Effective training of nanopore callers for epigenetic marks with limited labelled data.

Nanopore sequencing platforms combined with supervised machine learning (ML) have been effective at detecting base modifications in DNA such as 5-methylcytosine (5mC) and N6-methyladenine (6mA). These ML-based nanopore callers have typically been trained on data that span all modifications on all possible DNA [Formula: see text]-mer backgrounds-a complete training dataset. However, as nanopore technology is pushed to more and more epigenetic modifications, such complete training data will not be feasible to obtain. Nanopore calling has historically been performed with hidden Markov models (HMMs) that cannot make successful calls for [Formula: see text]-mer contexts not seen during training because of their independent emission distributions. However, deep neural networks (DNNs), which share parameters across contexts, are increasingly being used as callers, often outperforming their HMM cousins. It stands to reason that a DNN approach should be able to better generalize to unseen [Formula: see text]-mer contexts. Indeed, herein we demonstrate that a common DNN approach (DeepSignal) outperforms a common HMM approach (Nanopolish) in the incomplete data setting. Furthermore, we propose a novel hybrid HMM-DNN approach, amortized-HMM, that outperforms both the pure HMM and DNN approaches on 5mC calling when the training data are incomplete. This type of approach is expected to be useful for calling other base modifications such as 5-hydroxymethylcytosine and for the simultaneous calling of different modifications, settings in which complete training data are not likely to be available.

Exploring the potential of Oxford Nanopore Technologies sequencing for Mycobacterium tuberculosis sequencing: An assessment of R10 flowcells and V14 chemistry.

Oxford Nanopore Technologies (ONT) sequencing is a promising technology. We assessed the performance of the new ONT R10 flowcells and V14 rapid sequencing chemistry for Mtb whole genome sequencing of Mycobacterium tuberculosis (Mtb) DNA extracted from clinical primary liquid cultures (CPLCs). Using the recommended protocols for MinION Mk1C, R10.4.1 MinION flowcells, and the ONT Rapid Sequencing Kit V14 on six CPLC samples, we obtained a pooled library yield of 10.9 ng/µl, generated 1.94 Gb of sequenced bases and 214k reads after 48h in a first sequencing run. Only half (49%) of all generated reads met the Phred Quality score threshold (>8). To assess if the low data output and sequence quality were due to impurities present in DNA extracted directly from CPLCs, we added a pre-library preparation bead-clean-up step and included purified DNA obtained from an Mtb subculture as a control sample in a second sequencing run. The library yield for DNA extracted from four CPLCs and one Mtb subculture (control) was similar (10.0 ng/µl), 2.38 Gb of bases and 822k reads were produced. The quality was slightly better with 66% of the produced reads having a Phred Quality >8. A third run of DNA from six CPLCs with bead clean-up pre-processing produced a low library yield (±1 Gb of bases, 166k reads) of low quality (51% of reads with a Phred Quality score >8). A median depth of coverage above 10× was only achieved for five of 17 (29%) sequenced libraries. Compared to Illumina WGS of the same samples, accurate lineage predictions and full drug resistance profiles from the generated ONT data could not be determined by TBProfiler. Further optimization of the V14 ONT rapid sequencing chemistry and library preparation protocol is needed for clinical Mtb WGS applications.

Early assessment of fungal and oomycete pathogens in greenhouse irrigation water using Oxford nanopore amplicon sequencing.

