Biology subjects

Leggett, R. M.

Publications and source records attributed to Leggett, R. M..

14 recordsLinked to original sources

bioRxiv2026

City life: airborne DNA metagenomic biodiversity monitoring reveals dynamic changes across time and space

Airborne environmental DNA can capture biodiversity across the tree of life, but low sample biomass makes rapid, untargeted detection technically challenging. We combined 45-min air collection, nanopore sequencing and real-time taxonomic analysis in a shotgun metagenomic workflow capable of producing results within 3 hours. Across 77 samples from 13 London sites, including a year of weekly sampling at the Natural History Museum Wildlife Garden, we detected 1,916 species spanning bacteria, fungi, plants and animals. Communities varied spatially and seasonally, shifting from plant dominance in spring to ascomycete dominance in summer and basidiomycete dominance in late autumn and winter. Plant read abundance increased with upwind vegetation, linking airborne signals to surrounding habitat. Detection of catalogued garden plants depended on reference availability, dispersal biology, plant size and proximity to the collector. Together, these findings establish airborne shotgun metagenomics as a platform for rapid, repeated and scalable biodiversity assessment across space and time.

ecology↗

bioRxiv2025

Decoding the microbiome and resistome of advanced chronic liver disease through long-read metagenomics

IntroductionPatients with advanced chronic liver disease (ACLD) and underlying cirrhosis frequently require repeated courses of antimicrobial therapy, with both the frequency and spectrum of antimicrobial exposure increasing alongside disease progression. In this population, impaired immune function and increased intestinal barrier dysfunction contribute to a heightened susceptibility of multidrug-resistant bacterial infections. ObjectiveTo comprehensively characterise the gastrointestinal microbiome and antimicrobial resistance gene (ARG) landscape across the clinical spectrum of ACLD, and to identify microbial and resistome signatures associated with disease severity. DesignWe employed long-read metagenomic sequencing (Oxford Nanopore Technologies) to profile the gastrointestinal microbiome and resistome across distinct ACLD stages: acute-on-chronic liver failure (ACLF), decompensated cirrhosis (DC), and stable cirrhosis, compared to healthy controls. ResultsACLF patients had pronounced levels of Enterococcus faecium, with six samples out of 28 showing over 95% relative abundance, suggesting its potential as a bacterial biomarker for advanced cirrhosis. We reconstructed 28 high-quality MAGs of E. faecium from cirrhosis patients, 17 of which originated from ACLF cases. This dominance of E. faecium correlated with substantially reduced microbial diversity and a marked depletion of key commensal taxa, including Blautia, Akkermansia, Faecalibacterium, and Bifidobacterium. Resistome analysis revealed significant enrichment of clinically relevant ARGs in DC and ACLF, including those conferring resistance to aminoglycosides, beta-lactams, and glycopeptides, correlating with prior antimicrobial exposure. ConclusionLong-read metagenomics enables high-resolution characterisation of microbial and resistome dynamics across ACLD severities. By capturing taxonomic shifts, functional potential, and ARG enrichment, this approach provides valuable insights into microbiome trajectories linked with disease severity, informing mechanistic research and potential clinical interventions. Impact statementChronic liver disease is a major global health burden, responsible for approximately 2 million deaths each year. Advanced chronic liver disease profoundly disrupts the gut microbiome, often exacerbated by repeated antibiotic exposure, promoting the persistence of antimicrobial-resistant organisms. Leveraging Oxford Nanopore Technologies long-read metagenomic sequencing, this study delivers high-resolution insights into the gut microbiome and resistome across progressive stages of cirrhosis. We reveal Enterococcus faecium dominance as a defining feature of cirrhosis, accompanied by severe loss of commensal diversity and enrichment of clinically significant resistance genes. These findings underscore the clinical utility of culture-independent metagenomic profiling for detecting pathogenic taxa and resistance determinants within the gut ecosystem of high-risk patients. Our work highlights the translational potential of long-read metagenomics as an accessible tool for pathogen surveillance, antimicrobial stewardship, and precision infection management in advanced liver disease.

