Ontology type: schema:ScholarlyArticle Open Access: True
2014-12
AUTHORSGilberto E Flores, J Gregory Caporaso, Jessica B Henley, Jai Ram Rideout, Daniel Domogala, John Chase, Jonathan W Leff, Yoshiki Vázquez-Baeza, Antonio Gonzalez, Rob Knight, Robert R Dunn, Noah Fierer
ABSTRACTBACKGROUND: It is now apparent that the complex microbial communities found on and in the human body vary across individuals. What has largely been missing from previous studies is an understanding of how these communities vary over time within individuals. To the extent to which it has been considered, it is often assumed that temporal variability is negligible for healthy adults. Here we address this gap in understanding by profiling the forehead, gut (fecal), palm, and tongue microbial communities in 85 adults, weekly over 3 months. RESULTS: We found that skin (forehead and palm) varied most in the number of taxa present, whereas gut and tongue communities varied more in the relative abundances of taxa. Within each body habitat, there was a wide range of temporal variability across the study population, with some individuals harboring more variable communities than others. The best predictor of these differences in variability across individuals was microbial diversity; individuals with more diverse gut or tongue communities were more stable in composition than individuals with less diverse communities. CONCLUSIONS: Longitudinal sampling of a relatively large number of individuals allowed us to observe high levels of temporal variability in both diversity and community structure in all body habitats studied. These findings suggest that temporal dynamics may need to be considered when attempting to link changes in microbiome structure to changes in health status. Furthermore, our findings show that, not only is the composition of an individual's microbiome highly personalized, but their degree of temporal variability is also a personalized feature. More... »
PAGES531
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DOIhttp://dx.doi.org/10.1186/s13059-014-0531-y
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PUBMEDhttps://www.ncbi.nlm.nih.gov/pubmed/25517225
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"pub.1034675947"
]
}
],
"sameAs": [
"https://doi.org/10.1186/s13059-014-0531-y",
"https://app.dimensions.ai/details/publication/pub.1034675947"
],
"sdDataset": "articles",
"sdDatePublished": "2019-04-11T13:06",
"sdLicense": "https://scigraph.springernature.com/explorer/license/",
"sdPublisher": {
"name": "Springer Nature - SN SciGraph project",
"type": "Organization"
},
"sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000367_0000000367/records_88217_00000000.jsonl",
"type": "ScholarlyArticle",
"url": "http://link.springer.com/10.1186%2Fs13059-014-0531-y"
}
]Download the RDF metadata as: json-ld nt turtle xml License info
JSON-LD is a popular format for linked data which is fully compatible with JSON.
curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/s13059-014-0531-y'
N-Triples is a line-based linked data format ideal for batch operations.
curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s13059-014-0531-y'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s13059-014-0531-y'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s13059-014-0531-y'
This table displays all metadata directly associated to this object as RDF triples.
359 TRIPLES
21 PREDICATES
82 URIs
38 LITERALS
26 BLANK NODES