# Ease and Limitations in Using Environmental DNA to Track the Spread of Invasive Host–Parasite Complexes: A Case Study of the Freshwater Fish Pseudorasbora parva and the Cryptic Fungal Parasite Sphaerothecum destruens

Théo Deremarque, Rodolphe Elie Gozlan, Ravo Ravaozafindrasoa, Giuliano Mucci, Lucie Delalex, Jean-Michel Foissy, Michaël Cagnant, Mathieu Clair, Justina Givens, Fabienne Justy, et al.

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Théo Deremarque, Rodolphe Elie Gozlan, Ravo Ravaozafindrasoa, Giuliano Mucci, Lucie Delalex, et al.. Ease and Limitations in Using Environmental DNA to Track the Spread of Invasive Host–Parasite Complexes: A Case Study of the Freshwater Fish Pseudorasbora parva and the Cryptic Fungal Parasite Sphaerothecum destruens. Fishes, 2024, 9 (12), pp.477. 10.3390/fishes9120477. hal-04901196

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Article

# Ease and Limitations in Using Environmental DNA to Track the Spread of Invasive Host-Parasite Complexes: A Case Study of the Freshwater Fish *Pseudorasbora parva* and the Cryptic Fungal Parasite *Sphaerothecum destruens*

Théo Deremarque<fnref n="1" />, Rodolphe Elie Gozlan<fnref n="1" />, Ravo Ravaozafindrasoa <fnref n="1" />,<fnref n="2" />, Giuliano Mucci <fnref n="1" />,<fnref n="3" />, Lucie Delalex <fnref n="4" />, Jean-Michel Foissy <fnref n="4" />, Michaël Cagnant <fnref n="4" /> ID, Mathieu Clair <fnref n="4" />, Justina Givens <fnref n="1" />, Fabienne Justy <fnref n="1" />, Alice Valentini <fnref n="5" /> ID, Delphine Nicolas <fnref n="6" /> ID, Pascal Contournet <fnref n="6" />, Claire Tetrel <fnref n="7" />, Marc Thibault <fnref n="6" /> and Marine Combe <fnref n="1" />,\*

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**Citation:** Deremarque, T.; Gozlan, R.E.; Ravaozafindrasoa, R.; Mucci, G.; Delalex, L.; Foissy, J.-M.; Cagnant, M.; Clair, M.; Givens, J.; Justy, F.; et al. *Ease and Limitations in Using Environmental DNA to Track the Spread of Invasive Host-Parasite Complexes: A Case Study of the Freshwater Fish Pseudorasbora parva* and the Cryptic Fungal Parasite Sphaerothecum destruens. *Fishes* **2024**, *9*, 477. https://doi.org/10.3390/fishes9120477

Academic Editor: Elvira Abollo

Received: 11 October 2024

Revised: 20 November 2024

Accepted: 21 November 2024

Published: 26 November 2024

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**Copyright:** © 2024 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
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conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).

**Abstract:** The spread of non-native species threatens biodiversity and exacerbates societal challenges like food security. To address this, effective conservation programs require detection methods that are easy to implement, accurate, and non-invasive. Over the past 15 years, environmental DNA (eDNA) techniques have gained popularity, surpassing traditional sampling methods. In this context, our study focused on tracking the invasive host-pathogen complex *Pseudorasbora parva* and *Sphaerothecum destruens* using eDNA metabarcoding. We collected water samples from freshwater canals over five months in the Camargue region, and once in Corsica Island, both in southern France. Total DNA was extracted from filtered water samples, and PCR-amplicons were sequenced using Illumina or Nanopore technologies. Our results revealed a high detection rate of *P. parva* in lentic ecosystems, aligning with habitat preferences of this small freshwater fish. Additionally, the detection rate in Camargue increased in May and June, likely due to the peak of the spawning season, which leads to more DNA being released into the environment (i.e., concentration and interaction of individuals). While eDNA successfully detected this invasive fish, we were unable to detect its cryptic fungal parasite, *S. destruens*, highlighting the challenges of identifying intracellular and cryptic fungal pathogens through eDNA methods.

**Keywords:** biological invasions; fungal parasites; biodiversity; freshwater

**Key Contribution:** This study highlights the ability of eDNA-based methods to detect invasive species such as *P. parva*, with results matching the species' known ecological patterns. In contrast, our findings illustrate the difficulties of those methods to detect cryptic intracellular pathogens.

<footnote n="1">¹ ISEM, University of Montpellier, CNRS, IRD, Montpellier, France; theo.deremarque@ird.fr (T.D.); rudy.gozlan@ird.fr (R.E.G.); ravoravao@gmail.com (R.R.); giuliano.mucci@ird.fr (G.M.); justina.givens@ird.fr (J.G.); fabienne.justy@umontpellier.fr (F.J.)</footnote>

<footnote n="2">² Laboratoire Eau, Environnement et Systèmes Urbains, 77455 Marne-La-Vallée, France</footnote>

<footnote n="3">³ Maladie Infectieuses et Vecteurs: Écologie, Génétique, Évolution et Contrôle (MIVEGEC), University of Montpellier, CNRS, IRD, 34090 Montpellier, France</footnote>

<footnote n="4">⁴ Office Français de la Biodiversité, Direction Interrégionale Provence-Alpes-Côte d'Azur et Corse, Bâtiment A—Les Jardins de la Duranne, 510 rue René DESCARTES, 13592 Aix-en-Provence, France; luciemdelalex@gmail.com (L.D.); jean-michel.foissy@ofb.gouv.fr (J.-M.F.); michael.cagnant@ofb.gouv.fr (M.C.); mathieu.clair@ofb.gouv.fr (M.C.)</footnote>