microbiology↗

bioRxiv2025

MARTi: a real-time analysis and visualisation tool for nanopore metagenomics

The emergence of nanopore sequencing technology has the potential to transform metagenomics by offering low-cost, portable, and long-read sequencing capabilities. Furthermore, these platforms enable real-time data generation, which could significantly reduce the time from sample collection to result, a crucial factor for point-of-care diagnostics and bio-surveillance. However, the full potential of real-time metagenomics remains largely unfulfilled due to a lack of accessible, open-source bioinformatic tools. We present MARTi (Metagenomic Analysis in Real-Time), an innovative open-source software designed for the real-time analysis, visualisation, and exploration of metagenomic data. MARTi supports various classification methods, including BLAST, Centrifuge, and Kraken2, letting users customise parameters and utilise their own databases for taxonomic classification and antimicrobial resistance analysis. With a user-friendly, browser-based graphical interface, MARTi provides dynamic, real-time updates on community composition and AMR gene identification. MARTis architecture and operational flexibility make it suitable for diverse research applications, ranging from in-field analysis to large-scale metagenomic studies. Using both simulated and real-world data, we demonstrate MARTis performance in read classification, taxon detection, and relative abundance estimation. By bridging the gap between sequencing and actionable insights, MARTi marks a significant advance in the accessibility and functionality of real-time metagenomic analysis.

bioinformatics↗

bioRxiv2024

A Comparison of Nanopore Data Types, Basecalling, and Assembly Algorithms: Whole Plant Genome Assembly and Methylation Analysis from a Single MinION Flow cell

BackgroundOxford Nanopore Technologies MinION sequencer is a compact, USB-powered device that has been available since 2014. Since the release of the earliest model, the throughput and error rate of the platform have improved dramatically and it has become possible to consider sequencing and assembly of eukaryotic organisms using a single nanopore flow cell. Here, we present MinION sequence data, assembly and methylation analysis for the Columbia (Col-0) accession of the model plant Arabidopsis thaliana. Further, we demonstrate the effect that recent developments (specifically the Q20+ chemistry and basecaller improvements) have had on read accuracy and assembly quality. FindingsDNA extracted from leaves of A. thaliana Col-0 was sequenced on two MinION flow cells, together amounting to 115x coverage of the 135 Mb genome. Reads were assembled and polished using several bioinformatics pipelines for nanopore sequence data. We performed CpG methylation analysis directly from the nanopore data, and this correlated well with a previously published bisulfite dataset. ConclusionsOur results suggest that a single MinION flow cell can generate sufficient data to assemble a genome of 135Mb, indicate functional elements, and unlock genomics for researchers of novel species from $600 in under 5 days. Here we release the full nanopore read sets for both flow cells, together with the nanopore-only assemblies. The data presented here is expected to be of particular interest to those in the Arabidopsis community, designing genome projects (with functional annotations), expanding our understanding of epigenetics across the tree of life, and for designing university or high school practicals teaching genomics and epigenomics. HighlightWe evaluate the effect of recent nanopore chemistry and software improvements on the ability to assemble a complete genome and conduct methylation analysis using data from a single MinION flow cell.

genomics↗

bioRxiv2023

Algebraic invariants for inferring 4-leaf semi-directed phylogenetic networks

A core goal of phylogenomics is to determine the evolutionary history of a set of species from biological sequence data. Phylogenetic networks are able to describe more complex evolutionary phenomena than phylogenetic trees but are more difficult to accurately reconstruct. Recently, there has been growing interest in developing methods to infer semi-directed phylogenetic networks. As computing such networks can be computationally intensive, one approach to building such networks is to puzzle together smaller networks. Thus, it is essential to have robust methods for inferring semi-directed phylogenetic networks on small numbers of taxa. In this paper, we investigate an algebraic method for performing phylogenetic network inference from nucleotide sequence data on 4-leaf semi-directed phylogenetic networks by analysing the distribution of leaf-pattern probabilities. On simulated data, we found that we can correctly identify with high accuracy the undirected phylogenetic network for sequences of length at least 10kbp. We found that identifying the semi-directed network is more challenging and requires sequences of length approaching 10Mbp. We are also able to use our approach to identify tree-like evolution and determine the underlying tree. Finally, we employ our method on a real dataset from Xiphophorus species and use the results to build a phylogenetic network.

