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De novo species identification using 16S rRNA gene nanopore sequencing

Nanopore sequencing is rapidly becoming more popular for use in various microbiota-based applications. Major limitations of current approaches are that they do not enable de novo species identification and that they cannot be used to verify species assignments. This severely limits applicability of...

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Autores principales: Angell, Inga Leena, Nilsen, Morten, Carlsen, Karin C. Lødrup, Carlsen, Kai-Håkon, Hedlin, Gunilla, Jonassen, Christine M., Marsland, Benjamin, Nordlund, Björn, Rehbinder, Eva Maria, Saunders, Carina, Skjerven, Håvard Ove, Staff, Anne Cathrine, Söderhäll, Cilla, Vettukattil, Riyas, Rudi, Knut
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7585375/
https://www.ncbi.nlm.nih.gov/pubmed/33150059
http://dx.doi.org/10.7717/peerj.10029
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author Angell, Inga Leena
Nilsen, Morten
Carlsen, Karin C. Lødrup
Carlsen, Kai-Håkon
Hedlin, Gunilla
Jonassen, Christine M.
Marsland, Benjamin
Nordlund, Björn
Rehbinder, Eva Maria
Saunders, Carina
Skjerven, Håvard Ove
Staff, Anne Cathrine
Söderhäll, Cilla
Vettukattil, Riyas
Rudi, Knut
author_facet Angell, Inga Leena
Nilsen, Morten
Carlsen, Karin C. Lødrup
Carlsen, Kai-Håkon
Hedlin, Gunilla
Jonassen, Christine M.
Marsland, Benjamin
Nordlund, Björn
Rehbinder, Eva Maria
Saunders, Carina
Skjerven, Håvard Ove
Staff, Anne Cathrine
Söderhäll, Cilla
Vettukattil, Riyas
Rudi, Knut
author_sort Angell, Inga Leena
collection PubMed
description Nanopore sequencing is rapidly becoming more popular for use in various microbiota-based applications. Major limitations of current approaches are that they do not enable de novo species identification and that they cannot be used to verify species assignments. This severely limits applicability of the nanopore sequencing technology in taxonomic applications. Here, we demonstrate the possibility of de novo species identification and verification using hexamer frequencies in combination with k-means clustering for nanopore sequencing data. The approach was tested on the human infant gut microbiota of 3-month-old infants. Using the hexamer k-means approach we identified two new low abundant species associated with vaginal delivery. In addition, we confirmed both the vaginal delivery association for two previously identified species and the overall high levels of bifidobacteria. Taxonomic assignments were further verified by mock community analyses. Therefore, we believe our de novo species identification approach will have widespread application in analyzing microbial communities in the future.
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spelling pubmed-75853752020-11-03 De novo species identification using 16S rRNA gene nanopore sequencing Angell, Inga Leena Nilsen, Morten Carlsen, Karin C. Lødrup Carlsen, Kai-Håkon Hedlin, Gunilla Jonassen, Christine M. Marsland, Benjamin Nordlund, Björn Rehbinder, Eva Maria Saunders, Carina Skjerven, Håvard Ove Staff, Anne Cathrine Söderhäll, Cilla Vettukattil, Riyas Rudi, Knut PeerJ Bioinformatics Nanopore sequencing is rapidly becoming more popular for use in various microbiota-based applications. Major limitations of current approaches are that they do not enable de novo species identification and that they cannot be used to verify species assignments. This severely limits applicability of the nanopore sequencing technology in taxonomic applications. Here, we demonstrate the possibility of de novo species identification and verification using hexamer frequencies in combination with k-means clustering for nanopore sequencing data. The approach was tested on the human infant gut microbiota of 3-month-old infants. Using the hexamer k-means approach we identified two new low abundant species associated with vaginal delivery. In addition, we confirmed both the vaginal delivery association for two previously identified species and the overall high levels of bifidobacteria. Taxonomic assignments were further verified by mock community analyses. Therefore, we believe our de novo species identification approach will have widespread application in analyzing microbial communities in the future. PeerJ Inc. 2020-10-21 /pmc/articles/PMC7585375/ /pubmed/33150059 http://dx.doi.org/10.7717/peerj.10029 Text en ©2020 Angell et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Angell, Inga Leena
Nilsen, Morten
Carlsen, Karin C. Lødrup
Carlsen, Kai-Håkon
Hedlin, Gunilla
Jonassen, Christine M.
Marsland, Benjamin
Nordlund, Björn
Rehbinder, Eva Maria
Saunders, Carina
Skjerven, Håvard Ove
Staff, Anne Cathrine
Söderhäll, Cilla
Vettukattil, Riyas
Rudi, Knut
De novo species identification using 16S rRNA gene nanopore sequencing
title De novo species identification using 16S rRNA gene nanopore sequencing
title_full De novo species identification using 16S rRNA gene nanopore sequencing
title_fullStr De novo species identification using 16S rRNA gene nanopore sequencing
title_full_unstemmed De novo species identification using 16S rRNA gene nanopore sequencing
title_short De novo species identification using 16S rRNA gene nanopore sequencing
title_sort de novo species identification using 16s rrna gene nanopore sequencing
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7585375/
https://www.ncbi.nlm.nih.gov/pubmed/33150059
http://dx.doi.org/10.7717/peerj.10029
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