A multiple-level study of metal tolerance in Salix fragilis and Salix aurita clones

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A multiple-level study of metal tolerance in Salix fragilis and Salix aurita clones Aricia Evlarda,⁎,1 , Kjell Sergeant b,1 , Bruno Printzb , Cédric Guignardb , Jenny Renautb , Bruno Campanellaa , Roger Paula , Jean-Francois Hausmanb a

Soil and Water Systems Unit, Gembloux Agro-Bio Tech, University of Liège, 2, Passage des Déportés, B-5030 Gembloux, Belgium Centre de Recherche Public — Gabriel Lippmann, Department Environment Agrobiotechnologies, 41, Rue du Brill, L-4422 Belvaux, Luxembourg

b

AR TIC LE I N FO

ABS TR ACT

Article history:

The response of two willow clones (Salix fragilis (Sf) and Salix aurita (Sa)) to the presence

Received 28 August 2013

of metals (Zn, Cu, Cd, Ni) was studied. Rooted cuttings were planted in control and

Accepted 3 February 2014

contaminated soil. After 100 days, different parameters (biomass, chlorophyll fluorescence

Available online 14 February 2014

(Fv/Fm), pigment and sugar concentrations, electrolyte leakage and proteome-level changes) were analyzed. The growth of Sa was not influenced by metals whereas Sf produced

Keywords:

significantly less biomass when exposed to the pollutants. Furthermore, although Sa did

Willow

not show a growth reduction in the presence of metals, the overall view of the physiological

Metal trace elements

results among others the changes in the accumulation of sugars and pigments indicated

Abiotic stress

that metals had a more severe impact on this clone. The response at the proteome level

Proteomics

confirmed these observations. The growth reduction and the proteomic changes in Sf

Fluorescence

indicate that this clone adjusts its metabolism to maintain cellular homeostasis. Sa on the

Pigment

contrary maintains growth but the physiological and proteomics data suggests that this can only be done at the cost of cellular deregulation. Therefore high biomass is not linked with a good tolerance strategy. In a long-term study the survival of Sa might be compromised making it a poorer candidate for phytoremediation efforts. Biological significance In the last centuries human activity has resulted in the dispersal of heavy metals with potential phytotoxic effects over large areas. The increased knowledge of the responses of Salix-species, a group of trees with potential as biomass producer but also as phytoremediation agent, when growing on metal-polluted substrate provided by this study has the potential to help in the improved selection of clones with more or less potential for these aims. Contrary to most studies the trees in the current study were exposed to a mixture of metals, thereby facing a closer resemblance to the situation on soils polluted by human activity. Whereas many papers focused on the two main phenotypic characteristics (biomass and accumulation), fewer papers studied

Abbreviations: ROS, reactive oxygen species; SOD, superoxide dismutase; POD, peroxidase; CAT, catalase; 2-DiGE, of two-dimensional electrophoresis coupled with multiplexing fluorescent probes; ICP-MS, inductively coupled plasma mass spectrometry; Fo, initial fluorescence; PSII, photosystem II; Fm, maximal fluorescence; (Fm − Fo)/Fm = Fv/Fm, efficiency of photosystem II. ⁎ Corresponding author. Tel.: + 32 81622 209; fax: + 32 81614 817. E-mail addresses: [email protected] (A. Evlard), [email protected] (K. Sergeant), [email protected] (B. Printz), [email protected] (C. Guignard), [email protected] (J. Renaut), [email protected] (B. Campanella), [email protected] (R. Paul), [email protected] (J.-F. Hausman). 1 Equal contributors.

http://dx.doi.org/10.1016/j.jprot.2014.02.007 1874-3919/© 2014 Elsevier B.V. All rights reseved.

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proteomic and physiological parameters which allow to have a global view of the tolerance of probable willow candidates for phytoremediation purposes. Our data demonstrates that higher biomass production in presence of metals is not necessarily linked with higher tolerance whereas growth reduction might indicate longer long-term tolerance. In the long term and in the purpose of a future use in phytoremediation, the survival of this high producer clone could be compromised. © 2014 Elsevier B.V. All rights reseved.

1. Introduction When metals are in excess in soil, they become toxic as they can disturb plant physiology and thus affect plant development [1,2]. Indeed, metals can interact directly with proteins and lipids of membranes causing membrane damage and thus the loss of cellular electrolytes [2–6]. Moreover, a metal in excess is able to replace essential metals in pigments and enzymes, which can alter their function. The pigment synthesis can be disturbed and their concentrations reduced in the presence of metals, leading to a lower photosynthetic efficiency [6,7]. As has been observed for other abiotic stresses, carbohydrate metabolism can be affected by metal exposure. Several carbohydrates can accumulate, suggesting a role in osmotic adjustments and/or protection of cell constituents [6–9]. Consequently, the disruption of the physiological and biochemical processes in cells reduces plant growth or can even lead to plant death [5,6]. Indirect metal toxicity also exists and lies mainly in the increased generation of reactive oxygen species (ROS) (OU− 2, H2O2; HOU), inducing oxidative stress. Generally, ROS in cells are maintained below toxic levels due to the activity of antioxidative defense mechanisms, which are enzymatic (superoxide dismutase (SOD), peroxidase (POD) and catalase (CAT)) or non-enzymatic (glutathione, carotenoids and ascorbate) [10]. Nevertheless, metals can disrupt the activity of these antioxidative enzymes containing free cysteine residues as they can bind thiol groups which leads to further disturbance of the oxidative balance [5,11]. Because the effects of metals on plants are diverse, several physiological parameters (photosystem efficiency, sugar and pigment concentrations, and electrolyte leakage) are used to evaluate metal-induced cellular damage in this study. For instance, the chlorophyll fluorescence ratio Fv/Fm was used. This ratio estimates the photochemical efficiency of the photosystem II (PSII) as this ratio generally decreases when the photosynthetic apparatus functioning is impaired [12]. In parallel, a proteomic approach can contribute to a better understanding of the impact of metals. While gel-free techniques have become the standard approach for studying the proteome of well-characterized organisms, plant proteomics still largely depends on the use of two-dimensional gel electrophoresis as a quantification tool for proteins. The introduction of fluorescent labels in proteins prior to gel-based separation, as is done in 2D-DiGE, has alleviated some of the limits of this technique. Therefore it is the latter technique that is currently increasingly used to study the influence of biotic and abiotic constraints on the physiology of poorly characterized plant species [4,9,13–16]. Phytoremediation, the use of plants to clean up polluted soils, depends on the potential of plants to tolerate the conditions found on these sites. Furthermore the suitability

of plants for phytoextraction, the extraction of polluting metals from soils, depends on the potential of plants to extract metals from the soil and to accumulate these metals in harvestable plant parts. Because they are fast growing and able to tolerate diverse environmental conditions, the ability of Salix trees to concentrate metals has been investigated to select good candidates for phytoremediation [17]. However, most of these studies were screenings of different Salix clones and selection of the clones that performed best, therefore relatively few studies added molecular data on the mechanisms of extraction and accumulation of these Salix clones. Based on a previous study [18], two willow clones (Salix fragilis and Salix aurita) were selected. The general conclusion from this previous study was that clones that produce a high biomass generally have relatively low metals concentrations (in g/g dry weight) in their aerial parts. One notable exception was observed on this general observation, the S. aurita clone used in the current study produced a high biomass and accumulated high concentrations of metal. Therefore this clone was selected for further study. The S. fragilis clone used in the current study produced the same biomass but, in agreement with the general finding, did not accumulate high concentrations of metal. The detailed study of these clones, equal biomass production but a large difference in concentration of accumulated metals, could therefore shed some light on the differences in the used coping strategy. The aim of the present study was to provide insight in these differences by using not only morphology but also physiological parameters and proteomic analysis on these two willow clones growing with an excess of Cd, Zn, Cu and Ni to explain their metal tolerance/ accumulation abilities.

