Engineered bioreactors play a vital role in many processes to convert wastes to resources, such as biological wastewater treatment, bioremediation, and conversion of solid waste to methane in landfills. These biological systems rely on communities of microbes to convert waste to valuable resources. A central aspect of the design and operation of bioreactors involves an understanding of microbial community composition and dynamics, including the assembly processes through which they form. However, there remains a significant gap in our fundamental understanding of microbial community dynamics and microbial community assembly (MCA) processes, especially in engineered bioreactor settings. Here, we propose and employ a tool set that can be used by the research community, assess multiple bioreactor systems across a range of process types and ranges, and connect MCA patterns to relevant microbial groups in each bioreactor system. We applied multiple MCA assessment methods using available tools, layering on a trait-based approach, to seven experiments involving different engineered bioreactor systems. The calculated relative contributions of MCA processes varied by the method used, with null modeling approaches estimating a higher influence of stochastic MCA than neutral modeling. While most patterns of MCA were not discernible by general rules, anaerobic generalists assembled more deterministically than anaerobic specialists. Finally, statistical modeling of confidence levels suggests a minimum of 30–40 samples should be used for neutral modeling while a minimum 50–60 samples should be used for null modeling. Overall, we suggest caution when applying and interpreting the results of any one MCA assessment method.

中文翻译：

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使用不同方法量化生物反应器中微生物群落组装过程的模式会导致不同的结果


工程生物反应器在将废物转化为资源的许多过程中发挥着至关重要的作用，例如生物废水处理、生物修复以及在垃圾填埋场将固体废物转化为甲烷。这些生物系统依靠微生物群落将废物转化为有价值的资源。生物反应器设计和操作的一个核心方面涉及对微生物群落组成和动力学的理解，包括它们形成的组装过程。然而，我们对微生物群落动力学和微生物群落组装 （MCA） 过程的基本理解仍然存在很大差距，尤其是在工程生物反应器环境中。在这里，我们提出并采用了一套可供研究界使用的工具集，评估一系列工艺类型和范围内的多个生物反应器系统，并将 MCA 模式与每个生物反应器系统中的相关微生物组联系起来。我们使用可用工具应用了多种 MCA 评估方法，在基于性状的方法上分层，对涉及不同工程生物反应器系统的 7 个实验进行了分析。计算出的 MCA 过程的相对贡献因所使用的方法而异，零建模方法估计随机 MCA 的影响高于中性建模。虽然大多数 MCA 模式无法通过一般规则来辨别，但厌氧通才比厌氧专家更确定地聚集在一起。最后，置信度的统计建模表明，至少应使用 30-40 个样本进行中性建模，而至少应使用 50-60 个样本进行零建模。总的来说，我们建议在应用和解释任何一种 MCA 评估方法的结果时要谨慎。