Glyphosate-Based Herbicide Toxicophenomics in Marine Diatoms: Impacts on Primary Production and Physiological Fitness

applied sciences Article Glyphosate-Based Herbicide Toxicophenomics in Marine Diatoms: Impacts on Primary Production and Physiological Fitness Ricardo Cruz de Carvalho 1,2,* , Eduardo Feijão1, Ana Rita Matos 3,4 , Maria Teresa Cabrita 5, Sara C. Novais 6, Marco F. L. Lemos 6, Isabel Caçador 1,4, João Carlos Marques 7, Patrick Reis-Santos 1,8 , Vanessa F. Fonseca 1,9 and Bernardo Duarte 1,4 1MARE—Marine and Environmental Sciences Centre, Faculdade de Ciências da Universidade de Lisboa, Campo Grande, 1749-016 Lisbon, Portugal; [email protected] (E.F.); [email protected] (I.C.); [email protected] (P.R.-S.); vff[email protected] (V.F.F.); [email protected] (B.D.) 2cE3c, Centre for Ecology, Evolution and Environmental Changes, Faculty of Sciences, University of Lisbon, Campo Grande, Edifício C2, Piso 5, 1749-016 Lisbon, Portugal 3 BioISI—Biosystems and Integrative Sciences Institute, Plant Functional Genomics Group, Departamento de Biologia Vegetal, Faculdade de Ciências da Universidade de Lisboa, Campo Grande, 1749-016 Lisboa, Portugal; [email protected] 4Departamento de Biologia Vegetal da Faculdade de Ciências da Universidade de Lisboa, Campo Grande, 1749-016 Lisboa, Portugal 5Centro de Estudos Geográficos (CEG), Instituto de Geografia e Ordenamento do Território (IGOT) da Universidade de Lisboa, Rua Branca Edmée Marques, 1600-276 Lisboa, Portugal; [email protected] 6 MARE—Marine and Environmental Sciences Centre, ESTM, Polytechnic of Leiria, 2411-901 Leiria, Portugal; [email protected] (S.C.N.); [email protected] (M.F.L.L.) 7University of Coimbra, MARE—Marine and Environmental Sciences Centre, Department of Life Sciences, 3000 Coimbra, Portugal; [email protected] 8Southern Seas Ecology Laboratories, School of Biological Sciences, The University of Adelaide, Adelaide, SA 5005, Australia 9Departamento de Biologia Animal da Faculdade de Ciências da Universidade de Lisboa, Campo Grande, 1749-016 Lisboa, Portugal *Correspondence: rfcr[email protected] Received: 9 September 2020; Accepted: 19 October 2020; Published: 22 October 2020   Featured Application: Application of non-invasive bio-optical techniques to evaluate the ecotoxicity of glyphosate-based pesticide in marine diatoms with confirmation by classical biochemical tools. Abstract: Glyphosate is the main active component of the commercial formulation Roundup ® , the most widely used chemical herbicide worldwide. However, its potential high toxicity to the environment and throughout trophic webs has come under increasing scrutiny. The present study aims to investigate the application of bio-optical techniques and their correlation to physiological and biochemical processes, including primary productivity, oxidative stress, energy balance, and alterations in pigment and lipid composition in Phaeodactylum tricornutum, a representative species of marine diatoms, using the case study of its response to the herbicide glyphosate-based Roundup ® formulation, at environmentally relevant concentrations. Cultures were exposed to the herbicide formulation representing effective glyphosate concentrations of 0, 10, 50, 100, 250, and 500 µ g L −1 . Results showed that high concentrations decreased cell density; furthermore, the inhibition of photosynthetic activity was not only caused by the impairment of electron transport in the thylakoids, but also by a decrease of antioxidant capacity and increased lipid peroxidation. Nevertheless, concentrations of one of the plastidial marker fatty acids had a positive correlation with the highest concentration as well as an increase in total protein. Cell energy allocation also increased with concentration, relative to control and the lowest concentration, although culture growth was Appl. Sci. 2020,10, 7391; doi:10.3390/app10217391 www.mdpi.com/journal/applsci Appl. Sci. 2020,10, 7391 2 of 21 inhibited. Pigment composition and fatty acid profiles proved to be efficient biomarkers for the highest glyphosate-based herbicide concentrations, while bio-optical data separated controls from intermediate concentrations and high concentrations. Keywords: photobiology; energetic metabolism; pesticide; oxidative stress; glyphosate 1. Introduction In recent years, the concern over emerging pollutants and their effects on the marine biota metabolism has grown exponentially. Man-made contaminants invariably present new challenges in monitoring efforts and risk prevention [ 1 ]. These chemicals, including pesticides, pharmaceuticals, and personal and household care products, are used daily worldwide and their presence in the environment stems from an exponential increase in human activities related to their usage [ 2 ]. In the first decade of the 21st century, more than 50% of the total production of chemicals included environmentally harmful compounds [ 3 ]. Furthermore, the speed of technological advances made in synthetic chemical production continues to increase the list of these novel substances [ 4 ], raising important questions and concerns about their ecotoxicity and efficient monitoring methodologies. Glyphosate (N-(phosphonomethyl) glycine) is a phosphonate herbicide and the main active ingredient in the commercial mixture Roundup ® , the most used chemical herbicide worldwide [ 5 , 6 ]. Glyphosate is a broad-spectrum herbicide with a unique mode