2. Material and methods 2.1. Plant material and growth conditions A S. fragilis clone (Sf) and a S. aurita clone (Sa) were chosen from a previous screening [18]. These clones showed a similar biomass production but accumulated different metal concentrations in their annual twigs. Rooted cuttings of each clone were placed outdoors in 10 L containers filled up with a contaminated or non-contaminated (control) substrate. These containers had an open bottom in order to avoid waterlogging. The substrate used was composed of soil sampled from farm land, sand (0–2 mm granule size) and peat (V:V, 2:1:1). To contaminate the substrate, a mixture of metals (Cd, Cu, Zn and Ni as chloride salts) was added. The control and contaminated soils were matured outdoors for three years. The total concentration of Ca, Mg, Na, K, Fe, Mn and metal trace elements (Al, Cd, Cu, Ni, Mo, Zn) (after aqua regia digestion) of the soils was determined using inductively coupled plasma

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mass spectrometry (ICP-MS) (Perkin Elmer Elan DRC-e). Ten mL aqua regia was added to 100 to 250 mg of dried sample, acid digestion was carried out in Teflon tubes in a microwave oven (Anton Paar Multiwave 3000) by increasing the temperature and pressure up to 200 °C and 30 bars. At the end of the procedure, the samples were diluted with ultrapure water up to 25 mL and were maintained at 4 °C prior to analysis. For each of the soils a triplicate analysis was done and the mean values are presented in Table 1. Blank samples and certified reference material were included at each mineralization cycle for quality control. Ten rooted cuttings of each Salix clone were planted in the contaminated substrate and another ten in the control substrate. The 40 containers were put outside and randomly placed in racks. During the growth period, the substrates were watered to compensate the water loss until soil saturation. This experimental design is represented in Supplemental Fig. 1. At the planting time, for each treatment (control and contaminated substrate) and for each clone, the plants were randomly divided into 2 sets of 5 replicates. The first set was used to measure chlorophyll fluorescence, biomass production and metal accumulation. The second set was used to determine electrolyte leakage, sugar and pigment concentrations and to collect samples for the proteomic study.

2.2. Biomass measurement and metal analysis After a 100 day growing period, the annual twigs and leaves were collected from the plants, washed twice with double distilled water to remove surface dust, and dried at 60 °C in the oven until a constant mass and weight was attained. Significance was calculated with a two-way ANOVA with treatment and clone as the factors. Leaf and annual twig biomass productions were used as the variables. These analyses were carried out on MINITAB Statistical Software v.16.2.2. Metal concentrations (Cd, Zn, Cu, Ni) in twigs and leaves were analyzed using inductively coupled plasma mass spectrometry (ICP-MS) (Perkin Elmer Elan DRC-e). An aliquot of 100 to 250 mg of dried sample was digested in 7 mL HNO3 (Plasma Pure 67–70%, SCP Science) and 3 mL H2O2 (30%, trace metal analysis, Fisher Scientific). Acid digestion was carried out in Teflon tubes in a microwave oven (Anton Paar Multiwave 3000) as previously described for soils. Significance was calculated with a one-way ANOVA with the clone as the factor. Metal concentrations (Cd, Zn, Cu, Ni) in the leaves and annual twigs were used as the responses. A one-way ANOVA was also carried out with the organ (leaf/twig) as the factor for each clone. MINITAB Statistical Software v.16.2.2 was used for these analyses.

2.3. Chlorophyll fluorescence Analyses were accomplished with a portable fluorometer (PAM 2100 Walz, Effeltrich, Germany) after 30 min of dark adaptation on leaves that were intact, matured and fully exposed to the sun. The measurements were in as far as possible performed around noon. A dark adaptation allowed the electron chain transporters to reach their fully oxidized level (in this case, the photosystems are open) and thus, to

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measure the initial fluorescence (Fo) [19]. The excitation of the reaction centers of the photosystem II (PSII) is reached after the application of a saturation light pulse (0.8 s) (light intensity of the pulse 4 using the instrument's predefined parameters) and the measure of maximal fluorescence (Fm), the maximal emitted fluorescence when all QA are reduced, can be taken. The ratio (Fm − Fo)/Fm = Fv/Fm which represents the efficiency of the photosystem in the dark-adapted state was calculated [12]. Fluorescence measurements were taken on 4 leaves on the 5 replicates of each clone for each treatment. Significance was calculated with a two-way ANOVA with treatment and the clone as factors. The ratio Fv/Fm was used as the response. These analyses were carried out on MINITAB Statistical Software v.16.2.2.

2.4. Electrolyte leakage For each clone, 6 intact, matured leaves, fully exposed to the sun, were cut from each of the control and treated plants and rinsed briefly in milli-Q water. A foliar disc (ϕ 0.6 cm) was cut per leaf. The 6 discs were put in a tube containing 12 mL of milli-Q water. Conductivity was measured with a HI 9033 Multi-range (Hanna instruments). The 20 tubes were shaken for 60 min and the conductivity was measured (T1). The tubes were then autoclaved and, after cooling to room temperature, the maximal conductivity was measured (T2). The electrolyte leakage in per cent was calculated as follows: (T1/T2) × 100. Significance was calculated with a two-way ANOVA with treatment and clone as factors. The electrolyte leakage in per cent was used as the response. These analyses were performed on MINITAB Statistical Software v.16.2.2.

2.5. Sugar and pigment analyses For each sampling, 5–6 intact, mature leaves, fully exposed to the sun, were collected and pooled to form 1 replicate. A total of 5 replicates by genotype and condition were sampled, corresponding to 5 different trees and thus biological replicates. After collection, fresh material was washed with distilled water, frozen in liquid nitrogen and stored at − 80 °C. Prior to analysis, the leaves were crushed in liquid nitrogen and the resulting powder was divided into 2 samples, 1 for carbohydrate and salicin quantification, and 1 for pigment analysis.

2.5.1. Carbohydrate and salicin extraction and analysis Approximately 100 mg of powdered leaves were mixed with 1 mL of a water/ethanol solution (20/80, v/v). After vortexing and shaking with an Eppendorf Thermomixer (30 min,4 °C, 1400 rpm), the samples were centrifuged (17000 g, 4 °C,10 min). The supernatant was collected and the residue was extracted again with 0.5 mL of the water/ethanol mixture (20/80, v/v). The resulting supernatant was pooled with the first one and the final extract was dried at reduced pressure (Speedvac) before being resuspended in 1 mL double distilled water and filtered through 0.45 μm PVDF-filters. The samples were analyzed using High performance Anion Exchange Chromatography coupled with Pulsed Amperometric Detection HPAEC-PAD (Dionex ED 50A, Dionex Corp., Sunnyvale, USA) according to Evers et al. (2010) with slight

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modifications. HPAEC-PAD analyses for carbohydrates were conducted on a Dionex HPLC ICS2500-BioLC (Sunnyvale, USA), with an AS-50 autosampler, a GS-50 gradient pump and an EG-50 eluent generator. The mobile phase, with a flow-rate of 0.5 mL·min− 1, was generated on-line with KOH. The hydroxide concentration was programmed as follows: 9.5 mM for 25 min, 9.5–100 mM for 1 min, 100 mM for 14 min, 100– 9.5 mM for 4 min and column equilibration at 9.5 mM for 5 min. The analytical column was a Dionex CarboPac PA-20 (3 mm × 150 mm) kept at 35 °C. Carbohydrates were quantified using nine-point calibration curves with custom-made external standard solutions, containing arabinose, cellobiose, fructose, galactose, glucose, kestose, maltose, maltotriose, melibiose, raffinose, stachyose, sucrose, xylose and salicin, ranging from 1 to 100 μM. After 10 injections, a check standard solution was used to validate the calibration of the system [20]. Significance was calculated with a two-way ANOVA with treatment and clone as factors. Only the concentrations of fructose, glucose, galactose sucrose and salicin, the sugars that could reliably be quantified, were used. These analyses were carried out on MINITAB Statistical Software v.16.2.2.

2.5.2. Pigment extraction and analysis Approximately 100 mg of frozen powder was mixed with 1 mL acetone. After vortexing and shaking with an Eppendorf Thermomixer (30 min, 4 °C, 1400 rpm), the samples were centrifuged (6000 g, 4 °C, 15 min), the supernatant was collected and stored at − 20 °C, and the residue was extracted again with 0.5 mL of acetone. The resulting supernatant was pooled with the first one and the total extract filtered through a 0.22 μm Acrodisc GHP syringe filter prior to Waters Acquity UPLC® chromatography analysis. In order to assess the percentage recovery of the extraction, β-apo8′-carotenal was added as an internal standard to the extraction mixture to a final concentration of 20 μg·mL− 1. Pigments were analyzed and quantified using a Waters Acquity UPLC® chromatographic system (Milford, MA, USA) coupled with a photodiode array detector (UPLC-PDA). Separation was attained using an Acquity UPLC® HSS T3 column (2.1 × 100 mm, 1.8 μm particle size, Waters) at a flow rate of 0.5 μl·min− 1 with an injection volume of 5 μL, separations were done at 30 °C. The eluents were 50 mM ammonium acetate (A) and acetonitrile/dichloromethane/methanol (75/10/ 10, v/v) (B) with the following gradient: 0 min, 70% B; 13 min 70% B; 18 min 95% B; 26 min, 100% B; 33 min 100% B; 34 min 70% B for a total run time of 36 min. The peaks of all compounds were detected at 450 nm. Calibration curves were obtained from custom-made standard solutions containing a mixture of 13 pigments (α-carotene, antheraxanthin, β-apocarotenal, β-carotene, β-cryptoxanthin, chlorophyll A, chlorophyll B, lutein, lutein epoxide, lycopene, neoxanthin, violaxanthin and zeaxanthin), each ranging from 0.125 μg·mL−1 to 10 μg·mL−1. Samples were analyzed at a 1 to 2 dilution (in pure acetone) for chlorophyll A and chlorophyll B analyses and at a 1 to 10 dilution (in pure acetone) for neoxanthin, violaxanthin, antheraxanthin, zeaxanthin, lutein, b-cryptoxanthin, a-carotene, and b-carotene. Significance was calculated with a two-way ANOVA with treatment and clone as factors. Pigment concentration was used as the variable. These analyses were performed on MINITAB Statistical Software v.16.2.2.

2.6. Proteomics 2.6.1. Protein sample preparation, labeling and 2-DE Proteome analyses were carried out on intact, mature leaves, fully exposed to the sun. Four replicates were used for each clone × treatment. After grinding the plant material in liquid nitrogen, pigments and small molecules were eliminated from the sample by washing in organic solvents. The protocol used in the present study is based on a previously described protocol [21]. Briefly, the powder was resuspended in 1 mL cold 10% trichloroacetic acid (TCA) in acetone with 0.07% w/t DTT, kept in the freezer for 1 h and then centrifuged at 10,000 g for 5 min. After discarding the supernatant, the pellet was washed twice with cold acetone and allowed to dry at room temperature overnight before being resuspended in 0.5 mL SDS buffer (30% sucrose, 2% SDS, 0.1 M Tris–HCl, pH 8.0, 5% 2-mercaptoethanol) and 0.5 mL Tris-buffered phenol (pH 8.0). The sample was vortexed vigorously for 30 s, and shaken for 30 min before being centrifuged at 10000 g for 3 min. Three hundred microliters of the upper phenolic phase was taken and added to fresh tubes with 1.5 mL of cold 0.1 M ammonium acetate in methanol. After an incubation of 30 min at − 20 °C the sample was centrifuged, the supernatant decanted and the pellet washed twice with the same cold ammonium acetate solution in methanol. After two more washes with 80% acetone in water the pellet was dried and resuspended in 200 μL of labeling buffer (30 mM Tris pH 8.0; 7 M urea; 2 M thiourea; 2% w/v CHAPS). After adjusting the pH of the extracts to 8.5, the protein concentration was quantified using the 2D-Quant Kit (GE Healthcare, Little Chalfont, UK) with BSA as standard. All protein extracts and a pooled internal standard were labeled with CyDyes™ (GE Healthcare) prior to electrophoresis. For labeling, a volume of sample corresponding to 40 μg was used and the dyes were swapped to avoid the effects of preferential labeling on the statistical outcome. One hundred and twenty micrograms of proteins (two samples of 40 μg each and 40 μg of the internal standard), the volume adjusted to 120 μL with lysis buffer (7 M urea, 2 M thiourea, 0.5% (w/v) CHAPS) and 0.72 μL of Destreak Reagent, 2.4 μL of IPG buffer 3–10 NL (GE Healthcare) added, were loaded by cup loading onto 24 cm 3–10 NL IPG strips (GE Healthcare). Isoelectric focusing was carried out using an IPGphor IEF unit (GE Healthcare) with the following protocol: 150 V for 2 h, gradient to 1000 V for 4 h, 1000 V for 5 h, gradient to 10,000 V for 5 h, 10,000 V for 7 h until approximately 95,000 Vh were reached at 20 °C with a maximum current setting of 75 μA per strip. After equilibration, reduction and alkylation of cysteines using DTT and iodoacetamide respectively, the strips were applied to 12.5% precast gels (GelCompany, Tübingen, Germany) using the buffer kits according to the manufacturer's instructions.

2.6.2. Image capture and analysis As described by Renaut et al. [22], images for the different CyDyes™ were acquired using a 9400 Typhoon Variable Mode Imager (GE Healthcare) at a resolution of 100 μm using the excitation and detection wavelengths specified by the manufacturer. The images were analyzed using the Decyder v7.0.8.53 software (GE Healthcare). During the analysis of the gel images, the spots are checked for normal distribution.

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Table 1 – Metal concentration and pH in control and contaminated substrate (± standard error of mean) (n = 3). Concentration (pg·g− 1 dry weight) Treatment

Cd

Zn

Cu

Ni

Fe

Mn

Control Contaminated

0.14 ± 0.01 4.44 ± 0.15

44 ± 2 1351 ± 29

14.8 ± 0.4 883.8 ± 70.3

8.2 ± 0.2 96.1 ± 3.1

7964 ± 559 6373 ± 237

272 ± 16 215 ± 16

Concentration (μg·g−1 dry weight) Treatment

Na

Mg

K

Ca

pH

Control Contaminated

2821 ± 74 2495 ± 145

2196 ± 60 1835 ± 55

8081 ± 151 6953 ± 316

8036 ± 289 6520 ± 700

6.9 ± 0.03 6.4 ± 0.02

Normally 95% of the data fall within a +/−2 SD range, only data corresponding to this distribution is considered as being of normal distribution and considered for analysis. Statistical analysis of differential spot volume was carried out with the same software package [23]. Only spots detected on 75% of the gel-images were considered. The fold change was calculated as the ratio between the average spot intensity in control versus treated samples. If the ratio is > 1, lower spot intensity in treated samples, the fold change equals the ratio and if the ratio is <1, the spot intensity in the treated samples is higher than those of the controls, the reported fold change is equal to (− 1/ratio). Three statistical comparisons were made; in the first two the intensity of spots between treated and control were analyzed for each clone; treated Sf/control Sf and treated Sa/control Sa. A third comparison was made with treated Sf&Sa/control Sf&Sa. Spots were considered as significantly different between the compared conditions, when the fold change between conditions was < − 1.5 or > 1.5. Spots compliant with this change in volume were considered as spot of interest when the t-test gave a score p ≤ 0.01 and when a 2-way ANOVA, first condition species and second condition treatment, gave a significant value for the spot. The most used statistical parameter for detecting spots of interest is a p-value of < 0.05, however given the fact that the trials have been carried out in conditions resembling field trials a more stringent statistical threshold was used. This should eliminate influences other than the contamination of the soil, and thus provide a focus on changes induced by the metal concentrations in the soils only. Spots of interest (the gel of which the spots have been picked is given as Supplemental Fig. 2) were picked from the gels, and digested using the fully automated Ettan Spot Handling Workstation (GE Healthcare). After tryptic digestion, the dried peptide extracts were resuspended and spotted on stainless steel MALDI target plates, mixed with an alpha cyanohydroxy-cinnamic acid solution (500 mg in 1 mL 50% ACN/0.1% TFA) and allowed to dry. Mass spectrometry was done using a 5800 MALDI TOF/TOF (AB Sciex), calibrated in MS using the 4700 peptide mass calibration kit and in MS/MS using Glu-fibrinopeptide fragments as references. For each spot 1 MS spectrum was acquired and the 10 highest peaks selected for MS/MS analysis, excluding known contaminants and trypsin autocleavage products. For MS, 1500 laser shots were accumulated, while 3000 spectra were accumulated for MS/MS spectra. Using an in-house MASCOT-server on a ProteinPilot platform (ABSciex), all spectra from one spot

were submitted in a single search, PMF and MS/MS, against the NCBI database (limited to the taxonomy Viridiplantae, downloaded 04/06/2012 containing 1078293 sequences) and the EST Viridiplantae database (75859188 sequences downloaded, autumn 2010). When a protein or peptide was identified based on an EST sequence or a protein with a trivial name, the protein sequence was used in a Blast alignment. The results of these Blast alignments are also represented in Supplemental Table 3. Proteins were considered as being significantly identified when two individual non-identical peptides surpassed the threshold for identification or when one peptide resulted in a protein e-value of < 0.005. All identifications were manually validated and extra data was acquired when insignificant identifications were obtained. The manual validations were done as previously described [24], extra data obtained during this validation phase is added in Supplemental Table 3 with the peptide scores given in red in order to distinguish this data from the data obtained during automated database searches. For some spots, manual sequence determinations were performed and the sequences found used for cross-species identification with FASTS and MSBlast [25].

