Meng Qingxin, Liu Shuang, Guo Yue, Hu Yunlong, Yu Zhidan, Bello Ayodeji, Wang Zhigang, Xu Weihui, Xu Xiuhong
School of Life Science and Agriculture and Forestry, Qiqihar University, Qiqihar, 161006, China.
College of Resources and Environment, Northeast Agricultural University, Harbin, 150030, China.
Environ Sci Pollut Res Int. 2023 Feb;30(8):20265-20276. doi: 10.1007/s11356-022-23599-0. Epub 2022 Oct 17.
Microbes often form complex ecological networks in various habitats. Co-occurrence network analysis allows exploring the complex community interactions beyond the community diversities. This study explores the interspecific relationships within and between bacterial and fungal communities during composting of cow manure using co-occurrence network analysis. Furthermore, the keystone taxa that potentially exert a considerable impact on the microbiome were revealed by network analysis. The networks in the present study harbored more positive links. Specifically, the interactions/coupling within bacterial communities was tighter and the response to changes in external environmental conditions was more quickly during the composting process, while the fungal network had a better buffer capacity for changes in external environmental conditions. Interestingly, this result was authenticated in the bacterial-fungal (BF) network and the Mantel test of major modules and environmental variables. More than that, the Zi-Pi plot revealed that the keystone taxa including "module hubs" and "connectors" were all detected in these networks, which could prevent the dissociation of modules and networks.
微生物常常在各种栖息地中形成复杂的生态网络。共现网络分析能够探究群落多样性之外的复杂群落相互作用。本研究利用共现网络分析,探索牛粪堆肥过程中细菌和真菌群落内部以及它们之间的种间关系。此外,通过网络分析揭示了可能对微生物组产生重大影响的关键类群。本研究中的网络具有更多的正相关联系。具体而言,在堆肥过程中,细菌群落内部的相互作用/耦合更紧密,对外界环境条件变化的响应更快,而真菌网络对外界环境条件变化具有更好的缓冲能力。有趣的是,这一结果在细菌 - 真菌(BF)网络以及主要模块与环境变量的 Mantel 检验中得到了验证。不仅如此,Zi - Pi 图显示,这些网络中均检测到了包括“模块枢纽”和“连接子”在内的关键类群,它们能够防止模块和网络的解离。