Assessing the fecal microbiota: an optimized ion torrent 16S rRNA gene-based analysis protocol

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Assessing the fecal microbiota: an optimized ion torrent 16S rRNA gene-based analysis protocol

Milani, Christian; Hevia, Arancha; Foroni, Elena; Duranti, Sabrina; Turroni, Francesca; Lugli, Gabriele A.; Sanchez, Borja; Martin, Rebeca; Gueimonde, Miguel; van Sinderen, Douwe; Margolles, Abelardo; Ventura, Marco
Date: 2013
Copyright: © 2013 Milani et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Copyright information: http://creativecommons.org/licenses/by/4.0/
Citation: Milani C, Hevia A, Foroni E, Duranti S, Turroni F, Lugli GA, et al. (2013) Assessing the Fecal Microbiota: An Optimized Ion Torrent 16S rRNA Gene-Based Analysis Protocol. PLoS ONE 8(7): e68739. doi:10.1371/journal.pone.0068739
Published Version: 10.1371/journal.pone.0068739

Abstract:

Assessing the distribution of 16S rRNA gene sequences within a biological sample represents the current state-of-the-art for determination of human gut microbiota composition. Advances in dissecting the microbial biodiversity of this ecosystem have very much been dependent on the development of novel high-throughput DNA sequencing technologies, like the Ion Torrent. However, the precise representation of this bacterial community may be affected by the protocols used for DNA extraction as well as by the PCR primers employed in the amplification reaction. Here, we describe an optimized protocol for 16S rRNA gene-based profiling of the fecal microbiota.

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© 2013 Milani et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited Except where otherwise noted, this item's license is described as © 2013 Milani et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
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