Predicting microbial community compositions in wastewater treatment plants using artificial neural networks.

ABSTRACT:

Background

Activated sludge (AS) of wastewater treatment plants (WWTPs) is one of the world's largest artificial microbial ecosystems and the microbial community of the AS system is closely related to WWTPs' performance. However, how to predict its community structure is still unclear.

Results

Here, we used artificial neural networks (ANN) to predict the microbial compositions of AS systems collected from WWTPs located worldwide. The predictive accuracy R²_1:1 of the Shannon-Wiener index reached 60.42%, and the average R²_1:1 of amplicon sequence variants (ASVs) appearing in at least 10% of samples and core taxa were 35.09% and 42.99%, respectively. We also found that the predictability of ASVs was significantly positively correlated

SUBMITTER: Liu X 

PROVIDER: S-EPMC10142226 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature