### 2.7.5. Inter-assay precision and accuracy (reproducibility)

The inter-group accuracy and precision were determined by the injection of a calibration curve per day, at three different days. Each calibration curve was composed of the 6 concentration levels. The means, the standard deviations, the coefficients of variation (%CV) and the percent deviations of the back calculated concentrations (%bias) were calculated for each standard level. The coefficient of variation of the 3 injections of each level should be inferior to 15%. The back calculated concentration of each level had to be within 15% deviation from the nominal value.

### 2.7.6. Matrix effect

Crude extracts of *Trichoderma longibrachiatum* (MMS151) were spiked before LC/MS analyses with different concentrations of standard solutions to have final concentrations of 0.19, 0.38 and 0.75 µg/mL. Linear regressions were applied to model relative chromatographic areas vs concentrations. These regressions took in consideration the presence of matrix in standard solutions and in order to highlight matrix effect they were compared to the regressions obtained with standards in methanol (0.25, 0.50 and 1.00 µg/mL).

## 2.8. Evaluation of the sample preparation

The choice of the extracting solvents was done after different tests and by the comparison of the peptaibol extraction levels from the fungal biomass of the cultured strain *T. longibrachiatum* (MMS 151). The solvent or solvent mixtures involved in the extraction tests were: MeOH/CH₂Cl₂ (1:1, v/v), ethyl acetate, n-butanol, acetone/CH₃COOH 1% and CH₂Cl₂/ethyl acetate (1:1, v/v). The better solvent or solvent mixture was then used for the determination of the sample recoveries and all the other experiments.

The recovery of the extraction protocol was determined for the shortest and the longest-chain peptaibols, i.e., PEP-11 and PEP-20. The fungal biomass of a *T. longibrachiatum* cultured strain (MMS 151) was separated in 3 equivalent parts (considered as triplicates) and they were spiked with both standards. The peptaibols were added in order to find a final concentration of 1.00 µg/mL in the sample, considering 100% of recovery. After the biomass extraction and the sample preparation, the concentrations of both standards in the *Trichoderma* crude extracts were determined in the triplicates using the corresponding calibration curves and the recovery values were calculated.

## 2.9. Application of the validated quantification methods

The quantification of the different peptaibol subgroups were realized by summing the relative areas of chromatogram peaks obtained with the characteristic ions of each subgroup, then, by determining the corresponding concentrations with the external calibration curve.

### 2.9.1. Peptaibol production kinetic study

The fungal strain MMS151 (*T. longibrachiatum*) was chosen to study the peptaibol production kinetic because it is a strain producing the shortest—and longest-chain peptaibols, i.e., 11- and 20-residue peptaibols. This strain were cultured in 36 Petri dishes (10-cm diameter) containing DCA medium. The fungal cultures were harvested in 3 dishes at several times of culture (2,-7, 9, 11, 14, 17, 20, 23 days). Then, the crude extracts and peptaibols were obtained and analyzed respectively as mentioned above. The optimal culture time for peptaibol production will be determined.

### 2.9.2. Peptaibol production study by Trichoderma sp.

Crude extracts of twelve marine-derived and one commercial *Trichoderma* strains were obtained after a culture time of 9 days.

These stains were selected to represent a wide panel of characteristic ions of the peptaibol subgroups shown in Table 2. Extraction, sample preparation and analyses were performed as explained above. The peptaibol production of these stains will be determined according to the length of chain of peptaibols by the LC-MS validated methods.

# 3. Results and discussion

## 3.1. Method validation

### 3.1.1. Specificity

No chromatographic peaks of characteristic ions of PEP-11, PEP-14 and PEP-20 were detected at their respective retention times in methanol.

### 3.1.2. Linearity

The linear regressions, the slopes, the y-intercepts and the determination coefficients ($R^2$) for each standard (PEP-11, PEP-14 and PEP-20) are shown in Fig. 1.

The $R^2$ values calculated for the 3 standards were higher than 0.98. They are consequently considered as acceptable since the linear regressions were built with 3 different injections of calibration levels. Moreover, variance analyses validated the linear models of the three regressions performed with PEP-11, PEP-14 and PEP-20. The same results were observed for all of them: $F_{reg} < F_{table}$ with $p < 0.0001$ => significant regression and $F_{nl} > F_{table}$ with $p < 0.0001$ => the linear model can be applicable. The responses relative area/concentration were different according to the length of the peptaibol standards. These differences were probably due to different ionization of the standards. The ionization of the peptaibols seems to decrease with the length of their residue chain, leading to a quantification method sensitivity of 11-residue peptaibol (PEP-11) significantly higher than those of the longer peptaibols (14- and 20- residue). Then, the quantification method sensitivity is higher for 14-residue peptaibols compared to 20-residue peptaibols but the difference is not as great as compared to 11- residue peptaibols. These results show that an appropriated calibration is needed in function of the peptaibol chain length. The calibration curve of PEP-20 was chosen to quantify the 17-20-residue peptaibols. It seemed to be more adapted since all the longest peptaibols present structural similarities compared to the shortest ones. For example, shortest peptaibols (11-14-residues) contain more proline residues than longest ones (17-20-residues) leading to a structural deformation [34].

### 3.1.3. LOD and LOQ

The calculated LOD were respectively 0.05, 0.02 and 0.06 µg/mL for PEP-11, PEP-14 and PEP-20. The LOQ values were determined as 0.16, 0.07 and 0.22 µg/mL for PEP-11, PEP-14 and PEP-20 respectively. Considering the better sensitivity of PEP-11 quantification method, the obtained LOD an LOQ values seemed high compared to the others. Nevertheless, these results could be attributed to a higher y-intercept for PEP-11 regression probably due to a higher noise of the corresponding target ion.

### 3.1.4. Intra- and inter-assay precisions and accuracies

Results of intra- and inter-assay precisions and accuracies are given in Table 3. Concerning intra-assay results, the maximum %CV were 6%, 8% and 12%, respectively for PEP-11, PEP-14 and PEP-20. The back-calculated concentrations were within 5%, 7% and 10% of the nominal concentration for all levels of PEP-11, PEP-14 and PEP-20 respectively. About inter-assay results, the maximum %CV were 7%, 11% and 15% for PEP-11, PEP-14 and PEP-20, respectively. The mean percentage deviation of the back calculated concentra-
<figure><img src="image_68.png" /><figcaption>**Fig. 1.** Linear regressions, equations and determination coefficients of external calibration curves of PEP-11, PEP-14 and PEP-20, respectively 11-, 14- and 20-residue peptaibols injected in triplicates.</figcaption></figure>

<table><caption>**Table 3**

Results of intra- and inter-assay precisions and accuracies of the LC-MS methods develop to quantify peptaibols in *Trichoderma* crude extracts.</caption><thead><tr><th rowspan="2">Analyte</th><th rowspan="2">Nominal concentration (µg/mL)</th><th colspan="3">Intra-assay (n = 6)</th><th colspan="3">Inter-assay (n = 3)</th></tr><tr><th>Mean calculated concentration ± SD (µg/mL)</th><th>Accuracy (%bias)</th><th>%CV</th><th>Mean calculated concentration ± SD (µg/mL)</th><th>Accuracy (%bias)</th><th>%CV</th></tr></thead><tbody><tr><td rowspan="5">PEP-11</td><td>0.25</td><td></td><td></td><td></td><td>0.26 ± 0.03</td><td>8</td><td>7</td></tr><tr><td>0.50</td><td>0.51 ± 0.04</td><td>5</td><td>6</td><td>0.52 ± 0.02</td><td>4</td><td>5</td></tr><tr><td>0.75</td><td>0.74 ± 0.05</td><td>5</td><td>6</td><td>0.79 ± 0.04</td><td>5</td><td>5</td></tr><tr><td>1.00</td><td>1.01 ± 0.06</td><td>5</td><td>6</td><td>1.05 ± 0.01</td><td>2</td><td>2</td></tr><tr><td>1.25</td><td></td><td></td><td></td><td>1.21 ± 0.04</td><td>5</td><td>4</td></tr><tr><td rowspan="5">PEP-14</td><td>0.10</td><td></td><td></td><td></td><td>0.12 ± 0.00</td><td>6</td><td>9</td></tr><tr><td>0.25</td><td></td><td></td><td></td><td>0.25 ± 0.01</td><td>2</td><td>7</td></tr><tr><td>0.50</td><td>0.50 ± 0.03</td><td>5</td><td>7</td><td>0.48 ± 0.01</td><td>2</td><td>2</td></tr><tr><td>0.75</td><td>0.74 ± 0.05</td><td>7</td><td>8</td><td>0.70 ± 0.07</td><td>11</td><td>11</td></tr><tr><td>1.00</td><td>1.00 ± 0.04</td><td>4</td><td>5</td><td>1.05 ± 0.07</td><td>8</td><td>6</td></tr><tr><td rowspan="5">PEP-20</td><td>0.25</td><td></td><td></td><td></td><td>0.25 ± 0.02</td><td>8</td><td>11</td></tr><tr><td>0.50</td><td>0.51 ± 0.04</td><td>8</td><td>10</td><td>0.44 ± 0.03</td><td>7</td><td>8</td></tr><tr><td>0.75</td><td>0.74 ± 0.04</td><td>5</td><td>6</td><td>0.79 ± 0.10</td><td>15</td><td>12</td></tr><tr><td>1.00</td><td>1.01 ± 0.12</td><td>10</td><td>12</td><td>0.97 ± 0.02</td><td>2</td><td>15</td></tr><tr><td>1.25</td><td></td><td></td><td></td><td>1.27 ± 0.13</td><td>12</td><td>10</td></tr></tbody></table>