evolutionary biology↗

bioRxiv2022

Air-seq: Measuring air metagenomic diversity in an agricultural ecosystem

BackgroundAll species shed DNA into their environment during life or in death providing an opportunity to monitor biodiversity via its environmental DNA. Biodiversity monitoring using environmental DNA based technologies has become an important tool in understanding ecosystems. In recent years promising progress for non-invasive and, more importantly, non-destructive monitoring has been made by combining the retrieval of information transmitted by released environmental DNA with high-throughput sequencing technologies. Important ecosystems under continuous threat by disease but essential for food supplies are agricultural systems, often farmed as large monocultures and so highly vulnerable to disease outbreaks. Pest and pathogen monitoring in agricultural ecosystems is therefore key for efficient and early disease prevention and management. Air is rich in biodiversity, but has the lowest DNA concentration of all environmental media and yet it is required for windborne spread by many of the worlds most damaging crop pathogens. Our work and recent research suggests that ecosystems can be monitored efficiently using airborne nucleic acid information. ResultsHere we show that the airborne DNA of microbes can be recovered, sequenced and taxonomically classified, including down to the species level. Monitoring a field growing key crops we show that Air-seq can identify the presence of agriculturally significant pathogens and quantify their changing abundance over a period of 1.5 months often correlating with weather variables. ConclusionWe add to the evidence that aerial environmental DNA can be used as a source for biomonitoring in agricultural and more general terrestrial ecosystems. The ability to detect fluxes and occurrence patterns of species and strains with high throughput sample processing and analysis technologies highlights the value of airborne environmental DNA in monitoring biodiversity changes and tracking of taxa of human interest or concern.

genomics↗

bioRxiv2021

How low can you go? Driving down the DNA input requirements for nanopore sequencing

The requirement for large amounts of purified DNA limits many sequencing experiments, especially when seeking to avoid pre-amplification or when using third generation technology to sequence molecules directly. We wanted to test the limits of current nanopore sequencing input requirements and devised a set of experiments to evaluate extraction and library preparation approaches for low inputs. We found an optimised bead beating approach combined with a magnetic bead protocol, rather than traditional spin columns for DNA extraction, improved both molecule length, integrity score and DNA yield. Through reducing the DNA input to as little as 6.25 % of recommended (25 ng versus 400 ng) and reaction volumes in half, library construction can be completed, and sequencing begun within 20 minutes of sample collection. Applying these approaches, we demonstrated that our pipeline can be used as a cheap and effective method to de novo assemble a genome and identify genes from low quantities and quality of DNA. With our rapid extraction protocol using transportable equipment and low input library construction we were able to generate a de novo assembly from a single insect (Drosophila melanogaster) spanning 125 Mbp / 85 % of the reference genome, over 96.9% complete BUSCO genes, with a contig N50 over 1.2 Mbp, including chromosome arm sized contigs, for a modest consumable cost under {pound}600.

genomics↗

bioRxiv2021

Capturing variation in metagenomic assembly graphs with MetaCortex

MotivationThe assembly of contiguous sequence from metagenomic samples presents a particular challenge, due to the presence of multiple species, often closely related, at varying levels of abundance. Capturing diversity within species, for example viral haplotypes, or bacterial strain-level diversity, is even more challenging. ResultsWe present MetaCortex, a metagenome assembler that captures intra-species diversity by searching for signatures of local variation along assembled sequences in the underlying assembly graph and outputting these sequences in sequence graph format. We show that MetaCortex produces accurate assemblies with higher genome coverage and contiguity than other popular metagenomic assemblers on mock viral communities with high levels of strain level diversity, and on simulated communities containing simulated strains. Availability and ImplementationSource code is freely available to download from https://github.com/SR-Martin/metacortex, is implemented in C and supported on MacOS and Linux. Contactrichard.leggett@earlham.ac.uk Supplementary informationSupplementary materials are available at the journals website. All assemblies, simulated reads, and simulated genomes used in this paper have been deposited online on Zenodo and can be found at DOI 10.5281/zenodo.6616437.

bioinformatics↗

bioRxiv2021

Nanopore adaptive sampling: a tool for enrichment of low abundance species in metagenomic samples

