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Article

Short-Term Biochemical Biomarkers of Stress in the Oyster Magallana angulata Exposed to Gymnodinium catenatum and Skeletonema marinoi

by
Rui Cereja
1,2,*,
Joana P. C. Cruz
1,
Joshua Heumüller
1,
Bernardo Vicente
1,
Ana Amorim
1,3,
Frederico Carvalho
1,
Sara Cabral
1,
Paula Chainho
1,4,
Ana C. Brito
1,3,
Inês J. Ferreira
5,6 and
Mário Diniz
5,7
1
MARE—Marine and Environmental Science Centre, ARNET—Aquatic Research Network, Faculdade de Ciências, Universidade de Lisboa, 1749-016 Lisboa, Portugal
2
Division of Aquaculture, Upgrading and Bioprospection (DivAV), Portuguese Institute for the Sea and Atmosphere (IPMA, I.P.), Av. Doutor Alfredo Magalhães Ramalho 6, 1495-165 Lisboa, Portugal
3
Departamento de Biologia Vegetal, Faculdade de Ciências, Universidade de Lisboa, 1749-016 Lisboa, Portugal
4
CINEA-ESTSetubal, Instituto Politécnico de Setúbal, 2914-508 Setúbal, Portugal
5
UCIBIO—Applied Molecular Biosciences Unit, Department of Chemistry, School of Science and Technology, NOVA University Lisbon, 2819-516 Caparica, Portugal
6
LAQV-REQUIMTE, Chemistry Department, NOVA School of Science and Technology, 2829-516 Caparica, Portugal
7
Associate Laboratory i4HB—Institute for Health and Bioeconomy, School of Science and Technology, NOVA University Lisbon, 2819-516 Caparica, Portugal
*
Author to whom correspondence should be addressed.
Sci 2023, 5(3), 30; https://doi.org/10.3390/sci5030030
Submission received: 15 April 2023 / Revised: 6 July 2023 / Accepted: 12 July 2023 / Published: 17 July 2023
(This article belongs to the Section Biology Research and Life Sciences)
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Versions Notes

Abstract

:
Bivalves accumulate toxins produced by microalgae, thus becoming harmful for humans. However, little information is available about their toxicity to the bivalve itself. In the present work, the physiological stress and damage after the ingestion of toxic dinoflagellate species (Gymnodinium catenatum) and a diatom species (Skeletonema marinoi, which is non-toxic to humans but may be to grazers) in the oyster Magallana angulata are evaluated against a control treatment fed with the chlorophyte Tetraselmis sp. Oysters were exposed for two hours to a concentration of 4 × 104 cells/L of G. catenatum and 2 × 107 cells/L of S. marinoi. The biomarkers superoxide dismutase (SOD), catalase (CAT), glutathione S-Transferase, total Ubiquitin (Ubi) and Acetylcholinesterase (AchE) were assessed. The exposure of M. angulata to G. catenatum lead to a reduction in SOD and AchE activity and ubiquitin concentrations when compared to the control treatment. Moreover, it increased CAT activity in the adductor muscle, and maintained its activity in the other tissues tested. This may be related to the combination of reduced metabolism with the deployment of detoxification processes. S. marinoi also lead to a decrease in all biomarkers tested in the gills and digestive glands. Therefore, both species tested caused physiological alterations in M. angulata after two hours of exposure.