SD: standard deviation.

tions were within 8%, 11% and 15% of the nominal concentrations respectively for all levels of PEP-11, PEP-14 and PEP-20.

### 3.1.5. Matrix effect

The target ions of PEP-11 and PEP-20, respectively *m/z* = 1197 and 1004, were observed in the crude extract of *T. longibrachiatum*, as illustrated in Fig. 2A,C. About the characteristic ion of the standard PEP-11, this result was expectable since the same *m/z* was reported for 11-residue peptaibols produced by *Trichoderma* sp. Nevertheless, since PEP-11 and the 11-residue peptaibols had not the same sequences, they had not exactly the same retention time (RT). The relative area of the chromatographic peak at *m/z* = 1197 in the crude extract diluted by a factor 2 (RT = 13.24 min, Fig. 2A) represented 25% of the relative area obtained for the two peaks at *m/z* = 1197 in spiked crude extract at 0.75 µg/mL of PEP-11 (RT = 10.91 + 13.24 min, Fig. 2D). About the characteristic ion of PEP-20, the observed ion at *m/z* = 1004 in crude extract was not due to peptaibols produced by *Trichoderma* strains. The relative area of the chromatographic peak of *m/z* = 1004 (RT = 11.26 min, Fig. 2C) was under the method LOD. This unexpected response

could be due to the use of a low resolution mass spectrometer. It does not allow the differentiation of the PEP-20 characteristic ion (monocharged sodium adduct; *m/z* = 1004) and those of 20-residue peptaibols (monocharged sodium adduct; *m/z* = 1005).

About PEP-14, Fig. 2B compared to Fig. 2E show that ion at *m/z* = 1417 was not present in the crude extract since no chromatographic peak was detected. The linear regressions obtained with spiked crude extracts compared to those obtained with standards in methanol allow concluding that no matrix effects exist since the ratios between the slopes were lower than 5% (4%, 2% and 1% for PEP-11, PEP-14 and PEP-20, respectively). Since no matrix effect was revealed, the quantifications of strain production was performed with external calibration. Consequently, there is no peak from any standards which could lead to an error of quantification of strain production.

### 3.2. Evaluation of sample preparation

The calculated extraction efficiencies from the extracted peptaibols levels of *T. longibrachiatum* strain (MMS 151) showed that
<figure><img src="image_69.png" /><figcaption>**Fig. 2.** Chromatograms of crude extract of *Trichoderma longibrachiatum* (MMS 151) and standards (PEP-11, PEP-14 and PEP-20) in methanol (A and D: *m/z* = 1197; B and E: *m/z* = 1417; C and F: *m/z* = 1004).</figcaption></figure>

the more efficient solvent mixture for peptaibol extraction was MeOH/CH₂Cl₂ (1:1, v/v). The levels were about 3 times lower for acetone/CH₃COOH 1%, CH₂Cl₂/ethyl acetate (1:1, v/v) and n-butanol. With ethyl acetate, the extraction level was more than 6 times lower than with the best solvent mixture. Consequently, MeOH/CH₂Cl₂ (1:1, v/v) was chosen for the determination of sample recoveries as well as for all the other strain extractions. In order to extract a larger amount of peptaibols, the extraction were performed with 2 extraction steps involving increased polarity of solvent mixtures, i.e., MeOH/CH₂Cl₂ 1:2 then 2:1 (v/v), corresponding to a final proportion of 1:1.

Recovery values of extraction and sample preparation were 21.1 ± 5.4% and 31.5 ± 9.9% for PEP-11 and PEP-20, respectively. These values are not significantly different each other (Mann-Whitney test, *p* = 0.05). Consequently, whatever the peptaibol subgroups, the extractions could not be considered as different. Even though the recoveries of both standards were not optimal, they were quite consistent and reproducible. The molecules of interest could be lost during the distilled water wash or during the filtration step which would explain the low extraction recoveries. Nevertheless, in this study, the main application of these quantification procedures was to screen strains for their high production of peptaibols to use them as biological control agents. Consequently, peptaibols produced in low concentrations were not interesting. An optimization of the extraction recoveries could be needed to response to another problematic. Other solvent mixtures could lead to a better extraction, improving recovery yields.

### 3.3. Applications of the validated quantification methods

#### 3.3.1. Assignment of target ions to peptaibol subgroups

The assignment of target ions was achieved with the peptaibol clades and some sequences described in the literature. Nevertheless, some assignments need to be clarified.

Usually, 14-residue peptaibols are represented by characteristic ions with *m/z* lower than 1500 [35,36]. In the present study, *m/z* values of 1506, 1520 and 1534 were assigned to putative 14-residue peptaibols (Table 2) because they were observed in a *Trichoderma harzianum* strain, species usually producing 14- and 18-peptaibols [35]. This assignment will have to be confirmed by a sequencing of these observed ions.

In addition, there is an overlapping zone between the 19- and 20-residue peptaibol characteristic ions. But a *Trichoderma* strain seems not produce simultaneously 19- and 20-residue peptaibols [35,37]. Moreover, the peptaibol subgroup production by *Trichoderma* species can be reported in literature and/or determined by sequencing of the characteristic ions in mass spectrometry. Consequently, the individual quantification of 19- and 20-residue peptaibols is possible by low-resolution mass spectrometry.

#### 3.3.2. Peptaibol production kinetic study

The validated methods allowed the quantitative determination of peptaibol subgroups produced by *Trichoderma* sp. Consequently, they were quantified in *T. longibrachiatum* strain (MMS151) crude extracts during 23 days. MMS151 strain produces 11- and 20-residue peptaibols [38-40]. Using the quantification methods, 20-residue peptaibols appeared as singly charged [M + Na]⁺ and doubly charged [M + 2Na]²⁺ whereas 11-residue peptaibols appeared exclusively as singly charged sodium adducts as shown in Fig. 3.

The 11- and 20-residue peptaibols were quantified using the method achieved respectively with standards PEP-11 and PEP-20. Fig. 4 shows the mean of 11- and 20-residue peptaibol proportions in the fungal wet biomass of MMS 151 during the 23 days of the kinetic study. Fig. 4 shows that the trends of both peptaibol kinetic productions (11- and 20-residues) were similar. Before the 3rd day, the peptaibol productions were under the limit of quantification of the methods. Then, the productions began from the 3rd day to
<figure><img src="image_70.png" /><figcaption>**Fig. 3.** Mass spectrum of crude extract of *Trichoderma longibrachiatum* strain (MMS151).</figcaption></figure>

<figure><img src="image_71.png" /><figcaption>**Fig. 4.** Mean and standard deviation (n = 3) of 11- and 20-residue peptaibol subgroup proportions, normalized to the wet biomass, during the time.</figcaption></figure>

reach the maximum levels at the 9th day which corresponded to the beginning of a plateau until 23 days. At the 9th day of culture, 11- and 20-residue peptaibols represented 1.4% ± 0.2 and 2.3% ± 0.4 of the MMS 151 biomass, respectively.

