2011
DOI: 10.1073/pnas.1116053109
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Metagenomic systems biology of the human gut microbiome reveals topological shifts associated with obesity and inflammatory bowel disease

Abstract: The human microbiome plays a key role in a wide range of hostrelated processes and has a profound effect on human health. Comparative analyses of the human microbiome have revealed substantial variation in species and gene composition associated with a variety of disease states but may fall short of providing a comprehensive understanding of the impact of this variation on the community and on the host. Here, we introduce a metagenomic systems biology computational framework, integrating metagenomic data with … Show more

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Cited by 729 publications
(579 citation statements)
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“…This notion is supported by the observation that phylogenetically related microbes have a tendency to positively co-occur (Lozupone et al, 2012). Recent studies suggest that the microbial relationships shown in correlation interaction networks can be used to determine drivers in environmental ecology (Ruan et al, 2006;Steele et al, 2011;Zhou et al, 2011;Lima-Mendez et al, 2015) or contribution to habitat niches or disease (Chaffron et al, 2010;Arumugam et al, 2011;Greenblum et al, 2012;Oakley et al, 2013;Goodrich et al, 2014;Buffie et al, 2015). Correlation is also a powerful tool to help researchers with hypothesis generation, such as determining which interactions might be biologically relevant in their system, and should be given further study (for example, through co-culturing or whole-genome sequencing).…”
Section: Introductionsupporting
confidence: 48%
“…This notion is supported by the observation that phylogenetically related microbes have a tendency to positively co-occur (Lozupone et al, 2012). Recent studies suggest that the microbial relationships shown in correlation interaction networks can be used to determine drivers in environmental ecology (Ruan et al, 2006;Steele et al, 2011;Zhou et al, 2011;Lima-Mendez et al, 2015) or contribution to habitat niches or disease (Chaffron et al, 2010;Arumugam et al, 2011;Greenblum et al, 2012;Oakley et al, 2013;Goodrich et al, 2014;Buffie et al, 2015). Correlation is also a powerful tool to help researchers with hypothesis generation, such as determining which interactions might be biologically relevant in their system, and should be given further study (for example, through co-culturing or whole-genome sequencing).…”
Section: Introductionsupporting
confidence: 48%
“…(14) In addition, the high sugar content in energy drinks may reduce the activity, diversity and gene expression of intestinal bacteria resulting in increased risk of obesity and the metabolic syndrome. (22) Acute caffeine intake decreases insulin sensitivity, (23) which could explain the rise in blood glucose levels after energy drink consumption documented in some studies. (24) Beaudoin et al demonstrated that caffeine intake reduces insulin sensitivity in a dose dependent manner, with 5.8% increase in insulin for each mg/kg increase in caffeine.…”
Section: Cardiovascular Effectmentioning
confidence: 99%
“…In order to infer the metabolic repertoire of a gut metagenome data set, researchers usually map sequenced genes or organisms onto metabolic networks derived from the Kyoto Encyclopedia of Genes and Genomes (KEGG) 6 , and functional annotations from KEGG ontologies 7 . However, this approach cannot identify the contribution of each bacterial species to the metabolic repertoire of the whole gut microbiome, nor can it infer the effects of different gut microbial communities on host metabolism.…”
mentioning
confidence: 99%