A freshwater diatom challenged by Zn: Biochemical, physiological and metabolomic responses of Tabellaria flocculosa(Roth) Kützing

Environmental Pollution 238 (2018) 959e971

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A freshwater diatom challenged by Zn: Biochemical, physiological and metabolomic responses of Tabellaria flocculosa(Roth) Kützing*
F.P. Almeida a, c, Etelvina Figueira a, d, * Sara Gonçalves a, b, Maria Kahlert b, Salome a

Department of Biology, University of Aveiro, Campus de Santiago, 3810-193, Aveiro, Portugal Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences, Uppsala, Sweden c GeoBioTec - GeoBioSciences, GeoTechnologies and GeoEngineering Research Centre, University of Aveiro, Campus de Santiago, 3810-193, Aveiro, Portugal d CESAM, University of Aveiro, Campus de Santiago, 3810-193, Aveiro, Portugal b

a r t i c l e i n f o

a b s t r a c t

Article history: Received 24 July 2017 Received in revised form 19 January 2018 Accepted 31 January 2018

Freshwater ecosystems are under threatening anthropogenic pressures worldwide, namely by metals. Diatoms are used as water quality indicators, but the influence of micronutrients such as Zn and its impacts are poorly understood. Thus, our study aimed to elucidate the tolerance level, the cellular targets and the responses to counteract Zn toxicity of freshwater diatoms by exposing Tabellaria flocculosa, isolated from a Zn contaminated stream. Biochemical, physiological and metabolomic approaches were used. It was demonstrated that Zn is toxic to T. flocculosa at concentrations occurring in contaminated environments. At low stress (30 mg Zn/L) few alterations in the metabolome were observed, but the enzymatic (SOD, CAT) and molecular (GSH, GSSG) antioxidant systems were induced, protecting cells from oxidative stress. At moderate stress (500 mg Zn/L) the main changes occurred in the metabolome (increases in fatty acids, amino acids, terpenoids, glycerol and phosphate, decreases in sucrose and lumichrome) with a moderate increase in cell damage (LPO and PC). The concerted action of all these mechanisms resulted in a non-significant decrease of growth, explaining the survival of this T. flocculosa strain in an environment with this Zn concentration. At the highest stress level (1000 mg Zn/L) the metabolome was identical to 500 mg Zn/L, and the induction of antioxidant systems and extracellular ion chelation (exopolysaccharides, frustulins) were the main responses to the increase of Zn toxicity. However, these mechanisms were unable to effectively abrogate cellular damage and growth reduction was observed. Moreover, the decrease in sucrose and especially in lumichrome should be tested as new specific markers of Zn toxicity. The information obtained in this study can assist in environmental risk assessment policies, support the prediction of diatom behaviour in highly impacted Zn environments, such as mining scenarios, and may help develop new indices, which include alterations induced by metals. © 2018 Elsevier Ltd. All rights reserved.

Keywords: Zinc Diatoms Physiological and biochemical markers Metabolomics Tolerance strategies

1. Introduction Surface freshwater is highly affected by anthropogenic pressures, which compromise its quality worldwide (Allan and Castillo,

Abbreviations: ROS, Reactive Oxygen Species; LPO, Lipid Peroxidation; PC, Protein Carbonylation; PROT, proteins; FRUST, frustulinsETSmitochondrial Electron Transport System; EPS, Exopolysaccharides; SOD, Superoxide Dismutase; CAT, Catalase; GSTs, Glutathione-S-tranferases; GSH, Reduced Glutathione; GSSG, Oxidized Glutathione; GC-MS, Gas Chromatography Mass Spectrometry. * This paper has been recommended for acceptance by Prof. W. Wen-Xiong. * Corresponding author. Department of Biology, University of Aveiro, Campus de Santiago, 3810-193 Aveiro, Portugal. E-mail address: efi[email protected] (E. Figueira). https://doi.org/10.1016/j.envpol.2018.01.111 0269-7491/© 2018 Elsevier Ltd. All rights reserved.

2007; Millennium Ecosystem Assessment, 2005). Metals are one of the main environmental stressors, resulting from various sources such as mining and industry (Hogsden and Harding, 2012; Johnson and Hallberg, 2005). The persistence of metals and their potential to bioaccumulate can impact freshwater communities, leading to biodiversity loss and changes in ecosystems' functioning (Genter, 1996; Kalff, 2002; Lavoie et al., 2009). Most of the research evaluating metal effects on diatoms has been devoted to nonessential toxic metals as Pb, As, Hg, or in most cases Cd, and their potential effects on aquatic systems (Barral
n et al., 2010; Fraga et al., 2016; Branco et al., 2010; S
anchez-Mara Sarker et al., 2016). However, few studies evaluated the intracellular effects of essential and less toxic metals, such as Zn and even less on