<footnote n="5">⁵ SPYGEN, 73370 Le Bourget-du-Lac, France; alice.valentini@spygen.com</footnote>

<footnote n="6">⁶ Tour du Valat, Research Institute for the Conservation of Mediterranean wetlands, Le Sambuc, 13200 Arles, France; nicolas@tourduvalat.org (D.N.); contournet@tourduvalat.org (P.C.); thibault@tourduvalat.org (M.T.)</footnote>

<footnote n="7">⁷ Office Français de la Biodiversité, Direction Interrégionale PACA Corse, Service Appui aux Acteurs et Mobilisation des Territoires, Domaine des Grandes Cabanes, 13460 Saintes-Maries-de-la-Mer, France; claire.tetrel@ofb.gouv.fr</footnote>

<footnote>* Correspondence: marine.combe@ird.fr</footnote>
# 1. Introduction

Over the last century, global trade and increased transport of animals have driven an unprecedented surge in species introductions worldwide [1,2]. This wave of biological invasions has significantly impacted the distribution and diversity of plants, animals, and microbial pathogens [3,4], altering the function of both terrestrial and aquatic ecosystems [5,6]. Additionally, it has fueled the rise of native and invasive infectious diseases in livestock and wildlife populations [7–9]. Yet, despite these growing threats, we still lack routine tools to track and monitor the changes of communities’ compositions over time and space, particularly for pathogenic species co-introduced with their hosts. This is especially critical in freshwater environments, which remain largely uncharted when it comes to understanding the presence and spread of invasive species [10,11]. How can we effectively identify the pathways of introduction, establishment, and spread of invasive host–parasite complexes that pose high risk of biodiversity loss and the emergence of disease in newly invaded environments?

The introduction of fungal pathogens via their hosts presents an escalating threat to global health, ecosystems, food security, and the economy. Fungal diseases are responsible for up to 65% of biodiversity loss [12]. Though the impact of fungal infections on animal health was long overlooked, between 1995 and 2010, the proportion of fungal disease outbreaks in animals and plants recorded in the ProMED (The Program for Monitoring Emerging Diseases) database jumped from 1% to 7%, sparking a global fungal disease alert [12]. Fungal diseases are increasingly affecting both wild and farmed aquatic species, posing serious threats to global food security [13] and the aquaculture industry [14–16]. However, monitoring the introduction and spread of invasive host–parasite systems, particularly in cryptic biodiversity [17] remains difficult due to the unique challenges of freshwater environments—such as murky waters and large, deep systems, compounded by the lack of regular monitoring programs.

One of the most pervasive host–parasite invasions in freshwater ecosystems is the Asian topmouth gudgeon (*Pseudorasbora parva*) and its fungal parasite the rosette agent *Sphaerothecum destruens* [18,19]. Originating in East Asia, *P. parva* (up to 12 cm long) has become the fastest-spreading invasive fish species [20,21], largely due to the global transport of Chinese carps. The generalist fungal parasite *S. destruens*, carried asymptomatically by *P. parva*, is highly virulent to many native European fish species, causing significant ecological and economic damage [19]. Detecting *S. destruens*, however, is notoriously difficult due to its cryptic nature and its life cycle involving intracellular spores or free-living zoospores [18,22–26]. Despite studies documenting their global [19] and local [25,27] distribution, comprehensive monitoring of these invasive host–parasite species at the country or regional level remains limited. This is largely due to the challenges of tracking invasive freshwater fish populations and detecting cryptic pathogens like *S. destruens* [25, 28]. Such information, however, is crucial for protecting uninfested aquatic environments by isolating and removing carrier host populations and preventing the transfer of infected fish to parasite-free waters [19].

Environmental DNA (eDNA) offers a promising solution for rapid biodiversity surveys, and conservation and management efforts [29]. Unlike traditional methods, eDNA allows for the non-invasive, ethical detection of species through water samples combined with high-throughput sequencing technologies [30,31]. This method is particularly suited to identifying the presence of invasive species and tracking their spread. Despite some inherent limitations, such as biases in DNA collection and fragmentation, eDNA-based metabarcoding has been successfully used to survey bacterial [32], fungal [33], plant [30,34,35], and animal communities. Its application in invasive species biology is well-documented [36,37], from detecting invasive bullfrogs [38] and invasive crayfish in France [39], to tracking rare carp in the U.S. [17]. Furthermore, eDNA has been used to detect aquatic pathogens, such as the generalist fish parasite *Neobenedenia girellae* [40] and the chytrid fungus *Batrachochytrium dendrobatidis* [41,42]. These successes suggest that eDNA could play a key role in early detection and monitoring of invasive host–parasite species.
Here, we conducted eDNA-based surveys in the freshwater canals in the Camargue region and in a reservoir lake and its connected river in Corsica, both in southern France, where the invasive *P. parva*–*S. destruens* complex is well known to occur [25]. Our aim was to (1) assess the effectiveness of eDNA-based metabarcoding in co-detecting *P. parva* and *S. destruens*, (2) determine whether seasonality could affect their detection in the aquatic environment, and (3) whether eDNA highlights the preferential niche and distribution of *P. parva* in lotic versus lentic environments.

## 2. Materials and Methods

### 2.1. Study Sites

For logistical reasons and access to the study sites, two sampling strategies were followed. In the Camargue region, four freshwater areas were sampled every month from January to June 2023: the Fumemorte canal (Val), the Belugue canal (Bel), the Pebre canal (Peb), and the Grandes Cabanes domain (GC) (Figure 1, Table 1, Supplementary Figure S1). In each canal, sampling was performed on three aquatic sites separated each by up to 2 km, resulting in the collection of up to 12 eDNA water samples per month (Supplementary Table S1). In Corsica, sampling was carried out on a single occasion in April 2023 in 3 different areas: upstream of the artificial Lake of Calacuccia (2 sites, Gol1 and Gol2, located 2.5 and 1.4 km upstream of the lake, respectively) in the Golo River, in Lake Calacuccia (4 sites, Cal1 to Cal4), and downstream of the Lake (4 sites, Gol7 to Gol10 located 5, 11, 20, and 31 km downstream of the lake, respectively) in the Golo River for a total of 10 samples (Table 1, Figure 2, Supplementary Figure S1).

