Assessing and Interpreting the Within-Body Biogeography of Human Microbiome Diversity

• Main Authors: Zhanshan Ma, Lianwei Li, Wendy Li
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2018-08-01
• Series: Frontiers in Microbiology
• Subjects: diversity area relationship (DAR); within-body microbiome biogeography; power law; scale invariance; self-similarity; diversity area relationship (DAR) profile
• Online Access: https://www.frontiersin.org/article/10.3389/fmicb.2018.01619/full

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 (Dmax-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.