Article pubs.acs.org/jpr
From Tolerance to Acute Metabolic Deregulation: Contribution of Proteomics To Dig into the Molecular Response of Alder Species under a Polymetallic Exposure Bruno Printz,†,‡ Kjell Sergeant,† Stanley Lutts,‡ Cédric Guignard,† Jenny Renaut,† and Jean-Francois Hausman*,† †
Department Environment and Agro-biotechnologies, Centre de Recherche Public-Gabriel Lippmann, 41, rue du Brill, L-4422 Belvaux, GD Luxembourg ‡ Groupe de Recherche en Physiologie végétale (GRPV), Earth and Life Institute-Agronomy (ELI-A), Université catholique de Louvain, 5 (bte 7.07.13) Place Croix du Sud, 1348 Louvain-la-Neuve, Belgium S Supporting Information *
ABSTRACT: Alnus spp. are actinorhizal trees commonly found in wet habitats and able to grow effectively in soil slightly contaminated with metal trace- elements. Two clones belonging to two Alnus species, namely, A. incana and A. glutinosa, were grown in hydroponics and exposed for 9 weeks to a Cd + Ni + Zn polymetallic constraint. Although responding by a similar decrease in total biomass production, the proteomic analysis associated with the study of various biochemical parameters including carbohydrate and mineral analyses revealed that the two clones have a distinct stressresponsive behavior. All parameters indicated that the roots, the organ in direct contact with the media, are more affected than the leaves. In fact, in A. glutinosa the response was almost completely confined to the roots, whereas many proteins change significantly in the roots and in the leaves of the treated A. incana. In both clones, the changes affected a broad range of metabolic processes such as redox regulation and energy metabolism and induced the production of pathogenesis-related proteins. In particular, changes in the accumulation of bacterial proteins that were not identified as coming from the known symbionts of Alnus were reported. Further investigation should be performed to identify their origin and exact role in the plant response to the polymetallic exposure tested here. KEYWORDS: proteomics, Alnus, trace element, phytoremediation, plant abiotic stress, cadmium
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INTRODUCTION One of the heritages of the industrial development that began in the late 18th century is that the current European landscape is densely speckled with spots of small geographic sites that are chronically contaminated. Among the other compounds also responsible for this contamination, metal trace elements are major contaminants causing local soil toxicity.1 Physical and chemical methods of decontamination are considered to be too costly, restricted to small areas, and damaging for soil biological activity and fertility. In 1994, Baker et al. proposed phytoremediation, the cleanup of soils using plant species, as a method for green remediation of marginally polluted soils.2 Although interesting objects of study on the mechanics of metal accumulation, metal hyperaccumulators, defined as plant able to accumulate potential phytotoxic elements in the above-ground organs at concentrations exceeding 100-times those found in related nonaccumulating plants, may have limited practical application due to the existence of a trade-off between biomass production and hyperaccumulation.3,4 Besides, the discovery of metal-tolerant plants enhanced the development of phytostabi© 2013 American Chemical Society
lization techniques, in which plants are used to lower the mobility of the metals and prevent leaching into the groundwater. Although trees do not easily adapt to soils highly contaminated with heavy metal, nonetheless they may develop better capacities to withstand such constraints than agricultural crops.3 In an experiment comparing different tree species for their use as phytoremediative agents, Mertens et al. concluded that it is doubtful that trees have a potential for phytoextraction. However, the same authors concluded that some ligneous species, such as ash, alder, maple, and Robinia, have potential use in phytostabilization techniques aiming at the fixation of heavy metals in the soil.5 Perennial species from the genus Alnus (Mill.) are commonly found in wet habitats and have been widely used to Special Issue: Agricultural and Environmental Proteomics Received: June 21, 2013 Published: September 10, 2013 5160
