Eukaryote diversity and interactions with bacterial communities within laboratory granular activated carbon biofilter treating surface water

Abstract Background Drinking water biofilters rely on complex microbial communities to remove contaminants, yet studies have predominantly focused on bacteria, limiting understanding of the eukaryotes and their roles. Eukaryotes may influence biofilter performance through trophic interactions and cross-domain associations. This study aimed to characterise eukaryotic diversity and examine associations with bacterial communities during the start-up of laboratory-scale granular activated carbon (GAC) biofilters treating surface water using 18S rRNA and 16S rRNA amplicon sequencing. Results Eukaryotic biofilter communities displayed relatively low richness (60–80 ASVs), that spanned over 25 phyla, accounting for 98.9% of the relative abundance. Eukaryote biofilter communities were distinct in influent and effluent assemblages, but did not change over time or biofilter depth. The neutral model identified a suite of core taxa, several which were deterministically selected, including Vermamoeba . Generalised Linear Latent Variable Models identified 24 eukaryotes and 75 bacteria with significant positive or negative correlations, including a weak positive association between Vermamoeba and Legionella . The overall network analysis was dominated by bacteria, but showed three peripheral eukaryotes ( Chaetonotida , Pterocystis , Rigifilida ) exhibiting predominantly negative associations with bacteria. Conclusions These findings show that eukaryotes, despite their relatively low diversity, are a consistent and potentially influential component of biofilter microbiomes. While the observed associations do not establish causality, they highlight plausible pathways through which eukaryotes may contribute to microbial community structuring. This work broadens the ecological perspective of drinking water biofilters and provides a foundation for future studies investigating cross-domain interactions and their implications for optimising biological water treatment processes.