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PubMed2006

Multi-nanopore force spectroscopy for DNA analysis.

The need for low-cost DNA sequence detection in clinical applications is driving development of new technologies. We demonstrate a method for detection of mutations in a DNA sequence purely by electronic means, and without need for fluorescent labeling. Our method uses an array of nanopores to perform synchronized single-molecule force spectroscopy measurements over many molecules in parallel, yielding detailed information on the kinetics of hundreds of molecule dissociations in a single measurement.

Mutation↗
PubMed2025

SKiM: accurately classifying metagenomic ONT reads in limited memory.

MOTIVATION: Oxford Nanopore Technologies' devices, such as MinION, permit affordable, real-time DNA sequencing, and come with targeted sequencing capabilities. Such capabilities create new challenges for metagenomic classifiers that must be computationally efficient yet robust enough to handle potentially erroneous DNA reads, while ideally inspecting only a few hundred bases of a read. Currently available DNA classifiers leave room for improvement with respect to classification accuracy, memory usage, and the ability to operate in targeted sequencing scenarios. RESULTS: We present SKiM: Short K-mers in Metagenomics, a new lightweight metagenomic classifier designed for ONT reads. Compared to state-of-the-art classifiers, SKiM requires only a fraction of memory to run, and can classify DNA reads with higher accuracy after inspecting only their first few hundred bases. To achieve this, SKiM introduces new data compression techniques to maintain a reference database built from short k-mers, and treats classification as a statistical testing problem. AVAILABILITY AND IMPLEMENTATION: SKiM source code, documentation, and test data are available from: https://gitlab.com/SCoRe-Group/skim.

Metagenomics↗
PubMed2025

Chromosome scale genomes of two invasive Adelges species enable virtual screening for selective adelgicides.

Two invasive hemipteran adelgids are associated with widespread damage to several North American conifer species. Adelges tsugae, hemlock woolly adelgid, was introduced from Japan and reproduces parthenogenetically in North America, where it has rapidly decimated Tsuga canadensis and Tsuga caroliniana (the eastern and Carolina hemlocks, respectively). Adelges abietis, eastern spruce gall adelgid, introduced from Europe, forms distinctive pineapple-shaped galls on several native spruce species. While not considered a major forest pest, it weakens trees and increases susceptibility to additional stressors. Broad-spectrum insecticides that are often used to control adelgid populations can have off-target impacts on beneficial insects. Whole genome sequencing was performed on both species to aid in development of targeted solutions that may minimize ecological impact. Adelges abietis was sequenced using Illumina Linked-Read technology from 30 pooled individuals, with Hi-C scaffolding performed using data from a single individual collected from the same host plant. Adelges tsugae used Oxford Nanopore long-read sequencing from pooled nymphs. The assembled A. tsugae and A. abietis genomes, pooled from several parthenogenetic females, are 220.75 Mbp and 253.16 Mbp, respectively. Each consists of eight autosomal chromosomes, as well as two sex chromosomes (X1/X2), supporting the XX-XO sex determination system. The genomes are over 96% complete based on BUSCO assessment. Genome annotation identified 11,424 and 12,060 protein-coding genes in A. tsugae and A. abietis, respectively. Comparative analysis of proteins across 29 hemipteran species and 14 arthropod outgroups identified 31,666 putative gene families. Gene family evolution analysis with CAFE revealed lineage-specific expansions in immune-related aminopeptidases (ERAP1) and juvenile hormone binding proteins (JHBP), contractions in juvenile hormone acid methyltransferases (JHAMT), and conservation of nicotinic acetylcholine receptors (nAChR). These genes were explored as candidate families towards a long-term objective of developing adelgid-selective insecticides. Structural comparisons of proteins across seven focal species (Adelges tsugae, Adelges abietis, Adelges cooleyi, Rhopalosiphum maidis, Apis mellifera, Danaus plexippus, and Drosophila melanogaster) revealed high conservation of nAChR and ERAP1, while JHAMT exhibited species-specific structural divergence. The potential of JHAMT as a lineage-specific target for pest control was explored through virtual drug and pesticide screening.

adelgids↗
PubMed2025

Emerging protein sequencing technologies: proteomics without mass spectrometry?

