A lot of things come out with fecals. Not only is their DNA from animals ate and the animals themselves, but also DNA from parasites that infect the animals. Common parasites in the digestive system include nematodes, trematodes, and cestodes. Traditional techniques for parasite assessment have been to look for eggs in the fecals. But this work requires experts (which can mean expensive, slow, inexact) and cannot always differentiate closely related species. Sequencing DNA in fecals also has the potential to identify parasites. For one client, we used 18S sequencing to look for parasites in their birds. To begin, voucher specimens sequenced well. When we looked at DNA in fecals, animals identified as having parasites visually also tested positive using DNA sequencing. One thing we did learn is that for 95% accuracy in testing for the presence of parasites, multiple replicates need to be run (using our standard approach of swabbing the fecal). Still, for those interested in whether their animals might be infected with parasites in the digestive system, this is a simple test to add.
The technique of assessing the relative abundance of different organisms is one of the strengths of next generation sequencing. For one recent project, we assessed the relative abundance of different fish species across a number of streams in Nebraska by amplifying a region of the mitochondria that is more or less specific to fish. When the percentage data are aggregated, you get a graph something like below. We still have some more work to do to see how well the relative abundance of different fish species is represented by the data below, but the technique identifies a number of the more prevalent taxa found in the streams. We should be introducing a new product for fish eDNA pretty soon as we work out the final details. Stay tuned.
Jonah Ventures is currently working with Cameron Thrash at Louisiana State University to quantify the organisms of the Mississippi River using eDNA. The project is an amazing effort on the part of volunteers that have rowed the entire length of the Mississippi, collecting water samples as they go. Our contribution is to analyze the DNA in the samples for higher organisms such as phytoplankton, insects, and fish.
Something like this has never been done before. Our preliminary results have been encouraging. Analyzing the DNA in the samples, we’ve been able to reconstruct the phytoplankton community along 3000 km of river. Below is the abundance of just one taxa, Skeletonema marinoi (and/or related species), which is a diatom that apparently is more abundant in the larger portions of the river, especially below the confluence with the Missouri.
Skeletonema looks something like this:
Normally, if one wanted to determine its abundance, one would have to take a water sample, filter it, and then examine the contents under a light microscope, counting each shape that resembled something like the SEM above.
Using eDNA, we can do the same counting likely better (because we’re also counting all the green algae and cyanobacteria as we go) and a lot faster.
We’re working on publishing the phytoplankton data and should be acquiring data on insects and fish soon.
Phytoplankton–organisms such as cyanobacteria, green algae, and diatoms–are good indicators of water quality. The problem is that they are tiny and you need a microscope–and a lot of training–to identify them.
Good news is that all of the organisms have unique DNA and are pretty abundant in waters, which means we can sequence them.
We’re still in testing phase for phytoplankton, but are settling in on an approach that will rapidly allow us to quantify phytoplankton assemblages.
Using a plastid marker, we ran some tests on assorted samples we had collected. Some were from a reservoir in Colorado, a few were from a backyard koi point, and others were from rivers and ponds in Kansas.
The plastid marker we were using separated out the waters well.
CO reservoirs are ID’d by their Cyanobacteria. My koi pond by green algae and dinoflagellates. KS waters by their diatoms.
We’ve tested these out with other streams and feel they are working pretty well here, too.
We still have more testing to do, but we’ll likely be ready to offer phytoplankton testing soon.
Jonah Ventures is proud to announce that we will be assisting Sitting Bull College in research on bison diet and performance. The research, funded by the USDA, represents a collaboration among three Tribal Colleges: Little Big Horn (Montana, Crow Nation), Sinte Gleska (South Dakota, Lakota Nation), and Sitting Bull (North Dakota, Lakota/Dakota Nation). The goal of the research is to gain new knowledge of how to strengthen the health of bison and be able to care for them under new conditions. Jonah Ventures will assist in a number of aspects of the research, including analyses of bison diet and performance. Stay tuned for updates on this exciting project.
I remember the famous limnologist G. Evelyn Hutchinson was once mocked as supposedly believing that he could determine all there was to know about a lake simply by sticking one, perhaps two, fingers in a lake.
