Metagenomic systems biology of the human gut microbiome reveals topological shifts associated with obesity and inflammatory bowel disease

By Sharon I. Greenblum, Peter J. Turnbaugh, Elhanan Borenstein. Proceedings of the National Academy of Sciences of the United States of America, 2011

786 citations recorded by the source corpus.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/0b8b8df2796260df4bc7a3f85de5aa5ed2632628

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Citations in the corpus

A Symbiotic View of Life: We Have Never Been Individuals (2012, background): “2011), and new metagenomic sequencing continues to provide new insights into the relationships between human physiological states and the microbial populations found in humans (Turnbaugh and Gordon 2009; Greenblum et al. 2012).”
Geographic patterns of co-occurrence network topological features for soil microbiota at continental scale in eastern China (2016, background): “OTUs with low betweenness centrality values represent microorganisms that are located away from the core of the network, compared to other OTUs (Greenblum et al., 2012).”
Gut microbiota functions: metabolism of nutrients and other food components (2017, background): “More recently evidence has been accumulating that the microbiota may also be involved in obesity and diabetes [4, 5].”
Generation of genome-scale metabolic reconstructions for 773 members of the human gut microbiota (2016, background): “Cell 148, 1258–1270 (2012). 2. Shafquat, A., Joice, R., Simmons, S.L. & Huttenhower, C. Functional and phylogenetic assembly of microbial communities in the human microbiome. Trends Microbiol. 22, 261–266 (2014). 3. Duncan, S.H. et al. Reduced dietary intake of carbohydrates by obese subjects result”
Correlation detection strategies in microbial data sets vary widely in sensitivity and precision (2016, background): “, 2015) or contribution to habitat niches or disease (Chaffron et al., 2010; Arumugam et al., 2011; Faust and Raes 2012; Faust et al., 2012; Greenblum et al., 2012; Oakley et al., 2013; Goodrich et al., 2014; Buffie et al., 2015).”
Mining electronic health records: towards better research applications and clinical care (2012, positive): “Similar types of analyses can be used to interpret differences in the human microbiomes between individuals, as shown in a pathway analysis of gut metagenomics data in the context of obesity and inflammatory bowel disease 83 .”
Characterization of the Gut Microbiome Using 16S or Shotgun Metagenomics (2016, background): “For example, both IBD and obesity are associated with enrichment of enzymes in the nitrate reductase pathway, the metabolism of choline and pcresol, as well as the phosphotransferase system, required for assimilation of dietary carbohydrates (Greenblum et al., 2012; Levy and Borenstein, 2014).”
Mathematical Modeling of Microbial Community Dynamics: A Methodological Review (2014, background): “[40] in their in silico study of the human gut microbiome.”
Cross-talk between Akkermansia muciniphila and intestinal epithelium controls diet-induced obesity (2013, background): “muciniphila administration may identify the components that contribute to disease or the host physiological response (37).”
The human gut microbiota: Metabolism and perspective in obesity (2018, background): “Obese people tend to have a higher proportion of genes which encode membrane transport functions(8) and are involved in butyrate production,(9) whereas the genes related to cofactor, vitamin, and nucleotide metabolism or transcription are more frequently depleted.(8) Considering this influence of th”