An Integrated Biomarker Approach Using Flounder to Improve Chemical Risk Assessments in the Heavily Polluted Seine Estuary
Abstract
:1. Introduction
2. Materials and Methods
2.1. Fish Sampling
2.2. Metal Analysis
2.3. Organic Pollutants Analysis
2.4. Enzymatic Activities
2.4.1. Glucose 6-Phosphate Dehydrogenase (G6PDH) & Cytochrome C Oxidase (CCO)
- -
- Glucose 6-phosphate dehydrogenase (G6PDH; EC 1.1.1.49, Gauthier et al. 2008): Imidazole buffer ((imidazole 50 mM, MgCl2 25 mM, KCl 70 mM), pH 7.5, β-nicotinamide adenine dinucleotide phosphate (NADP) 0.3 mM, glucose-6-phosphate 200 mM (omitted in controls). G6PDH activity was undetected in muscle samples and was only measured in liver at 340 nm.
- -
2.4.2. Ethoxyresorufin-O-Deethylase (EROD) & Acetylcholinesterase (AChE)
2.5. Lipids Analysis
2.6. Genetic Diversity
2.6.1. Genotyping
2.6.2. Analysis of Genetic Diversity
2.7. Statistical Analyses
3. Results
3.1. Contaminant Concentrations
3.2. Fish Biometry, Condition Index, Hepato-Somatic Index, Muscle Protein Concentration
3.3. G6PDH, CCO, AChE and EROD Activities
3.4. Muscle Lipids
3.5. Integration of the Phenotypic Responses
3.6. Genetic Variability
4. Discussion
4.1. Chemical Contamination & Hypothesis on the Flounder Use of Habitat in the Seine Estuary and Douarnenez Bay
4.2. Condition Index, Muscle Protein Content, Antioxidant Defences and Bioenergetics
4.3. Neurotoxicity and Xenobiotic Metabolism
4.4. Storage Lipids and Membrane Lipids in Muscle
4.5. Potential Relationships between Phospholipids, Xenobiotic Metabolism, Antioxidant Defense and Bioenergetics in Contrasted Environments
4.6. Genetic Variability in the Two Populations
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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DORM-4 | DOLT-5 | TORT-3 | ||||
---|---|---|---|---|---|---|
Measured (n = 5) | Certified | Measured (n = 5) | Certified | Measured (n = 5) | Certified | |
As | 7.6 ± 0.7 | 6.9 ± 0.5 | 32 ± 6 | 35 ± 6 | 59 ± 11 | 60 ± 4 |
Cd | 0.31 ± 0.04 | 0.30 ± 0.02 | 12 ± 2 | 14.5 ± 0.6 | 34 ± 5 | 42 ± 2 |
Co | 0.28 ± 0.03 | 0.25 * | 0.29 ± 0.09 | 0.27 ± 0.03 | 1.04 ± 0.06 | 1.06 * |
Cr | 1.5 ± 0.1 | 1.9 ± 0.2 | 1.0 ± 0.2 | 2.3 ± 0.6 | 0.9 ± 0.1 | 1.9 ± 0.3 |
Cu | 16.1 ± 0.9 | 15.7 ± 0.5 | 31 ± 4 | 35 ± 3 | 350 ± 80 | 500 ± 30 |
Ni | 1.20 ± 0.08 | 1.3 ± 0.2 | 0.7 ± 0.2 | 1.7 ± 0.7 | 4.2 ± 0.4 | 5.3 ± 0.3 |
Pb | 0.30 ± 0.09 | 0.42 ± 0.06 | 0.04 ± 0.03 | 0.16 ± 0.04 | 0.26 ± 0.07 | 0.23 ± 0.02 |
V | 1.5 ± 0.1 | 1.6 ± 0.2 | 0.50 ± 0.04 | 0.51 ± 0.06 | 8.8 ± 0.3 | 9.1 ± 0.4 |
Zn | 49 ± 7 | 52 ± 3 | 96 ± 14 | 105 ± 6 | 125 ± 9 | 136 ± 6 |
ng.g−1 DW | LS | LD | MS | MD |
---|---|---|---|---|
Naphthalene | 97.26 | - | - | - |
PCB 101 | 91.32 | - | 70.12 | - |
PCB 118 | 57.56 | 24.96 | 69.85 | - |
PCB 153 | 255.20 | - | 164.93 | - |
PCB 138 | 290.65 | 45.49 | 167.34 | - |
PCB 180 | 26.20 | - | - | - |
Location | DZ | SE | |||
---|---|---|---|---|---|
mean | sd | sign. | mean | sd | |
Storage lipids | |||||
ST EST | 0.02 | 0.03 | *** | 0.06 | 0.05 |
GL ETH | 0.01 | 0.02 | NS | 0.02 | 0.03 |
TG | 1.96 | 1.82 | ** | 1.01 | 1.21 |
FFA | 0.05 | 0.05 | NS | 0.04 | 0.03 |
ALC | 0.04 | 0.12 | NS | 0.02 | 0.03 |