The study of Mikkola et al. [26] also quantified peptaibols in a *T. longibrachiatum* crude extract by HPLC/ESI-IT-MS. They found two peptaibol subgroups, i.e., 11- and 20-residues, representing 0.02–0.16% and 0.5–2.6% of the wet biomass at 15 days of culture, respectively. The difference of strains and of broths used for cultures could explain the difference of results with the present study. Mikkola et al., used malt extract agar (MEA) as culture broth whereas MMS 151 was cultured on DCA medium. It is commonly accepted that the culture broth change can lead to a variation of the metabolite productions [41]. Moreover, they quantified some peptaibols and not the whole subgroups, with alamethicin as standard, whatever the peptaibol length.

A qualitative kinetic study of trichobrachin (11-residue peptaibol) production by *Trichoderma parceramosum*, cultivated on MEA medium, was previously achieved by thin layer chromatography (TLC) [42]. Trichobrachins-TBIII production presented a similar trend of 11- and 20-residue peptaibol productions with detection from the 2nd culture day and a maximum at the 5th culture day.

According to the results shown in Fig. 4, the optimal peptaibol production was obtained at the 9th day for *T. longibrachiatum* MMS151. From these results and in order to evaluate the peptaibol productions of the 12 other *Trichoderma* strains (see above), they were cultured during 9 days in DCA medium, even if their optimal peptaibol production time could be different.

### 3.3.3. Study of peptaibol production in *Trichoderma* crude extracts

Consequently, the peptaibol subgroups in crude extracts of different *Trichoderma* strains were quantified at the 9th day and the
<figure><img src="image_72.png" /><figcaption>**Fig. 5.** Proportions normalized to the wet biomass of peptaibol subgroups in 13 Trichoderma strains.</figcaption></figure>

results are shown in Fig. 5. The peptaibol subgroup productions fluctuated strain to strain. Usually, when 18-residue peptaibols were produced by some strains, 14-residue peptaibols were also produced. These results were also observed in a previous study [35]. The concerned strains were *T. harzianum* (MMS 13, MMS 1255 and T 22) and *Trichoderma pleuroticola* (MMS 1541), which belongs to the same phylogenetic clade [35,43]. Nevertheless, the productions of 14-residue and 18-residue peptaibols were sometimes too low to reach the LOD of the quantification method, respectively for MMS 13, MMS 1541 and MMS 1255. The peptaibols detected in T22 (*T. harzianum*) crude extracts were under the LOQ of the quantification method (not represented).

The same result was observed for 17-residue peptaibols which were produced together with 19-residue peptaibols by two *T. atroviride* (MMS 639 and MMS 927). An hypothesis was given by Carroux et al. [32], i.e., the 17-residue peptaibols could be truncated 19-residue peptaibols due to an error during the biosynthesis.

The *T. longibrachiatum* strains (MMS 151 and MMS 58) produced high proportions of 20-residue peptaibols. It was also observed for *Trichoderma reesei* (MMS 510), *Trichoderma ghanense* (MMS 975), *Trichoderma citrinoviride* (MMS 19) and *Trichoderma capillare* (MMS 755). From a phylogenetic point of view, these strains are close, i.e., in a same clade [35,43,44].

Concerning the biocontrol purpose, the most interesting strains were those producing long-chain peptaibols. The longest peptaibols are indeed able to form voltage dependent ion channels in the lipid membranes which can lead to the phytopathogen cell death [45]. Moreover, depending on the target pathogen, the peptaibol subgroups could have not the same efficiency. Consequently, the final aim of the quantification would be the selection of the *Trichoderma* strains according to their production of long-chain peptaibols (up to 17-residues). Three strains seemed interesting, i.e., MMS 151, MMS 639 and MMS 1541 for the respective production of 20-, 19- and 18-residue peptaibols. This selection of strains was only based on the peptaibol productions and other information has to be taken into account for their use of as biocontrol agents. For example, some *Trichoderma* species, such as *T. longibrachiatum*, are able to cause opportunistic infections in immunocompromised humans [46]. *T. harzianum* could produce mycotoxins [28]. Nevertheless, *Trichoderma* infection in human or animal are quite rare [2] and the use of purified peptaibol mixtures as biocontrol agents could be considered in order to avoid the potential mycotoxin presence.

## 4. Conclusion

LC-ESI/IT/MS methods were developed and validated for peptaibol subgroup quantification. The analytical responses of the peptaibols were depending on their lengths. The quantification of all the peptaibols by only one standard, classically alamethicin (20-residue peptaibols), may lead to errors, particularly on the shortest-chain peptaibol quantification.

These methods were successfully applied to study a peptaibol production kinetic and to quantify peptaibols in crude extracts produced by *Trichoderma* species. This study permitted to determine the optimal culture time of a *Trichoderma* strain (*T. longibrachiatum*, MMS151) at the 9th day. The different peptaibol subgroup productions were consequently quantified after 9 days of culture in crude extracts to select new potential biocontrol agents. A screening was performed to select the most peptaibol producing strains. However, metabolomics and dereplication studies will be needed to make sure that these marine-derived *Trichoderma* strains do not produce mycotoxins before their potential use as biocontrol agent. Nevertheless, to overcome this problem, the direct use of purified peptaibol subgroups as biocontrol agent could be considered.

## Acknowledgements

We are grateful to the platform ThalassOMICS of Biogenouest, to M. Thibault Robiou du Pont for his technical support, to the NABUCO program of the Ecophyto plan of the French Ministry for Agriculture and Food for funding and to the French Ministry for Education and Research for a PhD grant.

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# Factors influencing the microplastic contamination of bivalves from the French Atlantic coast: Location, season and/or mode of life?

<figure><img src="image_75.png" /></figure>

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Nam Ngoc Phuong<sup>a,b</sup>, Laurence Poirier<sup>a</sup>, Quoc Tuan Pham<sup>b</sup>, Fabienne Lagarde<sup>c</sup>, Aurore Zalouk-Vergnoux<sup>a,*</sup>

## ARTICLE INFO

**Keywords:**

Microplastics

Mussel

Oyster

Influencing factor

Qualitative and quantitative analysis

## ABSTRACT

Monitoring the presence of microplastics (MP) in marine organisms is currently of high importance. This paper presents the qualitative and quantitative MP contamination of two bivalves from the French Atlantic coasts: the blue mussel (*Mytilus edulis*) and the Pacific oyster (*Crassostrea gigas*). Three factors potentially influencing the contamination were investigated by collecting at different sampling sites and different seasons, organisms both wild and cultivated. Inter- and intra-species comparisons were also achieved. MP quantity in organisms was evaluated at 0.61 ± 0.56 and 2.1 ± 1.7 MP per individual respectively for mussels and oysters. Eight different polymers were identified. Most of the MPs were fragments; about a half of MPs were grey colored and a half with a size ranging from 50 to 100 µm for both studied species. Some inter-specific differences were found but no evidence for sampling site, season or mode of life effect was highlighted.

## 1. Introduction

Plastics have changed our life since their appearance in the middle of the last century (Thompson et al., 2009). They are massively used as they replaced traditional materials due to their multiple advantages. Actually, their worldwide production is increasing, reaching > 300 million tons last years (PlasticsEurope, 2015). In contrast, many da- mages by plastic wastes to ecosystems were observed and reported (Cole et al., 2011; Gall and Thompson, 2015) due to lacks in plastic waste management faced to the increase of plastic uses. A recent work of Jambeck et al. (2015) estimated that approximately 4.8 to 12.7 million tons of plastic wastes entered the ocean only in 2010.