3. Results 3.1. Biomass production The metal-treated Salix fragilis clone (Sf) showed a significant decrease in biomass production both of twigs and leaves (g dry weight), whereas the biomass production of the S. aurita clone (Sa) did not differ significantly between the two conditions (Fig. 1). When the biomass production between the clones was compared, it was noticeable that on contaminated soil both produce the same biomass, as in the previous screening [18], while Sf has a higher biomass production on control soils.

3.2. Metal concentration in annual twigs For the soil-added trace elements (Cd, Cu, Ni and Zn), a significantly different concentration of metals was found in both twigs and leaves, and this for both clones in comparison to control. The remarkable observation was that, despite the close to 60 times higher total Cu concentration in contaminated soil, the concentration of Cu found in the plant biomass for both clones was lower for plants grown on polluted soil

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0.9

a

Leaves

0.7

2.5

I

0.6

b

g dry weight

g dry weight

3

Annual twigs

0.8

I

0.5 0.4 0.3

a

2 b

I

I

1.5 1

0.2 0.5

0.1 0.0

Control

Contaminated

Sf

Control

Contaminated

0

Control

Sa

Contaminated

Sf

Control

Contaminated

Sa

Fig. 1 – Biomass production (g dry weight) for the different clones of annual twigs (A) and leaves (B) of control and treated plants. Different letters and roman numerals indicate significant differences in biomass production between the two treatments for S. fragilis and S. aurita respectively (ANOVA p < 0.05). n = 5. Bars represent standard error of mean (SE).

(Tables 1 and 2A). The concentrations of Zn and Ni were higher in the treated plants. Cd concentrations in twigs were higher in the treated plants while no significant changes in the Cd concentrations were observed in leaves (Table 2A). The concentration of Mn in Sa was also significantly influenced by the treatment; in twigs it was significantly higher when grown on polluted soils, in leaves on the contrary a 28% lower concentration of Mn was found. When the clones grown on control substrate were compared, higher concentrations of Cd and Mn are found in Sa. A significantly lower Cu concentration was found in annual twigs of Sa. The same analysis on the plants grown on a polluted substrate confirmed these observations, but Cu and Ni were significantly lower in both leaves and twigs of Sa and furthermore Sa-tissues contained significantly less Zn than Sf after growth in polluted soil (Table 2B).

3.5. Pigment concentrations Chlorophyll a and b are the most abundant pigments. Chlorophyll a concentration (μg·g− 1 fresh weight) significantly decreased in the presence of metals for both clones. A decrease was likewise detected for chlorophyll b, but this was not significant mainly due to a larger variation between the measurements (Fig. 4). The ratio chlorophyll a/chlorophyll b did not change significantly (data not shown). Exposure to metals induced significant decreases in the concentration of violaxanthin and alpha-carotene in both clones. For the other pigments, the exposure to the metals induced significant pigment concentration changes only in one of the two clones (antheraxanthin, beta-carotene, neoxanthin) or did not have a significant effect on either of the clones (zeaxanthin, lutein, beta-cryptoxanthin) (Fig. 5).

3.3. Chlorophyll fluorescence and electrolyte leakage 3.6. Proteomics Both clones displayed significantly lower Fv/Fm values when grown in the presence of metals (Fig. 2A). In control conditions, Sa showed significantly higher values in comparison with Sf but the decrease of the ratio measured on the metal-exposed Sa leaves was more important. No significantly different Fv/Fm was observed between Sf and Sa in the metal treatment. The electrolyte leakage increased when Sa grew in the presence of metals (Fig. 2B) but did not vary between the two treatments for Sf. No significant difference was observed between Sf and Sa in both treatments.

3.4. Sugar accumulation The main carbohydrates quantified in the leaves (μmol·g−1 fresh weight) of the two clones were fructose, galactose, glucose and sucrose (Fig. 3). The concentrations of these metabolites did not significantly differ between the clones in control conditions and no increased concentration of carbohydrate was recorded in Sf after growth in a polluted soil. For Sa, the four carbohydrates accumulated to a higher concentration when the plants were grown on a polluted substrate, and for fructose, glucose and galactose the increase was close to 3-fold as compared to controls.

To assess the technical reproducibility of the gels, a correlation between the internal standards was calculated (same sample run as Cy2 labeled sample in all gels). A correlation factor of above 0.96 was obtained when the individual gels were compared with the average of all gels (Supplemental Table 1A), indicating good technical reproducibility of the 2D-gels. The number of spots detected for each sample and the number of spots matched to the master gel have been added as Supplemental Table 1B. The statistical analyses as described in the material and method section resulted in the highlighting of 73 spots that changed significantly in one of the comparisons made (the statistical data of these spots is added as Supplemental Table 2, Venn diagram presentation of these results in Fig. 6A). Of these 73 spots, 28 spots changed significantly in volume for Sf exposed to metals; for Sa 45 spots changed in volume after metal exposure (fold change <− 1.5 or > 1.5 and t-test p ≤ 0.01) (Supplemental Table 1C). Eight of these spots changed significantly in both clones. When the control samples are compared to the treated samples (Sf Sa/Sf cont Sa cont), 23 spots were discerned as changing significantly of these only 5 change in the three analyses that were done.

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Table 2A – Comparison of metal concentration in twigs and leaves between control and treated plants for each clone (± standard error of mean). Different letters and roman numerals indicate significant differences in metal concentration between the two treatments for S. fragilis and S. aurita respectively (ANOVA p < 0.05). n = 5. Sf

Sa

Control

Contaminated

Control

Contaminated

−1

Concentration Cd Zn Cu Ni Fe Mn

in twigs (μg·g dry weight) a 0.85 ± 0.07 a 143.9 ± 5.4 a 16.2 ± 1.4 a 1.1 ± 0.1 a 193.9 ± 11 a 18.5 ± 0.8

b b b b a a

1.30 574.1 11.4 12.8 208.7 17.1

± ± ± ± ± ±

0.05 19.4 0.7 0.3 21.9 2

I I I I I I

1.40 148.9 9.2 1.5 299.7 38.4

± ± ± ± ± ±

0.10 8.8 0.9 0.2 45.3 3.6

II II II II II II

2.14 372.7 5.6 6.1 254.5 49.4

± ± ± ± ± ±

0.19 29.3 0.6 0.7 30.1 2.7

Concentration Cd Zn Cu Ni Fe Mn

in leaves (μg.g−1 dry weight) a 1.40 ± 0.08 a 314 ± 135 a 7.2 ± 0.2 a 6.5 ± 5 a 349.5 ± 26.1 a 35.8 ± 1.9

a b b b a a

1.58 931.9 5.9 28.9 314.9 30.5

± ± ± ± ± ±

0.08 47.5 0.4 1.4 13.7 2.5

I I I I I I

2.22 276 7.7 2.1 421.7 281.5

± ± ± ± ± ±

0.23 15 0.6 0.3 20.5 26.0

I II II II I II

1.78 444 4.6 12.7 377.4 204.5

± ± ± ± ± ±

0.10 42 0.2 1.3 43.5 11.4

Finally this resulted in the significant identification of one or more proteins in 53 spots (Supplemental Table 3). Of these 53, 19 were excluded from biological interpretation because more than one protein was identified (Supplemental Table 3), resulting in the 34 spots that could be used for biological discussion (Table 3; Fig. 6B). Half of the identified proteins (17) are directly involved in sugar metabolism or photosynthesis with the majority being of higher abundance in metal-exposed plants. The groups of proteins involved in oxidoreduction (2 proteins), the antioxidant system (4 proteins of higher abundance after exposure) and protein metabolism (4 proteins of higher abundance in treated plants), changed only for Sa.

