# Domoic acid production by a Pseudo-nitzschia australis strain under zinc and copper exposure

Marie Bassez, Hélène Hégaret, Jean-François Maguer, Yoann Asquoët, Marie

Legain, Lucie Vannier, Gabriel Dulaquais

► To cite this version:

Marie Bassez, Hélène Hégaret, Jean-François Maguer, Yoann Asquoët, Marie Legain, et al.. Domoic acid production by a Pseudo-nitzschia australis strain under zinc and copper exposure. Aquatic Toxicology, 2026, 290, pp.107616. 10.1016/j.aquatox.2025.107616. hal-05390535

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# Domoic acid production by a *Pseudo-nitzschia australis* strain under zinc and copper exposure

Marie Bassez, Hélène Hégaret, Jean-François Maguer, Yoann Asquoët, Marie Legain, Lucie Vannier, Gabriel Dulaquais*

Laboratoire des Sciences de l'Environnement Marin UMR 6539 CNRS/UBO/IRD/Ifremer, Université de Bretagne Occidentale, Plouzané, F-29280, France

<figure><img src="image_3.png" /></figure>

## ARTICLE INFO

**Keywords:**

HAB

Domoic acid

Pseudo Nitzschia australis

copper

zinc

## ABSTRACT

The diatom species *Pseudo-nitzschia australis* can produce domoic acid (DA), a neurotoxin- responsible for amnesic shellfish poisoning. Copper (Cu) and zinc (Zn) are essential trace metals for marine phytoplankton, but they can become either limiting or toxic at pico- to subnanomolar ionic concentrations—levels that are can be reached in coastal ecosystems. The effect of exposure to these metals on DA production remains unclear for Cu and is largely unknown for Zn. In this study, we investigated the effects of toxic picomolar concentrations of Cu²⁺ and four non-limiting concentrations of Zn²⁺ on the metabolism and physiology of a toxic *P. australis* strain isolated from the coastal waters of North Biscay (France). Using principal component analysis, we observed changes in cell populations over time depending on metal exposure. Cu²⁺ toxicity was marked by a 35 % decrease in maximum cell density and a reduction in growth rate (μ·Cu = 0.55 μαx). DA production was differentially modulated by the two metals: toxic Cu²⁺ levels stimulated DA synthesis (+200 %), while elevated Zn²⁺ bioavailability significantly decreased it (by up to –85 %), including when Zn²⁺ was combined with toxic levels of Cu²⁺ (–65 %). We further discuss DA production by *P. australis* as a potential protective mechanism against oxidative stress. Additional data on intracellular glutathione (GSH) quotas—an important reactive oxygen species (ROS) scavenger and Cu²⁺ chelator—are presented and linked to Zn²⁺ bioavailability. GSH cell quotas were significantly correlated with DA production (*p* < 0.05) further supporting existing links between metal exposition, oxydative stress and DA production. This study suggests that ambient concentrations of Cu²⁺ and Zn²⁺ are critical factors regulating DA production in coastal marine systems.

## 1. Introduction

Among the wide diversity of autotrophic phytoplankton, diatoms are key players in ocean biogeochemical cycles notably due to their massive blooms in temperate waters and at high latitudes (Leblanc et al., 2012). Diatoms account for over 40 % of primary production in the ocean and dominate particulate organic carbon export below the euphotic zone (Tréguer et al., 2018). Among diatoms, *Pseudo-nitzschia* spp. are pennate diatoms widely distributed in the ocean. *Pseudo-nitzschia* genus comprises approximately 60 56 species, with 29 of which are recognize toxic (Lundholm et al., 2024) and produce domoic acid (DA), a potent neurotoxin causing human poisoning (Saeed et al., 2017) and lead to fisheries closures. Human poisoning occurs after ingestion of contaminated shellfish and can, in severe cases, result in death (Teitelbaum et al., 1990). *Pseudo-nitzschia* spp. are a leading cause of harmful algal blooms (HABs) especially *Pseudo-nitzschia australis*, that induced

massive DA contaminations along the western coast of the United States (Trainer et al., 2000; Anderson et al., 2006; Lewitus et al., 2012; McCabe et al., 2016; Ryan et al., 2017) as well as in Western Europe (Nezan et al., 2010; Klein et al., 2010; Ayache et al., 2021) over the past decades.

