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A Tripartite Microbial-Environment Network Indicates How Crucial Microbes Influence the Microbial Community Ecology

  • Environmental Microbiology
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Abstract

Current technologies could identify the abundance and functions of specific microbes, and evaluate their individual effects on microbial ecology. However, these microbes interact with each other, as well as environmental factors, in the form of complex network. Determination of their combined ecological influences remains a challenge. In this study, we developed a tripartite microbial-environment network (TMEN) analysis method that integrates microbial abundance, metabolic function, and environmental data as a tripartite network to investigate the combined ecological effects of microbes. Applying TMEN to analyzing the microbial-environment community structure in the sediments of Hangzhou Bay, one of the most seriously polluted coastal areas in China, we found that microbes were well-organized into 4 bacterial communities and 9 archaeal communities. The total organic carbon, sulfate, chemical oxygen demand, salinity, and nitrogen-related indexes were detected as crucial environmental factors in the microbial-environmental network. With close interactions with these environmental factors, Nitrospirales and Methanimicrococcu were identified as hub microbes with connection advantage. Our TMEN method could close the gap between lack of efficient statistical and computational approaches and the booming of large-scale microbial genomic and environmental data. Based on TMEN, we discovered a potential microbial ecological mechanism that crucial species with significant influence on the microbial community ecology would possess one or two of the community advantages for enhancing their ecological status and essentiality, including abundance advantage and connection advantage.

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Acknowledgments

We sincerely thank the following people in sample collection and pretreatment: Mr. Bei Huang and Mr. Qinglin Mu from Zhejiang Provincial Zhoushan Marine Ecological Environmental Monitoring Station; Dr. Rui Liu and Ms. Yaqiong Lan from Zhejiang Provincial Key Laboratory of Water Science and Technology, Department of Environmental Technology and Ecology, Yangtze Delta Region Institute of Tsinghua University. We also appreciate the advice about network visualization from Mr. Naijia Xiao at the Institute for Environmental Genomics, University of Oklahoma, and the advice about statistical methods from Mr. Molei Liu at the Department of Biostatistics, Harvard T.H. Chan School of Public Health.

Funding

This study was supported by General Projects (Nos. 51678003 and 51678334) granted by the Natural Science Foundation of China.

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Authors and Affiliations

  1. College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China

    Yushi Tang, Tianjiao Dai, Zhiguo Su & Donghui Wen

  2. Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA

    Yushi Tang & Kohei Hasegawa

  3. Massachusetts General Hospital, Harvard Medical School, 125 Nashua Street, Boston, MA, 02115, USA

    Kohei Hasegawa

  4. School of Environment, Tsinghua University, Beijing, 100084, China

    Jinping Tian & Lujun Chen

  5. Zhejiang Provincial Key Laboratory of Water Science and Technology, Department of Environmental Technology and Ecology, Yangtze Delta Region Institute of Tsinghua University, Jiaxing, 314050, Zhejiang, China

    Lujun Chen

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  1. Yushi Tang
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Correspondence to Donghui Wen.

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Tang, Y., Dai, T., Su, Z. et al. A Tripartite Microbial-Environment Network Indicates How Crucial Microbes Influence the Microbial Community Ecology. Microb Ecol 79, 342–356 (2020). https://doi.org/10.1007/s00248-019-01421-8

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