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Functional Molecular Ecological Networks

Biodiversity and its responses to environmental changes are central issues in ecology and for society. Almost all microbial biodiversity research focuses on “species” richness and abundance but not on their interactions. Although a network approach is powerful in describing ecological interactions a...

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Autores principales: Zhou, Jizhong, Deng, Ye, Luo, Feng, He, Zhili, Tu, Qichao, Zhi, Xiaoyang
Formato: Texto
Lenguaje:English
Publicado: American Society of Microbiology 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2953006/
https://www.ncbi.nlm.nih.gov/pubmed/20941329
http://dx.doi.org/10.1128/mBio.00169-10
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author Zhou, Jizhong
Deng, Ye
Luo, Feng
He, Zhili
Tu, Qichao
Zhi, Xiaoyang
author_facet Zhou, Jizhong
Deng, Ye
Luo, Feng
He, Zhili
Tu, Qichao
Zhi, Xiaoyang
author_sort Zhou, Jizhong
collection PubMed
description Biodiversity and its responses to environmental changes are central issues in ecology and for society. Almost all microbial biodiversity research focuses on “species” richness and abundance but not on their interactions. Although a network approach is powerful in describing ecological interactions among species, defining the network structure in a microbial community is a great challenge. Also, although the stimulating effects of elevated CO(2) (eCO(2)) on plant growth and primary productivity are well established, its influences on belowground microbial communities, especially microbial interactions, are poorly understood. Here, a random matrix theory (RMT)-based conceptual framework for identifying functional molecular ecological networks was developed with the high-throughput functional gene array hybridization data of soil microbial communities in a long-term grassland FACE (free air, CO(2) enrichment) experiment. Our results indicate that RMT is powerful in identifying functional molecular ecological networks in microbial communities. Both functional molecular ecological networks under eCO(2) and ambient CO(2) (aCO(2)) possessed the general characteristics of complex systems such as scale free, small world, modular, and hierarchical. However, the topological structures of the functional molecular ecological networks are distinctly different between eCO(2) and aCO(2), at the levels of the entire communities, individual functional gene categories/groups, and functional genes/sequences, suggesting that eCO(2) dramatically altered the network interactions among different microbial functional genes/populations. Such a shift in network structure is also significantly correlated with soil geochemical variables. In short, elucidating network interactions in microbial communities and their responses to environmental changes is fundamentally important for research in microbial ecology, systems microbiology, and global change.
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spelling pubmed-29530062010-10-12 Functional Molecular Ecological Networks Zhou, Jizhong Deng, Ye Luo, Feng He, Zhili Tu, Qichao Zhi, Xiaoyang mBio Research Article Biodiversity and its responses to environmental changes are central issues in ecology and for society. Almost all microbial biodiversity research focuses on “species” richness and abundance but not on their interactions. Although a network approach is powerful in describing ecological interactions among species, defining the network structure in a microbial community is a great challenge. Also, although the stimulating effects of elevated CO(2) (eCO(2)) on plant growth and primary productivity are well established, its influences on belowground microbial communities, especially microbial interactions, are poorly understood. Here, a random matrix theory (RMT)-based conceptual framework for identifying functional molecular ecological networks was developed with the high-throughput functional gene array hybridization data of soil microbial communities in a long-term grassland FACE (free air, CO(2) enrichment) experiment. Our results indicate that RMT is powerful in identifying functional molecular ecological networks in microbial communities. Both functional molecular ecological networks under eCO(2) and ambient CO(2) (aCO(2)) possessed the general characteristics of complex systems such as scale free, small world, modular, and hierarchical. However, the topological structures of the functional molecular ecological networks are distinctly different between eCO(2) and aCO(2), at the levels of the entire communities, individual functional gene categories/groups, and functional genes/sequences, suggesting that eCO(2) dramatically altered the network interactions among different microbial functional genes/populations. Such a shift in network structure is also significantly correlated with soil geochemical variables. In short, elucidating network interactions in microbial communities and their responses to environmental changes is fundamentally important for research in microbial ecology, systems microbiology, and global change. American Society of Microbiology 2010-10-05 /pmc/articles/PMC2953006/ /pubmed/20941329 http://dx.doi.org/10.1128/mBio.00169-10 Text en Copyright © 2010 Zhou et al. http://creativecommons.org/licenses/by-nc-sa/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-Share Alike 3.0 Unported License (http://creativecommons.org/licenses/by-nc-sa/3.0/) , which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Zhou, Jizhong
Deng, Ye
Luo, Feng
He, Zhili
Tu, Qichao
Zhi, Xiaoyang
Functional Molecular Ecological Networks
title Functional Molecular Ecological Networks
title_full Functional Molecular Ecological Networks
title_fullStr Functional Molecular Ecological Networks
title_full_unstemmed Functional Molecular Ecological Networks
title_short Functional Molecular Ecological Networks
title_sort functional molecular ecological networks
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2953006/
https://www.ncbi.nlm.nih.gov/pubmed/20941329
http://dx.doi.org/10.1128/mBio.00169-10
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