污水处理系统中微生物群落作用机制的统计学方法研究进展

Research Progress on Statistical Methods for Mechanisms of Microbial Communities in Wastewater Treatment Systems

摘要: 污水生物处理系统的运行性能与微生物群落结构、功能潜力及代谢响应密切相关。随着高通量测序和代谢组学数据的积累，统计学方法已成为解析污水处理微生物机制的重要工具。本文围绕微生物群落结构与功能研究，系统梳理α多样性、β多样性、差异检验、降维排序、互作网络和群落稳定性等结构统计方法，并进一步总结功能预测、代谢组统计及功能–物种关联分析的应用思路。结合填料强化多级生物接触氧化工艺和C/N比调控需求，本文指出现有方法在组成型数据处理、时间滞后刻画、因果解释和多组学整合方面仍存在局限。未来应加强动态统计模型、机器学习、多组学联合建模和工程预警应用，以提升污水处理系统的精准调控能力。

Abstract: The operation performance of wastewater biological treatment system is closely related to microbial community structure, functional potential and metabolic responses. With the accumulation of high-throughput sequencing and metabolomics data, statistical methods have become an important tool for analyzing the microbial mechanism of wastewater treatment. Focusing on the research of microbial community structure and function, this paper systematically reviews the structural statistical methods such as α diversity, β diversity, difference test, dimension reduction sorting, interaction network and community stability, and further summarizes the application ideas of functional prediction, metabolome statistics and functional-species association analysis. Combined with the packing-enhanced multi-stage biological contact oxidation process and C/N ratio control requirements, this paper points out that the existing methods still have limitations in compositional data processing, time lag characterization, causal interpretation and multi-omics integration. In the future, dynamic statistical models, machine learning, multi-omics joint modeling and engineering early warning applications should be strengthened to improve the precise control ability of wastewater treatment systems.