Water-borne plant pathogenic fungi and oomycetes are a major threat in greenhouse production systems. Early detection and quantification of these pathogens would enable us to ascertain both economic and biological thresholds required for a timely treatment, thus improving effective disease management. Here, we used Oxford nanopore MinION amplicon sequencing to analyze microbial communities in irrigation water collected from greenhouses used for growing tomato, cucumber and Aeschynanthus sp. Fungal and oomycete communities were characterized using primers that amplify the full internal transcribed spacer (ITS) region. To assess the sensitivity of the MinION sequencing, we spiked serially diluted mock DNA into the DNA isolated from greenhouse water samples prior to library preparation. Relative abundances of fungal and oomycete reads were distinct in the greenhouse irrigation water samples and in water samples from setups with tomato that was inoculated with Fusarium oxysporum. Sequence reads derived from fungal and oomycete mock communities were proportionate in the respective serial dilution samples, thus confirming the suitability of MinION amplicon sequencing for environmental monitoring. By using spike-ins as standards to test the reliability of quantification using the MinION, we found that the detection of spike-ins was highly affected by the background quantities of fungal or oomycete DNA in the sample. We observed that spike-ins having shorter length (538bp) produced reads across most of our dilutions compared to the longer spikes (>790bp). Moreover, the sequence reads were uneven with respect to dilution series and were least retrievable in the background samples having the highest DNA concentration, suggesting a narrow dynamic range of performance. We suggest continuous benchmarking of the MinION sequencing to improve quantitative metabarcoding efforts for rapid plant disease diagnostic and monitoring in the future.

Biofoundry-Scale DNA Assembly Validation Using Cost-Effective High-Throughput Long-Read Sequencing.

Biofoundries are automated high-throughput facilities specializing in the design, construction, and testing of engineered/synthetic DNA constructs (plasmids), often from genetic parts. A critical step of this process is assessing the fidelity of the assembled DNA construct to the desired design. Current methods utilized for this purpose are restriction digest or PCR followed by fragment analysis and sequencing. The Edinburgh Genome Foundry (EGF) has recently established a single-molecule sequencing quality control step using the Oxford Nanopore sequencing technology, along with a companion Nextflow pipeline and a Python package, to perform in-depth analysis and generate a detailed report. Our software enables researchers working with plasmids, including biofoundry scientists, to rapidly analyze and interpret sequencing data. In conclusion, we have created a laboratory and software protocol that validates assembled, cloned, or edited plasmids, using Nanopore long-reads, which can serve as a useful resource for the genetics, synthetic biology, and sequencing communities.

Lokatt: a hybrid DNA nanopore basecaller with an explicit duration hidden Markov model and a residual LSTM network.

BACKGROUND: Basecalling long DNA sequences is a crucial step in nanopore-based DNA sequencing protocols. In recent years, the CTC-RNN model has become the leading basecalling model, supplanting preceding hidden Markov models (HMMs) that relied on pre-segmenting ion current measurements. However, the CTC-RNN model operates independently of prior biological and physical insights. RESULTS: We present a novel basecaller named Lokatt: explicit duration Markov model and residual-LSTM network. It leverages an explicit duration HMM (EDHMM) designed to model the nanopore sequencing processes. Trained on a newly generated library with methylation-free Ecoli samples and MinION R9.4.1 chemistry, the Lokatt basecaller achieves basecalling performances with a median single read identity score of 0.930, a genome coverage ratio of 99.750%, on par with existing state-of-the-art structure when trained on the same datasets. CONCLUSION: Our research underlines the potential of incorporating prior knowledge into the basecalling processes, particularly through integrating HMMs and recurrent neural networks. The Lokatt basecaller showcases the efficacy of a hybrid approach, emphasizing its capacity to achieve high-quality basecalling performance while accommodating the nuances of nanopore sequencing. These outcomes pave the way for advanced basecalling methodologies, with potential implications for enhancing the accuracy and efficiency of nanopore-based DNA sequencing protocols.

Fast and cost-effective SARS-CoV-2 variant detection using Oxford Nanopore full-length spike gene sequencing.