BackgroundAdaptive sampling is a method of software-controlled enrichment unique to nanopore sequencing platforms recently implemented in Oxford Nanopores own control software. By examining the first few hundred bases of a DNA molecule as it passes through a pore, software can determine if the molecule is sufficiently interesting to sequence in its entirety. If not, the molecule is ejected from the pore by reversing the voltage across it, freeing the pore for a new molecule. User supplied sequences define the targets to be sequenced or ejected. Here we explore the potential of using adaptive sampling for enrichment of rarer species within metagenomic samples. ResultsWe created a synthetic mock community consisting of seven bacterial species at different proportions ranging from 1.2% to 47% and used this as the basis for a series of enrichment and depletion experiments. To investigate the effect of DNA length on adaptive sampling efficiency, we created sequencing libraries with mean read lengths of 1.7 kbp, 4.7 kbp, 10.6 kbp, and 12.8 kbp and enriched or depleted for individual and multiple species over a series of sequencing runs. Across all experiments enrichment ranged from 1.67-fold for the most abundant species with the shortest read length to 13.87-fold for the least abundant species with the longest read length. Factoring in the reduction to sequence output associated with repeatedly rejecting molecules reduces the calculated efficiency of this enrichment to between 0.96-fold and 4.93-fold. We note that reducing ejections due to false negatives (approximately 36%) would significantly increase efficiency. We used the relationship between abundance, molecule length and enrichment factor to produce a mathematical model of enrichment based on molecule length and relative abundance, whose predictions correlated strongly with experimental data. A web application is provided to allow researchers to explore model predictions in advance of performing their own experiments. ConclusionsOur data clearly demonstrates the benefit for enriching low abundant species in adaptive sampling metagenomic experiments, especially with longer molecules, and our mathematical model can be used to determine whether a given experimental DNA sample is suitable for adaptive sampling. Notably, repeated voltage reversals have no effect on pore stability.

genomics↗

bioRxiv2020

Metagenome-assembled genomes of phytoplankton communities across the Arctic Circle

Phytoplankton communities significantly contribute to global biogeochemical cycles of elements and underpin marine food webs. Although their uncultured genetic diversity has been estimated by planetary-scale metagenome sequencing and subsequent reconstruction of metagenome-assembled genomes (MAGs), this approach has yet to be applied for eukaryote-enriched polar and non-polar phytoplankton communities. Here, we have assembled draft prokaryotic and eukaryotic MAGs from environmental DNA extracted from chlorophyll a maximum layers in the surface ocean across the Arctic Circle in the Atlantic. From 679 Gbp and estimated 50 million genes in total, we recovered 140 MAGs of medium to high quality. Although there was a strict demarcation between polar and non-polar MAGs, adjacent sampling stations in each environment on either side of the Arctic Circle had MAGs in common. Furthermore, phylogenetic placement revealed eukaryotic MAGs to be more diverse in the Arctic whereas prokaryotic MAGs were more diverse in the Atlantic south of the Arctic Circle. Approximately 60% of protein families were shared between polar and non-polar MAGs for both prokaryotes and eukaryotes. However, eukaryotic MAGs had more protein families unique to the Arctic whereas prokaryotic MAGs had more families unique to south of the Arctic circle. Thus, our study enabled us to place differences in functional plankton diversity in a genomic context to reveal that the evolution of these MAGs likely was driven by significant differences in the seascape on either side of an ecosystem boundary that separates polar from non-polar surface ocean waters in the North Atlantic.

microbiology↗

bioRxiv2019

Alvis: a tool for contig and read ALignment VISualisation and chimera detection

BackgroundThe analysis of long reads or the assessment of assembly or target capture data often necessitates running alignments against reference genomes or gene sets. Aligner outputs are often parsed automatically by scripts, but many kinds of analysis can benefit from the understanding that can follow human inspection of individual alignments.\n\nFindingsWe developed Alvis, a simple command line tool that can generate visualisations for a number of common alignment analysis tasks. Alvis is a fast and portable tool that accepts input in the most common alignment formats and will output production ready vector images. Additionally, Alvis will highlight potentially chimeric reads or contigs, a common source of misassemblies. We found that splitting chimeric reads using the output provided by Alvis can improve the contiguity of assemblies, while maintaining correctness.

bioinformatics↗

bioRxiv2019

Semi-quantitative characterisation of mixed pollen samples using MinION sequencing and Reverse Metagenomics (RevMet)