1. Introduction

Algal blooms may affect the health of humans and aquatic species, leading to public health safety and economic issues [1]. In many regions, their frequency has increased in response to some human activities, namely eutrophication and aquaculture intensification [2,3]. Public health problems are mainly related to toxin transfer through seafood consumption. Among the most frequent human syndromes are Diarhetic Shellfish Poisoning (DSP), Paralythic Shellfish Poisoning (PSP) and Ciguatera Fish Poisoning (CFP) [3]. In addition to human health safety, harmful algae blooms (HABs) also pose economic issues, as they can interdict recreational activities, as well as fishing and shellfish harvesting, and they can condition aquaculture activities. Regarding fishing and aquaculture activities, HABs have implications not only due to the accumulation of toxins to which humans are susceptible, but also due to their threatening the health of target species. Some phytoplankton species can cause shellfish poisoning to higher trophic levels [4], which is expressed by a wide range of symptoms (e.g., paralytic, amnesic and diarrhetic shellfish poisoning [5,6,7]). The effect of toxins has been extensively studied in humans with less focus on the effects on the shellfish itself, which serves as a vector to the higher levels of the trophic web [8]. Algae blooms may last from days to months [9,10,11] but, in specific cases, like inland aquaculture and depuration tanks, exposure can be controlled by interrupting seawater intake [12], reducing exposure to just a few hours.
Gymnodinium catenatum is an unarmored dinoflagellate species known for producing saxitoxin analogues, being responsible for PSP outbreaks around the world, including Taiwan [13], China [14], Mexico [15], Spain [16], and Portugal [17]. Besides toxic algae, some nontoxic algae, such as chain-forming diatoms like Skeletonema spp., have also been reported as harmful to some marine species, although it is not considered harmful to humans [18,19]. These species do not produce any known type of toxin but blooms of Skeletonema spp. have been observed to significantly reduce feeding in Chinook salmon and cause mass mortality of herring eggs due to oxygen depletion during bloom decay [18,19]. In addition, S. marinoi produces polyunsaturated aldehydes (PUA) when under stress [20] that have proven to be toxic to many marine species [21,22,23,24,25], with scarce information on its effect on bivalves. Nevertheless, this species is used as food in bivalve aquaculture because it is safe for human consumption, and is easy to produce [26].
Antioxidant enzymes are a defense mechanism against an excess of reactive oxygen species (ROS) production. Furthermore, many sources of stress (e.g., temperature, salinity, pH, parasitization, metals and organic compounds) are known to cause oxidative stress in aquatic organisms with antioxidant enzymes and chaperones being often used as stress biomarkers [27,28,29,30]. For the relationship between shellfish and PSP intoxication, the authors of reference [31] found an increase in Catalase activity (CAT), Glutathione S-Transferase activity (GST) and lipoperoxidation (damage to cell membranes) in Crossostea gigas (now Magallana gigas) and Clamys farreri exposed to Saxitoxin for 12 to 96 h, while superoxide dismutase (SOD) activity varied over time, being higher than the control only in some time periods. Furthermore, the mussel Hyriopsis cumingii presented an increase in ROS concentration when exposed for several days to diets with Microcystis aeruginosa (a cyanobacteria producing the liver toxin microcystin) [13]. In addition, Microcystis aeruginosa also caused an increase in SOD and Glutathione peroxidase (GPX), and reduced Gluthatione (GSH) and GST activities and lipoperoxidation concentration while inhibiting CAT activity [13]. Nevertheless, such studies have been performed for relatively long periods considering the inland production or maintenance of bivalve species, since these can be closed to protect the stock from contaminated waters. Other stress biomarkers have been used to assess physiological stress, which has not often been used in this type of study, including total ubiquitin (Ubi) and acetylcholinesterase (AchE). Ubiquitin is responsible for the elimination of damaged proteins which can no longer be repaired, being thus an important biomarker of protein damage [32,33], while AchE is the enzyme responsible for the degradation of acetylcholine to promote the correct functioning of sodium and calcium channels in chemical synapses, which makes these two enzymes important biomarkers when looking at the effects of paralytic toxins [34,35].
The main aim of the present work was to evaluate the effects of S. marinoi (non-toxic) and G. catenatum (toxic due to the presence of saxitoxin) blooms on the commercial oyster M. angulata, by analyzing the response of the biomarkers Superoxide dismutase (SOD), Catalase (CAT), Glutathione S-transferase (GST), acetylcholinesterase (AchE) and total ubiquitin.

2. Materials and Methods

2.1. Oyster Collection and Maintenance:

A total of 30 specimens of M. angulata oysters of around two years of age, with a mean dry weight of 2.42 g, a mean fresh weight of 9.25 g and a mean body length (without the shell) of 5.3 cm, were collected in aquaculture ponds located in the Sado Estuary (Setúbal, Portugal, Figure S1). The oyster individuals were transported to the MARE facilities at the Faculty of Sciences—University of Lisbon where they were kept at 25 °C and 30 PSU for 20 days, inside a 70 L aquarium (in a closed aquarium system with 200 L of volume), to erase the oyster’s thermal history and responses to salinity and tidal variations. A continuous seawater flow was maintained in the aquarium to ensure adequate physico-chemical conditions and food supply. Salinity and temperature values were monitored with two loggers placed inside the aquarium while dissolved oxygen, turbidity, chlorophyll a and pH values were monitored daily with a multiparameter sonde YSI EXO 2. During the acclimatization period, all oysters were fed with ≈2 × 109 cells L−1 mix with Tetraselmis sp. and Phaeodactylum sp.

