Composition and Dynamics of the Activated Sludge Microbiome during Seasonal Nitrification Failure

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8 Scopus citations

Abstract

Wastewater treatment plants in temperate climate zones frequently undergo seasonal nitrification failure in the winter month yet maintain removal efficiency for other contaminants. We tested the hypothesis that nitrification failure can be correlated to shifts in the nitrifying microbial community. We monitored three parallel, full-scale sequencing batch reactors over the course of a year with respect to reactor performance, microbial community composition via 16S rRNA gene amplicon sequencing, and functional gene abundance using qPCR. All reactors demonstrated similar changes to their core microbiome, and only subtle variations among seasonal and transient taxa. We observed a decrease in species richness during the winter, with a slow recovery of the activated sludge community during spring. Despite the change in nitrification performance, ammonia monooxygenase gene abundances remained constant throughout the year, as did the relative sequence abundance of Nitrosomonadacae. This suggests that nitrification failure at colder temperatures might result from different reaction kinetics of nitrifying taxa, or that other organisms with strong seasonal shifts in population abundance, e.g. an uncultured lineage of Saprospiraceae, affect plant performance in the winter. This research is a comprehensive analysis of the seasonal microbial community dynamics in triplicate full-scale sequencing batch reactors and ultimately strengthens our basic understanding of the microbial ecology of activated sludge communities by revealing seasonal succession patterns of individual taxa that correlate with nutrient removal efficiency.

Original languageEnglish (US)
Article number4565
JournalScientific reports
Volume9
Issue number1
DOIs
StatePublished - Dec 1 2019

Bibliographical note

Funding Information:
We would like to thank Gregg Kropp and the team at Brainerd Wastewater Treatment Facilities for sample collection and access to treatment plant performance data. We would like to thank the University of Minnesota Genomics Center for assistance with amplicon sequencing and access to the 7900HT Fast Real-Time PCR System. We would like to thank the National Science Foundation Graduate Research Fellows Program for providing Juliet Johnston with a fellowship opportunity as well as the Legislative-Citizen Commission on Minnesota Resources for funding the project. Finally, thank you to Amelia McClure for helping with qPCR protocols and Deirdre Manion-Fischer for proofing. J. Johnston was supported by the National Science Foundation Graduate Research Fellowship Program (ID: 2015191729). The research was enabled by the Legislative-Citizen Commission on Minnesota Resources (LCCMR) through a grant entitled “Wastewater Treatment Process Improvements” funded by the Environment and Natural Resources Trust Fund (ENRTF) under legal citation M.L. 2016, Chp. 186, Sec. 2, Subd. 04 k.

Publisher Copyright:
© 2019, The Author(s).

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