<figure><img src="image_1.png" /></figure>

# Digital PCR (dPCR) vs. Quantitative PCR (qPCR) approaches for quantification of two *Perkinsus* species within clam tissue samples

Elisa Chailler<sup>a, *</sup>, Héliaz Le Bayon<sup>a</sup>, Annabelle Dairain<sup>a</sup>, Florentine Riquet<sup>b</sup>, Leslie Stout<sup>c</sup>, Aurélie Chambouvet<sup>a, 1, *</sup> <sup>ID</sup>, Morgan Smits<sup>a, 1</sup>

## ARTICLE INFO

**Keywords:**
Parasites
Bivalves
Protists
PCR inhibitors
Infection intensity
Prevalence

## ABSTRACT

The parasite *Perkinsus olseni* (Perkinsea, Alveolata), the etiological agent of Perkinsosis, infects a wide range of bivalves and gastropods, including clams, particularly in Europe. This parasite coexists in sympatry with another *Perkinsus* species, *P. chesapeaki*, which, as opposed to *P. olseni*, has not been directly associated to mortality events. Accurate detection and quantification of *Perkinsus* infections, even at low infection intensities, are crucial for monitoring clam population health and assessing risks associated with emerging diseases. In this study, we compared molecular methodologies based on duplex real-time quantitative PCR (qPCR) and digital PCR (dPCR) in order to develop effective host resource management strategies. We first evaluated detection capabilities and the impact of potential inhibitors using both methodologies across varying DNA concentrations. Subsequently, we applied these methods to two contrasting French environments: Noirmoutier, characterized by low prevalence and infection intensity, and Arcachon Bay, which exhibits high prevalence and infection intensity. Our results demonstrate that dPCR should be prioritized for detecting and quantifying parasites at low infection intensities (10<sup>-1</sup>-10<sup>2</sup> cp.µL<sup>-1</sup>), as it might minimize false-negative results compared to qPCR. Notably, dPCR provided new insights and revealed cryptic infections, demonstrating greater efficiency in detecting *P. chesapeaki* in lightly infected sites such as Noirmoutier. Conversely, infection intensity was underestimated with dPCR relative to qPCR for clams with moderate to high *Perkinsus* infection levels (10<sup>3</sup> cp.µL<sup>-1</sup> or higher), proving the latter more suitable for medium to heavily infected areas like Arcachon Bay. These findings are important as they represent the first *in situ* monitoring of both *Perkinsus* species using culture-free methodologies. This work provides essential tools for resource management and conservation strategies to address emerging diseases.

## 1. Introduction

As the global human population continues to grow, the demand for sustainable aquaculture resources is increasing. Bivalves – such as clams, oysters, mussels, and scallops – are recognized as sustainable and low-trophic-level resources that contribute significantly to human nutrition, particularly by providing omega-3 polyunsaturated fatty acids (PUFAs) (Carboni et al., 2019). However, the past few decades have seen a marked decline in global bivalve production due to the emergence and worsening of epizootics, zoonoses and other infectious diseases (Conn, 2014; Hedrick, 1998; Mardones et al., 2009; Ward and Lafferty, 2004). This phenomenon has been linked to multiple anthropogenic factors,

including the intensification of the transfer of infectious agents via their hosts or their free-living forms, the introduction of exotic parasitic species, and the accelerating effects of climate change (Lafferty et al., 2004). *In situ* detection and characterization of micro-parasites is often challenging due to (i) morphological similarity between most micro-parasites despite them having high diversity at the molecular level; (ii) generally low intensities of infection, and (iii) difficulties associated with cultivating most of them (Bass et al., 2015; Bass and del Campo, 2020). Consequently, it is crucial to adapt and develop methodologies for rapid *in situ* detection and characterization of potentially noxious pathogens, while also improving our understanding of their impact on cultured and wild bivalve populations, particularly in the context of

<footnote><sup>a</sup> Sorbonne Université, CNRS, Adaptation et Diversité en Milieu Marin, AD2M, F-29680 Roscoff, France</footnote>

<footnote><sup>b</sup> IFREMER, Adaptation et Santé des Invertébrés Marins, ASIM, Av de Mus de Loup-17390, La Tremblade, France</footnote>

<footnote><sup>c</sup> University of Bordeaux, CNRS, Bordeaux INP, EPOC, UMR 5805, Station Marine, F-33120 Arcachon, France</footnote>

<footnote>* Corresponding authorsat: UMR7144, Station Biologique de Roscoff, Place Georges Tessier, 29680 Roscoff, France.
E-mail addresses: echailler@sb-roscoff.fr (E. Chailler), auchambouvet@sb-roscoff.fr (A. Chambouvet).</footnote>

<footnote n="1">¹ Authors equally contributed to the work.</footnote>
global change.

Perkinsosis is one of the most widespread marine diseases infecting a broad range of commercially valuable mollusk species including oysters, abalone and clams (Choi and Park, 2010; Liggins and Upston, 2010; Ruano et al., 2015; Villalba et al., 2004). In Europe, the etiologic agent of this disease is *Perkinsus olseni*, which was putatively introduced from Asia in the 1970 s along with its host, the Manila clam, *Ruditapes philippinarum* (Cigarría et al., 1997). Since its introduction, *P. olseni* has spread along the Atlantic and Mediterranean coasts, infecting other clam species such as *R. decussatus* and *Venerupis corrugata* (Abollo et al., 2006; Arzul et al., 2012; Azevedo, 1989; Balseiro et al., 2010; Da Ros and Canzonier, 1985). This spread has led to mortality events in Italy (Pretto et al., 2014), Portugal (Azevedo, 1989), and Spain (Sagristá et al., 1996; Villalba et al., 2005). While *P. olseni* infections do not always result in host mortality, cryptic sublethal effects such as reduced somatic growth, lower condition index, altered gametogenesis leading to decreased reproduction (Park et al., 2006; Uddin et al., 2010; Villalba et al., 2004), and chronic activation of the host's defense system (Pretto et al., 2014) can also significantly affect clam population dynamics (Lassalle et al., 2007). Recognizing its ecological and economic implications, the World Organization for Animal Health (W.O.A.H.) has classified *P. olseni* as a notifiable pathogen for the last several decades (OIE, 2021).

