Towards an eDNA metabarcode-based performance indicator for full-scale municipal wastewater treatment plants

Abstract

Knowledge-driven management for wastewater treatment plant (WWTP) performance becomes increasingly important considering the globally growing production of wastewater and the rising demand of clean water supply. Even though the potential of microbial organisms (bacteria and protists) as bioindicators for WWTP performance is well known, it is far from being fully exploited for routine monitoring programs. Therefore, we here used massive sequencing of environmental (e)DNA metabarcodes from bacterial (V3-V4 region of the SSU rRNA gene) and eukaryote (V9 region of the SSU rRNA gene) communities in 21 activated sludge samples obtained from full-scale municipal WWTPs in Germany. Microbial community patterns were compared to standard WWTP operating parameters and two traditionally used WWTP performance indicators (Sludge Biotic Index and Sludge Index). Both indices showed low concordance and hardly correlated with chemical WWTP performance parameters nor did they correlate with microbial community structures. In contrast, microbial community profiles significantly correlated with WWTP performance parameters and operating conditions of the plants under study. Therefore, eDNA metabarcode profiles of whole microbial communities indicate the performance of WWTP and can provide useful information for management strategies. We here suggest a strategy for the development of an eDNA metabarcode based bioindicator system, which can be implemented in future standard monitoring programs for WWTP performance and effluent quality.