<table><caption>**Table 1.** Aquatic study areas sampled from January to June 2023 in the Camargue region and the island of Corsica. Canal name, identification name (ID), and geographical location are given. In the Camargue region, three sites separated each by up to 2 km were sampled for each canal. In Corsica, water samples were taken upstream (Gol1 and Gol2), downstream (Gol7 to Gol10), and in Lake Calacuccia (Cal1 to Cal4).</caption><thead><tr><th>Region</th><th>Canal</th><th>ID</th><th>Latitude</th><th>Longitude</th></tr></thead><tbody><tr><td>Camargue</td><td>Fumemorte</td><td>Val3</td><td>N 43°29.5078'</td><td>E 004°41.2537'</td></tr><tr><td>Camargue</td><td>Fumemorte</td><td>Val4</td><td>N 43°29.6671'</td><td>E 004°41.22104'</td></tr><tr><td>Camargue</td><td>Fumemorte</td><td>Val5</td><td>N 43°29.7727'</td><td>E 004°41.1476'</td></tr><tr><td>Camargue</td><td>Grandes Cabanes</td><td>GC1</td><td>N 43°32.1817'</td><td>E 004°27.0954'</td></tr><tr><td>Camargue</td><td>Grandes Cabanes</td><td>GC2</td><td>N 43°32.2297'</td><td>E 004°27.4076'</td></tr><tr><td>Camargue</td><td>Grandes Cabanes</td><td>GC3</td><td>N 43°32.4604'</td><td>E 004°28.7040'</td></tr><tr><td>Camargue</td><td>Pebre</td><td>Peb1</td><td>N 43°26.6560'</td><td>E 004°38.6720'</td></tr><tr><td>Camargue</td><td>Pebre</td><td>Peb2</td><td>N 43°26.6246'</td><td>E 004°38.6883'</td></tr><tr><td>Camargue</td><td>Pebre</td><td>Peb3</td><td>N 43°26.5448'</td><td>E 004°38.6771'</td></tr><tr><td>Camargue</td><td>Belugue</td><td>Bel1</td><td>N 43°25.2832'</td><td>E 004°41.0434'</td></tr><tr><td>Camargue</td><td>Belugue</td><td>Bel2</td><td>N 43°25.3285'</td><td>E 004°41.0637'</td></tr><tr><td>Camargue</td><td>Belugue</td><td>Bel3</td><td>N 43°25.3919'</td><td>E 004°41.2651'</td></tr><tr><td>Corsica</td><td>Golo river</td><td>Gol1</td><td>N 42°19.4950'</td><td>E 008°58.0561'</td></tr><tr><td>Corsica</td><td>Golo river</td><td>Gol2</td><td>N 42°19.1449'</td><td>E 008°58.5992'</td></tr><tr><td>Corsica</td><td>Golo river</td><td>Gol7</td><td>N 42°21.6127'</td><td>E 009°03.9365'</td></tr><tr><td>Corsica</td><td>Golo river</td><td>Gol8</td><td>N 42°22.4459'</td><td>E 009°07.1619'</td></tr><tr><td>Corsica</td><td>Golo river</td><td>Gol9</td><td>N 42°24.033'</td><td>E 009°11.492'</td></tr><tr><td>Corsica</td><td>Golo river</td><td>Gol10</td><td>N 42°28.375'</td><td>E 009°13.354'</td></tr><tr><td>Corsica</td><td>Lake Calacuccia</td><td>Cal1</td><td>N 42°19.5476'</td><td>E 009°01.0142'</td></tr><tr><td>Corsica</td><td>Lake Calacuccia</td><td>Cal2</td><td>N 42°19.7830'</td><td>E 009°01.3442'</td></tr><tr><td>Corsica</td><td>Lake Calacuccia</td><td>Cal3</td><td>N 42°19.9450'</td><td>E 009°01.1218'</td></tr><tr><td>Corsica</td><td>Lake Calacuccia</td><td>Cal4</td><td>N 42°19.7869'</td><td>E 009°00.8759'</td></tr></tbody></table>
<figure><img src="image_5.png" /><figcaption>**Figure 1.** Map of the sampling sites sampled from January to June 2023 and located in 4 areas of the Camargue region. For each area, 3 aquatic sites were sampled.</figcaption></figure>

<figure><img src="image_6.png" /><figcaption>**Figure 2.** Map of the sampling sites sampled in April 2023 located in the Golo River and Lake Calacuccia in Corsica Island.</figcaption></figure>

## 2.2. *Aquatic eDNA Sampling*

In the Camargue region and the Calacuccia Lake in Corsica, samples were collected following the protocol described by Miaud et al. [43] for eDNA sampling in lentic environments. For each sampling site, a 100 mL water sample was collected at 20 different micro-habitats equally spaced around the edge of the lentic waterway using a sterile water-
sample dipper, resulting in a pooled water sample of 2 L contained in a sterile 2 L Whirl-Pak bag (Supplementary Figure S2). Samples were collected from the top 10 cm of the water column, preceded by a gentle circular movement with the sampling ladle, and from the pond bank without entering the water, to avoid possible contamination from the boots or from stirring up sediment. A new and sterile water-sample dipper was used for each site to avoid cross-contaminations. The 2 L water sample was homogenized by gently shaking the bag to ensure the eDNA was evenly mixed throughout the sample, and the whole 2 L water sample was then filtered directly in the field through a VigiDNA 0.45 µm filter (SPYGEN) using a sterile 100 mL syringe. For the lotic aquatic systems located upstream and downstream of the Lake Calacuccia, sampling was performed according to Cantera et al. [44]. Water was collected using a Vampire pump, which allowed us to filter up to 30 L of water within 30 min of water filtration using a 0.45 µM VigiDNA filtration capsule. Filters were filled with 80 mL of a CL1 conservative buffer (SPYGEN) and stored at room temperature before DNA extraction.