4. Discussion In this study, a side-by-side comparison of two Salix clones belonging to 2 different species, S. fragilis (Sf) and S. aurita (Sa), growing on control and polluted soil was achieved. The two clones were compared based on different morphological and physiological parameters and a comparative proteomics study was carried out. When growing on a polluted substrate both clones produce a similar quantity of biomass, as was previously reported [18]. However, contrary to S. fragilis, for the S. aurita clone biomass production was not significantly influenced by the adverse

Table 2B – Comparison between clones of metal concentration in twigs and leaves in control and contaminated treatment (± standard error of mean). Different letters indicate significant differences in metal concentration between the two clones for each treatment (ANOVA p < 0.05). n = 5. Control

Contaminated −1

Concentration in twigs μpg·g Sf Cd Zn Cu Ni Fe Mn

a a a a a a

0.85 143.9 16.2 1.1 193.9 18.5

± ± ± ± ± ±

Concentration in twigs μg·g−1 dry weight

dry weight Sa

0.07 5.4 1.4 0.1 11 0.8

b a b a a b

1.40 148.9 9.2 1.5 299.7 38.4

± ± ± ± ± ±

Sf 0.10 8.8 0.9 0.2 45.3 3.6

Cd Zn Cu Ni Fe Mn

Concentration in leaves μg·g−1 dry weight Sf Cd Zn Cu Ni Fe Mn

a a a a a a

1.40 314 7.2 6.5 349.5 35.8

± 0.08 ±135 ± 0.2 ±5 ± 26.1 ± 1.9

1.30 574.1 11.4 12.8 208.7 17.1

± ± ± ± ± ±

0.05 19.4 0.7 0.3 21.9 1.2

b b b b a b

2.14 372.7 5.6 6.1 254.5 49.4

± ± ± ± ± ±

0.19 29.3 0.6 0.7 30.1 2.7

1.78 444 4.65 12.7 377.4 204.5

± ± ± ± ± ±

0.10 42 0.18 1.3 43.5 11.4

Concentration in leaves μg·g−1 dry weight Sa

b a a a a b

a a a a a a

Sa

2.22 276 7.7 2.1 421.7 281.5

± ± ± ± ± ±

Sf 0.23 15 0.6 0.3 20.5 26.0

Cd Zn Cu Ni Fe Mn

a a a a a a

Sa 1.58 931.9 5.9 28.9 314.9 30.5

± ± ± ± ± ±

0.08 47.5 0.4 1.4 13.7 2.5

a b b b a b

120

J O U RN A L OF P ROT EO M IC S 1 0 1 ( 2 01 4 ) 1 1 3 – 12 9

growth conditions, neither in twigs nor in leaves. Sf produced significantly less biomass, in both twigs and leaves, when exposed to the polluted substrate. The concentration of the metals Zn and Ni increased in the plants grown on the Cd, Cu, Ni and Zn contaminated soil, as could be expected, however for Cd and Cu this was not always as obvious. Indeed, no enhanced accumulation of Cd was observed in the leaves of both clones after the treatment. More surprisingly the concentration of Cu in all analyzed plant parts was lower in plants exposed to the metal-polluted soil (Table 2 A and B). The pH of the soil was checked but found to be invariant, thus not explaining this observation. The concentration of Cu found in the plants was in general very low, for instance as compared to the values obtained by Punshon and Dickinson [26] reporting values of 25–100 ppm for willows growing on non-polluted substrates. The presence of Cu in combination with high concentrations of other metals might result in the exclusion of Cu but no supporting observations were done. The most striking difference in the accumulation of non-added metals is the accumulation of Mn, with concentrations in Sa leaves being approximately 7 times higher compared to those in Sf leaves and this independent of the treatment. The concentration of Mn in twigs and leaves does not vary significantly when Sf plants are grown on a polluted substrate. For Sa plants, Mn concentration in leaves decreases in the presence of metals but in Sa twigs, Mn concentration is higher when growing on a polluted substrate. It is previously described that high concentrations of Zn decreases the uptake

A

and translocation of Mn [27]. The fact that this influence is not observed for Sa twigs indicates that the two clones are differentially influenced by high concentrations of Zn. Environmental constraints are known to have an influence on different plant fluorescence parameters and pigment concentrations; therefore quantification of these parameters is often used as a relative indicator for stress experienced by a plant [7]. In the present study, both clones showed a decrease of the ratio Fv/Fm (Fig. 2A). However, this decrease was double for Sa compared to Sf. Generally, a lower value of the ratio compared to a control situation is due to an increase in Fo, indication of permanent damage to the PSII, and a decrease in Fm [28]. Interestingly, these results were observed for Sa but not for Sf (Fig. 2C). So, the light absorbed by PSII was less efficiently used in the photochemistry of metal-treated Sa plants in comparison to Sf plants, indicating damage to the polypeptides of the photosynthetic machinery [12]. It was previously shown that metals can directly affect the photosynthesis apparatus [2] and alter the electron transport [5]. From this knowledge, we can also conclude that there is a direct effect of high metal concentrations for both clones. For both clones, no significant decrease in the ratio Chla/ Chlb was observed although the concentration of Chla significantly decreased in response to the treatment (Fig. 4). During the photosynthesis process, carotenoids absorb light at wavelengths not used by the chlorophylls, thereby protecting the photosynthetic apparatus and regulating the flow of energy in the chloroplast thylakoids [28]. Furthermore, carotenoids, especially violaxanthin and zeaxanthin, act as

B 0.78

14

a

0.72

b

0.7

II

0.68 0.66 0.64 0.62

Electrolyte leakage (%)

Fv/Fm

0.74

II

I

0.76

12

a

Contaminated

Control

Contaminated

Sa

Sf

I

10 8 6 4 2 0

Control

a

Control

Contaminated

Sf

Control

Contaminated

Sa

C Fo Control

Contaminated

Sf

a 0.51 ± 0.01

a 0.51 ± 0.01

Sa

a 0.52 ± 0.01

b 0.59 ± 0.02 Fm

Control

Contaminated

Sf

a 1.88 ± 0.06

a 1.72 ± 0.06

Sa

a 2.09 ± 0.04

b 1.88 ± 0.06

Fig. 2 – Values of Fv/Fm ratio, Fo and Fm (A, C) and electrolyte leakage (%) (B) of control and treated plants. Different letters and roman numerals indicate significant differences in fluorescence ratio values between the two treatments for S. fragilis and S. aurita respectively (ANOVA p < 0.05). n = 5. Bars in figures A and B represent standard error of mean (SE). Fig. 2C: mean ± SE.

121

J O U RN A L OF P ROT EO M IC S 1 0 1 ( 2 01 4 ) 1 1 3 – 12 9

0.6 Fructose

16

II

14 12 10

a

a

8 6 I

4

II

Galactose

µmol/g fresh weight

µmol/g fresh weight

18

0.5 0.4 a a

0.3 0.2

I

0.1

2 0

0 Control

Contaminated

Control

Contaminated

Control

Sa

Sf 12

Contaminated

Sa

a

a

6 4

I

2

II

Sucrose

80

µmol/g fresh weight

µmol/g fresh weight

II

10

0

Control

90 Glucose

8

Contaminated

Sf

70 60 50

I

a

a

40 30 20 10

Control

Contaminated

Control

0

Contaminated

Control

Sa

Sf

Contaminated

Control

Contaminated

Sa

Sf

Fig. 3 – Carbohydrate concentration in μmol/g fresh weight in leaves of control and treated plants. Different letters and roman numerals indicate significant differences in concentration of each carbohydrate between the two treatments for S. fragilis and S. aurita respectively (ANOVA p < 0.05). n = 5. Bars represent standard error of mean (SE).

1000 900 800 700 600 500 400 300 200 100 0

reduction of pigment concentration is accompanied by a decrease in the efficiency of PSII. For instance, Cheng et al. [8] showed a decrease in the ratio Fv/Fm, a decrease in Chla concentration and in the ratio Chla/Chlb in Canna indica in the presence of Cd. The authors indicated that Chla was more sensitive to Cd than Chlb. Maleva et al. [6] confirmed this last observation, and a decrease in Fv/Fm in Elodea plants. In the few studies which were done on woody plants (Salix, Populus), little or no decrease in the pigment concentrations and/or Fv/Fm were noted [4,17,38–41] except in Pietrini et al. [42] and Fernàndez et al. [43]. Our results corroborate the hypothesis that the reduction of the photosynthetic capacity is caused by an increased sensitivity to photo-destruction because of lower accumulation and/or biosynthesis of antioxidant carotenoids and pigments [29,35]. It 350

a

Chl a

I

II b

µg/g fresh weight

µg/g fresh weight

antioxidants by reacting with free radicals and dissipate the excess of excitation energy. As such, they protect the metabolism from free radicals [6,7,29]. Apart from zeaxanthin that increases, the concentrations of all pigments analyzed in the current study decreased when the clones were grown on the polluted substrate. However these changes in pigment accumulation were not always significant for both clones, only violaxanthin and alpha carotene decreased significantly in both clones. Antheraxanthin and beta carotene only decreased significantly in Sa while the decrease of neoxanthin was significant in Sf (Fig. 5). Decreased concentrations of chlorophyll and carotenoids are regarded as a symptom of plant stress perception [28–30], which can be caused by metals [31–37]. In agreement with our study, other reports indicated that the

300

Chl b

a

I I

250 200

a

150 100 50 0

Control

Contaminated

Sf

Control

Contaminated

Sa

Control

Contaminated

Sf

Control

Contaminated

Sa

Fig. 4 – Chlorophyll a and chlorophyll b concentrations in leaves of control and treated plants. Different letters and roman numerals indicate significant differences in chlorophylls a and b concentrations between the two treatments for S. fragilis and S. aurita respectively (ANOVA p < 0.05). n = 5. Bars represent standard error of mean (SE).

