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Semen Microbiome Biogeography: An Analysis Based on a Chinese Population Study
Investigating inter-subject heterogeneity (or spatial distribution) of human semen microbiome diversity is of important significance. Theoretically, the spatial distribution of biodiversity constitutes the core of microbiome biogeography. Practically, the inter-subject heterogeneity is crucial for u...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371047/ https://www.ncbi.nlm.nih.gov/pubmed/30804923 http://dx.doi.org/10.3389/fmicb.2018.03333 |
Sumario: | Investigating inter-subject heterogeneity (or spatial distribution) of human semen microbiome diversity is of important significance. Theoretically, the spatial distribution of biodiversity constitutes the core of microbiome biogeography. Practically, the inter-subject heterogeneity is crucial for understanding the normal (healthy) flora of semen microbiotas as well as their possible changes associated with abnormal fertility. In this article, we analyze the scaling (changes) of semen microbiome diversity across individuals with DAR (diversity-area relationship) analysis, a recent extension to classic SAR (species-area relationship) law in biogeography and ecology. Specifically, the unit of “area” is individual subject, and the microbial diversity in seminal fluid of an individual (area) is assessed via metagenomic DNA sequencing technique and measured in the Hill numbers. The DAR models were then fitted to the accrued diversity across different number of individuals (area size). We further tested the difference in DAR parameters among the healthy, subnormal, and abnormal microbiome samples in terms of their fertility status based on a cross-sectional study of a Chinese cohort. Given that no statistically significant differences in the DAR parameters were detected among the three groups, we built unified DAR models for semen microbiome by combining the healthy, subnormal, and abnormal groups. The model parameters were used to (i) estimate the microbiome diversity scaling in a population (cohort), and construct the so-termed DAR profile; (ii) predict/construct the maximal accrual diversity (MAD) profile in a population; (iii) estimate the pair-wise diversity overlap (PDO) between two individuals and construct the PDO profile; (iv) assess the ratio of individual diversity to population (RIP) accrual diversity. The last item (RIP) is a new concept we propose in this study, which is essentially a ratio of local diversity to regional or global diversity (LRD/LGD), applicable to general biodiversity investigation beyond human microbiome. |
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