Relating target fish DNA concentration to community composition analysis in freshwater fish via metabarcoding

Metabarcoding has been widely accepted as a useful tool for biodiversity assessment based on eDNA. The method allows for the detection of entire groups of organisms in a single sample, making it particularly applicable in aquatic habitats. The high sensitivity of the molecular approaches is especially beneficial in detecting elusive and rare fish species, improving biodiversity assessments. Numerous biotic and abiotic factors that affect the persistence and availability of fish DNA in surface waters and therefore affecting species detectability, have been identified. However, little is known about the relationship between the total fish DNA concentration and the detectability of differential abundant species. In this study three controlled mock-community DNA samples (56 individual samples) were analyzed by (a) metabarcoding (MiSeq) of 12S rDNA (175 bp) and by (b) total freshwater fish DNA quantification (via qPCR of 12S rDNA). We show that the fish DNA quantity affects the relative abundance of species-specific sequences and the detectability of rare species. In particular we found that samples with a concentration between 1000 picogram per microliter down to 10 picogram per microliter of total fish DNA revealed a stable relative frequency of DNA sequences obtained for a specific fish species, as well as a low variability between replicates. Additionally, we observed that even in complex mock-community DNA samples, a total fish DNA concentration of 23 picogram per microliter was sufficient to reliably detect all species in every replicate, including three rare species with proportions of below 0.5 percent. We also found that the DNA barcode similarity between species can affect detectability, if evenness is low. Our data suggest that the total DNA concentration of fish is an important factor to consider when analyzing and interpreting relative sequence abundance data. Therefore, the workflow proposed here will contribute to an ecologically and economically efficient application of metabarcoding in fish biodiversity assessment.