Multidomain analyses of a longitudinal human microbiome intestinal cleanout perturbation experiment.
Our work focuses on the stability, resilience, and response to perturbation of the bacterial communities in the human gut. Informative flash flood-like disturbances that eliminate most gastrointestinal biomass can be induced using a clinically-relevant iso-osmotic agent. We designed and executed suc...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2017-08-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://doi.org/10.1371/journal.pcbi.1005706 |
| _version_ | 1818582178886320128 |
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| author | Julia Fukuyama Laurie Rumker Kris Sankaran Pratheepa Jeganathan Les Dethlefsen David A Relman Susan P Holmes |
| author_facet | Julia Fukuyama Laurie Rumker Kris Sankaran Pratheepa Jeganathan Les Dethlefsen David A Relman Susan P Holmes |
| author_sort | Julia Fukuyama |
| collection | DOAJ |
| description | Our work focuses on the stability, resilience, and response to perturbation of the bacterial communities in the human gut. Informative flash flood-like disturbances that eliminate most gastrointestinal biomass can be induced using a clinically-relevant iso-osmotic agent. We designed and executed such a disturbance in human volunteers using a dense longitudinal sampling scheme extending before and after induced diarrhea. This experiment has enabled a careful multidomain analysis of a controlled perturbation of the human gut microbiota with a new level of resolution. These new longitudinal multidomain data were analyzed using recently developed statistical methods that demonstrate improvements over current practices. By imposing sparsity constraints we have enhanced the interpretability of the analyses and by employing a new adaptive generalized principal components analysis, incorporated modulated phylogenetic information and enhanced interpretation through scoring of the portions of the tree most influenced by the perturbation. Our analyses leverage the taxa-sample duality in the data to show how the gut microbiota recovers following this perturbation. Through a holistic approach that integrates phylogenetic, metagenomic and abundance information, we elucidate patterns of taxonomic and functional change that characterize the community recovery process across individuals. We provide complete code and illustrations of new sparse statistical methods for high-dimensional, longitudinal multidomain data that provide greater interpretability than existing methods. |
| first_indexed | 2024-12-16T07:45:16Z |
| format | Article |
| id | doaj.art-83ec744e733b4fbaa534536449ceeebb |
| institution | Directory Open Access Journal |
| issn | 1553-734X 1553-7358 |
| language | English |
| last_indexed | 2024-12-16T07:45:16Z |
| publishDate | 2017-08-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj.art-83ec744e733b4fbaa534536449ceeebb2022-12-21T22:38:58ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582017-08-01138e100570610.1371/journal.pcbi.1005706Multidomain analyses of a longitudinal human microbiome intestinal cleanout perturbation experiment.Julia FukuyamaLaurie RumkerKris SankaranPratheepa JeganathanLes DethlefsenDavid A RelmanSusan P HolmesOur work focuses on the stability, resilience, and response to perturbation of the bacterial communities in the human gut. Informative flash flood-like disturbances that eliminate most gastrointestinal biomass can be induced using a clinically-relevant iso-osmotic agent. We designed and executed such a disturbance in human volunteers using a dense longitudinal sampling scheme extending before and after induced diarrhea. This experiment has enabled a careful multidomain analysis of a controlled perturbation of the human gut microbiota with a new level of resolution. These new longitudinal multidomain data were analyzed using recently developed statistical methods that demonstrate improvements over current practices. By imposing sparsity constraints we have enhanced the interpretability of the analyses and by employing a new adaptive generalized principal components analysis, incorporated modulated phylogenetic information and enhanced interpretation through scoring of the portions of the tree most influenced by the perturbation. Our analyses leverage the taxa-sample duality in the data to show how the gut microbiota recovers following this perturbation. Through a holistic approach that integrates phylogenetic, metagenomic and abundance information, we elucidate patterns of taxonomic and functional change that characterize the community recovery process across individuals. We provide complete code and illustrations of new sparse statistical methods for high-dimensional, longitudinal multidomain data that provide greater interpretability than existing methods.https://doi.org/10.1371/journal.pcbi.1005706 |
| spellingShingle | Julia Fukuyama Laurie Rumker Kris Sankaran Pratheepa Jeganathan Les Dethlefsen David A Relman Susan P Holmes Multidomain analyses of a longitudinal human microbiome intestinal cleanout perturbation experiment. PLoS Computational Biology |
| title | Multidomain analyses of a longitudinal human microbiome intestinal cleanout perturbation experiment. |
| title_full | Multidomain analyses of a longitudinal human microbiome intestinal cleanout perturbation experiment. |
| title_fullStr | Multidomain analyses of a longitudinal human microbiome intestinal cleanout perturbation experiment. |
| title_full_unstemmed | Multidomain analyses of a longitudinal human microbiome intestinal cleanout perturbation experiment. |
| title_short | Multidomain analyses of a longitudinal human microbiome intestinal cleanout perturbation experiment. |
| title_sort | multidomain analyses of a longitudinal human microbiome intestinal cleanout perturbation experiment |
| url | https://doi.org/10.1371/journal.pcbi.1005706 |
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