Graduate School of Science and Technology, Shizuoka University.
Microbial Ecotechnology, Department of Biotechnology, Graduate School of Agricultural and Life Sciences, The University of Tokyo.
Microbes Environ. 2024;39(1). doi: 10.1264/jsme2.ME23091.
A more detailed understanding of the mechanisms underlying the formation of microbial communities is essential for the efficient management of microbial ecosystems. The stable states of microbial communities are commonly perceived as static and, thus, have not been extensively examined. The present study investigated stabilizing mechanisms, minority functions, and the reliability of quantitative ana-lyses, emphasizing a metabolic network perspective. A bacterial community, formed by batch transferred cultures supplied with phenol as the sole carbon and energy source and paddy soil as the inoculum, was analyzed using a principal coordinate ana-lysis (PCoA), mathematical models, and quantitative parameters defined as growth activity, community-changing activity, community-forming activity, vulnerable force, and resilience force depending on changes in the abundance of operational taxonomic units (OTUs) using 16S rRNA gene amplicon sequences. PCoA showed succession states until the 3 transferred cultures and stable states from the 5 to 10 transferred cultures. Quantitative parameters indicated that the bacterial community was dynamic irrespective of the succession and stable states. Three activities fluctuated under stable states. Vulnerable and resilience forces were detected under the succession and stable states, respectively. Mathematical models indicated the construction of metabolic networks, suggesting the stabilizing mechanism of the community structure. Thirteen OTUs coexisted during stable states, and were recognized as core OTUs consisting of majorities, middle-class, and minorities. The abundance of the middle-class changed, whereas that of the others did not, which indicated that core OTUs maintained metabolic networks. Some extremely low abundance OTUs were consistently exchanged, suggesting a role for scavengers. These results indicate that stable states were formed by dynamic metabolic networks with members functioning to achieve robustness and plasticity.
深入了解微生物群落形成的机制对于有效管理微生物生态系统至关重要。微生物群落的稳定状态通常被认为是静态的，因此尚未得到广泛研究。本研究从代谢网络的角度出发，研究了稳定机制、少数功能和定量分析的可靠性。利用主坐标分析（PCoA）、数学模型和定量参数，分析了由分批转移培养物形成的细菌群落，这些培养物以苯酚作为唯一的碳源和能源，以稻田土壤作为接种物。定量参数根据操作分类单元（OTU）丰度的变化定义为生长活性、群落变化活性、群落形成活性、脆弱力和恢复力，16S rRNA 基因扩增子序列。PCoA 显示出在 3 次转移培养物时的演替状态和在 5 到 10 次转移培养物时的稳定状态。定量参数表明，细菌群落无论在演替还是稳定状态下都是动态的。三种活性在稳定状态下波动。脆弱力和恢复力分别在演替和稳定状态下被检测到。数学模型表明代谢网络的构建，表明了群落结构的稳定机制。在稳定状态下，有 13 个 OTU 共存，被认为是由多数、中产阶级和少数组成的核心 OTU。中产阶级的丰度发生了变化，而其他的丰度没有变化，这表明核心 OTU 维持了代谢网络。一些极低丰度的 OTU 一直被交换，表明了清道夫的作用。这些结果表明，稳定状态是由具有实现稳健性和可塑性功能的动态代谢网络形成的。