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mechanically stabilize riverbanks.6 In this case, the tree root system forms an intimate network, making alder a good candidate to combine the sequestration of the metal within the soil with their primary role of riverbank stabilizer. Efforts have been carried out to highlight the potential of this genus in phytoremediation processes, and depending on the tree species, major variations in heavy metal uptake are observed.7 Trees from the genus Alnus fix atmospheric N2 by the means of symbiotic bacteria from the genus Frankia hosted in the roots. This symbiosis provides among others a selective benefit in adverse conditions of nutrient balance, which often gives this genus a status of pioneer plant. In particular, Alnus species have been reported to effectively grow on slightly heavy-metalpolluted dredged sediment,5 whereas Lefrançois et al. reported that the combination alder-Frankia is likely to enhance the remediation capabilities and the quality of the soil on inhospitable oil sand sites.8 Usually trees from the same population do not respond equally to the same constraint, and a high variability in metal tolerance is generally observed.3 Although it is unclear whether this degree of variability is a direct consequence of the genetic composition of the population, the differential response reflects nonetheless the variability in the cellular processes set by the plant to face constraints. Studies on tree species revealed that heavy metal contamination is likely to affect the whole set of metabolic pathways (primary and secondary metabolism,9−11 metal homeostasis,12,13 protein pattern,11,14 or transcript expression15). Trees, and more generally plants, employ a set of mechanisms helping them to face environmental constraints, and these mechanisms can be either specific for a certain type of constraint or part of a general stress-response program. Apart from the oxidative damage commonly caused by abiotic stresses, metallic constraints are known to affect a broad spectrum of cellular processes. In an extensive review dealing with the contribution of proteomics to understand plant responses to trace elements, Ahsan et al.16 pointed out that heavy metals lead to a global disruption of almost all cellular mechanisms. Among them, many reports quote a differential accumulation of proteins involved in the regulation of the cellular redox state such as superoxide dismutases, ascorbate peroxidases or other members of the ascorbate and/or the glutathione cycle. In addition, trace elements usually affect the production of pathogenesis-related proteins, the synthesis of chaperones, impact the synthesis, and consumptions of energy, affect the carbon cycle and interact with the synthesis of signaling molecules.11,16 Proteins involved in electron transport (either in mitochondria or in chloroplasts) and in the photooxidation of water as well as proteins directly associated with ATP synthesis are commonly found differentially expressed in plants affected by a metallic constraint.17 The latter being in close relation with carbohydrate synthesis and catabolism, it is not surprising that trace elemental exposure affects the allocation of carbohydrates between sink and source tissues.18 While most studies on metallic stresses are turned toward monometallic constraints, the occurrence of polymetallic constraints is the general rule in anthropogenically polluted sites. As the uptake of one mineral could be largely affected by the presence of other elements,19 the use of a polymetallic treatment appears to be more realistic than testing a single element alone. In this study, the aim is to compare the responses of two clones from two different species within the
Alnus genus, namely, A. glutinosa and A. incana, exposed to a same polymetallic constraint induced by the excess of three elements: zinc, nickel, and cadmium. The focus of the discussion is on the different molecular mechanisms setup by the two clones in both leaves and roots to face the polymetallic constraint.
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MATERIALS AND METHODS
Experimental Setup
Hydroponic experiments were conducted on 3 year-old nodulated saplings, vegetatively propagated from mature trees and generously provided by the CRA-W (Gembloux, Belgique). One clone of A. glutinosa L. (named W256) and one clone of A. incana L. (named W247), originating from riparian populations, were cultivated in 1/4 strength Hoagland solution (control) or in 1/4 strength Hoagland solution with additional 10 μM Cd, 20 μM Ni, and 200 μM Zn (treatment).20 The pH of the nutritive solution was adjusted to 5.8 with 1 M NaOH. By clone, saplings were cultivated in two sets (control and treatment) of six saplings grown 2 by 2 in 4 L of hydroponic solution. Media were continuously aerated and renewed every third week during the experiment, and the solution level was checked and adjusted every day during the 9 week experimental period. Physiological Parameters
