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High-resolution microbiome analysis enabled by linking of 16S rRNA gene sequences with adjacent genomic contexts
Sequence-based characterization of bacterial communities has long been a hostage of limitations of both 16S rRNA gene and whole metagenome sequencing. Neither approach is universally applicable, and the main efforts to resolve constraints have been devoted to improvement of computational prediction...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Microbiology Society
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8715429/ https://www.ncbi.nlm.nih.gov/pubmed/34473015 http://dx.doi.org/10.1099/mgen.0.000624 |
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author | Kapustina, Žana Medžiūnė, Justina Alzbutas, Gediminas Rokaitis, Irmantas Matjošaitis, Karolis Mackevičius, Gytis Žeimytė, Simona Karpus, Laurynas Lubys, Arvydas |
author_facet | Kapustina, Žana Medžiūnė, Justina Alzbutas, Gediminas Rokaitis, Irmantas Matjošaitis, Karolis Mackevičius, Gytis Žeimytė, Simona Karpus, Laurynas Lubys, Arvydas |
author_sort | Kapustina, Žana |
collection | PubMed |
description | Sequence-based characterization of bacterial communities has long been a hostage of limitations of both 16S rRNA gene and whole metagenome sequencing. Neither approach is universally applicable, and the main efforts to resolve constraints have been devoted to improvement of computational prediction tools. Here, we present semi-targeted 16S rRNA sequencing (st16S-seq), a method designed for sequencing V1–V2 regions of the 16S rRNA gene along with the genomic locus upstream of the gene. By in silico analysis of 13 570 bacterial genome assemblies, we show that genome-linked 16S rRNA sequencing is superior to individual hypervariable regions or full-length gene sequences in terms of classification accuracy and identification of gene copy numbers. Using mock communities and soil samples we experimentally validate st16S-seq and benchmark it against the established microbial classification techniques. We show that st16S-seq delivers accurate estimation of 16S rRNA gene copy numbers, enables taxonomic resolution at the species level and closely approximates community structures obtainable by whole metagenome sequencing. |
format | Online Article Text |
id | pubmed-8715429 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Microbiology Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-87154292021-12-29 High-resolution microbiome analysis enabled by linking of 16S rRNA gene sequences with adjacent genomic contexts Kapustina, Žana Medžiūnė, Justina Alzbutas, Gediminas Rokaitis, Irmantas Matjošaitis, Karolis Mackevičius, Gytis Žeimytė, Simona Karpus, Laurynas Lubys, Arvydas Microb Genom Methods Sequence-based characterization of bacterial communities has long been a hostage of limitations of both 16S rRNA gene and whole metagenome sequencing. Neither approach is universally applicable, and the main efforts to resolve constraints have been devoted to improvement of computational prediction tools. Here, we present semi-targeted 16S rRNA sequencing (st16S-seq), a method designed for sequencing V1–V2 regions of the 16S rRNA gene along with the genomic locus upstream of the gene. By in silico analysis of 13 570 bacterial genome assemblies, we show that genome-linked 16S rRNA sequencing is superior to individual hypervariable regions or full-length gene sequences in terms of classification accuracy and identification of gene copy numbers. Using mock communities and soil samples we experimentally validate st16S-seq and benchmark it against the established microbial classification techniques. We show that st16S-seq delivers accurate estimation of 16S rRNA gene copy numbers, enables taxonomic resolution at the species level and closely approximates community structures obtainable by whole metagenome sequencing. Microbiology Society 2021-09-02 /pmc/articles/PMC8715429/ /pubmed/34473015 http://dx.doi.org/10.1099/mgen.0.000624 Text en © 2021 The Authors https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License. |
spellingShingle | Methods Kapustina, Žana Medžiūnė, Justina Alzbutas, Gediminas Rokaitis, Irmantas Matjošaitis, Karolis Mackevičius, Gytis Žeimytė, Simona Karpus, Laurynas Lubys, Arvydas High-resolution microbiome analysis enabled by linking of 16S rRNA gene sequences with adjacent genomic contexts |
title | High-resolution microbiome analysis enabled by linking of 16S rRNA gene sequences with adjacent genomic contexts |
title_full | High-resolution microbiome analysis enabled by linking of 16S rRNA gene sequences with adjacent genomic contexts |
title_fullStr | High-resolution microbiome analysis enabled by linking of 16S rRNA gene sequences with adjacent genomic contexts |
title_full_unstemmed | High-resolution microbiome analysis enabled by linking of 16S rRNA gene sequences with adjacent genomic contexts |
title_short | High-resolution microbiome analysis enabled by linking of 16S rRNA gene sequences with adjacent genomic contexts |
title_sort | high-resolution microbiome analysis enabled by linking of 16s rrna gene sequences with adjacent genomic contexts |
topic | Methods |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8715429/ https://www.ncbi.nlm.nih.gov/pubmed/34473015 http://dx.doi.org/10.1099/mgen.0.000624 |
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