College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China.
Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA.
Microb Ecol. 2020 Feb;79(2):342-356. doi: 10.1007/s00248-019-01421-8. Epub 2019 Aug 19.
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.
当前的技术可以识别特定微生物的丰度和功能，并评估它们对微生物生态学的个体影响。然而，这些微生物以复杂网络的形式相互作用，以及与环境因素相互作用。确定它们的综合生态影响仍然是一个挑战。在这项研究中，我们开发了一种三方微生物-环境网络（TMEN）分析方法，将微生物丰度、代谢功能和环境数据整合为一个三方网络，以研究微生物的综合生态影响。将 TMEN 应用于分析中国污染最严重的沿海地区之一杭州湾沉积物中的微生物-环境群落结构，我们发现微生物被很好地组织成 4 个细菌群落和 9 个古菌群落。总有机碳、硫酸盐、化学需氧量、盐度和与氮有关的指标被检测为微生物-环境网络中的关键环境因素。与这些环境因素密切相互作用，硝化螺旋菌和甲烷微球菌被确定为具有连接优势的优势微生物。我们的 TMEN 方法可以缩小缺乏有效统计和计算方法与大规模微生物基因组和环境数据的蓬勃发展之间的差距。基于 TMEN，我们发现了一种潜在的微生物生态机制，即对微生物群落生态具有显著影响的关键物种将具有一种或两种增强其生态地位和重要性的群落优势，包括丰度优势和连接优势。
