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Taxonomy of anaerobic digestion microbiome reveals biases associated with the applied high throughput sequencing strategies

In the past few years, many studies investigated the anaerobic digestion microbiome by means of 16S rRNA amplicon sequencing. Results obtained from these studies were compared to each other without taking into consideration the followed procedure for amplicons preparation and data analysis. This neg...

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Autores principales: Campanaro, Stefano, Treu, Laura, Kougias, Panagiotis G., Zhu, Xinyu, Angelidaki, Irini
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5792648/
https://www.ncbi.nlm.nih.gov/pubmed/29386622
http://dx.doi.org/10.1038/s41598-018-20414-0
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author Campanaro, Stefano
Treu, Laura
Kougias, Panagiotis G.
Zhu, Xinyu
Angelidaki, Irini
author_facet Campanaro, Stefano
Treu, Laura
Kougias, Panagiotis G.
Zhu, Xinyu
Angelidaki, Irini
author_sort Campanaro, Stefano
collection PubMed
description In the past few years, many studies investigated the anaerobic digestion microbiome by means of 16S rRNA amplicon sequencing. Results obtained from these studies were compared to each other without taking into consideration the followed procedure for amplicons preparation and data analysis. This negligence was mainly due to the lack of knowledge regarding the biases influencing specific steps of the microbiome investigation process. In the present study, the main technical aspects of the 16S rRNA analysis were checked giving special attention to the approach used for high throughput sequencing. More specifically, the microbial compositions of three laboratory scale biogas reactors were analyzed before and after addition of sodium oleate by sequencing the microbiome with three different approaches: 16S rRNA amplicon sequencing, shotgun DNA and shotgun RNA. This comparative analysis revealed that, in amplicon sequencing, abundance of some taxa (Euryarchaeota and Spirochaetes) was biased by the inefficiency of universal primers to hybridize all the templates. Reliability of the results obtained was also influenced by the number of hypervariable regions under investigation. Finally, amplicon sequencing and shotgun DNA underestimated the Methanoculleus genus, probably due to the low 16S rRNA gene copy number encoded in this taxon.
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spelling pubmed-57926482018-02-12 Taxonomy of anaerobic digestion microbiome reveals biases associated with the applied high throughput sequencing strategies Campanaro, Stefano Treu, Laura Kougias, Panagiotis G. Zhu, Xinyu Angelidaki, Irini Sci Rep Article In the past few years, many studies investigated the anaerobic digestion microbiome by means of 16S rRNA amplicon sequencing. Results obtained from these studies were compared to each other without taking into consideration the followed procedure for amplicons preparation and data analysis. This negligence was mainly due to the lack of knowledge regarding the biases influencing specific steps of the microbiome investigation process. In the present study, the main technical aspects of the 16S rRNA analysis were checked giving special attention to the approach used for high throughput sequencing. More specifically, the microbial compositions of three laboratory scale biogas reactors were analyzed before and after addition of sodium oleate by sequencing the microbiome with three different approaches: 16S rRNA amplicon sequencing, shotgun DNA and shotgun RNA. This comparative analysis revealed that, in amplicon sequencing, abundance of some taxa (Euryarchaeota and Spirochaetes) was biased by the inefficiency of universal primers to hybridize all the templates. Reliability of the results obtained was also influenced by the number of hypervariable regions under investigation. Finally, amplicon sequencing and shotgun DNA underestimated the Methanoculleus genus, probably due to the low 16S rRNA gene copy number encoded in this taxon. Nature Publishing Group UK 2018-01-31 /pmc/articles/PMC5792648/ /pubmed/29386622 http://dx.doi.org/10.1038/s41598-018-20414-0 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Campanaro, Stefano
Treu, Laura
Kougias, Panagiotis G.
Zhu, Xinyu
Angelidaki, Irini
Taxonomy of anaerobic digestion microbiome reveals biases associated with the applied high throughput sequencing strategies
title Taxonomy of anaerobic digestion microbiome reveals biases associated with the applied high throughput sequencing strategies
title_full Taxonomy of anaerobic digestion microbiome reveals biases associated with the applied high throughput sequencing strategies
title_fullStr Taxonomy of anaerobic digestion microbiome reveals biases associated with the applied high throughput sequencing strategies
title_full_unstemmed Taxonomy of anaerobic digestion microbiome reveals biases associated with the applied high throughput sequencing strategies
title_short Taxonomy of anaerobic digestion microbiome reveals biases associated with the applied high throughput sequencing strategies
title_sort taxonomy of anaerobic digestion microbiome reveals biases associated with the applied high throughput sequencing strategies
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5792648/
https://www.ncbi.nlm.nih.gov/pubmed/29386622
http://dx.doi.org/10.1038/s41598-018-20414-0
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