Metabarcodingof eDNAfrom Suspended Particulate Matter (SPM ...
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Metabarcoding of eDNA from Suspended Particulate
Matter (SPM) for fish population monitoring Franziska-Frederike Wege1, Cecilia Andrea Diaz Navarrete1, Gisela Böhle1, Manfred Kohler2, Matthias Teigeler1, Christoph Schäfers1, Heinz Rüdel1, Elke Eilebrecht1, Jan Koschorreck3
1Fraunhofer IME, Applied Ecology, Auf dem Aberg 1, 57392 Schmallenberg, Germany2Fraunhofer IME ScreeningPort, Schnackenburgallee 114, 22525 Hamburg, Germany3German Environment Agency (UBA), Bismarckplatz 1, 14193 Berlin, Germany
Introduction
Conventional biomonitoring of fish species in aquatic environments is time
consuming, hard to standardize and taxonomic expertise is needed for
species identification. Sampling of so called environmental DNA (eDNA)
allows for non-invasive species determination and measurement of their
DNA abundance. Species detection using eDNA has the potential to
overcome the problems of conventional methods.
In this study we aim to establish a methodology to monitor fish
populations, from suspended particulate matter (SPM) from river samples,
using eDNA barcoding/metabarcoding.
Methods
For testing the method, a control sample was prepared mixing DNA (at
equal concentration) of 5 different fish species (Roach, Bream, Chub, Perch
and Pike). For metabarcoding analysis, DNA was extracted from suspended
particulate matter (SPM), which was sampled at 3 different riverine
sampling points in Germany (retrieved from the German Environmental
Specimen Bank). The metabarcoding results were compared with
electrofishing results obtained from 3 points near the SPM sampling
points (Figure 1). The year of sampling was different though.
The workflow for the Next Generation Sequencing (NGS) method
development is described in Figure 2.
Figure 1. Suspended particulate matter (SPM) sampling poin ts (A) and sections of theriver for the electrofishing comparison points (B)
Conclusion and remarks
The applicability of a metabarcoding approach using eDNA extracted from suspended particulate matter is confirmed and used for the first time in this
project. The methodology permits differentiation at least to the level of the subfamily. However, it has been found that, with the primers used, firstly a PCR
bias is produced (compare different "read" numbers in the positive control despite the identical quantity of DNA used) and secondly not all species have been
detected . Further steps are now to be made to optimize the method developed here. To this end, new primers are to be designed which bind in an ideal
manner to more species and additionally amplify a larger fragment of the COI gene in order to increase the specificity. The optimized approach is to be tested
in the following applications: plausibility (comparison with conventional monitoring methods), estimation of abundances based on the eDNA, retrospective
consideration of the development of fish populations and extension of the reference library to the possible identification of non-fish species.
Figure 2. Workflow for the development of a metabarcoding ap proach for fish monitoring
The metabarcoding showed successful and specific identification of fish
species with the designed primers. The comparison with electrofishing
results showed only partial agreement between the species found (Figure
3). On the other hand, the metabarcoding approach also identified species
that were not detected by electrofishing. However, due to the lack of
actual data from the electric water supply at the Saar in Güdingen and the
Danube River in Ulm, the generated NGS data were compared with a fish
inventory from 2003. Therefore the fish populations can change
considerably during this period.
Table 1. Fish species identified with NGS in the control samp le
Results and Discussion
The DNA extraction method from SPM, which resulted in better extraction
yield and purity (Absorvance 260/280 ratio near 2), was using the
PowerSoil DNA isolation kit (MoBio).
The method allowed the identification of five fish species in the spiked
control SPM sample. However, one species was missasigned -
presumably due to the sequence homology of the closely related species.
In addition, the number of "reads" varied by a factor of 100. This different
"read" number is presumably due to a PCR bias (different affinity of the
primers for a DNA fragment) (Table 1).
a)
b)
c)
Figure 3. Venn Diagram of the fish species detected with Elec trofishing (Red) and ,Metabarcoding (Green) from a) Koblenz (Rhine); b) Güdingen (Saar); c) Ulm (Danube)
1. DNA extraction from SPM
- CTAB
- MoBio Power Soil Kit
- Filtration
2. PCR optimization
- Primer design for different conserved regions (genes: COI,
CytB, 12S)
- Protocol development for amplification of the COI region
with NGS using the Ion Torrent Technologie
- Fragment size: 150 bp approx.
4. Data processing and analysis
- Generation of a fish reference database (types and types),
which are defined in the European Water Framework
Directive
- Data generation on the Ion Torrent system
- Development of a processing pipeline
3. NGS at the Ion Torrent Platform
- Generation of a NGS library based on
the amplified products
- Sequencing
Spiked fish species Identified fish species N° of reads
Rutilus rutilus (Roach) Rutilus rutilus (Roach) 8220
Perca fluviatilis (Perch) Perca fluviatilis (Perch) 5255
Squalius cephalus (Chub)Ballerus sapa (White-eye
bream) 2077
Abramis brama (Bream) Abramis brama (Bream) 464
Esox lacius (Pike) Esox lacius (Pike) 34