Fish eDNA metabarcoding is usually performed from filtered water samples. The volume of filtered water depends on the study scope and can rapidly become time consuming according to the number of samples that have to be processed. To avoid time allocated to filtration, passive DNA samplers have been used to recover fish eDNA from marine environments faster. In freshwater ecosystems, aquatic biofilms were used to catch eDNA from macroinvertebrates. Here, we test the capacity of aquatic biofilms to entrap fish eDNA in a large lake and, therefore, the possibility to perform fish eDNA metabarcoding from this matrix compared to the traditional fish eDNA approach from filtered water samples. Methodological aspects of the use of aquatic biofilms for fish eDNA metabarcoding (e.g. PCR replicates, biological replicates, bioinformatics pipeline, reference database and taxonomic assignment) were validated against a mock community. When using biofilms from habitats sheltered from wind and waves, biofilm and water approach provided similar inventories. Richness and diversity were comparable between both approaches. Approaches differed only for rare taxa. Our results illustrate the capacity of aquatic biofilms to act as passive eDNA samplers of fish eDNA and, therefore, the possibility to use biofilms to monitor fish communities efficiently from biofilms. Furthermore, our results open up avenues of research to study a diversity of biological groups (among which bioindicators as diatoms, macroinvertebrates and fish) from eDNA isolated from a single environmental matrix reducing sampling efforts, analysis time and costs.

No abstract

This protocol is part of the DNA workflow applied in the Eco-ALpsWater Project, here in particular to characterize the diversity of diatom assemblage in biofilms or plankton samples. Different studies have already revealed the potential of diatom metabarcoding applications for freshwater quality assessment (Kermarrec et al. 2014; Vasselon et al. 2017ab; Visco et al. 2015). The choice of the marker gene and barcode region is key for obtaining relevant inventories of diversity and precise taxonomic assignment. For benthic diatoms, the rbcL gene has proved to be an appropriate taxonomic marker for biomonitoring (Kermarrec et al. 2013, 2014; Vasselon et al. 2017a,b) and a well-curated barcode reference library is already available to assign species names to rbcL sequences (R-Syst::diatom, Rimet et al. 2016). For the Eco-AlpsWater project, biolfilms sampled in rivers and lakeshores are collected as described in the dedicated protocols ("Lake plankton sample collection ..." and "Biofilms sample collection ...") and DNA is extracted as described in the protocol "Biofilms DNA extraction" ; all these protocols are part of the Deliverable D.T1.1.2. We present here the following step in the DNA workflow (i.e. PCR amplification of selected barcodes, and wet lab methods to prepare DNA library for downstream MiSeq Sequencing). This protocol has been used in recent studies (e.g. Keck et al 2018 ; Vasselon et al 2018) where diatoms metabarcoding has been used for ecological assessment of rivers. Several primers were proposed in the literature to characterize Diatom communities through environmental DNA metabarcoding approaches, including the 18S, COI and rbcL barcodes. Following the recommendation provided by Kermarrec et al. 2014, who compared the efficiency of those 3 barcodes to accurately characterize diatom communities from freshwater samples (lakes and rivers), the rbcL barcode will be used within the Eco-AlpsWater project as he provides a good taxonomical resolution.

Environmental DNA (eDNA) metabarcoding is revolutionizing the monitoring of aquatic biodiversity. The use of eDNA has the potential to enable non-invasive, cost-effective, time-efficient and high-sensitivity monitoring of fish assemblages. Although the capacity of eDNA metabarcoding to describe fish assemblages is recognised, research efforts are still needed to better assess the spatial and temporal variability of the eDNA signal and to ultimately design an optimal sampling strategy for eDNA monitoring. In this context, we sampled three different lakes (a dam reservoir, a shallow eutrophic lake and a deep oligotrophic lake) every 6 weeks for 1 year. We performed four types of sampling for each lake (integrative sampling of sub-surface water along transects on the left shore, the right shore and above the deepest zone, and point sampling in deeper layers near the lake bottom) to explore the spatial variability of the eDNA signal at the lake scale over a period of 1 year. A metabarcoding approach was applied to analyse the 92 eDNA samples in order to obtain fish species inventories which were compared with traditional fish monitoring methods (standardized gillnet samplings). Several species known to be present in these lakes were only detected by eDNA, confirming the higher sensitivity of this technique in comparison with gillnetting. The eDNA signal varied spatially, with shoreline samples being richer in species than the other samples. Furthermore, deep-water samplings appeared to be non-relevant for regularly mixed lakes, where the eDNA signal was homogeneously distributed. These results also demonstrate a clear temporal variability of the eDNA signal that seems to be related to species phenology, with most of the species detected in spring during the spawning period on shores, but also a peak of detection in winter for salmonid and coregonid species during their reproduction period. These results contribute to our understanding of the spatio-temporal distribution of eDNA in lakes and allow us to provide methodological recommendations regarding where and when to sample eDNA for fish monitoring in lakes.