Sapling height was measured at day 0 and then every week from the second week of growth, and total biomass production was measured at sampling after 9 weeks of growth. The diameters of the main stem and of the second lignified branch starting from the apex were weekly estimated with a calliper right from the second week of growth. Plant Mineral Content
For each of the six saplings per clone and condition, fine roots, lignified roots, lignified stem (3-year old), newly formed stems, and leaves were sampled after 9 weeks of growth and ovendried at 105 °C for 2 days. About 250 mg of dried sample was subsequently mineralized using a Multiwave 3000 microwave digester (Anton Paar GmbH, Austria) in 7 mL of nitric acid (67−69%) and 3 mL of hydrogen peroxide (30%) according to the manufacturer’s instructions. After mineralization, the volumes were adjusted to 25 mL with ultrapure water (Millipore), and the metal content of each organ was determined by inductively coupled plasma−mass spectrometry (ICP-MS), using an Elan DRC-e (PerkinElmer, Waltham, MA).21 The elements taken into consideration were Ca, Cd, Cu, Fe, K, Mg, Mn, Mo, Ni, Na, and Zn. Carbohydrate and Proteomics Sampling
Carbohydrate and proteomics analyses were carried out on young leaves and roots developed during the period of treatment and sampled after 9 weeks of hydroponic growth. One leaf sample consisted of a pool of 4 or 5 fully expanded leaves from the last developed twigs, and one root sample consisted of nonlignified fine roots. Leaves and roots were sampled and washed with deionized water. Droplets on the surface were then dried, and the plant material was frozen in liquid nitrogen and stored at −80 °C prior to analysis. After grinding, the sampled material was divided into samples for carbohydrate and proteome analysis. 5161
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Carbohydrate Analysis
samples, whereas Cy3 and Cy5 were used to label the different samples, applying a dye swap to avoid biasing of the results due to differential labeling. The labeling was carried out according to the manufacturer’s instructions. Labeled samples were pooled by 3 such that each pool contained an equal ratio of proteins marked with Cy2, Cy3, and Cy5, and lysis buffer was added to reach a final volume of 120 μL. Finally, 0.72 μL of Destreak Reagent (GE-Healthcare, Sweden) and 2% (v/v) Biolyte (pH 3−10) (Bio-Rad, USA) were added. For each clone and tissue, 1 additional charged gel with a total protein load of 300 μg was run and dedicated to picking. The samples used for running the charged gels consisted of 270 μg of unlabeled protein and 30 μg of proteins labeled with one of the CyDyes. The inclusion of labeled protein in the charged gels allowed the matching of the charged gels with the gel images used for the differential expression analysis. Lysis buffer was added to attain a final volume of 450 μL. Finally, 2.7 μL of Destreak Reagent and 2% (v/v) Biolytes was added. Protein Migration. The migration on the first dimension (isoelectric focusing) was carried out using ReadyStrip IPG (Bio-Rad, pH 3−10 NL, 24 cm), rehydrated overnight with 450 μL of Destreak Rehydration Solution (GE Healthcare) and 0.5% v/v ampholyte. Proteins were uploaded, and IEF was carried out on an Ettan IPG-phor IEF unit (GE Healthcare) with the following parameters: (1) 150 V for 4 h, 2) gradient to 1000 V for 4 h, (3) 1000 V for 5 h, (4) gradient to 10000 V in 5 h, and (5) constant voltage of 10000 V for 7 h. The temperature was set at 20 °C, and the current was limited to 0.75 μA/strip. After the first dimension, strips were equilibrated in equilibration buffer (The Gelcompany, Tübingen, Germany) complemented with 6 M urea and 1% w/v DTT for 15 min and subsequently 15 min in equilibration buffer complemented with 6 M urea and 2.5% w/v iodoacetamide. Strips were rinsed in a cathode buffer (Buffer Kit 2Dgel DALT twelve, The Gelcompany), placed on top of the second dimension gels (Precast 2DGel DALT NF 12.5%, 1 mm, 255 mm × 195 mm, The Gelcompany), and sealed with 5 mL of agarose from the kit. Cathode and