Most biologically relevant and diagnostic mutations in the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) genome have been identified in the S gene through global genomic surveillance efforts. However, large-scale whole-genome sequencing (WGS) is still challenging in developing countries due to higher costs, reagent delays and limited infrastructure. Consequently, only a small fraction of SARS-CoV-2 samples are characterized through WGS in these regions. Here, we present a complete workflow consisting of a fast library preparation protocol based on tiled amplification of the S gene, followed by a PCR barcoding step and sequencing using Nanopore platforms. This protocol facilitates fast and cost-effective identification of main variants of concern and mutational surveillance of the S gene. By applying this protocol, report time and overall costs for SARS-CoV-2 variant detection could be reduced, contributing to improved genomic surveillance programmes, particularly in low-income regions.

Microbial Water Quality Assessment of Private Wells Using 16S rRNA Gene Amplicon Sequencing with a Nanopore Sequencer.

Private wells are used daily worldwide as convenient household water sources. In Japan, where water supply coverage is high, well water is occasionally used for non-potable purposes, such as irrigation and watering. Currently, the main microbiological test of well water is designed to detect Escherichia coli, which is an indicator of fecal contamination, using culture methods. Water use such as watering generates bioaerosols, which may cause airborne infection. However, many causative bacteria of aerosol-derived infections, such as Legionella spp., are difficult to detect using culture methods. Thus, more comprehensive modern assessment is desirable for securing the microbiological quality of well water. Here, the bacterial community structure of five private wells located in different environments was examined using the rapid and portable MinION sequencer, which enabled us to identify bacteria to the species level based on full-length 16S ribosomal RNA (rRNA) gene sequences. The results revealed the differences in the bacterial community structures of water samples from the five wells and detected Legionella pneumophila and Aeromonas hydrophila as new candidate microbial indicators. The comprehensive analysis method used in this study successfully detected bacteria causing opportunistic infections, which are difficult to detect by conventional methods. This approach is expected to be routinely applied in the future as a highly accurate method for assessing the microbiological quality of private well water.

Assessment of Rapid MinION Nanopore DNA Virus Meta-Genomics Using Calves Experimentally Infected with Bovine Herpes Virus-1.

Bovine respiratory disease (BRD), which is the leading cause of morbidity and mortality in cattle, is caused by numerous known and unknown viruses and is responsible for the widespread use of broad-spectrum antibiotics despite the use of polymicrobial BRD vaccines. Viral metagenomics sequencing on the portable, inexpensive Oxford Nanopore Technologies MinION sequencer and sequence analysis with its associated user-friendly point-and-click Epi2ME cloud-based pathogen identification software has the potential for point-of-care/same-day/sample-to-result metagenomic sequence diagnostics of known and unknown BRD pathogens to inform a rapid response and vaccine design. We assessed this potential using in vitro viral cell cultures and nasal swabs taken from calves that were experimentally challenged with a single known BRD-associated DNA virus, namely, bovine herpes virus 1. Extensive optimisation of the standard Oxford Nanopore library preparation protocols, particularly a reduction in the PCR bias of library amplification, was required before BoHV-1 could be identified as the main virus in the in vitro cell cultures and nasal swab samples within approximately 7 h from sample to result. In addition, we observed incorrect assignment of the bovine sequence to bacterial and viral taxa due to the presence of poor-quality bacterial and viral genome assemblies in the RefSeq database used by the EpiME Fastq WIMP pathogen identification software.

Combining dynamic Monte Carlo with machine learning to study nanoparticle translocation.

Resistive pulse sensing (RPS) measurements of nanoparticle translocation have the ability to provide information on single-particle level characteristics, such as diameter or mobility, as well as ensemble averages. However, interpreting these measurements is complex and requires an understanding of nanoparticle dynamics in confined spaces as well as the ways in which nanoparticles disrupt ion transport while inside a nanopore. Here, we combine Dynamic Monte Carlo (DMC) simulations with Machine Learning (ML) and Poisson-Nernst-Planck calculations to simultaneously simulate nanoparticle dynamics and ion transport during hundreds of independent particle translocations as a function of nanoparticle size, electrophoretic mobility, and nanopore length. The use of DMC simulations allowed us to explicitly investigate the effects of Brownian motion and nanoparticle/nanopore characteristics on the amplitude and duration of translocation signals. Simulation results were verified with experimental RPS measurements and found to be in quantitative agreement.