Besides, plastic wastes are known as the main source of micro- plastics (MPs) which were defined as plastics with a size inferior to 5 mm by Arthur et al. (2009). The fragmentation of plastic wastes oc- curring in the environment and leading to MPs is due to mechanical, chemical and biological factors (Andrady, 2011; Costa et al., 2010; Zettler et al., 2013) and corresponds to the secondary source of con- tamination. The primary contamination of MPs is characterized by the microspheres used in the industry, in the personal care products for example. Because of their small size and their properties, MPs can be accumulated in the environment leading to a potential MP exposure of biota undergoing bioaccumulation and biological effects (Barnes et al.,

2009; Wright et al., 2013). The occurrence of MPs was reported in continental environments: air (Gasperi et al., 2015), freshwater (Dris et al., 2015b; Free et al., 2014; Jambeck et al., 2015), wastes and treated waters (Dris et al., 2015a), lake sediments (Fischer et al., 2016) and soil organisms (Huerta Lwanga et al., 2016; Rillig, 2012). Nu- merous studies focused also on marine environments, studying sea- water (Cózar et al., 2015; Desforges et al., 2014; Van Cauwenberghe et al., 2015); sand and sediment (Blaskovic et al., 2017; Graca et al., 2017; Woodall et al., 2014) and many marine animals (Besseling et al., 2015; Desforges et al., 2015; Karami et al., 2017). In marine ecosys- tems, many species of invertebrates are known to accumulate con- taminants from seawater and marine sediments, representing valuable biological indicators of environmental pollution (Kaiser, 2001). Among these species, benthic suspension-feeding bivalves, such as mussels or oysters, have been widely used in biomonitoring surveys in coastal waters (e.g. the Mussel Watch program; Farrington et al., 1995; RNO, 2006), on account of their abundance and broad distribution, their suspended particle filter-feeding mode, their sedentary living and their importance for human food web. As for chemical hazards, these species may be good indicators of MP contamination in the water column (Avio et al., 2017). Published studies presenting data on MP contamination in marine bivalves are scarce at this moment even if many of them are currently performed. Comparisons are furthermore debatable because

<footnote><sup>a</sup> Laboratoire Mer, Molécules, Santé (MMS, EA 2160), Université de Nantes, 2 rue de la Houssinière, Nantes F-44000, France</footnote>

<footnote><sup>b</sup> PhuTho college of Medicine and Pharmacy, 2201 Hung Vuong Boulevard, Viettri City, PhuTho Province 290000, Viet Nam</footnote>

<footnote><sup>c</sup> Institut des Molécules et Matériaux du Mans (IMMM, UMR CNRS 6283), Le Mans Université, Avenue Olivier Messiaen, Le Mans F-72000, France</footnote>

<footnote>* Corresponding author.</footnote>

<footnote>E-mail address: aurore.zalouk-vergnoux@univ-nantes.fr (A. Zalouk-Vergnoux).</footnote>
of a lack of standardized protocols (Phuong et al., 2016).

In this context, the present study aimed to evaluate the MP contents of two filter-feeder bivalve species, the blue mussel, *Mytilus edulis* and the Pacific oyster, *Crassostrea gigas*, collected on the French Atlantic coast (Pays de la Loire, France) according to a validated protocol (Phuong et al., 2016). Mussels and oysters have a considerable socio-economic weight in this regional area where 16 thousand tons are annually produced for national consumption. For both species, several sampling sites, seasons and modes of life (cultivated and wild) were investigated in order to determine the factors influencing the contamination and to run an inter-species comparison. The seasonality was evaluated through two sampling campaigns that were performed in autumn and spring, selected because these periods arise from times of high exposure of organisms. The beginning of autumn succeeds to summer which is a period of strong anthropic pressure due to tourism activities on the coast and it is after a warm period leading to higher rate of filtration of suspensivorous bivalves. Moreover, this time is included in the main commercialization periods of mussels (summer and autumn) and oysters (autumn and winter). The beginning of spring arises from the winter period marked by stormy climatic conditions which remobilize the contaminants stored in the sediments, increasing the risk of organism exposure.

Furthermore, the relation between MP contamination and the living environment of organisms was suggested by previous studies (Mathalon and Hill, 2014; Van Cauwenberghe and Janssen, 2014; Vandermeersch et al., 2015; Li et al., 2016). For example, Li et al. (2016) found significant differences between mussels sampling along about 20,000 km coastline showing that sampling location could be one important factor influencing MP content in marine ecosystems. The sampling sites chosen in this study are separated of 140 km at the maximum. They were selected because of the intensive and important shellfish aquaculture for regional and national socio-economy and because they are under different oceanic and terrigenous influences. Moreover, wild mussels were shown to be more contaminated than farmed ones in this latter study, while the opposite was found by Mathalon and Hill (2014). As numerous tools made of plastic are used in mussel and oyster farms for spat collection or on-growing stages, wild and cultivated organisms from different major farming areas along the Atlantic coast were analyzed in the present work to investigate the influence of farming practices on MP contents, and assess the spatial variations of MP contamination. Overall, it provides first data on the MP contamination level of the French Atlantic coast for these two chosen bivalve species, contributing to the global MP contamination assessment.

## 2. Materials and methods

### 2.1. Reagents

KOH pellets were purchased from CARLOERBA reagents (France); KI pellets were from VWR (France) and the membrane filters of cellulose nitrate with pores of 12 µm and 25 mm of diameter were provided by Whatman (Germany).

### 2.2. Sample collection strategy

Fig. 1 shows the sampling locations of adult mussels (*M. edulis*) and oysters (*C. gigas*) on French Atlantic coasts (Pays de la Loire region, France). Oysters were sampled in the three points located on the map: Pen-Bé (N 47°25'33" W 2°27'46"), Coupelasse (N 47°01'19" W 2°01'59") and Aiguillon Bay (N 46°16'26" W 1°14'14") while mussels were only sampled in Pen-Bé and Aiguillon Bay because of their absence in the third site. For each sampling site, wild and cultivated organisms were randomly collected at two different seasons: October 2015 (beginning of autumn) and March 2016 (beginning of spring).

The sampling site Pen-Bé is located in the Pen-Bé bay. The watershed of the bay is mainly represented by agriculture activities (60%)

and urbanization (15%) (IFREMER, 2006). The urbanization is quite limited since the towns present in the watershed do not have > 2000 inhabitants. Activities of salt production are also present in the watershed (580 ha) as well as the aquaculture of mussels and oysters (280 ha). The supply of freshwater of the bay is limited. The impacts of the Loire estuary are negligible whereas those of the estuary of the Vilaine can be considered depending on weather conditions. In the bay, it was measured that about 41 to 92% of the water is renewed after 5 tidal cycles. The samples were collected at about 300 m of the coastline.

Coupelasse is located in the bay of Bourgneuf (340 km²). The watershed is mainly represented by protected zones (habitats and birds), in particular in the south where the marsh Breton is recognized for its biodiversity as 3rd national wetland (IFREMER, 1997). The main supply of freshwater is done by Millac, a small river draining a watershed composed of hedgerows, grasslands and 2 towns in its downstream part (Les Moutiers en Retz and Bourneuf en Retz: 1500 inhabitants and 3500 inhabitants respectively) (Schéma d'aménagement et de gestion des eaux du marais breton et du bassin versant de la baie de Bourgneuf, 2014). It is the main shellfish farming area in the Pays de la Loire region with high oyster farming activity (90%) and little mussel farming explaining why no mussels were sampled for this study. This area is separated from the ocean by the island of Noirmoutier which shelters it from the swell. It communicates with the ocean to the north through an opening of 12 km. The oceanic waters more salted than the waters of Bourgneuf lead to a difficult mixing of them. It was estimated that it takes about 2 months for the waters of the Bay of Bourgneuf to be renewed by ocean waters. The bay is to the south of the Loire estuary but its plume rarely penetrates the bay only by northerly wind or in low water period. The samples were collected at about 1 km of the coastline.

The samples taken in Aiguillon bay were collected just outside the bay to the north, remaining in the Pays de la Loire region. This site is exposed offshore and is under oceanic and terrigenous influences (IFREMER, 1996). The terrigenous influence is limited and comes from the bay where the residence times of the waters appear to be quite long and the exchanges relatively limited with the outside. Freshwater supply of the bay is due to the rivers Sèvre Niortaise and the Lay and less frequently to the Canal du Curé. All these rivers drain the watershed of the Poitevin marsh which is a protected zone. Along the coast, an extensive mussel farming activity occurs accounting for 15% of the national production. The samples were collected at about 300 m of the coastline.

Five samples, i.e. 5 oysters and 5 pools of 3 mussels, were analyzed per sampling location, per season and per mode of life, leading to a total of 180 marine bivalves: 60 oysters and 120 mussels.

