Trait-based life-history strategies explain succession scenario for complex bacterial communities under varying disturbance. bioreactor sludge metagenome

Trait-based approaches are increasingly gaining importance in community ecology, as a way of finding general rules for the mechanisms driving changes in community structure and function under the influence of perturbations. Frameworks for life-history strategies have been successfully applied to describe changes in plant and animal communities upon disturbance. To evaluate their applicability to complex bacterial communities, we operated replicated wastewater treatment bioreactors for 35 days and subjected them to eight different disturbance frequencies of a toxic pollutant (3-chloroaniline), starting with a mixed inoculum from a full-scale treatment plant. Relevant ecosystem functions were tracked and microbial communities assessed through metagenomics and 16S rRNA gene sequencing. Combining a series of ordination, statistical and network analysis methods, we associated different life-history strategies with microbial communities across the disturbance range. These strategies were evaluated using tradeoffs in community function and genotypic potential, and changes in bacterial genus composition. We further compared our findings with other ecological studies and adopted a semi-quantitative CSR (competitors, ruderals, stress-tolerants) classification. The framework reduces complex datasets of microbial traits, functions, and taxa into ecologically meaningful components to help understand the system response to disturbance, and hence represents a promising tool for managing microbial communities.

基于性状的研究方法（Trait-based approaches）在群落生态学中的重要性与日俱增，其核心目标是探寻扰动条件下驱动群落结构与功能变化的机制性通用规律。生活史策略理论框架已成功应用于描述扰动下动植物群落的动态变化。为评估该框架在复杂细菌群落中的适用性，本研究搭建多组平行污水处理生物反应器并运行35天，以某规模化污水处理厂的混合接种菌群为起始菌群，施加8种不同频率的有毒污染物3-氯苯胺（3-chloroaniline）扰动。研究通过宏基因组学（metagenomics）与16S rRNA基因测序技术，对相关生态系统功能进行动态监测并完成微生物群落表征。本研究结合一系列排序分析、统计分析与网络分析方法，将不同生活史策略与不同扰动梯度下的微生物群落建立关联；从群落功能与遗传潜力的权衡关系、细菌属水平组成变化两方面，对上述生活史策略进行评估。此外，本研究将研究结果与其他生态学研究进行对比，并采用半定量的CSR（competitors, ruderals, stress-tolerants）分类体系。该框架可将微生物性状、功能与类群的复杂数据集简化为具有生态学意义的组分，助力理解生态系统对扰动的响应，因此有望成为调控微生物群落的有效工具。