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freshwater benthic diatoms (Admiraal et al., 1999; Gonçalves et al., 2018; Hassler et al., 2005; Masmoudi et al., 2013; Morin, 2014; Nagai and De Schamphelaere, 2016; Nguyen-Deroche et al., 2012; Pandey et al., 2018, 2015; Pandey and Bergey, 2016; Paulsson et al., 2002). Using algae, and specially diatoms to assess water quality became a common practice worldwide (Koukal et al., 2007; OCDE, 1984; Rand, 1995). Diatoms are one of the most important and often dominant group of algae (van den Hoek et al., 1995). They are a mandatory group to monitor under the Water Framework Directive, WFD (Directive, 2000/60/EC), in Europe (Kelly et al., 2009, 2012). In monitoring programs, changes in diatom species composition is commonly used to evaluate water quality (Kelly et al., 1998; Lavoie et al., 2008; Teittinen et al., 2015). Nevertheless, these common diatom-based indices and metrics do not indicate metal contamination. Just recently some indices concerning metal contamination were published (Fern
andez et al., 2017; Riato et al., 2018). Consequently, developing tools to evaluate and monitor the stress caused by metals in aquatic ecosystems became of great importance. Several studies reported biochemical and physiological effects of metals on freshwater species and communities (Bonet et al., 2013, 2012; Branco et al., 2010; Corcoll et al., 2012; Leguay et al., 2016; Santos et al., 2013). However, these previous studies do not use specific tools to evaluate metals nor could they fully understand how the observed metal tolerance of certain diatom strains is established or the cellular processes involved under high metal concentration. Zn is an essential micronutrient with important cell functions. Zn is a cofactor of several enzymes, such as carbonic anhydrase, rubisco (Hassler et al., 2005), carboxypeptidases, aminopeptidases, phospholipase C and in proteins with Zn finger domains (Godinho et al., 2014; Silva et al., 2001). However, Zn is a common contaminant in surface freshwater, with no observed effects at concentrations below 10 mg Zn/L (Aschberger et al., 2010). Nonetheless, longterm effects have been reported in microbenthic communities for concentrations ranging from 0.05 to 2.5 mg Zn/L (Paulsson et al., 2000). Above concentrations required by organisms, Zn may be toxic, disturbing metabolism, impacting chlorophyll and inhibiting cell division, thus being considered a growth inhibitor (Filippis
ska, 2003, 2001; Stauber et al., 1990). et al., 1981; Pawlik-Skowron In European stream water, Zn concentrations vary from mg to mg per litre (Salminen et al., 2005), mining being the main source of Zn in the environment (Aschberger et al., 2010). Countries as Sweden, Portugal, Canada and U.S.A have included Zn in the priority substances' list (APA, 2016; ATSDR, 2014; CEPA, 1999; HVMFS, 2016). In Sweden, concentrations of bioavailable Zn above the range 5.5e20 mg/L are considered “not good ecological status” (HVMFS, 2016). Toxicity of Zn is associated with an overproduction of reactive oxygen species - ROS, (Hamed et al., 2017). ROS are potentially toxic above certain concentrations, leading to oxidative stress, interacting with lipids, nucleic acids and proteins and resulting in lipid peroxidation (LPO), protein damage (e.g. protein carbonylation) and DNA alterations, which can be used to evaluate the damage inflicted on cells (Regoli and Giuliani, 2014). In order to reduce and avoid the effects of metals, organisms trigger cellular defence mechanisms, such as extracellular immobilization, restriction of metal ions' transport into the cell, intracellular precipitation and chelation. The free metal ions remaining will interfere with cellular molecules and processes, leading to enzyme inactivation and ROS production. ROS scavenging by antioxidant enzymes and molecules and biotransformation of xenobiotics, all contribute to decrease the toxicity originated by metal ions (Branco et al., 2010; Figueira et al., 2014; Pinto et al., 2003a,b; Regoli and Giuliani, 2014). The induction of these mechanisms can be

monitored and used as biomarkers of oxidative stress for different contamination scenarios (Branco et al., 2010; Figueira et al., 2014; Santos et al., 2013). The use of different approaches is needed for detecting and fully understanding the intracellular stress-caused by metals (Pandey and Bergey, 2016; Soldo and Behra, 2000). Several studies assessed the biochemical, physiological and Omics alterations caused by contamination in algae (Allen et al., 2008; Branco et al., 2010; Dyhrman et al., 2012; Fernie et al., 2012; Jamers et al., 2009; Morelli and Scarano, 2001; Pandey et al., 2017; Pinto et al., 2003a,b; Rijstenbil et al., 1994; Saade and Bowler, 2009; SerraCompte et al., 2017). These approaches enable a comprehensive view of the changes cells undergo and the mechanisms they resort when exposed to challenging conditions, such as metal stress (Branco et al., 2010; Gonçalves et al., 2018; Jamers et al., 2009; Serra-Compte et al., 2017). In particular metabolomics is a powerful tool to characterize cellular response to environmental stress stimuli, by identifying and quantifying changes in metabolites and elucidating the metabolic pathways involved in the response to a specific stress (Jamers et al., 2009; Serra-Compte et al., 2017). However, until now metabolite profiling analysis has focused on the identification of algae metabolites with economic value (Jamers et al., 2009). To our best knowledge, the targets of Zn toxicity and the mechanisms of freshwater diatoms to tolerate high Zn concentrations are far from being understood. The determination of the tolerance level, cellular targets and responses to counteract Zn toxicity can bring novel information, contributing to a deeper understanding on the Zn influence on tolerant diatoms, especially at Zn contaminated areas. The use of adapted or tolerant species and the characterization of their response to different stress levels, is important since in contaminated areas the sensitive species are unlikely to survive (Genter, 1996). To become tolerant, species activate and develop mechanisms that are able to differentiate them and it should be on these mechanisms that the research effort should be made. To recognize the features enabling freshwater benthic diatoms to colonize Zn polluted environments, lab experiments were carried out using Tabellaria flocclulosa (Roth) Kützing 1844 isolated from a stream with 500 mg Zn/L and pH 5.0. Cells were submitted to Zn concentrations representing low (30 mg/L) to highly contaminated (1000 mg/L) environments. With this approach, we hypothesized that: 1) Zn negatively affects T. flocculosa cells; 2) Zn induces biochemical and metabolic alterations; 3) different Zn concentrations impose different stress levels; 4) different mechanisms are used to counteract toxicity. 2. Material & methods 2.1. Region characterization, diatom isolation, cultivation and growth determination Dalarna region, in Sweden, is known for metal exploitation (Larson, 2010). The region contains old (approx. 1000 years) and new mines and a history of mine effluents draining on the surrounding waters (Larson, 2010). According to the report from Dalarna's Administration County Board (2010), in some sites river/ stream water may have Zn concentrations above 1000 mg/L, with the highest value registered of 9300 mg/L. The species used for this study, Tabellaria flocculosa, was isolated from a stream in this region with 500 mg Zn/L and water pH~5 (water parameters summarized in Supplementary Table S1) (Larson, 2010). The isolation of a single cell was made by the micropipette technique and isolated cells were transferred to agar plates (Andersen, 2005; Round et al., 1990) followed by transference to WC liquid medium (Guillard and Lorenzen, 1972).

