Suppr超能文献

综合网络分析揭示了微生物相互作用对玉米生长的重要性。

Integrated network analysis reveals the importance of microbial interactions for maize growth.

机构信息

School of Minerals Processing and Bioengineering, Central South University, Changsha, China.

College of agronomy, Hunan Agricultural University, Changsha, China.

出版信息

Appl Microbiol Biotechnol. 2018 Apr;102(8):3805-3818. doi: 10.1007/s00253-018-8837-4. Epub 2018 Mar 12.

Abstract

Microbes play a critical role in soil global biogeochemical circulation and microbe-microbe interactions have also evoked enormous interests in recent years. Utilization of green manures can stimulate microbial activity and affect microbial composition and diversity. However, few studies focus on the microbial interactions or detect the key functional members in communities. With the advances of metagenomic technologies, network analysis has been used as a powerful tool to detect robust interactions between microbial members. Here, random matrix theory-based network analysis was used to investigate the microbial networks in response to four different green manure fertilization regimes (Vicia villosa, common vetch, milk vetch, and radish) over two growth cycles from October 2012 to September 2014. The results showed that the topological properties of microbial networks were dramatically altered by green manure fertilization. Microbial network under milk vetch amendment showed substantially more intense complexity and interactions than other fertilization systems, indicating that milk vetch provided a favorable condition for microbial interactions and niche sharing. The shift of microbial interactions could be attributed to the changes in some major soil traits and the interactions might be correlated to plant growth and production. With the stimuli of green manures, positive interactions predominated the network eventually and the network complexity was in consistency with maize productivity, which suggested that the complex soil microbial networks might benefit to plants rather than simple ones, because complex networks would hold strong the ability to cope with environment changes or suppress soil-borne pathogen infection on plants. In addition, network analyses discerned some putative keystone taxa and seven of them had directly positive interactions with maize yield, which suggested their important roles in maintaining environmental functions and in improving plant growth.

摘要

微生物在土壤全球生物地球化学循环中起着至关重要的作用,近年来微生物-微生物相互作用也引起了极大的兴趣。绿肥的利用可以刺激微生物的活性,影响微生物的组成和多样性。然而,很少有研究关注微生物的相互作用或检测群落中的关键功能成员。随着宏基因组技术的进步,网络分析已被用作检测微生物成员之间稳健相互作用的有力工具。在这里,基于随机矩阵理论的网络分析用于研究四个不同绿肥施肥制度(野豌豆、紫云英、金花菜和萝卜)在 2012 年 10 月至 2014 年 9 月两个生长周期内对微生物网络的影响。结果表明,绿肥施肥显著改变了微生物网络的拓扑性质。在添加金花菜的情况下,微生物网络显示出明显更复杂和相互作用的特性,这表明金花菜为微生物相互作用和生态位共享提供了有利条件。微生物相互作用的转变可能归因于一些主要土壤特性的变化,并且这些相互作用可能与植物生长和产量有关。随着绿肥的刺激,正相互作用最终主导了网络,并且网络的复杂性与玉米产量一致,这表明复杂的土壤微生物网络可能对植物有益,而不是简单的网络,因为复杂的网络将具有更强的应对环境变化或抑制植物土传病原体感染的能力。此外,网络分析区分了一些假定的关键类群,其中有 7 个与玉米产量有直接正相互作用,这表明它们在维持环境功能和促进植物生长方面具有重要作用。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验