122

J O U RN A L OF P ROT EO M IC S 1 0 1 ( 2 01 4 ) 1 1 3 – 12 9

25

50

Violaxanthin

a

I

40 30 II b

20 10

Control

Contaminated

Control

Control

Contaminated

Control

α-Carotene

5

I

II

b

4 3 2 1

40

Contaminated

Sa

Sf

µg/g fresh weight

µg/g fresh weight

5

45 a

I

β-Carotene

a

II

35

a

30 25 20 15 10 5

0

0 Control

Contaminated

Control

Sf

Contaminated

Control

Sa

Contaminated

Control

Sf

60

Contaminated

Sa

35 I

a

I

40 b

30 20 10

µg/g fresh weight

Neoxanthin

µg/g fresh weight

II

10

Contaminated

6

I

Zeaxanthin

30 25

I

a a

20 15 10 5

0

0 Control

Contaminated

Control

Sf

Contaminated

Control

Contaminated

Control

Sf

Sa I I

a

a

3 2.5 2 1.5 1

µg/g fresh weight

β-Cryptoxanthin

4

140

Contaminated

Sa

160

4.5

µg/g fresh weight

a

15

Sa

Sf

3.5

I

20

0

0

50

Antheraxanthin

a

µg/g fresh weight

µg/g fresh weight

60

I a

Lutein

I

120 a

100 80 60 40 20

0.5

0

0 Control

Contaminated

Sf

Control

Contaminated

Sa

Control

Contaminated

Sf

Control

Contaminated

Sa

Fig. 5 – Pigment concentration in μg/g fresh weight in leaves of control and treated plants. Different letters and roman numerals indicate significant differences in concentration of each pigment between the two treatments for S. fragilis and S. aurita respectively (ANOVA p < 0.05). n = 5. Bars represent standard error of mean (SE). is remarkable that most pigments decrease but not zeaxanthin and beta-cryptoxanthin. This could potentially be due to the specific metal-induced inhibition of zeaxanthin epoxidase, the enzyme catalyzing the two-step conversion of zeaxanthin to antheraxanthin and violaxanthin. Such inhibition, through the interaction of Cd with an essential cysteine residue, was previously described [44]. However, since no enzymatic activities were recorded during the present study the

increased activation of the reverse reaction by violaxanthin de-epoxidase under the conditions described here could give similar changes in pigment concentration and can thus not be ignored. Furthermore, the increased electrolyte leakage of the Sa leaves indicates that Sa experiences more influence on membrane integrity compared to Sf from the exposure to metals in the current experiment (Fig. 2B). These stress

123

J O U RN A L OF P ROT EO M IC S 1 0 1 ( 2 01 4 ) 1 1 3 – 12 9

A

B Sf/Sfcont

Sa/Sa cont

3

13 7

5

34 3

8 SfSa/SfcontSa cont

Sf/Sf cont

Sa/Sacont

3

5

17

5

1 3 SfSa/Sf

Sa

cont

cont

Fig. 6 – Venn diagram representation of the result of the gel image analysis. A: spots of interest for the different comparisons made. B: the number of spots wherein a single protein was identified for the different comparisons; only these spots were used for biological interpretation. Sa, S. aurita; Sf, S. fragilis; the subscript “cont” indicates plants exposed to the contaminated substrate.

indicators point to the conclusion that Sa experiences more stress compared to Sf, contradicted by the fact that in Sf growth was reduced while Sa did not show negative effects on biomass production. The concentration of the four quantified sugars increased in the leaves of treated Sa plants while no significant increase for any of these sugars was measured in Sf (Fig. 3). On the contrary, salicin did not accumulate in the presence of metals. The accumulation of soluble sugars was previously observed in poplar and Solanum lycopersicum exposed to metals [9,45]. In other studies on herbaceous plants different hypotheses have been proposed to explain the increased accumulation of photoassimilates during exposure to metals [46]. This might have beneficial results such as increased osmoprotection or the direct scavenging of ROS by sucrose, limiting the oxidative damage generally associated with biotic and abiotic stresses [47]. In a study on oak, Spieβ et al. [48] noted the accumulation of hexoses after drought treatment and indicated that osmotic adjustment is an adaptive response. But the accumulation of sugars is known to have more profound effects as well; because of feedback inhibition, important parts of the central metabolism are regulated by the concentrations of sugars and, additionally, sugars have signaling properties, which interact with stress-signal pathways to modulate metabolism [49]. Feeding external glucose to tomato plants resulted in a decrease of the pigment concentration, as is observed in Sa. But similarly the accumulation of soluble sugars might account for the decrease in photosynthesis noted in most studies on metal-exposed plants [50,51]. The reverse relationship between sugar accumulation and photosynthesis stems from the sugar-induced down regulation of the expression of gene coding for photosynthetic proteins [52,53]. Sugar accumulation can be a reflex of growth retardation (lower metabolic use), changes in the allocation pattern of the carbon reserves and/or distinct metabolic strategies [9,54] Although metals have no impact on the biomass production of Sa plants, the overall view on the results from the above mentioned parameters indicates that this clone suffers the most from the imposed stress. The corresponding parameters in Sf commonly change in the same direction but generally the changes in Sa are non-significant. For the proteomic results exactly the same conclusions can be drawn. The normalized volumes of the majority of the spots change in the same

direction (increased or decreased spot volume) for both clones, but with a different amplitude of change, passing from significant for one clone to non-significant for the other. Only two groups of proteins do not follow this pattern, proteins that are part of the antioxidant system and proteolytic proteins which were less abundant only in treated Sa plants. Most of the photosynthesis-related proteins are less abundant in the presence of metals in both clones. This concerns proteins from the Calvin Cycle, which were identified in 13 spots (Table 3); RuBisCO small chain (1857, 1871, 1886, 1887), RuBisCO activase (902, 982, 984)), sedoheptulose-1,7-bisphosphatase (1069 and 1073) and proteins involved in light-harvesting or oxygen generation (1377, 1532 and 1571). For RuBisCO large chain, the observations are somewhat more ambiguous although some spots containing this protein decrease others have an increased volume. Given the multitude of spots wherein this protein is generally identified conclusions on its increased/decreased abundance are difficult to attain. The lower abundance in photosynthetic proteins is in agreement with those previously observed in abiotic stress studies. The decreased amount of RuBisCO and RuBisCO activase, indicates a diminution of the CO2 fixation capacity due to the presence of metals [4,9,15,55–59]. This diminution in carbon fixation is confirmed by the decreased intensity of two spots containing sedoheptulose-1,7-bisphosphatase, a key enzyme in ribulose1,5-bisphosphate regeneration [2,45], known to be important in determining the photosynthetic capacity [60]. Spots containing proteins involved in the photosystem are likewise less abundant in metal-stressed plants and again the impact on Sa is more important than that on Sf. This is linked with the decreased Fv/Fm ratio, showing the same difference between the clones. Chloroplastic ATP synthase beta subunit (791) was less abundant in both clones in the presence of metals, again linked with the suppression of photosynthesis. A vacuolar proton ATPase, catalytic subunit A (625), was, on the contrary, more abundant in the presence of metal for Sf. This trend was also observed for Sa but it was not significant. This protein, an ATP-dependent proton pump which transports protons across membranes, was previously found to be induced in the presence of an excess of metals [4,61]. Two proteins were found to be more abundant after two months of growth on a polluted substrate, this was the case for

124

Table 3 – Spots that changed significantly when comparing the proteome of the control-versus the treated clones. The data resulting in these identifications is shown in Supplemental Table 3. Sf Spot a) Photosynthesis 623

Function/protein name

b)

982

RuBisCO activase

984

Ribulose bisphosphate carboxylase/oxygenase activase 1 Oxygen-evolving enhancer protein 1 (OEE1) Predicted chlorophyll a–b binding protein CP26 Chlorophyll a/b-binding protein type III Putative sedoheptulose-1, 7-bisphosphatase Putative sedoheptulose-1, 7-bisphosphatase Carbonic anhydrase