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T. flocculosa culture is now part of SLU diatom culture collection. The strain was pre-cultured in WC medium at pH 5, until exponential growth was reached. Cells at exponential growth were used for Zn experiments by transferring approximately 250 000 cells to new sterile flasks containing 250 mL of WC modified medium (1000 cells/ml), supplemented with different Zn concentrations. At the end of exposure time, 1 mL of each Erlenmeyer was preserved with Lugol's solution for cell counting. Cell density was measured by direct counting in a Neubauer chamber using Nikon Eclipse 80i microscope. The experiments were performed with cells in exponential growth, at 20 ± 2
C with a 12 h/12 h light/dark cycle at 75 mmol/ m2/s in WC medium, with nominal Zn concentrations of 0, 30, 500 and 1000 mg/L (added as ZnSO4) during 96 h. The WC medium was modified by using just 1/10 of the EDTA/trace metal solution to ensure that the added zinc would be present in solution (calculations performed by Visual MINTEQ ver. 3.0). Zn concentration in WC medium alone (control) was 2.2 mg/L. The concentrations of Zn where chosen considering modelled values (Salminen et al., 2005), measured concentrations in the Swedish national monitoring system of reference sites (HVMFS, 2016), measured concentrations in mining impacted areas and recommendations for threshold values for risk assessment of Zn (e.g. Larson, 2010). Measured concentrations in the Swedish national monitoring system of reference sites are in general below 10 mg/L, which fits well with our nominal control concentration of Zn in the WC medium (2.2 mg/L). Zn concentration of 30 mg/L was chosen as a low concentration occurring in Swedish rivers and lakes (Naturvårdsverket, 1999) and being common in Zn hotspots of European streams (Salminen et al., 2005). In current Swedish legislation, 30 mg Zn/L is considered to indicate below good ecological quality of freshwater, indicating a risk for toxic effects due to Zn in freshwater organisms (European Union, 2010; HVMFS, 2016). According to Naturvårdsverket (1999), 500 mg Zn/L was considered a very high concentration for Swedish waters. However, 12% of all sites studied from Dalarna region have concentrations above 500 mg Zn/L and the strain used was isolated from a site with this concentration. The selection of 1000 mg Zn/L, an extremely high Zn concentration, was not meant to cause total growth inhibition of T. flocculosa. Furthermore, 1000 mg Zn/L is also the threshold concentration where all tested organisms showed toxic effects under Zn exposure (European Union, 2010). As stated above, such high values are observed in mining areas in Sweden (Larson, 2010). 2.2. Intracellular Zn quantification Cell cultures were centrifuged at 5000 rpm for 15 min. Cell pellets were resuspended in deionized water, vortexed and centrifuged again. The washing procedure was repeated two more times to ensure the removal of all the Zn from the culture medium. Pelleted cells were re-suspended in 3 mL EDTA (0.1 M pH 7.8) and incubated overnight, at 4
C under agitation (150 rpm). Incubated cells were centrifuged (9000g, 2min, at 4
C), the supernatant discarded, and the cell pellets resuspended in deionized water, vortexed and centrifuged again as described by Santos et al. (2013). Cell pellets were resuspended in 1 mL of potassium phosphate buffer (50 mM pH 7.0, 1 mM EDTA, 1% (v/v) Triton X-100, 1% (w/v) PVP, and 1 mM DTT) and sonicated for 20 s at 0.5 cycles. The suspension was centrifuged at 10 000g at 4
C for 10 min and the supernatant collected. HNO3 65% (100 mL) was added to the supernatant and deionized water was also added until a final volume of 5 mL was reached. Intracellular Zn concentration was quantified by Inductively Coupled Plasma Mass Spectrometry (ICP-MS) analysis.

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2.3. Lipid peroxidation (LPO) LPO was measured by quantification of thiobarbituric acid reactive substances (TBARS), according to the protocol described by Buege and Aust (1978). T. flocculosa cells were harvested and washed as described in section 2.2. The pellet was suspended in Trichloroacetic acid, TCA (20%), sonicated and centrifuged as in section 2.2. Absorbance was measured at 535 nm (Ɛ ¼ 1.56  105/ M.cm). Results were expressed in mmol of malondialdehyde (MDA) equivalents per million cells (mmol MDA/M cells). 2.4. Proteins 2.4.1. Intracellular proteins (Prot) Protein concentration was measured following the method described by Spector (1978). T. flocculosacells were harvested, washed and supernatant was extracted as described in section 2.2. Protein was quantified at 595 nm using bovine serum albumin (BSA) as standard. Results were expressed in milligram protein per million cells (mg protein/M cells). 2.4.2. Frustulins (Frust) €ger et al. Frutulins' extraction was prepared as described by Kro (1994) and adapted by Santos et al. (2013). Harvested and washed cells (section 2.2) were resuspended in 3 mL of EDTA (0.1 M pH 7.8) and incubated overnight, at 4
C under agitation (150 rpm). Incubated cells were centrifuged (9000g, 2 min, at 4
C) and the supernatant absorbance read at 280 nm (concentration (mg/L) ¼ Abs 280 nm/light path (cm)) (Noble and Bailey, 2009). Results were expressed in mg protein per million cells (mg protein/M cells). 2.4.3. Protein carbonylation (PC) Carbonyl groups (CG) in proteins were quantified based on the method described by Mesquita et al. (2014). In the same cell extracts used for intracellular protein determination, the amount of CG was quantified spectrophotometrically at 450 nm (Ɛ ¼ 22 308/ M.cm) and results were expressed in nmol of CG per million cells (nmol CG/M cells). 2.5. Electron chain transport system activity (ETS) ETS activity was measured based on King and Packard (1975) method, using the modifications described by De Coen and Janssen (1997). Cells were harvested and washed as in section 2.2. Pelleted cells were sonicated and centrifuged as in section 2.2. The absorbance was read at 490 nm. The amount of formazan formed was calculated using the molar extinction coefficient of formazan (15900/M.cm) and the results were expressed in mmol of formazan per million cells (mmol/M cells). 2.6. Attached and non-attached exopolysaccharides (EPS) Undisturbed culture medium (non-attached) and cell attached EPS were determined using Staats et al. (2000) procedure adapted by Santos et al. (2013). Attached and non-attached EPS were determined by the phenol-sulphuric acid colorimetric method (DuBois et al., 1956). The absorbance was measured at 490 nm using sucrose as standard. Results were expressed in mg saccharides per million cells (mg/M cells). 2.7. Antioxidant response 2.7.1. Superoxide dismutase activity (SOD) Harvested and washed cells (section 2.2) were resuspended in extraction buffer (50 mM potassium phosphate, pH 7.0, 1 mM EDTA,