Despite public health concerns, the origin and dynamics of DA production by *Pseudo-nitzschia* spp. remain unclear and may vary between species and ecotypes. DA synthesis requires energy and thus substantial irradiance (Lelong et al., 2012a), linking DA production to photosynthetic activity (Brunson et al., 2018; Pan et al., 1998). Temperature increases, nutrient limitations, growth phase and physiological state of cells are all factors affecting cellular DA production by *P. australis* (Howard et al., 2007; Lelong et al., 2012a; Maldonado et al., 2002; Pan et al., 1998, 2001; Thorel et al., 2014; Cochlan et al., 2023; Sauvey et al., 2023). Additional studies have proposed links between production of DA and trace metals concentrations. DA could be synthesized by *Pseudo-nitzschia* spp. as a metal chelator to make up for nutrient-stress

<footnote>* Corresponding author.
E-mail address: gabriel.dulaquais@univ-brest.fr (G. Dulaquais).</footnote>
situations, specifically Fe limitation or Cu toxicity (Rue and Bruland, 2001; Wells et al., 2005; Lelong et al., 2012b). DA production under copper toxicity may also be a strategy of *Pseudo-nitzschia* spp to mitigate oxidative stress (Liu et al., 2021). Previous studies showed that exposure to high Cu²⁺ concentrations increases intercellular reactive oxygen species (ROS) content (Pinto et al., 2003; Knauert and Knauer, 2008). Cu can cycle between oxidation states I and II. As a result, Cu can catalyze the production of ROS through the metal catalyzed Haber-Weiss reactions with the production of hydroxyl radicals.

While the effect of Fe and Cu was extensively considered over the past decades (Trainer et al., 2012; Lelong et al., 2012b; Trick et al., 2018; Liu et al., 2021), the effect of zinc (Zn) toxicity on DA production has received little attention (Rhodes et al., 2006). Fe, Zn and Cu are essential metals for cellular biochemistry (Sunda and Huntsman, 1995a) and they can limit the growth of diatoms, including *Pseudo-nitzschia* spp., at extremely low ionic concentrations (Sunda and Huntsman, 1995a; Maldonado et al., 2002). In addition to limitation, Cu and Zn can become toxic at picomolar and nanomolar ionic concentrations respectively (Brand et al., 1986; Sunda and Huntsman, 1995b). At these concentrations, Zn inhibits the reductive stage of pigment biosynthesis (De Filippis et al., 1981) and Cu inhibits cell growth by interfering with the enzyme responsible for electron transport (Hindarti and Larasati, 2019) in phytoplankton cells. In addition, as state earlier high Cu concentration trigger oxidative stress. The oxidative stress generates by ROS can be toxic to cells, damaging lipid, protein, and DNA (Kehrer, 2000). Cellular oxidative stress can be assessed by measuring the cellular GSH quota, as these parameters are inversely correlated (Rijstenbil et al., 1994). GSH is a multifunctional tri-peptide with diverse biochemical roles. It is easily oxidized or reduced, making this molecule a major ROS scavenger (Ahner et al., 2002).

In open ocean waters, organic complexation keeps these elements within optimal ionic concentration ranges (Whitby et al., 2024). However, in coastal and estuarine environments, Cu and Zn concentrations are 100 to 1000 times higher than in open ocean surface waters (Bruland and Franks, 1983) with ionic concentrations close or higher than toxic threshold levels (Dulaquais et al., 2020; Prego and Cobelo-García, 2003). These high levels of Cu and Zn result from soil erosion (Noulas et al., 2018), the deposition of natural or anthropogenic atmospheric dust (Conway and John, 2014; Blossom, 2007) and river discharge (Gaillardet et al., 2003; Richon and Tagliabue, 2019). Additional anthropogenic inputs from wastewater treatment plant discharge (Constantino et al., 2017; Dulaquais et al., 2020), industrial point-sources (Andres et al., 2000; Prego and Cobelo-García, 2003) and even tourism (Cindrić et al., 2015) further alter estuarine and coastal biogeochemistry of these metals with ionic concentrations reaching toxic levels. In this context, understanding the effect of Zn and Cu on the DA production by *P. australis* is of economic and public health interest.

Here we examine DA production by a *P. australis* strain exposed to toxic and non-toxic levels of Cu²⁺ at four non-limiting Zn²⁺ concentrations relevant to natural field conditions. Using morphological, physiological GSH and DA measurements, we attempt to decipehr the links between these metals, oxidative stress and toxin production by *P. australis* and to highlight the role of Zn in DA production pathway.

## 2. Materials and methods

### 2.1. Algal culture

All culture experiments were conducted with the *P. australis* strain IFR-CC 22-041, a non-axenic culture isolated from the North Biscay coastal waters, Brittany, France during spring 2022. Identification of the strain was performed by transmission electron microscopy at IFREMER (Concarneau, France). Between isolation and start of culture experiments the strain was maintained in primary L1 medium (Guillard and Hargraves, 1993) under batch conditions in sterile plastic culture boxes at 17±1 °C, exposed to a photosynthetic photon flux density of 150 µmol

photons m⁻² s⁻¹ with a 12:12 light:dark (L:D) cycle (control PPFD).

