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Diversity-scaling analysis of human breast milk microbiomes from population perspective

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机构: [1]College of Mathematics, Honghe University, Mengzi, China. [2]Computational Biology and Medical Ecology Lab, State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China. [3]Kunming College of Life Sciences, University of Chinese Academy of Sciences, Kunming, China. [4]Department of Endocrinology, Yan'an Hospital of Kunming City, Kunming, China. [5]Physiatrics Medicine, Yan'an Hospital of Kunming City, Kunming, China. [6]The Yunnan Red-Cross Hospital, Affiliated Hospital of Yunnan University, Kunming, China. [7]Department of Neurology, The First People's Hospital of Yunnan Province, Kunming, China. [8]Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China. [9]Department of Biology, Taiyuan Normal University, Jinzhong, China.
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关键词: human breast milk microbiome (BMM) diversity-area relationship (DAR) diversity heterogeneity population potential diversity ratio of individual-to-population accrual diversity (RIP)

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Quantitative measuring the population-level diversity-scaling of human microbiomes is different from conventional approach to traditional individual-level diversity analysis, and it is of obvious significance. For example, it is well known that individuals are of significant heterogeneity with their microbiome diversities, and the population-level analysis can effectively capture such kind of individual differences. Here we reanalyze a dozen datasets of 2,115 human breast milk microbiome (BMM) samples with diversity-area relationship (DAR) to tackle the previous questions. Our focus on BMM is aimed to offer insights for supplementing the gut microbiome research from nutritional perspective. DAR is an extension to classic species-area relationship, which was discovered in the 19th century and established as one of a handful fundamental laws in community ecology. Our DAR modeling revealed the following numbers, all approximately: (i) The population-level potential diversity of BMM is 1,108 in terms of species richness (number of total species), and 67 in terms of typical species. (ii) On average, an individual carry 17% of population-level diversity in terms of species richness, and 61% in terms of typical species. (iii) The similarity (overlap) between individuals according to pair-wise diversity overlap (PDO) should be approximately 76% in terms of total species, and 92% in terms of typical species, which symbolizes the inter-individual heterogeneity. (iv) The average individual (alpha-) diversity of BMM is approximately 188 (total-species) and 37 (typical-species). (v) To deal with the potential difference among 12 BMM datasets, we conducted DAR modeling separately for each dataset, and then performed permutation tests for DAR parameters. It was found that the DAR scaling parameter that measures inter-individual heterogeneity in diversity is invariant (constant), but the population potential diversity is different among 30% of the pair-wise comparison between 12 BMM datasets. These results offer comprehensive biodiversity analyses of the BMM from host individual, inter-individual, and population level perspectives.Copyright © 2022 Chen, Yi, Li, Qiao, Peng, Zhang, Li, Zheng, Ning and Li.

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出版当年[2022]版:
大类 | 2 区 生物学
小类 | 2 区 微生物学
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大类 | 2 区 生物学
小类 | 3 区 微生物学
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Q1 MICROBIOLOGY
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Q2 MICROBIOLOGY

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第一作者机构: [1]College of Mathematics, Honghe University, Mengzi, China. [2]Computational Biology and Medical Ecology Lab, State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China. [3]Kunming College of Life Sciences, University of Chinese Academy of Sciences, Kunming, China.
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通讯机构: [2]Computational Biology and Medical Ecology Lab, State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China. [9]Department of Biology, Taiyuan Normal University, Jinzhong, China.
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