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10.1080/19490976.2015.1128625 http://scihub22266oqcxt.onion/10.1080/19490976.2015.1128625 C4856449!4856449!26979110     free     free     free Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\26979110.jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       Gut+Microbes 2016 ; 7 (2): 126-35 Nephropedia Template TP {{tp|p=26979110|t=2016. Investigating a holobiont: Microbiota perturbations and transkingdom networks |pdf=|usr=}}{{26979110}} gab.com Text Investigating a holobiont: Microbiota perturbations and transkingdom networks JO: Gut Microbes http://www.kidney.de/pget.php?&tw=1&pmid=26979110 #FOAvip The scientific community has recently come to appreciate that, rather than existing as independent organisms, multicellular hosts and their microbiota comprise a complex evolving superorganism or metaorganism, termed a holobiont. This point of view leads to a re-evaluation of our understanding of different physiological processes and diseases. In this paper we focus on experimental and computational approaches which, when combined in one study, allowed us to dissect mechanisms (traditionally named host-microbiota interactions) regulating holobiont physiology. Specifically, we discuss several approaches for microbiota perturbation, such as use of antibiotics and germ-free animals, including advantages and potential caveats of their usage. We briefly review computational approaches to characterize the microbiota and, more importantly, methods to infer specific components of microbiota (such as microbes or their genes) affecting host functions. One such approach called transkingdom network analysis has been recently developed and applied in our study.1 Finally, we also discuss common methods used to validate the computational predictions of host-microbiota interactions using in vitro and in vivo experimental systems. Twit Text FOAVip Investigating a holobiont: Microbiota perturbations and transkingdom networks ????Gut Microbes http://www.kidney.de/pget.php?&tw=1&pmid=26979110 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=26979110 #FOAvip English Wikipedia <ref>{{Cite pmid|26979110}}</ref> Investigating a holobiont: Microbiota perturbations and transkingdom networks #MMPMID26979110 Greer R; Dong X; Morgun A; Shulzhenko N Gut Microbes 2016[]; 7 (2): 126-35 PMID26979110show ga The scientific community has recently come to appreciate that, rather than existing as independent organisms, multicellular hosts and their microbiota comprise a complex evolving superorganism or metaorganism, termed a holobiont. This point of view leads to a re-evaluation of our understanding of different physiological processes and diseases. In this paper we focus on experimental and computational approaches which, when combined in one study, allowed us to dissect mechanisms (traditionally named host-microbiota interactions) regulating holobiont physiology. Specifically, we discuss several approaches for microbiota perturbation, such as use of antibiotics and germ-free animals, including advantages and potential caveats of their usage. We briefly review computational approaches to characterize the microbiota and, more importantly, methods to infer specific components of microbiota (such as microbes or their genes) affecting host functions. One such approach called transkingdom network analysis has been recently developed and applied in our study.1 Finally, we also discuss common methods used to validate the computational predictions of host-microbiota interactions using in vitro and in vivo experimental systems. äInvestigating a holobiont: Microbiota perturbations and transkingdom n(epmc).pdf DeepDyve Pubget Overpricing