## 2.3. DNA Extraction

DNA extraction was performed following the protocol described by Pont et al. [45]. Each filtration capsule was shaken on an S50 Shaker (Cat Ingenieurbüro, Staufen, Germany) at 800 rpm for 15 min and the CL1 buffer inside the capsule was drained into a 50 mL tube which was then centrifuged at 15,000 × g for 15 min. The supernatant was removed with a sterile pipette, leaving 15 mL of liquid at the bottom of the tube. Then, 33 mL of ethanol and 1.5 mL of 3 M sodium acetate were added to each 50 mL tube and stored overnight at -20 °C. The tubes were centrifuged at 15,000 × g for 15 min at 6 °C, and the supernatant was discarded. Then, 720 µL of ATL buffer from the DNeasy Blood & Tissue Extraction Kit (QIAGEN GmbH, Hilden, Germany) were added, the tubes were vortexed, and the supernatants were transferred to a 2 mL tube previously filled with 20 µL of Proteinase K. The tubes were incubated at 56 °C for two hours. DNA extractions were then performed using the NucleoSpin® Soil Kit (MACHEREY-NAGEL GmbH & Co., Düren, Germany) starting from step 6, according to the manufacturer's instructions. Elution was performed by adding 100 µL of SE buffer twice. Two negative extraction controls were included to monitor for possible contamination. One negative control was added during the transfer of the CL1 buffer from the filtration capsule to the 50 mL tube using 50 mL of CL1 buffer. A second DNA extraction control was added the second day of the extraction using 720 µL of ATL buffer. The extracted DNA was stored at -20 °C.

## 2.4. In Silico Assessment of Primer Specificity for *S. destruens* Detection

The specificity of the previously proposed ChF2-ChR2 primers to amplify *S. destruens* from fish organs [46] was assessed by using BLASTn via a blast of the primers against the 18S rRNA genes of different species belonging to the clade Ichthyosporea (Supplementary Table S2). Those primers were investigated due to their ability to amplify short amplicons, which is suitable for detecting degraded eDNA. The number of nucleotide mismatches for both (forward and reverse) primers and the number of bases contained between the primers (amplicon size) were reported for each species.

## 2.5. PCR Amplifications of Host–Parasite DNA

Two different primer sets were used to amplify *P. parva* DNA: PparvaF-PparvaR in Camargue and teleo_F-teleo_R in Corsica. In Camargue, *P. parva* was the only fish species monitored, allowing for the use of species-specific primers, while in Corsica, *P. parva* was part of a broader monitoring campaign led by the OFB, which required the use of non-specific primers.

Prior to DNA amplification, each DNA extract had been diluted fivefold in DNase/ RNase-free water to remove PCR inhibitors (Supplementary Table S3). For practical reasons, the ISEM laboratory in Montpellier performed the detection of *P. parva* DNA in Camargue, targeting a 147 bp fragment of the mtDNA 16S rRNA genes using PparvaF-PparvaR
primers [47]. PCR amplifications were performed in 0.2 mL PCR tubes using the following mix: 1X GoTaq G2 Green master mix (Promega Corp., Madison, WI, USA)), 0.5 µM of each primer, 3 µL of DNA, and made up to 25 µL with DNase/RNase-free water. PCR amplification cycles consisted of an initial denaturation at 95 °C for 5 min, followed by 35 cycles of 30 s denaturation at 94 °C, 90 s hybridization at 60 °C, and 60 s elongation at 72 °C, ending with a final elongation at 72 °C for 5 min after the 35 cycles. Only one PCR per sample was performed (no replicates). For each sample, 3 µL of PCR product was loaded onto a 2% agarose gel and migrated by electrophoresis at 100 V for 60 min. Migration profiles were checked under UV light and scored a band of the expected size given the primers used. PCR-amplicons were further subjected to Oxford Nanopore Sequencing at ISEM.

SPYGEN performed the detection of *P. parva* DNA in Corsica by targeting a different genetic marker, such as a 100 bp fragment of the mtDNA 12S rRNA genes using teleo_F-teleo_R primers [30]. The PCR amplifications were performed in a final volume of 25 µL of amplification mixture, using 3 µL of DNA extract as the template. The amplification mixture contained 1 U of AmpliTaq Gold DNA Polymerase (Applied Biosystems, Foster City, CA, USA), 10 mM Tris-HCl, 50 mM KCl, 2.5 mM MgCl₂, 0.2 mM of each dNTP, 0.2 µM of each primer, and 0.2 µg/µL bovine serum albumin (BSA, Roche Diagnostic, Basel, Switzerland). The primer sets were 5'-labelled with an eight-nucleotide tag unique to each sample (with at least three differences between any pair of tags), allowing the assignment of each sequence to the corresponding sample during sequence analysis. The tags for the forward and reverse primers were identical. The PCR mixture was then amplified using the protocol described above with 50 PCR cycles. Twelve PCR replicates per sample were performed. PCR-amplicons were sequenced by Illumina by SPYGEN.