anode buffers were added in the electrophoresis tank (Ettan DALT twelve, GE Healthcare), and the gels were run at 20 °C. The migration settings were (1) 0.5 W/strip for 2 h, (2) 2.5 W/strip for 14 h. After SDS-PAGE the proteins were fixed in 15% (v/v) ethanol containing 1% (w/v) citric acid for a minimum of 2 h and rinsed in MQ prior to scanning. A similar procedure was used for the charged samples dedicated for picking with slight modification; samples were directly added during the rehydration step of the strip (passive rehydration), and the second dimension was done using an Ettan DALT six (GE Healthcare). Gel Scanning and Analyses. Gels were scanned using a Typhoon Variable Mode Imager 9400 (GE Healthcare) at a resolution of 100 μm according to the instructions provided for each dye. The gel images were analyzed using the software Decyder 2D v7.0 (GE Healthcare). Leaf protein analysis was performed on 4 replicates; for the root protein analyses the quality of 1 gel did not allow a reliable matching with the other gel images, and this one was consequently discarded from the analyses. Spot comparisons between treated and control saplings were carried out by calculating the ratio r between the average intensity in treated vs control conditions. When the average intensity of a spot
Carbohydrate analyses were carried out on 5 or 6 replicates. Soluble sugars were extracted and analyzed using HPEAC-PAD as described by Printz et al.22 with slight modifications. Briefly, about 100 mg of fresh material (leaf or root) were ground in liquid nitrogen with a precooled mortar and extracted with 1 mL of ethanol/water (80/20 v/v). Samples were mixed at 1400 rpm (4 °C, 10 min) in an Eppendorff Thermomixer and centrifuged at 17000g (4 °C, 10 min). The supernatant was collected, and the pellet was used for a second extraction with 0.5 mL of ethanol/water (80/20 v/v). Both supernatants were pooled before drying under vacuum using a SpeedVac concentrator (Heto, Thermo Electron Corporation, Waltham, MA). The dried extract was dissolved in 1 mL of MQ water, filtered through a 0.45 μm Acrodisc PVDF syringe filter, and analyzed with HPEAC-PAD (Dionex ICS2500-BioLC, Sunnyvale, CA). The column used was a Dionex CarboPac PA20 (3 mm i.d. × 150 mm) kept at 35 °C. Analyses were carried out as described by Guignard et al.23 In brief, the mobile phase was online generated KOH at a flow rate of 0.5 mL min−1 with the following concentrations: 9.5 mM during 25 min, 9.5−100 mM in 1 min, 100 mM during 10 min, 100−9.5 mM in 4 min, and a final step of column equilibration at 9.5 mM during 5 min. Carbohydrates were quantified using nine-point calibration curves with custom-made external standard solutions containing the simple sugars most commonly found in plant tissues, ranging from 1 to 100 μmol L−1. A check standard solution was used to validate the calibration of the system every 10 injections. Proteomic Analysis
Proteomic analyses were carried out on each clone, on both roots and leaves. By clone and by condition, four biological replicates were randomly selected, and 200−300 mg FW was used for protein extraction. Foliar proteins were solubilized by adding 1.2 mL of lysis buffer (7 M urea, 2 M thiourea, 2% w/v CHAPS) to the ground sample, and this mixture was subsequently shaken at 1400 rpm in an Eppendorf Thermomixer (60 min, 19 °C). The resulting suspension was centrifuged at 5000g (10 min, 19 °C). The supernatant was collected, adjusted to 10 mL with ice-cold 20% (w/v) TCA in acetone containing 0.1% (w/v) DTT, and kept overnight at −20 °C. For the root samples the protein ground material were directly precipitated with precooled 20% (w/v) TCA in acetone containing 0.1% (w/v) DTT. After precipitation, the samples were centrifuged at 30000g (4 °C, 45 min), the supernatants was discarded, and the pellets were washed in 10 mL of ice-cold acetone and centrifuged again at 30000g (4 °C, 45 min). The washing protocol was repeated 2 more times. The resulting pellets were vacuum-dried (Speedvac) at room temperature (20 min). Proteins were solubilized for 30 min at room temperature in 100 μL of labeling buffer (7 M urea, 2 M thiourea, 2% w/v CHAPS, 30 mM Tris), followed by a centrifugation at 16000g (15 min, room temperature). The resulting supernatant was collected. Prior to quantification, the pH of the protein extract was adjusted to 8.5−9. The concentrations of proteins were determined by using the 2D Quant Kit (GE Healthcare, Little Chalfont, U.K.) with BSA as standard. Protein Labeling for DIGE Analysis. Proteins, 30 μg for each sample, were labeled with the CyDyes minimal labeling method (GE Healthcare). Cy2 was used for the internal standard, composed of a balanced amount of each of the 5162