Membrane lipids | |||||
FST | 0.40 | 0.09 | ** | 0.45 | 0.10 |
SPG | 0.20 | 0.12 | *** | 0.35 | 0.10 |
LPC | 0.19 | 0.08 | *** | 0.10 | 0.08 |
PC | 5.40 | 0.71 | *** | 4.42 | 0.68 |
PS | 0.27 | 0.05 | ** | 0.32 | 0.10 |
PI | 0.87 | 0.15 | *** | 0.64 | 0.12 |
CL | 0.33 | 0.15 | NS | 0.27 | 0.12 |
PE | 2.47 | 0.39 | *** | 2.17 | 0.31 |
∑ SL | 2.08 | ** | 1.15 | ||
∑ ML | 10.14 | ** | 8.73 | ||
∑ ALL | 12.21 | ** | 9.88 |
Locus | Panels | Douarnenez | Seine | ||||
---|---|---|---|---|---|---|---|
Na | Ho | He | Na | Ho | He | ||
Nplaf_8 | 1 | 4 | 0.444 | 0.448 | 4 | 0pl.300 | 0.339 |
Nplaf_14 | 3 | 3 | 0.378 | 0.413 | 4 | 0.352 | 0.342 |
Nplaf_15 | 2 | 5 | 0.272 | 0.338 | 5 | 0.718 | 0.569 |
Nplaf_23 | 2 | 5 | 0.500 | 0.637 | 6 | 0.419 | 0.580 |
Nplaf_24 | 3 | 6 | 0.588 | 0.645 | 6 | 0.656 | 0.664 |
Nplaf_25 | 3 | 6 | 0.756 | 0.673 | 4 | 0.685 | 0.658 |
Nplaf_28 | 3 | 7 | 0.620 | 0.728 | 6 | 0.650 | 0.710 |
Nplaf_30 | 3 | 4 | 0.166 | 0.205 | 4 | 0.437 | 0.371 |
Nplaf_35 | 1 | 17 | 0.971 | 0.917 | 19 | 0.903 | 0.915 |
PFUSC3 | 1 | 6 | 0.529 | 0.478 | 3 | 0.382 | 0.349 |
PFUSC4 | 3 | 3 | 0.527 | 0.526 | 6 | 0.666 | 0.568 |
PFUSC7 | 2 | 10 | 0.617 | 0.742 | 7 | 0.709 | 0.721 |
PFUSC8 | 1 | 4 | 0.450 | 0.502 | 3 | 0.428 | 0.438 |
PL142 | 2 | 14 | 0.896 | 0.878 | 11 | 0.619 | 0.833 |
StPfl001 | 1 | 21 | 0.742 | 0.832 | 18 | 0.774 | 0.868 |
StPfl002 | 3 | 10 | 0.638 | 0.649 | 6 | 0.558 | 0.626 |
StPfl003 | 2 | 5 | 0.756 | 0.679 | 4 | 0.454 | 0.543 |
StPfl005 | 2 | 3 | 0.457 | 0.452 | 4 | 0.457 | 0.530 |
StPfl015 | 1 | 9 | 0.432 | 0.747 | 9 | 0.363 | 0.604 |
StPfl025 | 2 | 7 | 0.500 | 0.551 | 7 | 0.687 | 0.617 |
Multilocus | 7.45 | 0.562 | 0.602 | 6.8 | 0.561 | 0.592 |
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Borcier, E.; Charrier, G.; Couteau, J.; Maillet, G.; Le Grand, F.; Bideau, A.; Waeles, M.; Le Floch, S.; Amara, R.; Pichereau, V.; et al. An Integrated Biomarker Approach Using Flounder to Improve Chemical Risk Assessments in the Heavily Polluted Seine Estuary. J. Xenobiot. 2020, 10, 14-35. https://doi.org/10.3390/jox10020004
Borcier E, Charrier G, Couteau J, Maillet G, Le Grand F, Bideau A, Waeles M, Le Floch S, Amara R, Pichereau V, et al. An Integrated Biomarker Approach Using Flounder to Improve Chemical Risk Assessments in the Heavily Polluted Seine Estuary. Journal of Xenobiotics. 2020; 10(2):14-35. https://doi.org/10.3390/jox10020004
Chicago/Turabian StyleBorcier, Elodie, Grégory Charrier, Jérôme Couteau, Géraldine Maillet, Fabienne Le Grand, Antoine Bideau, Matthieu Waeles, Stéphane Le Floch, Rachid Amara, Vianney Pichereau, and et al. 2020. "An Integrated Biomarker Approach Using Flounder to Improve Chemical Risk Assessments in the Heavily Polluted Seine Estuary" Journal of Xenobiotics 10, no. 2: 14-35. https://doi.org/10.3390/jox10020004
APA StyleBorcier, E., Charrier, G., Couteau, J., Maillet, G., Le Grand, F., Bideau, A., Waeles, M., Le Floch, S., Amara, R., Pichereau, V., & Laroche, J. (2020). An Integrated Biomarker Approach Using Flounder to Improve Chemical Risk Assessments in the Heavily Polluted Seine Estuary. Journal of Xenobiotics, 10(2), 14-35. https://doi.org/10.3390/jox10020004