# Developing and Evaluating Aquatic Passive Sampling of Environmental DNA for Microbial Community Profiling

## TL;DR

A new passive sampling method for collecting environmental DNA in water is shown to be more effective than traditional methods for studying microbial diversity.

## Contribution

The study introduces and validates a passive sampling method for eDNA collection that outperforms active filtration in microbial biodiversity monitoring.

## Key findings

- Passive sampling for 24 hours with enzymatic extraction yielded significantly more eDNA and higher biodiversity than shorter durations and mechanical extractions.
- Passive sampling outperformed active filtration with over 100% higher eDNA yields and 50% higher taxonomic and phylogenetic diversities.
- Passive sampling detected more environmental factors and bioindicators compared to active filtration.

## Abstract

Environmental DNA (eDNA) metabarcoding has transformed biodiversity monitoring across taxa from bacteria to mammals, yet sample collection remains a major bottleneck. Passive sampling via adsorption and entrapment has emerged as a promising alternative to overcome the limitations of conventional active filtration. However, the performance of passive sampling for microbial biodiversity monitoring remains unknown. Here, we developed passive sampling‐based microbial community profiling by testing five submersion times and three common eDNA extraction methods in mesocosms, and comprehensively evaluated it by comparing results with active filtration in estuarine and coastal environments. We found that passive sampling for 24 h with enzymatic extraction yielded significantly more eDNA and higher biodiversity than shorter durations and mechanical extractions. Passive sampling consistently outperformed active filtration at every field site, with average increases of >100% in eDNA yields and >50% in taxonomic and phylogenetic diversities. Additionally, active filtration and passive sampling yielded significantly different prokaryotic and microeukaryotic community compositions, driven primarily by turnover rather than nestedness (on average 4‐fold larger), implying that passive sampling is better suited for spatiotemporal detection than active filtration. Passive sampling showed greater sensitivity in identifying key environmental factors (3 vs. 2) and potential environmental bioindicators (40 vs. 20) compared with active filtration. Overall, this study establishes an efficient and practical passive sampling method for microbial biodiversity monitoring and environmental assessment in aquatic environments.