### 2.3. Biometric parameters and sample preparation

After the collection, organisms were placed in sealed freezer plastic bags made of PE and conducted to the laboratory in a refrigerated enclosure. Organisms were then kept in bags at -20 °C until analysis. All of laboratory experiments were carefully performed with the aim of preventing MP contamination. Concerning sample preparation, the bivalves were taken out of the freezer for thawing during 1 h. Then, each oyster and mussel shell was individually measured and the individual total wet weight without internal water and soft tissue wet weight were determined after the elimination of the byssus for the mussels. Organisms sized from 3.5 to 5.8 cm and from 7.3 and 13.7 cm for mussels and oysters respectively. The condition index (CI) was calculated according to the recommendation of the French Association for Standardization (AFNOR, 1985) using the formula: $CI = (soft tissue wet weight / total wet weight without internal water) \times 100$. CI ranged from 22.3 to 53.5 for mussels and from 17 to 46.8 for oysters.

MP analyses were performed on individual oysters and on a pool of 3 mussels following the protocol elaborated by Phuong et al. (2017). In brief, the sample (one oyster or a pool of 3 mussels) was placed into a
<figure><img src="image_76.png" /><figcaption>Fig. 1. Sampling locations in Pays de la Loire, France: Pen-Bé, Coupelasse, Aiguillon Bay.</figcaption></figure>

150 mL conical flask. Then 50 mL of KOH 10% (m/v) were added. The mix was heated at 60 °C and at the same time, agitated during 24 h. After the digestion, the obtained solution went through a density separation step after the transfer to a 125 mL separating funnel. After 4 h, 10 mL of the bottom solution was transferred into a second separating funnel, whereas the top of the solution was put into a 100 mL conical flask. In order to separate dense MPs from mineral particles, 20 mL of a KI solution (50%, m/v) was added into the second separating funnel. After a vigorous hand shaking, this solution was left for 4 h at room temperature. After this second decantation time, the top of the solution was then added into the conical flask with the first one. The mix of solutions was then filtered on a cellulose nitrate filter with a porosity of 12 µm. Filter was dried at room temperature in a glass Petri dish which was closed until analysis.

## 2.4. µFT-IR analysis

The identification of MP types on the filters was performed by using Fourier transform infrared microscopy system (µFT-IR; Spotlight 200i FT-IR microscopy system, PerkinElmer) in reflection mode. Each spectrum was recorded after 8 accumulations ranging from 600 to 4000 $cm^{-1}$ and the whole surface filter was inspected, each detected particles being individually analyzed. Each obtained spectrum was then compared to the polymer database (PerkinElmer Polymer database) and the type of plastic was determined when the research score was higher than 60%. Each identified plastic particle was analyzed in order to categorize MPs according to the size: < 50 µm; from 50 to 100 µm and > 100 µm. Their color and their form were recorded for their classification according to Galgani et al. (2013).

## 2.5. Quality control

The main concern in terms of quality control for the analysis of MP is the cross-contamination. The first point was to lead strategies to prevent it. All equipments used in the laboratory were previously rinsed with MilliQ water and dried at room temperature avoiding contact with

the ambient air. Once dried, they were immediately kept under aluminum foil. During the analysis procedure, the contact of the digestion solution with the ambient air was limited by the use of aluminum foils. Once the filtration performed, the filters were kept in Petri dishes made of glass until the µFT-IR analysis. During the experiments, laboratory coats made of cotton and gloves were worn all the time. Because of a remaining risk of cross-contamination of the samples, different blanks were performed. The first ones were realized following the procedure of sample preparation and µFT-IR analysis without bivalves on 6 replicates. Then, two other types of blanks were performed to assess the potential cross-contamination due to the storage of bivalves in the plastic bags. Three plastic bags were kept with MilliQ water during 24 h and three other bags were filled of MilliQ water and frozen at -20 °C during 24 h. Water volumes were then filtered and the obtained filters analyzed by µFT-IR.

The other concern of the quality control is the validation of the analytical procedure which was previously performed by spiking with 20 particles of PP, PE and PVC with and without bivalves (N = 3 for each condition) as it was explained in a study carried on the laboratory (Phuong et al., 2017).

## 2.6. Statistical analysis

Data were analyzed using XLSTAT software. The conditions for applying parametric tests, i.e. homogeneity of variance and normality, were verified using Fisher and Shapiro-Wilk tests respectively. As result of these tests, non-parametric tests (Kruskal-Wallis ANOVA (KW)) were used in order to highlight significant differences of MP contamination in bivalves collected at different locations, seasons and with different modes of life. Differences between groups were considered as significant when $p < 0.05$. The KW test was followed by a post hoc test Multiple Comparisons of p-value (MCP) when it was significant at $p < 0.05$.
# 3. Results

## 3.1. Quality control and MP identification

The whole analytical procedure was performed without any sample (N = 6) in parallel with bivalve samples to evaluate cross-contamination due to airborne, vessels and reagents. An average of 1.2 (± 0.8) particle per filter (N = 6) was observed by microscopy. Other types of blanks corresponding to plastic bags rinsed with MilliQ water during 24 h (N = 3) and placed in freezer with MilliQ water during 24 h (N = 3) respectively displayed 0.7 (± 0.6) and 1.3 (± 1.2) particles with the microscopic observation. The identification by µFT-IR of all the particles found on filters corresponding to the different types of blanks concluded to no particles made of plastic.

The results of the validation of the analysis procedure performed with and without bivalves by spiking 20 particles of PP, PE and PVC were published in a previous work (Phuong et al., 2017). The conclusion was that recoveries reached about 100%, 70% and 90% for PE, PP and PVC particles leading to the procedure validation.

In bivalves, a total of 199 particles were identified as plastics by µFT-IR among 3285 measured ones on all particles observed by microscopy. The ratio of identified MPs/measured particles reached about 6%.

## 3.2. MPs in mussels

### 3.2.1. Quantitative analysis

The whole abundance of MPs found in mussels was about 0.23 ± 0.20 MP per gram of wet weight soft tissues and about 0.60 ± 0.56 MP per individual (N = 120). Quantitative results of each sampling location, season and mode of life are presented in Fig. 2.

The statistical tests applied to the obtained data showed no significant differences between the abundance of MPs related to the three studied influencing factors: sampling location, season and mode of life, whatever the way of result expression (MP/g or MP/mussel). Even if no significant difference between MP contaminations was highlighted concerning the mussel mode of life, a higher detection frequency was noticed in cultivated mussels compared to wild ones. Indeed, 90% of pools of cultivated mussels presented MP particles while just 65% for pools of wild mussels.

### 3.2.2. Qualitative analysis

The 73 MPs identified in the whole studied mussels were distributed according to their plastic type, their color and their size for a qualitative

study (Fig. 3).

Among the MPs found in mussels, seven different natures of plastics were determined with µFT-IR spectroscopy. The majority of identified polymers were PP and PE with respective proportion of 47 and 38% (Fig. 3I). The other plastic types reached 15% and were essentially represented by PE-PP copolymers (5.4%), polystyrene (4.1%), poly-methyl methacrylate (PMMA; 2.7%), polyester (1.4%) and acrylonitrile butadiene styrene (ABS; 1.4%).

Galgani et al. (2013) proposed categorizes for shape and color of MPs. In the present study, the majority MPs was fragments reaching 82% and the remaining MPs were filaments. Several other filaments were also observed but could not be identified as polymeric fibers with µFT-IR analysis. Regarding the color, most of MPs found in the mussels were grey-colored, counting for 51% of MPs (Fig. 3II). Then black, red, green and white MPs were observed reaching 23, 11, 8 and 7% respectively.

Concerning the size of MPs found in the mussels as shown in Fig. 3, the highest proportion up to 52% corresponded to MPs ranging from 50 to 100 µm (Fig. 3III). Then, MPs from 20 to 50 µm reached 37% and finally 11% of MPs were > 100 µm. The largest particle found in mussels sized 400 µm (a fragment of PP).

Fig. 4 is helpful in order to study the influence of the sampling site, the season and the mode of life of mussels. In Fig. 4I, the type of plastic seemed to be influenced by the mode of life of mussels in Pen-Bé. The wild mussels displayed only MPs made of PP and PE, this latter being largely predominant compared to all other sites, seasons and mode of lifes. On the same way, Fig. 4III shows that mode of life of mussels in Pen-Bé could have an influence on the size of MPs, since no MP larger than 100 µm was observed in wild mussels. In Aiguillon Bay, no influence of season or mode of life can be noticed. Finally no trend was observed concerning MP color (Fig. 4III). Regarding correlations between type, size and color no trend could be highlighted except that 26/28 MPs made of PE were grey.