of action: It acts as a glycine analogue, inhibiting the enzyme 5-enolpyruvyl-shikimate-3-phosphate synthase (EPSPS) of the shikimate pathway, thus affecting the synthesis of aromatic amino acids [ 7 ]. The dramatic increase in its use globally is also associated with the development of glyphosate-tolerant crops that present a tolerant EPSPS synthase and/or a glyphosate metabolism gene [ 8 ]. Being relatively unsusceptible to chemicaland photodecomposition, glyphosate can easily reach coastal and marine areas via a multitude of direct and/or diffuse pathways [ 9 ]. While pesticides are mainly used in both agriculture and weed control, their persistence in any given aquatic environment can allow them to be carried into remote marine environments, although the exact means by which this occurs is still a subject under debate [10,11]. Marine phytoplankton is a key biomonitor in many marine trophic webs which, under natural conditions, responds to a wide range of environmental disturbances and contamination events [ 12 – 16 ] and any impacts at this level are highly likely to lead to bottom-up impacts. Glyphosate was shown to impair cyanobacteria growth at concentrations as low as 50 µ g L −1 [ 17 ], and in freshwater, glyphosate influences microbial community structure, changing the community from green algae and diatoms (glyphosate sensitive) to cyanobacteria (glyphosate tolerant) [ 18 , 19 ]. Moreover, structural changes to marine communities have been associated with glyphosate application [ 20 ]. Ultimately, ecotoxicological studies on marine organisms are of the utmost importance to establish guidelines to safeguard local biodiversity and the functioning of estuarine, coastal, and marine environments [21,22]. Diatoms, as part of phytoplankton, are among the first organisms to be affected by contaminants, quickly responding to suspended toxicants due to their small size (0.2–200 µ m) and high uptake rates [ 13 , 23 – 26 ]. Diatoms are also constantly re-adjusting the equilibrium between energy production from photosynthesis and energy consumption under environmental stress conditions, an ability that undermines their success in highly dynamic coastal and estuarine environments [27]. While they are responsible for half of all the photosynthesis on Earth and thus have an important role in the global biological carbon pump and the silica cycle [ 28 ], our knowledge of carbon allocation regulation in diatoms is very limited, particularly because of these present distinct metabolic compartmentations and additional metabolic pathways in comparison to the more widely studied green algae [29–32]. Diatoms are also major marine producers of specific fatty acids [ 32 ], including essential fatty acids (EFA), linoleic acid (omega-6 [ ω -6] class), and α -linolenic acid (ALA). Diatoms also produce long-chain polyunsaturated fatty acids (LC-PUFA) such as eicosapentaenoic acid (EPA) and docosahexaenoic acid Appl. Sci. 2020,10, 7391 3 of 21 (DHA) (omega-3 [ ω -3] class) [ 33 ]. Vertebrates cannot synthesize essential fatty acids and the ability to produce LC-PUFA is also limited; they do not obtain these through their diet [ 34 , 35 ]. Furthermore, LC-PUFA plays key roles in animal and human health, being major components of neurological tissues [36]. Photosynthesis has been shown to be impaired by glyphosate-based herbicides within wide ranges of concentrations, including in cordgrass Spartina densiflora from spray application at concentrations of 720–7200 g ha −1 [ 37 ], to direct contact of 10–80 mg L −1 in Anabaena fertilissima [ 38 ]. In both cases, there was inhibition of CO 2 assimilation and depletion of intermediates from the photosynthetic carbon reduction cycle due to deregulation of the shikimate pathway [ 39 , 40 ]. In such scenarios, non-invasive high-throughput bio-optical screening tools, such as Pulse Amplitude Modulated (PAM) fluorometry, emerge as invaluable techniques to evaluate ecotoxicity in photosynthetic organisms [ 12 , 41 , 42 ]. Through PAM it is possible to translate the fluorescence signals as proxies to the bioenergetics involved in photosynthesis in a non-destructive form [ 13 , 41 – 44 ] to efficiently assess primary productivity [ 45 , 46 ] and the physiological effects in plant material at different concentrations of contaminants [ 12 , 41 , 42 , 44 ]. The half-life of glyphosate in water varies between 45 and 60 days [ 47 ] and phytoplankton have a fast response in the presence of contaminants [ 13 , 25 ]. Thus, it is of the utmost importance to evaluate the potential effects of glyphosate in the environment, namely on primary producers. The present study aimed to correlate bio-optical data with the ecotoxicological effects of the exposure of the glyphosate-based herbicide Roundup ® (i.e., currently found in estuarine and marine systems) [ 48 – 51 ], with the working hypothesis that, similarly to other photosynthetic organisms, this herbicide will have a negative impact on primary productivity, antioxidant enzyme activity, energy balance, pigment and fatty acid composition of the model diatom Phaeodactylum tricornutum, and its potential implications on estuarine or coastal marine ecosystems. 