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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| Veröffentlicht in: | BMC genomics Jg. 26; H. 1; S. 835 - 6 |
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BioMed Central
26.09.2025
BioMed Central Ltd Springer Nature B.V BMC |
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| Abstract | 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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| AbstractList | 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.
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.
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. Abstract 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. BackgroundLong-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.ResultsAlthough 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.ConclusionsDespite 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. 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. 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. 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. 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. 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. Keywords: Automation, Long-read sequencing, Metagenomics, Oxford nanopore, Library preparation, Soil 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.BACKGROUNDLong-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.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.RESULTSAlthough 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.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.CONCLUSIONSDespite 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. |
| ArticleNumber | 835 |
| Audience | Academic |
| Author | Haxhiraj, Qiellor Joslin, Gabrielle R. Roper, Katherine Child, Harry T. Tennant, Richard K. Wierzbicki, Lucy |
| Author_xml | – sequence: 1 givenname: Harry T. surname: Child fullname: Child, Harry T. organization: Geography, Faculty of Environment, Science and Economy – sequence: 2 givenname: Lucy surname: Wierzbicki fullname: Wierzbicki, Lucy organization: Geography, Faculty of Environment, Science and Economy – sequence: 3 givenname: Gabrielle R. surname: Joslin fullname: Joslin, Gabrielle R. organization: Geography, Faculty of Environment, Science and Economy – sequence: 4 givenname: Katherine surname: Roper fullname: Roper, Katherine organization: Agilent Technologies LDA UK Limited – sequence: 5 givenname: Qiellor surname: Haxhiraj fullname: Haxhiraj, Qiellor organization: Agilent Technologies LDA UK Limited – sequence: 6 givenname: Richard K. surname: Tennant fullname: Tennant, Richard K. email: R.K.Tennant@exeter.ac.uk organization: Geography, Faculty of Environment, Science and Economy |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/41013192$$D View this record in MEDLINE/PubMed |
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Long-read sequencing has revolutionised metagenomics through improved metagenome assembly, taxonomic classification and functional characterisation.... Long-read sequencing has revolutionised metagenomics through improved metagenome assembly, taxonomic classification and functional characterisation. Automation... Background Long-read sequencing has revolutionised metagenomics through improved metagenome assembly, taxonomic classification and functional characterisation.... BackgroundLong-read sequencing has revolutionised metagenomics through improved metagenome assembly, taxonomic classification and functional characterisation.... Abstract Background Long-read sequencing has revolutionised metagenomics through improved metagenome assembly, taxonomic classification and functional... |
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| SubjectTerms | 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 |
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| Title | Automated environmental metagenomics using Oxford nanopore sequencing |
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| Volume | 26 |
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