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1% (v/v) Triton X-100, 1% (w/v) PVP, and 1 mM DTT) and sonicated for 20 s at 0.5 cycles. Extracts were centrifuged at 10 000g at 4
C for 10 min. The method of Beauchamp and Fridovich (1971) was followed with slight modifications (Branco et al., 2010). The absorbance was measured at 560 nm using a standard curve with SOD standards. Results were expressed in enzyme units per million cells (U/M cells). 2.7.2. Catalase activity (CAT) Cell extracts were obtained using the procedure described for SOD. CAT activity was determined by the method of Johansson and Håkan Borg (1988) adapted by Branco et al. (2010). The absorbance was measured at 540 nm using formaldehyde standards. Results were expressed in enzyme milliunits per million cells (mU/M cells). 2.7.3. Glutathione S-transferases activity (GSTs) Cell extracts were obtained using the procedure described for SOD. GSTs activity was determined by the method of Habig and Jakoby (1981) using CDNB (2,4-Dinitrochlorobenzene) as substrate. The thioether formed (Ɛ ¼ 9.6/mM. cm) can be monitored by the increase of absorbance at 340 nm. Results were expressed in enzyme milliunits per million cells (mU/M cells). 2.7.4. Glutathione content Cell extracts were obtained using the procedure described for SOD, but cell pellet was suspended in a different extraction buffer (0.1% Triton X-100, 0.6% sulphosalicylic acid in KPE buffer (0.1 M phosphate buffer, 5 Mm EDTA, pH ¼ 7.5)). Glutathione content was quantified as described by Rahman et al. (2006). GSH and total GSH were determined by measuring at 412 nm the TNB (2-nitro-5thiobenzoate) formed. Oxidized glutathione was estimated by the difference between total and reduced glutathione (GSSG¼(GSHTGSH)), since one molecule of GSSG is formed by the oxidation of two GSH. Results were expressed in nmol GSH or GSSG per million cells (nmol/M cells). 2.8. Metabolite profiling by GC-MS 2.8.1. Sample preparation Sample preparation was performed according to Gullberg et al. (2004) using 300 mL of extraction buffer (20/20/60 v/v chloroform:water:methanol) including internal standards which were added to 1 million T. flocculosa cells. At the end of the procedure, 250 mL of supernatant was transferred to a microvial and solvents were evaporated. 2.8.2. Derivatization Derivatization of the prepared samples (2.8.1) was performed according to Gullberg et al. (2004) using a volume of 7.5 mL of methoxyamine, MSTFA and of methyl stearate solution instead of 30 mL. 2.8.3. Analytical procedure Gas chromatography with mass spectrometry analysis was performed as described previously (Gullberg et al., 2004; € m and Lewensohn, 2010). In detail, 1 mL of the derivatized Nordstro sample was injected splitless (or split 1:20) by a CTC Combi Pal Xt Duo (CTC Analytics AG, Switzerland) autosampler/robot into an Agilent 7890 A gas chromatograph equipped with a 30 m  0.25 mm i. d. fused-silica capillary column with a chemically bonded 0.25 mm DB 5-MS UI stationary phase (J&W Scientific, Folsom, CA). The injector temperature was 260
C, the purge flow rate was 20 mL/min, and the purge was turned on after 75 s. The gas flow rate through the column was 1 mL/min, and the column

temperature was held at 70
C for 2 min, after increased 20
C/min until 320
C, and held at 320
C for 8 min. The column effluent was introduced into the ion source of a Pegasus HT time-of-flight mass spectrometer, GC/TOFMS (Leco Corp., St Joseph, MI). The transfer line and the ion source temperatures were 250 and 200
C, respectively. Ions were generated by a 70 eV electron beam at an ionization current of 2.0 mA, and 20 spectra s1 were recorded in the mass range m/z 50e800. The acceleration voltage was turned on after a solvent delay of 290 s. The detector voltage was 1500e2000V. 2.8.4. Data analysis MS-files from the obtained metabolic analysis were exported ^ from the ChromaTOF software in NetCDF format to MATLABO R2011b (Mathworks, Natick, MA, USA), where all data pretreatment procedures, such as base-line correction, chromatogram alignment, data compression and Hierarchical Multivariate Curve Resolution (H-MCR), were performed using custom scripts according to Jonsson et al. (2006). The extracted mass spectra were identified by comparisons of their retention index and mass spectra with libraries of retention time indices and mass spectra (Schauer et al., 2005). All multivariate statistical investigations (PCA, OPLSDA) were performed using the software package SIMCA version 13.0.2 (Umetrics, Umeå, Sweden). Identification of compounds was based on comparison with mass spectra libraries (in-house database) as well as retention index. 2.9. Statistical analysis Hypothesis testing was performed by Permutation Multivariate Analysis of Variance (PERMANOVA) (Anderson et al., 2005). All data analysis was performed with the software PRIMERv6 (Clarke and Gorley, 2006) with the add-on PERMANOVAþ (Anderson et al., 2008). To run the PERMANOVA tests we considered 9999 Monte Carlo permutations and pairwise comparisons between Zn conditions. Our null hypothesis was: different Zn concentrations (0, 30, 500, 1000 mg/L) does not cause differences in T. flocculosa. This hypothesis was tested for all parameters described in section 2, including metabolomic analysis. Values of p  0.05 revealed that conditions differed significantly, indicated in figures by different lowercase letters. Matrix gathering the biomarker responses (Growth, LPO, Prot, Frust, PC, ETS, EPS, SOD, CAT, GSTs, GSSG and GSH) was used to calculate the Euclidean distance similarity matrix. The data used to calculate the matrix was previously normalized and transformed (square root). The matrix was then simplified through the calculation of the distance among centroid based on the condition and then submitted to ordination analysis, performed by Principal Coordinates (PCO). Spearman correlation vectors (r > 0.95) of biochemical responses of T. flocculosa cells were superimposed on the top of the PCO graph. 3. Results 3.1. Growth T. flocculosa exposed for 96 h to different zinc concentrations only showed significant growth differences at the highest Zn concentration (1000 mg/L). However, at 500 mg/L, cells showed a 20% growth decrease compared to control (Fig. 1). 3.2. Zn concentration Zn was detected in the cytosol (control condition), since the growth medium contained 2.2 mg Zn/L (Fig. 2). However, when

