Two dynamic regimes in the human gut microbiome
The gut microbiome is a dynamic system that changes with host development, health, behavior, diet, and microbe-microbe interactions. Prior work on gut microbial time series has largely focused on autoregressive models (e.g. Lotka-Volterra). However, we show that most of the variance in microbial tim...
| Main Authors: | , , , |
|---|---|
| 其他作者: | |
| 格式: | 文件 |
| 语言: | en_US |
| 出版: |
Public Library of Science
2017
|
| 在线阅读: | http://hdl.handle.net/1721.1/109970 https://orcid.org/0000-0002-8033-8380 https://orcid.org/0000-0002-8202-5222 https://orcid.org/0000-0001-8294-9364 |
| _version_ | 1826191708872769536 |
|---|---|
| author | Gibbons, Sean Michael Kearney, Sean M Smillie, Chris S Alm, Eric J |
| author2 | Broad Institute of MIT and Harvard |
| author_facet | Broad Institute of MIT and Harvard Gibbons, Sean Michael Kearney, Sean M Smillie, Chris S Alm, Eric J |
| author_sort | Gibbons, Sean Michael |
| collection | MIT |
| description | The gut microbiome is a dynamic system that changes with host development, health, behavior, diet, and microbe-microbe interactions. Prior work on gut microbial time series has largely focused on autoregressive models (e.g. Lotka-Volterra). However, we show that most of the variance in microbial time series is non-autoregressive. In addition, we show how community state-clustering is flawed when it comes to characterizing within-host dynamics and that more continuous methods are required. Most organisms exhibited stable, mean-reverting behavior suggestive of fixed carrying capacities and abundant taxa were largely shared across individuals. This mean-reverting behavior allowed us to apply sparse vector autoregression (sVAR)—a multivariate method developed for econometrics—to model the autoregressive component of gut community dynamics. We find a strong phylogenetic signal in the non-autoregressive co-variance from our sVAR model residuals, which suggests niche filtering. We show how changes in diet are also non-autoregressive and that Operational Taxonomic Units strongly correlated with dietary variables have much less of an autoregressive component to their variance, which suggests that diet is a major driver of microbial dynamics. Autoregressive variance appears to be driven by multi-day recovery from frequent facultative anaerobe blooms, which may be driven by fluctuations in luminal redox. Overall, we identify two dynamic regimes within the human gut microbiota: one likely driven by external environmental fluctuations, and the other by internal processes. |
| first_indexed | 2024-09-23T09:00:08Z |
| format | Article |
| id | mit-1721.1/109970 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T09:00:08Z |
| publishDate | 2017 |
| publisher | Public Library of Science |
| record_format | dspace |
| spelling | mit-1721.1/1099702022-09-30T12:45:44Z Two dynamic regimes in the human gut microbiome Gibbons, Sean Michael Kearney, Sean M Smillie, Chris S Alm, Eric J Broad Institute of MIT and Harvard Massachusetts Institute of Technology. Department of Biological Engineering Gibbons, Sean Michael Kearney, Sean M Smillie, Chris S Alm, Eric J The gut microbiome is a dynamic system that changes with host development, health, behavior, diet, and microbe-microbe interactions. Prior work on gut microbial time series has largely focused on autoregressive models (e.g. Lotka-Volterra). However, we show that most of the variance in microbial time series is non-autoregressive. In addition, we show how community state-clustering is flawed when it comes to characterizing within-host dynamics and that more continuous methods are required. Most organisms exhibited stable, mean-reverting behavior suggestive of fixed carrying capacities and abundant taxa were largely shared across individuals. This mean-reverting behavior allowed us to apply sparse vector autoregression (sVAR)—a multivariate method developed for econometrics—to model the autoregressive component of gut community dynamics. We find a strong phylogenetic signal in the non-autoregressive co-variance from our sVAR model residuals, which suggests niche filtering. We show how changes in diet are also non-autoregressive and that Operational Taxonomic Units strongly correlated with dietary variables have much less of an autoregressive component to their variance, which suggests that diet is a major driver of microbial dynamics. Autoregressive variance appears to be driven by multi-day recovery from frequent facultative anaerobe blooms, which may be driven by fluctuations in luminal redox. Overall, we identify two dynamic regimes within the human gut microbiota: one likely driven by external environmental fluctuations, and the other by internal processes. 2017-06-16T18:31:14Z 2017-06-16T18:31:14Z 2017-02 2016-08 Article http://purl.org/eprint/type/JournalArticle 1553-7358 1553-734X http://hdl.handle.net/1721.1/109970 Gibbons, Sean M.; Kearney, Sean M.; Smillie, Chris S. and Alm, Eric J. “Two Dynamic Regimes in the Human Gut Microbiome.” Edited by Elhanan Borenstein. PLOS Computational Biology 13, no. 2 (February 2017): e1005364 © 2017 Gibbons et al https://orcid.org/0000-0002-8033-8380 https://orcid.org/0000-0002-8202-5222 https://orcid.org/0000-0001-8294-9364 en_US http://dx.doi.org/10.1371/journal.pcbi.1005364 PLoS Computational Biology Creative Commons Attribution 4.0 International License http://creativecommons.org/licenses/by/4.0/ application/pdf Public Library of Science PLoS |
| spellingShingle | Gibbons, Sean Michael Kearney, Sean M Smillie, Chris S Alm, Eric J Two dynamic regimes in the human gut microbiome |
| title | Two dynamic regimes in the human gut microbiome |
| title_full | Two dynamic regimes in the human gut microbiome |
| title_fullStr | Two dynamic regimes in the human gut microbiome |
| title_full_unstemmed | Two dynamic regimes in the human gut microbiome |
| title_short | Two dynamic regimes in the human gut microbiome |
| title_sort | two dynamic regimes in the human gut microbiome |
| url | http://hdl.handle.net/1721.1/109970 https://orcid.org/0000-0002-8033-8380 https://orcid.org/0000-0002-8202-5222 https://orcid.org/0000-0001-8294-9364 |
| work_keys_str_mv | AT gibbonsseanmichael twodynamicregimesinthehumangutmicrobiome AT kearneyseanm twodynamicregimesinthehumangutmicrobiome AT smilliechriss twodynamicregimesinthehumangutmicrobiome AT almericj twodynamicregimesinthehumangutmicrobiome |