For *S. destruens*, the ISEM laboratory performed the detection of the parasite DNA in Corsica while its detection in Camargue was performed by SPYGEN. Both laboratories amplified a 154 bp fragment of the 18S rRNA genes using the ChF2-ChR2 primers. The aforementioned PCR conditions respective to each laboratory were followed for the amplification of *S. destruens* DNA.

All PCR products, either positive or negative on the gel, were sequenced using either an Illumina HiSeq 2500 sequencer (Illumina, San Diego, CA, USA) or a MinION mk1C sequencer (Oxford Nanopore Technology, Oxford, UK).

## 2.6. *Library Preparation and Sequencing*

ONT. Before library preparation, DNA quantification of PCR-amplicons was performed using Qubit Fluorometric Quantification (ThermoFisher Scientific, Waltham, MA, USA). The samples were then standardized in order to start the preparation of the sequencing libraries with the same amount of DNA for each sample, such as 110 fmol. ONT libraries were prepared using native barcoding 24 v14 (SQK-NBD114.24, Oxford Nanopore Technologies, Oxford, UK) according to the manufacturer's instructions for barcoding of amplicon libraries. At the end of the library preparation, 20 fmol of DNA was loaded onto a flow cell (R10.4.1) and sequencing was performed on an Oxford Nanopore Technologies (Oxford, UK) Mk1c device (MinKNOW software v23.07.12) with a maximum run time of 48 h.

Illumina. Prior to the Illumina sequencing, amplified samples were quantified using capillary electrophoresis, purified using MinElute PCR purification kit (Qiagen GmbH, Hilden, Germany), and quantified again. The primer sets were 5'-labelled with an eight-nucleotide tag unique to each sample (with at least three differences between any pair of tags), allowing the assignment of each sequence to the corresponding sample during sequence analysis. The tags for the forward and reverse primers were identical. The PCR mixture was then amplified using the protocol described above with 50 PCR cycles. PCR products were pooled in equal volumes to achieve a theoretical sequencing depth of 500,000 reads for fish primer and 50,000 for *S. destruens*; libraries were prepared using the
True Seq protocol (Illumina, San Diego, CA, USA) and paired-end sequencing was carried
out on an Illumina NextSeq 1000 sequencer.

2.7. *Bioinformatic Analysis*

ONT. Reads were basecalled and demultiplexed in real time using the guppy soft-
ware v3.5.2, with default parameters, integrated into the MinION device, resulting in
fastq files. The bioinformatic analysis of the reads was performed using the pipeline
developed by Eger et al. [48] and dedicated to the treatment of Nanopore sequencing
data in metabarcoding studies. This pipeline addresses Nanopore's high error rate
through a series of polishing steps: (1) The raw reads were trimmed on both ends using
cutadapt v3.0 [49] to remove low quality bases, and length filtering was applied to keep
only reads in a range between 100 and 200 bp; (2) the filtered reads were clustered using
ISONCLUST [50] v0.0.6 (mapped threshold: 0.825; aligned threshold: 0.65) and a con-
sensus was generated with RACON v1.4.13 [51]; (3) the consensus sequences obtained
were clustered at 99% sequence identity with CD-HIT [52] v4.8.1 and a centroid was
selected as a representative of each cluster; (4) after trimming the primers (PparvaF and
PparvaR for *P. parva* or ChF2 and ChR2 for *S. destruens*) from the centroid sequences, a
second length filtering was applied using the previously specified ranges, completing
the production of polished reads. Those polished reads were then BLAST against a
reference database restricted to *P. parva* and some other species from the cyprinoidei
suborder (Supplementary Table S4) or all Ichthyosporean species using the same settings
as Eger et al. [48]. The BLAST results were analyzed using a lowest common ancestor
approach with stringent percentage identity thresholds: 99% for species level, 97% for
genus level, 95% for family level, and 93% for higher-than-family-level. In order to avoid
taking into account spurious detections, sequences displaying less than 10 reads or with
a frequency of occurrence <0.001 per sequence and per library were excluded.

Illumina. Sequence reads were analyzed using the programs implemented in the OBITools package (http://metabarcoding.org/obitools [53] accessed on 1 February 2023). Forward and reverse reads were assembled using the illuminapairedend program and assigned to each sample using the ngsfilter program. Sequences shorter than 20 bp, occurring <10 times per sample, or labeled as 'internal' by the obiclean program (likely due to PCR/sequencing errors) were discarded. The taxonomic assignment of ASVs (Amplicon Sequence Variants) was performed using the program ecotag with the local reference database [30] and the sequences extracted from the release 247 (standard sequences) of the GenBank® (National Center for Biotechnology Information, Bethesda, MD, USA). To account for the incorrect assignment of a small number of sequences to the sample due to tag jumps [54], all sequences with a frequency of occurrence <0.001 per sequence and per library were excluded. Subsequently, the data were curated for index-hopping [55], with a threshold empirically determined using experimental blanks (i.e., combinations of tags not present in the libraries) for a given sequencing batch between libraries.

2.8. *Fish Sampling*

In order to assess the robustness of the eDNA sampling in Corsica, we conducted fish
sampling targeting *P. parva* inside Lake Calacuccia and downstream to the lake, inside the
Golo River. The sampling was performed a year later in June 2024 using either traps (in the
lake) or electrofishing (in the river). One site was sampled in the lake while 8 sites were
sampled in the river. Giving the fact that the sampling time was not the same for all the
sites, the number of *P. parva* individuals collected was normalized to 60 min of sampling
for all the sites, allowing for the obtainment of a standardized catch per unit effort (CPUE)
for the sampling of *P. parva*.