*P. olseni* is not the only *Perkinsus* species detected in Europe. It co-
occurs with a closely related species, *P. chesapeaki*, which has been
detected in *R. decussatus* from Leucate Lagoon, France (*Arzul et al.,*
2012), and in *R. philippinarum* from Arcachon Bay, France (*Itoïz et al.,*
2021) and Galicia, Spain (*Ramilo et al., 2016*). It has been hypothesized
that *P. chesapeaki* was accidentally introduced to Europe via its North
American hosts, the soft-shell clam, *Mya arenaria*, or the hard clam,
*Mercenaria mercenaria* (*Arzul et al., 2012*). While no mortality events
have been directly attributed to *P. chesapeaki* thus far (e.g., *Bushek et al.,*
2008; Carrasco et al., 2014), the existence of sympatric co-infection by
these two congeners is intriguing and warrants further research (Itoïz
et al., 2024).

The W.O.A.H. recommends culture-dependent methodologies based on Ray's Fluid Thioglycollate Medium (RFTM) followed by Lugol's iodine staining to detect *Perkinsus* species (Choi et al., 1989; OIE, 2021; OIE Listed Diseases, 2021; Ray, 1952). While this method is inexpensive, sensitive to very low intensities of infection, and easy to perform, it possesses several biases: (i) as a culture-based methodology, it may underestimate infection intensity (Itoïz et al., 2021), and (ii) it cannot discriminate between *Perkinsus* species or differentiate them from other protists (Almeida et al., 1999; Itoh et al., 2013; Itoïz et al., 2021). Recently, quantitative PCR (qPCR) for the detection and quantification of *P. olseni* has gained more attention (Itoïz et al., 2021; Ríos-Castro et al., 2022). Duplex qPCR assays targeting the distribution and intensity of infection of two *Perkinsus* species simultaneously in Manila clams from Arcachon Bay, France, revealed that *P. olseni* single-infections were largely dominant and showed high intensities of infection, while single-infections by *P. chesapeaki* were more cryptic (Itoïz et al., 2024). Surprisingly, co-infections by the two parasites were more frequent than single-infections by *P. chesapeaki*. A precise methodology for *in situ* identification and quantification of *Perkinsus* infections appears critical for (i) establishing a robust baseline to track the shifting distribution and potential development of mortality events across Europe, and (ii) understanding the complex interplay of factors including the host's level of infection, the presence of other micro- or macro-parasites, and the environmental factors affecting both hosts and parasites that shape parasite distribution.

Quantifying parasites within clam tissue is challenging, as the host tissue contains a variety of inhibitors that can interfere with the efficiency of the DNA polymerase during qPCR, potentially resulting in false negatives or inaccurate Cycle threshold (Ct) values (De Faveri et al., 2009). Moreover, qPCR may struggle to reliably detect target symbionts present at low-abundances, making it difficult to identify subtle population shifts within the dominant host DNA matrix (Damavandi et al.,

2021). The development of alternative molecular biology techniques, such as digital PCR (dPCR), presents an excellent opportunity to overcome limitations like PCR inhibitors (Coudray-Meunier et al., 2015; Devonshire et al., 2015; Hindson et al., 2013; Pavšić et al., 2017; Racki et al., 2014; Sedlak et al., 2014) and low levels of parasitic infections (Hayden et al., 2013; Hindson et al., 2013).

The aim of this study was to adapt a duplex dPCR assay and compare its performance with a previously established duplex qPCR assay (Itoïz et al., 2021) for monitoring and quantifying the infection intensity of *Perkinsus olseni* and *P. chesapeaki* in clams. The assays were tested in clams with varying infection intensities collected from two sampling sites along the French Atlantic Coast.

## 2. Material and methods

2.1. Clam sampling

Two sampling campaigns were conducted along the French Atlantic coast, in Arcachon Bay (south-western France, 44°41'60"N, 1°10'W) and in Noirmoutier (western France, 47°1'28.341"N, 2°14'51.264"W) in June 2022 and September 2023, respectively. Arcachon Bay was selected for its high infection intensity and prevalence of *Perkinsus* spp. in clams *Ruditapes* spp. (Itoïz et al., 2024), whereas Noirmoutier was chosen following previous observations of low intensity of infection and prevalence of *Perkinsus* spp. (pers. obs.).

Briefly, 49 and 46 clams were collected by hand from Arcachon Bay and Noirmoutier, respectively. For each individual, shell measurements were taken, and gill tissues were dissected on ice. Samples were weighed, preserved in 80 % ethanol, and stored at 4 °C for DNA extraction for molecular analyses.

## 2.2. Clam sampling in a *Perkinsus*-free sampling site

To evaluate the impact of different inhibitors on dPCR and qPCR efficiency, five clams were sampled in Carantec (north-western France, 48°40'36.2"N, 3°55'33.8"W), a site previously identified as *Perkinsus*-free (Le Bayon et al., unpubl. data). The absence of *Perkinsus* spp. was assessed using Ray's fluid thioglycolate medium (RFTM) method as recommended by the W.O.A.H. (Choi et al., 1989; OIE, 2021; Ray, 1952).

2.3. DNA extraction

Genomic DNA (gDNA) was extracted from gill samples using a CTAB-
based DNA extraction method adapted from Winnepenninckx et al. 1993
and Itoiz et al. 2021. Each gill tissue sample was dried to remove excess
ethanol and transferred to a tube containing 200 µL of CTAB solution (2
% CTAB, 100 mM TrisHCl pH = 8, 20 mM EDTA, 1.4 mM NaCl), then
flash-frozen five times in liquid nitrogen. After thawing, a mix con-
taining 100 µL of 10 % Na-Sarcosyl, 10 µL of lysozyme (500 mg.mL⁻¹),
and 5 µL of proteinase K (20 mg.mL⁻¹, Sigma-Aldrich) was added to
each tube, and samples were individually manually ground using a
sterile plunger compatible with 2 mL Eppendorf tubes until the tissues
were homogenized. Each plunger was rinsed with 650 µL of CTAB so-
lution directly over its sample tube to collect any residual adhering
tissue, and samples were incubated for one hour at 37 °C. Then,
β-mercaptoethanol (0.2 %, Sigma-Aldrich) was added to each tube, and
samples were incubated for 30 min at 60 °C.

Lysates were mixed with chloroform:isoamylalcohol (24:1, v/v) and centrifuged at 12,700 rpm for 10 min at 4 °C. The aqueous phases were collected and treated with a RNase A solution (10 mg.mL⁻¹, Sigma-Aldrich) for 30 min at 37 °C. DNA precipitation was carried out using cold 100 % isopropanol for 30 min at room temperature. The DNA was pelleted and rinsed once with a solution of 76 % ethanol and 10 mM of ammonium acetate. The DNA pellets were then dried at room temperature and resuspended in 100 µL of pure molecular-grade water
(Invitrogen). DNA samples were quantified using both the Nanodrop and the Qubit dsDNA BR assay kit (Invitrogen) (Suppl. Table 1). All gDNA, except those used to evaluate the inhibitory effect of host tissue on dPCR assays (see section 2.8), were normalized to 20 ng.µL⁻¹ to avoid the inhibitory effect of gill tissue samples, as recommended by Itoiz et al. (2021), and stored at -20 °C for further analysis.

