Functional Molecular Ecological Networks

Zhou, Jizhong; Deng, Ye; Luo, Feng; He, Zhili; Tu, Qichao; Zhi, Xiaoyang

doi:10.1128/mbio.00169-10

Functional Molecular Ecological Networks

Journal Article · Tue Oct 05 04:00:00 EDT 2010 · mBio (Online)

DOI:https://doi.org/10.1128/mbio.00169-10· OSTI ID:1626091

Zhou, Jizhong ^[1]; Deng, Ye ^[2]; Luo, Feng ^[3]; He, Zhili ^[4]; Tu, Qichao ^[4]; Zhi, Xiaoyang ^[4]

Univ. of Oklahoma, Norman, OK (United States). Inst. for Environmental Genomics. Dept. of Botany and Microbiology; Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Earth Sciences Division; Tsinghua Univ., Beijing (China). Dept. of Environmental Science and Engineering; DOE/OSTI
Univ. of Oklahoma, Norman, OK (United States). Inst. for Environmental Genomics. Dept. of Botany and Microbiology; Glomics Inc., Norman, OK (United States)
Clemson Univ., SC (United States). School of Computing
Univ. of Oklahoma, Norman, OK (United States). Inst. for Environmental Genomics. Dept. of Botany and Microbiology

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.

View Accepted Manuscript (DOE)

Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); Univ. of Oklahoma, Norman, OK (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER). Earth and Environmental Systems Science Division

Grant/Contract Number:: AC02-05CH11231; SC0004601

OSTI ID:: 1626091

Journal Information:: mBio (Online), Journal Name: mBio (Online) Journal Issue: 4 Vol. 1; ISSN 2150-7511

Publisher:: American Society for Microbiology (ASM)Copyright Statement

Country of Publication:: United States

Language:: English

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