Cells from this initial culture medium were inoculated into a secondary medium, under control PPFD condition, and acclimatized for 3 weeks. In this medium, cells were kept in the exponential phase by weekly sub-culture. This secondary culture medium was composed of natural coastal seawater collected from the Iroise Sea (Argenton, France, the 20th January 2023), filter-sterilized (0.45 µm, HATF millipore) and enriched with nutrients, EDTA, vitamins and metals (calculated using visual MinTEQ software) to produce a modified L1 medium with 0.1 µmol l⁻¹ MnCl₂, 0.09 µmol l⁻¹ Na₂MoO₄; FeCl₃: 1 µmol l⁻¹ and 100 µmol l⁻¹ EDTA. Total iron (Fe) concentration was set to 1 µmol l⁻¹ to limit the precipitation of iron oxyhydroxides on the cell surface (John et al., 2007). In this medium, total zinc [Zn] and copper [Cu] concentration were set to 76.5 nM and 19.6 nM respectively resulting in non-limiting and nontoxic free ionic concentration of 14 pmol l⁻¹ for Zn²⁺ and 12 fM for Cu²⁺.

### 2.2. Experimental setup

After acclimation in the secondary medium, cells were inoculated into four different culture media (300 mL) for 10 days in triplicate to start experiments (day 0) with a targeted initial cell concentration of 5000 cell mL⁻¹. All were exposed to PPFD control condition. The four different culture tested media were:

- "Control": the secondary medium ([Zn] = 76.5 nmol l⁻¹ [Zn²⁺] = 14 pmol l⁻¹; [Cu] = 19.6 nmol l⁻¹; [Cu²⁺] = 12 fmol l⁻¹)

- "+Zn": the secondary medium spiked with Zn ([Zn] = 2.29 µmol l⁻¹ [Zn²⁺] = 433 pmol l⁻¹; [Cu] = 19.6 nmol l⁻¹; [Cu²⁺] = 12 fmol l⁻¹) or

- "+Cu": the secondary medium spiked with Cu: ([Cu] = 19.6 µmol l⁻¹ [Cu²⁺] = 15 pmol l⁻¹; [Zn] = 38.25 nmol l⁻¹ [Zn²⁺] = 8.8 pmol l⁻¹),

- "+Zn+Cu": the secondary medium spiked with Cu²⁺ and Zn²⁺ simultaneously: ([Cu] = 19.6 µmol l⁻¹; [Cu²⁺] = 15 pmol l⁻¹; [Zn] = 0.46 µmol l⁻¹, i.e. [Zn²⁺] = 106 pmol l⁻¹).

### 2.3. Specific growth rate, morphological and physiological measurements

All equipment used for culture monitoring was sterile, and sub-sampling was performed under a laminar flow hood to avoid external contamination. 0.5 mL of each culture bottle was collected daily to monitor the cell density. Cell density was measured by light microscopy (Leitz Wetzlar®) immediately after sampling using a Nageotte cell. *P. australis* cells were counted at least in 20 strips of the Nageotte cell to have a homogeneous repartition of cells. As each strip has a volume of 1.25 µL, the number of cells were divided by the total volume: 1.25 * number of counted strips. Specific growth rates were calculated as the linear regression of the natural log (cell concentration) vs. time on the exponential growth phase according to Guillard (1973). We determined the exponential phase by determining the maximum coefficient of determination (r²) by fitting linear regression to semi-logarithmic plots of the cell concentrations as described in Sauvey et al. (2023). Specific growth rate (µ, d⁻¹) were determined daily in triplicate for each treatment.

$$ \mu (d^{-1}) = \frac{LnN_2 - LnN_1}{t2 - t1} $$

Where t is time (days) and N₁ and N₂ are cell concentrations (cells mL⁻¹) at t1 and t2, respectively.

One mL aliquots of each culture were collected daily for morphological and physiological measurements using single use sterile plastic pipettes. Analyses were carried out using flow cytometry (Guava® easyCyte™ 1st generation cytometer - flow rate: 1.18 µL s⁻¹) according to the protocol described in Lelong et al. (2011). Cell size and complexity were obtained by Forward Scatter (FSC; light diffracted under 10°) and Side Scatter (SSC; light diffracted at 90°) detection respectively. Chlorophyll a autofluorescence was detected at long
<figure><img src="image_4.png" /><figcaption>Fig. 1. A Cell density along with time in the different culture media, standard errors (SE) are indicated; B Semi log plot of cell density along with time, length of exponential phase for the different treatments are indicated on the top of the panel; C Calculated growth rate during the exponential phase for each treatment. D Maximum cell density observed for each treatment. Results are presented as Mean±SE, letters indicate significant differences between treatments (p < 0.05).</figcaption></figure>

wavelengths (FL3, 670 nm). Neutral lipid content were estimated using BODIPY 493/503 (Invitrogen, Eugene, OR, USA) (Invitrogen, Eugene, OR, USA) fluorescence probe. Instrumental settings of flow cytometer remained unchanged throughout the four experiments for consistency between results.