## 2.4. Production of *p*. *Olseni* and *p*. *Chesapeaki* plasmid standards

To enable relative quantification and to test for analytical sensitivity, linearity, and dynamic range of qPCR and dPCR assays, we used the two monoclonal culture strains *P. olseni* (RCC7289) and *P. chesapeaki* (RCC7290) (available from the Roscoff Culture Collection, https://roscoculture-collection.org/) to establish plasmid standard curves as described by Itoiz et al. (2021).

DNA extraction from both cultures was carried out as described above (see section 2.3) and PCR assays were conducted using *Perkinsus* genus-specific primers ITS-85F/ITS-750R (ITS-85F 5'-CCGCTTTGTTTGGATCCC-3' and ITS-750R 5'-ACATCAGGCCTTCTAATTGATG-3') targeting the rDNA Internal Transcribed Spacer (ITS) regions (Casas et al., 2002). All PCR reactions were performed in a final volume of 25 µL using GoTaq Polymerase G2 (Promega), following the manufacturer's protocol, which included 1X green GoTaq reaction buffer (Promega), 0.2 mM of each dNTP, 0.5 µM of each primer, and 1.25 U of GoTaq DNA polymerase (Promega). The thermal cycling program began with an initial denaturation at 95 °C for 5 min, followed by 35 cycles of three steps: denaturation at 95 °C for 30 s, annealing at 56 °C for 30 s, and extension at 72 °C for 45 s. After a final extension at 72 °C for 10 min, and cooling to 4 °C, the amplified PCR products were analyzed on a 1 % agarose gel and purified using the Wizard SV Gel and PCR Clean-Up System (Promega) according to the manufacturer's instructions.

The ITS sequences were cloned using the StrataClone PCR Cloning Kit (Agilent). Clones were screened using white/blue selection, and five white colonies per condition were selected for overnight growth in Lysogeny Broth (LB) medium at 37 °C. Plasmid DNA was purified using PureYield Plasmid Miniprep system (Promega) and quantified using the Qubit dsDNA HS assay kit (Invitrogen).

The number of plasmids obtained was calculated using the following formula: $cp.µL⁻¹ = a/(3665 bp × 660 Da) × 6.022 × 10²³$ where a is the plasmid DNA concentration, 3665 bp is the plasmid size (including the vector of 3015 bp and the amplified fragment of 650 bp), 660 Da is the molecular weight of a base pair, and $6.022 × 10²³$ is Avogadro's constant. The purified plasmids of both *Perkinsus* species were then serially diluted in molecular-grade water (Invitrogen) to construct a standard range from $2.5 × 10¹$ to $2.5 × 10⁷$ cp.µL⁻¹ for both qPCR and dPCR.

## 2.5. Primers and probes

For both qPCR and dPCR analyses, we used species-specific primers and TaqMan hydrolysis probes designed by Itoiz et al. (2021). For the dPCR assays, the 5' and 3' ends of the probes were adapted to fit the specific features of the QIAcuity platform (Table 1).

<table><caption>**Table 1**

Primers and probes used for dPCR and qPCR assays.</caption><thead><tr><th>Name</th><th>Sequence (5'-3')</th><th>Specificity</th><th>Probe ends for qPCR</th><th>Probe ends for dPCR</th><th>Reference</th></tr></thead><tbody><tr><td>P.olsF</td><td>CAC-CAC-AAC-ACA-GTC-GGA-C</td><td>P. olseni</td><td></td><td></td><td>Itoiz et al. (2021)</td></tr><tr><td>P.olsR</td><td>TCG-TAT-TGT-AGC-CCC-TCC-G</td><td>P. olseni</td><td></td><td></td><td>Itoiz et al. (2021)</td></tr><tr><td>P.ols_probe</td><td>AGA-CAC-TCA-CAG-GCG-CGG-TCC</td><td>P. olseni</td><td>5' 6-FAM<br>3' BHQ-2</td><td>5' 6-FAM<br>3' BHQ-1</td><td>Itoiz et al. (2021)</td></tr><tr><td>P.chesF</td><td>GGA-ACA-CGG-AAT-CAA-CCA-CA</td><td>P. chesapeaki</td><td></td><td></td><td>Itoiz et al. (2021)</td></tr><tr><td>P.chesR</td><td>TAC-TGT-AGC-CCC-TTC-GCA-AG</td><td>P. chesapeaki</td><td></td><td></td><td>Itoiz et al. (2021)</td></tr><tr><td>P.ches_probe</td><td>CAG-TCG-AGT-TCG-CGA-GYA-TCC-AA</td><td>P. chesapeaki</td><td>5' 6-LC640<br>3' BHQ-2</td><td>5' ROX<br>3' BHQ-2</td><td>Itoiz et al. (2021)</td></tr></tbody></table>

## 2.6. Quantitative PCR (qPCR)

qPCR reactions were performed on a LightCycler 480 II (Roche). Each 15 µL reaction contained: 1X LightCycler 480 Probes Master premix (Roche), 0.2 µM for each primer, 0.5 µM for each probe, and 5 µL of template DNA previously adjusted to a concentration of 20 ng.µL⁻¹ as recommended by Itoiz et al. (2021). The thermal cycling program was as follows: 5 min of pre-incubation at 95 °C, followed by 45 amplification cycles consisting of 10 s of denaturation at 95 °C and 20 s of annealing at 55 °C. The qPCR reaction was terminated with a 2-minute cooling step at 4 °C (acquiring FAM/LC640). All reactions were performed at least in triplicate alongside a no-template control.

Variability was assessed based on the repeatability of the 10-fold dilution plasmid standards for *P. olseni* and *P. chesapeaki*. For each dilution, ranging from $2.5 × 10¹$ to $2.5 × 10⁷$ total copies of the reference standards, the mean Ct values and their standard deviations were determined from three separate qPCR runs, and the coefficients of variation (CV) were subsequently calculated for all plasmid concentrations as follows: $CV = (sd/x) × 100\%$, where sd represents the standard deviation and x is the mean corresponding to a specific plasmid dilution (Itoiz et al., 2021).

