Knowl. Manag. Aquat. Ecosyst.
Number 424, 2023
Biological conservation, ecosystems restoration and ecological engineering
Article Number 17
Number of page(s) 11
Published online 14 June 2023

© B. Števove et al., Published by EDP Sciences 2023

Licence Creative CommonsThis is an Open Access article distributed under the terms of the Creative Commons Attribution License CC-BY-ND (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. If you remix, transform, or build upon the material, you may not distribute the modified material.

1 Introduction

Trophic interactions represent a very important topic, as well as a methodological challenge in ecological studies. In particular, the accurate identification of prey is a fundamental requirement in elucidating the food-web structure (Jo et al., 2014). In fishes, traditional approaches of diet analysis (dissected gut/stomach content analysis) suffer one serious weakness: difficulties to identify items in the gut content to species level, because the soft-bodied organisms are often digested beyond the possibility of visual recognition. The traditional approaches thus often fail to identify many diet items, which inevitably leads to loss of important information (Jo et al., 2016; Legler et al., 2010). Moreover, obtaining a sufficient number of fish samples for trophic studies is a problem, especially when considering endangered/protected species or small populations. As the abundance of native fish populations decreases, killing large numbers of fish for scientific purposes should be avoided whenever possible (Bammer et al., 2015).

Molecular methods of diet analysis appear more precise than traditional visual techniques, and they have become an important tool for studying feeding interactions (Carreon-Martinez et al., 2011; Sint et al., 2011). However, DNA degradation rates due to digestion, assay sensitivity and the ability to quantify the amount of individual components of the diet still pose major limitations to this approach (Deagle et al., 2013). On the other hand, these methods often provide a greater taxonomic resolution (more species identified) than the visual analyses of gut/stomach content and can also identify highly digested prey that have lost all physical characteristics (Carreon-Martinez et al., 2011; Guillerault et al., 2017; Smith et al., 2005). The dietary samples like regurgitates or faeces, which may be a very good source of information for molecular prey analyses, can be obtained non-lethally (Briem et al., 2018; Kamenova et al., 2018; Oehm et al., 2016; Thalinger et al., 2016). For example, in fishes, gently squeezing the abdomen, i.e. lightly pressing the peritoneal cavity towards the rectum allows to obtain faeces samples with no harm to the examined specimen (Corse et al., 2010; Guillerault et al., 2017).

Despite all the advantages, potential contamination from the environment and from the body surface of the organism itself is a major challenge in molecular approaches of diet analysis. Field collected specimens may be externally contaminated by DNA from the environment they live in, therefore potentially contaminating and biasing the results of diet analysis (Briem et al., 2018; Greenstone et al., 2012). In fishes, the question is whether foreign DNA (contamination from the environment) can be captured on the surface of their bodies, which might lead to contamination of faeces samples directly from the fish‘s own skin mucus. In other organisms (e.g. insects), the external contamination can be removed using proper bleaching protocol, that is lethal to the sampled specimen (Briem et al., 2018). The problem comes when the examined organisms are not allowed to be sacrificed during the research. Although the fish skin mucus produces substances that can cause environmental DNA (eDNA) degradation, and it is constantly secreted and replaced (Alexander and Ingram, 1992; Nagashima et al., 2003 Guardiola et al., 2015; Kumari et al., 2019; Patel et al., 2020; Wang et al., 2019), the question whether eDNA can be captured on the fish skin mucus has never been answered satisfactorily. Thus, to reduce the risk of contamination when collecting faeces from fishes, it might be helpful to wipe out the mucus around their anus area.

In this study, we tested the hypothesis that eDNA (i.e. foreign DNA) is present on the fish skin mucus. For doing so we performed a laboratory experiment in which fish individuals were exposed to the target contaminant (eDNA). Molecular analyses were applied to find out whether the foreign DNA is detectable on mucus. Subsequently we tested whether the potential foreign DNA detection could be removed by repeated wiping of the fish mucus.

2 Material and methods

2.1 Experimental setup

The experiment was conducted in the fish laboratory with aquaria used for rearing fish only. The lab itself consists of two rooms, Room 1 was equipped with four experimental aquaria (214.5 l/aquarium, Ae, Be, Ce, De) and two additional aquaria (Ee, Fe). The Room 2 contained eight aquaria that served for rearing the experimental fish (Fig. 1). To remove possible DNA contamination, all aquaria in Room 1 were bleached (Sodium hypochlorite solution) and cleaned properly with tap water. Each aquarium was irradiated overnight using germicidal UVC lamp, and then filled with tap water, filtration was put on, and once again germicidal UVC radiation was used overnight in each aquarium. Similarly, every surface in the Room 1 was bleached and irradiated with germicidal UVC lamp for five nights before placing target contaminants in the experimental aquaria.

Common roach Rutilus rutilus (Linnaeus; n = 39) was used for this experiment. This species is listed as Least Concern in the IUCN Red list and it is one of the most common and abundant species in the Danube water bodies. The fish were collected from the northern drainage channel of the Gabčíkovo Hydroelectric Scheme (the River Danube, 47.9385N, 17.4483E), and reared subsequently in aquaria for more than one year. Such acclimatized fish tolerated handling very well and did not show signs of stress.

Throughout the whole study, the standards set for fish rearing in laboratory conditions according to Directive 2010/63/EU of the European Parliament and of the Council of 22 September 2010 on the protection of animals used for scientific purposes were followed carefully. After the experiment, the fish were carefully released back to their natural environment.

thumbnail Fig. 1

Schema of the fish laboratory and experimental procedure. The fish laboratory consists of two separate rooms − Room 1 (experimental room) and Room 2 (rearing room). Aquaria in both rooms were placed on stands. Abbreviations: Ae, Be, Ce, De − experimental aquaria; Ee − negative control aquarium and the control of the fish survival; Fe − control of the fish survival; G, H, I, J, K, L, M, N − aquaria for rearing the fish (Room 2).

2.2 Experimental procedure

To simulate the macrozoobenthos contamination, i.e. the presence of macrozoobenthos eDNA in aquaria, individuals of Dugesia sp. and chironomid larvae (i.e. target macrozoobenthos) were used. These two groups were selected due to easy availability in large quantities, whether by direct sampling in the field (Dugesia sp.) or by purchase from external breeder (Chironomidae). To ensure a large amount of eDNA (from different types of organisms), uncontrolled algae contamination was also added at the beginning of the experiment (placed into the aquarium using a hose). Before the onset of the experiment, fishes in Room 2 were fed with dried granulated fish feed that contained no invertebrates to avoid bias contamination during experiment (SAK Mix, Exot Hobby s r.o.).

The experiment itself took place in four experimental aquaria (Ae, Be, Ce, De) and one negative control (Ee). Before the start of the experiment, 150 ml of water from each aquarium was filtered using a hand sampling vacuum pump (Schenchen pump SC600, flow rate: 0–2280 ml/min) and nitrate cellulose filters (Nalgene™ Single Use Analytical Filter Funnels, 0.2 μm pore size) to check for the contamination. The target macrozoobenthos was then placed into four experimental aquaria in the fish breeding boxes, to avoid predation from fish. In each of the four aquaria, the same amount of Dugesia sp. (29 g), as well as, chironomid larvae (59 g) was added. The water was filtered after 17, 41, 65, 89, 113 and 137 hours from each of the four experimental aquaria to check the overall DNA concentration (Fig. 1). To prepare suitable conditions in the experimental aquaria, approximately stable eDNA concentrations was necessary.

The negative control aquarium (Ee) was treated in the same way as the experimental aquaria, except for the insertion of target macrozoobenthos. Three fish individuals were placed in Ee aquarium for 3 days. Afterwards, the fish skin mucus was wiped with two consecutive smears. The smears were taken from the same body part in each fish, using a forensic swab (not performed around the anus to avoid contamination of samples by faeces). Before the onset of the experiment, the negative control aquarium (Ee) served to test, if the water samples and the skin mucus of fish from this aquarium did not contain target macrozoobenthos DNA. Afterwards, Ee and Fe aquaria served as the control of fish survival during experiment.

Subsequently, three fish individuals were placed in each of the four experimental aquaria. The time scale of exposure of fish to eDNA (macrozoobenthos and algae) was: 24, 48 and 72 h. Such a time scale was set to detect when the eDNA appears on the fish skin mucus for the first time. After 24 h, the fish skin mucus was wiped with two consecutive smears (the same procedure as for the fish from Ee aquarium, see above). The wiped fish were subsequently placed into the aquarium Ee, and new specimens were taken from Room 2 and placed into the four experimental aquaria for 48 h. The same procedure was applied after 72 hours (Fig. 1). The fish were not fed during the experiment (i.e. their 24, 48 and 72 h stay in the four experimental aquaria). Once placed in the Ee/Fe aquarium (now used as the control of the fish survival), fish were fed again.

All persons involved in the experiment (including molecular analysis) wore full body protective laboratory clothing and surgical gloves. All surfaces in the fish laboratory were cleaned with bleach and denatured ethanol several times a day. Also, the molecular laboratory was frequently cleaned with bleach and denatured ethanol, and irradiated with high-intense UV light for one hour every morning. Samples for molecular analysis were isolated separately and handled under sterile UV hoods.

To identify whether foreign DNA can be captured on the fish skin mucus, only the first smears with eDNA were taken into account. To find out if the foreign DNA can be removed by repeated wiping of the skin mucus, first smears, as well as the first and the second smears with eDNA were taken into consideration. The presence of foreign DNA on the second smear was considered additional contamination only. Molecular analyses of actual contamination of the fish faeces by the mucus were not performed.

2.3 Molecular analysis: DNA extraction

Using sterile tweezers, filters were transferred to DNA-free Eppendorf tubes (2 ml) containing 96% molecular grade ethanol. Fresh, TNES preserved smears (Forensics swab in transport tube with ventilation membrane, DNA-free) from the fish were cut into DNA-free Eppendorf tubes (1.5 ml). Before DNA extraction, the filters were dried overnight in sterile Petri dishes and ripped into small pieces using sterile tweezers. DNA was extracted from both types of samples (filters, smears) in a PCR-free laboratory using a modified salt extraction protocol (Sunnucks and Hales, 1996; Weiss and Leese, 2016) with an increased proteinase K digestion time of 12 hours. After extraction, DNA was treated with 1 μl of RNase A (10 mg/ml, Canvax Biotech) to 30 μl of eluted DNA solution. Afterwards, samples were cleaned using the Nucleospin® gel and PCR Clean-up kit (Macherey-Nagel).

2.4 Molecular analysis: Concentration/presence of eDNA in aquaria

Purity (260 nm/280 nm) and total DNA concentration (ng/μl) in aquaria were determined by optical density spectrophotometry (BioDrop® Touch Duo Spectrophotometer) and quantified by using Qubit™ 4 Fluorometer (Thermo Fisher Scientific) with the 1x dsDNA HS Assay kit (Thermo Fisher Scientific). In addition to the general eDNA concentration, the presence of macrozoobenthos DNA (i.e. Dugesia sp. and Chironomidae) in aquaria was verified using the specific primer pairs and Sanger sequencing. These specific primers were designed for this experiment using Primer-BLAST (Tab. 1). GC scanning and the melting temperature (Tm) were also verified in Vector NTI version 11 (Invitrogen, Carlsbad). The primers were designed according to standard criteria (Chuang et al., 2013; Wu et al., 2004), focusing on small fragment size (100–300 bp) and lower Tm. Several genes (18S rRNA, COB, COI) were compared to find the most suitable region for the widest possible species representation. The resulting genus-specific and group specific primers were designed in the Cytochrome c Oxidase subunit I (COI) gene (Tab. 1) and the sequences of the compared sections were obtained from the NCBI database (Tab. S1).