## 3.3. MPs in oysters

### 3.3.1. Quantitative analysis

The whole abundance of MPs in oysters was about 0.18 ± 0.16 MP per gram of wet tissue and 2.10 ± 1.71 MP per individual (N = 60). Quantitative results of each sampling site, season and mode of life of organisms are presented in Fig. 5.

The statistical tests applied to the data showed no significant differences between the groups of oysters related to the sampling location, the season and the mode of life of organisms, whatever the unit of result

<figure><img src="image_77.png" /><figcaption>Fig. 2. MPs in mussels related to sampling location, season and mode of life expressed as MP number per gram of wet weight soft tissues of mussels (I) and as MP number per mussel (II). N = 5 and box-plots depict minimum, first quartile, median, third quartile and maximum.</figcaption></figure>
<figure><img src="image_78.png" /><figcaption>**Fig. 3.** Qualitative analysis of MPs found in mussels. Distribution of MPs according to: (I): the type of plastic; (II): the color; (III): the size. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>

<figure><img src="image_79.png" /><figcaption>**Fig. 4.** Distributions of MPs related to the sampling site, the season and the mode of life of mussels, according to: (I): the type of plastic; (II): the color; (III): the size. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>
<figure><img src="image_80.png" /><figcaption>Fig. 5. MPs in oysters related to sampling location, season and mode of life expressed as MP number per gram of wet weight soft tissues of oysters (I) and as MP number per oyster (II). N = 5 and box-plots depicted minimum, first quartile, median, third quartile and maximum.</figcaption></figure>

expression (MP/g or MP/oyster). Without statistical basis, some light effects of sampling locations and modes of life could be evidenced. Hence, 28/30 (93%) cultivated oysters contained MPs vs only 24/30 (80%) of wild oysters. Moreover, a total of 55 MPs were found at Coupelasse vs only 41 at Aiguillon and 30 at Pen-Bé.

### 3.3.2. Qualitative analysis

The 126 MPs observed in the whole studied oysters were distributed according to their plastic type, their color and their size for a qualitative study (Fig. 6).

Among the 126 MPs found in sampled oysters, seven different plastic types were identified with FT-IR spectroscopy. About half of the MPs were made of PE and a quarter of PP (Fig. 7I). Then, ABS was also frequently found reaching 15% of the recovered MPs. The last 13% were PE-PP copolymers (6.6%), polyester (4.0%), polyisobutylene (PIB; 0.8%) and polystyrene (1.6%). No PVC were found in the oysters,

neither PMMA.

About the shape categorizes from Galgani et al. (2013), the majority of MPs were fragments, with a distribution reaching 79% (99/126), the remaining MPs being filaments. Regarding the color, a lot of MPs found in the oysters were grey-colored, counting for 40% of MPs. Then green, red, black, white and blue MPs were observed reaching 22, 21, 11, 4 and 2% respectively (Fig. 6II).

Fig. 6III shows the distribution of MPs found in oysters related to their size. The highest proportion, up to 53%, corresponded to MPs ranging from 50 to 100 µm. Then, MPs > 100 µm reached 32% and finally 15% were MPs ranging from 20 to 50 µm. The largest particle found in oysters sized 1300 µm (a filament of polyester).

As for mussels, some trends could be highlighted about the influence of the sampling site, the season and the mode of life of oysters (Fig. 7). The patterns of plastic types and colors (Fig. 7I and II) found in wild oysters from Aiguillon bay in October were particular: it is the only

<figure><img src="image_81.png" /><figcaption>Fig. 6. Qualitative analysis of MPs found in oysters. Distribution of MP according to: (I): the type of plastic; (II): the color; (III): the size. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>
<figure><img src="image_82.png" /><figcaption>**Fig. 7.** Distributions of MPs related to the sampling site, the season and the mode of life of oysters, regarding: (I): the type of plastic; (II): the color; (III): the size. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>

<caption>**Table 1**</caption>

Studies dealing with MP contamination of marine bivalve species: location, type of digestion, identification method of MPs, quantity, predominant form and type found in bivalves with the corresponding references.

<table><thead><tr><th>Species</th><th>Location</th><th>Digestion</th><th>Identification</th><th>Quantity</th><th>Predominant form (type)</th><th>References</th></tr></thead><tbody><tr><td rowspan="6">Mytilus edulis</td><td rowspan="2">Canada<br>China</td><td rowspan="2">H<sub>2</sub>O<sub>2</sub> 30%</td><td>Observation</td><td>34–178 items/individual</td><td>Fibers</td><td>Mathalon and Hill (2014)</td></tr><tr><td>μFT-IR spectroscopy</td><td>0.9–4.6 items/g</td><td>Fibers<br>(CP<sup>a</sup>, PET<sup>a</sup>)</td><td>Li et al. (2016)</td></tr><tr><td>Belgium<br>Europe</td><td>HNO<sub>3</sub>/HClO<sub>4</sub></td><td>Observation</td><td>0.26–0.51 items/g</td><td>Fibers</td><td>De Witte et al. (2014)</td></tr><tr><td>Germany<br>North Sea</td><td>HNO<sub>3</sub> 69%</td><td>Raman spectroscopy</td><td>0–0.32 items/g</td><td>Fibers, fragments</td><td>Vandermeersch et al. (2015)</td></tr><tr><td>England</td><td>Protease</td><td>Stereomicroscope</td><td>0.36 items/g</td><td>Fragments</td><td>Van Cauwenberghe and Janssen (2014)</td></tr><tr><td>France</td><td>KOH 10%</td><td>μFT-IR spectroscopy</td><td>0.2–0.3 items/g</td><td>Fibers</td><td>Van Cauwenberghe et al. (2015)</td></tr><tr><td rowspan="2">Mytilus galloprovincialis</td><td rowspan="2">Europe</td><td>HNO<sub>3</sub>/HClO<sub>4</sub></td><td>Observation</td><td>2.5 items/g</td><td>Fibers</td><td>Catarino et al. (2016)</td></tr><tr><td>HNO<sub>3</sub> 69%</td><td>Observation</td><td>0.24 item/g</td><td>Fragments<br>(PE<sup>a</sup>, PP<sup>a</sup>)</td><td>Phuong et al. (2017)</td></tr><tr><td rowspan="2">Nine bivalves</td><td rowspan="2">China</td><td>H<sub>2</sub>O<sub>2</sub> 30%</td><td>μFT-IR spectroscopy</td><td>0.04–0.34 items/g<br>0.08–0.16 items/g</td><td>Fibers, fragments</td><td>Vandermeersch et al. (2015)</td></tr><tr><td></td><td></td><td>2.1–10.5 items/g</td><td>Fibers<br>(PE<sup>a</sup>, PET<sup>a</sup>)</td><td>Li et al. (2015)</td></tr><tr><td>Crassostrea gigas</td><td>France</td><td>HNO<sub>3</sub> 69%</td><td>Raman spectroscopy</td><td>0.47 items/g</td><td>Particles</td><td>Van Cauwenberghe and Janssen (2014)</td></tr><tr><td>Perna perna</td><td>Brazil</td><td>HNO<sub>3</sub> 69%</td><td>Polarized light microscope</td><td>Not estimated</td><td>Irregular shapes</td><td>Santana et al. (2016)</td></tr></tbody></table>

<footnote><sup>a</sup> CP: Cellophane; PET: Polyethylene Terephthalate; PE: polyethylene.</footnote>
condition where PP particles were absent and other types of plastics represented > 60% of the identified particles. Moreover, for these samples all the particles found being grey-colored. On the contrary, in Pen-Bé, other plastic types than PP and PE were present in very low proportions whereas high proportions of PE were observed in cultivated oysters. Finally, the season could have an effect on the patterns of MP size (Fig. 7III): the proportions of MPs from 20 to 50 µm were not similar between the two studied seasons, they were higher in October.

Studying the correlations between type, size and color, it appears that all MPs in ABS were green while all green-colored MPs, except those made of ABS, were made of PP. Concerning other colors, no trend could be highlighted and no correlation was found implying the size.

# 4. Discussion

## 4.1. Quality control and analytical considerations

Associated to the care given to the experiments in order to avoid cross-contamination of samples, different types of blanks were performed. According to the low number of particles observed in the different types of blanks (extraction without mussel or oyster, MilliQ water in plastic bags with and without freezing), and their identification with FT-IR spectroscopy as non-plastic, the cross-contamination of the samples during the whole analysis procedure (storage, sample preparation, FT-IR analysis) could be considered as negligible.