Acute Leukemia Classification Using Transcriptional Profiles From Low-Cost Nanopore mRNA Sequencing.

PURPOSE: Most cases of pediatric acute leukemia occur in low- and middle-income countries, where health centers lack the tools required for accurate diagnosis and disease classification. Recent research shows the robustness of using unbiased short-read RNA sequencing to classify genomic subtypes of acute leukemia. Compared with short-read sequencing, nanopore sequencing has low capital and consumable costs, making it suitable for use in locations with limited health infrastructure. MATERIALS AND METHODS: We show the feasibility of nanopore mRNA sequencing on 134 cryopreserved acute leukemia specimens (26 acute myeloid leukemia [AML], 73 B-lineage acute lymphoblastic leukemia [B-ALL], 34 T-lineage acute lymphoblastic leukemia, and one acute undifferentiated leukemia). Using multiple library preparation approaches, we generated long-read transcripts for each sample. We developed a novel composite classification approach to predict acute leukemia lineage and major B-ALL and AML molecular subtypes directly from gene expression profiles. RESULTS: We demonstrate accurate classification of acute leukemia samples into AML, B-ALL, or T-lineage acute lymphoblastic leukemia (96.2% of cases are classifiable with a probability of > 0.8, with 100% accuracy) and further classification into clinically actionable genomic subtypes using shallow RNA nanopore sequencing, with 96.2% accuracy for major AML subtypes and 94.1% accuracy for major B-lineage acute lymphoblastic leukemia subtypes. CONCLUSION: Transcriptional profiling of acute leukemia samples using nanopore technology for diagnostic classification is feasible and accurate, which has the potential to improve the accuracy of cancer diagnosis in low-resource settings.

Diffusion of molecules through nanopores under confinement: Time-scale bridging and crowding effects via Markov state model.

Passive transport of molecules through nanopores is characterized by the interaction of molecules with pore internal walls and by a general crowding effect due to the constricted size of the nanopore itself, which limits the presence of molecules in its interior. The molecule-pore interaction is treated within the diffusion approximation by introducing the potential of mean force and the local diffusion coefficient for a correct statistical description. The crowding effect can be handled within the Markov state model approximation. By combining the two methods, one can deal with complex free energy surfaces taking into account crowding effects. We recapitulate the equations bridging the two models to calculate passive currents assuming a limited occupancy of the nanopore in a wide range of molecular concentrations. Several simple models are analyzed to clarify the consequences of the model. Eventually, a biologically relevant case of transport of an antibiotic molecule through a bacterial porin is used to draw conclusions (i) on the effects of crowding on transport of small molecules through biological channels, and (ii) to demonstrate its importance for modelling of cellular transport.

ECNano: A cost-effective workflow for target enrichment sequencing and accurate variant calling on 4800 clinically significant genes using a single MinION flowcell.