2.2. Microalgae Production

Gymnodinium catenatum and Skeletonema marinoi, strains IO13-04 and IO126-01, respectively, were obtained from the algae culture collection at Lisbon University (ALISU). Both species were isolated by single cell isolation from water samples collected along the Portuguese coast. Strain IO13-04 was isolated from a bloom that occurred in Espinho, in September 2005. Strain IO126-01 was isolated from water samples collected in the Sado Estuary, Setúbal, in June 2018. All cultures were clonal and monospecific but non-axenic.
Both strains were scaled-up to obtain the necessary cell concentrations for the assay. The scale-up of G. catenatum was carried out in batches of 500 mL L1 culturing media [36] using 1 L Schott flask, under the following experimental settings: 19 ± 1 °C (Fitoclima 750E, Aralab, Rio de Mouro, Portugal), 115 μmol photons m−2, s-1 cool white fluorescent light (18 W, Osram, Munich, Germany) with 12:12 light/dark cycle. The total volume produced amounted to 2.0 L. For S. marinoi, a total volume of 8 L was produced in 1 L batches. Cultures were cultivated with f/2 + Si culture medium [36] in 2 L Erlenmeyer. The experimental settings were the following: 21 ± 1 °C, 135 μmol photons m−2, s-1 cool white fluorescent light (18 W, Osram, Munich, Germany) with 12:12 light/dark cycle. Both cultures were previously adapted to experimental conditions for several generations.
Cultures were monitored by cell counting. For each batch, aliquots of 3.5 mL were collected every two days and fixed with Neutral Lugol’s solution. Cells were counted at 100× magnification (Zeiss Axioskop, Zeiss, Oberkochen, Germany) using a Palmer–Maloney counting chamber [34]. A minimum of 400 cells was counted to ensure statistical significance.

2.3. Exposure to Bloom Tests

During the exposure tests, a microalgae solution was added to three aquaria (70 L of volume) with 6 oysters each containing ≈2 × 107 cells L−1 of Tetraselmis sp. for the control group, while ≈4 × 107 cells L−1 of S. marinoi and ≈1 × 104 cells L−1 of G. catenatum were added for the exposure treatments. Then they were allowed to filter for two hours. The algae concentrations used were based on standard concentrations used for Tetraselmis sp. and S. marinoi in shellfish aquaculture production, while the concentration of G. catenatum was estimated based on natural concentrations in the Sado estuary [37]. The experimental procedures were performed twice to allow replication of the experimental conditions, thus avoiding interference from different handling or water experimental conditions. After the two hours experiments, 6 organisms of each treatment were sampled and opened by cutting the adductor muscle. The gills, the digestive gland and the adductor muscle were removed and weighed, then stored at −80 °C. On average, during each experiment, around 6 × 103 cells of G. catenatum and 1 × 107 cells of S. marinoi were consumed by the oysters. Cell consumption was evaluated by sampling the water tanks at the end of the experiment and counting microalgae cells as described above.

2.4. Physiologic Stress Biomarkers

2.4.1. Samples Treatment and Quantification of Total Protein

All M. angulata tissue samples were briefly washed with ultrapure water to clean debris. Then, about 150 mg of each tissue were homogenized using an electric tissue homogenizer (Tissue Master 125, Omni, Kennesaw, GA, USA); the samples were homogenized in 1.0 mL of phosphate buffer saline solution (PBS, 140 mM NaCl, 3 mM KCl, 10 mM Na2HPO4, 2 mM KH2PO4, pH 7.4) on ice. The homogenates were then centrifuged at 4 ˚C for 15 min at 10,000× g (VWR, Hitachi Koki Co., Ltd., Braselton, GA, USA), and supernatants were collected in 1.5 mL microtubes and frozen at −60 °C. Then, the total protein in each sample was quantified following the Bradford assay [38]. The total protein results were then used to standardize the biomarkers analysis.