Each PCR reaction consisted of illustra PuReTaq Ready-to-go PCR beads (GE Healthcare), 0.5 µM of primers and 10 ng of DNA. A range of annealing temperatures (ATs) similar to the calculated Tm were tested in a gradient PCR (45 °C − 55 °C) and subsequently all PCRs were run with the following program: 95 °C for 5 min; 38 cycles of 95 °C for 30 s, 45 °C for 30 s (Duge primers) / 52 °C for 30 s (Chiro primers), and 72 °C for 1 min; and final extension at 72 °C for 5 min (C1000 Touch™ Thermal Cycler). Selected PCR products were purified using a Thermosensitive Alkaline Phosphatase (FastAP; Thermoscientific) and Exonuclease 1 (Exo 1; Thermoscientific) according to manufacturer's instructions. For a quick verification, the selected samples were sequenced via conventional Sanger sequencing in a commercial laboratory (Eurofins Genomics GmbH). Alignments and the final matrix were completed in MEGA-X (Kumar et al., 2018). Sequences were identified with BLAST searches (Basic Local Alignment Search Tool).

Table 1

Primers developed and used for the quick verification of the target invertebrates' DNA (Chironomidae, Dugesia sp.) presence in the experimental aquaria.

2.5 Molecular analysis: Presence of eDNA on the fish mucus

The smears were pooled for aquaria Ae + Be and Ce + De due to similar eDNA concentrations in these aquaria, respectively. Thus, higher concentrations of eDNA in the samples, as well as reduced sequencing costs were achieved. A total of 13 selected smear samples were sent for MiSeq sequencing (sample pooling scheme in Tab. S2). The COI gene region was amplified using the universal primers mlCOIintF and jgHCO2198 (Geller et al., 2013; Leray et al., 2013). The PCR was performed using the HotStarTaq Plus Master Mix Kit (Qiagen) under the following conditions: 94 °C for 3 min, followed by 30 cycles of 94 °C for 30 s, 53 °C for 40 s and 72 °C for 1 min, after which a final elongation step at 72 °C for 5 min was performed. Then, all amplicon products were mixed in equal concentrations and purified using calibrated Agencourt AMPure XP beads. The pooled and purified PCR product was used to prepare Illumina MiSeq DNA library according to the manufacturer's guidelines. Sequencing was performed at MR DNA ( on a MiSeq following the manufacturer's guidelines.

Sequence data were processed using MR DNA analysis pipeline. Sequences were depleted of barcodes and primers, then sequences <150 bp were removed, as well as sequences with ambiguous base calls and with homopolymer runs exceeding 6 bp. Sequences were quality filtered using a maximum expected error threshold of 1.0 and dereplicated. The dereplicated or unique sequences were denoised; unique sequences identified with sequencing or PCR point errors were removed, followed by chimera removal, thereby providing zOTU (zero-radius Operational Taxonomic Units). In the case of zOTUs, all correct biological sequences were identified. This level of specificity is not achievable when using a 97% identity threshold as with traditional zOTUs. Final zOTUs were taxonomically classified using BLASTn against a curated database derived from NCBI and compiled into each taxonomic level into both “counts” and “percentage” files.

3 Results

3.1 Concentration/presence of eDNA in aquaria

The concentration of DNA in all aquaria fluctuated over time mostly around 0.2 ng/μl and 6.0 ng/μl, depending on the method used, Qubit™ and BioDrop® respectively (Figs. 2a,b). The BioDrop® was used to identify purity of the samples and the difference between BioDrop/Qubit numbers indicates presence of contaminants. The Qubit™ showed final DNA concentrations that are not affected by the presence of other contaminants. However, the difference was observed in the time of maximum concentration per aquarium. Based on the Qubit™ numbers, aquaria Ae and Be reached the highest concentration on days 3 and 4, whereas Ce and De had their maxima immediately after 20–24 h. The highest measured concentration (Qubit™) was 0.55 ng/μl for aquarium Ae, 0.45 ng/μl for aquarium Be, 0.51 ng/μl for aquarium Ce and 0.27 ng/μl for aquarium De (Fig. 2a).

Genus-specific primers designed for Dugesia sp. (Duge_for/rev) appeared to be effective to detect not only the tissue samples of this target macrozoobenthos (Fig. S1) but also the eDNA of Dugesia sp. from filter samples (Fig. 3a). Selected PCR products (Ae after 17 h, and Ae after 65 h sample − Fig. 3a) matched with the sequence of Dugesia sp. at 99% (Tab. S1). However, group specific primers designed for Chironomidae (Chiro_for/rev) were problematic. These primers worked for the tissue samples (Fig. S1); however, they failed to detect eDNA of Chironomidae from filter samples (Fig. 3b). It was not possible to obtain a sufficiently good-quality sequence from Sanger sequencing (due to unclear and overlapping peaks) before using an Illumina MiSeq platform. Thus, the eDNA presence of Chironomidae in aquaria could only be assumed based on the expected length of the fragments on the agarose gel (Fig. 3b). In both cases, genus-specific primers and group specific primers were able to detect presence of target macrozoobenthos in the aquaria right after 17 hours (Fig. 3a, b).

thumbnail Fig. 2

DNA concentration in experimental aquaria over time (hours). (A) Qubit™ 4 Fluorometer (ng/μl). (B) BioDrop® Touch Duo Spectrophotometer (ng/μl).

thumbnail Fig. 3

The results of 3% agarose gel electrophoresis with the target fragments bounded by a rectangle: (A) Results of the eDNA filters for Dugesia sp. (B) Results of the eDNA filters for chironomid larvae. Abbreviations as in Figure 1; also SM − DNA Ladder (Promega).