2.9. *Ethics*

All fish were collected under a specific authorization delivered by the Préfet de la
Haute Corse to OFB, and the agreement N°A1320001. Fish collected were immediately
euthanized with an overdose of tricaine. M. Combe and R. Gozlan are trained for animal
(fish) manipulation and are notably allowed to practice fish euthanasia. For fish and
water sampling, M. Combe received the Nagoya agreement N°TREL2302365S/661 from
the "Ministère de la transition écologique et de la cohesion des territoires", as well as an
internationally recognized certificate of compliance constituted from information on the
permit, or its equivalent made available to the Access and Benefit-sharing Clearing-house
N° ABSCH-IRCC-FR-263712-1.

## 2.10. Statistical Analysis

Statistical analyses were performed on R (v4.3.2) and Rstudio (v2023.06.2+561) using the R package rstatix (v0.7.2). For statistical analyses, values from the Belugue canal were removed from the dataset for January, February, March, and June as these values were missing for the month of May. A Shapiro-Wilk normality test was applied and indicated a non-normal distribution of the data (w = 0.9283, *p*-value = 0.0081). Therefore, a Friedman test (non-parametric one-way repeated measures ANOVA) was performed to assess whether the month of the sampling had an effect on the percentage mapping of reads. Wilcoxon signed rank post hoc tests with Holm-Bonferroni correction were then performed to compare the percentage mapping of reads for each pair of months.

## 3. Results

3.1. *Detection of the Invasive P. parva Fish Host from Water Samples from Camargue and Corsica Island*

3.1.1. In the Camargue Region: Targeting the 16S rRNA Gene and Using Nanopore Sequencing

Nanopore sequencing of *P. parva* DNA-amplicons revealed filtered reads mapping only to the *Pseudorasbora parva* sequence (Supplementary Figure S3; Supplementary Table S3). No matches were found for other species tested. In the Camargue region, targeting the 16S rRNA gene and using Nanopore sequencing allowed for the detection of *P. parva* in all areas sampled, with a detection in all sites in May and June 2023 (Figure 3). The detection of *P. parva* in the Camargue region showed an increase over the study period (mean detection rate of *P. parva* of 0.69 for all areas sampled in January, February, and March versus mean detection rate of 1 for the areas sampled in May and June), which was not supported by statistical significance. However, the proportion of reads mapping the target 16S rRNA gene showed a significant increase from January to June 2023 (Friedman Stat = 24.8, *p* < 0.001) (Supplementary Table S5). The proportion of mapping reads for June 2023 was significantly different (according to the Wilcoxon signed rank post hoc tests performed) of those for January, February, and March 2023 while the proportion for May 2023 was only significantly different when compared to the result for January 2023 (Figure 4).

<figure><img src="image_7.png" /><figcaption>**Figure 3.** Detection rate of *P. parva* in four areas in the Camargue for each month studied.</figcaption></figure>
<figure><img src="image_8.png" /><figcaption>**Figure 4.** Box plot of the percentage of reads generated by Nanopore sequencing and mapping the mtDNA 16S gene of *P. parva* in the Camargue region. * *p*-value < 0.05.</figcaption></figure>

### 3.1.2. In Corsica Island: Targeting the 12S rRNA Gene and Using Illumina Sequencing

Illumina sequencing of DNA amplified with PCR primers targeting the mt12S gene of the Telestoei species allowed for the detection of *P. parva* alongside other fish species such as *Anguilla anguilla*, *Oncorhynchus mykiss*, *Oncorhynchus* sp., *Phoxinus* sp., *Salaria fluviatilis*, and *Salmo trutta* in and from either side of Lake Calacuccia (Supplementary Figure S4). In the Lake Calacuccia, *P. parva* was only detected at 3/4 sites and at three sites downstream of the lake (gol7, gol9, and gol10) but was not detected upstream of the lake. Among the detected species, *P. parva* had the highest number of mapped reads at three sites located in the lake (cal2, cal3, and cal4), whereas it was the least abundant species downstream of the lake. Consequently, the mean number of mapped reads was higher in Lake Calacuccia compared to the Golo River (92,704 reads vs. 2533 reads, respectively).

*P. parva* individual sampling followed the same patterns as those in the eDNA results. Indeed, the CPUE value in the lake was high (mean of 300 individuals per hour) while this number severely decreased downstream of the lake (mean CPUE value of 1.8 individuals per hour) with *P. parva* only found in two sites out of eight (Supplementary Figure S5).

### 3.2. In Silico Assessment of Primer Specificity to Detect *S. destruens*

The sequence of the tested species showed either no mismatch or only one mismatch to the ChF2 primer binding sequence used to amplify *S. destruens* DNA (Supplementary Figure S6). The binding region of the reverse primer ChR2 had a lower degree of similarity among the species tested with only *Anurofeca richardsi*, *Sphaeroforma tapetis*, and *Sphaeroforma* sp. isolate B7 and isolate CRG3, showing two mismatches with the primer sequence, while the other species showed more than two mismatches. Taken together, this information suggests the possibility of cross-amplification of other closely related species using these primers and a similar amplicon size (154 pb) with *S. destruens*.

### 3.3. Detection of *Sphaerothecum Destruens* from Water Samples from Camargue and Corsica Island

#### 3.3.1. In the Camargue Region: Targeting the 18S rRNA Gene and Using Illumina Sequencing

The results showed the amplification and matches on several species, confirming in silico observations of the lack of specificity of the only primers available and therefore used in this study in the case of eDNA surveys (Figure 5). Read mapping revealed amplification of DNA from species distantly related phylogenetically to *S. destruens*, such as CruMs within
the Eukaryota domain, which lies outside the Opisthokonta clade. Surprisingly, we found no reads that matched the published *S. destruens* 18S rRNA genes, regardless of the areas or time periods considered. However, reads mapping Ichthyosporean species were detected in all the areas. Among the Ichthyosporea, *S. tapetis* (Ichthyophonida) was detected in three areas, mainly in the Fumemorte canal (32,830 reads), but also in the Pebre canal and the Grandes Cabanes domain (1062 and 869 reads respectively), while *Sphaerothecum caipira* (Dermocystida) was found in the latter area, and the Belugue canal and Fumemorte canal as well. At the area scale, the largest number of mapped reads came from the Pebre canal (144,553 reads), while the area with the greatest clade diversity was the Grandes Cabanes domain.

