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Understanding the microbial ecology of a system allows linking members of the community and their metabolic functions to the performance of the wastewater bioreactor. This study provided a comprehensive conceptual framework for microbial communities in wastewater treatment electro-bioreactors (EBRs). The model was based on data acquired from monitoring the effect of altering different bioreactor operational parameters, such as current density and hydraulic retention time, on the microbial communities of an EBR and its nutrient removal efficiency. The model was also based on the 16S rRNA gene high-throughput sequencing data analysis and bioreactor efficiency data. The collective data clearly demonstrated that applying various electric currents affected the microbial community composition and stability and the reactor efficiency in terms of chemical oxygen demand, N and P removals. Moreover, a schematic that recommends operating conditions that are tailored to the type of wastewater that needs to be treated based on the functional microbial communities enriched at specific operating conditions was suggested. In this study, a conceptual model as a simplified representation of the behavior of microbial communities in EBRs was developed. The proposed conceptual model can be used to predict how biological treatment of wastewater in EBRs can be improved by varying several operating conditions.

A conceptual framework modeling of functional microbial communities in wastewater treatment electro-bioreactors