Sensitivity was assessed using two parameters: 1) efficiency (E), which measures the proportion of target molecules copied in a single PCR cycle, where 100 % indicates optimal DNA doubling (Bustin, 2010); and 2) limit of detection (LOD), defined as the lowest DNA concentration that yields positive and consistent Ct values. The qPCR efficiency (%) was calculated from the slope of each dilution curve using the formula: $E = (10^{(-1/slope)} - 1) × 100\%$. The LOD (in total copies) was identified as the lowest plasmid concentration within the linear range that demonstrated a significant and consistent amplification signal in triplicate (Itoiz et al., 2021).

## 2.7. Digital PCR (dPCR)

Specificity and sensibility of primers and probes were tested using monoclonal strains of *P. olseni* and *P. chesapeaki* gDNA.

Primers and probes specificity for qPCR assays was previously conducted in Itoiz et al. (2021). These analyses revealed no cross-amplification, either with non-target templates or across different fluorescence channels. In the present study, we extended these specificity tests to dPCR assays by comparing 1 pg of *P. olseni* and *P. chesapeaki* genomic DNA (gDNA) extracted from monoclonal cultures. In accordance with the dPCR manufacturer's recommendations, the fluorophore of the *P. chesapeaki* probe was modified to ROX in order to avoid cross-excitation with fluorophores emitting at other wavelengths. No amplification was observed from *P. chesapeaki* gDNA, host gDNA, or DNA-free controls using the *P. olseni*-specific primers and probe with the FAM filter (465–510 nm). Similarly, no amplification occurred from *P. olseni* gDNA, host gDNA, or DNA-free controls using the *P. chesapeaki*-specific primers and probe with the ROX filter (584–612 nm). These results confirm that primer/probe sets for both *P. olseni* and *P. chesapeaki* are highly specific to their respective targets, with no evidence of cross-reactivity in either qPCR or dPCR assays.

Digital PCR reactions were performed on the QIAcuity One Digital
PCR system (Qiagen) and QIAcuity Nanoplate 8.5 k 96-well (Qiagen). Each 12 µL reaction contained: 4x Qiagen QIAcuity Probe PCR kit (Qiagen), 0.8 µM of each primer, 0.4 µM for each probe, and 2 µL of gDNA normalized at 20 ng.µL⁻¹. A temperature gradient was performed, ranging from 52 to 64 °C, which established the ideal Tm as 58 °C (Suppl. Fig. 1).

The thermal cycling program was as follows: 2 min at 95 °C, followed by 40 cycles of 15 s at 95 °C and 30 s at 58 °C (acquiring FAM/ROX). All reactions were performed at least in triplicates alongside a no-template control.

The dPCR Limit of Blank (LOB) was assessed following the manufacturer's instructions. Briefly, LOB was determined using 30 replicates of one *Ruditapes* spp. gDNA template previously identified as *Perkinsus*-free by RFTM. The average concentration obtained for *P. olseni* and *P. chesapeaki* using dPCR assays was used to set the LOB in order to eliminate false positives by considering all concentrations below the LOB as negatives.

## 2.8. Inhibitory effect of host tissue sample on the dPCR assays

The inhibitory effect of host tissue concentration on dPCR assays was assessed as previously described for qPCR assays in Itoïz et al. (2021). Briefly, the non-inhibited reaction for both *P. olseni* and *P. chesapeaki* using dPCR assays was carried out using parasite DNA for standard curves. Subsequently, triplicate dPCR assays were conducted using one *Perkinsus*-free clam gDNA template from Carantec to determine the inhibitory effect of gill tissue. Sensitivity parameters were determined through duplex reactions with 10-fold serial dilutions of *P. olseni* and *P. chesapeaki* plasmid DNA (2.5 × 10¹ to 2.5 × 10⁵ total copies), supplemented with varying concentrations of gill tissue gDNA (20, 30, 40, 50, and 80 ng.µL⁻¹). Each dPCR assay included inhibitor-free standard curves (without host gDNA) for comparison. The standard dilution curves, which included extracted gill gDNA, were plotted by graphing the logarithm of the plasmid copy number against the corresponding measured concentration. The previously established standard curves (which contained plasmids only) served as a non-inhibitory reference curve for each duplex dPCR assay, allowing for the comparison of any potential inhibitory effects of the concentration of gill tissue samples. The detection limit was determined by defining the lowest concentration of plasmids within the linear range that displayed significant and consistent amplification signals over triplicate.

## 2.9. Statistical analysis

### 2.9.1. Comparison of qPCR and dPCR methodologies on plasmid standard curves

Plasmid concentrations were log-transformed. Statistical differences between qPCR and dPCR using all replicates for each concentration of the curve were tested using a pairwise Wilcoxon rank sum test (*p*-value < 0.01).

### 2.9.2. Effects of PCR inhibitors in dPCR assays

ANCOVA (R stats package v4.2.2) was used to evaluate the impact of gill gDNA concentration (covariate) on *P. olseni* and *P. chesapeaki* concentrations (cp.µL⁻¹) according to 5 different concentrations of matrix gDNA. Plasmid concentrations were log-transformed. Residuals demonstrated independence (Durbin-Watson test, *p*-value > 0.05); normal distribution (Shapiro-Wilk test, *p*-value > 0.05) and homogeneity of variances were confirmed (Levene test, *p*-value > 0.05). A pairwise comparisons post-hoc test (correction of multiple Bonferroni tests) was used to determine at which matrix concentration the inhibitors had a significant effect on the measured concentration of *Perkinsus* spp. obtained in dPCR compared to the control without clam gDNA matrix. Curves with no significant difference from the standard plasmid dilution were considered unaffected by the host gDNA matrix.

### 2.9.3. Comparison of qPCR and dPCR methodologies on the prevalence and intensity infection of two *Perkinsus* species in gill tissues

Infection intensity was calculated in cp.g⁻¹ of wet tissue and, when possible, a pairwise Wilcoxon rank sum test was performed to determine significant differences.

## 2.10. Similarities parameters

The concordance of the two methods is the percentage of chance that an identical sample analyzed by dPCR and qPCR methodologies will yield the same result (Langton et al., 2002). It is calculated by counting paired positive samples and paired negative samples. Conversely, the discordance is the percentage of chance that an identical sample analyzed by dPCR and qPCR methodologies will yield a different result, which is calculated by counting unpaired samples (positive samples in one methodology and negative samples in the other). Finally, the Cohen's Kappa (κ) coefficient was calculated (Pfeiffer, 2010) to assess the agreement between duplex qPCR and dPCR assay for prevalence in Noirmoutier and in Arcachon Bay.

# 3. Results

## 3.1. Optimization of dPCR assays

In order to optimize the results obtained with dPCR, we tested a melting temperature (Tm) range from 52 to 64 °C to determine the most suitable Tm for the primers using this assay. This temperature range showed that a temperature of 58 °C was ideal for our primers, enabling us to reduce "rain" (droplets of intermediate fluorescence which make it difficult to discriminate between a positive and negative result), as recommended by the manufacturer (Suppl. Fig. 1).

