Automated environmental metagenomics using Oxford nanopore sequencing

Background Long-read sequencing has revolutionised metagenomics through improved metagenome assembly, taxonomic classification and functional characterisation. Automation can enhance the throughput, reproducibility, and accuracy of library preparation. However, the validation of automated library pr...

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Bibliographic Details
Published in:BMC genomics Vol. 26; no. 1; pp. 835 - 6
Main Authors: Child, Harry T., Wierzbicki, Lucy, Joslin, Gabrielle R., Roper, Katherine, Haxhiraj, Qiellor, Tennant, Richard K.
Format: Journal Article
Language:English
Published: London BioMed Central 26.09.2025
BioMed Central Ltd
Springer Nature B.V
BMC
Subjects:
Analysis
Animal Genetics and Genomics
Automation
Bar codes
Biological diversity
Biomedical and Life Sciences
Classification
Community structure
DNA sequencing
Gene Library
Genetic testing
Genomes
Genomic libraries
High-Throughput Nucleotide Sequencing - methods
Library preparation
Life Sciences
Long-read sequencing
Mechanization
Metagenome
Metagenomics
Metagenomics - methods
Methods
Microarrays
Microbial Genetics and Genomics
Microorganisms
Nanopore Sequencing - methods
Nucleotide sequencing
Oxford nanopore
Plant Genetics and Genomics
Proteomics
Protocol
Reproducibility
Sequence Analysis, DNA - methods
Soil
Soils
Taxonomy
United Kingdom
United Kingdom > UK
Long-read sequencing
Soil
Metagenomics
Automation
Oxford nanopore
Library preparation
ISSN:1471-2164, 1471-2164
Online Access:Get full text
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Summary:Background Long-read sequencing has revolutionised metagenomics through improved metagenome assembly, taxonomic classification and functional characterisation. Automation can enhance the throughput, reproducibility, and accuracy of library preparation. However, the validation of automated library preparation protocols remains undetermined for metagenomic workflows, which are particularly sensitive to methodological perturbation. Here, we compare long-read metagenomic sequencing of environmental samples through parallel manual and automated protocols. Results Although automated library preparation led to minor reduction in read and contig lengths, taxonomic classification rate and alpha diversity was slightly higher than manual libraries, including the detection of more rare taxa. Despite this, no significant difference in microbial community structure was identified between manual and automated libraries. Conclusions Despite minor differences in sequencing and classification metrics, automated and manual library preparation resulted in comparable characterization of environmental community metagenomes. These findings demonstrate the suitability of automation for high-throughput long-read metagenomics, with broad applicability to automated long-read sequencing for improved efficiency and reproducibility.
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ISSN:1471-2164
1471-2164
DOI:10.1186/s12864-025-11989-w