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Environmental and Experimental Botany 67 (2009) 335–344

Contents lists available at ScienceDirect

Environmental and Experimental Botany

journa l homepage: www.e lsev ier .com/ locate /envexpbot

ene expression analysis of Populus deltoides roots subjected to copper stress

ernando Guerraa,b,c,∗, Sébastien Duplessisd, Annegret Kohlerd, Francis Martind,aime Tapiae, Pablo Lebeda, Francisco Zamudio f, Enrique Gonzáleza

Instituto de Biología Vegetal y Biotecnología, Universidad de Talca, 2 Norte 685, Talca, ChileCentro de Investigación en Biotecnología Silvoagrícola, 2 Norte 685, Talca, ChileDepartamento de Ciencias Forestales, Universidad Católica del Maule, Avenida San Miguel 3605, Talca, ChileUMR 1136 INRA/UHP-Nancy 1 Interactions Arbres/Microorganismes, Centre INRA de Nancy, F-54280 Champenoux, FranceInstituto de Química de Recursos Naturales, Universidad de Talca, 2 Norte 685, Talca, ChileCentro Tecnológico del Alamo, Universidad de Talca, 2 Norte 685, Talca, Chile

r t i c l e i n f o

rticle history:eceived 31 December 2008eceived in revised form 18 August 2009ccepted 20 August 2009

eywords:

a b s t r a c t

An analysis of the Populus root transcriptome was carried out in order to improve our understanding ofmolecular mechanisms underlying the response of trees to copper (Cu) stress. In a first stage, cuttingsof nine Populus species were grown hydroponically and screened for differential phenotypical responseto Cu. In a second stage, plants of the most Cu tolerant clone (Populus deltoides) were exposed to 30 and60 �M CuSO4 for 12 and 24 h. RNA isolated from root tissues was analyzed with 4.6 k cDNA arrays in order

opulusopperootsene expressionDNA arrayshytoremediation

to determine alterations in transcription. Copper exposures increased significantly Cu concentration inroots. A series of transcripts differentially accumulated in a general or a specific way under the differentstress conditions. Most of the transcripts encode proteins related to defense against biotic stress, antiox-idant mechanisms, metal homeostasis, and water flux control. Expression of several transcripts involvedin signaling, such as MAP kinases, calcium and ethylene-related enzymes were also altered under Cuexposure. Our results suggest the Cu accumulation in roots and a general defensive response against

oxidative stress.

. Introduction

Copper is among the major heavy metal contaminants in thenvironment (Xiong and Wang, 2005). Mining, smelting, agricul-ure and other human activities have widespread this metal in soilsBlaylock and Huang, 2000). Interest for developing plants usefulor phytoremediation has increased the understanding of the bio-ogical basis underlying metal tolerance and accumulation process.ome important morphological, physiological and genetic aspectsf Cu tolerance in tree species have been studied (Borghi et al.,007; Keinänen et al., 2007). However, information about molec-lar genetic mechanisms involved in the response of trees to Cutress is scarce.

Copper is required for normal growth of plants. It is an essen-

ial redox component participating in a wide variety of processes,ncluding the electron transfer reactions of respiration and pho-osynthesis or the detoxification of superoxide radicals (Fox anduerinot, 1998). However, intracellular free Cu ions in excess can

∗ Corresponding author. Current address: Departamento de Ciencias Forestales,niversidad Católica del Maule, Avenida San Miguel 3605, P.O. Box 617, Talca, Chile.el.: +56 71 203567; fax: +56 71 203524.

E-mail address: fguerra@ucm.cl (F. Guerra).

098-8472/$ – see front matter © 2009 Elsevier B.V. All rights reserved.oi:10.1016/j.envexpbot.2009.08.004

© 2009 Elsevier B.V. All rights reserved.

produce radical hydroxyls by autoxidation and Fenton reaction(Gupta et al., 1999; Schützendübel and Polle, 2002). Successively,radical hydroxyls react to cause membrane lipid peroxidation,cleavage of the sugar phosphate backbone of nucleic acids, andprotein denaturation. In addition, Cu can displace other divalentcations coordinated with macromolecules, causing their inactiva-tion or malfunction (Murphy et al., 1999).