<figure><img src="image_9.png" /><figcaption>**Figure 5.** Clades detected in Camargue (data pooled for February, March, and June) by Illumina sequencing of amplicons obtained by PCR with the ChF2-ChR2 primers. For each clade the number</figcaption></figure>

of reads mapping its genome is indicated. (A) Pebre canal; (B) Fumemorte canal; (C) Grandes Cabanes Domain; (D) Belugue canal.

### 3.3.2. In the Corsica Region: Targeting the 18S rRNA Gene and Using Nanopore Sequencing

Aligning with the results obtained in Camargue, the amplification of DNA by ChF2-ChR2 primers resulted in the identification of Ichthyosporean species but not *S. destruens* (Supplementary Figure S7). The Lake was the area with the largest number of mapped reads followed by the area upstream and the area downstream the Lake (4743, 1287, and 45 reads, respectively). Overall, the order Dermocystida was the most detected compared to the order Ichthyophonida (5483 and 519 reads, respectively). *Dermocystidium* sp. was the only species detected with its DNA found upstream the Lake and within the Lake.

## 4. Discussion

Our findings reveal that eDNA-based metabarcoding is a powerful and non-invasive detection tool for tracking the spread and prevalence of the highly invasive fish *P. parva*
in freshwater ecosystems. However, we also highlight some limitations when it comes to detecting cryptic fungal parasites such as *S. destruens*.

In the Camargue region, we consistently detected *P. parva* over time and space, aligning with existing monitoring data on its populations in the areas. This study is novel as it uniquely combines barcoding with Nanopore sequencing to assess the prevalence and spread of this invasive species. Previous studies reported varying detection levels of *P. parva* at the different sites (ranging from 2.6% to 38%, [56,57]), which were notably lower than what we found. This discrepancy could be due to our more efficient sampling approach in small canals or simply because *P. parva* is more numerous in our selected areas [25].

Our results, showing consistent detection across all sampled areas in the Camargue, reinforce reports of the species' rapid colonization of interconnected watercourses within just a few years [20,58]. Notably, our sampling primarily took place in small water bodies with low flow rates, minimizing DNA transport and potential dilution that can occur in faster-flowing waters [59].

In the Camargue region, we observed an increase in *P. parva* DNA detection at the end of spring and early summer that could be linked to the abiotic conditions being more favorable to *P. parva* growth and proliferation. In controlled environments, *P. parva* exhibited enhanced growth rates at higher water temperatures, with an optimal growth temperature of 23 °C [26]. Photoperiod also plays a crucial role; as Zhu et al. [60] discovered, juvenile *P. parva* thrive under long-day conditions compared to short-day ones. During our sampling period, water temperature and photoperiod conditions reached optimal levels for *P. parva* growth. Moreover, this timing coincides with the spawning season of *P. parva* [61,62]. Similar correlations between increased DNA detection and spawning events have been documented in lakes, rivers or even seawater [63,64]. Such correlation allowed for instance the use of eDNA as an indicator of spawning events [65–67]. The peak in eDNA concentration during spawning can be attributed to a spike in DNA shedding rate, meaning the rise in *P. parva* DNA could result from the release of sperm and eggs in the aquatic environment, a source of DNA usually more persistent in the environment than the DNA from somatic cells [68,69].

On Corsica Island, our Illumina sequencing allowed for the successful detection of *P. parva* in Lake Calacuccia. Consistent with fish capture data over the last decade (OFB personal communication), *P. parva* emerged as the most detected species in the Lake, even outpacing native species like *Salmo trutta*, which ranked second. This suggests a significant occupancy of the Lake by *P. parva*. Furthermore, we also found its DNA downstream in the Golo River, though not upstream. To ascertain whether this detection indicated colonization or simply DNA transport from the lake, we needed to delve deeper into eDNA transport dynamics [70,71]. Wood et al. [72] predicted that in flowing waters, eDNA concentration peaks a few meters to hundreds of meters downstream before tapering off with increasing distance from the source. The distance covered by eDNA varies from hundreds of meters for small streams to over a hundred kilometers for large rivers [45,73]. However, the Golo River is considered a small river which minimizes the potential distance covered by transported DNA. Furthermore, furthest sites (gol9 and gol10), about 30 kms from the lake, yielded more reads than those closer to the lake (gol7 and gol8), challenging the expected patterns of eDNA transport [72]. While interpreting eDNA results collected downstream of the lake poses challenges, capturing several individuals in slower-flow sections of the Golo River suggests that *P. parva* may have passed over the dam during flood events. However, whether a permanent population can establish itself in this environment remains uncertain. Despite the presence of *P. parva* in the Golo River, it seems likely that Lake Calacuccia is the primary introduction point, particularly given the higher number of reads from this location. This higher detection rate in the Lake compared to the River underscores *P. parva*'s preference for lentic habitats over lotic ones [74,75]. Although *P. parva* displays remarkable plasticity regarding various abiotic factors, such as temperature tolerance [20,76], phenotype [77], and diet [78], it tends to favor lentic environments. Jia et al. [79] found that habitat type (lentic/lotic) was the most significant factor in *P.*
*parva* development among several other variables. Pollux and Korosi [74] proposed that lotic habitats serve primarily as dispersal corridors while lentic environments act as true permanent habitats.