## 3.2. qPCR and dPCR parameters

The copy number concentrations measured by qPCR and dPCR assays for *P. olseni* and *P. chesapeaki* were plotted against the Ct and fitted with a linear regression mode (Suppl. Fig. 2). The efficiency of the primers was calculated at 115 % for *P. olseni* and 106 % for *P. chesapeaki*.

The two methods yield different profiles to increasing parasite concentration: qPCR assays revealed quantitative linearity over the dynamic range ($R^2$ = 0.9968 and *p*-value < 0.001 for *P. olseni* and $R^2$ = 0.9982 and *p*-value < 0.001 for *P. chesapeaki*), when dPCR assays show a logarithmic profile from 2.5 × 10¹ to 2.5 × 10⁷ cp.µL⁻¹ ($R^2$ = 0.9582 and *p*-value < 0.001 for *P. olseni* and $R^2$ = 0.9712 and *p*-value < 0.001 for *P. chesapeaki*). A saturation in the dPCR curve was observed at concentrations ≥ 8.5 × 10⁴ cp.µL⁻¹, as indicated by the manufacturer (Fig. 1).

Using this standard curve, the Limit of Detection (LOD) for qPCR assays was established at 35.66 cp.µL⁻¹ for *P. olseni* and 33.11 cp.µL⁻¹ for *P. chesapeaki*; below this threshold, triplicates yielded non-reproducible Ct values. For dPCR assays, the LOD was established at 31.93 cp.µL⁻¹ for *P. olseni* and 36.98 cp.µL⁻¹ for *P. chesapeaki*.

For both *P. olseni* and *P. chesapeaki* standard curves, a discrepancy was observed between dPCR and qPCR results, with dPCR assays showing underestimated values as the plasmid concentration increased from concentrations as low as 2.5 × 10³ cp.µL⁻¹ for *P. olseni* and for *P. chesapeaki* (Wilcoxon paired-test, *p*-values < 0.01).

## 3.3. Inhibitory effects of clam gDNA in dPCR assays

*Perkinsus*-free clams from Carantec sampling site were chosen based on the results of RFTM analysis, which confirmed the absence of *Perkinsus* spp. infection.

For *P. olseni* and for *P. chesapeaki* plasmid DNA supplemented with *Perkinsus*-free host gDNA concentrations of 20 and 30 ng.µL⁻¹, there were no significant differences from the dPCR standard curve. However,
<figure><img src="image_2.png" /><figcaption>**Fig. 1.** Comparison of ITS rDNA copy numbers, determined from the standard curve, calculated using qPCR and dPCR for *P. olseni* (A) and *P. chesapeaki* (B). The standard curves were generated using 10-fold serial dilutions of *P. olseni* and *P. chesapeaki* plasmids, and the theoretical copy numbers were plotted against the calculated copy numbers obtained using qPCR and dPCR. The qPCR data are represented by purple lines, with R² values of 0.9968 for *P. olseni* and 0.9982 for *P. chesapeaki*. The dPCR data are shown by green lines, with R² values of 0.9582 for *P. olseni* and 0.9712 for *P. chesapeaki*. The shaded green area indicates the saturation of dPCR, where the curve flattens at concentrations above 8.5 × 10⁴ cp.µL⁻¹. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>

from 40 ng.µL⁻¹, significant differences from the standard curve are observed for both parasites. (Fig. 2; ANCOVA, F = 90.394, p-value < 0.05 for *P. olseni* and F = 77.152, p-value < 0.05 for *P. chesapeaki* and Emmeans test Bonferroni correction, p-value < 0.05).

### 3.4. Comparison case study of *P. olseni* and *P. chesapeaki* parasite prevalence and intensity of infection in clam tissue samples using dPCR and qPCR assays

Using the LOD parameters established for qPCR and dPCR assays (i. e., above 35.66 cp.µL⁻¹ for *P. olseni* and 33.11 cp.µL⁻¹ for *P. chesapeaki* for qPCR and above 31.93 cp.µL⁻¹ for *P. olseni* and 36.98 cp.µL⁻¹ for *P. chesapeaki* for dPCR), the prevalence and intensity of infections of both parasites were evaluated in Arcachon Bay, known as a site with

high intensity of infection, and in Noirmoutier, known as a site with low intensity of infection.

#### 3.4.1. A high infection intensity site: the case of Arcachon Bay

For the detection of *P. olseni* single-infections, 23 clams out of 49 were identified as positive by both methodologies. The prevalence of *P. olseni* single infections was 57.1 % (n = 28/49) using qPCR and 51.0 % (n = 25/49) using dPCR assays (Table 2). Four samples were detected as positive by qPCR but negative by dPCR, while two samples were detected as negative by qPCR but positive by dPCR. Samples detected as positive by one method but not the other generally had infection intensity values very close to the LOD.

The mean infection intensity was 1.27 × 10⁷ ± 1.62 × 10⁷ cp.g⁻¹ of wet tissue for qPCR and 9.09 × 10⁶ ± 1.12 × 10⁷ cp.g⁻¹ of wet tissue for