Morphology, chlorophyll a autofluorescence and neutral lipid content of *P. australis* cells grown under the different metal conditions were compared between treatments at day 6 (exponential phase) and 10 (decline phase) and between these two phases to identify metal growth phase effects on the morphology and metabolism of cells.

## 2.4. Domoic acid quantification and production rate

Five mL aliquots of each culture bottle (n = 12) were collected daily for the determination of total DA concentrations. Samples were placed in 5.0 mL microtube (Eppendorf Tubes®) and kept at -20 °C until analysis. The day before analysis, samples were thawed and sonicated on ice for 2 min (2 s - 8 s, 13 W, MISONIX®), then filtered with sterile cellulose acetate syringe filters (0.22 µm, Millex®-GS, Merck). DA concentrations were determined using an ELISA kit (ABRAXIS®, eurofins) following the manufacturer recommendations. According to manufacturer, kits permit an accurate detection of DA for concentrations ranging from 6.5 to 10 000 ng l⁻¹. All samples with DA < 6.5 ng l⁻¹ were considered below the detection limit. For each culture bottle, samples were run in duplicate, and coefficients of variation (CVs) were calculated to check data

repeatability (<10 %). Total cell-normalized DA concentrations (TCN-DA fg cell⁻¹) were defined as the ratio between total DA concentrations and cell densities. Total DA was measured daily under all conditions of the experiment. DA production rates were calculated during the exponential phase and according to the following equation as described in Tong et al. (2011):

$$ \text{Net total DA production (fg mL}^{-1} \text{ Cell}^{-1} \text{d}^{-1}) = \frac{TDA_2 - TDA_1}{(N_1 - N_2) / \ln\left(\frac{N_2}{N_1}\right) \times (t_2 - t_1)} $$

In this formula TDA₂, TDA₁ and N₂, N₁ representing respectively total DA concentrations and cell densities (cell mL⁻¹) at t₂ and t₁. The term net is used since the calculated rates represent effective production by *P. australis* minus degradation. Net TDA production rates were determined daily in triplicate for each treatment.

## 2.5. Glutathione cell quota quantification

Due to water budget limitations, cellular contents of glutathione (GSH) were only measured at the end of the experiment, when all culture were in the decline phase (day 10), cells were harvested by filtration of 100 mL of each culture on a pre-combusted GF/F 25 mm filter (0.7 µm, Whatmann). Filters were kept in glass tubes (10 mL) at -20 °C until
<figure><img src="image_5.png" /><figcaption>**Fig. 2.** Flow cytometry measurements (forward scatter, FSC; side scatter, SSC; chlorophyll a autofluorescence, Chl a; neutral lipid content), total cell normalized domoic acid concentration (total CN-DA, fg cell⁻¹) and glutathione cell quota (fg cell⁻¹) of cells growing in the different culture media. Results for the exponential phase (day 6) are presented in the upper panel. Results for the decline phase (day 10) are presented in the lower panel. Letters indicate significant differences between culture media. Stars indicate difference between growth phases for a given culture medium. Arrows indicate the direction of change between the two phases of growth. Flow cytometry results are in arbitrary unit (a.u.).$</figcaption></figure>

extraction. Extraction of cell organic content was performed following the protocol described in Risøet al. (2021). Extracts were stored at 4 °C in the dark until analyses (two days after extraction). For analyses, 500 µL aliquots of the extracts were placed together with 6 mL of artificial seawater (Fourrier et al., 2022) in a voltametric glass cell. GSH concentrations were determined using cathodic stripping voltammetry by the standard addition method following the protocol described by Perнет-Coudrier et al. (2013). Cellular GSH quotas were calculated considering the concentrations measured in voltametric cell, dilution factors and cell densities. Uncertainties were calculated using the standard deviation of triplicate analysis.

## 2.6. Statistics

All results were reported as the mean ± standard error (SE). Statistical analyses were performed using R software. Significant differences were estimated using an ANOVA test. This test was performed after checking the data distribution. A Shapiro-Wilk test was used to check that the data followed a normal distribution and variances homogeneity was verified by performing the Levene test. Finally, a post hoc test was used to assess different metal concentrations effect on the physiological data of *P. australis*. For each statistical result, a probability *p* < 0.05 was considered significant. Data were further analyzed using principal components analysis (PCA) models at day 1 (post inoculation), 6 (exponential phase) and 10 (decline phase) to better identify the effect of metal exposure with time.