BACKGROUND: The application of long-read sequencing using the Oxford Nanopore Technologies (ONT) MinION sequencer is getting more diverse in the medical field. Having a high sequencing error of ONT and limited throughput from a single MinION flowcell, however, limits its applicability for accurate variant detection. Medical exome sequencing (MES) targets clinically significant exon regions, allowing rapid and comprehensive screening of pathogenic variants. By applying MES with MinION sequencing, the technology can achieve a more uniform capture of the target regions, shorter turnaround time, and lower sequencing cost per sample. METHOD: We introduced a cost-effective optimized workflow, ECNano, comprising a wet-lab protocol and bioinformatics analysis, for accurate variant detection at 4800 clinically important genes and regions using a single MinION flowcell. The ECNano wet-lab protocol was optimized to perform long-read target enrichment and ONT library preparation to stably generate high-quality MES data with adequate coverage. The subsequent variant-calling workflow, Clair-ensemble, adopted a fast RNN-based variant caller, Clair, and was optimized for target enrichment data. To evaluate its performance and practicality, ECNano was tested on both reference DNA samples and patient samples. RESULTS: ECNano achieved deep on-target depth of coverage (DoC) at average > 100× and > 98% uniformity using one MinION flowcell. For accurate ONT variant calling, the generated reads sufficiently covered 98.9% of pathogenic positions listed in ClinVar, with 98.96% having at least 30× DoC. ECNano obtained an average read length of 1000 bp. The long reads of ECNano also covered the adjacent splice sites well, with 98.5% of positions having ≥ 30× DoC. Clair-ensemble achieved > 99% recall and accuracy for SNV calling. The whole workflow from wet-lab protocol to variant detection was completed within three days. CONCLUSION: We presented ECNano, an out-of-the-box workflow comprising (1) a wet-lab protocol for ONT target enrichment sequencing and (2) a downstream variant detection workflow, Clair-ensemble. The workflow is cost-effective, with a short turnaround time for high accuracy variant calling in 4800 clinically significant genes and regions using a single MinION flowcell. The long-read exon captured data has potential for further development, promoting the application of long-read sequencing in personalized disease treatment and risk prediction.

Forensic nanopore sequencing of microhaplotype markers using QitanTech's QNome.

In recent years, extraordinary progress has been made in genome sequencing technologies, which has led to a decrease in cost and an increase in the diversity of sequenced genomes. Nanopore sequencing is one of the latest genome sequencing technologies. It aims to sequence longer contiguous pieces of DNA, which are essential for resolving structurally complex regions, and provides a new approach for forensic genetics to detect longer markers in real time. To date, multiple studies have been conducted to sequence forensic markers using MinION from Oxford Nanopore Technologies (ONT), and the results indicate that nanopore sequencing holds promise for forensic applications. Qitan Technology (QitanTech) recently launched its first commercial nanopore genome sequencer, QNome. It could achieve a read length of more than 150 kbp, and could generate approximately 500 Mb of data in 8 h. In this pilot study, we explored and validated this alternative nanopore sequencing device for microhaplotype (MH) profiling using a custom set of 15 MH loci. Seventy single-contributor samples were divided into 7 batches, each of which included 10 samples and control DNA 9947A and was sequenced by QNome. MH genotypes generated from QNome were compared to those from Ion Torrent sequencing (Ion S5XL system) to evaluate the accuracy and stability. Twelve samples randomly selected from the last three batches and Control DNA 9947A were also subjected to ONT MinION sequencing (with R9.4 flow cell) for parallel comparison. Based on MHtyper, a bioinformatics workflow developed for automated MH designation, all MH loci can be genotyped and reliably phased using the QNome data, with an overall accuracy of 99.83% (4 errors among 2310 genotypes). Three occurred near or in the region of homopolymer sequences, and one existed within 50 bp of the start of the sequencing reaction. In the last 15 samples (12 individual samples and 3 replicates of control DNA 9947A), two SNPs located at 4-mer homopolymers failed to obtain reliable genotypes on the MinION data. This study shows the potential of state-of-the-art nanopore sequencing methods to analyze forensic MH markers. Given the rapid pace of change, sporadic and nonrepetitive errors presented in this study are expected to be resolved by further developments of nanopore technologies and analysis tools.

Assessment of Automated Nucleic Acid Extraction Systems in Combination with MinION Sequencing As Potential Tools for the Detection of Microbial Biosignatures.

