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About markus majaneva

Markus Majaneva is a post-doctoral fellow at the Institute of Natural History, NTNU University Museum. He has a strong interest in methodologies and in combining ecological, morphological and molecular information in his studies. His educational background is in aquatic protistan ecology and bioinformatics.

DNA based methods for detecting species from various environments have advanced quickly recently. Our EBAI project has been actively involved in this development. However, molecular monitoring methods have been employed mainly in detecting endangered or invasive species, and DNA metabarcoding of macroinvertebrate communities has focused on small-scale comparisons within single systems or countries. Therefore, researchers from the Nordic countries developed a project, SCANDNAnet, to allow testing DNA metabarcoding of macroinvertebrate communities on a large geographic scale and across countries.

From the SCANDNAnet webpage: «SCANDNAnet covers a geographically very large extent by using samples from the annual national monitoring programs of all Nordic countries. The novel advances made during this project can directly be put into use in the national monitoring programs of the Nordic countries and will have far reaching impact in Europe and beyond. Through intensive dialogue with relevant national and international stakeholders our results will help facilitate cost-effective, standardized DNA-based biomonitoring and create a significant societal impact by promoting reliable future aquatic ecosystem status and service management»

In total, SCANDNAnet has 305 samples, of which 50 samples are from Sweden, 48 from Finland, 139 from Norway, 8 from Iceland, and 60 samples are from Denmark. Currently, these samples are dried and homogenized at the NTNU University Museum. After homogenizing, DNA will be extracted from the samples, and a fragment of the barcoding gene COI will be amplified, using primers BF2 and BR2 (Elbrecht and Leese 2017). The samples will be sequenced, using Illumina HiSeq system. This study scales up the study of Elbrecht et al. (2017) that showed very promising results, using Finnish stream monitoring samples.


Participating institutes:


Finnish Environment Institute SYKE - SCANDNAnet, Finland

Swedish University of Agricultural Sciences, Sweden

NTNU University Museum, Department of Natural History, Norway

Norwegian Institute for Nature Research (NINA), Norway

Norwegian Institute for Water Research (NIVA), Norway

Marine and Freshwater Research Institute, Iceland

Aarhus University, Denmark

University of Duisburg Essen, Germany

University of Guelph, Canada

In sparsely populated countries, many freshwater systems are fairly remote and reachable only by, for example, walking (Fig.1). Therefore, acquiring information about the biological status of these remote systems may pose a challenge if sampling requires carrying a lot of sampling equipment to the site and a lot of sample material back to the lab. This has been the case for traditional monitoring of freshwater invertebrate communities, which is based on extensive sampling of the bottom fauna and storing the collected specimens in ethanol.

Fig. 1. Torbjørn and Markus walking to a sampling site in the Rondane National Park, Central Norway. Photo: Elisabeth Stur cc-by.

The EBAI project will develop and test new ways of monitoring freshwater invertebrates, and we identify species in environmental samples using short, standardized DNA fragments, so called environmental barcoding. By introducing this cost-effective, rapid and repeatable technique in nature management, monitoring may be expanded also to more remote locations.

One way of doing environmental barcoding is to sample DNA that animals shed to their environment, in water in our case. This environmental DNA (eDNA) can be collected to a filter from the sampled water and be extracted from the filter for downstream analyses. Usually, investigators have carried the sampled water to their laboratory for filtration, but carrying liters of water from remote locations is not practical. Thus, we tested if we could carry some filtration equipment to the field (Fig. 2), and do the filtration in the field (Fig. 3), and then carry just the filters to the lab. Filtering in the field allows more sampling in remote locations and therefore, gives more data for the assessments. The critical part in the in-field filtration approach is how to preserve the filters.

Fig. 2. For filtration in the field, we used an electrical vacuum pump and a manifold with three filter holder bases. We preserved the filters in microcentrifuge tubes or in sterile petri dishes. Photo: Torbjørn Ekrem cc-by.
Fig. 3. We used a car trunk as our filtration laboratory and a bensin-driven aggregate as a power supply for our pump. However, the water filtration is possible using a hand pump if a simpler way is preferred. Photo: Torbjørn Ekrem cc-by.

In our first experiment, we filtered 64 litres of water in the field and tested how different filtration techniques affect the eDNA-based invertebrate community results (Fig. 4).

We found out that mixed cellulose ester filters preserved either dry or in lysis buffer give the most consistent community composition (Fig. 5). Thus, we advocate filtering in the field, using mixed cellulose ester filters and preserving the filters either dry or in lysis buffer. You can find the results summarized in our recently published article:

Fig. 4. Experimental setup. Water samples were collected from two sites, the River Atna and the Lake Jonsvatn. One litre was filtered and eDNA captured onto 0.20-µm polyethersulfone (PES) or 0.45-µm mixed cellulose ester (CN) filters at the river site. At the lake site, eDNA was captured onto 0.45-µm CN filters either directly or after pre-filtration using 12-µm CN filters. Filters were stored in 99% ethanol (EtOH), silica gel (Dry), Qiagen lysis buffer ATL (Buffer) or kept cold (Ice) until DNA was extracted in the laboratory. 500 mL of molecular grade water was filtered and the filters stored with the respective methods as negative controls (B). Fig. 1 in Majaneva et al. 2018 Sci Rep 8: 4682.
Fig. 5. Similarity of community composition in River Atna (a,b) and in Lake Jonsvatn (c,d) samples. The solid line gives the mean similarity and the dashed lines give the 95% confidence intervals. If the 95 % confidence intervals overlap, there is no difference in the methods. The small letters denote significantly different groupings of treatments. Fig. 4 in Majaneva et al. 2018 Sci Rep 8: 4682.

One of the goals of the EBAI project is to distribute knowledge on DNA metabarcoding. We started with a small workshop with two students: Zhenhua Sun from Chalmers University, Sweden and Xiaolong Lin from NTNU University Museum. Our goal was to go through the steps of sample processing using own datasets.

To have a proper feeling on the methodology, we went to sample some water for eDNA analyses in Theissendammen. A suitable outfit for this kind of near-city sampling is a smart casual. (Photos Xiaolong Lin)

We expect to find mallard DNA in our samples. Also beaver is quite potential finding as Markus steps over a beaver dinner to go for the sample. (Photos Xiaolong Lin and Erik Boström)

We visited the molecular lab and Markus showed how to extract DNA and amplify your target gene in PCR as well as explained the paired-end sequencing. (Photos Xiaolong Lin)

Using our own laptops, we analyzed our data. (Photo Xiaolong Lin)

The second field-sampling trip in EBAI was directed to the Lake Jonsvatn on September 28. We sampled a depth gradient (0.25 m, 2 m, 7.5 m and 15 m) for benthic invertebrates starting from Trondhjems Roklub, and eDNA from water from the Roklub pier. Also, adult flying insects were sampled with a net. Weather conditions were perfect during the second successful field trip, and in addition to the samples, we got nice pictures including the spectacular panorama photo on top of the page.


Erik is sampling water from the pier. Photo: Torbjørn Ekrem.
Relaxing day in the field (at least for some of us). Photo: Elisabeth Stur.
Captain Hårsaker leaving the field site (we'll be back). Photo: Torbjørn Ekrem.

Field filtering requires some patience. Photo: Elisabeth Stur.