3.2 Presence of eDNA on the fish mucus

The eDNA was present on smears after all three time periods (i.e. 24, 48, 72 h; Tab. 2). Sequencing of amplified DNA from fish smears generated from 92146 to 245944 raw reads per sample (Tab. S3) with an average read length of 300 bp (299–301 bp). Post filtering reads were mapped to 7 phyla and 32 genera assigned to the 53 sequence zOTUs, of which the target contaminants represented 5 or 6 zOTUs (zOTU_1–zOTU_6; Tab. S4). The DNA quality or partial degradation on the fish skin mucus were likely to lead to changes/inaccuracies in zOTU richness (zOTU_1 and zOTU_16–zOTU_26). The zOTU_1 most likely belonged to Chironomidae (78% homology, Diptera), and the zOTUs_16–26 to Homo sapiens (∼80% homology, Primates; Tab. S4).

The vast majority of the reads from all smears was assigned to Rutilus rutilus (58.8–99.6%). Invertebrates represented 0.96% on average, of which the target taxa of macrozoobenthos represented 0.27% on average. The target macrozoobenthos taxa on the smears were represented only by Chironomidae (Tab. S4), although DNA from Dugesia sp. was present in the aquaria during the concentration measurements (Fig. 3a). Algae represented 0.32% on average. Despite the effort to maintain a sterile environment, human DNA, as well as DNA from Aves and Fungi were also captured in the smears (Tab. S4). Based upon the percent identity for most of the gained zOTUs, the most relevant taxonomic level was class (based on the percentage of homology ≥ 80%; Tab. S4).

Cases, when the foreign DNA occurred only on the second smear (i.e. when no DNA was detected on the first smear; n = 17) were excluded from further evaluation. This contamination contained mainly Fungi and various terrestrial groups of animals (Tab. S4). The relative abundance of zOTUs decreased (or was completely reduced) between the first and the second smear in 78.8% of cases and increased in 21.2% of cases (Tab. 2). The decrease was observed in the following target taxa: order Diptera (zOTU_1, 2) and group Algae (zOTU_3, 4, 5), as well as in non-target taxa, e.g. orders Hymenoptera and Odonata (zOTU_49, 50 respectively), and class Aves (zOTU_27; Tab. 2).

In the negative control aquarium (Ee), no target species of macrozoobenthos and algae were found on the smears. In addition to the zOTUs of Rutilus rutilus, only 2 other sequences of zOTUs were present in the samples of fish skin mucus from this aquarium, namely zOTU_48 and zOTU_50 belonging to Hemiptera and Odonata, respectively (Tab. S4). Fish survival rate after manipulation during the experiment was 97.4%.

Table 2

Relative abundance (%) of zOTUs with the most relevant taxonomic level identified on the first or on the first and second fish smear. Reduction in the number of DNA copies from the first to the second smear is marked in green. Increase in DNA copies from the first to the second smear is marked in pink. Abbreviations: AeBe-1s − pooled sample from experimental aquaria Ae and Be, first smear; AeBe-2s − pooled sample from experimental aquaria Ae and Be, second smear; CeDe-1s − pooled sample from experimental aquaria Ce and De, first smear; CeDe-2s − pooled sample from experimental aquaria Ce and De, second smear;

4 Discussion

Both the detectability and concentration of the organismś eDNA depend on many variables, such as production rate of individuals, environmental conditions, density of animals, and their residence time (Barnes and Turner, 2016; Goldberg et al., 2016; Hering et al., 2018; Pilliod et al., 2014). After the initial concentrations of target macrozoobenthos eDNA have culminated, approximately stable eDNA concentrations was observed in all experimental aquaria. Although the target organisms were placed into each aquarium at the same time, the upper aquaria (Ae and Be) reached their maximum later than the lower aquaria (Ce and De; Figs. 1, 2a). The initial rapid increase in eDNA is not uncommon in experimental aquaria, and it is caused by physiological stress of organisms (Pilliod et al., 2014; Thomsen et al., 2012). Such an increase was observed for Ce and De aquaria where the largest increase in eDNA concentration was around 24 hours (Fig. 2a). The postponed maximum of eDNA concentration in Ae and Be aquaria can be explained by their location closer to the light source (Fig. 1). These light conditions could have some impact on the rate of eDNA degradation (Mächler et al., 2018; Strickler et al., 2015), and on the other hand, promoted algal growth, which would correspond with a delayed peak of DNA concentration in Ae and Be aquaria. Higher occurrence of algae eDNA in Ae and Be aquaria can also be seen on the smears. In smears AeBe, algae were present in the samples after 24, 48 and 72 h, whereas in CeDe, smears algae were present only in one sample − after 72 h (Tab. 2).

Using group-specific primers, the eDNA of target organisms was captured immediately from the first filter − after 17 h. As the time progressed, a decreasing intensity of target taxa bands on the agarose gel and an occurrence of stutter bands was observed (Figs. 3a, b). This probably happened due to the increasing amount of inhibitors in aquaria or due to DNA degradation, which commonly occurs within eDNA samples (Schneider et al., 2016; Stoeckle et al., 2017). Although Chironomidae seemed to be an ideal group of target contaminants, because they can be obtained in large quantities, their primer design is challenging, mainly due to the limited number of sequences available in GenBank. Moreover, some species are known to hybridize (Martin, 2011).

Interestingly, eDNA from Dugesia sp. was not present on any smear, although it was present in the water (Fig. 3a). There are several possible explanations to this phenomenon, e.g. the use of non-specific primers. The mitochondrial gene COI is so variable in flatworms that the primers often have to be taxon-specific (Moszczynska et al., 2009; Vanhove et al., 2013). For example, when testing a new universal primer intended for eDNA monitoring of aquatic invertebrates, flatworms appeared to be a problematic group that could not be captured even after optimizing primers to a wide range of aquatic invertebrates (Leese et al., 2021). Nevertheless, the development of new primers could also reveal presence of Dugesia sp. or other flatworms DNA on the mucus in the future. Another possible explanation is the time that had elapsed between the moments when the fish and Dugesia were placed into the aquaria (5.5 days). At that time, a settled layer of mucus from Dugesia sp. was present at the bottom of the aquaria. It is possible that the DNA remained stuck at the bottom and did not float in the water column, just like at the beginning of the experiment (Fig. 3a).

