Functional Molecular Ecological Networks

By Jizhong Zhou, Ye Deng, Feng Luo, Zhili He, Qichao Tu, Xiaoyang Zhi. mBio, 2010

875 citations recorded by the source corpus.

ABSTRACT 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 CO2 (eCO2) 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, CO2 enrichment) experiment. Our results indicate that RMT is powerful in identifying functional molecular ecological networks in microbial communities. Both functional molecular ecological networks under eCO2 and ambient CO2 (aCO2) 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 eCO2 and aCO2, at the levels of the entire communities, individual functional gene categories/groups, and functional genes/sequences, suggesting that eCO2 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. IMPORTANCE Microorganisms are the foundation of the Earth's biosphere and play integral and unique roles in various ecosystem processes and functions. In an ecosystem, various microorganisms interact with each other to form complicated networks. Elucidating network interactions and their responses to environmental changes is difficult due to the lack of appropriate experimental data and an appropriate theoretical framework. This study provides a conceptual framework to construct interaction networks in microbial communities based on high-throughput functional gene array hybridization data. It also first documents that elevated carbon dioxide in the atmosphere dramatically alters the network interactions in soil microbial communities, which could have important implications in assessing the responses of ecosystems to climate change. The conceptual framework developed allows microbiologists to address research questions unapproachable previously by focusing on network interactions beyond the listing of, e.g., the number and abundance of species. Thus, this study could represent transformative research and a paradigm shift in microbial ecology. Microorganisms are the foundation of the Earth's biosphere and play integral and unique roles in various ecosystem processes and functions. In an ecosystem, various microorganisms interact with each other to form complicated networks. Elucidating network interactions and their responses to environmental changes is difficult due to the lack of appropriate experimental data and an appropriate theoretical framework. This study provides a conceptual framework to construct interaction networks in microbial communities based on high-throughput functional gene array hybridization data. It also first documents that elevated carbon dioxide in the atmosphere dramatically alters the network interactions in soil microbial communities, which could have important implications in assessing the responses of ecosystems to climate change. The conceptual framework developed allows microbiologists to address research questions unapproachable previously by focusing on network interactions beyond the listing of, e.g., the number and abundance of species. Thus, this study could represent transformative research and a paradigm shift in microbial ecology.

Subfields: Molecular Biology, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/6834ce9becd4c8897b23dbd98a024b8bba4dc5b5

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Citations in the corpus

Fungal networks in yield-invigorating and -debilitating soils induced by prolonged potato monoculture. (2013, background): “…et al., 2010), dental biofilm (Duran-Pinedo et al., 2011), human microbiome (Faust et al., 2012; Greenblum et al., 2012), bacterial communities in variety of soil samples (Barberan et al., 2012), and the communities in soils influenced by elevated CO2 (Deng et al., 2012; Zhou et al., 2010, 2011).”
NetCoMi: network construction and comparison for microbiome data in R (2020, neutral): “Existing tools for network comparison either require pre-computed networks [32] or are tailored for specific biological purposes, including protein– protein interactions [33, 34] or gene functions [35].”
Machine learning for metagenomics: methods and tools (2015, background): “…been argued that a functional view should better characterize a microbial community than its taxonomic composition since different organisms are able to perform similar biological functions, giving rise to the concept of community-realized functions (Liu, 2012; Fuhrman, 2009; Zhou et al., 2010).”
Soil Bacterial and Fungal Response to Wildfires in the Canadian Boreal Forest Across a Burn Severity Gradient (2019, positive): “We determined standard network characterization metrics (Guimera and Amaral, 2005; Olesen et al., 2007; Zhou et al., 2010; Deng et al., 2012; Shi et al., 2016).”