Environmental DNA: An Emerging Tool for Understanding Aquatic Biodiversity

Trey Simmons, National Park Service
Damian Menning and Sandra Talbot, US Geological Survey

All organisms shed DNA into the environment. Using the right analysis tools, environmental DNA (eDNA) can be used to determine the identities of the species that were present at the time of sample collection.

IMAGE COURTESY OF FISHBIO

Field surveys for aquatic organisms provide critical information that is important for robust resource management. However, such surveys are expensive and labor intensive, particularly in large, remote landscapes like those that characterize much of Alaska. Traditionally, characterizing aquatic biodiversity necessitated the physical capture and identification of individual organisms, which required that field crews have some level of expertise in identifying the species likely to be present. Many other limitations of surveys that rely on direct observation of aquatic organisms have been noted (Evans and Lamberti 2018). However, what if it were possible to identify all of the species present at a site without having to capture or even see them? While we are not there yet, the recent revolution in environmental DNA (eDNA) technology is bringing us closer to that goal (Thomsen and Willerslev 2014).

Analysis of eDNA using sophisticated genetic techniques holds the promise of being able to identify unseen species from material collected in water samples. The National Park Service, along with other agencies and researchers in Alaska, is actively developing eDNA-based methods for the identification of fish and other aquatic organisms, including both native and potentially invasive species. The objectives of this effort include improving long-term monitoring of fish and other aquatic species and early detection of aquatic invasive species.

The term environmental DNA refers to DNA that organisms shed into the environment. Sources of eDNA can include shed skin cells, feces, hair, and reproductive secretions. In terrestrial ecosystems, eDNA generally ends up in the soil. However, in aquatic ecosystems, eDNA can be present at relatively high densities in both the bottom sediments and in the water itself (e.g., Barnes and Turner 2016). This eDNA can be easily recovered from the water column either by filtration, centrifugation, or precipitation, and preserved for later analysis in the laboratory (Goldberg et al. 2016). Generally, multiple water samples, ranging in volume from about 8-34 ounces (250 mL to 1 liter), are collected from a site and then filtered and prepared for analysis in the laboratory.

Collection of an eDNA sample from a stream. On-site filtration using peristaltic pumps is a common method (note the blue filter unit visible at the end of the intake tubing in the upper left).

IMAGE COURTESY OF US FOREST SERVICE ROCKY MOUNTAIN RESEARCH STATION

The quantity of recoverable eDNA present in a lake or stream is a product of many factors that can influence its generation and degradation (Barnes and Turner 2016). The density of organisms is important as species present in large numbers tend to generate more eDNA than species that are rare and there is evidence that the quantity of recovered eDNA may be related to species biomass (e.g., Evans and Lamberti 2018). Environmental factors also play a role by affecting the persistence of eDNA over time, influencing the quantity of eDNA that can be successfully recovered. For example, ultraviolet light rapidly degrades DNA, so eDNA will disappear more quickly in systems subject to considerable exposure to sunlight relative to those protected from sunlight. Other major agents of degradation for aquatic eDNA include microbes and extracellular enzymes in the water. Because temperature affects microbial metabolism and enzyme activity, eDNA tends to degrade faster in warmer temperatures. Other factors such as pH, salinity, and oxygen levels also likely influence degradation rates. Although the extent to which life history stage or species-specific differences play a role in the generation or persistence of eDNA is unclear, such differences may also influence detectability. Finally, the persistence and detectability of eDNA is affected by the hydrology of the system. In streams and rivers, eDNA is rapidly transported downstream, but also persists in sediments from where it can be periodically resuspended. In lakes, recoverability of eDNA likely depends on drivers such as the presence or absence of inflows and outflows, currents, lake stratification, and the turnover time of water in the lake (how long, on average, the water remains in the lake). Synergistically, these factors may result in significant differences in the detectability of aquatic species using eDNA. Many researchers are currently focused on addressing how these differences may influence the conclusions we are able to draw from eDNA studies, but much work remains to be done (Barnes and Turner 2016, Goldberg et al. 2016).

There are two main approaches to the analysis of eDNA recovered from environmental samples. Most often, eDNA is used to detect the presence of individual species of interest, such as invasive or rare and endangered species (Barnes and Turner 2016). A technology called quantitative polymerase chain reaction (qPCR) is a powerful way to determine whether eDNA corresponding to a particular target species is present. In qPCR analyses, researchers look, typically in the genomes of intracellular organelles like mitochondria or chloroplasts, for short stretches of DNA with nucleotide sequences unique to the target species. Mitochondrial DNA is generally the focus of eDNA studies involving animal species, since animal cells contain many more copies of it than of nuclear DNA (a single cell may contain several hundred mitochondria) and it may be more resistant to degradation. These unique sequences are targeted in qPCR reactions to make millions of copies of the DNA (this is called amplification), which can be detected, indicating that eDNA from the target species is present in the sample. If there is no eDNA in the sample that contains these species-specific sequences, then no detectable copies will be created. This method is generally precise and sensitive, but because a separate test must be used for each species, it is best suited for the detection of no more than three or four species.