<figure><img src="image_3.png" /><figcaption>**Fig. 2.** Inhibitory effects induced by five concentrations of gDNA from the gill tissue samples (20 ng.µL⁻¹ in purple, 30 ng.µL⁻¹ in blue, ng.µL⁻¹ in blue-green, 50 ng.µL⁻¹ in green and 80 ng.µL⁻¹ in yellow) in comparison of no-inhibitory effects (0 ng.µL⁻¹ in red) for (A) *P. olseni*-plasmids and (B) *P. chesapeaki*-plasmids dilution using dPCR assays. Significant differences are observed from 40 ng.µL⁻¹ for both parasites (ANCOVA, F = 90.394, p-value < 0.05 for *P. olseni* and F = 77.152, p-value < 0.05 for *P. chesapeaki*). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>
<table><caption>**Table 2**
Prevalence and infection intensities for *P. olseni* single-infection, *P. chesapeaki* single-infection and co-infection of both *Perkinsus* spp. in Noirmoutier and in Arcachon.</caption><thead><tr><th>Site</th><th>Method</th><th>Prevalence of <em>P. olseni</em> single infections</th><th>Mean intensity of single infection of <em>P. olseni</em></th><th>Prevalence of <em>P. chesapeaki</em> single infections</th><th>Mean intensity of single infection of <em>P. chesapeaki</em></th><th>Prevalence of co-infection</th><th>Mean intensity of co-infection of <em>P. olseni</em> and <em>P. chesapeaki</em></th></tr></thead><tbody><tr><td rowspan="2">Noirmoutier</td><td>dPCR</td><td>19.6 %</td><td>2.06 × 10<sup>7</sup> ± 4.70 × 10<sup>7</sup> cp.g<sup>-1</sup> of wet tissue</td><td>0 %</td><td>/</td><td>6.5 %</td><td>1.44 × 10<sup>6</sup> ± 1.45 × 10<sup>6</sup> and 1.21 × 10<sup>7</sup> ± 1.97 × 10<sup>7</sup> nb. of cp.g<sup>-1</sup> of wet tissue</td></tr><tr><td>qPCR</td><td>2.2 %</td><td>1.62 × 10<sup>8</sup> nb. of cp.g<sup>-1</sup> of wet tissue</td><td>0 %</td><td>/</td><td>0 %</td><td>/</td></tr><tr><td rowspan="2">Arcachon</td><td>dPCR</td><td>51 %</td><td>9.09 × 10<sup>6</sup> ± 1.12 × 10<sup>7</sup> cp.g<sup>-1</sup> of wet tissue</td><td>0 %</td><td>/</td><td>2 %</td><td>6.42 × 10<sup>6</sup> and 2.75 × 10<sup>6</sup> cp. g<sup>-1</sup> of wet tissue</td></tr><tr><td>qPCR</td><td>57.1 %</td><td>1.27 × 10<sup>7</sup> ± 1.62 × 10<sup>7</sup> cp.g<sup>-1</sup> of wet tissue</td><td>0 %</td><td>/</td><td>0 %</td><td>/</td></tr></tbody></table>

dPCR assays, and the differences between the two methodologies was statistically significant (Fig. 3; pairwise Wilcoxon rank sum test, *p*-value < 0.05). In contrast, no single-infection with *P. chesapeaki* was identified using either methodology. Finally, none of the qPCR samples showed the genetic signature of a co-infection of both *P. olseni* and *P. chesapeaki* parasites, whereas one sample was identified as positive for both parasites using the dPCR methodology (prevalence = 2.0 %, n = 1/49). Infection intensities in this sample were 174.35 cp.µL⁻¹ for *P. olseni* and 74.71 cp.µL⁻¹ for *P. chesapeaki*, which corresponds to infection intensities of 6.42 × 10⁶ and 2.75 × 10⁶ cp.g⁻¹ of wet tissue, respectively (Table 2).

The concordance between dPCR and qPCR results for detecting *P. olseni* in gill tissue samples in Arcachon Bay was 87.76 %. Additionally, the κ-value for *P. olseni* detection, calculated to assess the agreement between the two methodologies, was 0.7529, indicating substantial agreement (Table 3). Given the low prevalence of *P. chesapeaki* infection, the concordance and κ-value could not be calculated for this parasite.

### 3.4.2. A low infection intensity site: the case of noirmoutier

The prevalence of *P. olseni* single-infections estimated using qPCR was 2.2 % (n = 1/46), and 19.6 % (n = 9/46) using dPCR. The infection intensity of the only sample detected as positive in both methods was

<figure><img src="image_4.png" /><figcaption>**Fig. 3.** Comparison of infection intensities obtained by dPCR and qPCR on Arcachon samples determined positive for *P. olseni* by both methods.</figcaption></figure>

<table><caption>**Table 3**
Discordance, concordance and Kappa coefficient between qPCR and dPCR as-says on Noirmoutier and Arcachon samples.</caption><thead><tr><th>Site</th><th>Discordance (%)</th><th>Concordance (%)</th><th>Kappa coefficient (K)</th></tr></thead><tbody><tr><td>Noirmoutier</td><td>21.74</td><td>78.26</td><td>0.1321</td></tr><tr><td>Arcachon</td><td>12.24</td><td>87.76</td><td>0.7529</td></tr></tbody></table>

9.30 × 10³ cp.µL⁻¹ by qPCR and 8.19 × 10³ cp.µL⁻¹ by dPCR, corresponding to 1.62 × 10⁸ and 1.42 × 10⁸ nb. of cp.g⁻¹ of wet tissue, respectively. For the other 8 samples positive for *P. olseni* in dPCR, the mean infection intensity was 2.56 × 10² ± 4.82 × 10² cp.µL⁻¹, representing 5.35 × 10⁶ ± 1.19 × 10⁷ nb. of cp.g⁻¹ of wet tissue (Table 2).

For *P. chesapeaki* single-infection detection, no positive sample was identified using either methodology.

All samples were negative for *P. olseni* and *P. chesapeaki* co-infection detection by qPCR. In contrast, three samples, representing a prevalence of 6.5 % (n = 3/46), were positive to both parasites using dPCR, with a mean of infection intensity of 1.22 × 10² ± 1.38 × 10² cp.µL⁻¹ for *P. olseni* and 7.73 × 10² ± 1.23 × 10³ cp.µL⁻¹ for *P. chesapeaki* (1.44 × 10⁶ ± 1.45 × 10⁶ and 1.21 × 10⁷ ± 1.97 × 10⁷ nb. of cp.g⁻¹ of wet tissue, respectively) (Table 2). Of the three samples co-infected by *P. olseni* and *P. chesapeaki*, one presented a higher concentration of *P. olseni* (3.10 × 10⁶ nb. of cp.g⁻¹ of wet tissue for *P. olseni* vs. 8.01 × 10⁵ nb. of cp.g⁻¹ of wet tissue for *P. chesapeaki*), one had a higher concentration of *P. chesapeaki* (8.05 × 10⁵ nb. of cp.g⁻¹ of wet tissue for *P. olseni* vs. 3.48 × 10⁷ nb. of cp.g⁻¹ of wet tissue for *P. chesapeaki*), and one had similar infection intensity for both parasites (4.17 × 10⁵ nb. of cp.g⁻¹ of wet tissue for *P. olseni* vs. 6.64 × 10⁵ nb. of cp.g⁻¹ of wet tissue for *P. chesapeaki*).

The concordance between dPCR and qPCR results for detecting *P. olseni* in gill tissue samples was 78.26 %. Additionally, the κ-value, calculated to assess the agreement between the two methodologies, was 0.1321, indicating low agreement (Table 3). Given the low prevalence of *P. chesapeaki* infection in Noirmoutier, neither the concordance nor the κ-value could be calculated.

