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Balance Trees Reveal Microbial Niche Differentiation
Advances in sequencing technologies have enabled novel insights into microbial niche differentiation, from analyzing environmental samples to understanding human diseases and informing dietary studies. However, identifying the microbial taxa that differentiate these samples can be challenging. These...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Society for Microbiology
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5264246/ https://www.ncbi.nlm.nih.gov/pubmed/28144630 http://dx.doi.org/10.1128/mSystems.00162-16 |
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author | Morton, James T. Sanders, Jon Quinn, Robert A. McDonald, Daniel Gonzalez, Antonio Vázquez-Baeza, Yoshiki Navas-Molina, Jose A. Song, Se Jin Metcalf, Jessica L. Hyde, Embriette R. Lladser, Manuel Dorrestein, Pieter C. Knight, Rob |
author_facet | Morton, James T. Sanders, Jon Quinn, Robert A. McDonald, Daniel Gonzalez, Antonio Vázquez-Baeza, Yoshiki Navas-Molina, Jose A. Song, Se Jin Metcalf, Jessica L. Hyde, Embriette R. Lladser, Manuel Dorrestein, Pieter C. Knight, Rob |
author_sort | Morton, James T. |
collection | PubMed |
description | Advances in sequencing technologies have enabled novel insights into microbial niche differentiation, from analyzing environmental samples to understanding human diseases and informing dietary studies. However, identifying the microbial taxa that differentiate these samples can be challenging. These issues stem from the compositional nature of 16S rRNA gene data (or, more generally, taxon or functional gene data); the changes in the relative abundance of one taxon influence the apparent abundances of the others. Here we acknowledge that inferring properties of individual bacteria is a difficult problem and instead introduce the concept of balances to infer meaningful properties of subcommunities, rather than properties of individual species. We show that balances can yield insights about niche differentiation across multiple microbial environments, including soil environments and lung sputum. These techniques have the potential to reshape how we carry out future ecological analyses aimed at revealing differences in relative taxonomic abundances across different samples. IMPORTANCE By explicitly accounting for the compositional nature of 16S rRNA gene data through the concept of balances, balance trees yield novel biological insights into niche differentiation. The software to perform this analysis is available under an open-source license and can be obtained at https://github.com/biocore/gneiss. Author Video: An author video summary of this article is available. |
format | Online Article Text |
id | pubmed-5264246 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | American Society for Microbiology |
record_format | MEDLINE/PubMed |
spelling | pubmed-52642462017-01-31 Balance Trees Reveal Microbial Niche Differentiation Morton, James T. Sanders, Jon Quinn, Robert A. McDonald, Daniel Gonzalez, Antonio Vázquez-Baeza, Yoshiki Navas-Molina, Jose A. Song, Se Jin Metcalf, Jessica L. Hyde, Embriette R. Lladser, Manuel Dorrestein, Pieter C. Knight, Rob mSystems Research Article Advances in sequencing technologies have enabled novel insights into microbial niche differentiation, from analyzing environmental samples to understanding human diseases and informing dietary studies. However, identifying the microbial taxa that differentiate these samples can be challenging. These issues stem from the compositional nature of 16S rRNA gene data (or, more generally, taxon or functional gene data); the changes in the relative abundance of one taxon influence the apparent abundances of the others. Here we acknowledge that inferring properties of individual bacteria is a difficult problem and instead introduce the concept of balances to infer meaningful properties of subcommunities, rather than properties of individual species. We show that balances can yield insights about niche differentiation across multiple microbial environments, including soil environments and lung sputum. These techniques have the potential to reshape how we carry out future ecological analyses aimed at revealing differences in relative taxonomic abundances across different samples. IMPORTANCE By explicitly accounting for the compositional nature of 16S rRNA gene data through the concept of balances, balance trees yield novel biological insights into niche differentiation. The software to perform this analysis is available under an open-source license and can be obtained at https://github.com/biocore/gneiss. Author Video: An author video summary of this article is available. American Society for Microbiology 2017-01-17 /pmc/articles/PMC5264246/ /pubmed/28144630 http://dx.doi.org/10.1128/mSystems.00162-16 Text en Copyright © 2017 Morton et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license (http://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Research Article Morton, James T. Sanders, Jon Quinn, Robert A. McDonald, Daniel Gonzalez, Antonio Vázquez-Baeza, Yoshiki Navas-Molina, Jose A. Song, Se Jin Metcalf, Jessica L. Hyde, Embriette R. Lladser, Manuel Dorrestein, Pieter C. Knight, Rob Balance Trees Reveal Microbial Niche Differentiation |
title | Balance Trees Reveal Microbial Niche Differentiation |
title_full | Balance Trees Reveal Microbial Niche Differentiation |
title_fullStr | Balance Trees Reveal Microbial Niche Differentiation |
title_full_unstemmed | Balance Trees Reveal Microbial Niche Differentiation |
title_short | Balance Trees Reveal Microbial Niche Differentiation |
title_sort | balance trees reveal microbial niche differentiation |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5264246/ https://www.ncbi.nlm.nih.gov/pubmed/28144630 http://dx.doi.org/10.1128/mSystems.00162-16 |
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