Identifying keystone species in the human gut microbiome from metagenomic timeseries using sparse linear regression.
Identifying keystone species in the human gut microbiome from metagenomic timeseries using sparse linear regression.
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DOI：
10.1371/journal.pone.0102451
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发表时间：
2014
期刊：
影响因子：
3.7
通讯作者：
Mehta P
中科院分区：
文献类型：
--
作者：
Fisher CK;Mehta P
Human associated microbial communities exert tremendous influence over human health and disease. With modern metagenomic sequencing methods it is now possible to follow the relative abundance of microbes in a community over time. These microbial communities exhibit rich ecological dynamics and an important goal of microbial ecology is to infer the ecological interactions between species directly from sequence data. Any algorithm for inferring ecological interactions must overcome three major obstacles: 1) a correlation between the abundances of two species does not imply that those species are interacting, 2) the sum constraint on the relative abundances obtained from metagenomic studies makes it difficult to infer the parameters in timeseries models, and 3) errors due to experimental uncertainty, or mis-assignment of sequencing reads into operational taxonomic units, bias inferences of species interactions due to a statistical problem called “errors-in-variables”. Here we introduce an approach, Learning Interactions from MIcrobial Time Series (LIMITS), that overcomes these obstacles. LIMITS uses sparse linear regression with boostrap aggregation to infer a discrete-time Lotka-Volterra model for microbial dynamics. We tested LIMITS on synthetic data and showed that it could reliably infer the topology of the inter-species ecological interactions. We then used LIMITS to characterize the species interactions in the gut microbiomes of two individuals and found that the interaction networks varied significantly between individuals. Furthermore, we found that the interaction networks of the two individuals are dominated by distinct “keystone species”, Bacteroides fragilis and Bacteroided stercosis, that have a disproportionate influence on the structure of the gut microbiome even though they are only found in moderate abundance. Based on our results, we hypothesize that the abundances of certain keystone species may be responsible for individuality in the human gut microbiome.
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Keystone-Pathogen假设。
DOI：
10.1038/nrmicro2873
发表时间：
2012-10
期刊：
Nature reviews. Microbiology
影响因子：
--
作者：
通讯作者：
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影响因子：
17.1
作者：
Turnbaugh PJ;Ridaura VK;Faith JJ;Rey FE;Knight R;Gordon JI
通讯作者：
Gordon JI
影响因子：
4.3
作者：
Wooley JC;Godzik A;Friedberg I
通讯作者：
Friedberg I
DOI：
10.1126/science.1241214
发表时间：
2013-09-06
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Ridaura VK;Faith JJ;Rey FE;Cheng J;Duncan AE;Kau AL;Griffin NW;Lombard V;Henrissat B;Bain JR;Muehlbauer MJ;Ilkayeva O;Semenkovich CF;Funai K;Hayashi DK;Lyle BJ;Martini MC;Ursell LK;Clemente JC;Van Treuren W;Walters WA;Knight R;Newgard CB;Heath AC;Gordon JI
通讯作者：
Gordon JI
影响因子：
64.8
作者：
Arumugam, Manimozhiyan;Raes, Jeroen;Pelletier, Eric;Le Paslier, Denis;Yamada, Takuji;Mende, Daniel R.;Fernandes, Gabriel R.;Tap, Julien;Bruls, Thomas;Batto, Jean-Michel;Bertalan, Marcelo;Borruel, Natalia;Casellas, Francesc;Fernandez, Leyden;Gautier, Laurent;Hansen, Torben;Hattori, Masahira;Hayashi, Tetsuya;Kleerebezem, Michiel;Kurokawa, Ken;Leclerc, Marion;Levenez, Florence;Manichanh, Chaysavanh;Nielsen, H. Bjorn;Nielsen, Trine;Pons, Nicolas;Poulain, Julie;Qin, Junjie;Sicheritz-Ponten, Thomas;Tims, Sebastian;Torrents, David;Ugarte, Edgardo;Zoetendal, Erwin G.;Wang, Jun;Guarner, Francisco;Pedersen, Oluf;de Vos, Willem M.;Brunak, Soren;Dore, Joel;Weissenbach, Jean;Ehrlich, S. Dusko;Bork, Peer
通讯作者：
Bork, Peer