2. Materials and Methods 2.1. Experimental Setup The model diatom P. tricornutum Bohlin (Bacillariophyceae) (IO 108–01, IPMA, ALISU—Algae Collection of the University of Lisbon, Lisbon, Portugal) was harvested from monoclonal cultures in 250 mL of f/2 medium [ 52 ] in culture flasks (Drechsel-type gas washing bottles) under controlled conditions for 4 days (18 ± 1 ◦ C, under constant aeration and a 14 h light/10 h dark photoperiod). The growth chamber was programmed to simulate sunrise and sunset using a sinusoidal function with a light intensity at noon simulating a natural light environment (RGB 1:1:1, Maximum PAR 80 µ mol photons m −2 s −1 , 14/10 h day/night rhythm). According to the Organization for Economic Cooperation and Development (OECD) guidelines for algae bioassays [ 53 ] and the recommended initial cell density for microalgae cells with similar size to P. tricornutum, initial cell concentration was approximately 2.7 ×105cells mL−1 . Forty-eight hours after inoculation, cultures were exposed to 0, 10, 50, 100, 250, or 500 µ g L −1 glyphosate for 48 h [ 24 , 41 , 46 ], obtained from the glyphosate-based herbicide “Roundup ® Pronto” containing 7.2 g L −1 of glyphosate. Since no studies have measured glyphosate in marine water, the herbicide concentrations were chosen based on the range of environmental concentrations found in agricultural water streams in relevant literature [ 49 – 52 ], as it was found that this chemical presents the same half-life in saltwater as it does in freshwater [ 10 , 11 ]. While other substances compose Roundup ® , glyphosate is the main active component. Exposure took place 48 h after inoculation to ensure that the experiment was performed during the cell exponential growth phase [ 24 , 41 , 46 ]. There were three replicates for each herbicide concentration from a total of 18 experimental units. To avoid contamination, the labware was washed with HNO 3 (20%) for 48 h, rinsed thoroughly with ultra-pure water and autoclaved. All culture manipulations were performed in a laminar airflow chamber using aseptic techniques. Appl. Sci. 2020,10, 7391 4 of 21 2.2. Growth Rates and Cell Harvesting During the exposure trials, daily cell counting of P. tricornutum subjected to different glyphosate-based herbicide concentrations was performed using a Neubauer improved counting chamber, with an Olympus BX50 (Tokyo, Japan) inverted microscope, at 400-times magnification. Culture growth was determined from the difference between initial and final logarithmic cell densities divided by the exposure period [ 54 ], expressed as the mean specific growth rate per day. Samples for photochemical and biochemical analysis were collected after 48 h of exposure to glyphosate-based herbicide (4 days after inoculation). Based on the glyphosate-based herbicide concentrations, we determined the No Observed Effect Concentration (NOEC) and the Lowest Observed Effect Concentration (LOEC) [ 55 ]. Furthermore, by application of a sigmoidal dose-response curve to the endpoint measurement for each exposure concentration, we also determined the Effective Concentration (EC) which inhibited growth by 10% (EC 10 ), 25% (EC 25 ), and 50% (EC 50 ) [ 55 ]. At the end of the exposure time and after the chlorophyll fluorescence measurements (see next section), samples of 30 mL of culture were centrifuged at 4000 × gfor 15 min at 4 ◦ C (Sigma 2-16K, Sigma Laborzentrifugen GmbH, Germany). The supernatant was removed, and pellets were immediately frozen in liquid nitrogen and stored at −80 ◦C until analysis. 2.3. Bio-Optical Assessment through Chlorophyll a Pulse Amplitude Modulated (PAM) Fluorometry Pulse amplitude modulated (PAM) chlorophyll fluorescence measurements were performed using a FluorPen FP100 (Photo System Instruments, Drasov, Czech Republic) on 15 min dark-adapted samples using a 1 mL cuvette. Culture cell density was assessed daily, using a non-actinic light to measure minimum chlorophyll fluorescence (F 0 ). Analysis of chlorophyll transient light curves (Kautsky plot) was carried out using the OJIP test according to [ 41 ]. Fluorometric analysis parameters and their description can be accessed in Table 1. Table 1. Fluorometric analysis parameters and their description. OJIP Test Area Corresponds to the oxidized quinone pool size available for reduction and is a function of the area above the Kautsky plot N Reaction center turnover rate SMCorresponds to the energy needed to close all reaction centers M0Net rate of PS II RC closure γRC Probability that a PS II chlorophyll molecule will function as an RC PGGrouping probability between the two PS II units ABS/CS Absorbed energy flux per cross-section TR/CS Trapped energy flux per cross-section ET/CS Electron transport energy flux per cross-section DI/CS Dissipated energy flux per cross-section RC/CS Number of available reaction centers per cross-section TR0/DI0 Contribution or partial performance due to the light reactions for primary photochemistry δR0/(1 −δR0) Contribution of PS I, reducing its end acceptors ψ0/(1 −ψ0) Contribution of the dark reactions from QA−to PC ψE0/(1 −ψE0) Equilibrium constant for the redox reactions between PS II and PS I RE0/RC Electron transport from PQH2to the reduction of PS I end electron acceptors RC/ABS Reaction center II density within the antenna chlorophyll bed of PS II Appl. Sci. 2020,10, 7391 5 of 21 2.4. Pigment Analysis Pigment extraction was performed according to methodologies from previous works [ 12 , 13 , 46 ]. Pure acetone was added to sample pellets and maintained in an ultra-sound cold bath for 2 min, ensuring total disaggregation of cell material, and kept in the dark at − 20 ◦ C for 24 h to prevent degradation. Samples were centrifuged for 15 min at 4000 × gand 4 ◦ C and the supernatants were scanned by a dual-beam spectrophotometer from 350 nm to 750 nm at 0.5 nm steps (Shimadzu UV-1603, Shimadzu Co., Kyoto, Japan). Using the SigmaPlot Software, the absorbance spectrum was introduced in the Gauss-Peak Spectra (GPS) fitting library. Pigment analysis was performed according to [ 56 ], allowing the detection of chlorophyll aand c, pheophytin a, β -carotene, fucoxanthin, diadinoxanthin (DD), and diatoxanthin (DT). 