Rapid profiling of the preterm infant gut microbiota using nanopore sequencing aids 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.

Data and Resources

Additional Info

Field Value
Author Leggett, Richard M.
Last Updated November 20, 2019, 16:57 (UTC)
Created August 1, 2019, 10:28 (UTC)
Article Host Type publisher
Article Is Open Access true
Article License Type cc-by-nc-nd
Article Version Type publishedVersion
Citation Report https://scite.ai/reports/10.1101/180406
DOI 10.1101/180406
Date Last Updated 2019-01-01T11:00:37.632472
Evidence open (via page says license)
Funder code(s)
Journal Is Open Access false
Open Access Status hybrid
PDF URL https://www.biorxiv.org/content/biorxiv/early/2018/10/12/180406.full.pdf
Publisher URL https://doi.org/10.1101/180406