2.4.2. Determination of Enzyme Activities

Superoxide Dismutase (SOD) activity was measured indirectly by inhibition of NBT reduction by O2− produced by Xanthine Oxidase (XOD) [34] adapted to a 96-well microplate. The results of this enzymatic assay, after normalization by total protein, are given as the percentage of inhibition mg−1 of total protein.
The assay of catalase (EC 1.11.1.6) was carried out according to the authors of reference [39] and adapted for 96-well microplates as described elsewhere [40]. Absorbance was read at 530 nm and results were presented as μM min−1 mg protein−1.
The enzymatic assay of glutathione S-transferase (GST) activity (EC 2.5.1.18) was performed according to the authors of reference [41] adapted to a 96-well microplate [28]. Results were expressed as nmol min−1 mg−1 of total protein.
Acetylcholinesterase (AchE) activity was determined by following an adaptation of Ellman’s method [42], adapted to 96-well microplates, as described by the authors of reference [43]. Acetylcholinesterase measurements were normalized to total protein concentration as nmol min−1 mg−1 total protein.

2.4.3. Total Ubiquitin Quantification

Total ybiquitin (Ubi) was quantified through indirect enzyme-linked immunosorbent assays (ELISA) (see [44]). Total ubiquitin concentrations in samples were then calculated using a calibration curve previously built by serial dilutions of purified ubiquitin (UbpBIO, USA) standards to give a range of 0 to 0.8 µg ml−1 and then normalized by total protein concentration as µg ml−1 mg−1 total protein.

2.5. Statistical Analysis

The biomarker data were compared using a Permanova test comparing the different treatments using normalized variables (i.e., scaled by subtracting the mean and dividing by the standard deviation). To avoid multiple hypotheses tests a Principal Component Analysis was performed to compare the different tissues and the integrated biomarker response index was calculated and the respective radar plots were used for comparison. Permanova and PCA were performed on primer-E software while the Integrated Biomarker Response (IBR) calculation was made using Excel software.
IBR was performed as described in reference [45] to allow visual and numerical integration of a set of early warning responses measured with biomarkers. Due to greater variability in the response to these stressors in the present study [8,12,30], and to facilitate the direct understanding of the plots, all biomarkers were compared using Z = Y.

3. Results

The biomarkers analyzed presented significant differences between the different studied tissues (Table 1). The gills and the adductor muscles had similar values of ubiquitin and SOD, with the digestive gland being the tissue with the lowest activity of these biomarkers (Figure 1A and Figure 2). The gills were the tissue with the higher values of GST and AChE, followed by the digestive gland, with the adductor muscle being the tissue with the lowest activity of these biomarkers (Figure 1C,E and Figure 2).
There were significant differences between treatments in all tissues analyzed. In general, all tissues presented higher biomarker values in the controls, which resulted in higher IBR values (Figure 1 and Figure 3, Table 2). S. marinoi was the treatment showing the lowest IBR mainly due to the higher CAT and GST activities measured in the G. catenatum treatment when compared to the S. marinoi treatment. Looking at the variation of the biomarkers independently, SOD and total Ubi were higher in the controls when compared to both S. marinoi and G. catenatum treatments. In the digestive gland and gills, AChE was also significantly higher in the controls. Furthermore, in the muscle, there was higher CAT activity in the G. catenatum treatment.

4. Discussion

The results obtained in the present work showed that both G. catenatum and S. marinoi lead to physiological stress in the oyster M. angulata, compared to the control treatment fed with Tetraselmis sp. It is important to note that the used G. catenatum concentrations are found in nature while the ones for S. marinoi are only normal in aquaculture. In general, both treatments lead to a decrease in most biomarkers being more noticeable in the SOD and AChE activity and total Ubi concentrations. Also, the analyzed tissues presented significant variations among them, with the digestive gland presenting the lowest SOD activity and total Ubi. Thus, differences between treatments should be thoroughly analyzed for each tissue. Hence, the next sub-sections will begin with an analysis of the differences between tissues followed by an analysis of the differences between treatments in each tissue.

