@article {21946,
	title = {A Tripartite Microbial-Environment Network Indicates How Crucial Microbes Influence the Microbial Community Ecology},
	journal = {Microbial Ecology},
	year = {2019},
	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.},
	url = {https://link.springer.com/article/10.1007\%2Fs00248-019-01421-8},
	author = {Tang, Yushi and Dai, Tianjiao and Su, Zhiguo and Hasegawa, Kohei and Tian, Jinping and Chen, Lujun and Wen, Donghui}
}