The other commonly used method, designed to simultaneously detect many species in the same test from the same environmental sample, is referred to as metabarcoding. For animal species, metabarcoding typically involves an initial PCR amplification of mitochondrial DNA, but is otherwise quite different from qPCR analyses. Briefly, target gene(s) specific to particular groups of species (e.g., salmonid fishes) are amplified from the eDNA mixture, using group-specific DNA sequences. The amplified products are pooled into what is referred to as a library. This library is then compared, using advanced DNA sequencing technology, to a reference library composed of many sequences derived from species of known identity. If a sequence obtained from the eDNA sample matches that from a known species in the reference library, either exactly or above a threshold of similarity (generally 98-99%), a hit is recorded, indicating that the species’ DNA was present in the original sample. While metabarcoding provides an efficient way to describe biodiversity, one of the challenges in developing metabarcoding tests is properly accounting for the DNA sequence differences that exist between individuals within a species and how that compares to the differences that exist between different species. That is, the target DNA sequences should vary among species to facilitate accurate species identification, but if within-species genetic diversity is not accounted for in the test design, problems can arise. For example, if the sequence similarity threshold is set too stringently, then small sequence differences within a species may lead to a failure to detect that species even when it is, in fact, present. On the other hand, if the threshold is set too loosely, then a closely related species may be mistakenly identified when it is not present.

Using eDNA to Conduct Fisheries Surveys

The National Park Service has been collaborating with the US Geological Survey Alaska Science Center to develop several metabarcoding tests aimed at assessing aquatic communities, including the detection of invasive species. The first of these was designed to detect any of 37 freshwater and anadromous fish species known to occur in Alaska (Menning et al. 2020). The goal of the research was to allow freshwater fish surveys to be conducted using analysis of eDNA collected in water samples, rather than relying on traditional capture-based surveys, which are expensive and labor intensive, and therefore impractical for the collection of comprehensive fish community data across our large and remote parklands. As described in Menning et al. (2020), we used a set of genetic markers from the mitochondrial 12S ribosomal RNA and cytochrome oxidase I (COI) genes to develop the test. Targeting multiple genetic markers is important for reducing the chance of spurious detections or false positives. We validated this method using eDNA samples obtained from a number of lakes and rivers where the expected fish species composition was known, based on the results of traditional capture-based fish surveys. The sites were located in both Denali National Park and Preserve and Wrangell-St. Elias National Park and Preserve, as well as on the North Slope of Alaska. A second validation step involved tests of eDNA from aquarium samples with a known fish community. The results showed that, in most cases, this method accurately identified all of the species known to be present in a system. In the aquarium sample, we identified 100% of species known to be present. Across all national park and North Slope sites, we detected nearly 90% of the species expected to be present. In addition, at many sites we detected additional species that had not been captured using capture-based surveys. This finding is consistent with other studies that have found eDNA can be more sensitive than capture-based surveys in detection of fish species (reviewed in Evans and Lamberti 2018). Based on these initial experiments, we recently developed additional genetic markers to improve discrimination among some sets of closely related species (sculpin, Cottus spp.; char, Salvelinus spp.; whitefish, Coregonus spp.; salmon and trout, Oncorhynchus spp.) that can be difficult to distinguish genetically. We have also successfully applied this test to determine the fish species composition of loon diets in Bering Land Bridge National Preserve and Cape Krusenstern National Monument by analyzing eDNA isolated from loon feces (Menning et al. in prep).

Using eDNA for Early Detection of Invasive Species

A second collaborative metabarcoding project is designed to detect the presence of multiple aquatic invasive species (AIS). AIS are an enormous and growing problem in much of the world, with significant negative effects on native species, aquatic ecosystems and infrastructure (Pejchar and Mooney 2009, Gallardo et al. 2015). Alaska, however, is (so far) relatively free of AIS, providing a unique opportunity to limit the negative impacts of invasions. A cornerstone of effective invasive species management is early detection (Lodge et al. 2006); however, detection of invasive species when they are still rare is extremely challenging using traditional surveys that rely on capture or observation, especially across large remote landscapes. The sensitivity of eDNA-based methods suggests that they are well-suited for implementation of a robust early detection system, and there are multiple examples of the use of qPCR for the detection of individual AIS (reviewed in Barnes and Turner 2016). A metabarcoding approach has the advantage that we can test simultaneously for the presence of a large number of potential AIS, which is important since it is unclear, with a few exceptions, which species are expected to appear first in Alaska. Based on consultation with staff from state and federal agencies, we have prioritized a list of 18 species for inclusion in this test (Table 1). We are targeting numerous genes for detection and are including multiple markers for each species to minimize the chance of false positives. For plants, our metabarcoding approach targets multiple genes in the chloroplast genome. For the other species on the list, we are targeting a set of mitochondrial and nuclear ribosomal RNA genes, in addition to the mitochondrial COI and cytochrome b genes.