4.1. Comparison between Tissues

Different tissues of the oyster M. angulata showed different ranges of variation for the tested biomarkers, with the digestive gland presenting the lowest enzyme activities and total Ubi concentrations. Both gills and digestive glands are usually exposed to both water-borne and food-web xenobiotics due to their role in bivalve feeding processes [46,47].
The digestive gland has often been identified as the tissue with higher CAT and GST [46,48], since it is largely exposed to contaminants present in the environment and collected with food. Moreover, the digestive gland has also been identified as a tissue in which detoxification is faster, with several biomarkers involved in the detoxification of xenobiotics (e.g., CAT and GST) [46,48]. This was also the tissue with the greatest variation between the control and the two treatments tested in this work, with both treatments (S. marinoi and G. catenatum) presenting lower biomarker levels. Again, this is likely due to its direct contact with the tested species. This high exposure of the digestive gland to waterborne and food-web xenobiotics has led some authors to identify the digestive gland as a reliable target tissue to investigate the effects of xenobiotics at the cellular, biochemical and molecular levels [49]. Gills represent another tissue which is strongly affected by waterborne and particulate xenobiotics. It was the tissue with a higher IBR value after the digestive gland in the control treatment, but it decreased in the two test treatments. Such reduction and low values in the treatments with S. marinoi and G. catenatum are probably a consequence of direct exposure to the noxious species since the gills are the organ that proceeds with the collection of food into the digestive organs [50].
Of the tested tissues, the adductor muscle is the tissue less exposed to xenobiotics justifying the low IBR. Similarly, it was the tissue with less variance between different treatments, probably due to not being directly exposed to xenobiotics but rather through the organism metabolism.

4.2. Comparison between Treatments

Our results show that the tested phytoplankton species lead to a physiological response in M. angulata tissues, even under short-term exposure (two hours in the present work). Many bivalve species have shown responses in the activity of antioxidant enzymes when exposed to G. catenatum. For instance, the study by the authors of reference [31] showed a high increase in CAT activity in Chlamys farreri after 12 h of exposure (the shortest time period in that work), even though no higher concentration of ROS was detected at that period of time. The authors of reference [51] observed an increase in CAT and GPx activities accompanied by an inhibition of AChE in mussels, cockles and razor shells exposed to a natural bloom of G. catenatum that lasted around a week. However, oysters have proven to be more resistant to stress caused by G. catenatum, as reported by the authors of reference [31], in whose study M. gigas presented responses to G. catenatum only after 48 h of exposure and that were less evident than in Chlamys farreri, which present responses in more biomarkers and sooner than M. gigas. The study in reference [52] also showed no response after exposing M. angulata to G. catenatum for 6 h but recorded increases in both SOD and GST activities after 12 h of exposure. Therefore, a different trend was observed in the present work, with SOD and AChE activities diminishing and total Ubi decreasing, which may be a result of a lowered metabolism of M. angulata because of the paralytic shellfish toxin effect. The inhibition of the nervous system would directly inhibit the AChE activity of which the main effect is to clean the acetylcholine of the cholinergic synapses [34,35]. A lower metabolism would also mean lower ROS production and lower protein degradation by metabolic processes [53]. However, the hypothesis of a reduced metabolism must be analyzed in future works, including the assessment of metabolic rates, for instance, through respirometry. These reactions were also different when compared to exposure to toxins other than PSP with different modes of action. The mussel Hyriopsis cumingii, exposed to microcystin, presented an increase in SOD and GPX activities, while reducing GSH, GST and lipoperoxidation, having an almost opposite reaction in relation to what was seen in M. angulata in the present work. On the contrary, DSP toxins increase GST in mussels and clams as a detoxification pathway, as suggested in the present work [54,55]. In other studies, detoxification processes are known to increase the levels of these biomarkers, mainly CAT, GST and GPx [31,56]. In the present work, an increase in CAT activity in the muscle was identified, with high activity values also being measured in the gills and digestive glands, which are the tissues where the detoxification process is faster [23]. Moreover, the G. catenatum treatment also presented high GST (like the control treatment) activity in both gills and digestive glands, while all other biomarkers tested showed a decreasing trend. Both enzymes are often responsible for detoxification processes and, therefore, further analyses are needed to test whether the different trends of these biomarkers are a result of detoxification processes by testing different concentrations and verifying the relative toxicity of different PSP toxins.
Regarding the S. marinoi treatment, there is a significant lack of information in the current scientific bibliography, as this species is considered harmless to bivalves and is often used as food in aquaculture. However, when in high densities, phytoplankton species with setae, barbs, processes or spines like Chaetoceros, Skeletonema and Rhizosolenia may harm aquatic animals due to being trapped in their gills. Skeletonema species are known to affect other animals, such as fish, by blocking and damaging their gills due to inflammatory reactions and an excess of mucus production [57,58,59]. No information was found on the effects of Skeletonema species on bivalves, although similar effects were described in mussels exposed to high densities of the diatom species Rhizosolenia chunii [60]. Additionally, S. marinoi produce polyunsaturated aldehyde (PUA) [20]. PUAs have shown toxicity (mainly over reproduction) in many different invertebrate taxa, such as Copepoda, Artemia salina (Branchiopoda), Paracentrotus lividus (Echinoidea), Asterias rubens (Asteroidea), Nereis virens and Arenicola marina (Polychaeta) and even Ciona intestinalis (Ascidiacea) [21,22,23,24,25]. However, the only information available regarding the PUA effect in bivalves is that Decadenial PUA may affect M. gigas hemocytes, without any studies having been performed on the effects of PUA on living oysters [61]. Nevertheless, in the present work, the presence of S. marinoi led to a decrease in the activity of all biomarkers and, therefore, the possibility that S. marinoi cause stress in M. angulata (either by physical damage or toxicity) should be further analyzed in future studies.
The present work found that even short-term exposure to blooms of G. catenatum and S. marinoi can affect the physiological state of M. angullata. Thus, further studies comparing different PUA compounds and concentrations are necessary. Specifically, addressing the Skeletonema sp. and PUA effects on bivalves is important in order to correctly assess the risk that these species, often used as food, pose to commercial activities. Furthermore, it is important to perform long-term studies on the effects of Skeletonema sp. on bivalves. This work is thus an important step in proceeding with further physiological and histological studies.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/sci5030030/s1, Figure S1: Location of the aquaculture from which the oysters Magallana angulata were collected.