The results of our study clearly demonstrated that eDNA from other organisms is present on fish skin mucus (Tab. 2, S4), despite the mucus antimicrobial activity (Alexander and Ingram, 1992). If such contamination is found in experimental conditions, it will be probably present on the fish collected in the field, too. It is thus important to consider this finding, because such foreign DNA could be a source of bias for the results of diet analyses of faeces (Corse et al., 2010; Guillerault et al., 2017). However, careful wiping can be an effective way to decrease foreign DNA concentration from the surface of fish body. Indeed, the concentration of target (macrozoobenthos and algae) as well as non-target contaminant DNA decreased between the first and the second smear (Tab. 2, S4). Moreover, this procedure can be applied with minor harm to fish studied, considering the fish survival rate after experiment (97.4%). However, such a survival rate refers to experimental conditions only. In the wild the survival rate may be lower due to higher risk of infections (Svendsen and Bøgwald, 1997).

As the diet of many species is either unknown or consists of a broad array of taxa, mainly universal primers have been recently used for molecular diet analyses to allow amplification of DNA from a wider range of eukaryotes (Elbrecht and Leese, 2017; Klymus et al., 2017; Piñol et al., 2015, Piñol et al., 2018;2018). However, the use of universal primers brings a risk of bias to the results, and distinguishing individual diet components from the contamination may turn to be difficult. Indeed, the universal primers (Leray et al., 2013) used in our study captured a high number of contaminations.

Although the rules to prevent contamination were strictly followed throughout the experiment, some degree of non-target contamination was present in the samples, e.g. fungi and terrestrial organisms (Tab. 2, S4). Fungi may invade living organisms and infect plants, animals, and humans (Eduard, 2009) and they are the most common contaminants found in the water and in the air (e.g., Babič et al., 2017; Pyrri et al., 2020), and have even been detected in fish food (Namulawa et al., 2020). The fungal and terrestrial organism's contamination in our study probably came from the air, being trapped on smears during sampling (these groups mostly occurred on the second smears; Tab. S4). The presence of bird DNA was also identified in the samples (zOTU_27 Gallus gallus with 100% homology; Tab. S4). It probably came from the fish food, which contains egg products. Fish were not fed during the experiment, therefore the chicken DNA most likely originated from faeces (fish were fed before the onset of the experiment in the Room 2). Only one type of contamination (Odonata, zOTU_50) found on smears from negative control aquarium (Ee) was present on almost all smears from experimental aquaria. Therefore, it is assumed that Odonata DNA came from the Room 2 aquaria (Tab. S4, Fig. 1). Cases when the relative abundance (%) of zOTUs increased between the first and second smear, as well as the presence of the foreign DNA on the second smear only were considered additional contamination (Tab. 2). This contamination arose from outside, probably during manipulation with fish.

Since the fish skin mucus in this experiment contained eDNA from various organisms, such as Diptera, Algae, Fungi, Coleoptera, Odonata, Hydrozoa and even Aves, it is assumed that skin mucus of fish from the wild is contaminated by eDNA of diverse organisms. Although the percentage of contamination appears to be quite low in some cases, the number of contaminants is several times higher in the natural environment. Moreover, the contaminants are in constant contact with the fish body.

The potential capacity of fish skin mucus to catch eDNA of other organisms found in our study suggests its potential use for screening the environment's biodiversity. The fish skin mucus could thus become an alternative to aquatic biofilms, that act as passive eDNA samplers of aquatic communities (Rivera et al., 2022). Nevertheless, the constant renewal of mucus and the high mobility of fishes should be considered.

In conclusion, this study demonstrates that DNA of other organisms can be captured on the fish skin mucus, posing a risk of contamination, especially when faeces samples are taken by gently squeezing the abdomen area. It is assumed that the fish skin mucus is exposed to a large number of contaminants (DNA of other species) especially in natural conditions, and such DNA may be incorrectly analysed as a part of the fish diet spectrum. Therefore, it is important to minimize this risk as much as possible and this can be achieved simply by careful cleaning of the anus area, with minor harm posed to the fishes examined. This study also demonstrates that just a simple but careful manual wiping (without the use of any cleaning agent) significantly reduces or removes the amount of foreign DNA, and thus eliminates the possible bias.

Data availability statement

The short COI fragments from tissue samples were sequenced by our designed primers (Tab. 1) and are deposited in NCBI's Genbank database (Sample D1: MZ605406; Sample CH1: MZ605405; Sample_K_Dugesia_sp.: MZ883097; Sample_U_Dugesia_sp.: MZ883098) ( High-throughput sequence data are in NCBI's Sequence Read Archive under BioProject ID: PRJNA755506 (Tab. S3) (

Ethical approval

The standards set for fish rearing in laboratory conditions according to Directive 2010/63/EU of the European Parliament and of the Council of 22 September 2010 on the protection of animals used for scientific purposes were followed carefully. The permission for sample collection was granted by Ministry of Environment of the Slovak republic (license no. 16/2018).


This study was supported by the Operational Program Integrated Infrastructure co-financed with the European Fund for Regional Development (EFRD). ITMS: ITMS2014+313021W683: “DNA barcoding of Slovakia (SK-BOL), as a part of international initiative International Barcode of Life (iBOL)”. We would like to thank M. Traugott for his help with the initial idea of this study and his valuable comments to the design of the experiment. We are grateful V. Kováč for his assistance with English corrections and his valuable comments and suggestions to the manuscript. We would also like to thank L. Arendt for his help with English and P. Mosná and S. Masaryková for their assistance in the fish laboratory and in the field (collecting samples).


