Evidence map›Paper›PMID 36225365›Full record

ArticleFrontiers in microbiology2022

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

Hongju Chen, Bin Yi, Yuting Qiao, Kunbao Peng, Jianmei Zhang, Jinsong Li, Kun-Wen Zheng, Ping Ning, Wendy Li

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Article in Frontiers in microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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0cells of the map it votes in
3citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Hongju ChenCollege of Mathematics, Honghe University, Mengzi, China.
Bin YiCollege of Mathematics, Honghe University, Mengzi, China.
Yuting QiaoComputational Biology and Medical Ecology Lab, State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.
Kunbao PengDepartment of Endocrinology, Yan'an Hospital of Kunming City, Kunming, China.
Jianmei ZhangPhysiatrics Medicine, Yan'an Hospital of Kunming City, Kunming, China.
Jinsong LiThe Yunnan Red-Cross Hospital, Affiliated Hospital of Yunnan University, Kunming, China.
Kun-Wen ZhengDepartment of Neurology, The First People's Hospital of Yunnan Province, Kunming, China.
Ping NingChengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
Wendy LiComputational Biology and Medical Ecology Lab, State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

diversity-area relationship (DAR)diversity heterogeneityhuman breast milk microbiome (BMM)population potential diversityratio of individual-to-population accrual diversity (RIP)

Identifiers

PMID36225365
PMCPMC9549050

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