-molecule sensors, bearing the potential for the sequencing of DNA. Although they offer advantages in terms of high mechanical robustness, tunable geometry, and compatibility with existing semiconductor fabrication techniques in comparison with their biological counterparts, efforts to sequence DNA with these nanopores have been hampered by insufficient spatial resolution and high noise in the measured ionic current signal. Here we show that these limitations can be overcome by the use of solid-state nanopores featuring a thin, narrow constriction as the sensing region, inspired by biological protein nanopores that have achieved notable success in DNA sequencing. Our extensive molecular dynamics simulations show that these bio-inspired nanopores can provide high spatial resolution equivalent to 2D material nanopores and, meanwhile, significantly inhibit noise levels. A theoretical model is also provided to assess the performance of the bio-inspired nanopore, which could guide its design and optimization.

Precise Structural Analysis of Neutral Glycans Using Aerolysin Mutant T240R Nanopore.

Glycans play vital roles in nearly all life processes of multicellular organisms, and understanding these activities is inseparable from elucidating the biological significance of glycans. However, glycan research has lagged behind that of DNA and protein due to the challenges posed by structural heterogeneity and isomerism (i.e., structures with equal molecular weights) the lack of high-efficiency structural analysis techniques. Nanopore technology has emerged as a sensitive single-molecule biosensor, shining a light on glycan analysis. However, a significant number of glycans are small and uncharged, making it challenging to elicit identifiable nanopore signals. Here we introduce a R-binaphthyl tag into glycans, which enhances the cation-π interaction between the derivatized glycan molecules and the nanopore interface, enabling the detection of neutral glycans with an aerolysin nanopore. This approach allows for the distinction of di-, tri-, and tetrasaccharides with monosaccharide resolution and has the potential for group discrimination, the monitoring of enzymatic transglycosylation reactions. Notably, the aerolysin mutant T240R achieves unambiguous identification of six disaccharide isomers, trisaccharide and tetrasaccharide linkage isomers. Molecular docking simulations reveal that multiple noncovalent interactions occur between residues R282, K238, and R240 and the glycans and R-binaphthyl tag, significantly slowing down their translocation across the nanopore. Importantly, we provide a demonstration of the kinetic translocation process of neutral glycan isomers, establishing a solid theoretical foundation for glycan nanopore analysis. The development of our technology could promote the analysis of glycan structural isomers and has the potential for nanopore-based glycan structural determination and sequencing.

Selective Capture and Manipulation of DNA through Double Charged Nanopores.

In the past few decades, nanometer-scale pores have been employed as powerful tools for sensing biological molecules. Owing to its unique structure and properties, solid-state nanopores provide interesting opportunities for the development of DNA sequencing technology. Controlling DNA translocation in nanopores is an important means of improving the accuracy of sequencing. Here we present a proof of principle study of accelerating DNA captured across targeted graphene nanopores using surface charge density and find the intrinsic mechanism of the combination of electroosmotic flow induced by charges of nanopore and electrostatic attraction/repulsion between the nanopore and ssDNA. The theoretical study performed here provides a new means for controlling DNA transport dynamics and makes better and cheaper application of graphene in molecular sequencing.

Design Principles of DNA-Barcodes for Nanopore-FET Readout, Based on Molecular Dynamics and TCAD Simulations.

Nanopore field-effect transistor (NP-FET) devices hold great promise as sensitive single-molecule sensors, which provide CMOS-based on-chip readout and are also highly amenable to parallelization. A plethora of applications will therefore benefit from NP-FET technology, such as large-scale molecular analysis (e.g., proteomics). Due to its potential for parallelization, the NP-FET looks particularly well-suited for the high-throughput readout of DNA-based barcodes. However, to date, no study exists that unravels the bit-rate capabilities of NP-FET devices. In this paper, we design DNA-based barcodes by labeling a piece of double-stranded DNA with dumbbell-like DNA structures. We explore the impact of both the size of the dumbbells and their spacing on achievable bit-rates. The conformational fluctuations of this DNA-origami, as observed by molecular dynamics (MD) simulation, are accounted for when selecting label sizes. An experimentally informed 3D continuum nanofluidic-nanoelectronic device model subsequently predicts both the ionic current and FET signals. We present a barcode design for a conceptually generic NP-FET, with a 14 nm diameter pore, operating in conditions corresponding to experiments. By adjusting the spacing between the labels to half the length of the pore, we show that a bit-rate of 78 kbit·s-1 is achievable. This lies well beyond the state-of-the-art of ≈40 kbit·s-1, with significant headroom for further optimizations. We also highlight the advantages of NP-FET readout based on the larger signal size and sinusoidal signal shape.