The Table 1 reports literature data on MP contamination of marine bivalves around the world. The use of different methods for sample treatment and MP identification could represent a main source of heterogeneity of the results. Indeed, regarding our results, the ratio of identified MPs/analyzed particles was relatively low, reaching about 6%. Thus, a lot of particles were not identified as plastics and then, were not included in the set of data. This result implies that a microscopic observation is not enough for the determination of plastic-like or non-plastic particles. The identification step in studies about MPs is consequently necessary in order to avoid an overestimation of the MP contents. According to literature (Table 1), only 3 out of 9 studies about MP contents in bivalves achieved the characterization of the plastic nature of particles. Li et al. (2016) found 109 plastic-like particles among 129 particles randomly selected from a total of 1519 microscopically observed particles (ratio higher than 84%). In this latter study, authors used µFT-IR spectroscopy in transmission mode. This mode is not compatible with the cellulose nitrate filters, hence one needs to select the particles and place them on another type of IR-transparent substrate for the identification step. Spectra obtained in transmission mode allow higher research scores than in reflection mode leading probably to a higher proportion of particle identification (Li et al., 2016) which may be one reason for the differences in MP identification rates.

On the other hand, regarding sample treatment by chemical digestion, the use of different reagents as acids, hydroxides or peroxides leads to results hardly comparable (Dehaut et al., 2016). For example, digestions performed with acids were reported as destructing or damaging the surface, the color, the size of some types of MPs (Claessens et al., 2013; Catarino et al., 2016). For these reasons, it seems to not be suitable for the MP contamination assessment in bivalves. Our previous study (Phuong et al., 2017) reported that KOH (10%, m/v) appeared as one of the best reagent for the digestion step among others (NaOH, KOH, HNO₃ or HNO₃ mixed with H₂O₂, HCl or HClO₄) for an application to the blue mussel *Mytilus edulis*. Moreover, KOH is reported as the best adaptable reagent for the majority of MP types among 15 different tested (Dehaut et al., 2016). Secondly, concerning MP identification, the observation by microscopy is not enough for the characterization of particles as plastic with a strong risk to overestimate the MP content in organisms. Two vibrational microspectroscopic methods (Raman and FT-IR) appeared so far as the most applicable identification methods for MPs in organisms. While Raman spectroscopy allows the

identification of MPs with a smaller size than with µFT-IR spectroscopy (inferior to 50 µm), this latter is a faster method of identification (Kappler et al., 2016).

## 4.2. Variations of MP contents in bivalves

Beyond variations in analytical procedures, the qualitative and quantitative variations of MP contamination may be related to differences in sampled area pressures and interspecies physiology. Many scientific reports demonstrated that MP quantity is spatially different from pole to pole in global ocean (Cózar et al., 2015). In this study, the quantities of MPs found in mussels and oysters were comparable to quantities depicted in numerous previous studies (De Witte et al., 2014; Van Cauwenberghie and Janssen, 2014; Vandermeersch et al., 2015), even if the sample preparation protocols and the analysis methods were different. On the contrary, despite a protocol of analysis close to the one used in this study, Li et al. (2016) obtained levels of MP contamination in mussels sampled from the coast of China on average 10 times higher than the ones obtained here. As the coast of China is known to be a hotspot of MP contamination (Qiu et al., 2015), it appears that these high levels of contamination could be directly related to sampling location and bivalves could then be considered as good bioindicators of MP contamination. Significant differences were moreover noticed between the 22 studied sites covering about 20,000 km coastline. Mathalon and Hill (2014) found also high levels of contamination with 34-178 items per mussel. The difference with our results could be explained once a more by a spatial influence, but also, in this case, partially attributed to differences in the method used for MP analysis. Since the quantification by Mathalon and Hill (2014) was based only on observations, a probable over-estimation of the MP quantities could occur.

In the present study, no significant quantitative difference was observed between the two or three sampling sites studied on the Atlantic coast, whether for mussels or oysters. The anthropogenic pressures of the different sites, the maximum distance of 140 km between them and their oceanic and terrigenous influences did not lead to different MP contaminations. Nevertheless, a tendency of a higher number of MP particles in oysters from Coupelasse (55 items) than Pen-Bé (30 items) was noticed, Aiguillon bay being intermediate (41 items).

Regarding the sampling period, no clear influence on MP contents could be observed. October and March arising both from times of high exposure of organisms (summer pressure and higher filtration rates, remobilization of contaminants stored in the sediments during winter), it will be interesting to further investigate the MP contents in bivalve throughout a farming life cycle including, in this way, seasonal and age variables.

Mathalon and Hill (2014) demonstrated different MP contamination levels between wild and cultivated mussels as it is also suggested in the present study. Even if the differences were not significant, about 90% of pools of cultivated mussels contained MPs while just 60% of wild mussels contained some. The greater contamination of cultivated mussels could be explained by a proximity to MPs coming from the degradation of plastic materials (PE, PP, polyester) used in aquaculture as collectors, ropes, nets and pipes used from the spat collection to on-growing steps. However, Li et al. (2016) showed the opposite trend displaying data on wild mussels being more contaminated than cultivated ones. But the levels of MP contamination in their case were very high compared to all other studies, which prevents any relevant comparison. Regarding oysters, similar results were found as the frequency of MP detection tend to be higher for cultivated oysters (93%) than for wild ones (80%). Even if this observation is less convincing than for mussels, we cannot exclude that oyster cages made in PE could participate to increase oysters' exposure.

From a qualitative point of view, PE and PP were highly predominant among identified plastic particles in all samples. This is consistent with production data as these two polymers account for
43.5% of the annual world production. These two polymers are indeed predominantly sampled in marine waters (Phuong et al., 2016). PS, PE-PP copolymers and ABS were also found in both bivalves representing respectively on average 2.9; 6.0 and 8.2% of the identified particles. This is not surprising for PS as it is the third most produced polymer. Industrial production of PE-PP copolymers has appeared more recently than PE or PP homopolymers (no data on the current production could be found) but they are more and more used for adhesives and packaging applications. Their presence in environmental samples is already scarce and an increase of the concentration can be expected in the future. ABS is less produced and by crossing results of color and type of MPs, all ABS MPs were found green-colored. Hence, it could mean that the ABS contamination in this study originate from a same source. This type of plastic is usually used in toys and in car industry. At last, although PVC production reaches 10% (PlasticsEurope, 2015) of the polymer production, this type of plastic was not found in the mussels and the oysters studied in this present work. It is in accordance with the literature, since PVC MPs have never been observed in bivalves until now. A postulate could be the density of PVC lead to the sinking of MPs which would not be in contact with the mussels or oysters, living in the water column. For all these reasons, the mussels and the oysters could be considered as good indicators of MP contamination of marine waters as shown by Avio et al. (2017) for mussels, even if they are less representative of benthic environments than surface waters.

For both bivalve species, the majority of MPs were fragments and grey-colored suggesting a long-time spent in the environment after fragmentation of wastes (secondary source of contamination). Contrarily to Li et al. (2015, 2016), no plastic pellets (primary origin of contamination) were found in the bivalves.

Finally, regarding the sizes, MPs found in the present study were on average bigger than those found in mussels by Van Cauwenberghe and Janssen (2014). In their study, the predominant size of MPs was in the range inferior to 25 µm instead of MPs ranging from 50 to 100 µm as in the present study. These variations of size could be attributed to a different mussel contamination but also to the different identification procedures used in the studies. Van Cauwenberghe and Janssen (2014) indeed used Raman spectroscopy for MP identification which allows a lower resolution and consequently the identification of MPs with size inferior to 20 µm which is more difficult with µFT-IR spectroscopy.

