Abstract:
Traditional mathematical models utilized in wastewater treatment plants (WWTPs)
design encounter limitations in accurately characterizing the intricate metabolic functions
transpiring within bacterial cells. Nevertheless, the progress in sequencing technologies
and computational power has made it easier to study and identify the taxonomic and
functional aspects of microorganisms present in wastewater treatment plants (WWTPs).
Furthermore, adopting a systems biology approach enables a holistic comprehension of
the ecological interactions between microbial communities and their subsequent effects
on the efficiency of the treatment process. This study conducted a meta-analysis to
identify the core microbial community members of municipal wastewater treatment
plants, community diversities across the different regions, and correlations among key
microbial families. A mathematical model was developed to represent the relationship
between relative abundance and occurrence frequency of microbial families. Principal
component analysis and network analysis were used to identify community diversities
and microbial correlations. While important microbial species and their relationships were
identified, no significant variations were observed among different geographical regions.
Through the application of meta-analysis, it is possible to leverage the obtained results to
provide a comprehensive understanding of the factors that influence the dynamics of the
process.