2.5. Antioxidant Enzyme Assays The soluble protein fraction was extracted at 4 ◦ C from cell pellets in 1 mL of 50 mM sodium phosphate buffer (pH 7.6) with 0.1 mM Na-EDTA and placed in an ultrasound bath for 1 min from the previously collected pellets. The homogenate was centrifuged at 10,000 × gfor 10 min at 4 ◦ C to remove debris and the supernatant collected to a new tube. Protein concentration was determined according to [ 57 ]. Catalase (CAT) activity was measured according to [ 58 ], monitoring H 2 O 2 consumption and the consequent decrease in absorbance at 240 nm ( ε =39.4 mM −1 cm −1 ). The reaction mixture contained 50 mM of sodium phosphate buffer (pH 7.6), 0.1 mM of Na-EDTA, and 100 mM of H 2 O 2 with the reaction being started by the addition of 100 µ L of extract. Ascorbate peroxidase (APX) was assayed according to [ 59 ]. The reaction mixture contained 50 mM of sodium phosphate buffer (pH 7.0), 5 µ M of H 2 O 2 , and 0.25 µ M L-ascorbate, and the reaction was also initiated with the addition of 100 µ L of the extract. The activity was recorded as the decrease in absorbance at 290 nm and the amount of ascorbate oxidized calculated from the molar extinction coefficient ( ε =2.8 mM −1 cm −1 ). Superoxide dismutase (SOD) activity was assayed according to [ 60 ] by monitoring the reduction of pyrogallol at 325 nm. The reaction mixture contained 50 mM of sodium phosphate buffer (pH 7.0) and 0.24 mM of pyrogallol and ultra-pure water, with the reaction being started by the addition of 10 µ L of extract. Control assays were done in the absence of substrate to evaluate the autoxidation of the substrates. All the assays were performed at 25 ◦C in a UV500 UV-Visible Spectrometer (Unicam, Waltham, MA, USA). 2.6. Lipid Peroxidation Analysis Lipid peroxidation products were determined according to [ 61 ]. Sample pellets were homogenized briefly in 1.5 mL of 10% (v/v) Trichloroacetic acid (TCA), containing 0.4% (w/v) thiobarbituric acid (TBA) and placed in an ultrasound bath for 1 min. The reaction was conducted at 100 ◦ C for 30 min; immediately after it was halted through placement in ice, and after centrifugation at 15,000 × gfor 10 min at 4 ◦ C, 1 mL of the supernatant was collected and mixed with 1 mL of 0.4% TBA and incubated again under the same conditions. After again cooling down in ice and centrifuging, the absorbance at 532 nm and 600 nm of the supernatant was recorded by spectrophotometry. The concentration of malondialdehyde (MDA) was determined using the molar extinction coefficient ( ε =155 mM −1 cm −1 ). 2.7. Fatty Acid Profiles The fatty acid analysis was performed according to [ 46 ] by direct trans-esterification of sample pellets, in freshly prepared methanol sulfuric acid (97.5:2.5, v/v), at 70 ◦ C for 60 min, using the internal standard pentadecanoic acid (C15:0). Fatty acid methyl esters (FAMEs) were recovered using petroleum ether, dried with an N 2 flow, and re-suspended in an adequate amount of hexane. Through gas chromatography (Varian 430-GC gas chromatograph equipped with a hydrogen flame ionization detector set at 300 ◦ C, Middelburg, The Netherlands), 1 µ L of the FAME solution was analyzed, setting the injector temperature to 270 ◦ C, with a split ratio of 50. The fused-silica capillary column (50 m × 0.25 mm; WCOT Fused Silica, CP-Sil 88 for FAME; Varian, Middelburg, The Netherlands) Appl. Sci. 2020,10, 7391 6 of 21 was maintained at a constant nitrogen flow of 2.0 mL min −1 and the oven set to 190 ◦ C. Fatty acids identification was performed by comparison of retention times with standards (Sigma-Aldrich) and chromatograms analyzed by the peak surface method, using the Galaxy software. To determine the membrane saturation levels, the double bond index (DBI) was calculated according to [46]: DBI =2×(% monoenes +2×% dienes +3×% trienes +4×% tetraenes +5×% pentaenes) 100 (1) 2.8. Energy Balance Cell pellets were homogenized by ultrasonication on ice (3x 10s at A =20%) using 1 mL of Milli-Q water. Aliquots were taken from each sample for the analysis of lipid, carbohydrate and protein contents, and electron transport system (ETS) activity. In all assays, ultrapure water was used as reaction blank. The spectrophotometric measurements were performed in triplicates, at 25 ◦ C, using a synergy H1 Hybrid Multi-Mode microplate reader (Biotek®Instrument, Winooski, VT, USA). 