## 4. Discussion

Monitoring and characterizing parasitic protists affecting wild and cultured shellfish has become crucial in the context of global environmental changes. Their rapid identification and quantification are necessary to evaluate the emergence or re-emergence of harmful parasitic species. DNA-based diagnostic methodologies, particularly qPCR and dPCR, offer promising tools for detecting and quantifying these pathogens. Here, we provide a comparison of both assays for detecting *Perkinsus olseni* and *Perkinsus chesapeaki* in two different infection contexts, focusing on performance, sensitivity, and application of these methods for Perkinsosis disease monitoring in natural populations.
## 4.1. Performance of qPCR and dPCR for quantification

Following the Minimum Information for Publication of Quantitative Real-Time PCR experiments (MIIQE) (Bustin, 2010) and the Minimum Information for Publication of Quantitative Digital PCR Experiments (dMIIQE) guidelines (Huggett and Whale, 2013), we provide here a comparison of performances of qPCR and dPCR assays. To do so, we firstly adapted the parameters established by Itoïz et al. (2021) for qPCR to dPCR assays.

Our results revealed both strengths and limitations in the use of qPCR and dPCR methodologies for parasite quantification. A notable limitation of the dPCR system is its saturation at high DNA concentrations, as indicated by the manufacturer, with the upper limit observed at $8.5 \times 10^4$ cp.µL$^{-1}$. Although the dPCR assay maintains linearity up to $2.5 \times 10^5$ cp.µL$^{-1}$, an underestimation of parasite DNA concentration was detected starting from $2.5 \times 10^3$ cp.µL$^{-1}$. Indeed, for *P. olseni* quantification, the underestimation compared to qPCR assay goes from 13.9 % at $2.5 \times 10^3$ cp.µL$^{-1}$ to 17.8 % at $2.5 \times 10^7$ cp.µL$^{-1}$. For *P. chesapeaki* quantification, the underestimation goes from 8.8 % at $2.5 \times 10^3$ cp.µL$^{-1}$ to 18.6 % at $2.5 \times 10^7$ cp.µL$^{-1}$. This limitation suggests that dPCR is less suited for samples with high infection intensities ($> 10^3$ cp.µL$^{-1}$, corresponding to ca. $10^6-10^7$ cp.g$^{-1}$ of wet tissue.) These *Perkinsus* spp. DNA concentrations, potentially leading to mortality events depending on abiotic conditions, i.e. increasing temperature (Waki and Yoshinaga, 2013), were noticed in Arcachon Bay samples, where qPCR is thus preferable to avoid underestimation of parasite load.

For samples with lower infection levels (ranging from $10^1$ to $10^2$ cp.µL$^{-1}$), dPCR demonstrated a higher reliability in quantifying parasite DNA compared to qPCR. This underscores the suitability of dPCR for detecting low-intensity infections, particularly where qPCR may yield false negatives. Numerous studies have suggested that dPCR methodology is more sensitive than qPCR assay particularly for detecting low-abundance targets (Lei et al., 2020; Lewin et al., 2020; Li et al., 2018). These results underscore the advantages of dPCR assays, especially their potential application in parasitology, owing to their superior precision and sensitivity.

## 4.2. Influence of PCR inhibitors

Results obtained under controlled conditions using plasmid standards may differ when applied to environmental samples because such samples often contain PCR inhibitors that can reduce assay efficiency and sensitivity (Umeda and Yoshinaga, 2012). The comparison of qPCR and dPCR methodologies was performed using the ITS gene sequence ligated into a vector (Dhanasekaran et al., 2010; Itoïz et al., 2021), to detect the genetic signatures of *P. olseni* and *P. chesapeaki*.

Our results, based on varying gDNA concentrations extracted from clam gills (Fig. 2), demonstrated that inhibitory effects significantly affect detection by dPCR for clam gDNA concentrations as low as 40 ng.µL$^{-1}$ for both *P. olseni* and *P. chesapeaki*. While dPCR exhibited greater resistance to inhibitors compared to qPCR (threshold at 20 ng.µL$^{-1}$), it remains susceptible under certain conditions, particularly with complex matrices. Complete inhibition was observed at higher concentrations, emphasizing that dPCR, although more robust, is not entirely immune to PCR inhibitors in challenging matrices such as clam tissues.

In clam tissues, inhibitors are particularly abundant, making the detection of *Perkinsus* spp. especially difficult (Itoïz et al., 2021). For qPCR, inhibitory effects can be minimized when the clam tissue concentration is maintained at a maximum of $20 \times 10^4$ cp.µL$^{-1}$ of gDNA extracted from the gills or digestive gland, which are less likely to contain PCR inhibitors within the detection limits of qPCR (Itoïz et al., 2021; Umeda and Yoshinaga, 2012). However, diluting the genomic DNA to meet this low concentration threshold could result in some low-parasitized samples being classified as negative, thus reducing the sensitivity of parasite detection and underestimating the prevalence of *Perkinsus* spp. infections. An alternative approach could involve the use of PCR anti-

inhibitor reagents, which are often incorporated into commercial kits to remove inhibitors during sample preparation. However, complete removal of inhibitors is rarely achieved (Rieder et al., 2024) and such reagents can lead to DNA loss, potentially resulting in the underestimation of parasite infection intensity or an increase in false-negative results (Kreader, 1996; Rieder et al., 2024). Optimization of anti-inhibitor protocols for mollusk samples has not yet been successfully achieved, further complicating their application to accurately detect and quantify *Perkinsus* spp. in a complex host matrix. This issue is particulary pertinent as numerous other shellfish species contain PCR inhibitors (Berthe et al., 1999; Blackstone et al., 2003), such as oysters (*Crassostrea gigas*, *Ostrea edulis*), mussels (*Mytilus edulis*, *Pinna nobilis*) (Lees et al., 1994; López-Sanmartín et al., 2019) and scallops (*Argopecten irradians*, *Chlamys farreri*, *Mizuhopecten yessoensis*) (Mao et al., 2013), which complicates the detection and quantification of many of their micro-parasites.

## 4.3. Comparison in natural populations

### 4.3.1. Arcachon Bay

We compared qPCR and dPCR assays for the detection of *Perkinsus olseni* and *Perkinsus chesapeaki* genetic signatures in clam gill tissue samples in natural populations of *Ruditapes* spp. from Arcachon Bay (Table 2).

The prevalence obtained by the two methods was similar as shown by the high percentage of the concordance coefficient, even though some samples were determined as positive by one methodology and negative by the other. This may be explained by the fact that the infection intensity values of these samples were very close to the LOD, which differs between the two methodologies.

Regarding measured infection intensities, there were significant differences between qPCR and dPCR assays, with the dPCR method underestimating infection level at high parasite concentration as compared to the qPCR (Fig. 3). It points towards the preferred usage of qPCR in samples with high infection intensity sites such as Arcachon Bay. That said, our dPCR assay was the only method able to detect one co-infected sample as positive, perhaps due to the fact that this specific sample had a low infection intensity for both parasites.