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products of this residue (Trp; Trp +4 Da = kynurenin, Trp +16 Da = oxidized Trp; Trp +32 Da = N-formylkynurenin). This likewise resulted in the delineation of several signal and transit peptides and the discovery of different molecular forms of the same protein in some of the spots. MS/MS spectra resulting in a score around the MASCOT threshold (p < 0.05) of 40 were validated by using the following criteria: high intensity peaks should be matched and well-known sequence-dependent characteristics should be present. These easy-to-recognize spectral features include the presence of a peak corresponding to the C-terminal arginine and the presence of the neutral loss of 64 Da from peptides containing oxidized methionine. Furthermore, the impact that specific residues (most notably proline and aspartic acid) have on the intensity of fragment peaks must be respected.25−27 In case high quality spectra did not result in significant identification, manual de novo sequence analysis was applied and/or extra peaks were fragmented to confirm near-to-threshold identifications (peptide score added in red in Supplementary Table 3).28 Gene Ontology (GO) Annotation. GO classification was carried out to identify the main biological processes putatively affected by the treatment. GO annotation were obtained by using the web-based tools GOanna and GOSlimViewer available at the Agbase database http://agbase.msstate.edu/ cgi-bin/tools/index.cgi. Proteins were uploaded as FASTA format sequences.
measured in the treated sapling exceeded the one measured in the control sapling, we reported a protein fold-change equal to the ratio r. In the case where the spot intensity was lower than the one measured in the control plants (when r < 1), we reported a fold-change equal to −1/r. Only absolute fold changes superior to 1.5 (Student’s t test, p-value ≤0.05) were considered as significantly different between the 2 conditions (statistical values of these spots given in Supplementary Table 1). Spots that were differentially expressed were matched onto the gel loaded with 300 μg of protein and picked from the latter. To assess the reproducibility of the protein migration, the similarities between the gel images were calculated by clone and by tissue. In brief, by clone and by tissue we carried out a 1 by 1 comparison of the spotmaps obtained with the internal standard (Cy2) by calculating the Pearson product-moment correlation coefficient between the gel images based on the normalized volumes of the spots that were matched (Supplementary Table 2). Picking, digestion, and MALDI spotting was carried out using the Ettan Spot Handling Workstation (GE Healthcare). Each sample was washed initially in a 50 mM ammonium bicarbonate solution containing 50% (v/v) methanol and dehydrated using a 75% (v/v) ACN solution. Proteins were then digested in 8 μL of trypsin Gold (Promega), 5 ng/mL trypsin in 20 mM ammonium bicarbonate. After extraction with 50% (v/v) ACN containing 0.1% (v/v) TFA, the peptides were dried and spotted on MALDI-TOF target plates. A volume of 0.7 μL of 7 mg/mL α-cyano-4-hydroxycinnamic acid in 50% (v/v) ACN containing 0.1% (v/v) TFA was added. A MALDI peptide mass spectrum was acquired using the Applied Biosystems 5800 TOF/TOF (Applied Biosystems, Foster City, CA), and the 10 most abundant peaks, excluding known contaminants, were selected and fragmented. All spectra, MS and MS/MS, were submitted for databasedependent identification using the NCBInr database with the taxonomies viridiplantae and bacteria (http://www.ncbi.nlm. nih.gov) downloaded on September 26, 2011 (15,334,873 sequences) on an in-house MASCOT server (Matrix Science, www.matrixscience.com, London, U.K.). A secondary search was always carried out against an EST eudicots database downloaded from the NCBI server on October 4, 2010 (12.643.198 sequences).The parameters used for these searches were mass tolerance MS 100 ppm, mass tolerance MS/MS 0.75 Da, fixed modifications cysteine carbamidomethylation, and variable modifications methionine oxidation, double oxidation of tryptophan, tryptophan to kynurenine. Proteins were considered as identified when at least two peptides passed