Identifying eukaryotes in drinking water metagenomes and factors influencing their biogeography.

Abstract

The 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., View larger version (33K): org.highwire.dtl.DTLVardef@1ae8423org.highwire.dtl.DTLVardef@653471org.highwire.dtl.DTLVardef@5606b7org.highwire.dtl.DTLVardef@1d30cde_HPS_FORMAT_FIGEXP M_FIG C_FIG