Phylogenetic Placement of Exact Amplicon Sequences Improves Associations with Clinical Information
ABSTRACT Recent algorithmic advances in amplicon-based microbiome studies enable the inference of exact amplicon sequence fragments. These new methods enable the investigation of sub-operational taxonomic units (sOTU) by removing erroneous sequences. However, short (e.g., 150-nucleotide [nt]) DNA se...
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American Society for Microbiology
2018
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oai:doaj.org-article:786a8d36f43344f08d693065616724182021-12-02T18:15:44ZPhylogenetic Placement of Exact Amplicon Sequences Improves Associations with Clinical Information10.1128/mSystems.00021-182379-5077https://doaj.org/article/786a8d36f43344f08d693065616724182018-06-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/mSystems.00021-18https://doaj.org/toc/2379-5077ABSTRACT Recent algorithmic advances in amplicon-based microbiome studies enable the inference of exact amplicon sequence fragments. These new methods enable the investigation of sub-operational taxonomic units (sOTU) by removing erroneous sequences. However, short (e.g., 150-nucleotide [nt]) DNA sequence fragments do not contain sufficient phylogenetic signal to reproduce a reasonable tree, introducing a barrier in the utilization of critical phylogenetically aware metrics such as Faith’s PD or UniFrac. Although fragment insertion methods do exist, those methods have not been tested for sOTUs from high-throughput amplicon studies in insertions against a broad reference phylogeny. We benchmarked the SATé-enabled phylogenetic placement (SEPP) technique explicitly against 16S V4 sequence fragments and showed that it outperforms the conceptually problematic but often-used practice of reconstructing de novo phylogenies. In addition, we provide a BSD-licensed QIIME2 plugin (https://github.com/biocore/q2-fragment-insertion) for SEPP and integration into the microbial study management platform QIITA. IMPORTANCE The move from OTU-based to sOTU-based analysis, while providing additional resolution, also introduces computational challenges. We demonstrate that one popular method of dealing with sOTUs (building a de novo tree from the short sequences) can provide incorrect results in human gut metagenomic studies and show that phylogenetic placement of the new sequences with SEPP resolves this problem while also yielding other benefits over existing methods.Stefan JanssenDaniel McDonaldAntonio GonzalezJose A. Navas-MolinaLingjing JiangZhenjiang Zech XuKevin WinkerDeborah M. KadoEric OrwollMark ManarySiavash MirarabRob KnightAmerican Society for MicrobiologyarticleSEPPamplicon sequencingmicrobial community analysisphylogenetic placementMicrobiologyQR1-502ENmSystems, Vol 3, Iss 3 (2018) |
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| collection |
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| language |
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| topic |
SEPP amplicon sequencing microbial community analysis phylogenetic placement Microbiology QR1-502 |
| spellingShingle |
SEPP amplicon sequencing microbial community analysis phylogenetic placement Microbiology QR1-502 Stefan Janssen Daniel McDonald Antonio Gonzalez Jose A. Navas-Molina Lingjing Jiang Zhenjiang Zech Xu Kevin Winker Deborah M. Kado Eric Orwoll Mark Manary Siavash Mirarab Rob Knight Phylogenetic Placement of Exact Amplicon Sequences Improves Associations with Clinical Information |
| description |
ABSTRACT Recent algorithmic advances in amplicon-based microbiome studies enable the inference of exact amplicon sequence fragments. These new methods enable the investigation of sub-operational taxonomic units (sOTU) by removing erroneous sequences. However, short (e.g., 150-nucleotide [nt]) DNA sequence fragments do not contain sufficient phylogenetic signal to reproduce a reasonable tree, introducing a barrier in the utilization of critical phylogenetically aware metrics such as Faith’s PD or UniFrac. Although fragment insertion methods do exist, those methods have not been tested for sOTUs from high-throughput amplicon studies in insertions against a broad reference phylogeny. We benchmarked the SATé-enabled phylogenetic placement (SEPP) technique explicitly against 16S V4 sequence fragments and showed that it outperforms the conceptually problematic but often-used practice of reconstructing de novo phylogenies. In addition, we provide a BSD-licensed QIIME2 plugin (https://github.com/biocore/q2-fragment-insertion) for SEPP and integration into the microbial study management platform QIITA. IMPORTANCE The move from OTU-based to sOTU-based analysis, while providing additional resolution, also introduces computational challenges. We demonstrate that one popular method of dealing with sOTUs (building a de novo tree from the short sequences) can provide incorrect results in human gut metagenomic studies and show that phylogenetic placement of the new sequences with SEPP resolves this problem while also yielding other benefits over existing methods. |
| format |
article |
| author |
Stefan Janssen Daniel McDonald Antonio Gonzalez Jose A. Navas-Molina Lingjing Jiang Zhenjiang Zech Xu Kevin Winker Deborah M. Kado Eric Orwoll Mark Manary Siavash Mirarab Rob Knight |
| author_facet |
Stefan Janssen Daniel McDonald Antonio Gonzalez Jose A. Navas-Molina Lingjing Jiang Zhenjiang Zech Xu Kevin Winker Deborah M. Kado Eric Orwoll Mark Manary Siavash Mirarab Rob Knight |
| author_sort |
Stefan Janssen |
| title |
Phylogenetic Placement of Exact Amplicon Sequences Improves Associations with Clinical Information |
| title_short |
Phylogenetic Placement of Exact Amplicon Sequences Improves Associations with Clinical Information |
| title_full |
Phylogenetic Placement of Exact Amplicon Sequences Improves Associations with Clinical Information |
| title_fullStr |
Phylogenetic Placement of Exact Amplicon Sequences Improves Associations with Clinical Information |
| title_full_unstemmed |
Phylogenetic Placement of Exact Amplicon Sequences Improves Associations with Clinical Information |
| title_sort |
phylogenetic placement of exact amplicon sequences improves associations with clinical information |
| publisher |
American Society for Microbiology |
| publishDate |
2018 |
| url |
https://doaj.org/article/786a8d36f43344f08d69306561672418 |
| work_keys_str_mv |
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1718378340871569408 |