I am not sure how many fingers it would take, but with environmental DNA one can convince themselves that we are getting pretty close with just a few fingers worth of water.
Almost everything that touches a stream or lake should leave some DNA behind. We tested that a bit with some filtered stream samples from Nebraska taken by NE DEQ. Across a wide range of streams in eastern Nebraska, we amplified vertebrate DNA (here fishes and mammals) to see what animals were leave DNA signatures behind.
Turns out a lot.
On the mammal side, a lot of human DNA, which might be from handling the samples, but also cattle, skunk, muskrat, beaver, deer and mice.
On the fish side, we found about 20 species of fish, including long nose gar, common carp, silver carp (!), fathead minnow, quillback, longnose sucker, and spotfin shiner.
Keys to using eDNA for vertebrates is a combination of choosing the right primer and getting enough sequencing depth to capture as much of the assemblage as possible. These data were pulled from ~300,000 reads across ~25 sites. Doing it right will likely take at least an order of magnitude more sequencing depth.
Still, it’s encouraging to see so many species in our data.
We’re continuing to work on the issue, so stay tuned…
One power of reconstructing diets with sequencing is to know what an animal had recently ate. Even more powerful is reconstructing diets for a large number of animals to infer how diets change over space or time.
In the global change world, it is an open question about how warming will affect the diets of animals. To test this, we worked with Texas A&M’s GANLab to sequence the fecals of cattle across the central US.
Geographic trends in individual OTUs were evident. For example, species like the cool-season grass Bromus were dominant in the northern grasslands.
When we put all the data together, it was clear that northern cattle relied more on grasses than southern cattle. Cattle in southern, warmer sites typically consumed a greater proportion of forbs and woody species in their diet.
The paper also showed that certain species were indicative of low-quality diets, which could benefit ranchers in improving the nutrition of their cattle.
The inference from this work is that warming favors consumption of non-grasses. Why this is was beyond the scope of this particular project, but even being able to reconstruct the diet of any species across such a large geographic gradient is a major advance in and of itself.
Recent work by Noah Fierer and others (Craine et al. in press Aerobiologia) examined the distributions of plant DNA in dust inside and outside homes across the US. They sequenced of a chloroplast marker gene to identify the plant DNA found in settled dust collected on indoor and outdoor surfaces across 459 homes. The reported research shows a few interesting patterns. First, there were broad geographic patterns of plant DNA across the US. For example, the Pacific Northwest could be uniquely identified from the DNA of trees and mosses found in homes there. Second, environmental plant DNA signatures were similar inside and outside homes, but some taxa (largely food species) were more abundant inside than outside. There was also little pattern to the prevalence of DNA from plant species that are known to be have allergenic pollen.
In all, the work shows that sequencing dust for plant DNA can provide forensic information and yield information useful to the health sector.
Here at Jonah Ventures, we can analyze the composition of DNA in dust for a number of purposes. The composition of DNA from plants, insects, and fungi can all be quantified from a simple swab of a surface.
Just a quick note here. We had run some tests on mixtures of plants to see how representative our DNA data are of the relative proportions of the biomass of different three species that were mixed together.
We put together 10 mixtures of leaves of 4 plant species. 2 were alfalfa, 1 was lotus, 1 was Onobrychis. Mixtures were either 50-50 or 90-10.
We then compared the expected % of mixture with actual % of reads from each species.
In short, about 85% of variation in actual % of reads could be explained by % in mixture and the species identity. Those plants that were higher in the mixture were higher in the reads. Alfalfa read a higher percentage than was expected, but this is likely due to higher protein concentrations than the other species.
We could do more sophisticated analyses and other tests (results from feeding trials are forthcoming), but this is a pretty good start. It supports the idea that the relative percentage of reads should indicate relative intake of protein of different plant species.
We recently had a request to sequence the diets of granivorous birds.
This time, instead of fecals, we’d get crop samples. Grinding up tiny seeds can be difficult. Mortar and pestles are tough to use and have the risk of contamination.
We started using disposable tubes with disposable steel beads to grind the samples. This goes in the bead beater and 5 minutes later, voila. Perfect for DNA extraction.