Dataset Information

Biogeography of the ecosystems of the healthy human body.

ABSTRACT: Characterizing the biogeography of the microbiome of healthy humans is essential for understanding microbial associated diseases. Previous studies mainly focused on a single body habitat from a limited set of subjects. Here, we analyzed one of the largest microbiome datasets to date and generated a biogeographical map that annotates the biodiversity, spatial relationships, and temporal stability of 22 habitats from 279 healthy humans.We identified 929 genera from more than 24 million 16S rRNA gene sequences of 22 habitats, and we provide a baseline of inter-subject variation for healthy adults. The oral habitat has the most stable microbiota with the highest alpha diversity, while the skin and vaginal microbiota are less stable and show lower alpha diversity. The level of biodiversity in one habitat is independent of the biodiversity of other habitats in the same individual. The abundances of a given genus at a body site in which it dominates do not correlate with the abundances at body sites where it is not dominant. Additionally, we observed the human microbiota exhibit both cosmopolitan and endemic features. Finally, comparing datasets of different projects revealed a project-based clustering pattern, emphasizing the significance of standardization of metagenomic studies.The data presented here extend the definition of the human microbiome by providing a more complete and accurate picture of human microbiome biogeography, addressing questions best answered by a large dataset of subjects and body sites that are deeply sampled by sequencing.

SUBMITTER: Zhou Y

PROVIDER: S-EPMC4054670 | biostudies-literature | 2013 Jan

REPOSITORIES: biostudies-literature

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Biogeography of the ecosystems of the healthy human body.

Zhou Yanjiao Y Gao Hongyu H Mihindukulasuriya Kathie A KA La Rosa Patricio S PS Wylie Kristine M KM Vishnivetskaya Tatiana T Podar Mircea M Warner Barb B Tarr Phillip I PI Nelson David E DE Fortenberry J Dennis JD Holland Martin J MJ Burr Sarah E SE Shannon William D WD Sodergren Erica E Weinstock George M GM

Genome biology 20130114 1

<h4>Background</h4>Characterizing the biogeography of the microbiome of healthy humans is essential for understanding microbial associated diseases. Previous studies mainly focused on a single body habitat from a limited set of subjects. Here, we analyzed one of the largest microbiome datasets to date and generated a biogeographical map that annotates the biodiversity, spatial relationships, and temporal stability of 22 habitats from 279 healthy humans.<h4>Results</h4>We identified 929 genera fr ...[more]

PMID: 23316946

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Project description:A human body hosts a relatively independent microbiome including five major regional biomes (i.e., airway, oral, gut, skin, and urogenital). Each of them may possess different regional characteristics with important implications to our health and diseases (i.e., so-termed microbiome associated diseases). Nevertheless, these regional microbiomes are connected with each other through diffusions and migrations. Here, we investigate the within-body (intra-individual) distribution feature of microbiome diversity via diversity area relationship (DAR) modeling, which, to the best of our knowledge, has not been systematically studied previously. We utilized the Hill numbers for measuring alpha and beta-diversities and built 1,200 within-body DAR models with to date the most comprehensive human microbiome datasets of 18 sites from the human microbiome project (HMP) cohort. We established the intra-DAR profile (z-q pattern: the diversity scaling parameter z of the power law (PL) at diversity order q = 0-3), intra-PDO (pair-wise diversity overlap) profile (g-q), and intra-MAD (maximal accrual diversity) profile (D max-q) for the within-body biogeography of the human microbiome. These profiles constitute the "maps" of the within-body biogeography, and offer important insights on the within-body distribution of the human microbiome. Furthermore, we investigated the heterogeneity among individuals in their biogeography parameters and found that there is not an "average Joe" that can represent majority of individuals in a cohort or population. For example, we found that most individuals in the HMP cohort have relatively lower maximal accrual diversity (MAD) or in the "long tail" of the so-termed power law distribution. In the meantime, there are a small number of individuals in the cohort who possess disproportionally higher MAD values. These findings may have important implications for personalized medicine of the human microbiome associated diseases in practice, besides their theoretical significance in microbiome research such as establishing the baseline for the conservation of human microbiome.

Project description:RationaleThe lung microbiome is spatially heterogeneous in advanced airway diseases, but whether it varies spatially in health is unknown. We postulated that the primary determinant of lung microbiome constitution in health is the balance of immigration and elimination of communities from the upper respiratory tract (URT; "adapted island model of lung biogeography"), rather than differences in regional bacterial growth conditions.ObjectivesTo determine if the lung microbiome is spatially varied in healthy adults.MethodsBronchoscopy was performed on 15 healthy subjects. Specimens were sequentially collected in the lingula and right middle lobe (by bronchoalveolar lavage [BAL]), then in the right upper lobe, left upper lobe, and supraglottic space (by protected-specimen brush). Bacterial 16S ribosmal RNA-encoding genes were sequenced using MiSeq (Illumina, San Diego, CA).Measurements and main resultsThere were no significant differences between specimens collected by BAL and protected-specimen brush. Spatially separated intrapulmonary sites, when compared with each other, did not contain consistently distinct microbiota. On average, intrasubject variation was significantly less than intersubject variation (P = 0.00003). By multiple ecologic parameters (community richness, community composition, intersubject variability, and similarity to source community), right upper lobe microbiota more closely resembled those of the URT than did microbiota from more distal sites. As predicted by the adapted island model, community richness decreased with increasing distance from the source community of the URT (P < 0.05).ConclusionsIn healthy lungs, spatial variation in microbiota within an individual is significantly less than variation across individuals. The lung microbiome in health is more influenced by microbial immigration and elimination (the adapted island model) than by the effects of local growth conditions on bacterial reproduction rates, which are more determinant in advanced lung diseases. BAL of a single lung segment is an acceptable method of sampling the healthy lung microbiome. Clinical trial registered with www.clinicaltrials.gov (NCT02392182).

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Biogeography of the ecosystems of the healthy human body.

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Biogeography of the ecosystems of the healthy human body.

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