Abstract
The human breast milk microbiome (HMM) has far reached health implications for both mothers and infants, and understanding the structure and dynamics of milk microbial communities is therefore of critical biomedical importance. Community heterogeneity, which has certain commonalities with familiar diversity but also with certain fundamental differences, is an important aspect of community structure and dynamics. Taylor’s (1961) power law (TPL) (Nature, 1961) was discovered to govern the mean–variance power function relationship of population abundances and can be used to characterize population spatial aggregation (heterogeneity) and/or temporal stability. TPL was further extended to the community level to measure community spatial heterogeneity and/or temporal stability (Ma 2015, Molecular Ecology). Here, we applied TPL extensions (TPLE) to analyze the heterogeneity of the human milk microbiome by reanalyzing 12 datasets (2115 samples) of the healthy human milk microbiome. Our analysis revealed that the TPLE heterogeneity parameter (b) is rather stable across the 12 datasets, and there were approximately no statistically significant differences among ¾ of the datasets, which is consistent with the hypothesis that the heterogeneity scaling (i.e., change across individuals) of the human microbiome, including HMM, is rather stable or even constant. For this, we built a TPLE model for the pooled 12 datasets (b = 1.906), which can therefore represent the scaling rate of community-level spatial heterogeneity of HMM across individuals. Similarly, we also analyzed mixed-species (“averaged virtual species”) level heterogeneity of HMM, and it was found that the mixed-species level heterogeneity was smaller than the heterogeneity at the previously mentioned community level (1.620 vs. 1.906).
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Data availability statement and ethical approval
All datasets used in this study are available in the public domain and their sources are noted in Table S1. No data related to human subjects were used in this study, and no ethical approval was inapplicable. The original contributions presented in the study are included in the article/Supplementary Material, and further inquiries can be directed to the corresponding authors.
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Funding
This research received funding from the following sources: The State Key Laboratory of Genetic Resources and Evolution (#GREKF21-06#, GREKF20-06, GREKF19-07) and Yunnan Province Local University (Part) Basic Research for Youths (No. 202001BA070001-100 and 202101BA070001-018); National Science Foundation of China (Grant #12161033); The Yunnan Provincial Department of Education Scientific Research Fund Project (No. 2022J0896); National Natural Science Foundation (NSFC) (Grant No. 31970116).
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HC and BY conducted the data analysis and wrote the manuscript; We appreciate the data curation support from LW Li and WM Xiao (from Computational Biology and Medical Ecology Lab, Chinese Academy of Sciences). All authors approved the submission.
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Yi, B., Chen, H. Power law analysis of the human milk microbiome. Arch Microbiol 204, 585 (2022). https://doi.org/10.1007/s00203-022-03171-7
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DOI: https://doi.org/10.1007/s00203-022-03171-7