Plants dispose of several defense mechanisms for coping withheavy metal toxicity. They operate at different levels and theway in which they are regulated determinate the ability of plantsto restrict the metal uptake and/or root to shoot transport, andtheir sequestration and compartmentalization in organelles and/ororgans (Clemens et al., 2002). In excess Cu, some species such asTriticum aestivum reduce the uptake of toxic free metal ions releas-ing malate and citrate from roots, which act as metal chelators(Nian et al., 2002). At the cellular level, cell walls can bind metalions regulating their influx toward cytoplasm by cationic exchange(Wang and Evangelou, 1995). Copper can be bound to pectine(Konno et al., 2005) or proteins as oxalate oxidase (Bringezu et al.,

1999). Additionally, different transmembrane metal-transportingproteins allow sub-cellular compartmentalization or efflux towardthe apoplast (Williams and Mills, 2005). Cu transporters identi-fied in Arabidopsis include the family COPT 1-5 (Sancenón et al.,2003) and members HMA5-8 of P1B-ATPases family (Williams and

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36 F. Guerra et al. / Environmental and

ills, 2005). Intracellular distribution of Cu is performed by chap-rones directing the metal to its final destination. Cu chaperonesan act coordinately with Cu-ATPases in detoxification Cu in rootsAndres-Colas et al., 2006). Some Cu chaperones characterized inrabidopsis are AtCCH (Mira et al., 2001) and AtCOX17 (Balandinnd Castresana, 2002) and PoCCH in the poplar hybrid Populuslba × P. tremula var. glandulosa (Lee et al., 2005). On the otherand, excess of free metallic ions in cytoplasm can be diminished byhelators such as phytochelatins (PCs) and metallothioneins (MTs)reviewed for Cobbett and Goldsbrough, 2002). A further defen-ive line against Cu effects is a series of antioxidant mechanismsgainst reactive oxygen species (ROS) produced by excess of metalons. These includes enzymes (peroxidases, catalases, superoxideismutases, peroxiredoxins or glutathione S-transferases), as wells reducing metabolites (ascorbate, glutathione or tocopherols)Foyer and Noctor, 2005). The behavior of different componentsf the defense system in response to Cu-induced stress have beeneported for some plant species. However, evidences about Cuffects in Populus species from a molecular genetic perspective arecarce.

Populus genus has been proposed as a model for studying theiology of trees (Bradshaw et al., 2000). Multiple informationesources and tools are already available for studying differentraits from a genomic approach (Strauss and Martin, 2004), includ-ng the genome sequence of Populus trichocarpa (Tuskan et al.,006). In that sense, in this study we assessed the root transcrip-ome of a Cu tolerant Populus deltoides clone utilizing cDNA arrays,n order to have a global insight about the molecular mechanismsnderlying the Cu detoxification and accumulation in poplar. Rootsre usually the organ in direct contact with Cu sources and there-ore, they are the first defensive barrier and the sensor for signalransduction pathways in whole plant. The analysis of differentialene expression in plants exposed to 30 and 60 �M of Cu for 12 and4, using 4.6 k cDNA macroarrays, allowed us to identify a set ofenes involved in the response to Cu exposure. In order to validatehe cDNA array results, Northern hybridizations were done. Theossible role of identified genes in Cu homeostasis and tolerance islso discussed.

. Materials and methods

.1. Screening for Cu tolerance in Populus genotypes

Cuttings of nine Populus genotypes: P. deltoides, P. tri-hocarpa × maximowiczii, (P. trichocarpa × deltoides) × P.eltoides, (P. trichocarpa × deltoides) × P. trichocarpa, (P.richocarpa × maximowiczii) × P. maximowiczii, (P. tri-hocarpa × deltoides) × (P. trichocarpa × deltoides), two P.richocarpa × trichocarpa and (P. trichocarpa × deltoides) × (P.richocarpa × nigra), coming from the germplasm bank of theentro Tecnológico del Álamo (Talca, Chile), were rooted andrown in a hydroponic culture for 4 weeks. A commercial solutionVilmorin-Oxadis, France) was used as nutrient medium, whichad a composition of: 2.3 mM NO3, 7.2 mM NH4, 1.4 mM P2O5,.7 mM K2O, 0.1 mM CaO, 0.1 mM MgO, 0.2 mM SO3, 6.0 �M B,.2 �M Cu, 1.9 �M Fe (Fe-EDTA chelate), 1 �M Mn, 0.1 �M Mo and.4 �M Zn. Solution was constantly aerated by aquarium pumps,enewed every 3 days, and pH was fixed to 5 with KOH. Plants wererown in a room at 16 h photoperiod (photosynthetically activeadiation: 64 �mol m−2 s−1) and 20 ± 3 ◦C (not controlled). After