1. The ability to identify and quantify the constituent plant species that make up a mixed-species sample of pollen has important applications in ecology, conservation, and agriculture. Recently, metabarcoding protocols have been developed for pollen that can identify constituent plant species, but there are strong reasons to doubt that metabarcoding can accurately quantify their relative abundances. A PCR-free, shotgun metagenomics approach has greater potential for accurately quantifying species relative abundances, but applying metagenomics to eukaryotes is challenging due to low numbers of reference genomes. 2. We have developed a pipeline, RevMet (Reverse Metagenomics), that allows reliable and semi-quantitative characterization of the species composition of mixed-species eukaryote samples, such as bee-collected pollen, without requiring reference genomes. Instead, reference species are represented only by genome skims: low-cost, low-coverage, short-read sequence datasets. The skims are mapped to individual long reads sequenced from mixed-species samples using the MinION, a portable nanopore sequencing device, and each long read is uniquely assigned to a plant species. 3. We genome-skimmed 49 wild UK plant species, validated our pipeline with mock DNA mixtures of known composition, and then applied RevMet to pollen loads collected from wild bees. We demonstrate that RevMet can identify plant species present in mixed-species samples at proportions of DNA [≥]1%, with few false positives and false negatives, and reliably differentiate species represented by high versus low amounts of DNA in a sample. 4. The RevMet pipeline could readily be adapted to generate semi-quantitative datasets for a wide range of mixed eukaryote samples, which could include characterising diets, quantifying allergenic pollen from air samples, quantifying soil fauna, and identifying the compositions of algal and diatom communities. Our per-sample costs were {pound}90 per genome skim and {pound}60 per pollen sample, and new versions of sequencers available now will further reduce these costs.

ecology↗

bioRxiv2018

Rapid Diagnosis of Lower Respiratory Infection using Nanopore-based Clinical Metagenomics

Lower respiratory infections (LRIs) accounted for three million deaths worldwide in 2016, the leading infectious cause of mortality. The \"gold standard\" for investigation of bacterial LRIs is culture, which has poor sensitivity and is too slow to guide early antibiotic therapy. Metagenomic sequencing potentially could replace culture, providing rapid, sensitive and comprehensive results. We developed a metagenomics pipeline for the investigation of bacterial LRIs using saponin-based host DNA depletion combined with rapid nanopore sequencing. The first iteration of the pipeline was tested on respiratory samples from 40 patients. It was then refined to reduce turnaround and increase sensitivity, before testing a further 41 samples. The refined method was 96.6% concordant with culture for detection of pathogens and could accurately detect resistance genes with a turnaround time of six hours. This study demonstrates that nanopore metagenomics can rapidly and accurately characterise bacterial LRIs when combined with efficient human DNA depletion.

microbiology↗

bioRxiv2017

Rapid MinION metagenomic profiling of the preterm infant gut microbiota to aid in pathogen diagnostics

The Oxford Nanopore MinION sequencing platform offers near real time analysis of DNA reads as they are generated, which makes the device attractive for in-field or clinical deployment, e.g. rapid diagnostics. We used the MinION platform for shotgun metagenomic sequencing and analysis of gut-associated microbial communities; firstly, we used a 20-species human microbiota mock community to demonstrate how Nanopore metagenomic sequence data can be reliably and rapidly classified. Secondly, we profiled faecal microbiomes from preterm infants at increased risk of necrotising enterocolitis and sepsis. In single patient time course, we captured the diversity of the immature gut microbiota and observed how its complexity changes over time in response to interventions, i.e. probiotic, antibiotics and episodes of suspected sepsis. Finally, we performed real-time runs from sample to analysis using faecal samples of critically ill infants and of healthy infants receiving probiotic supplementation. Real-time analysis was facilitated by our new NanoOK RT software package which analysed sequences as they were generated. We reliably identified potentially pathogenic taxa (i.e. Klebsiella pneumoniae and Enterobacter cloacae) and their corresponding antimicrobial resistance (AMR) gene profiles within as little as one hour of sequencing. Antibiotic treatment decisions may be rapidly modified in response to these AMR profiles, which we validated using pathogen isolation, whole genome sequencing and antibiotic susceptibility testing. Our results demonstrate that our pipeline can process clinical samples to a rich dataset able to inform tailored patient antimicrobial treatment in less than 5 hours.

genomics↗