Table 1. List of invasive and potentially invasive species that are targets of the National Park Service eDNA assay.

Common Name	Scientific Name	Current Status
American waterweed	Elodea canadensis	Present and spreading
Nuttall’s waterweed	Elodea nuttalli	Present and spreading
Northern pike	Esox lucius	Present and invasive south of the Alaska Range, spreading?
Red swamp crayfish	Procamborus clarkia	Present, reproduction documented
Northern Pacific tree frog	Pseudacris regilla	Present, reproduction documented
Northern red-legged frog	Rana aurora	Present, reproduction documented
Chytrid fungus	Batrachochytrium dendrobatidis	Present as of 2008, status unclear
Atlantic salmon	Salmo salar	Occassionally detected
American shad	Alosa sapidissima	Rarely detected
Purple loosestrife	Lythrum salicaria	Was present, eradicated?
New Zealand mud snail	Potamopyrgus antipodarum	Not yet documented
Quagga mussel	Dreissena bugensis	Not yet documented
Zebra mussel	Dreissena polymorpha	Not yet documented
Signal crayfish	Pacifasticus leniusculus	Not yet documented
Whirling disease parasite	Myxobolus cerebralis	Not yet documented
Chinese mittencrab	Eriocheir sinensis	Not yet documented
Spiny waterflea	Bythotrephes longimanus	Not yet documented
Brazilian waterweed	Egeria densa	Not yet documented

The initial stages of this project focus on the detection of Elodea spp., a highly invasive aquatic plant that has recently begun to spread to multiple water bodies in Alaska (Larsen et al. this issue). Replicate eDNA samples were collected from two locations where Elodea was present (Chena Slough and Tokchaket Slough), as well as from 52 lakes in four national parks and one national wildlife refuge sampled in 2016 and 2017 that comprise part of an extensive and ongoing field survey for Elodea being conducted in lakes thought to be at high risk for Elodea infestation. Vouchered specimens representing both Elodea species known to be present in Alaska were also analyzed to ensure that species detection was accurate. Our test detected Elodea in both locations where it is known to be present, although the signal strength was low, suggesting that eDNA concentrations were also low. In particular, although Tokchaket Slough is extensively infested with Elodea, the eDNA test resulted in marginal detection in the samples collected there; only one of four replicates met the criterion for detection (two additional replicates were also positive, but below the detection threshold). This result may be because the eDNA samples were collected nearly a mile downstream of the infestation, where already low Elodea eDNA concentrations may have been further diluted and/or degraded. Some other recent studies also suggest that eDNA-based methods may be less sensitive for plants than for animals, probably as a result of lower eDNA concentrations (Anglès d’Auriac et al. 2019, Kuehne et al. in review). No Elodea was detected, either by traditional physical surveys or using eDNA, at any of the 52 lakes.

Ongoing experiments being conducted by the US Fish and Wildlife Service should shed light on how proximity of sample collection to Elodea plants affects its detectability in eDNA tests, which may influence how negative results are interpreted. The next phase in the AIS detection project, conducted in collaboration with the US Forest Service, involves field validation of our ability to detect two exotic amphibian species in southeast Alaska (northern Pacific tree frog, Pseudacris regilla and northern red-legged frog, Rana aurora) using eDNA. We plan to continue testing the detectability of additional species from the list in Table 2 in the near future. Once completed, this will allow for multiple potential AIS to be detected in a single test, allowing us to begin implementation of a robust early warning program for AIS in Alaska.

Future eDNA Surveys Expanded to Other Species

The third collaborative metabarcoding project is aimed at using these same methods for the detection of a wide variety of native aquatic species of interest, including native amphibians (6 species), birds (18 species), and mammals (5 species). This will provide a powerful tool to rapidly test for the presence of multiple species of potential interest, some of which are difficult or expensive to reliably detect using traditional field surveys. We have already determined that we can use this method to detect all 5 species of loons (Gavia spp.) present in Alaska from lake water samples. This project is still in its pilot stages.

In summary, eDNA is an emerging and powerful approach for detecting aquatic species and is already beginning to revolutionize aquatic science. The methods we have outlined here will allow us to simultaneously test waterbodies in Alaska national parklands for multiple native vertebrate species (fish, amphibians, mammals, and birds) as well as for nearly 20 potentially invasive species, using water samples that can be easily and rapidly collected. Because these are relatively new techniques, much work remains to optimize field and laboratory methods and to determine how species detectability and the potential for both false positive and false negative detections are affected by environmental and biological factors. However, the potential of eDNA-based methods to improve the characterization of aquatic biodiversity is enormous. This in turn will substantially enhance our capacity for understanding aquatic ecosystems in park landscapes and provide critical information for monitoring change.

Cite this article as:

Simmons, T., D. Menning, and S. Talbot 2020. Environmental DNA: An emerging tool for understanding aquatic biodiversity. Alaska Park Science 19(1): 34-41.

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