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significant (p > 0.05) between 0 and 30 mg Zn/L. At 500 mg/L, LPO levels are significantly higher compared to control (0) and 30 mg/L and exposure to 1000 mg Zn/L induces LPO concentrations, which are significantly higher compared to the remaining conditions. Protein carbonylation (PC) followed the LPO trend. However, at 1000 mg Zn/L, the increase is more expressive (3.5, 3.2 and 2.4-fold comparing to 0, 30 mg/L and 500 mg/L, respectively) (Fig. 3B). 3.4. Physiological response

Fig. 1. Growth of Tabellaria flocculosa (cells/mL) exposed for 96 h to different Zn concentrations. Values are means (þstandard deviation) of 36 replicates from 12 independent experiments. Different lowercase letters indicate significant differences (p < 0.01) among Zn exposures.

Fig. 2. Intracellular zinc concentrations (mg/M cells) in Tabellaria flocculosa exposed for 96 h to different Zn concentrations. Values are means (þstandard deviation) of 6 replicates from 2 independent experiments. Different lowercase letters indicate significant differences (p < 0.05) among Zn exposures.

growth medium was supplemented with Zn, the concentrations were 10e15 times higher. Intracellular Zn did not show significant differences in cells exposed to 30 and 500 mg/L. At 1000 mg/L, the intracellular Zn increased 50% compared with lower Zn concentrations (30 and 500 mg/L). 3.3. Cell damage Lipid peroxidation (LPO) tends to increase as cells are exposed to increasing Zn concentrations (Fig. 3A). However, differences are not

T. flocculosa cells exposed to Zn showed a steady increase of proteins as Zn concentration increased with significant differences among all conditions tested. Cells grown at 500 mg/L have 4.3 and 2.4-fold more proteins than those at 0 and 30 mg/L, respectively. Differences are higher at 1000 mg Zn/L comparing with the remaining conditions (14, 8, 3-fold for 0, 30, 500 mg/L, respectively) (Fig. 4A). T. flocculosa cells of the control and of the lowest Zn concentrations (30 and 500 mg/L) present similar activity of the electron transport system (ETS). At 1000 mg/L, activity increased 3-fold (Fig. 4B). The production of exopolysaccharides (EPS) attached and nonattached to the frustule showed that non-attached represented less than 1% of total EPS, therefore they were not considered significant and were not presented. Attached EPS at 30 mg/L decreased significantly compared to the control. However, an opposite trend was observed at higher zinc concentrations, especially at 1000 mg/L, when EPS increased almost 3-fold compared to the control and 22fold compared to 30 mg/L (Fig. 4C). Frustulins' synthesis did not change significantly among the control and the two lower Zn concentrations, but a 2.5-fold increase was noticed at 1000 mg/L, compared with the remaining conditions (Fig. 4D). 3.5. Antioxidant and biotransformation response Superoxide dismutase (SOD) and catalase (CAT) activities were similar (p > 0.05) between 30 and 500 mg Zn/L, but were both higher compared to the control and lower compared to 1000 mg/L. The activity of both enzymes at the highest Zn concentration was specially increased (6-fold for SOD and 4.7-fold for CAT) when compared to the control (Fig. 5A and B). Glutathione S-transferases (GSTs) activity was similar (p > 0.05) among the control, 30 and 500 mg Zn/L, but increased significantly for 1000 mg/L (Fig. 5C). For all conditions, glutathione was mainly present in the reduced form. Zinc exposure did not induce the synthesis of glutathione (GSH) at the lowest Zn concentrations (30 and 500 mg/ L) (Fig. 5D), but the level of oxidation differed (p < 0.05) between

Fig. 3. Damage of Tabellaria flocculosa exposed for 96 h to different Zn concentrations. A) Lipid peroxidation (LPO). B) Protein carbonylation (PC). Values are means (þstandard deviation) of 6 replicates from 2 independent experiments. For each parameter different lowercase letters indicate significant differences (p < 0.05) among Zn exposures.

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Fig. 4. Physiological responses of Tabellaria flocculosa exposed for 96 h to different Zn concentrations. A) Total protein (Prot). B) mitochondrial electron chain activity (ETS). C) Attached exopolysaccharide substances (EPS). D) Frustulins (Frust). Values are means (þstandard deviation) of 8 replicates from 4 independent experiments. For each parameter different lowercase letters indicate significant differences (p < 0.05) among Zn exposures.

exposed (30 and 500 mg/L1) and non-exposed cells (Fig. 5E). At the highest Zn concentration, a 4-fold increase in GSH was observed compared with the remaining conditions. The concentration of GSSG also increased at 1000 mg/L. 3.6. PCO biochemistry analysis Principal Components Ordination (PCO) diagram resulting from applying a multivariate analysis to the physiological and biochemical parameters determined for each condition tested (0, 30, 500 and 1000 mg Zn/L) evidenced PCO1 as the main axis explaining most of the variation (87.9%) obtained among conditions (Fig. 6). Along PCO1, two groups are clearly separated, 0, 30 and 500 mg/L on the negative side and 1000 mg/L on the positive side of the axis. PCO2 explained 6.9% of total variation, separating 500 mg/L in the positive side from the other two conditions at the negative side of the axis. The highest concentration (1000 mg/L) is highly correlated with protein (r ¼ 0.95), GSH (r ¼ 0.98) GSSG (r ¼ 0.94) and LPO (r ¼ 0.91) contents and SOD (r ¼ 0.96) activity. Indeed, all these parameters evidenced a strong increase at 1000 mg/L compared with the remaining conditions. 3.7. Metabolomics Metabolomics' analysis was able to separate 123 compounds (Supplementary Table S2), but only 90 compounds were statistically significant and further analysed. The sum of the peak areas of all the compounds (123) showed a slight and non-significant increase from 0 to 30 mg/L. However, at 500 mg/L, a significant increase was observed, and at 1000 mg/L the total peak area was even higher and significantly different from the remaining conditions (Fig. 7A). The number of compounds with peak area significantly differing between conditions showed variation (Fig. 7B). A low number of compounds varied between 0 and 30 mg/L (8) and between 500 and

