Many things can negatively affect stream ecosystems – water abstraction, eutrophication and fine sediment influx are just a few. However, only intact freshwater ecosystems can sustainably deliver the ecosystem services – such as particle filtration, food biomass production and the supply of drinking water – that we rely on. Because of this, stream management and restoration has often been in the focus of environmental legislation world-wide. Macrozoobenthic communities are often key biological components of stream ecosystems. As many taxa within these communities are sensitive to negative stressors introduced by humans, they’re ideal for assessing the quality of water.
Unfortunately, most macrozoobenthic taxa – such as stone-, may-, and caddisflies as well as most other invertebrates – are often found in juvenile larval life stages in these ecosystems, so they’re often difficult to identify based on morphology. With the DNA based metabarcoding method though, almost all taxa in a stream can be reliably identified up to species level using a standardised gene fragment. One key component of this strategy is the development of universal markers, which allow detection of the diverse macrozoobenthic groups.
Our new R package PrimerMiner provides a framework for obtaining sequence data from available reference databases and identifying suitable primer binding sites for marker amplification. The package makes this process quicker and easier. In the following pictures, we summarise the key steps of DNA metabarcoding.
Rivers are home to a wide range of macroinvertebrate species. These are often used to assess water quality as many respond sensitively to anthropogenic stressors, like organic pollution, eutrophication or fine sediment influx.
One macroinvertebrate sample can contain hundreds or even thousands of specimens.
Invertebrates are collected using standardised field sampling protocols and usually identified based on their morphology. The taxa lists obtained this way are then used to assess stream water quality based on associated bioindication values of the individual taxa. But identifying juvenile invertebrates by morphology isn’t possible for all collected taxa.
DNA based identification is a promising alternative to morphology based identification. Whole bulk samples with hundreds of organisms can be identified at once – often to species level – which can improve the accuracy of assessments.
All specimens in the sample have to be well homogenised for DNA extraction before we can move on to DNA metabarcoding. The specimens are easier to homogenise if they are dried first.
The dried samples are mechanically homogenised using a bead mill and sterile tubes (which are only used once).
After 30 minutes of grinding, all specimens are homogenised to fine powder, which can then used for DNA extraction.
The homogenized macroinvertebrate tissue is incubated in digestion buffer (a solution that dissolves cell membranes) to enable DNA extraction. Only a few mg (~10 – 20 mg) of the homogenate is used for DNA extraction, as the efficiency decreases when too much tissue is extracted at once.
We used the R package PrimerMiner to obtain sequences for the 15 most important freshwater invertebrates from reference databases. Edith Vamos and I are screening the sequence alignment for suitable primer binding sites in this picture.
The developed primers are tested and PCR optimised using both mock samples and complete communities.
After successful marker amplification, several uniquely tagged samples are pooled and then sent to an external service provider for high throughput sequencing. The sequences are then bioinformatically processed and compared to reference databases. These precisely identify the taxa in each sample and connect bioindication values to taxa lists and stream types.
To find out more about PrimerMiner, read our Methods in Ecology and Evolution article ‘PrimerMiner: an r package for development and in silico validation of DNA metabarcoding primers’. Like all Applications articles, this paper is freely available to everyone.