INTRODUCTION: Liquid chromatography-tandem mass spectrometry (LC-MS/MS) has been a leading method for proteomics for 30 years. Advantages provided by LC-MS/MS are offset by significant disadvantages, including cost. Recently, several non-mass spectrometric methods have emerged, but little information is available about their capacity to analyze the complex mixtures routine for mass spectrometry. AREAS COVERED: We review recent non-mass-spectrometric methods for sequencing proteins and peptides, including those using nanopores, sequencing by degradation, reverse translation, and short-epitope mapping, with comments on bioinformatics challenges, fundamental limitations, and areas where new technologies will be more or less competitive with LC-MS/MS. In addition to conventional literature searches, instrument vendor websites, patents, webinars, and preprints were also consulted to give a more up-to-date picture. EXPERT OPINION: Many new technologies are promising. However, demonstrations that they outperform mass spectrometry in terms of peptides and proteins identified have not yet been published, and astute observers note important disadvantages, especially relating to the dynamic range of single-molecule measurements of complex mixtures. Still, even if the performance of emerging methods proves inferior to LC-MS/MS, their low cost could create a different kind of revolution: a dramatic increase in the number of biology laboratories engaging in new forms of proteomics research.

Proteomics↗
PubMed2019

Direct RNA nanopore sequencing of full-length coronavirus genomes provides novel insights into structural variants and enables modification analysis.

Sequence analyses of RNA virus genomes remain challenging owing to the exceptional genetic plasticity of these viruses. Because of high mutation and recombination rates, genome replication by viral RNA-dependent RNA polymerases leads to populations of closely related viruses, so-called "quasispecies." Standard (short-read) sequencing technologies are ill-suited to reconstruct large numbers of full-length haplotypes of (1) RNA virus genomes and (2) subgenome-length (sg) RNAs composed of noncontiguous genome regions. Here, we used a full-length, direct RNA sequencing (DRS) approach based on nanopores to characterize viral RNAs produced in cells infected with a human coronavirus. By using DRS, we were able to map the longest (∼26-kb) contiguous read to the viral reference genome. By combining Illumina and Oxford Nanopore sequencing, we reconstructed a highly accurate consensus sequence of the human coronavirus (HCoV)-229E genome (27.3 kb). Furthermore, by using long reads that did not require an assembly step, we were able to identify, in infected cells, diverse and novel HCoV-229E sg RNAs that remain to be characterized. Also, the DRS approach, which circumvents reverse transcription and amplification of RNA, allowed us to detect methylation sites in viral RNAs. Our work paves the way for haplotype-based analyses of viral quasispecies by showing the feasibility of intra-sample haplotype separation. Even though several technical challenges remain to be addressed to exploit the potential of the nanopore technology fully, our work illustrates that DRS may significantly advance genomic studies of complex virus populations, including predictions on long-range interactions in individual full-length viral RNA haplotypes.

Cell Line↗
PubMed2003

Nanodiagnostics: application of nanotechnology in molecular diagnostics.

Nanotechnology extends the limits of molecular diagnostics to the nanoscale. Nanotechnology-on-a-chip is one more dimension of microfluidic/lab-on-a-chip technology. Biological tests measuring the presence or activity of selected substances become quicker, more sensitive and more flexible when certain nanoscale particles are put to work as tags or labels. Magnetic nanoparticles, bound to a suitable antibody, are used to label specific molecules, structures or microorganisms. Magnetic immunoassay techniques have been developed in which the magnetic field generated by the magnetically labeled targets is detected directly with a sensitive magnetometer. Gold nanoparticles tagged with short segments of DNA can be used for detection of genetic sequence in a sample. Multicolor optical coding for biological assays has been achieved by embedding different-sized quantum dots into polymeric microbeads. Nanopore technology for analysis of nucleic acids converts strings of nucleotides directly into electronic signatures. DNA nanomachines can function as biomolecular detectors for homogeneous assays. Nanobarcodes, submicrometer metallic barcodes with striping patterns prepared by sequential electrochemical depositon of metal, show differential reflectivity of adjacent stripes enabling identification of the striping patterns by conventional light microscopy. All this has applications in population diagnostics and in point-of-care hand-held devices.

Animals↗
PubMed2026

NanoSSL: attention mechanism-based self-supervised learning method for protein identification using nanopores.

