Causality and correlation analysis for deciphering the microbial interactions in activated sludge - Cai, Weiwei; Han, Xiangyu; Sangeetha, Thangavel; Yao, Hong (Frontiers in Microbiology, 2022)
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 the 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 genus Nitrospira, was responsible for nitrification in activated sludge, and interaction with Proteobacteria and Bacteroidetes in the form of amensal and commensal relationships, respectively. 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 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.