1000 mg/L (10). The largest differences were observed between conditions 0e1000 mg Zn/L, 30e1000 mg Zn/L and 0e500 mg Zn/L. From the 90 compounds showing differences among conditions, 11 were not considered for the analysis of chemical families since their identification was not possible. The remaining 79 were divided by chemical families (Fig. 7C). Lipids, N-compounds (75% amino acids) and terpenoids are the most representative families. The lipid percentage was similar among conditions, but the percentage of nitrogenous and terpenoid compounds showed higher variations, increasing at the highest Zn concentration compared to the control (0 mg Zn/L). The total peak area of each chemical family is presented in Fig. 8. The variation at each Zn concentration relatively to the control of the most biologically relevant compounds is also presented. The total peak area of lipids increased steadily with increasing Zn concentrations. Differences are not significant between 0 and 30 mg/L, but these two conditions have significantly smaller areas than 500 mg/L and 1000 mg/L (Fig. 8A). Several types of lipids (saturated, unsaturated, cyclic, branched and glycerol lipids) were identified. Twenty-four saturated and 12 unsaturated lipids were identified but the total area of both classes is similar (Supplementary Table S2). The five lipid compounds presented are fatty acids (FA) with 10e16 carbons and a fatty alcohol. The variation trend is similar to all, with a slight increase or decrease at 30 mg/L, and 2.3e2.8-fold increase at 500 and 1000 mg/L compared to the control, except for decanoic acid and 1-hexadecanol, which displayed lower increases (c.f. Fig. 8A). Other lipids, such as eicosapentaenoic acid, docosahexaenoic acid, palmitoleic and palmitic acids, hexadecatrienoic acid and myristic acid were also identified (Supplementary Table 2S). The total peak area of N-compounds also increases as Zn concentration increased (Fig. 8B). On the polar amino acids, glutamine is the amino acid displaying the highest variations for all tested Zn concentrations. For other amino acids increases of 2e5 fold at 500

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Fig. 5. Antioxidant response of Tabellaria flocculosa exposed for 96 h to different Zn concentrations. A) Superoxide dismutase (SOD). B) Catalase (CAT) activity. C) Glutathione Stransferases (GSTs) activity. D) Reduced glutathione (GSH). E) Oxidized glutathione (GSSG). Values are means (þstandard deviation) of 6 replicates from 2 independent experiments. For each parameter different lowercase letters indicate significant differences (p < 0.05) among Zn exposures.

Fig. 6. Principal Coordinates with Centroids ordination (PCO) of Tabellaria flocculosa exposed for 96 h to different Zn concentrations (0, 30, 500 and 1000 mg/L). Pearson correlation vector imposed lipid peroxidation (LPO), proteins (Proteins), reduced (GSH) and ixidized (GSSG) glutathione concentrations and superoxide dismutase (SOD) activity (r > 0.99).

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Fig. 7. Metabolomic analysis of Tabellaria flocculosa exposed for 96 h to different Zn concentrations (0, 30, 500 and 1000 mg/L). A) Total peak area from 123 compounds, B) Number of compounds differing significantly (p < 0.05) between conditions and C) Distribution of compounds by chemical family (based on peak areas). Values are means (þstandard deviation) of 3 replicates from 1 independent experiment. For A) different lowercase letters indicate significant differences (p < 0.05) among Zn concentrations.

and 1000 mg/L compared to the control were observed (c.f. Fig. 8 B). The non-amino acid, pyroglutamic acid showed a decrease at 30 mg/ L compared to the control and modest increases at higher Zn concentrations (c.f. Fig. 8B). The total peak areas of sugar related compounds also increase as Zn concentrations increased (Fig. 8C). For glycerol, a slight decrease is observed at 30 mg/L but at higher Zn concentrations glycerol increased compared to the control. Sucrose decreased for all Zn concentrations compared to the control. Identified terpenoids include diterpenoids, steroids and sterols (Fig. 8D). The total peak area of terpenoids also follows Zn concentrations, with a modest increase at 30 mg/L and a 3-fold increase at 500 and 1000 mg/L. The most abundant terpenoids (highest peak areas) are different sterols, all showing small increases at 30 mg/L and a 3e4-fold increase at 500 and 1000 mg/L compared to the control. Phytol, a natural linear diterpene alcohol, evidenced identical variation. Some identified compounds do not belong to any of the mentioned chemical families. The overall trend of the peak areas of these compounds is to decrease as Zn concentrations increase. For inorganic phosphate, a slight decrease is observed at 30 mg/L, but an increase of 1.4e1.7-fold was observed for 500 and 1000 mg/L respectively. Glutaric acid and GABA increased along the Zn concentration gradient (c.f. Fig. 8E). Lumichrome evidenced a distinct trend, with peak areas decreasing as Zn concentrations increased, especially, at 1000 mg/L. 4. Discussion T. flocculosa is often characterized as a sensitive diatom species

to pollutants (Hofmann et al., 2013; Olenina et al., 2006), including to metal pollution (Morin et al., 2012). However, in this study T. flocculosashowed tolerance to Zn. Thus, our strain must have developed efficient tolerance mechanisms to Zn, since it was isolated from a high Zn concentration site (500 mg Zn/L). An insight into the results obtained in our study confirm the hypotheses presented. The highest Zn concentrations used, which are environmentally relevant, severely decreased T. flocculosa growth, thereby supporting the first hypothesis. The second hypothesis, that T. flocculosa underwent biochemical and metabolomic changes due to the pressure of high intracellular Zn concentration, was confirmed. It was also possible to identify increased levels of stress caused by increasing Zn concentrations (third hypothesis). In order to survive to high Zn concentrations and counteract Zn toxicity, T. flocculosa was able to trigger different tolerance mechanisms (fourth hypothesis). The data obtained showed that T. flocculosa possesses several mechanisms enabling cells to tolerate Zn. The ability to trigger defence mechanisms as a response to stress is considered the key to organism's intrinsic tolerance levels (Soldo and Behra, 2000). In detail, at 30 mg Zn/L, T. flocculosa did not decrease growth compared to the control. At this concentration, the extracellular defence mechanisms (EPS and frustulins) even showed a decrease (only significant for EPS). Nevertheless, 30 mg Zn/L induced an intracellular global enzymatic response. Proteins increased significantly, showing that cells adjusted to the higher intracellular Zn concentrations, such as the significant increase of SOD and CAT activity and the slight increase of ETS activity and glutathione content. These results indicate that cells suffered mild oxidative stress, which was effectively abrogated since membrane and

