Effects of preservation strategies on environmental DNA detection and quantification using ddPCR

Abstract

Molecular-based monitoring relying on environmental DNA (eDNA) detection became routinely used around the world in the last few years, especially in aquatic environments. The large potential and increasing applications of this technique calls for technical improvements to optimize the reliability of these surveys. An important technical aspect in the eDNA workflow is the appropriate preservation of samples taken in the field, as it can significantly affect eDNA recovery and ultimately false negative rates. In this study, we explored the efficiency of five different preservation strategies by using a controlled mesocosm experiment in which we included three fish communities of different composition. Specifically, we compared eDNA recovery in DNA extractions (a) performed immediately following collection, or after eight months storage from (b) frozen filters, (c) unfiltered water samples stored at −20°C, and filters preserved at room temperature with (d) Longmire and (e) Sarkosyl buffer. Effects of different preservation strategies were quantified using ddPCR measurements of three fish species (Neogobius melanostomus, Rutilus rutilus, and Lota lota) and total fish DNA content using group-specific primers for Teleostei. Samples extracted immediately following collection without any further preservation yielded significantly less DNA compared to the other approaches. Overall, Longmire's buffer facilitated the best eDNA recovery across all fish species although approaches such as filter freezing or the use of Sarkosyl buffer yielded similar recovery results. Relative measurement variability, an important indicator for reliable eDNA quantification, was lowest when using Longmire's and Sarkosyl buffers and generally decreased when increasing eDNA quantity. Overall, our results clearly highlight the significant impact of sample preservation and how this can substantially affect the performance and reliability of eDNA-based approaches.