Author Contributions

The contribution of each author for the present work was: conceptualization, R.C., M.D., A.C.B. and P.C.; methodology, S.C., J.P.C.C., J.H., F.C., B.V., A.A., I.J.F. and M.D.; software, R.C.; validation, A.C.B., M.D. and A.A.; formal analysis, R.C.; investigation, F.C., S.C., J.H., J.P.C.C., B.V., I.J.F. and R.C.; resources, P.C., A.C.B., A.A. and M.D.; data curation, F.C., J.P.C.C. and R.C.; writing—original draft preparation, R.C.; writing—review and editing, all authors contributed equally; visualization, R.C.; supervision, P.C., A.C.B., A.A. and M.D.; project administration, P.C., A.C.B., A.A. and M.D.; funding acquisition, P.C., A.C.B., A.A. and M.D. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Portuguese Foundation for Science and Technology, grant numbers (UI/BD/151399/2021, PD/BD/135064/2017, COVID/BD/152137/2021, CEECIND/00095/2017 and 2020.01797.CEECIND, SFRH/BD/145746/2019, 2020.06325.BD, UIDB/04292/2020, UIDB/04378/2020 and LA/P/0140/2020). Additionally, this work was also co-funded by the MAR2020, Portugal 2020 and the European Union EMFF projects (MAR-02.01.01-FEAMP-0050, MAR-02.01.01-FEAMP-0051 and MAR-01.03.02-FEAMP-0013) and by the European Union’s Horizon 2020 Research and Innovation Program under grant agreement N810139.

Institutional Review Board Statement

Ethical review and approval were waived for this study since the tested animals are not from a taxa requiring ethical review to be used in animal science trials. However, all possible procedures were performed to minimize animal suffering. Rui Cereja has a category B certification according to the Federation of European Laboratory Animal Science Associations (FELASA).

Informed Consent Statement

Not applicable.

Data Availability Statement

Data are available through direct contact with the corresponding author.

Acknowledgments

For the present work, Rui Cereja acknowledges three different PhD scholarships (PD/BD/135064/2017, COVID/BD/152137/2021, BI-DOUTORANDO-COASTNET), Ana C. Brito and P. Chainho a senior researcher scholarship (CEECIND/00095/2017 and 2020.01797.CEECIND, respectively), J.P.C. Cruz, S. Cabral and F. Carvalho hold a PhD grant (UI/BD/151399/2021, SFRH/BD/145746/2019 and 2020.06325.BD, respectively), and all granted by Fundação para a Ciência (FCT) e Tecnologia. This work received support from the MARECentre strategic grant (UIDB/04292/2020), also granted by FCT. This work was funded by the Crassoreab project (MAR-02.01.01-FEAMP-0050) AQUASADO project (MAR-02.01.01-FEAMP-0051), project NIPOGES (MAR-01.03.02-FEAMP-0013) and was also supported by funding from the European Union’s Horizon 2020 Research and Innovation Program under grant agreement N810139: Project Portugal Twinning for Innovation and Excellence in Marine Science and Earth Observation—PORTWIMS. The projects UIDP/04378/2020 and UIDB/04378/2020 of the Research Unit on Applied Molecular Biosciences—UCIBIO and the project LA/P/0140/2020 of the Associate Laboratory Institute for Health and Bioeconomy—i4HB are also acknowledged.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