Ion detection in a DNA nanopore FET device.

An ion detection device that combines a DNA-origami nanopore and a field-effect transistor (FET) was designed and modeled to determine sensitivity of the nanodevice to the local cellular environment. Such devices could be integrated into a live cell, creating an abiotic-biotic interface integrated with semiconductor electronics. A continuum model is used to describe the behavior of ions in an electrolyte solution. The drift-diffusion equations are employed to model the ion distribution, taking into account the electric fields and concentration gradients. This was matched to the results from electric double layer theory to verify applicability of the model to a bio-sensing environment. The FET device combined with the nanopore is shown to have high sensitivity to ion concentration and nanopore geometry, with the electrical double layer behavior governing the device characteristics. A logarithmic relationship was found between ion concentration and a single FET current, generating up to 200 nA of current difference with a small applied bias.

NanoMUD: Profiling of pseudouridine and N1-methylpseudouridine using Oxford Nanopore direct RNA sequencing.

Nanopore direct RNA sequencing provided a promising solution for unraveling the landscapes of modifications on single RNA molecules. Here, we proposed NanoMUD, a computational framework for predicting the RNA pseudouridine modification (Ψ) and its methylated analog N1-methylpseudouridine (m1Ψ), which have critical application in mRNA vaccination, at single-base and single-molecule resolution from direct RNA sequencing data. Electric signal features were fed into a bidirectional LSTM neural network to achieve improved accuracy and predictive capabilities. Motif-specific models (NNUNN, N = A, C, U or G) were trained based on features extracted from designed dataset and achieved superior performance on molecule-level modification prediction (Ψ models: min AUC = 0.86, max AUC = 0.99; m1Ψ models: min AUC = 0.87, max AUC = 0.99). We then aggregated read-level predictions for site stoichiometry estimation. Given the observed sequence-dependent bias in model performance, we trained regression models based on the distribution of modification probabilities for sites with known stoichiometry. The distribution-based site stoichiometry estimation method allows unbiased comparison between different contexts. To demonstrate the feasibility of our work, three case studies on both in vitro and in vivo transcribed RNAs were presented. NanoMUD will make a powerful tool to facilitate the research on modified therapeutic IVT RNAs and provides useful insight to the landscape and stoichiometry of pseudouridine and N1-pseudouridine on in vivo transcribed RNA species.

From shells to sequences: A proof-of-concept study for on-site analysis of hemolymphatic circulating cell-free DNA from sentinel mussels using Nanopore technology.

Blue mussels are often abundant and widely distributed in polar marine coastal ecosystems. Because of their wide distribution, ecological importance, and relatively stationary lifestyle, bivalves have long been considered suitable indicators of ecosystem health and changes. Monitoring the population dynamics of blue mussels can provide information on the overall biodiversity, species interactions, and ecosystem functioning. In the present work, we combined the concept of liquid biopsy (LB), an emerging concept in medicine based on the sequencing of free circulating DNA, with the Oxford Nanopore Technologies (ONT) platform using a portable laboratory in a remote area. Our results demonstrate that this platform is ideally suited for sequencing hemolymphatic circulating cell-free DNA (ccfDNA) fragments found in blue mussels. The percentage of non-self ccfDNA accounted for >50 % of ccfDNA at certain sampling Sites, allowing the quick, on-site acquisition of a global view of the biodiversity of a coastal marine ecosystem. These ccfDNA fragments originated from viruses, bacteria, plants, arthropods, algae, and multiple Chordata. Aside from non-self ccfDNA, we found DNA fragments from all 14 blue mussel chromosomes, as well as those originating from the mitochondrial genomes. However, the distribution of nuclear and mitochondrial DNA was significantly different between Sites. Similarly, analyses between various sampling Sites showed that the biodiversity varied significantly within microhabitats. Our work shows that the ONT platform is well-suited for LB in sentinel blue mussels in remote and challenging conditions, enabling faster fieldwork for conservation strategies and resource management in diverse settings.