748

371

654

1857

1871 1886 1887

1377 1532 1571 1069 1073 1543

Control/ contaminated

2-way ANOVA

t-Test e)

Av. ratio f)

t-Test e)

Av. ratio f)

t-Test e)

Av. ratio f)

Clone

340511874

7.10E −04

− 1.89

4.90E−01

−1.06

3.10E− 03

−1.41

8.90E −01

2.30E−04

1.20E−03

C

297167025

7.60E −03

1.63

1.60E−01

−1.29

4.50E −01

1.16

1.40E −01

2.90E−01

3.30E−03

Tetrachondra hamiltonii

C

912530

2.10E −01

1.16

3.20E−03

− 2.69

1.60E −01

−1.27

7.90E−05 6.80E −03

4.70E− 04

Podocarpus longifoliolatus

C

13548800

8.60E −01

−1.05

2.80E−03

− 1.51

4.90E −01

−1.15

1.70E−07 5.10E−02

9.20E −02

Nicotiana plumbaginifolia

C

132118

3.00E −02

1.76

1.20E−04

1.73

1.70E −01

1.74

9.30E−09 1.30E −04

8.70E −01

Populus trichocarpa

C

224127464 255560434

1.60E −03

3.43

7.90E−03

1.58

1.70E −01

1.73

1.60E−09 2.60E −05

8.70E−03

Populus trichocarpa

C

224127464 255560434

9.20E −03

2.05

5.60E−04

1.65

2.80E −01

1.69

1.90E−10 6.90E −05

2.90E −01

Ricinus communis

C

224127464 255560434

1.10E −03

2.64

5.10E−03

1.53

3.70E −01

1.58

1.60E−12 9.90E −06

1.60E −02

Zantedeschia aethiopica Zantedeschia aethiopica P. trichocarpa × P. deltoides

C

13430332

6.70E −03

1.66

2.10E−01

1.13

8.70E−03

1.34

1.80E −02

1.60E−03

3.80E −02

C

13430336

4.70E −03

1.71

2.80E−02

1.47

2.00E− 04

1.57

2.00E −01

2.70E−04

4.30E −01

C

118489408 255566442

1.20E −02

2.12

2.80E−02

1.46

8.60E−04

1.79

2.70E −01

7.20E−04

1.30E −01

Species

Subcell. loc c)

NCBI access d)

Potentilla reptans

C

Pimelea humilis

EST access

Treatment Interaction

Lycopersicon esculentum Glycine max

C

12644171

8.10E −05

1.67

6.70E−02

1.39

7.60E−04

1.51

1.50E −02

2.00E−04

3.00E −01

C

356535308

3.90E −01

1.28

3.50E−03

2.26

4.20E −02

1.54

5.20E−03 1.00E−02

1.80E −01

Lycoris aurea

C

116519121

5.50E −01

1.14

7.50E−03

1.93

2.90E −01

1.72

6.40E−06 2.70E−02

1.80E −01

Ricinus communis

C

224098511 255579134

4.90E −02

1.62

3.10E−02

1.49

3.10E− 03

1.56

1.30E −01

3.30E−03

7.80E −01

Ricinus communis

C

224098511 255579134

2.70E −01

1.25

8.40E−03

1.57

5.30E −02

1.43

8.80E−04 7.30E −03

2.40E −01

P. tremula × P. tremuloides

C

1354517

8.00E −03

2.26

3.20E−02

1.35

9.90E− 04

1.72

2.30E −01

3.40E −02

4.40E−04

J O U RN A L OF P ROT EO M IC S 1 0 1 ( 2 01 4 ) 1 1 3 – 12 9

902

Partial ribulose-1,5bisphosphate carboxylase/oxygenase Ribulose-1,5-bisphosphate carboxylase/oxygenase large subunit Ribulose-1,5-bisphosphate carboxylase/oxygenase large subunit Ribulose-1,5-bisphosphate carboxylase/oxygenase large subunit Ribulose bisphosphate carboxylase small chain 8B precursor Ribulose bisphosphate carboxylase small chain 1B Ribulose bisphosphate carboxylase small chain 1B Putative ribulose bisphosphate carboxylase chain 1B precursor Partial RuBisCO activase

Sa

Sf Spot a)

Function/protein name

b)

t-Test e)

Av. ratio f)

t-Test e)

255539098

5.60E −01

1.1

N

224065729 283135880

3.80E −01

Solanum tuberosum

N

76573291

Populus trichocarpa

C

Populus trichocarpa

Control/ contaminated

2-way ANOVA

Av. ratio f)

t-Test e)

Av. ratio f)

8.90E−03

1.63

1.70E −02

1.35

4.80E−01

1.20E −02

6.40E −02

−1.2

3.30E− 03

2.14

1.30E −01

1.36

4.40E−01

3.80E −02

2.80E −03

5.10E −01

−1.1

1.90E− 03

2.01

1.90E −01

1.2

4.70E−05 1.10E −02

1.60E −03

224091909

1.70E −01

1.3

9.00E− 03

1.51

4.40E −03

1.4

2.60E−01

6.30E−03

5.50E −01

N

224105373

6.20E−03

−2.51

3.50E −01

−1.31

2.60E −01

−2.25

1.70E−05 1.50E −02

3.00E −01

Populus trichocarpa

N

224105373

1.90E −02

−2.23

4.50E −02

−1.51

9.50E −03

− 1.93

4.20E−03 1.60E − 03

2.80E −01

Brachypodium distachyon

M

326527549 357111628

9.60E −01

−1.01

3.70E−03

− 1.61 2.90E −01

−1.18

5.60E−06 2.20E −02

1.90E −02

Brachypodium distachyon

M

357111628

6.20E −01

−1.23

5.30E− 04

− 2.11 9.80E −02

−1.46

2.90E−04 9.90E −03

5.90E−02

Salix reticulata

C

7708632

1.20E−03

1.89

1.00E −03

1.46

4.80E −02

1.58

1.80E−08 4.00E −06

7.20E −02

Ricinus communis

C

118489858 255550363

7.20E −02

1.63

2.70E− 03

1.8

1.30E −01

1.76

1.30E−06 1.40E − 03

8.20E −01

Populus trichocarpa

C

224128696 225446693

2.60E −01

−1.26

8.60E−03

1.76

4.50E −01

1.34

3.30E−05 1.20E −01

4.40E −03

Populus trichocarpa

C

224128696 225446693

3.90E −01

−1.26

5.60E−03

1.68

5.70E −01

1.35

8.70E−06 2.10E −01

1.30E −02

Vitis vinifera

C

225459844

4.10E −01

−1.11

2.10E−03

1.5

2.10E −01

1.15

3.90E−01

1.20E −01

7.30E −03

Populus trichocarpa

N

224097420 12585490

3.20E−05

−1.87

6.40E −02

−1.28

1.30E −02

−1.62

3.70E−06 1.40E − 05

1.20E −02

Ricinus communis Ricinus communis O. sativa Japonica group

C C C

224069480 255556984 224140195 255556984 224073126 50509325

4.70E −02 1.50E −02 2.40E− 03

1.72 1.22 1.81

6.60E− 04 2.70E− 03 7.30E−02

2.96 1.73 1.4

1.30E −03 7.10E −02 3.30E −02

2.41 1.54 1.66

3.20E−03 1.00E −04 2.20E−07 7.20E − 05 3.10E−05 5.10E −04

1.60E −01 1.90E −02 2.50E −01

Species

Subcell. loc c)

NCBI access d)

Ricinus communis

N

Populus trichocarpa

EST access

Clone

Treatment Interaction

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Antioxidant system 1542 Putative glutathione-stransferase theta (gst) 1546 Phi class glutathione transferase (GSTF2) 1568 Dehydroascorbate reductase-like protein 1637 2-Cys peroxiredoxin Secondary metabolism 1265 Phenylcoumaran benzylic ether reductase 3 1268 Phenylcoumaran benzylic ether reductase 3 Oxidoreduction 628 Predicted succinate dehydrogenase [ubiquinone] flavoprotein 646 Predicted succinate dehydrogenase [ubiquinone] flavoprotein Energy metabolism 791 ATP synthase beta subunit Protein folding 1563 Putative groes chaperonin Proteolysis 612 Predicted ATP-dependent zinc metalloprotease (FTSH 2) 613 Predicted ATP-dependent zinc metalloprotease (FTSH 2) 604 Predicted ATP-dependent zinc metalloprotease (FTSH) ATP synthesis coupled proton transport 625 V-type proton ATPase catalytic subunit A Miscellaneous 1462 Putative ribonucleoprotein 1536 Putative ribonucleoprotein 1284 Putative SHOOT1 protein