  • Alexander JB, Ingram GA. 1992. Noncellular nonspecific defence mechanisms of fish. Annu Rev Fish Dis 2: 249–279. [CrossRef] [Google Scholar]
  • Babič MN, Gunde-Cimerman N, Vargha M, Tischner Z, Magyar D, Veríssimo C, Sabino R, Viegas C, Meyer W, Brandão J. 2017. Fungal contaminants in drinking water regulation? A tale of ecology, exposure, purification and clinical relevance. Int J Environ Res Public Health 14: 636. [CrossRef] [Google Scholar]
  • Bammer V, György A, Pehlivanov L, Schabuss M, Szaloky Z. 2015. Fish. Chapter 9In Liška I, Wagner F, Sengl M, Deutsch K,Slobodník J, eds. Joint Danube Survey 3: A Comprehensive Analysis of Danube Water Quality. International Commission for the Protection of the Danube River, Vienna. [Google Scholar]
  • Barnes MA, Turner CR. 2016. The ecology of environmental DNA and implications for conservation genetics. Conserv Genet 17: 1–17. [CrossRef] [Google Scholar]
  • Briem F, Zeisler C, Guenay Y, Staudacher K, Vogt H, Traugott M. 2018. Identifying plant DNA in the sponging-feeding insect pest Drosophila suzukii. J Pest Sci 91: 985–994. [CrossRef] [Google Scholar]
  • Carreon‐Martinez L, Johnson TB, Ludsin SA, Heath DD. 2011. Utilization of stomach content DNA to determine diet diversity in piscivorous fishes. J Fish Biol 78: 1170–1182. [CrossRef] [PubMed] [Google Scholar]
  • Chuang LY, Cheng YH, Yang ChH. 2013. Specific primer design for the polymerase chain reaction. Biotechnol Lett 35: 1541–1549. [Google Scholar]
  • Corse E, Costedoat C, Chappaz R, Pech N, Martin JF, Gilles A. 2010. A PCR‐based method for diet analysis in freshwater organisms using 18S rDNA barcoding on faeces. Mol Ecol Resour 10: 96–108. [CrossRef] [PubMed] [Google Scholar]
  • Deagle BE, Thomas AC, Shaffer AK, Trites AW, Jarman SN. 2013. Quantifying sequence proportions in a DNA-based diet study using Ion Torrent amplicon sequencing: Which counts count? Mol Ecol Resour 13: 620–633. [CrossRef] [PubMed] [Google Scholar]
  • Eduard W. 2009. Fungal spores: A critical review of the toxicological and epidemiological evidence as a basis for occupational exposure limit setting. Crit Rev Toxicol 39: 799–864. [CrossRef] [PubMed] [Google Scholar]
  • Elbrecht V, Leese F. 2017. Validation and development of COI metabarcoding primers for freshwater macroinvertebrate bioassessment. Front Environ Sci 5: 1–11. [Google Scholar]
  • Geller J, Meyer C, Parker M, Hawk H. 2013. Redesign of PCR primers for mitochondrial cytochrome c oxidase subunit I for marine invertebrates and application in all-taxa biotic surveys. Mol Ecol Resour 13: 851–861. [CrossRef] [PubMed] [Google Scholar]
  • Goldberg CS, Turner CR, Deiner K, Klymus KE, Thomsen PF, Murphy MA, Spear SF, McKee A, Oyler-McCance SJ, Cornman RS, Laramie MB, Mahon AR, Lance RF, Pilliod DS, Strickler KM, Waits LP, Fremier AK, Takahara T, Herder JE, Taberlet P. 2016. Critical considerations for the application of environmental DNA methods to detect aquatic species. Methods Ecol Evol 7: 1299–1307. [CrossRef] [Google Scholar]
  • Greenstone MH, Weber DC, Coudron TA, Payton ME, Hu JS. 2012. Removing external DNA contamination from arthropod predators destined for molecular gut‐content analysis. Mol Ecol Resour 12: 464–469. [CrossRef] [PubMed] [Google Scholar]
  • Guardiola FA, Cuartero M, del Mar Collado-González M, Arizcún M, Díaz Baños FG, Meseguer J, Cuesta A, Esteban MA. 2015. Description and comparative study of physico-chemical parameters of the teleost fish skin mucus. Biorheology 52: 247–256. [Google Scholar]
  • Guillerault N, Bouletreau S, Iribar A, Valentini A, Santoul F. 2017. Application of DNA metabarcoding on faeces to identify European catfish Silurus glanis diet. J Fish Biol 90: 2214–2219. [CrossRef] [PubMed] [Google Scholar]
  • Hering D, Borja A, Jones JI, Pont D, Boets P, Bouchez A, Bruce K, Drakare S, Hänfling B, Kahlert M, Leese F, Meissner K, Mergen P, Reyjol Y, Segurado P, Vogler A, Kelly M. 2018. Implementation options for DNA-based identification into ecological status assessment under the European water framework directive. Water Res 138: 192–205. [CrossRef] [PubMed] [Google Scholar]
  • Jo H, Gim JA, Jeong KS, Kim HS, Joo GJ. 2014. Application of DNA barcoding for identification of freshwater carnivorous fish diets: is number of prey items dependent on size class for Micropterus salmoides? Ecol Evol 4: 219–229. [Google Scholar]
  • Jo H, Ventura M, Vidal N, Gim JS, Buchaca T, Barmuta LA, Jeppesen E, Joo GJ. 2016. Discovering hidden biodiversity: the use of complementary monitoring of fish diet based on DNA barcoding in freshwater ecosystems. Ecol Evol 6: 219–232. [CrossRef] [PubMed] [Google Scholar]
  • Kamenova S, Mayer R, Rubbmark OR, Coissac E, Plantegenest M, Traugott M. 2018. Comparing three types of dietary samples for prey DNA decay in an insect generalist predator. Mol Ecol Resour 18: 966–973. [CrossRef] [PubMed] [Google Scholar]
  • Klymus KE, Marshall NT, Stepien CA. 2017. Environmental DNA (eDNA) metabarcoding assays to detect invasive invertebrate species in the Great Lakes. PLoS ONE 12: e 0177643. [Google Scholar]
  • Kumar S, Stecher G, Li M, Knyaz C, Tamura K. 2018. MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms. Mol Biol Evol 35: 1547–1549. [Google Scholar]
  • Kumari S, Tyor AK, Bhatnagar A. 2019. Evaluation of the antibacterial activity of skin mucus of three carp species. Int Aquat Res 11: 225–239. [CrossRef] [Google Scholar]
  • Leese F, Sander M, Buchner D, Elbrecht V, Haase P, Zizka VMA. 2021. Improved freshwater macroinvertebrate detection from environmental DNA through minimized nontarget amplification. Environ DNA 3: 261–276. [CrossRef] [Google Scholar]
  • Legler ND, Johnson TB, Heath DD, Ludsin SA. 2010. Water temperature and prey size effects on the rate of digestion of larval and early juvenile fish. Trans Am Fish Soc 139: 868–875. [CrossRef] [Google Scholar]