2.8.1. Energy Available The energy available (Ea) was measured by determining the total protein, carbohydrate, and lipid contents and transforming the results into energetic equivalents (combustion energies: 17,500 mJ mg carbohydrates −1 , 24,000 mJ mg protein −1 , and 39,500 mJ mg lipid −1 ) [ 61 ]. Extraction and quantification of total lipids, proteins, and carbohydrates were performed according to [ 62 , 63 ] with minor modifications [ 64 ]. Cell pellets were resuspended in 50 mM sodium phosphate buffer (pH 7) containing 1 mM phenylmethylsulfonyl fluoride (PMSF). Cell disruption was performed with 0.42–0.6 mm glass beads (Sigma-Aldrich) for 15 min at 6.5 ms –1 (FastPrep-24, MP Biomedicals). Cell extract was centrifuged at 10,000 × gfor 20 min at 4 ◦ C. The supernatant was stored at − 80 ◦ C until further analysis. Total protein content in the samples was determined using Bradford’s method [ 56 ]. Total lipids were extracted by adding 250 µ L of chloroform (spectrophotometric grade, Sigma-Aldrich), 250 µ L of methanol (spectrophotometric grade, Sigma-Aldrich) and 125 µ L Milli-Q water to 150 µ L of the sample. After centrifugation at 1000 × gfor 5 min, the organic phase and interphase were removed and 500 µ L of H 2 SO 4 was added to 100 µ L of lipid extract and charred for 15 min at 200 ◦ C. The mixture was cooled down to 20 ◦ C, 1.5 mL of deionized water was added, and total lipid content was determined by measuring the absorbance at 375 nm and compared to a calibration curve using tripalmitin values as standard. Total carbohydrate content was determined by adding 50 µ L of 15% TCA to the 150 µ L of sample and subjected to − 20 ◦ C for 10 min. After centrifugation at 1000 × gfor 10 min, the total carbohydrate content of the supernatant fraction was quantified by adding 50 µ L of 5% (v/v) phenol and 200 µ Lof18MH 2 SO 4 to 50 µ L extract [ 65 ]. Following 30 min of incubation at 20 ◦ C, absorbance was measured at 492 nm and compared to a calibration curve using glucose as standard. 2.8.2. Energy Consumption Cellular oxygen consumption and metabolism are directly linked to mitochondrial ETS activity. As such, ETS was determined according to [ 66 ] with major modifications [ 65 ]. In 30 µ L of sample or blank, 20 µ L of homogenizing buffer [0.3 M Tris, 15% (w/v) polyvinyl pyrrolidone (PVP), 459 µ M MgSO4, 1.5 mL Triton X-100, pH 8.5], 100 µ L of buffered substrate solution (reduced nicotinamide adenine dinucleotide (NADH) (1.79 mM) and reduced nicotinamide adenine dinucleotide phosphate (NADPH) (280 µ M) in 0.13 M Tris, 0.3% (w/v) Triton X-100, pH 8.5) were added. The reaction was initiated by adding 50 µ L of 8 mM p-iodonitrotetrazolium (INT), following the change in absorbance at 490 nm over a 3 min period at 20 ◦ C. The formazan formed was calculated by using the extinction coefficient, ε=15,900 mM–1 cm–1. The cellular energy consumption (Ec) was determined by using the ETS data (for each 2 µ mol of INT-formazan formed, 1 µ mol of O 2 was consumed in the ETS), transforming the calculated quantity Appl. Sci. 2020,10, 7391 7 of 21 of oxygen consumed into energetic equivalents by using the specific oxyenthalpic equivalents for an average lipid, protein, and carbohydrate mixture of 480 kJ mol O2−1[62]. 2.8.3. Cellular Energy Allocation The cellular energy allocation (CEA), a methodological approach that integrates the energy available and energy consumption of an organism, was standardized to 10 6 cells and calculated based on measurements of lipid, carbohydrate, and protein content and ETS activity for each sample as follows [67]: CEA =Ea Ec (2) where: Ea (available energy)=carbohydrate +lipid +protein mJ 10−6cells(3) Ec (energy consumption)=ETS activity mJ h−110−6cells(4) 2.9. Statistical Analysis Each variable was evaluated through one-way ANOVA with Tukey’s multiple comparisons test (GraphPad Prism 6.03 for Windows, GraphPad Software, San Diego, CA, USA), regarding differences among glyphosate-based herbicide concentrations. The data obtained from the Kautsky plots, pigment, and fatty acid profiles, were used as the basis for the construction of the respective resemblance matrixes based on the Euclidean distances between samples. To classify and separate the different treatment groups, statistical multivariate models based on the Kautsky plot, pigment composition, and fatty acid profile variable were generated using Canonical Analysis of Principal Coordinates (CAP), through the non-parametric multivariate analysis packages in Primer 6 software as described previously in other works [12,45,68,69]. 3. Results 3.1. Cell Growth Rates Regarding cell density, after 48 h exposure P. tricornutum cultures were negatively affected, in particular by the two highest concentrations of glyphosate-based herbicide (250 and 500 µ g L −1 ), with slight decreases in cell density observed only at lower concentrations (50 and 100 µ g L −1 ) (Figure 1A). Appl. Sci. 2020, 10, x FOR PEER REVIEW 7 of 23 2.8.3. Cellular Energy Allocation The cellular energy allocation (CEA), a methodological approach that integrates the energy available and energy consumption of an organism, was standardized to 106 cells and calculated based on measurements of lipid, carbohydrate, and protein content and ETS activity for each sample as follows [67]: 𝐶𝐸𝐴 = 𝐸𝑎 𝐸𝑐 (2) where: 𝐸𝑎 (𝑎𝑣𝑎𝑖𝑙𝑎𝑏𝑙𝑒 𝑒𝑛𝑒𝑟𝑔𝑦)= 𝑐𝑎𝑟𝑏𝑜ℎ𝑦𝑑𝑟𝑎𝑡𝑒 + 𝑙𝑖𝑝𝑖𝑑 + 𝑝𝑟𝑜𝑡𝑒𝑖𝑛 (𝑚𝐽 10−6 𝑐𝑒𝑙𝑙𝑠) (3) 𝐸𝑐 (𝑒𝑛𝑒𝑟𝑔𝑦 𝑐𝑜𝑛𝑠𝑢𝑚𝑝𝑡𝑖𝑜𝑛)=𝐸𝑇𝑆 𝑎𝑐𝑡𝑖𝑣𝑖𝑡𝑦 (𝑚𝐽 ℎ−1 10−6 𝑐𝑒𝑙𝑙𝑠) (4) 2.9. Statistical Analysis Each variable was evaluated through one-way ANOVA with Tukey’s multiple comparisons test (GraphPad Prism 6.03 for Windows, GraphPad Software, San Diego, CA, USA), regarding differences among glyphosate-based herbicide concentrations. The data obtained from the Kautsky plots, pigment, and fatty acid profiles, were used as the basis for the construction of the respective resemblance matrixes based on the Euclidean distances between samples. To classify and separate the different treatment groups, statistical multivariate models based on the Kautsky plot, pigment composition, and fatty acid profile variable were generated using Canonical Analysis of Principal Coordinates (CAP), through the non-parametric multivariate analysis packages in Primer 6 software as described previously in other works [12,45,68,69]. 