# 3. Results

## 3.1. Effect of Cu²⁺ and Zn²⁺ on growth rate and maximum cell densities

Maximum cell densities, duration of exponential phase and growth rates were significantly (*p* < 0.05) different between treatments (Fig. 1). The maximum cell densities reached for control, +Zn, +Zn+Cu and +Cu treatments were respectively 30.7 ± 0.7 10³; 30.3 ± 2.2 10³; 20.9 ± 1.6 10³ and 19.8 ± 0.7 10³ cell mL⁻¹ (Fig. 1A and D). Exponential phase starts on day 1 for all treatments and end on day 6 for the control, on day 7 for +Zn and +Zn+Cu conditions and on day 9 for +Cu condition (Fig. 1B). At day 6 all culture were in the exponential phase. At day 10 they were all in the decline phase. During exponential phases, growth rates for control, +Zn, +Zn+Cu and +Cu treatments were respectively of 0.31 ± 0.02; 0.27 ± 0.02; 0.21 ± 0.04 and 0.17 ± 0.02 d⁻¹ (Fig. 1C). Exposure to +Cu condition resulted in a 58 % decrease of the growth rate and 36 % decrease of maximum cell density compared to the control condition. Exposure to +Zn condition did not however have any significant effect on the growth rate neither on the maximum cell density compared to the control condition. When both metals were added (+Zn+Cu condition), the growth rate was lowered by 33 % and max cell density was decreased by 32 % (Fig. 1).

## 3.2. Effect of Cu²⁺ and Zn²⁺ treatment on morphology, chlorophyll a autofluorescence and lipid content of P. australis

On day 6, an increase of chlorophyll *a* autofluorescence (+10 ± 3 %, *p* < 0.05) was observed in the three metal treatment conditions compare to the control. On day 10, only the complexity of cells that grew in the +Cu treatment was different from the control condition (-20 ± 6 %; *p* <
<figure><img src="image_6.png" /><figcaption>Fig. 3. A. Total domoic acid concentration (TDA) in the different culture media along with time. B. Cell normalized total domoic acid concentration (TC~N~DA) in culture media along with time. C. Net Total domoic acid production rate during the exponential phase in the different culture media. Results are presented as Mean ±SE, letters indicate significant differences between treatments (*p* < 0.05).</figcaption></figure>

0.05).

From the exponential (day 6) to the decline (day 10) phase, the morphology of cells was slightly affected (Fig. 2). In the control condition, cell size decreased by 24 ± 9 % (*p* < 0.05), while cell complexity rose by 20 ± 7 % (*p* < 0.05). A 30 ± 14 % (*p* < 0.05) increase in complexity was also observed for cells that grew in the +Zn+Cu condition. For all treatments, chlorophyll α autofluorescence and neutral lipid content drastically decreased by 34 ± 4 % and 42 ± 4 % respectively (*p* < 0.05, Fig. 2).

### 3.3. *Glutathione cell content of P. australis after Cu²⁺ and Zn²⁺ exposure*

At the end of the experiment (decline phase day 10), GSH cellular quotas of *P. australis* cells were significantly different (*p* < 0.05; Fig. 2) in the four treatments. In the +Zn condition, GSH cell quotas (179.0 ± 6.1 fg cell⁻¹) were 3 times higher than in the control medium (57.4 ± 6.7 fg cell⁻¹). Meanwhile, cells that grew in the +Cu condition exhibited GSH cell quotas 1.8 times lower (30.3 ± 3.0 fg cell⁻¹) than in the control. The +Zn+Cu condition showed an intermediate response between the +Cu and +Zn treatments (87.7 ± 12.7 fg cell⁻¹; Fig. 2).

### 3.4. Total DA, cell normalized DA and DA production by P. australis

Total DA concentrations in the culture media (TDA) were measured throughout the entire growth phase (Fig. 3A). TDA ranged from 340 ± 42 ng l⁻¹ at day 1 in the +Zn+Cu condition to 10,385 ± 1047 ng l⁻¹ in the control condition at day 10. Cell normalized total DA (TC~N~DA) ranged from 21 fg cell⁻¹ at day 8 in the +Zn condition to 524 fg cell⁻¹ at day 10 in the +Cu condition.

At day 1, both TDA and TC~N~DA were statistically similar across all

tested conditions (*p* > 0.05). However, from day 3 until the end of the experiment, significant differences (*p* < 0.05) in both TDA and TC~N~DA were observed among the treatment conditions (Fig. 3A and B). In the early exponential phase and decline phase, TDA concentrations in the +Cu and control media were similar. During mid and end of exponential phase (day 4 to 8), TDA concentrations sharply increased for +Cu and control conditions, however concentrations were significantly higher (+66 ± 25%; *p* < 0.05) in the +Cu medium than in the control. At the same time, for culture media +Zn and +Zn+Cu, TDA concentrations increased slowly over time and TC~N~DA remained stable. Both TDA and TC~N~DA were 2 to 10 times lower than those observed in the control condition (*p* < 0.05). Total DA production rates were calculated for the four conditions during the exponential phase. Production rate were different between metal treatments (*p* < 0.05) and varied between 4 ± 4 fg cell⁻¹d⁻¹ for the +Zn and to 91 ± 15 fg cell⁻¹d⁻¹ for the +Cu condition. Meanwhile, control conditions presented an intermediate DA production rate of 39 ± 11 fg cell⁻¹d⁻¹.