Sequencing accuracy and systematic errors of nanopore direct RNA sequencing.

BACKGROUND: Direct RNA sequencing (dRNA-seq) on the Oxford Nanopore Technologies (ONT) platforms can produce reads covering up to full-length gene transcripts, while containing decipherable information about RNA base modifications and poly-A tail lengths. Although many published studies have been expanding the potential of dRNA-seq, its sequencing accuracy and error patterns remain understudied. RESULTS: We present the first comprehensive evaluation of sequencing accuracy and characterisation of systematic errors in dRNA-seq data from diverse organisms and synthetic in vitro transcribed RNAs. We found that for sequencing kits SQK-RNA001 and SQK-RNA002, the median read accuracy ranged from 87% to 92% across species, and deletions significantly outnumbered mismatches and insertions. Due to their high abundance in the transcriptome, heteropolymers and short homopolymers were the major contributors to the overall sequencing errors. We also observed systematic biases across all species at the levels of single nucleotides and motifs. In general, cytosine/uracil-rich regions were more likely to be erroneous than guanines and adenines. By examining raw signal data, we identified the underlying signal-level features potentially associated with the error patterns and their dependency on sequence contexts. While read quality scores can be used to approximate error rates at base and read levels, failure to detect DNA adapters may be a source of errors and data loss. By comparing distinct basecallers, we reason that some sequencing errors are attributable to signal insufficiency rather than algorithmic (basecalling) artefacts. Lastly, we generated dRNA-seq data using the latest SQK-RNA004 sequencing kit released at the end of 2023 and found that although the overall read accuracy increased, the systematic errors remain largely identical compared to the previous kits. CONCLUSIONS: As the first systematic investigation of dRNA-seq errors, this study offers a comprehensive overview of reproducible error patterns across diverse datasets, identifies potential signal-level insufficiency, and lays the foundation for error correction methods.

Nanopore Blockade Sensors for Quantitative Analysis Using an Optical Nanopore Assay.

Nanopore sensing is a popular biosensing strategy that is being explored for the quantitative analysis of biomarkers. With low concentrations of analytes, nanopore sensors face challenges related to slow response times and selectivity. Here, we demonstrate an approach to rapidly detect species at ultralow concentrations using an optical nanopore blockade sensor for quantitative detection of the protein vascular endothelial growth factor (VEGF). This sensor relies on monitoring fluorescent polystyrene nanoparticles blocking nanopores in a nanopore array of 676 nanopores. The fluorescent signal is read out using a wide-field fluorescence microscope. Nonspecific blockade events are then distinguished from specific blockade events based on the ability to pull the particles out of the pore using an applied electric field. This allows the detection of VEGF at sub-picomolar concentration in less than 15 min.

Long-Read Nanopore-Based Sequencing of Anelloviruses.

Routinely used metagenomic next-generation sequencing (mNGS) techniques often fail to detect low-level viremia (<104 copies/mL) and appear biased towards viruses with linear genomes. These limitations hinder the capacity to comprehensively characterize viral infections, such as those attributed to the Anelloviridae family. These near ubiquitous non-pathogenic components of the human virome have circular single-stranded DNA genomes that vary in size from 2.0 to 3.9 kb and exhibit high genetic diversity. Hence, species identification using short reads can be challenging. Here, we introduce a rolling circle amplification (RCA)-based metagenomic sequencing protocol tailored for circular single-stranded DNA genomes, utilizing the long-read Oxford Nanopore platform. The approach was assessed by sequencing anelloviruses in plasma drawn from people who inject drugs (PWID) in two geographically distinct cohorts. We detail the methodological adjustments implemented to overcome difficulties inherent in sequencing circular genomes and describe a computational pipeline focused on anellovirus detection. We assessed our protocol across various sample dilutions and successfully differentiated anellovirus sequences in conditions simulating mixed infections. This method provides a robust framework for the comprehensive characterization of circular viruses within the human virome using the Oxford Nanopore.