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Figure 1. Biomarker values for the three tested tissues (gills, adductor muscle and digestive gland) and the three treatments (control—Tetraselmis sp. in blue, Skeletonema marinoi in orange and Gymnodinium catenatum in green). Bars represent the mean and error bars are the standard deviation for (A) superoxide dismutase activity (SOD), (B) Catalase activity (CAT), (C) glutathione S-Transferase activity (GST), (D) total ubiquitin concentrations (Ubi) and (E) acetylcholinesterase activity (AChE). Statistical significance is not shown in this figure since the performed analysis is multivariated and is, rather, seen in Figure 2 and Figure 3 and Table 1 and Table 2.
Figure 1. Biomarker values for the three tested tissues (gills, adductor muscle and digestive gland) and the three treatments (control—Tetraselmis sp. in blue, Skeletonema marinoi in orange and Gymnodinium catenatum in green). Bars represent the mean and error bars are the standard deviation for (A) superoxide dismutase activity (SOD), (B) Catalase activity (CAT), (C) glutathione S-Transferase activity (GST), (D) total ubiquitin concentrations (Ubi) and (E) acetylcholinesterase activity (AChE). Statistical significance is not shown in this figure since the performed analysis is multivariated and is, rather, seen in Figure 2 and Figure 3 and Table 1 and Table 2.
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Figure 2. Principal Component Analysis comparing the enzyme activities in the different tissues tested: gills (G), adductor muscle (AM) and digestive gland (DG). The biomarkers tested were the activities of superoxide dismutase (SOD), Catalase, Glutathione S-Transferase (GST), acetylcholinesterase (AChE), and the concentration of total ubiquitin (Ubi). The first two principal components (PC) explained 85.8% of the total variance, with 66.7% explained in PC 1 and 19.2% in PC2.
Figure 2. Principal Component Analysis comparing the enzyme activities in the different tissues tested: gills (G), adductor muscle (AM) and digestive gland (DG). The biomarkers tested were the activities of superoxide dismutase (SOD), Catalase, Glutathione S-Transferase (GST), acetylcholinesterase (AChE), and the concentration of total ubiquitin (Ubi). The first two principal components (PC) explained 85.8% of the total variance, with 66.7% explained in PC 1 and 19.2% in PC2.
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Figure 3. Radar Chart for the IBR values of each treatment and tissue. (A) Gills, (B) adductor muscle and (C) digestive gland. The blue line represents the control treatment, the orange line the Skeletonema marinoi treatment and the green line the Gymnodinium catenatum treatment. Each chart presents normalized value for the activities of Superoxide dismutase (SOD), Catalase, Gluthatione S-transferase (GST), acetylcholinesterase (AChE) and the concentrations of total ubiquitin (Ubi). Higher values mean higher concentrations of a certain biomarker and thus the area of the polygon for a certain color gives the relative response of a certain tissue to the group of analyzed biomarkers.
Figure 3. Radar Chart for the IBR values of each treatment and tissue. (A) Gills, (B) adductor muscle and (C) digestive gland. The blue line represents the control treatment, the orange line the Skeletonema marinoi treatment and the green line the Gymnodinium catenatum treatment. Each chart presents normalized value for the activities of Superoxide dismutase (SOD), Catalase, Gluthatione S-transferase (GST), acetylcholinesterase (AChE) and the concentrations of total ubiquitin (Ubi). Higher values mean higher concentrations of a certain biomarker and thus the area of the polygon for a certain color gives the relative response of a certain tissue to the group of analyzed biomarkers.
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Table
Table 1. Statistic analysis including the PerMANOVA and pair-wise results comparing the biomarker values for different tissues (Ti) and different treatments (Tr) in each tissue (Tr, nested in Ti). The degrees of freedom (df), the sum of squares (SS), the mean squares (MS), pseudo-F distribution values, the p-value (P(perm)) and the number of permutations (perms) of the PerMANOVA analysis are presented. For pair-wise, the group comparisons were with G for gills, AM for adductor muscle, DG for digestive gland, C for control treatment, Sm for S. marinoi treatment and Gc for G. catenatum treatment. The t dist is the t distribution value, and Perm is the number of permutations. p-values under 0.05 are considered as demonstrating that the variables being compared are significantly different and are marked in bold.
Table 1. Statistic analysis including the PerMANOVA and pair-wise results comparing the biomarker values for different tissues (Ti) and different treatments (Tr) in each tissue (Tr, nested in Ti). The degrees of freedom (df), the sum of squares (SS), the mean squares (MS), pseudo-F distribution values, the p-value (P(perm)) and the number of permutations (perms) of the PerMANOVA analysis are presented. For pair-wise, the group comparisons were with G for gills, AM for adductor muscle, DG for digestive gland, C for control treatment, Sm for S. marinoi treatment and Gc for G. catenatum treatment. The t dist is the t distribution value, and Perm is the number of permutations. p-values under 0.05 are considered as demonstrating that the variables being compared are significantly different and are marked in bold.
Permanova
SourcedfSSMSPseudo-FP(perm)perms
Ti228.45814.2299.28480.00029954
Tr(Ti)622.9513.82522.4960.00959923
Res3350.5731.5325
Total41105.7
Tissue pair-wiseTreatments (in Gills) pair-wise
Groupst distp-valuePerm.Groupst distp-valuePerm.
G, AM1.76220.03689949C, Sm2.80610.029235
G, DG3.01130.0019951C, Gc2.13910.026835
AM, DG4.19430.00019944Sm, Gc0.586560.708635
Treatments (in Aduct. Muscle) pair-wiseTreatments (in Gills) pair-wise
Groupst dist.p-valuePerm.Groupst dist.p-valuePerm.
C, Sm1.86450.107835C, Sm2.14450.0233126
C, Gc2.70350.027635C, Gc2.41140.0258126
Sm, Gc1.29110.199335Sm, Gc1.05550.3845126
Table
Table 2. Integrated Biomarker Response index values for the different treatments (Control, Skeletonema marinoi and Gymnodinium catenatum for the three analyzed tissues (gills, adductor muscle and digestive gland)).
Table 2. Integrated Biomarker Response index values for the different treatments (Control, Skeletonema marinoi and Gymnodinium catenatum for the three analyzed tissues (gills, adductor muscle and digestive gland)).
TissueControlS. marinoiG. catenatum
Gills9.2335428673.0722343764.564557118
Adductor Muscle6.1697148745.5218085215.230830722
Digestive gland8.001916040.7435429991.68210452
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Cereja, R.; Cruz, J.P.C.; Heumüller, J.; Vicente, B.; Amorim, A.; Carvalho, F.; Cabral, S.; Chainho, P.; Brito, A.C.; Ferreira, I.J.; et al. Short-Term Biochemical Biomarkers of Stress in the Oyster Magallana angulata Exposed to Gymnodinium catenatum and Skeletonema marinoi. Sci 2023, 5, 30. https://doi.org/10.3390/sci5030030

