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Structure and Dynamics of the Breast Tissue Microbiomes Under Tumor Influences: An Approach With Neutral, Near-Neutral, and Niche-Neutral Hybrid Models
The structure and dynamics of breast tissue bacteria can have far-reaching influences on women’s health, particularly on breast tumor development. However, there is little understanding on the ecological processes that shape the structure and dynamics of breast tissue bacteria. Here, we fill the gap...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8326911/ https://www.ncbi.nlm.nih.gov/pubmed/34349731 http://dx.doi.org/10.3389/fmicb.2021.614967 |
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author | Li, Lianwei Ning, Ping Ma, Zhanshan (Sam) |
author_facet | Li, Lianwei Ning, Ping Ma, Zhanshan (Sam) |
author_sort | Li, Lianwei |
collection | PubMed |
description | The structure and dynamics of breast tissue bacteria can have far-reaching influences on women’s health, particularly on breast tumor development. However, there is little understanding on the ecological processes that shape the structure and dynamics of breast tissue bacteria. Here, we fill the gap by applying three metacommunity models for investigating the community assembly and diversity maintenance, including Sloan near neutral model, Harris et al. multisite neutral and Tang & Zhou niche-neutral hybrid models to reanalyze the 16S-rRNA sequencing datasets of 23 healthy, 12 benign tumor, and 33 malignant tumor tissue samples. First, we found that, at the community/metacommunity levels, the mechanisms of bacteria assembly and diversity maintenance of breast tissue bacteria were moderately influenced by stochastic drifts of bacteria demography (division, death, and dispersal of bacterial cells). At species level, on average, approximately 10 and 5% species were above (positively selected) and below (negatively selected) neutral, respectively. Furthermore, malignant tumor may raise the positively selected species up to 17%. Second, malignant tumor appears to inhibit microbial dispersal as evidenced by lowered migration rates, compared with the migration in normal and benign tumor tissues. These theoretic findings can be inspirational for further investigating the relationships between tissue bacteria and breast tumor progression/development. |
format | Online Article Text |
id | pubmed-8326911 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-83269112021-08-03 Structure and Dynamics of the Breast Tissue Microbiomes Under Tumor Influences: An Approach With Neutral, Near-Neutral, and Niche-Neutral Hybrid Models Li, Lianwei Ning, Ping Ma, Zhanshan (Sam) Front Microbiol Microbiology The structure and dynamics of breast tissue bacteria can have far-reaching influences on women’s health, particularly on breast tumor development. However, there is little understanding on the ecological processes that shape the structure and dynamics of breast tissue bacteria. Here, we fill the gap by applying three metacommunity models for investigating the community assembly and diversity maintenance, including Sloan near neutral model, Harris et al. multisite neutral and Tang & Zhou niche-neutral hybrid models to reanalyze the 16S-rRNA sequencing datasets of 23 healthy, 12 benign tumor, and 33 malignant tumor tissue samples. First, we found that, at the community/metacommunity levels, the mechanisms of bacteria assembly and diversity maintenance of breast tissue bacteria were moderately influenced by stochastic drifts of bacteria demography (division, death, and dispersal of bacterial cells). At species level, on average, approximately 10 and 5% species were above (positively selected) and below (negatively selected) neutral, respectively. Furthermore, malignant tumor may raise the positively selected species up to 17%. Second, malignant tumor appears to inhibit microbial dispersal as evidenced by lowered migration rates, compared with the migration in normal and benign tumor tissues. These theoretic findings can be inspirational for further investigating the relationships between tissue bacteria and breast tumor progression/development. Frontiers Media S.A. 2021-07-19 /pmc/articles/PMC8326911/ /pubmed/34349731 http://dx.doi.org/10.3389/fmicb.2021.614967 Text en Copyright © 2021 Li, Ning and Ma. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Microbiology Li, Lianwei Ning, Ping Ma, Zhanshan (Sam) Structure and Dynamics of the Breast Tissue Microbiomes Under Tumor Influences: An Approach With Neutral, Near-Neutral, and Niche-Neutral Hybrid Models |
title | Structure and Dynamics of the Breast Tissue Microbiomes Under Tumor Influences: An Approach With Neutral, Near-Neutral, and Niche-Neutral Hybrid Models |
title_full | Structure and Dynamics of the Breast Tissue Microbiomes Under Tumor Influences: An Approach With Neutral, Near-Neutral, and Niche-Neutral Hybrid Models |
title_fullStr | Structure and Dynamics of the Breast Tissue Microbiomes Under Tumor Influences: An Approach With Neutral, Near-Neutral, and Niche-Neutral Hybrid Models |
title_full_unstemmed | Structure and Dynamics of the Breast Tissue Microbiomes Under Tumor Influences: An Approach With Neutral, Near-Neutral, and Niche-Neutral Hybrid Models |
title_short | Structure and Dynamics of the Breast Tissue Microbiomes Under Tumor Influences: An Approach With Neutral, Near-Neutral, and Niche-Neutral Hybrid Models |
title_sort | structure and dynamics of the breast tissue microbiomes under tumor influences: an approach with neutral, near-neutral, and niche-neutral hybrid models |
topic | Microbiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8326911/ https://www.ncbi.nlm.nih.gov/pubmed/34349731 http://dx.doi.org/10.3389/fmicb.2021.614967 |
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