### 3.5. Assessing the effects of cu²⁺ and zn²⁺ exposure on P. australis using PCA

At day 1, no differences could be observed among the four *P. australis* culture conditions, resulting in one single cluster (Fig. 4). At day 6, during the exponential growth phase, three distinct clusters were depicted along principal component 1 (40.4 %), highlighting differences between high TDA and high cell density. Control and +Cu conditions were well-separated forming two independent clusters. +Zn and +Zn+Cu conditions formed an intermediate cluster in the middle of the two others. At day 10, when all cultures where in decline phase, four independent clusters corresponding to each culture condition were

<figure><img src="image_7.png" /><figcaption>Fig. 4. Principal component analysis of the 12 culture experiments (3 replicates of each 4 conditions) from left to right at day 1 (24 h after inoculation in the specific media), day 6 (exponential phase) and day 10 (decline phase). Distinction between populations is gradually observed from day 1 to day 10.</figcaption></figure>
identified along both principal components 1 and 2 (50,7 % and 18.8 % respectively) that highlighted differences between high TDA, high cell density and high chlorophyll a autofluorescence (Fig. 4).

# 4. Discussion

## 4.1. Effects of copper and zinc on the physiology of P. australis

The decrease in maximum cell density and growth rate, observed in cultures with 15 pmol l⁻¹ of Cu²⁺ (µₐₐₐₐₐ = 0.55 µₐₐₐₐ), relative to the control, indicates a toxic effect of Cu²⁺. Similar toxicity of Cu, inducing decreased growth rates, have already been previously reported for *P. australis* (Maldonado et al., 2002) as well as for other *Pseudo-nitzschia* species, such as *P. multiseries* (Maldonado et al., 2002; Ladizinsky, 2003), *P. pungens* (Liu et al., 2021) and *P. delicatissima* (Lelong et al., 2012b). However, most of these studies reported total Cu concentrations in their culture media, which vary depending on the medium used (e.g. f/2; L1; AQUIL), each with various EDTA final concentrations. These differences make direct comparison of Cu²⁺ concentrations between studies challenging. In their study assessing Cu toxicity on both *P. multiseries* and *P. australis*, Maldonado et al. (2002) used a Cu²⁺ concentration of 31.5 pmol l⁻¹. This concentration is of the same order of magnitude, but still two times higher than the one we tested in our study (15 pmol l⁻¹). The similar decrease in growth rate decrease between this study (µₐₐₐₐ = 55 % of µₘₘₐ) and Maldonado et al. (2002) (µₐₐₐₐ = 30–50 % of µₘₘₐ) highlights a similar sensitivity to Cu²⁺ toxicity between the two *P. australis* strains. The toxicity observed under Cu exposure may be mediated, at least in part, by oxidative stress. Previous studies showed that exposure to high Cu²⁺ concentrations increases intercellular Reactive Oxygen Species (ROS) content (Pinto et al., 2003; Knauert and Knauer, 2008). Cu can cycle between oxidation states I and II. As a result, Cu can catalyze the production of ROS through the metal catalyzed Haber-Weiss reactions with the production of hydroxyl radicals. ROS can be toxic to cells, damaging lipid, protein, and DNA (Kehrer, 2000).

Addition of Zn²⁺ to toxic Cu²⁺ concentration (+Zn+Cu condition) did not significantly increased the growth rate nor the maximal cell density compared to exposure to Cu²⁺-alone (*p* > 0.05). This result indicate that Zn limitation was unlikely at the tested concentration and is in agreement with previous studies reporting that Zn becomes limiting only at subpicomolar levels for most of coastal and marine diatoms (Brand et al., 1983; Tortell and Price, 1996; Varela et al., 2011). Growth rate in the +Zn condition (Zn²⁺ = 433 pmol l⁻¹) was on average 15 % lower than in the control condition indicating possible higher sensitivity of the tested species to Zn toxicity. Nevertheless, growth rates and maximal cell density were not significantly different (*p* > 0.05) between +Zn and Control conditions indicating that Zn toxicity was unlikely in line with a Zn²⁺ toxicity reached at nanomolar levels (Sunda and Huntsman, 1996).

Our results showed that the morphology of cells exposed to toxic Cu²⁺ levels were only slightly affected compared to those grown in control medium (Fig. 2). However metal exposure gradually changed the physiology of cell populations with time as depicted by PCA analysis from day 1 to day 10 (Fig. 4). These results are consistent with findings reported for *P. multiseries* where no significant morphological changes were observed for cells exposed 96 h to 139 µg l⁻¹ Cu (Lelong et al., 2012b). In our, study, the physiology of cells growing under +Cu condition was marked by a moderate (*p* < 0.05) increase of the chlorophyll a autofluorescence and no effect on neutral lipid content compared to control cultures. To our knowledge, there is no comparable data for *P. australis*. For *P. multiseries* and *P. delicatissima* grown in Cu-spiked media, Lelong et al. (2012b) reported similar increase in chlorophyll autofluorescence with additional increase of lipid content. These physiological changes were interpreted as signs of metabolic dysfunction, including alterations in photosystem II (PSII) efficiency, increased cellular respiration rate and storage of excess energy as lipids, due to a

reduced capacity of cell division (Lelong et al., 2012a and references therein).

