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10.1371/journal.pcbi.1005364 http://scihub22266oqcxt.onion/10.1371/journal.pcbi.1005364 C5340412!5340412 !28222117     free     free     free Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\28222117 .jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       PLoS+Comput+Biol 2017 ; 13 (2 ): e1005364 Nephropedia Template TP {{tp|p=28222117 |t=2017. Two dynamic regimes in the human gut microbiome |pdf=|usr=}}{{28222117 }} gab.com Text Two dynamic regimes in the human gut microbiome JO: PLoS Comput Biol http://www.kidney.de/pget.php?&tw=1&pmid=28222117 #FOAvip 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. Twit Text FOAVip Two dynamic regimes in the human gut microbiome ????PLoS Comput Biol http://www.kidney.de/pget.php?&tw=1&pmid=28222117 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28222117 #FOAvip English Wikipedia <ref>{{Cite pmid|28222117 }}</ref> Two dynamic regimes in the human gut microbiome #MMPMID28222117 Gibbons SM ; Kearney SM ; Smillie CS ; Alm EJ PLoS Comput Biol 2017[Feb]; 13 (2 ): e1005364 PMID28222117 show ga 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. |Animals [MESH] |Bacteria/classification/*genetics [MESH] |Computer Simulation [MESH] |Digestion/*physiology [MESH] |Eating/*genetics [MESH] |Gastrointestinal Microbiome/*genetics/*physiology [MESH] |Gastrointestinal Tract/*microbiology/physiology [MESH] |Humans [MESH] |Microbial Interactions/genetics [MESH] |Models, Biological [MESH] |Models, Statistical [MESH]Two dynamic regimes in the human gut microbiome (epmc).pdf DeepDyve Pubget Overpricing