TY - JOUR
T1 - Moving pictures of the human microbiome
AU - Caporaso, J. Gregory
AU - Lauber, Christian L.
AU - Costello, Elizabeth K.
AU - Berg-Lyons, Donna
AU - Gonzalez, Antonio
AU - Stombaugh, Jesse
AU - Knights, Dan
AU - Gajer, Pawel
AU - Ravel, Jacques
AU - Fierer, Noah
AU - Gordon, Jeffrey I.
AU - Knight, Rob
N1 - Funding Information:
We wish to acknowledge funding from NIH (HG004872, DK078669, AI070921 and AI083264), ARRA supplement (HG004872-02S1); Crohn’s and Colitis Foundation of America; the Bill and Melinda Gates Foundation; Amazon Web Services (AWS) in Education Researchers Grant; and the Howard Hughes Medical Institute. We additionally wish to acknowledge Nigel Cook for assisting with deployment of QIIME on AWS, and Reece Gesumaria for performing DNA extraction.
PY - 2011/5/30
Y1 - 2011/5/30
N2 - Background: Understanding the normal temporal variation in the human microbiome is critical to developing treatments for putative microbiome-related afflictions such as obesity, Crohn's disease, inflammatory bowel disease and malnutrition. Sequencing and computational technologies, however, have been a limiting factor in performing dense time series analysis of the human microbiome. Here, we present the largest human microbiota time series analysis to date, covering two individuals at four body sites over 396 timepoints.Results: We find that despite stable differences between body sites and individuals, there is pronounced variability in an individual's microbiota across months, weeks and even days. Additionally, only a small fraction of the total taxa found within a single body site appear to be present across all time points, suggesting that no core temporal microbiome exists at high abundance (although some microbes may be present but drop below the detection threshold). Many more taxa appear to be persistent but non-permanent community members.Conclusions: DNA sequencing and computational advances described here provide the ability to go beyond infrequent snapshots of our human-associated microbial ecology to high-resolution assessments of temporal variations over protracted periods, within and between body habitats and individuals. This capacity will allow us to define normal variation and pathologic states, and assess responses to therapeutic interventions.
AB - Background: Understanding the normal temporal variation in the human microbiome is critical to developing treatments for putative microbiome-related afflictions such as obesity, Crohn's disease, inflammatory bowel disease and malnutrition. Sequencing and computational technologies, however, have been a limiting factor in performing dense time series analysis of the human microbiome. Here, we present the largest human microbiota time series analysis to date, covering two individuals at four body sites over 396 timepoints.Results: We find that despite stable differences between body sites and individuals, there is pronounced variability in an individual's microbiota across months, weeks and even days. Additionally, only a small fraction of the total taxa found within a single body site appear to be present across all time points, suggesting that no core temporal microbiome exists at high abundance (although some microbes may be present but drop below the detection threshold). Many more taxa appear to be persistent but non-permanent community members.Conclusions: DNA sequencing and computational advances described here provide the ability to go beyond infrequent snapshots of our human-associated microbial ecology to high-resolution assessments of temporal variations over protracted periods, within and between body habitats and individuals. This capacity will allow us to define normal variation and pathologic states, and assess responses to therapeutic interventions.
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U2 - 10.1186/gb-2011-12-5-r50
DO - 10.1186/gb-2011-12-5-r50
M3 - Article
C2 - 21624126
AN - SCOPUS:79957574938
SN - 1474-7596
VL - 12
JO - Genome biology
JF - Genome biology
IS - 5
M1 - R50
ER -