The utilization of nanopore technologies for the detection of organic biogenic compounds has garnered significant focus in recent years. Oxford Nanopore Technologies' (ONT) MinION instrument, which can detect and sequence nucleic acids (NAs), is one such example. These technologies have much promise for unambiguous life detection but require significant development in terms of methods for extraction and preparation of NAs for biosignature detection and their feasibility for use in astrobiology-focused field missions. In this study, we tested pre-existing, automated, or semiautomated NA extraction technologies, coupled with automated ONT VolTRAX NA sample preparation, and verification with Nanopore MinION sequencing. All of the extraction systems tested (SuperFastPrep2, ClaremontX1, and SOLID-Sample Preparation Unit) showed potential for extracting DNA from Canadian High Arctic environments analogous to Mars, Europa, and Enceladus, which could subsequently be detected and sequenced with the MinION. However, they differed with regard to efficacy, yield, purity, and sequencing and annotation quality. Overall, bead beating-based systems performed the best for these parameters. In addition, we showed that the MinION could sequence unpurified DNA contained in crude cell lysates. This is valuable from an astrobiology perspective because purification steps are time-consuming and complicate the requirements for an automated extraction and life detection system. Our results indicate that semiautomated NA extraction and preparation technologies hold much promise, and with increased optimization and automation could be coupled to a larger platform incorporating nanopore detection and sequencing of NAs for life detection applications.

Multiplexed assessment of engineered bacterial constructs for intracellular ß-galactosidase expression by redox amplification on catechol-chitosan modified nanoporous gold.

Synthetic biology approaches for rewiring of bacterial constructs to express particular intracellular factors upon induction with the target analyte are emerging as sensing paradigms for applications in environmental and in vivo monitoring. To aid in the design and optimization of bacterial constructs for sensing analytes, there is a need for lysis-free intracellular detection modalities that monitor the signal level and kinetics of expressed factors within different modified bacteria in a multiplexed manner, without requiring cumbersome surface immobilization. Herein, an electrochemical detection system on nanoporous gold that is electrofabricated with a biomaterial redox capacitor is presented for quantifying ß-galactosidase expressed inside modified Escherichia coli constructs upon induction with dopamine. This nanostructure-mediated redox amplification approach on a microfluidic platform allows for multiplexed assessment of the expressed intracellular factors from different bacterial constructs suspended in distinct microchannels, with no need for cell lysis or immobilization. Since redox mediators present over the entire depth of the microchannel can interact with the electrode and with the E. coli construct in each channel, the platform exhibits high sensitivity and enables multiplexing. We envision its application in assessing synthetic biology-based approaches for comparing specificity, sensitivity, and signal response time upon induction with target analytes of interest.

Combining machine learning and nanopore construction creates an artificial intelligence nanopore for coronavirus detection.

High-throughput, high-accuracy detection of emerging viruses allows for the control of disease outbreaks. Currently, reverse transcription-polymerase chain reaction (RT-PCR) is currently the most-widely used technology to diagnose the presence of SARS-CoV-2. However, RT-PCR requires the extraction of viral RNA from clinical specimens to obtain high sensitivity. Here, we report a method for detecting novel coronaviruses with high sensitivity by using nanopores together with artificial intelligence, a relatively simple procedure that does not require RNA extraction. Our final platform, which we call the artificially intelligent nanopore, consists of machine learning software on a server, a portable high-speed and high-precision current measuring instrument, and scalable, cost-effective semiconducting nanopore modules. We show that artificially intelligent nanopores are successful in accurately identifying four types of coronaviruses similar in size, HCoV-229E, SARS-CoV, MERS-CoV, and SARS-CoV-2. Detection of SARS-CoV-2 in saliva specimen is achieved with a sensitivity of 90% and specificity of 96% with a 5-minute measurement.

The Use of Low Cost Nanoporous Catalysts on the Catalytic Pyrolysis of Polyethylene Terephthalate.

This study evaluated the feasibility of low-cost nanoporous catalysts, such as dolomite and red mud, on the production of aromatic hydrocarbons via the catalytic pyrolysis of polyethylene terephthalate (PET). Compared to the non-catalytic pyrolysis of PET, catalytic pyrolysis over both dolomite and red mud produced larger amounts of aromatic hydrocarbons owing to their catalytic cracking efficiency and decarboxylation efficiency. Between the two catalysts, red mud, having a larger BET surface area and higher basicity than dolomite, showed higher efficiency for the production of aromatic hydrocarbons.

