Data_Sheet_1_Causality and correlation analysis for deciphering the microbial interactions in activated sludge.docx

Time series data has been considered to be a massive information provider for comprehending more about microbial dynamics and interaction, leading to a causality inference in a complex microbial community. Granger causality and correlation analysis have been investigated and applied for the construction of a microbial causal correlation network (MCCN) and efficient prediction of the ecological interaction within activated sludge, which thereby exhibited ecological interactions at the OTU-level. Application of MCCN to a time series of activated sludge data revealed that the hub species OTU56, classified as the one belonging to the genus Nitrospira, was responsible for nitrification in activated sludge and interaction with Proteobacteria and Bacteroidetes in the form of amensal and commensal relationships, respectively. The phylogenetic tree suggested a mutualistic relationship between Nitrospira and denitrifiers. Zoogloea displayed the highest ncf value within the classified OTUs of the MCCN, indicating that it could be a foundation for activated sludge through the formation of characteristic cell aggregate matrices where other organisms embed during floc formation. Inclusively, the research outcomes of this study have provided a deep insight into the ecological interactions within the communities of activated sludge.

时序数据（time series data）是解析微生物动态与种间互作的海量信息载体，可为复杂微生物群落的因果关系推断提供重要依据。格兰杰因果分析（Granger causality）与相关性分析已被研究并应用于构建微生物因果关联网络（microbial causal correlation network, MCCN），并实现对活性污泥内生态互作的高效预测，进而在操作分类单元（Operational Taxonomic Unit, OTU）层面呈现生态互作特征。将微生物因果关联网络（MCCN）应用于活性污泥时序数据集后发现，归类为硝化螺菌属（Nitrospira）的关键物种OTU56主导了活性污泥中的硝化过程，并分别以偏害共生（amensal）与偏利共生（commensal）的模式与变形菌门（Proteobacteria）、拟杆菌门（Bacteroidetes）产生互作。系统发育树（phylogenetic tree）分析结果显示，硝化螺菌属与反硝化细菌之间存在互利共生关系。在微生物因果关联网络（MCCN）的已分类操作分类单元中，动胶菌属（Zoogloea）的ncf值最高，表明其可通过形成特征性细胞聚集基质，为活性污泥絮凝体形成过程中其他微生物的附着提供基础。综上，本研究的结果为解析活性污泥群落内的生态互作关系提供了深刻见解。