  • Leray M, Yang J, Meyer C, Mills S, Agudelo N, Ranwez V, Boehm J, Machida R. 2013. A new versatile primer set targeting a short fragment of the mitochondrial COI region for metabarcoding metazoan diversity: application for characterizing coral reef fish gut contents. Front Zool 10: 1–14. [Google Scholar]
  • Martin J. 2011. From bands to base pairs: Problems in the identification of species using the example of Chironomus oppositus Walker (Honorary Thienemann Lecture). In Wang X, Liu W eds. Contemporary Chironomid Studies − Proceedings of the 17th International Symposium on Chironomidae. Tianjin: Nankai University Press, pp. 126–143. [Google Scholar]
  • Mächler E, Osathanunkul M, Altermatt F. 2018. Shedding light on eDNA: neither natural levels of UV radiation nor the presence of a filter feeder affect eDNA-based detection of aquatic organisms. PLoS ONE 13: e 0195529. [Google Scholar]
  • Moszczynska A, Locke SA, McLaughlin JD, Marcogliese DJ, Crease TJ. 2009. Development of primers for the mitochondrial cytochrome c oxidase I gene in digenetic trematodes (Platyhelminthes) illustrates the challenge of barcoding parasitic helminths. Mol Ecol Resour 9: 75–82. [CrossRef] [PubMed] [Google Scholar]
  • Nagashima Y, Kikuchi N, Shimakura K, Shiomi K. 2003. Purification and characterization of an antibacterial protein in the skin secretion of rockfish Sebastes schlegeli. Comp Biochem Physiol C Toxicol Pharmacol 136: 63–71. [CrossRef] [PubMed] [Google Scholar]
  • Namulawa VT, Mutiga S, Musimbi F, Akello S, Ngángá F, Kago L, Kyallo M, Harvey J, Ghimire S. 2020. Assessment of Fungal Contamination in Fish Feed from the Lake Victoria Basin, Uganda. Toxins 12: 233. [CrossRef] [PubMed] [Google Scholar]
  • Oehm J, Thalinger B, Mayr H, Traugott M. 2016. Maximizing dietary information retrievable from carcasses of Great Cormorants Phalacrocorax carbo using a combined morphological and molecular analytical approach. Ibis 158: 51–60. [CrossRef] [PubMed] [Google Scholar]
  • Patel M, Ashraf MS, Siddiqui AJ, Ashraf SA, Sachidanandan M, Snoussi M, Adnan M, Hadi S. 2020. Profiling and role of bioactive molecules from Puntius sophore (freshwater/brackish fish) skin mucus with its potent antibacterial, antiadhesion, and antibiofilm activities. Biomolecules 10: 920. [Google Scholar]
  • Pilliod DS, Goldberg CS, Arkle RS, Waits LP. 2014. Factors influencing detection of eDNA from a stream-dwelling amphibian. Mol Ecol Resour 14: 109–116. [Google Scholar]
  • Piñol J, Mir G, Gomez‐Polo P, Agustí N. 2015. Universal and blocking primer mismatches limit the use of high‐throughput DNA sequencing for the quantitative metabarcoding of arthropods. Mol Ecol Resour 15: 819–830. [CrossRef] [PubMed] [Google Scholar]
  • Piñol J, Senar MA, Symondson WOC. 2018. The choice of universal primers and the characteristics of the species mixture determine when DNA metabarcoding can be quantitative. Mol Ecol 28: 407–419. [PubMed] [Google Scholar]
  • Pyrri I, Tripyla E, Zalachori A, Chrysopoulou M, Parmakelis A, Kapsanaki-Gotsi E. 2020. Fungal contaminants of indoor air in the National Library of Greece. Aerobiologia 36: 387–400. [CrossRef] [Google Scholar]
  • Rivera SF, Rimet F, Vasselon V, Vautier M, Domaizon I, Bouchez A. 2022. Fish eDNA metabarcoding from aquatic biofilm samples: Methodological aspects. Mol Ecol Resour 22: 1440–1453. [CrossRef] [PubMed] [Google Scholar]
  • Schneider J, Valentini A, Dejean T, Montarsi F, Taberlet P, Glaizot O, Fumagalli L. 2016. Detection of Invasive Mosquito Vectors Using Environmental DNA (eDNA) from Water Samples. PLoS ONE 11: e 0162493. [Google Scholar]
  • Sint D, Raso L, Kaufmann R, Traugott M. 2011. Optimizing methods for PCR‐based analysis of predation. Mol Ecol Resour 11: 795–801. [CrossRef] [PubMed] [Google Scholar]
  • Smith PJ, McVeagh SM, Allain V, Sanchez C. 2005. DNA identification of gut contents of large pelagic fishes. J Fish Biol 67: 1178–1183. [CrossRef] [Google Scholar]
  • Stoeckle BC, Beggel S, Cerwenka AF, Motivans E, Kuehn R, Geist J. 2017. A systematic approach to evaluate the influence of environmental conditions on eDNA detection success in aquatic ecosystems. PLoS ONE 12: e 0189119. [Google Scholar]
  • Strickler KM, Fremier AK, Goldberg CS. 2015. Quantifying effects of UV-B, temperature, and pH on eDNA degradation in aquatic microcosms. Biol Conserv 183: 85–92. [Google Scholar]
  • Sunnucks P, Hales DF. 1996. Numerous transposed sequences of mitochondrial cytochrome oxidase I-II in aphids of the genus Sitobion (Hemiptera: Aphididae). Mol Biol Evol 13: 510–524. [CrossRef] [PubMed] [Google Scholar]
  • Svendsen Y, Bøgwald J. 1997. Influence of artificial wound and non-intact mucus layer on mortality of Atlantic salmon (Salmo salar L.) following a bath challenge with Vibrio anguillarum and Aeromonas salmonicida. Fish Shellfish Immunol 7: 317–325. [CrossRef] [Google Scholar]
  • Thalinger B, Oehm J, Mayr H, Obwexer A, Zeisler C, Traugott M. 2016. Molecular prey identification in Central European piscivores. Mol Ecol Resour 16: 123–137. [CrossRef] [PubMed] [Google Scholar]
  • Thomsen PF, Kielgast J, Iversen LL, Wiuf C, Rasmussen M, Gilbert MTP, Orlando L, Willerslev E. 2012. Monitoring endangered freshwater biodiversity using environmental DNA. Mol Ecol 21: 2565–2573. [CrossRef] [PubMed] [Google Scholar]
  • Vanhove M, Tessens B, Schoelinck C, Jondelius U, Littlewood T, Artois T, Huyse T. 2013. Problematic barcoding in flatworms: a case-study on monogeneans and rhabdocoels (Platyhelminthes). ZooKeys 365: 355–379. [CrossRef] [Google Scholar]
  • Wang H, Tang W, Zhang R, Ding S. 2019. Analysis of enzyme activity, antibacterial activity, antiparasitic activity and physico-chemical stability of skin mucus derived from Amphiprion clarkii. Fish Shellfish Immunol 86: 653–661. [CrossRef] [PubMed] [Google Scholar]
  • Weiss M, Leese F. 2016. Widely distributed and regionally isolated! Drivers of genetic structure in Gammarus fossarum in a human-impacted landscape. BMC Evol Biol 16: 1–14. [Google Scholar]
  • Wu JS, Lee C, Wu CC, Shiue YL. 2004. Primer design using genetic algorithm. Bioinformatics 20: 1710–1717. [Google Scholar]