AMA Style

Cereja R, Cruz JPC, Heumüller J, Vicente B, Amorim A, Carvalho F, Cabral S, Chainho P, Brito AC, Ferreira IJ, et al. Short-Term Biochemical Biomarkers of Stress in the Oyster Magallana angulata Exposed to Gymnodinium catenatum and Skeletonema marinoi. Sci. 2023; 5(3):30. https://doi.org/10.3390/sci5030030

Chicago/Turabian Style

Cereja, Rui, Joana P. C. Cruz, Joshua Heumüller, Bernardo Vicente, Ana Amorim, Frederico Carvalho, Sara Cabral, Paula Chainho, Ana C. Brito, Inês J. Ferreira, and et al. 2023. "Short-Term Biochemical Biomarkers of Stress in the Oyster Magallana angulata Exposed to Gymnodinium catenatum and Skeletonema marinoi" Sci 5, no. 3: 30. https://doi.org/10.3390/sci5030030

APA Style

Cereja, R., Cruz, J. P. C., Heumüller, J., Vicente, B., Amorim, A., Carvalho, F., Cabral, S., Chainho, P., Brito, A. C., Ferreira, I. J., & Diniz, M. (2023). Short-Term Biochemical Biomarkers of Stress in the Oyster Magallana angulata Exposed to Gymnodinium catenatum and Skeletonema marinoi. Sci, 5(3), 30. https://doi.org/10.3390/sci5030030

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