Sa

a)

Spot number according to Supplemental Fig. 2. Obtained as result of database searching as described in the material and method section, or after a blast sequence alignment of the EST sequence on which the identification was based. c) Subcellular localization as taken either from the description of the NCBI entry or after submitting the sequence to TargetP: C for chloroplast, M for mitochondrium and N for other/unknown. d) Accession number from the NCBInr database, where a protein has been identified based on the EST database or where the identified protein has a trivial name, the found sequence was blasted and the protein with the highest homology is given. e) P-value of the t-test for the treatment factor (p < 0.01, t-test). f) Average ratio of the spot intensity (control/contaminated). Positive ratio values are given as such, while negative values are given according to the following formula: given value = −1/average ratio. In bold, spots for which the t-test are significant. Negative values indicate proteins that are more abundant in metal-exposed plants. b)

125

126

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two spots containing phenylcoumaran benzylic ether reductase (PCBER) (1265 significant for Sf and 1268 only significant when comparing control versus exposed); the direction of change was the same for Sa but not significant. PCBER is an enzyme involved in cell wall dynamics and lignan synthesis [62]. They are predominantly found in secondary xylem and associated with the active growth period [62]. Several PCBER have been identified by screening for plant genes that are induced by fungal elicitors or during defensive responses and increased protection against oxidative stress has been suggested [63,64], but involvement in plant growth regulation has likewise been suggested for the coumaran lignans produced by this enzyme [65]. In our case, we can hypothesize that inducing cell wall synthesis proteins helped to maintain membrane integrity, which corroborates the electrolyte leakage results. The predicted enzyme, the succinate dehydrogenase flavoprotein (628, 646), was more abundant in treated Sa while stable in Sf. The succinate dehydrogenase complex (SDH) is a succinate:ubiquinone oxidoreductase integrated in the inner membrane of the mitochondria and the flavoprotein subunit is one of the four subunits. This protein forms the complex II of the electron transport chain and is also a functional component of the Krebs cycle [66,67]. SDH also catalyzes the conversion of succinate in gluconeogenesis [67]. The increased accumulation of succinate dehydrogenase in Sa in the presence of metals might help to maintain mitochondrial succinate-dependent respiration that is known to be inhibited by metals [68]. On the other hand, it might also indicate increased respiration, as was previously reported for poplar exposed to Cd [58]. While the above-discussed proteins changed in the same direction in both clones, two groups of proteins have a completely different abundance pattern in Sa and Sf when exposed to metallic stress; these are the proteolysis proteins and those involved in antioxidant responses. Three spots containing predicted ATP-dependent zinc metalloproteases (filamentation temperature sensitive H, FTSH) (612, 613, 604) were less abundant in metal-treated Sa whereas the opposite was observed in Sf although not significant. ATP-dependent protease FTSH contains both intrinsic chaperone and proteolytic activities [69,70]. The specific identification of FTSH protease in this study in three spots with coherent fold changes makes it an interesting enzyme for further study. For the moment the exact physiological function is unknown, it is known to be involved in the degradation of photosystem subunits, for the D1 protein this involvement is confirmed both in vitro and in vivo [71]. Furthermore, the in vitro degradation of light harvesting complexes by FTSH has been observed but in vivo confirmation is currently lacking [72]. In the current study, no proof of changes in the degradation of photosynthesis-related proteins was found. The fact that FTSH is linked to the degradation of oxidatively inhibited photosystem proteins and that this protein is less abundant in treated Sa is interesting when looking at the changes in proteins involved in the antioxidant system. Indeed, antioxidant proteins are likewise less abundant in Sa in the presence of metals (1542, 1546, 1568, 1637). This is an observation contrary to what is expected for metal-exposed plants [58,73,74]. Glutathione-S-transferases (GST) (1542, 1546) are ubiquitous and multifunctional proteins involved in the detoxification of lipophilic compounds.

Dehydroascorbate reductase, part of the Halliwell–Asada pathway (DHAR) (1568) is also known to play an important role in protecting plant cells from oxidative damage [61,75–77]. 2-Cys peroxiredoxins (1637) is a family of antioxidative peroxidases where the two cysteine residues are involved in the reduction of peroxides [78,79]. Grouping all the data results in a picture of two different willow-clones, producing the same biomass when exposed to excess metals, but which have different strategies for coping with the imposed stress. In both clones, proteins involved in photosynthesis and photosystem efficiency decrease. On the contrary with the Sf clone, this decrease is accompanied by increased cellular damage in the Sa clone, as illustrated by the increased electrolyte leakage (Fig. 2B), and functions that could counteract this damage or eliminate damaged molecules appear to decrease. The antioxidant system in Sa decreases while in Sf enzymes linked with protection against oxidants (Table 3) are increased or maintained. The mechanisms that account for these observations are not known but it can be hypothesized that differential sugar accumulation may be an important signaling event leading to the observed proteome level changes. The accumulation of soluble sugars in source leaves, caused by a general down regulation of metabolism or important changes in sugar allocation to the different plant parts, is known not only to have an allosteric effect on the activity of proteins but also to influence gene expression [49,80]. One of the pathways regulated by the repression of its genes by high sugar concentrations is photosynthesis; by lowering the activity of this pathway further generation of reactive oxygen is limited. A sugar-induced decrease in photosynthesis might be the mechanism by which the Sa clone limits the generation of ROS, and settles a new homeostasis without necessitating a significant reduction in growth, be it at the expense of an increase in cellular damage. In the Sf clone no accumulation of sugars is observed, the efficiency of photosynthesis is likewise decreased but as seen in the Fv/Fm data (Fig. 2A) not to the same degree as in Sa. However, contrary to the Sa clone, the Sf clone has to increase the abundance of proteins with antioxidant activities or at least keeps them on the same level as in control plants and this at the price of a significant reduction in biomass production (Fig. 1).

5. Conclusion The S. fragilis and S. aurita clones used produce about the same biomass but accumulate different amounts of metals when grown on a polluted substrate. In order to identify the mechanisms resulting in this difference the physiological and proteome-level changes of these clones growing on polluted and control substrate were compared. We measured a decrease in the Fv/Fm ratio and a decreased concentration for most of the major pigments. In both clones, the majority of the proteome-level changes are similar in direction but change from significant to non-significant depending on the clone. However, some of the measured parameters strongly differ. In particular, growth on a polluted substrate does not result in a significant difference in biomass production for the Sa clone whereas the growth of Sf is significantly lower on a

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polluted substrate. Furthermore, the Sa clone, but not the Sf, has several characteristics that are commonly linked with exposure to stress such as increased accumulation of sugars and increased cellular damage. Together with the proteome-level data, this indicates that the Sa clone can maintain its biomass production but endures increased damage due to metal exposure. On the contrary, the Sf clone induces or at least maintains mechanisms that aid in the protection of the cell from metal-induced damage. As a result, the accumulation of sugars in Sf only increases slightly, the electrolyte leakage does not change indicating the maintenance of cellular integrity but this coinciding with a significant growth reduction. Which of these strategies is preferable is not clear after the 100 day experimental period of the current trial. We can draw the conclusion that higher biomass production in the presence of metals does not necessarily mean higher tolerance whereas growth reduction might indicate long-term tolerance. Only a long-term monitoring study can provide answers on the preferability of either strategy. Supplementary data to this article can be found online at http://dx.doi.org/10.1016/j.jprot.2014.02.007.

Conflict of interest The authors declare no financial/commercial conflicts of interest.

Acknowledgments The authors gratefully acknowledge financial support from the project Ecolirimed, co-financed by the Fonds Européen de Développement Régional as part of the program Interreg IV A ‘Grande Région’. This study was also supported by the National Research Fund, Luxembourg as part of the project ENERREMCORE call 2008. We thank the Unité de Génie biologique of the Centre wallon de Recherches agronomiques (Belgium) for supplying the willow plants. We acknowledge Dr Lucien Hoffmann from the CRP — Gabriel Lippmann for their careful reading of the manuscript, Johanna Ziebel for the elemental analyses, Laurent Solinhac, Marine D'Aulisa and Myriam Pilliet for their technical help and Sebastien Planchon for his support during the proteomics experiments.

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