3. Results 3.1. Cell Growth Rates Regarding cell density, after 48 h exposure P. tricornutum cultures were negatively affected, in particular by the two highest concentrations of glyphosate-based herbicide (250 and 500 µg L−1), with slight decreases in cell density observed only at lower concentrations (50 and 100 µg L−1) (Figure 1A). Figure 1. Growth indicators ((A) cell density and (B) derived growth parameters) of Phaeodactylum tricornutum following exposure to a herbicide formulation representing different glyphosate-based herbicide concentrations for (A) 24 h and 48 h, and (B) 48 h (mean ± s.d., n = 3, different letters indicate significant differences at p < 0.05). However, after 48 h exposure only decreases in specific growth rates, with lower divisions per day and higher doubling time, were observed at the highest glyphosate-based herbicide concentrations (>250 µg L−1) (Figure 1B). Therefore, a negative effect was observed in the two highest herbicide formulation concentrations regarding all the determined growth parameters. Based on the Figure 1. Growth indicators (( A ) cell density and ( B ) derived growth parameters) of Phaeodactylum tricornutum following exposure to a herbicide formulation representing different glyphosate-based herbicide concentrations for ( A ) 24 h and 48 h, and ( B ) 48 h (mean ± s.d., n =3, different letters indicate significant differences at p<0.05). Appl. Sci. 2020,10, 7391 8 of 21 However, after 48 h exposure only decreases in specific growth rates, with lower divisions per day and higher doubling time, were observed at the highest glyphosate-based herbicide concentrations ( >250 µg L−1) (Figure 1B). Therefore, a negative effect was observed in the two highest herbicide formulation concentrations regarding all the determined growth parameters. Based on the glyphosate-based herbicide concentrations present in the environment surrounding the diatom population used in the experiment, we determined the respective NOEC (10 µ g L −1 ), the LOEC (50 µg L−1), the EC10 (15.4 µg L−1), the EC25 (94.4 µg L−1), and the EC50 (225.9 µg L−1). 3.2. Bio-Optical Assessment of Diatom Photochemistry Apart from the lowest concentration (10 µ g L −1 ), the Kautsky plots showed decreasing fluorescence values with increasing herbicide quantities (Figure 2), particularly at the highest glyphosate-based herbicide concentrations (250 and 500 µg L−1). Appl. Sci. 2020, 10, x FOR PEER REVIEW 8 of 23 glyphosate-based herbicide concentrations present in the environment surrounding the diatom population used in the experiment, we determined the respective NOEC (10 µg L−1), the LOEC (50 µg L−1), the EC10 (15.4 µg L−1), the EC25 (94.4 µg L−1), and the EC50 (225.9 µg L−1). 3.2. Bio-Optical Assessment of Diatom Photochemistry Apart from the lowest concentration (10 µg L−1), the Kautsky plots showed decreasing fluorescence values with increasing herbicide quantities (Figure 2), particularly at the highest glyphosate-based herbicide concentrations (250 and 500 µg L−1). Figure 2. Chlorophyll transient kinetics (OJIP curves) in Phaeodactylum tricornutum following a 48 h exposure to a glyphosate-based herbicide formulation in different concentrations (mean ± s.d., n = 3). The analysis of the photochemical process from light-harvesting electronic transport, represented by the four main energy fluxes, demonstrates the effects of exposure of the different herbicide concentrations in P. tricornutum cultures (Figure 3). Figure 2. Chlorophyll transient kinetics (OJIP curves) in Phaeodactylum tricornutum following a 48 h exposure to a glyphosate-based herbicide formulation in different concentrations (mean ± s.d., n =3). The analysis of the photochemical process from light-harvesting electronic transport, represented by the four main energy fluxes, demonstrates the effects of exposure of the different herbicide concentrations in P. tricornutum cultures (Figure 3). The amount of energy absorbed by the photosystem II (PS II) antennae (ABS/CS), the energy flux that was effectively trapped inside the PS II (TR/CS) and transported within the electron transport chain (ETC) (ET/CS), as well as in the energy dissipation flux (DI/CS) and the reduction of the number of oxidized PS II reaction centers (RC/CS), all showed the same pattern with increasing concentrations. Overall, no effects relative to the control were observed at the lowest glyphosate-based herbicide concentration (10 µ g L −1 ), but a small decreasing effect of intermediate concentrations (50 and 100 µ g L −1 ) and a high decrease in the highest glyphosate-based herbicide concentrations (250 and 500 µ g L −1 ) was evident. These changes can be further analyzed through inspection of the functioning of different components of the photosystems and ETC in response to glyphosate-based herbicide concentration (Supplementary Figure S1). Regarding the oxidized quinone pool size, there was a decrease only in the highest glyphosate-based herbicide concentrations (250 and 500 µ g L −1 ). However, there were no significant