## 4.2. DA production under Cu toxic concentrations

In this study, nutrient concentrations were not measured, we could not evaluate the effect of nutrient limitation on DA production. During the exponential growth, quotas quickly reach a quasi-equilibrium while nutrients are still abundant (Klausmeier et al., 2004). Thereby cells are not expected to be nutrient-limited, suggesting that differences in net TDA production between culture conditions are primarily driven by metal treatment.

Significant increase in TCₙDA concentrations and net TDA production rates was observed in the +Cu condition compared to the control condition during the exponential phase (Fig. 3B & C). This evidences a positive effect of Cu stress on the production of DA by *P. australis*. Similar effect of Cu²⁺ on DA production has been documented for *P. multiseries* (Maldonado et al., 2002; Ladizinsky, 2003; Fuentes and Wikfors, 2013; Liu et al., 2021). For *P. australis*, to our knowledge, only one study (Rhodes et al., 2002) observed a similar effect of Cu²⁺ on DA production. The reason for this enhanced DA production remains unclear and is often attributed to a direct and active detoxification mechanism. A study by Rue and Bruland (2001) highlighted the complexation properties of DA for Cu²⁺ suggesting that DA might be produced and released during toxic bloom conditions to influence Cu chemical speciation and biological availability. Two other studies (Maldonado et al., 2002; Wells et al., 2005) further hypothesized that DA production by cells promotes the formation of a Cu-DA complex that can cross the membrane barrier easier than Cu alone. DA production could serve as either a Cu acquisition mechanism (at limiting concentrations) or as a detoxification mechanism (at toxic concentrations). However, in their study on *P. delicatissima*, Lelong et al. (2012b) did not observe a positive effect of Cu²⁺ stress on DA production. They found that DA production under Cu²⁺ stress did not alleviate the Cu toxicity undergone by the cells, suggesting that extracellular DA could not compensate Cu toxicity itself. This was supported by Liu et al. (2021), who did not observe any changes in Cu²⁺ concentration in culture media after addition of DA to the medium. Since excess Cu increases oxidative stress in cells (Rijstenbil et al., 1994), an alternative hypothesis proposes that DA plays a role in mitigating oxidative stress (Liu et al., 2021). Indeed, Liu et al. (2021) studied the effect of DA production on the growth rate of cells undergoing oxidative stress. Their conclusions suggest that DA plays an important protective role, either by directly reacting with (ROS) or by complexing Cu²⁺ within the cell to buffer its activity and reduce ROS formation.

During the first 4 days of growth in our experiment, TCₙDA concentrations were not significantly different in the +Cu condition compared to the control (Fig. 3A), suggesting that the response of net TDA production to Cu²⁺ is not immediate. If TDA production were solely dependent on Cu²⁺ concentration in the medium, cells would increase TDA production from the beginning of the experiment to reduce Cu²⁺ activity. The observed delay between exposure to toxic Cu²⁺ concentration and increase of TCₙDA may indicate a threshold level of ROS accumulation within the cell that triggers the activation of the DA detoxification mechanism. This mechanism would not alter the cellular Cu quota but would reduce internal ROS concentration over time during the experiment (Liu et al., 2021).

## 4.3. The role of Zn bioavailability in DA production

The net TDA production rate that was 4 times lower in the +Zn condition than in the control condition during the exponential phase (4 ± 4 fg cell⁻¹d⁻¹, Fig. 3C). Furthermore, the positive effect of Cu²⁺ on net TDA production (Fig. 3C) was erased in the presence of Zn²⁺ with a net DA production rate twice as low in the +Zn+Cu condition than the control and 8 times lower than in the +Cu condition during exponential
<figure><img src="image_8.png" /><figcaption>Fig. 5. A. Net total domoic acid production during exponential phase as a function of Zn²⁺ concentration (Mean±SE). B. Scatter plot of net total domoic acid production during decline phase (day 9 to 10) against glutathione cell quota at day 10. The correlation is significant at *p* < 0.05.</figcaption></figure>

phase (10 ± 4 fg cell⁻¹d⁻¹, Fig. 3C). The inverse covariation between [Zn²⁺] and net TDA production observed during the exponential phase (Fig. 5A) indicates a role of zinc bioavailability in the regulation of DA production.