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Fig. 8. Metabolomic profiling (total peak area) of Tabellaria flocculosa cells exposed for 96 h to different Zn concentrations (0, 30, 0500 and 1000 mg/L) and ratio (Zn condition/ control) of biological relevant compounds for each family of compounds. A) Lipids. B) N-compounds. C) Sugar related compounds. D) Terpenoids; E) Others. Values are means (þstandard deviation) of 3 replicates from 1 independent experiment different lowercase letters indicate significant differences (p < 0.05) among Zn concentrations.

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protein damage, expressed by lipid peroxidation (LPO) and protein carbonylation (PC) presented small but non-significant increases compared to the control. This concentration (30 mg Zn/L) also caused slight changes in cell metabolome with increases and decreases of different amino acids. The sucrose decrease observed at this concentration probably indicates the increased energy demand required to perform these metabolic alterations. Similar to our results, Stauber et al. (1990) found that Zn concentrations below 500 mg/L caused only slight effects (cell division rate, respiration and photosynthesis) in the marine diatom Nitzschia closterium. In our study, we found that at 500 mg Zn/L, extracellular chelation mechanisms were activated compared to 30 mg/L, explaining the maintenance of the intracellular Zn concentrations. The observed increase of EPS can reduce metal toxicity, due to extracellular metal complexation (Koukal et al., 2003; Wilde et al., 2006). The observed higher amount of frustulins may also sequester extracellularly Zn ions as described by Santos et al. (2013) for Cd. Zn extracellular chelation was already reported by Stauber et al. (1990), in N. closterium grown at 100 and 200 mg Zn/L, however no chelation mechanism was identified by these authors. The increase of EPS at 500 mg Zn/L may be related to the observed GABA increase at this concentration. Indeed, GABA was reported to promote quorum sensing (cell to cell communication), to induce EPS secretion, to be involved in tolerance to abiotic stress (Chevrot et al., 2006) and to have antioxidant properties (Tiansawang et al., 2016). A general increase in lipids, amino acids, glycerol and phosphate was observed at 500 mg Zn/L. The increase in inorganic phosphate, glycerol and lipids and the decrease in sucrose indicate that at this Zn concentration cells might be at a low energy status. Storage lipids seem to be produced and accumulated in order to be used as the main source of energy production once sucrose (a prompt energy source) levels decrease. In fact, diatoms are known to accumulate lipid bodies under different stress conditions (e.g.Kroth et al., 2008; Pandey et al., 2015), including Zn (Pandey and Bergey, 2016). The molecular (glutathione) and enzymatic (SOD, CAT, GSTs) antioxidant response did not increase at 500 mg/L compared to 30 mg/L. However, the oxidative stress was not alleviated efficiently at 500 mg/L, since LPO and PC presented significant increases at this concentration compared to 0 and 30 mg/L. Though non-significant, growth decreased by 20% compared to the control. The increase in proteins and several amino acids, at 500 mg/L relatively to lower Zn concentrations, showed the cell effort to compensate the expected decrease in enzyme activity, due to damage by PC. The synthesis of a higher number of enzyme copies was already reported for Nitzschia palea exposed to Cd as a mechanism compensating the lower enzymes' activity in cells (Santos et al., 2016). The increase of metabolic pathways producing compounds involved in cell response to Zn toxicity, which rely on enzymatic activity, may also explain the increase in proteins and amino acids. For example, chlorophyll synthesis increased at high Zn concentrations (500 mg/L), as indicated by the increase of phytol, a terpenoid that anchors the tetra-pyrrolic rings to the membrane. Additionally, phytol feeds the biosynthesis of tocopherols, which are well known lipid antioxidants and are able to protect membranes from peroxides (Mach, 2015). Lumichrome has been described to influence many cellular processes (Gouws, 2009). Thus, the decrease in this metabolite, observed in our study, supports a reconfiguration of cellular metabolism. Lumichrome was shown to induce a general decrease in the amino acid pool (Gouws, 2009), so the decrease in lumichrome is compatible with the increase of several amino acids observed in our study. Moreover, lumichrome was reported to decrease the activity of antioxidant (SOD, glutathione peroxidase and dehydroascorbate reductase) and glycolytic (glyceraldehyde 3-