Regrettably, we did not detect the cryptic fungal parasite *S. destruens*, despite its previous identification in fish organs from the same aquatic environments in Camargue and Corsica, where it showed a prevalence of 2% within the *P. parva* population of both regions [25]. This absence could stem from the fact that *S. destruens* is an intracellular parasite transported by asymptomatic hosts, making it elusive in the aquatic environment even when its carrier host, *P. parva*, is abundant. Other intracellular parasites, such as the fungus *Pseudoloma neurophilia*, which infects a broad range of fish species [80], have been detected using eDNA techniques [81]. However, the detection of *P. neurophilia* occurred in controlled environments (75 L tanks) where the sensitive host, *Danio rerio*, allowed for active parasite multiplication, whereas our study focused on open freshwater systems for detecting *S. destruens*. Few studies have explored *S. destruens* detection via eDNA [82,83]. Spikmans et al. [83] found it present in only 12% of eDNA samples despite its detection in 90% of captured *P. parva* individuals, emphasizing the challenges of tracking this parasite with eDNA. Additionally, eDNA sequences attributed to *S. destruens* were in fact genetically closer to *S. caipira* (Supplementary Table S6), while our sequences tagged as *S. caipira* matched closely (99–100%) with those assigned to *S. destruens* by Spikmans et al. [83], even though we targeted a shorter DNA fragment compared to Spikmans’ study. *S. caipira* is a recently described amphibians’ parasite, only found in Brazil so far [84]. It would be thus crucial to gain information about this parasite especially to make sure that its ecological preferences are consistent with a detection of the parasite in Camargue. If the establishment of this species outside of Brazil is confirmed, then (i) the design of new molecular markers might be necessary to make the distinction between *S. destruens* and *S. caipira* and (ii) a wide campaign of detection and monitoring of this parasite should be set up to evaluate the potential spread of this disease among amphibians worldwide, which are already weakened by other invasive fungal parasites such as *Batrachochytrium dendrobatidis* [85,86].

Specifically regarding *S. destruens* detection, it is well-documented that identifying rare—cryptic—species using eDNA can yield false negative results [87], especially when more abundant species are present, leading to amplification alongside the targeted genetic sequences [88]. Evans et al. [89] suggested that this ‘masking’ phenomenon may arise from a PCR bias favoring more abundant sequences in DNA extracts or from sequencing bias towards more prevalent amplicons. To enhance detection of less abundant species in eDNA studies, employing multiple genetic markers is highly recommended [90,91], as this approach increases sensitivity and confidence in positive results. Developing such markers will be essential once we fully elucidate the genome of *S. destruens*.

**5. Conclusions**

We showed that eDNA surveys, using either 12S or 16S genetic markers and Illumina or Nanopore sequencing, are highly effective for detecting and tracking the distribution of invasive *P. parva* populations in freshwater environments. Our findings emphasize the strong potential of eDNA as a tool for monitoring the introduction and spread of non-native fish species. However, detecting the intracellular and cryptic fungal parasite *S. destruens* remains challenging. The limited availability of specific molecular markers that can precisely target its DNA, while avoiding amplification of closely related species, has hindered its reliable detection through eDNA surveys. Despite this, we are confident that the development of more specific molecular targets will enable the use of eDNA to monitor its geographic distribution effectively and help environmental and governmental agencies to better evaluate the spread of invasive host–parasite complexes in aquatic environments, and guide biodiversity conservation strategies at a local (regional) and global (country) level.
**Supplementary Materials:** The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/fishes9120477/s1, Figure S1. Pictures of the studied sites in Camargue and Corsica; Figure S2. Pictures illustrating the eDNA sampling steps; Figure S3. Percentages of raw reads generated by Nanopore mapping on the mtDNA 16S gene of targeted species; Figure S4. Number of sequenced reads mapping Teleostei species mt12S gene; Figure S5. Log(10) of the number of catch per unit effort (CPUE) for 60' of *P. parva* in the Golo River according to its distance from the Lake Calacuccia; Figure S6. Test of the specificity of the ChF2 and ChF2 primers; Figure S7. Clades detected in Corsica by Nanopore sequencing; Table S1. Number of sites and replicates sampled for each area in Camargue and Corsica; Table S2. NCBI accession number of the different species used to assess the specificity of the ChF2-ChR2 primers via a blast of the primers against their 18S rRNA genes; Table S3. Measuring of potential PCR inhibitors among extracted DNA; Table S4. NCBI accession numbers of the different species used during the mapping step of the Nanopore sequencing; Table S5. Results of Friedman test and post hoc Wilcoxon tests for the impact of the time of the sampling on the percentage of mapped reads; Table S6. NCBI Blast results for S. *caipira* and S. *destruens* of the sequences obtained from eDNA samples attributed to S. *destruens* in Spikmans et al. [83].

**Author Contributions:** Conceptualization, R.E.G. and M.C. (Marine Combe); Formal Analysis, T.D. and R.R.; Investigation, T.D., R.E.G., G.M., L.D., J.-M.F., M.C. (Michaël Cagnant), M.C. (Mathieu Clair), J.G., F.J., A.V., D.N., P.C., C.T., M.T. and M.C. (Marine Combe); Writing—Original Draft Preparation, T.D.; Writing—Review and Editing, R.E.G. and M.C. (Marine Combe); Funding Acquisition, M.C. (Marine Combe). All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was funded by the Agence Nationale de la Recherche (ANR-22-CE02-0013-01 DRIVE) and by the Office Français de la Biodiversité (OFB). TD received a PhD fellow from ANR DRIVE.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The data presented in this study are available on request from the corresponding author.

**Conflicts of Interest:** A.V. is a research scientist in a private company specializing in the use of eDNA for biodiversity monitoring, with some patented technologies (SPYGEN). The other authors declare no conflicts of interest.

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