This inhibition of net TDA production in the presence of Zn²⁺ may occur either directly and/or indirectly by blocking the biochemical production pathway. As growth rate was unaffected under +Zn condition (Fig. 1C), a slowdown of *P. australis* metabolism (including DA production) due to Zn toxicity is unlikely, thus suggesting an additional mechanism.

Since DA production may serve to limit oxidative stress (Liu et al., 2021), it is possible that high Zn bioavailability reduces oxidative stress undergone by cells, thereby decreasing the need of cells to produce DA. The GSH cell quotas measured in the cultured cells at the end of the experiment (day 10, decline phase) showed lower quotas in the +Cu condition and higher quotas in the +Zn and +Zn+Cu conditions compared to the control (Fig. 5B). These results suggest that a high bioavailability of Zn²⁺ helps protect cells from an oxidative stress induced by toxic Cu²⁺ concentrations. Our findings are consistent with previous observations reporting a decrease of GSH cell quota in the diatom *Ditylum brightwelli* (Rijstenbil et al., 1994) under toxic Cu as well as an increase in GSH in *Chlamydomonas reinhardtii* following exposure to high Zn concentration (Li et al., 2023). The correlation (R² > 0.6; *p* < 0.05; Fig. 5B) between net DA production at the end of the experiment and cellular GSH quota further confirms the existing links between TDA production and oxidative stress, as previously suggested by Liu et al. (2021). To our knowledge, the inverse relationship between GSH and DA cell contents is the first reported for *P. australis*. However, Cabrera et al. (2023) reported a decrease in GSH cell content in cultures of the non-toxic marine diatom *Phaeodactylum tricornutum* exposed to micromolar DA levels. This was combined with an increase in antioxidant enzyme activities, namely superoxide dismutase and catalase activities, further highlighting the role of DA in cellular oxidative stress of phytoplankton

The precise mechanism underlying the inhibitory effect of Zn²⁺ on DA production remains unclear. It could be hypothesized that elevated GSH cell quota mitigates oxidative stress, either by direct scavenging ROS or by reducing Cu²⁺ activity through organic complexation. GSH can chelate Cu through its thiol functional group (Dulaquais et al., 2020) and thus reduce the need for DA production by cells to lower intracellular Cu²⁺ activity and thus oxidative stress.

An additional complementary hypothesis is that Zn and Cu compete for uptake via transmembrane proteins. As Cu competitively inhibits Zn uptake, cellular Zn requirements increase at high Cu concentrations (Sunda, 1989). Since there is no evidence that Zn inhibits Cu uptake, we hypothesize that under high Cu²⁺ conditions (+Cu), higher Zn²⁺ concentrations are required to sustain essential processes, including GSH synthesis. In our experiments, this threshold was likely exceeded under

the +Zn and +Zn+Cu conditions (Fig. 5A).

## 5. Conclusion

In this study, Cu²⁺ exposure was found to reduce the growth rate and limit the maximum cell density of a toxic *P. australis* strain, whereas pico to subnanomolar Zn²⁺ concentrations were non-limiting and non-toxic. DA production by *P. australis* was enhanced under toxic Cu²⁺ conditions and high bioavailability of Zn²⁺ significantly decreased DA cellular concentrations—even when combined with toxic Cu²⁺ levels. Although the exact mechanism remains unclear, we propose that Zn²⁺ bioavailability exerts a positive feedback effect on GSH synthesis. Increased intracellular GSH levels may limit oxidative stress and consequently decrease the cellular demand for DA.

We acknowledge that ecological responses can vary among species and even among ecotypes, making it difficult to directly extrapolate laboratory results to natural environments. Therefore, to validate these hypotheses, future research—including field studies—should investigate the relationship between Cu and Zn availability, ROS levels, and the gene expression of DA and GSH biosynthesis.

## CRediT authorship contribution statement

**Marie Bassez:** Writing – original draft, Methodology, Investigation, Formal analysis.
**Hélène Hégaret:** Writing – review & editing, Resources, Methodology.
**Jean-François Maguer:** Writing – review & editing, Resources, Methodology.
**Yoann Asquoët:** Investigation.
**Marie Legain:** Investigation.
**Lucie Vannier:** Investigation.
**Gabriel Dulaquais:** Writing – original draft, Supervision, Resources, Methodology, Funding acquisition, Formal analysis, Conceptualization.

## Declaration of competing interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Gabriel Dulaquais reports financial support was provided by University of Western Brittany. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

## Acknowledgments

This work is part of the PhyZiCo project (Principal Investigator: Gabriel Dulaquais), funded by the ISblue research program (www.isblue.fr). The PhD grant for Marie Bassez was provided by the Université de Bretagne Occidentale. We thank Audrey Duval from IFREMER LER-BO for isolating and providing the *P. australis* strain (IFR-CC 22-041). We also extend our warm thanks to Johann Lavaud (LEMAR,
CNRS) for engaging discussions. We thank Jérôme Lepioufle for
proofreading.

Data availability

Data will be made available on request.

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