Cite this article as: Števove B, Arendt D, Slovák Švolíková K, Szabóová D, Žitňanová K, Grul’a D. 2023. Environmental DNA captured on the fish skin mucus – a potential bias to molecular diet analyses. Knowl. Manag. Aquat. Ecosyst., 424, 17.

Supplementary Material

Fig. S1: Primer tested at the tissue samples extracted from 2 randomly selected individuals from the Dugesia sp. biomass (D1, D2) and from the chironomid larvae biomass (CH1, CH2). Abbreviations: SM – DNA Ladder (Promega); K – negative control.

Table S1. Homogeneity of gained sequences from tissue and eDNA samples with the most related taxa available in NCBI GenBank. Sequences (NCBI GenBank) used for primer design for Dugesia sp. and Chironomidae.

Table S2. Scheme of pooling samples from the experimental aquariums (Ae, Be, Ce, De) and negative control aquarium (Ee).

Table S3. Summary table of raw reads, reads clustered to zOTUs and number of zOTUs detected at all fish smears after various number of hours. Abbreviations: Ee-1s – 3 pooled samples of the first smear from three fish from negative control aquarium; AeBe-1s – pooled sample from experimental aquariums Ae and Be, first smear; AeBe-2s – pooled sample from experimental aquariums Ae and Be, second smear; CeDe-1s – pooled sample from experimental aquariums Ce and De, first smear; CeDe-2s – pooled sample from experimental aquariums Ce and De, second smear.

Table S4. Summary of all identified zOTUs with their percentage reads per sample after various number of hours. Homogeneity of gained zOTUs was identified via BLAST search. Abbreviations as in Table S3. For the assignment of individual zOTUs to taxonomic levels, please see Tab. S5.

Table S5. Taxonomic levels of each zOTU detected from the smears of fish skin mucus during experiment.

Access here

All Tables

Table 1

Primers developed and used for the quick verification of the target invertebrates' DNA (Chironomidae, Dugesia sp.) presence in the experimental aquaria.

Table 2

Relative abundance (%) of zOTUs with the most relevant taxonomic level identified on the first or on the first and second fish smear. Reduction in the number of DNA copies from the first to the second smear is marked in green. Increase in DNA copies from the first to the second smear is marked in pink. Abbreviations: AeBe-1s − pooled sample from experimental aquaria Ae and Be, first smear; AeBe-2s − pooled sample from experimental aquaria Ae and Be, second smear; CeDe-1s − pooled sample from experimental aquaria Ce and De, first smear; CeDe-2s − pooled sample from experimental aquaria Ce and De, second smear;

All Figures

thumbnail Fig. 1

Schema of the fish laboratory and experimental procedure. The fish laboratory consists of two separate rooms − Room 1 (experimental room) and Room 2 (rearing room). Aquaria in both rooms were placed on stands. Abbreviations: Ae, Be, Ce, De − experimental aquaria; Ee − negative control aquarium and the control of the fish survival; Fe − control of the fish survival; G, H, I, J, K, L, M, N − aquaria for rearing the fish (Room 2).

In the text
thumbnail Fig. 2

DNA concentration in experimental aquaria over time (hours). (A) Qubit™ 4 Fluorometer (ng/μl). (B) BioDrop® Touch Duo Spectrophotometer (ng/μl).

In the text
thumbnail Fig. 3

The results of 3% agarose gel electrophoresis with the target fragments bounded by a rectangle: (A) Results of the eDNA filters for Dugesia sp. (B) Results of the eDNA filters for chironomid larvae. Abbreviations as in Figure 1; also SM − DNA Ladder (Promega).

In the text

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.