Use of Droplet Digital PCR for Estimation of Fish Abundance and Biomass in Environmental DNA Surveys

<div><p>An environmental DNA (eDNA) analysis method has been recently developed to estimate the distribution of aquatic animals by quantifying the number of target DNA copies with quantitative real-time PCR (qPCR). A new quantitative PCR technology, droplet digital PCR (ddPCR), partitions PCR reactions into thousands of droplets and detects the amplification in each droplet, thereby allowing direct quantification of target DNA. We evaluated the quantification accuracy of qPCR and ddPCR to estimate species abundance and biomass by using eDNA in mesocosm experiments involving different numbers of common carp. We found that ddPCR quantified the concentration of carp eDNA along with carp abundance and biomass more accurately than qPCR, especially at low eDNA concentrations. In addition, errors in the analysis were smaller in ddPCR than in qPCR. Thus, ddPCR is better suited to measure eDNA concentration in water, and it provides more accurate results for the abundance and biomass of the target species than qPCR. We also found that the relationship between carp abundance and eDNA concentration was stronger than that between biomass and eDNA by using both ddPCR and qPCR; this suggests that abundance can be better estimated by the analysis of eDNA for species with fewer variations in body mass.</p></div

Relationships between eDNA concentrations of common carp in mesocosms that were measured using qPCR and ddPCR.

<p>Black, red, and green symbols indicate samples collected on days 1, 2, and 3, respectively. Solid red and dashed red lines indicate Type II regression and 95% CI, respectively.</p

Relationships between eDNA concentrations of common carp and their biomass in the mesocosm experiment.

<p>Black, red, and green symbols indicate samples collected on days 1, 2, and 3, respectively. Solid red and dashed red lines indicate Type II regression and 95% CI, respectively.</p

Droplet Digital Polymerase Chain Reaction (PCR) Outperforms Real-Time PCR in the Detection of Environmental DNA from an Invasive Fish Species

Environmental DNA (eDNA) has been used to investigate species distributions in aquatic ecosystems. Most of these studies use real-time polymerase chain reaction (PCR) to detect eDNA in water; however, PCR amplification is often inhibited by the presence of organic and inorganic matter. In droplet digital PCR (ddPCR), the sample is partitioned into thousands of nanoliter droplets, and PCR inhibition may be reduced by the detection of the end-point of PCR amplification in each droplet, independent of the amplification efficiency. In addition, real-time PCR reagents can affect PCR amplification and consequently alter detection rates. We compared the effectiveness of ddPCR and real-time PCR using two different PCR reagents for the detection of the eDNA from invasive bluegill sunfish, Lepomis macrochirus, in ponds. We found that ddPCR had higher detection rates of bluegill eDNA in pond water than real-time PCR with either of the PCR reagents, especially at low DNA concentrations. Limits of DNA detection, which were tested by spiking the bluegill DNA to DNA extracts from the ponds containing natural inhibitors, found that ddPCR had higher detection rate than real-time PCR. Our results suggest that ddPCR is more resistant to the presence of PCR inhibitors in field samples than real-time PCR. Thus, ddPCR outperforms real-time PCR methods for detecting eDNA to document species distributions in natural habitats, especially in habitats with high concentrations of PCR inhibitors

Relationships between eDNA concentrations of common carp and their abundance in the mesocosm experiment.

<p>Black, red, and green symbols indicate samples collected on days 1, 2, and 3, respectively. Solid red and dashed red lines indicate Type II regression and 95% CI, respectively.</p

Relationships between eDNA concentrations of common carp and coefficients of variation (CV, %) measured using qPCR and ddPCR.

<p>Solid red and dashed red lines indicate Type II regression and 95% CI, respectively. Boxes in the box plot indicate median ± quartiles, and points indicate the outliers. The means of CVs were significantly different by Welch’s t-test (t = –2.98, p = 0.0047).</p