It should also be pointed out that our present results differ markedly from those of Itoïz et al. (2024), who reported a much higher prevalence of *P. chesapeaki* (24 %) than observed in the present study (2 %). However, these results should be interpreted with caution, as we quantified prevalence only in gill tissue samples, whereas Itoïz et al. (2024) analyzed the whole body. Furthermore, the dynamics of infection and co-infection by *P. chesapeaki* and *P. olseni* remain unexplored and may explain the discrepancies in prevalence between the two species.

We therefore recommend the routine use of qPCR, with the complementary use of dPCR for doubtful samples.

### 4.3.2. Noirmoutier

The results for the detection of *Perkinsus olseni* and *P. chesapeaki* genetic signatures in clam gill samples were quite different in the case of natural populations of *Ruditapes* spp. from Noirmoutier (Table 2). For *P. olseni* single detection, we noted a low agreement between qPCR and dPCR results ($κ = 0.1321$). Interestingly, the prevalence of *P. olseni* single-infections detected by dPCR was almost ten times higher than those observed by qPCR, and the only sample identified as positive for *P. olseni* single-infection by qPCR had the highest infection intensity measured in Noirmoutier. Coupled with the fact that samples detected as positive for *P. olseni* solely by dPCR assays presented a much lower mean infection intensity, these results highlight that dPCR is more sensitive than qPCR for detecting the presence of parasites at low concentrations. The use of dPCR may reduce false negatives and refine the prevalence and intensity of infection in clam populations previously considered *Perkinsus*-free.
Regarding the detection of *P. chesapeaki* single-infections, neither method detected the genetic signature of this parasite alone in *Ruditapes* spp., which is consistent with results from a previous study on *R. philippinarum* from Arcachon Bay, where single-infections of *P. chesapeaki* were identified only as cryptic (Itoïz et al., 2024).

Interestingly, our results revealed rare co-infections by both para-
sites *P. olseni* and *P. chesapeaki* in our samples, but only using dPCR. Two
out of the three co-infected samples identified by dPCR in our study
showed an overrepresentation of the genetic signature of *P. olseni*
compared to *P. chesapeaki*, consistent with previous studies on
*R. decussatus* in Leucate Lagoon (French Mediterranean Sea), and on
*R. philippinarum* from Arcachon Bay (Arzul et al., 2012; Itoïz et al.,
2024). The concentrations of *P. olseni* in the co-infected samples iden-
tified in our study were moderate and similar to those found in single-
infections, consistent with findings by Itoïz et al. (2024) which re-
ported that 98 % of co-infected hosts exhibited moderate *P. olseni*
infection intensities.

The choice between qPCR and dPCR is ultimately dependent on the local infection context, with each method offering distinct advantages. While qPCR may quantify more accurately at higher infection intensities, relevant for studies of host-parasite dynamics, dPCR is generally better suited for surveillance purposes such as early detection or for confirming the absence of parasitic genetic signature detection, due to its superior sensitivity at low infection levels.

5. Conclusions

This study provides the first evidence of *Perkinsus* spp. genetic sig-
natures in *Ruditapes* spp. clams harvested from Noirmoutier, and iden-
tifies co-infection between these two parasitic species in a site previously
thought to be exempt of these events. Our results demonstrate that dPCR
may be significantly more sensitive than qPCR for detecting parasite
genetic signatures in low-intensity infection samples, that might reduce
false negatives. Conversely, for highly infected samples, dPCR assays
may underestimate the genetic signature concentration for both para-
sites due to saturation. This issue could be mitigated by further diluting
the samples. However, dilution can introduce significant biases in DNA
quantification, especially when the dilution factor is large (Multinu
et al., 2018).

Accurate detection and quantification of parasite infections are
essential for monitoring the health of clam populations and assessing the
potential risks posed by emerging diseases. These findings provide
baseline data for understanding the epidemiology of *Perkinsus* infections
in two sites on the French Atlantic Coast in the context of climate change
and its impacts on aquaculture. Continued surveillance and detailed
organ-specific analyses will be crucial for elucidating the dynamics of
co-infections and informing management strategies.

CRediT authorship contribution statement

**Elisa Chailler:** Writing – original draft, Methodology, Data curation, Writing – review & editing, Validation, Formal analysis, Visualization, Investigation, Conceptualization. **Héliaz Le Bayon:** Investigation, Writing – review & editing, Data curation. **Annabelle Dairain:** Methodology, Writing – review & editing, Formal analysis. **Florentine Riquet:** Writing – review & editing, Formal analysis. **Leslie Stout:** Review & editing. **Aurélie Chambouvet:** Visualization, Supervision, Project administration, Data curation, Writing – review & editing, Validation, Methodology, Funding acquisition, Resources, Investigation, Conceptualization. **Morgan Smits:** Formal analysis, Writing – review & editing, Investigation, Methodology, Conceptualization.

Declaration of competing interest

The authors declare that they have no known competing financial
interests or personal relationships that could have appeared to influence

the work reported in this paper.

Acknowledgements

EC was funded by a French doctoral research grant from Ecole
Doctorale Sciences de la nature et de l'Homme: évolution et écologie
(ED227 MNHN-SU). MS was funded by SAD region Bretagne
(N°23007142). HLB was funded by Région Bretagne (ARED, POLEMIC)
and by ANR project JCJC PANIC (2022-2027) (ANR-21-CE02-0025).
This work was also supported by the the French National program
EC2CO (Ecosphère Continentale et Côtière) projects, THRAUSTO
(No13046) and EPATANT (N°18726). The authors would like to thank
Claire Daguin-Thièbaut and Gwenn Tanguy for their contribution to
digital PCR acquisition at the Genomer platform at Station Biologique de
Roscoff, EMBRC-France partner core facility, member of Biogenouest.
This operation was supported by EMBRC-France and AO-EMBRC, whose
French state funds are managed by the ANR within the "Investments of
the Future" program under reference ANR-10-INBS-0 and ANR-21-
ESRE-0038. The authors also would like to thank Odile Bouyer and
Xavier de Montaudouin for their precious help in the sampling of
Noirmoutier and Arcachon Bay clams, respectively, and Camille Poirier
for reviewing this manuscript. In Arcachon Bay, samples were per-
formed with Planula 4 vessel (CNRS-INSU, Flotte Oceanographique
Française).

The funders had no role in study design, data collection and analysis,
decision to publish, or preparation of the manuscript.

**Appendix A. Supplementary data**

Supplementary data to this article can be found online at https://doi.
org/10.1016/j.jip.2025.108417.

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