Intermittent Hypoxia and Hypercapnia Reproducibly Change the Gut Microbiome and Metabolome across Rodent Model Systems

• Published in: mSystems Vol. 4; no. 2
• Main Authors: Tripathi, Anupriya, Xu, Zhenjiang Zech, Xue, Jin, Poulsen, Orit, Gonzalez, Antonio, Humphrey, Gregory, Meehan, Michael J., Melnik, Alexey V., Ackermann, Gail, Zhou, Dan, Malhotra, Atul, Haddad, Gabriel G., Dorrestein, Pieter C., Knight, Rob
• Format: Journal Article
• Language: English
• Published: United States American Society for Microbiology 01.03.2019
• Subjects: Accuracy; Animal models; Animals; Apnea; Apolipoprotein E; Arteriosclerosis; Artificial intelligence; Atherosclerosis; Bile acids; cardiovascular; Cardiovascular diseases; Datasets; Digestive system; Ecosystems; Fatty acids; Genotype & phenotype; Gut microbiota; Host-Microbe Biology; Hypercapnia; Hypoxia; Inflammatory bowel disease; Intestinal microflora; Learning algorithms; Liquid chromatography; machine learning; Mass spectrometry; Mass spectroscopy; metabolism; Metabolites; microbiome; Microbiomes; Microbiota; Pulmonary arteries; Rodents; rRNA 16S; Scientific imaging; Sleep; sleep apnea; Sleep disorders; United States > US; California; metabolism; cardiovascular; machine learning; microbiome; sleep apnea

Reproducibility of microbiome research is a major topic of contemporary interest. Although it is often possible to distinguish individuals with specific diseases within a study, the differences are often inconsistent across cohorts, often due to systematic variation in analytical conditions. Here we...