changes in the number of Q A redox turnovers until maximum fluorescence was reached (N), except for the highest concentration in which enhancement was observed. The same pattern occurred in the energy needed to close (reduce) all RCs (S M ). At the highest glyphosate-based Appl. Sci. 2020,10, 7391 9 of 21 herbicide exposure concentrations (250 and 500 µ g L −1 ), a decrease in the probability of a PS II chlorophyll molecule functioning as an RC ( γRC ) was detected. However, no differences were observed in the QAreduction rate (M0). Appl. Sci. 2020, 10, x FOR PEER REVIEW 8 of 23 glyphosate-based herbicide concentrations present in the environment surrounding the diatom population used in the experiment, we determined the respective NOEC (10 µg L−1), the LOEC (50 µg L−1), the EC10 (15.4 µg L−1), the EC25 (94.4 µg L−1), and the EC50 (225.9 µg L−1). 3.2. Bio-Optical Assessment of Diatom Photochemistry Apart from the lowest concentration (10 µg L−1), the Kautsky plots showed decreasing fluorescence values with increasing herbicide quantities (Figure 2), particularly at the highest glyphosate-based herbicide concentrations (250 and 500 µg L−1). Figure 2. Chlorophyll transient kinetics (OJIP curves) in Phaeodactylum tricornutum following a 48 h exposure to a glyphosate-based herbicide formulation in different concentrations (mean ± s.d., n = 3). The analysis of the photochemical process from light-harvesting electronic transport, represented by the four main energy fluxes, demonstrates the effects of exposure of the different herbicide concentrations in P. tricornutum cultures (Figure 3). Figure 3. The energy fluxes (absorbed (ABS/CS), trapped (TR/CS), transported (ET/CS) and dissipated (DI/CS)) and the number of available reaction centers per cross-section (RC/CS) in Phaeodactylum tricornutum following a 48 h exposure to a glyphosate-based herbicide formulation in different concentrations (mean ±s.d., n =3, different letters indicate significant differences at p<0.05). While the active OECs showed a decrease only under the highest glyphosate-based herbicide concentration (500 µ g L −1 ), the P G , the grouping probability that correlates with the disconnection between the two PS II units, increased with the highest glyphosate-based herbicide concentration (250 and 500 µg L−1) (Figure 4). Between PS II and PS I, photochemical processes showed a significant decrease in the contribution of light (TR 0 /DI 0 ) and dark ( ψ0 /1 −ψ0 ) reactions of the photochemical cycle in the highest glyphosate-based herbicide concentration (250 and 500 µ g L −1 ). A similar pattern was observed in the reaction center density within the PS II antenna chlorophyll bed (RC/ABS). On the other hand, at the PS I level there was a significant enhancement in the activity of this photosystem ( δR0 /1 −δR0 ) in response to the highest glyphosate-based herbicide concentrations, also leading to an increase in the equilibrium constant for the redox reaction between both photosystems towards the PS II ( ψE0 /(1 −ψE0 )). Furthermore, regarding PS I, intrinsic changes led, in turn, to an increase of the electron transport from PQH 2 to the reduction of the PS I end acceptors (RE0/RC). In the rapid light curve (RLC)-derived parameters, the photosynthetic efficiency ( α ) and the maximum electron transport rate (ETR max ) only decreased with the highest glyphosate-based herbicide concentration (500 µ g L −1 ), with no effect on photoinhibition ( β ) and light saturation (E k ), with only a slight reduction at 250 µ g L −1 glyphosate-based herbicide exposure in the latter parameter (Supplementary Figure S2). Appl. Sci. 2020,10, 7391 16 of 21 Yet, a severe shift in the redox equilibrium between photosystems towards the PS II ( ψE0 /(1 −ψE0 )) was still observed, decreasing the redox potential reaching the PS I, and thus impairing the light and dark reactions of photosynthesis and the renewal of substrates in the PS I [45]. Nevertheless, the available energy (Ea) increased in the highest glyphosate-based herbicide concentrations, particularly at 500 µ g L −1 , probably due to an increase in lipid and protein concentrations. The increase in Ea has been observed in green algae, which accumulated energy reserves as a response to environmental stress [ 64 , 80 , 81 ]. A possible explanation could be related to the need for algae to counteract the increase in energy expenditure, as observed in the present study. Therefore, following a similar pattern as Ea, the energy consumption demonstrated by the mitochondrial ETS of P. tricornutum increased significantly at the highest concentrations, reaching a 300% increase in the highest concentration relative to control. This increase in energy consumption has been observed in other microalgae [ 65 ]. Nonetheless, the Ea was higher than the ETS, which led to a slight increase of the CEA in the highest concentrations but only allowing a differentiation of the highest concentrations from the control and the lowest concentrations. This increase in CEA may reflect a higher impairment in mitochondria functioning relative to chloroplast functioning that can ultimately impact the latter due to biophysical disturbances [ 82 ]. While these energy balances appear to indicate an increase in the energy available for growth or cell division, the highest glyphosate-based herbicide concentrations inhibited diatom culture growth. Based on this data, stress