MOTIVATION: Nanopores are cutting-edge interdisciplinary tools that can analyze biomolecules at the single-molecule level for many applications, e.g. DNA sequencing. Efforts are underway to extend nanopores to proteomics, including the development of machine learning algorithms for protein sequencing and identification. However, single-molecule data are intrinsically noisy and hard to process. Moreover, the development and performance of machine learning for nanopore is jeopardized by data scarcity. Self-supervised learning is an emerging method that may yield advantages in nanopore scenarios. RESULTS: We propose and experimentally validate Nanopore analysis using Self-Supervised Learning (NanoSSL), a generative self-supervised learning framework based on attention mechanisms for the identification of protein signals from nanopores. Leveraging a two-step approach consisting of self-supervised pre-training and supervised fine-tuning, NanoSSL learns useful feature representations from empirical data to facilitate downstream classification tasks. Inspired by the concept of fragmentation in conventional protein sequencing technologies, during pretraining each translocation event is split into multiple non-overlapping fragments of equal size, some of which are randomly masked and reconstructed using a masked autoencoder. Learning the feature representations of the reconstructed nanopore events facilitates molecular identification in fine-tuning. In this study, we retested a publicly available nanopore multiplexed protein sensing dataset for model iteration, and subsequently measured Alzheimer's disease biomarker Aβ1-42 using homemade solid-state nanopores. Empirical results indicated NanoSSL achieved an unprecedented performance across four metrics: accuracy, precision, recall, and F1 score, when classifying two mutated Aβ1-42, E22G and G37R. The self-supervised learning and attention mechanism were verified as the source of performance gains. AVAILABILITY AND IMPLEMENTATION: The main program is available at https://doi.org/10.5281/zenodo.17172822.

Nanopores↗
PubMed2025

Targeted next-generation sequencing for drug-resistant tuberculosis diagnosis: implementation considerations for bacterial load, regimen selection and diagnostic algorithm placement.

INTRODUCTION: Early and accurate diagnosis of drug-resistant tuberculosis (DR-TB) is essential for improving treatment outcomes. Phenotypic drug susceptibility testing (pDST) is comprehensive but slow, while rapid molecular assays provide resistance information for a limited number of drugs. Targeted next-generation sequencing (tNGS) offers the potential for broad and rapid resistance detection, but its integration into diagnostic algorithms has been hindered by uncertainty about its placement within existing workflows. METHODS: This study evaluated the extent to which two tNGS solutions-Deeplex Myc-TB (GenoScreen) and TB Drug Resistance Test (Oxford Nanopore Technologies, ONT)-provided interpretable drug resistance results that could inform regimen design, in comparison to other WHO-recommended molecular assays and pDST. Data were collected from three high-burden DR-TB settings under the Seq&Treat study. Sequencing success rates and drug resistance detection were analysed based on: (1) the initial Xpert MTB/RIF result (very low, low, medium, high), (2) resistance results for drugs in WHO-recommended regimens and (3) performance relative to other WHO-endorsed assays. The potential impact of different algorithms on the estimates was also considered. Key factors influencing successful tNGS adoption within diagnostic pathways were identified, leveraging insights from the Seq&Treat diagnostic accuracy study. RESULTS: Sequencing success rates were 88.5% (GenoScreen) and 93.1% (ONT) across 763 samples. While tNGS provided complete resistance data for 73%-86% of drugs in recommended regimens, pDST achieved 92%-93%. Both tNGS solutions matched or exceeded the sensitivity of WHO-recommended molecular assays. CONCLUSIONS: This study highlights the critical role of tNGS as a centralised tool for comprehensive drug resistance testing to inform DR-TB treatment decisions following initial screening assays. By complementing existing molecular tests with tNGS, diagnostic workflows can be optimised to ensure timely and comprehensive resistance detection. These findings support policy updates to integrate tNGS into global TB diagnostic algorithms. TRIAL REGISTRATION NUMBER: NCT04239326.

Humans↗
PubMed2025

Autocycler: long-read consensus assembly for bacterial genomes.

MOTIVATION: Long-read sequencing enables complete bacterial genome assemblies, but individual assemblers are imperfect and often produce sequence-level and structural errors. Consensus assembly using Trycycler can improve accuracy, but its lack of automation limits scalability. There is a need for an automated method to generate high-quality consensus bacterial genome assemblies from long-read data. RESULTS: We present Autocycler, a command-line tool for generating accurate bacterial genome assemblies by combining multiple alternative long-read assemblies of the same genome. Without requiring user input, Autocycler builds a compacted De Bruijn graph from the input assemblies, clusters and filters contigs, trims overlaps, and resolves consensus sequences by selecting the most common variant at each locus. It also supports manual curation when desired, allowing users to refine assemblies in challenging or important cases. In our evaluation using Oxford Nanopore Technologies reads from five bacterial isolates, Autocycler outperformed individual assemblers, automated pipelines, and other consensus tools, producing assemblies with lower error rates and improved structural accuracy. AVAILABILITY AND IMPLEMENTATION: Autocycler is implemented in Rust, open-source, and freely available at github.com/rrwick/Autocycler. It runs on Linux and macOS and is extensively documented.