Advances in Micro/Nanoporous Membranes for Biomedical Engineering.

Porous membrane materials at the micro/nanoscale have exhibited practical and potential value for extensive biological and medical applications associated with filtration and isolation, cell separation and sorting, micro-arrangement, in-vitro tissue reconstruction, high-throughput manipulation and analysis, and real-time sensing. Herein, an overview of technological development of micro/nanoporous membranes (M/N-PMs) is provided. Various membrane types and the progress documented in membrane fabrication techniques, including the electrochemical-etching, laser-based technology, microcontact printing, electron beam lithography, imprinting, capillary force lithography, spin coating, and microfluidic molding are described. Their key features, achievements, and limitations associated with micro/nanoporous membrane (M/N-PM) preparation are discussed. The recently popularized applications of M/N-PMs in biomedical engineering involving the separation of cells and biomolecules, bioparticle operations, biomimicking, micropatterning, bioassay, and biosensing are explored too. Finally, the challenges that need to be overcome for M/N-PM fabrication and future applications are highlighted.

Assessment of 1/f noise associated with nanopores fabricated through chemically tuned controlled dielectric breakdown.

Recently, we developed a fabrication method-chemically-tuned controlled dielectric breakdown (CT-CDB)-that produces nanopores (through thin silicon nitride membranes) surpassing legacy drawbacks associated with solid-state nanopores (SSNs). However, the noise characteristics of CT-CDB nanopores are largely unexplored. In this work, we investigated the 1/f noise of CT-CDB nanopores of varying solution pH, electrolyte type, electrolyte concentration, applied voltage, and pore diameter. Our findings indicate that the bulk Hooge parameter (αb ) is about an order of magnitude greater than SSNs fabricated by transmission electron microscopy (TEM) while the surface Hooge parameter (αs ) is ∼3 order magnitude greater. Theαs of CT-CDB nanopores was ∼5 orders of magnitude greater than theirαb , which suggests that the surface contribution plays a dominant role in 1/f noise. Experiments with DNA exhibited increasing capture rates with pH up to pH ∼8 followed by a drop at pH ∼9 perhaps due to the onset of electroosmotic force acting against the electrophoretic force. The1/f noise was also measured for several electrolytes and LiCl was found to outperform NaCl, KCl, RbCl, and CsCl. The 1/f noise was found to increase with the increasing electrolyte concentration and pore diameter. Taken together, the findings of this work suggest the pH approximate 7-8 range to be optimal for DNA sensing with CT-CDB nanopores.

Rapid and economical drug resistance profiling with Nanopore MinION for clinical specimens with low bacillary burden of Mycobacterium tuberculosis.

OBJECTIVE: We designed and tested a Nanopore sequencing panel for direct tuberculosis drug resistance profiling. The panel targeted 10 resistance-associated loci. We assessed the feasibility of amplifying and sequencing these loci from 23 clinical specimens with low bacillary burden. RESULTS: At least 8 loci were successfully amplified from the majority for predicting first- and second-line drug resistance (14/23, 60.87%), and the 12 specimens yielding all 10 targets were sequenced with Nanopore MinION and Illumina MiSeq. MinION sequencing data was corrected by Nanopolish and recurrent variants were filtered. A total of 67,082 bases across all consensus sequences were analyzed, with 67,019 bases called by both MinION and MiSeq as wildtype. For the 41 single nucleotide variants (SNVs) called by MiSeq with 100% variant allelic frequency (VAF), 39 (95.1%) were called by MinION. For the 22 mixed bases called by MiSeq, a SNV with the highest VAF (70%) was called by MinION. With short assay time, reasonable reagent cost as well as continuously improving sequencing chemistry and signal correction pipelines, this Nanopore method can be a viable option for direct tuberculosis drug resistance profiling in the near future.