forces the energy to shift from photosynthesis into energy consumption. This may change photosynthetic electron pathways, leading to Ea downregulation and an increase in ETS to avoid carbon waste, as a strategy to handle an excess of metabolic energy. There are different metabolic pathways under which energy spillover can be managed, but current relevant knowledge is still very scarce [32]. The CAP analyses were very efficient in the assessment of the effects of the glyphosate-based herbicide on the photochemistry, pigment composition, and lipid metabolism of P. tricornutum, as well as on the potential of these metabolic features as toxicity biomarkers. However, only the use of bio-optical techniques (e.g., Kautsky plot) allowed an efficient identification of all the different glyphosate-based herbicide exposure treatments (control, low, intermediate, and high concentrations). As in previous studies, multivariate analysis efficiently classified groups subjected to different exposure levels, in comparison to the often-used univariate analysis [ 12 , 45 , 69 ]. While glyphosate is the main component of Roundup ® , other substances are also in its composition and it is of great interest in future works to assess synergies and/or antagonisms between the herbicide formulation versus glyphosate in its pure form, comparing the values to those measured in the habitats. 5. Conclusions Glyphosate-based pesticides, particularly at high concentrations, have a clear effect on several metabolic pathways in marine diatoms (changes in pigment profile, photosynthetic impairment, and decreased antioxidant capacity). Even though photoprotective mechanisms were induced, membrane damage still occurred. These facts highlight the application of pulse amplitude modulated chlorophyll fluorescence bio-optical methods as a promising tool for inclusion in ecotoxicological studies with several advantages relative to the classical biochemical approaches, namely fast data acquisition, lower monetary costs, and a high number of variables obtained while ensuring a high degree of accuracy. Thus, bio-optical tools appear as a fast, inexpensive, and reliable method for toxicophenomic assessment of the impacts of this widespread pesticide in marine diatoms, with a clear dose-response pattern. Moreover, the high volume of data produced by these bio-optical techniques can be efficiently applied in multivariate analysis, providing a classification with a high degree of accuracy. With this in mind, PAM fluorometry appears to be a promising tool for inclusion in ecotoxicological studies aiming towards a possible use in long-range detection through satellite imagery in a global chemical pollution-monitoring network. Appl. Sci. 2020,10, 7391 17 of 21 Supplementary Materials: The following are available online at http://www.mdpi.com/2076-3417/10/21/7391/s1, Figure S1: Photosystem II and ETC related photochemical traits, Figure S2: Rapid light curves and derived parameters, Figure S3: Major fatty acids classes, Figure S4: Fatty acid ratios, Figure S5: Omega 6 to omega 3 fatty acid ratio, Table S1: Fluorometric analysis parameters and their description. Author Contributions: Conceptualization, B.D., V.F.F. and P.R.-S.; methodology, B.D.; formal analysis, R.C.d.C. and B.D.; investigation, R.C.d.C., E.F. and S.C.N.; data curation, R.C.d.C.; writing—original draft preparation, R.C.d.C.; writing—review and editing, E.F., A.R.M., M.T.C., S.C.N., M.F.L.L., I.C., J.C.M., P.R.-S., V.F.F., B.D.; supervision, B.D.; project administration, B.D.; funding acquisition, B.D. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by Fundaç ã o para a Ci ê ncia e a Tecnologia (FCT) via project grants PTDC/CTA-AMB/30056/2017 (OPTOX), UID/MAR/04292/2019, UID/MULTI/04046/2019. Work was also funded by the Integrated Programme of SR&TD SmartBioR (reference Centro-01-0145-FEDER-000018), co-funded by Centro 2020 program, Portugal 2020, European Union, through the European Regional Development Fund. B. Duarte and V. Fonseca were supported by investigation contracts (CEECIND/00511/2017 and DL57/2016/CP1479/CT0024). P. Reis-Santos was supported by FCT through a postdoctoral grant (SFRH/BPD/95784/2013). Acknowledgments: The authors would like to thank Caroline Casey and Joana Roma for revising the English language, grammar, punctuation, and spelling of the manuscript. Conflicts of Interest: The authors declare no conflict of interest. Abbreviations ALA α-linolenic acid; APX ascorbate peroxidase; CAP Canonical Analysis of Principal Coordinates; CAT catalase; CEA cellular energy allocation; DBI double bond index; DD diadinoxanthin; DHA docosahexaenoic acid; DT diatoxanthin; Ea energy available; Ec energy consumption; EC Effective Concentration; EFA essential fatty acids; EPA eicosapentaenoic acid; EPSPS 5-enolpyruvyl-shikimate-3-phosphate synthase; ETC electron transport chain; ETS electron transport system; FAME fatty acids methyl esters; FCP fucoxanthin-chlorophyll protein; LC-PUFA polyunsaturated fatty acids; LOEC Lowest Observed Effect Concentration; MDA malondialdehyde; NOEC No Observed Effect Concentration; OEC oxygen-evolving complexes; PAM Pulse Amplitude Modulated; PS I photosystem I; PS II photosystem II; RC reaction centers; RLC rapid light curves; SOD superoxide dismutase References 1. Gavrilescu, M.; Demnerov á , K.; Aamand, J.; Agathos, S.; Fava, F. 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