the MASCOT-calculated 0.05 threshold score of 40. However when a high-scoring peptide (>2 times the 0.05 threshold) was matched and a protein p-value of new stems > 3-year stems, whereas the accumulation of Cd decreases in the series fine roots > lignified roots ≫ new stems > 3-year stems > leaves (Table 1). Similarities between Cd and Zn in their atomic properties make Zn a potential competitor of Cd uptake,19,38 but antagonism appears to be species-dependent and may be reverted in the case of high Zn or Cd imbalances.39−41 In our study, the concentrations of Zn in the treated culture medium are 20 times higher than that of Cd, but nonetheless the mean Zn content (expressed in molar by g DW) in the fine roots did not reach more than 10.1−11.5 times that of Cd, suggesting that in the treatment condition, Cd2+ uptake by the roots is preferential to Zn2+ absorption (Table 2). Interestingly, the Zn/ Cd ratio varies along the saplings to finally reach values of 186− 202 in leaves. This variability in the distribution of Zn and Cd within the different plant parts suggests that although having a high chemical identity plants have evolved to the production of low to highly specific carriers/transporters/channels, allowing them to differentiate these two highly analogous ions. Although the most obvious changes were observed for the three added elements Cd, Ni and Zn, the data presented in Table 3 indicate that the polymetallic exposure influences the tissular content of other minerals. In A. incana, the ionic homeostasis appears extensively affected in the fine roots as 8 out of the 11 elements measured changed significantly in treated vs control plants. In contrast, only 6 of the 11 elements tested in the study were significantly affected by the treatment in the fine roots of A.glutinosa. In total, among the 5 organs analyzed here, 31 elements × tissue changed significantly in A. glutinosa in response to the treatment, whereas only 24 are significantly affected in the A.incana saplings.
Table 2. Mean Zn/Cd Ratio with Standard Deviation by Clone and by Tissue Measured in Treated Plantsa Zn/Cd ratio - treated plants specie
clone
A. glutinosa
W256
A. incana
W247
tissue leaves new stems 3-year stems lignified roots fine roots leaves green stems old stems old roots fine roots
mean a
202.4 31.8b 19.8c 18.5c 10.1d 186.5a 33.8b 19.7 c 16.8 d 11.5 e
SD
n
85.1 4.6 2.2 1.8 1.7 28.9 11.3 2.3 1.4 1.7
6 6 6 6 6 6 6 6 6 6
a
Ratio was obtained with Zn and Cd concentration expressed in molarity by g DW. Multiple comparisons of means were carried out following a Kruskal−Wallis test. Each letter indicates a group whose values are significantly different from the others (p < 0.05). “n” represents sample size. Calculations were carried out by clone separately.
Despite the imperative role of Mo as cofactor in the nitrogenase activity located in root nodules, here Mo was found to be mainly present in the new stems where it reaches 6.8 times (A. glutinosa) and 5.1 times (A. incana) the contents measured in the young roots of control saplings and 14.6 times (A. glutinosa) and 7.1 times (A. incana) the content measured in the fine roots of treated ones. Metal Trace Elements Affect Sapling Growth
The saplings growth was evaluated in control and treated conditions using the total biomass produced after 2 months of cultivation, a weekly evaluation of the total height of the trees, and by measurement of the diameter of the base of the main stem and of the second lignified branch down from the apex. The capacity of the two clones to grow in hydroponics was compared in control conditions using absolute growth and linear regression models (Supplementary Figure 1). The regression slope values measured for A. incana and A. glutinosa differ neither for the growth in height nor for the growth of the second lignified twig down from apex. Nonetheless, in control condition, the growth of the main stem appears significantly higher for A. incana than for A. glutinosa. 5165
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Table 3. Ratio of the Mineral Content after 9 Weeks of Growth by Clone and by Organa
a This ratio corresponds to the concentration (expressed in g kg−1 dry weight) of each metal measured in each plant part of the treated plants divided by the concentration (expressed in g kg−1 dry weight) of the same element measured in control plant parts. Dark grey boxes indicate significant differences between treatment and control (Welch t test, p-value