### 4.3. Comparison between bivalve species

Considering quantitative results, a great variation of MP quantities per individual were observed between mussels and oysters, with respectively 0.61 ± 0.56 and 2.10 ± 1.71 MP per individual. However, when expressed in MP/g of wet weight soft tissue, the results did not appear so different anymore, with 0.178 ± 0.160 MP/g and 0.228 ± 0.197 respectively for mussels and oysters. Even if the levels of MPs were approximatively one order of magnitude higher than in the present study, this observation seems in accordance with the report of Li et al. (2015). They found in nine commercial bivalves from China, relatively similar MP numbers when expressed in MP/g while significant differences between species were observed for results in MP/item. These results showed that the number of MPs found in different bivalve species could be more or less proportional to the weight/size of organisms. About the differences of MPs/individual between mussels and oysters, the filtration rates could be an explanation since it reaches up to 1.8 L/h (Clausen and Riisgard, 1996) and 5 L/h (Barillé et al., 1997) for mussels and oysters respectively. Oysters filtering twice more water than mussels, they are supposed to be more exposed to MPs leading to a greater bioaccumulation per individual.

From a qualitative point of view, the comparison of Figs. 3I and 6I shows that the predominant plastic type is different for the two studied species. In mussels, PP was predominant while PE particles were the most abundant ones in oysters. This observation may be due to a selective absorption of MPs according to their type or to their position in

the water column. More investigation has to be done to confirm these differences. Another difference was a more important abundance of ABS MPs in oysters (15%) compared to mussels (1%). This higher presence of green colored ABS particles in oysters could be attributed to an alimentary confusion of the oysters. A similar observation was found in the study of De Sa et al. (2015), who showed a confusion between preys and MPs for fish species during laboratory exposures. The confusion could be attributed to the color of MPs.

The comparison of the MP sizes found in both bivalves (Figs. 3III and 6III) showed that the proportion of MPs from 50 to 100 µm were similar between both species (about 50%) and an inversion was observed for the other size ranges with more small MPs (from 20 to 50 µm) observed in mussels whereas a higher proportion of big ones (> 100 µm) was found in oysters. These differences in size distributions could be explained by the size of both bivalve species (shell length of 4.42 ± 0.48 and 9.60 ± 1.53 cm respectively for mussels and oysters). The oysters being bigger have also bigger gills and labial pulps which lead probably to the possible ingestion of bigger particles than mussels. For example, Dupuy et al. (1999) reported that mussels most effectively retained particles larger than 20 to 30 µm whereas Cognie et al. (2003) found that the oysters accepted food items larger than 150 µm. The sizes of the biggest MPs found in the bivalves, 400 and 1300 µm respectively for mussels and oysters, illustrate also this hypothesis. Nevertheless, these large particles were probably located in gills since it seems impossible that such fragments could be filtrated and penetrated into the organisms. It would be interesting to study the organanotropism in order to answer this point. No correlation was found between the shell length and the MP quantity into each species, and it could also be interesting to link the quantity to the age of the organisms. For the cultivated bivalves, the age could be easily calculated but it would be more difficult for the wild ones. The shell length is not a good indicator of the age since the growth of the organisms is dependent on the local environmental conditions, especially the water quality and the nutrient contents.

Finally, the sampling site, the season, the mode of life or any combinations of these factors were not revealed as relevant influencing factors on the quantitative and qualitative analysis of MPs in bivalves since no systematic effect was highlighted for both species in this study.

### 5. Conclusion

This study provided interesting quantitative and qualitative results about the MP contamination of two bivalve species, the blue mussel (Mytilus edulis) and the Pacific oyster (Crassostrea gigas) from the French Atlantic coast. It contributes to the global MP contamination assessment through a large set of data allowing comparisons between the two species at same locations with the analysis of 180 organisms. Actually, the French Atlantic coast appears to not be under an important MP contamination pressure compared to other sites. Three influencing factors were investigated by the analysis of wild and cultivated bivalves collected at different sampling sites and different seasons. This is the first research work combining these three factors. Even if no evident intra-specific difference was highlighted related to the three influencing factors, some inter-specific differences were found either qualitatively or quantitatively. For example, MP quantity in organisms was higher in oysters than mussels when results were expressed in MP per individual, with values reaching 2.10 ± 1.71 and 0.61 ± 0.56 MP per individual respectively. Once expressed in MP per g of wet weight of soft tissues, quantitative results were quite similar with 0.178 ± 0.160 and 0.228 ± 0.197 items per gram respectively for mussels and oysters. About the qualitative results, different polymers were identified with a high predominance of polyethylene (PE) and polypropylene (PP) and a noticed recurrence of green acrylonitrile butadiene styrene (ABS) fragments in oysters. Most of the MPs were fragments; about a half of MPs were grey colored. MP size ranging from 50 to 100 µm accounted for about 50% of recovered MPs for both studied species. Up to now, all
studies on MP contamination of bivalves focused on the whole organism. Hence for future works, it would be interesting to study the organotropism of MPs in these filter-feeder species. Are MPs translocated to the tissues or trapped in the gills and/or the digestive tract?

## Acknowledgments

We would like to greatly thank the LEX (Laboratoire d'Ecotoxicologie) and the LER PC (Laboratoire Environnement Ressources des Pertuis Charentais) of IFREMER for their advices and their help during the sampling campaigns. This study was partly supported by the region Pays de la Loire through the program Miplaqua. Great thanks to PhuTho college of Medecine and Pharmacy and government of Vietnam for the scholarship of N.N. Phuong.

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# HABILITATION A DIRIGER LES RECHERCHES

## Dr Aurore ZALOUK-VERGNOUX

**Titre :** Évaluation de la contamination environnementale par les Hydrocarbures Aromatiques Polycycliques, les nanoparticules métalliques et les microplastiques

### Résumé :

Ce dossier de demande d'Habilitation à Diriger des Recherches (HDR) présente un point bilan de mes activités de recherche depuis 13 ans, doctorat inclus. J'ai eu l'opportunité d'évoluer au sein de différents laboratoires de l'Université Paul Cézanne et de l'Université de Provence (Aix-Marseille Université) et je suis à présent Maître de Conférences à l'Université de Nantes, dans l'UFR des Sciences Pharmaceutiques et Biologiques, au sein du laboratoire Mer, Molécules, Santé (EA 2160). Le domaine dans lequel s'inscrivent mes travaux de recherche est la chimie de l'environnement, associée à des problématiques écotoxicologiques, ayant pour objectif global d'évaluer les risques environnementaux.

Dans un premier chapitre, ce dossier présente mon curriculum vitae, mes activités d'enseignement et de recherche, ainsi que la valorisation de mes travaux.

Puis, un deuxième chapitre traite de la synthèse des travaux de recherche que j'ai réalisés jusqu'à ce jour sur l'évaluation de la contamination environnementale. Les études menées se positionnent au niveau de la détermination du devenir des contaminants dans l'environnement, de l'exposition et de l'imprégnation d'espèces vivantes. Les expérimentations in vivo ont principalement porté sur des nanoparticules métalliques, alors que divers contaminants ont été ciblés lors d'études in situ, comme des composés organiques hydrophobes, des métaux ou encore des microplastiques. Les milieux étudiés étaient continentaux, avec des forêts incendiées, mais aussi estuariens en Loire, et côtiers sur le littoral de la région des Pays de la Loire. Des mesures abiotiques ont été réalisé à la fois sur des sols, des sédiments et des masses d'eau, faisant intervenir des mesures directes ou indirectes, par le biais d'échantillonneurs passifs. Pour ce qui est du compartiment biotique, des végétaux ont été analysés, ainsi que des espèces animales ayant divers intérêts au niveau écosystémique, écotoxicologique, biologique, sanitaire, et/ou socio-économique. La multiplicité des matrices a mené à la mise au point, la validation et l'utilisation de nombreuses méthodes analytiques.

Le troisième et dernier chapitre a pour objectif de présenter mes projets de recherche à venir qui se positionnent au niveau de l'estimation des sources de contamination jusqu'à l'évaluation de la qualité des milieux. Dans la continuité de ce que j'ai réalisé tout au long de mon parcours professionnel, une étude est en cours sur des contaminants qui étaient non étudiés au laboratoire : les éléments terres rares (scandium, yttrium et lanthanides). Par ailleurs, le continuum terre-mer est une problématique que je souhaiterais approfondir pour mieux caractériser les flux provenant du milieu continental et qui impactent les milieux estuariens et côtiers. Pour finir, je souhaiterais développer des méthodes d'évaluation de la qualité des milieux, et notamment un indice d'anthropisation, basés sur la spectroscopie proche infrarouge associée à des outils chimiométriques. Ces méthodes permettraient une évaluation rapide et peu coûteuse grâce à des mesures sur les sédiments et les moules, qui sont de bons intégrateurs de la contamination chimique.