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