Genome, Bacterial↗
PubMed2024

Evaluating culture-free targeted next-generation sequencing for diagnosing drug-resistant tuberculosis: a multicentre clinical study of two end-to-end commercial workflows.

BACKGROUND: Drug-resistant tuberculosis remains a major obstacle in ending the global tuberculosis epidemic. Deployment of molecular tools for comprehensive drug resistance profiling is imperative for successful detection and characterisation of tuberculosis drug resistance. We aimed to assess the diagnostic accuracy of a new class of molecular diagnostics for drug-resistant tuberculosis. METHODS: We conducted a prospective, cross-sectional, multicentre clinical evaluation of the performance of two targeted next-generation sequencing (tNGS) assays for drug-resistant tuberculosis at reference laboratories in three countries (Georgia, India, and South Africa) to assess diagnostic accuracy and index test failure rates. Eligible participants were aged 18 years or older, with molecularly confirmed pulmonary tuberculosis, and at risk for rifampicin-resistant tuberculosis. Sensitivity and specificity for both tNGS index tests (GenoScreen Deeplex Myc-TB and Oxford Nanopore Technologies [ONT] Tuberculosis Drug Resistance Test) were calculated for rifampicin, isoniazid, fluoroquinolones (moxifloxacin, levofloxacin), second line-injectables (amikacin, kanamycin, capreomycin), pyrazinamide, bedaquiline, linezolid, clofazimine, ethambutol, and streptomycin against a composite reference standard of phenotypic drug susceptibility testing and whole-genome sequencing. FINDINGS: Between April 1, 2021, and June 30, 2022, 832 individuals were invited to participate in the study, of whom 720 were included in the final analysis (212, 376, and 132 participants in Georgia, India, and South Africa, respectively). Of 720 clinical sediment samples evaluated, 658 (91%) and 684 (95%) produced complete or partial results on the GenoScreen and ONT tNGS workflows, respectively, with 593 (96%) and 603 (98%) of 616 smear-positive samples producing tNGS sequence data. Both workflows had sensitivities and specificities of more than 95% for rifampicin and isoniazid, and high accuracy for fluoroquinolones (sensitivity approximately ≥94%) and second line-injectables (sensitivity 80%) compared with the composite reference standard. Importantly, these assays also detected mutations associated with resistance to critical new and repurposed drugs (bedaquiline, linezolid) not currently detectable by any other WHO-recommended rapid diagnostics on the market. We note that the current format of assays have low sensitivity (≤50%) for linezolid and more work on mutations associated with drug resistance is needed. INTERPRETATION: This multicentre evaluation demonstrates that culture-free tNGS can provide accurate sequencing results for detection and characterisation of drug resistance from Mycobacterium tuberculosis clinical sediment samples for timely, comprehensive profiling of drug-resistant tuberculosis. FUNDING: Unitaid.

Humans↗
PubMed2026

Chromosome-level assembly and annotation of the Jaguar (Panthera onca) genome.

OBJECTIVES: The Jaguar (Panthera onca) is a large cat species native to the Americas. Despite being successful predators, jaguar populations have declined due to habitat loss. Genome resources can help in conservation efforts as well as in understanding the interesting biology of these Felids. Beside contiguity, a well annotated reference genome provides contextual information for variants that will benefit the design of appropriate conservation programs. DATA DESCRIPTION: We sequenced material from two individuals using a combination of ONT reads and Illumina PE. The resulting nuclear genome assembly has a larger contig N50 (48.04 Mb) compared with the existing annotated chromosome-level assembly published by the DNA Zoo project. Using public Hi-C data, we obtained an improved chromosome-level assembly of the Jaguar genome (mPanOnc3.5) with larger contigs, 99.85% of the sequence assigned to chromosomes and 25,267 protein coding genes annotated. Overall, this improved assembly provides a better reference to study this threatened species.

Animals↗
PubMed2026

Population-scale detection of methylation outliers from long-read genome sequencing.

