Biology subjects

Leggett, R. M.

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

3 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↗

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↗