phosphate dehydrogenase) enzymes (Gouws, 2009; Gouws et al., 2012). The increase of SOD activity in all Zn exposures, observed in our study, is consistent with the decrease in lumichrome. The increase in glycolysis, originated by lower lumichrome levels, can feed the tricarboxylic acid (TCA) cycle and the electron transport system (as shown in our study by the increase in ETS activity), thus providing energy for cells to fight the toxicity generated by high Zn concentrations, such as the antioxidant response. In this study, general increase in amino acids in this study must be related with protein synthesis. However, free amino acids play several other roles. Free amino acids are involved in signal transduction, phytohormone synthesis and are percursors of other Ncompounds or other secondary metabolites (Hildebrandt et al., 2015). Diatoms share many features of amino acids' metabolism with higher plants, including the urea cycle (Bromke, 2013). The increase of the amino acid pool under stress conditions, including metals, observed in our study, was already described as an active response of great importance in plants (Hildebrandt et al., 2015; Sharma and Dietz, 2006). Branched amino acids as isoleucine and valine and other as lysine and threonine were also induced in plant stress (Hildebrandt et al., 2015). The accumulation of most of these amino acids was also observed in our study, especially at 500 and 1000 mg Zn/L. Isoleucine, valine and lysine directly feed electrons for the ETS (Hildebrandt et al., 2015), which was increased when T. flocculosa cells were exposed to high Zn concentrations. Moreover, the increase in glutamine and arginine could be linked with the increase of N- storage (Hildebrandt et al., 2015), which can be used as alternative substrate for energy production in stress conditions (Fernie et al., 2012). Additionally, amino acids as tyrosine are precursors of tocopherols (terpenoids) (Hildebrandt et al., 2015), which as pointed before have an active role in the cell redox balance. Several amino acids are also involved in sugar metabolism, such as alanine which results from pyruvate transamination. Alanine is one of the most common amino acids in proteins (Bromke, 2013) and its increase at 500 and 1000 mg Zn/L relatively to the control reflects the increase of proteins observed at these two concentrations of Zn. The conversion of pyruvate to alanine has an important role in CO2 fixation on the C4 carbon photosynthetic assimilation €utigam and Gowik, 2016; Hatch, pathway (Bar-Even et al, 2010; Bra 1975, Iglesias et al., 1986). The observed increase of alanine under Zn exposure can indicate an attempt of cells to increase CO2 fixation through C4 pathway (Hopkinson et al., 2011; Reinfelder et al., 2000) and consequently to increase the efficiency of organic compounds' €utigam and Gowik, production, translated into biomass gain (Bra 2016) or additional energy to fight stress. It is however not clear if the C4 pathway is important or even present in all diatoms (Fernie et al., 2012), but it has been shown to be present in some (Haimovich-dayan et al., 2013). Thus, further research should be conducted to elucidate if Zn could have an impact in C4 pathway. At the highest Zn concentration (1000 mg/L), the metabolomic profile followed a similar trend as 500 mg/L. The major alterations occurred at biochemical and physiological levels with a high increase of most parameters, evidencing the cell effort to restrain the increase of oxidative stress generated by the higher intracellular Zn concentration. The extracellular complexation mechanisms and the antioxidant response increased, and were sustained by higher respiration rates (high ETS activity). All together these changes were however not sufficient to avoid oxidative damage, as LPO and PC increased steadily. Much of the oxidative damage is caused by lipid peroxidation products, such as aldehydes, which are toxic to cells (Cardoso et al., 2017). The mitigation of this effect is achieved by biotransformation enzymes, such as GSTs, that transform aldehydes into less toxic compounds, such as alcohols (as 1hexadecanol, an alcohol derived from lipids that increased at high

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Zn concentrations). However, the increase of GSTs was not enough to quash the toxic effects of lipid peroxides and the number of carbonyl groups in proteins evidenced a high increase. 5. Conclusions The results of this study showed that T. flocculosa responded differently to the three Zn concentrations. These responses can be used to identify the level of stress imposed to diatom species or communities. Slight but significant increases in the antioxidant response (SOD, CAT, GSSG) can be markers of mild stress. Metabolome reconfiguration with changes in several families of metabolites (carbohydrates, amino acids, terpenes, lipids) mark moderate stress. High increase of the antioxidant response (SOD, CAT, GSH synthesis), induction of extracellular chelation mechanisms (EPS and frustulins) and high cellular damage (LPO and PC) are markers of high stress. Moreover, metabolites such as sucrose and lumichrome showed a decrease with the increase of Zn concentration, suggesting that these compounds should be tested as specific markers of Zn toxicity in environmentally exposed diatoms and possibly other algae. This study generated fundamental knowledge that may help to develop new tools based on cell responses at the biochemical, physiological and metabolomic levels and to establish appropriate regulatory guidelines, allowing to predict and mitigate the impacts of mining activity in freshwater systems. Thus, results from this study can make a significant contribution to environmental risk assessment and environmental management strategies which will update relevant decision- and policy-makers (both government and industry). Acknowledgements We acknowledge the financial support of SLU's Environmental monitoring and assessment (EMA)programme “Non-Toxic environment” and the Portuguese Science Foundation (FCT) through CESAM:UID/AMB/50017/2013 and Geo-BioTec: UID/GEO/04035/2013 as well as the biology department of the University of Aveiro. Swedish Metabolomics Centre (www.swedishmetabolomicscentre.se) is acknowledged for the metabolite profiling by GC-MS. Gunilla Ericson-Forslund from Institution for anatomy, physiology and biochemistry (AFB) at SLU, Uppsala is acknowledged for the technical help. We especially thank Daniel Larson, County Administration Board of Dalarna, for information on metal contaminated sites in Dalarna, and for the sampling of diatoms from these sites. Appendix A. Supplementary data Supplementary data related to this article can be found at https://doi.org/10.1016/j.envpol.2018.01.111. References Admiraal, W., Blanck, H., Buckert-De Jong, M., Guasch, H., Ivorra, N., Lehmann, V., Nystrӧm, B.A.H., Paulsson, M., Sabater, S., 1999. Short-term toxicity of zinc to microbenthic algae and bacteria in a metal polluted stream. Water Res. 33, 1989e1996. https://doi.org/10.1016/S0043-1354(98)00426-6. Allan, J.D., Castillo, M.M., 2007. Stream Ecology: Struture and Functions of Running Waters, second. ed. Springer, US https://doi.org/10.1007/978-1-4020-5583-6. Allen, A.E., Laroche, J., Maheswari, U., Lommer, M., Schauer, N., Lopez, P.J., Finazzi, G., Fernie, A.R., Bowler, C., 2008. Whole-cell response of the pennate diatom Phaeodactylum tricornutum to iron starvation. Proc. Natl. Acad. Sci. U.S.A. 105, 10438e10443. https://doi.org/10.1073/pnas.0711370105. Andersen, R.A., 2005. Algal Culturing Techniques. Elsevier Academic Press. Anderson, M., Gorley, R., Clarke, R., 2008. Permanovaþ for Primer: Guide to Software and Statistical Methods. Anderson, M., Gorley, R., Clarke, R., Permanova, Multivar, 2005. Anal. Variance, a Comput.

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