BACKGROUND: Aberrant DNA methylation can mediate the functional effects of rare genetic variation and contribute to imprinting disorders, repeat expansion diseases, and other pathogenic regulatory mechanisms. Long-read sequencing technologies now enable genome-wide detection of CpG methylation alongside genetic variation from a single assay. However, methods for systematic identification and interpretation of methylation outliers from long-read sequencing data remain limited. METHODS: We developed METAFORA, a computational workflow for detecting methylation outlier regions from PacBio and Oxford Nanopore long-read sequencing data. METAFORA constructs population-level methylation references, segments the genome into correlated CpG blocks, infers technical and biological sources of variation through hidden factor estimation, models uncertainty due to variable depth sequencing, and computes covariate-adjusted methylation outlier scores for individual samples. We applied METAFORA across large long-read sequencing cohorts and integrated methylation outliers with multi-omic data. METAFORA is implemented as a snakemake workflow available at https://github.com/tjense25/METAFORA. RESULTS: METAFORA identified methylation outlier regions associated with rare structural variants, tandem repeat expansions, and imprinting abnormalities. We found outlier regions were enriched for molecular outliers across transcriptomic and chromatin accessibility datasets, supporting their functional relevance in gene regulation. In a representative case, METAFORA identified an imprinting defect affecting the GNAS locus associated with an STX16 deletion. CONCLUSIONS: METAFORA enables scalable detection and interpretation of methylation outliers from long-read sequencing data and provides a framework for integrating epigenetic outliers with genomic and multi-omic analyses. These approaches may improve interpretation of rare regulatory variation and support discovery of clinically relevant epigenetic abnormalities in genomic medicine.

DNA methylation↗
PubMed2025

High-resolution metagenome assembly for modern long reads with myloasm.

Long-read metagenome assembly promises complete genomic recovery from microbiomes. However, the complexity of metagenomes poses challenges. We present myloasm, a metagenome assembler for PacBio HiFi and Oxford Nanopore Technologies (ONT) R10.4 long reads. Myloasm uses polymorphic k-mers to construct a high-resolution string graph and then leverages differential abundance for graph simplification. On real-world ONT metagenomes, myloasm assembled three times more complete circular contigs than the next-best assembler. Myloasm can make ONT and HiFi comparable for assembly: for a jointly sequenced gut metagenome, myloasm with ONT assembled more complete circular genomes than any assembler with HiFi. Myloasm recovers previously inaccessible within-species diversity; we recovered six complete Prevotella copri single-contig genomes from a gut metagenome and eight complete TM7 (Saccharibacteria) contigs with > 93% similarity from an oral metagenome. With this improved resolution, we resolved two 98% similar ermF antibiotic resistance genes spreading through distinct strain-specific mobile genetic elements in a human gut.

Journal Article↗
PubMed2026

DNA sequencing for microbial surveillance in cystic fibrosis airways: advances, challenges, and clinical translation.

SUMMARYDNA sequencing has revolutionized microbial surveillance in cystic fibrosis (CF), transforming pathogen identification from culture-dependent to total microbial community identification using molecular-based approaches. Techniques such as 16S rRNA gene sequencing have uncovered the complexity of the CF airway microbiome, while shotgun metagenomics, metatranscriptomics, and viromics now provide strain-level, functional, and viral insights beyond bacterial identification. Despite these advances, key technical and logistical challenges remain, including the processing of high-viscosity sputum samples, overwhelming host DNA contamination, managing large data sets, and the integration of complex bioinformatic outputs into clinical workflows. Emerging innovations such as host DNA depletion protocols, targeted enrichment panels, and adaptive sampling on Oxford Nanopore platforms are helping to overcome these barriers, improving microbial recovery and sequencing efficiency. As cystic fibrosis transmembrane conductance regulator (CFTR) modulator therapies are changing the lives of people with cystic fibrosis (pwCF), sequencing offers an unprecedented opportunity to track potential microbial adaptation in response. This review investigates current advances, limitations, and translational opportunities in DNA sequencing for CF airway microbiome surveillance, highlighting how these technologies can help reshape research and clinical microbiology in the post-modulator era.

Cystic Fibrosis↗
PubMed2005

Miniaturized detection technology in molecular diagnostics.

Miniaturization of genetic tests represents the convergence of molecular biology and engineering and is leading to a new class of small analyzers and test systems for genetic testing with improved analytical characteristics. Miniaturization initially focused on devices that contained micrometer-sized features designed for a particular analytical purpose (e.g., filters for cell isolation and chips for capillary electrophoresis). Now, the focus is shifting to analytical applications based on nano-sized objects such as nanotubes, nanochannels, nanoparticles, nanopores and nanocapacitors. These nanofabricated objects provide new tools for sequencing of nucleic acids and rapid, multiplexed, nucleic acid detection.

Animals↗