Identifying eukaryotes in drinking water metagenomes and factors influencing their biogeography

Abstract

AbstractThe biogeography of eukaryotes in drinking water systems is poorly understood relative to prokaryotes or viruses. A common challenge with studying complex eukaryotic communities from natural and engineered systems is that the metagenomic analysis workflows are currently not as mature as those that focus on prokaryotes or even viruses. In this study, we benchmarked different strategies to recover eukaryotic sequences and genomes from metagenomic data and applied the best-performing workflow to explore eukaryotic communities present in drinking water distribution systems (DWDSs). We developed an ensemble approach that exploits k-mer and reference-based strategies to improve eukaryotic sequence identification from metagenomes and identified MetaBAT2 as the best performing binning approach for clustering of eukaryotic sequences. Applying this workflow on the DWDSs metagenomes showed that eukaryotic sequences typically constituted a small proportion (i.e., <1%) of the overall metagenomic data. Eukaryotic sequences showed higher relative abundances in surface water-fed and chlorine disinfected systems. Further, the alpha and beta-diversity of eukaryotes were correlated with prokaryotic and viral communities. Finally, a co-occurrence analysis highlighted clusters of eukaryotes whose presence and abundance in DWDSs is affected by disinfection strategies, climate conditions, and source water types.SynopsisAfter benchmarking tools and developing a dedicated consensus workflow for eukaryotic sequence detection in metagenomes, the experimental, environmental, and engineering factors affecting their biogeography in drinking water distribution systems were investigatedGraphical abstract