weeks, nutrient solution was supplemented with 0 (control),00 or 1000 �M of Cu applied as CuSO4 in a 0.5 g l−1 solution ofa(NO3)2 (Tilstone and Macnair, 1997). Plants were maintained inhose conditions for 48 h. According to our preliminary tests, thesetress conditions allowed to obtain a pronounced phenotypical

imental Botany 67 (2009) 335–344

effect among different Populus genotypes. The presence of damagesignals (necrosis) in aerial tissues was assessed in each plant atthe end of the assay by a binomial qualification (presence/absenceof damage). The length of the longest root (LLR), a morphologi-cal parameter associated to Cu tolerance in some plant species(Ginocchio et al., 2002), was assessed in each plant before andafter the stress treatment. Experimental design included twoplants (ramets) per genotype in each concentration and threereplicates. The statistical analysis for the qualification of damagewas performed by a cluster analysis (Ward’s minimum varianceanalysis). Analysis of LLR included ANOVA and the Tukey–Kramertest. Variance components were estimated by the method ofmoments. Analyses were performed using the GLM and CLUSTERprocedures in software SAS 8e (SAS Institute Inc., 2000).

2.2. Analysis of Cu-stress response in a Cu tolerant P. deltoidesgenotype

Plants of a Cu tolerant P. deltoides clone, selected from the Custress screening, were grown in similar conditions as describedabove. In this case, the Hoagland’s modified basal salt mixture (Phy-toTechnology Laboratories, USA) was used as a nutrient solution at1/6 strength. After 4 weeks, nutrient solution was supplementedwith 0 (control), 30 or 60 �M of Cu, as indicated in the previ-ous paragraph. Plants were exposed to the Cu stress for 12 or24 h. Lower Cu concentrations and shorter exposure times thanthe screening stage were applied to detect possible early geneticregulatory mechanisms at the transcritptome level and avoid theeffect of a generalized plant response to stress. On the other hand,a limited exposure time allows avoiding effects of aging in earlystages of metal assimilation (Cuypers et al., 2000). Experimentaldesign included four plants (ramets) in each concentration-timecombination and three replicates. After exposure, root sampleswere separated from plants, immediately frozen in liquid nitrogenand kept at −80 ◦C. Samples for Cu determination were collected atthe end of the experiment and processed as described below.

2.3. Determination of copper content in tissues

Four P. deltoides plants allocated to each treatment in the time-course experiment were collected to determine the Cu content.Roots, leaves and cuttings (a 1:1 mix of wood from cuttings andtwigs) were analyzed separately. Tissues were washed with deion-ized water and oven dried (80 ◦C) to constant weight. The driedtissues were ground into powder, then ashed at 500 ◦C and dis-solved in HCl 2 M, according to Karla (1998). Total Cu concentrationwas measured by atomic absorption spectrometry using flame. Astandard reference plant material (SRM-1570) from the NationalInstitute of Standards and Technology (USA) was used to verify theaccuracy of metal determination. Statistical analysis of Cu concen-tration was based on ANOVA and a Tukey–Kramer test, using theGLM procedure in the software SAS 8e (SAS Institute Inc., 2000).

2.4. RNA extraction

Total RNA was extracted from 100 mg of frozen roots (−80 ◦C)utilizing the RNeasy Plant Mini Kit (Qiagen, USA) according themanufacturer’s instructions. In order to improve the performanceof extraction, 20 mg ml−1 of polyethylene glycol 8000 (Sigma, USA)were added to the homogenization buffer RLC, containing guani-dine hydrochloride (Kohler et al., 2004).

2.5. cDNA macroarrays

The P. trichocarpa × P. deltoides ‘Beaupré’ macroarray, com-posed of 4600 cDNA (matching to near 2500 different genes),

Exper

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F. Guerra et al. / Environmental and

s fully described in the array platform GPL4887 (Rinaldit al., 2007) stored in the Gene Expression Omnibus (GEO)epository at NCBI (http://www.ncbi.nlm.nih.gov/geo) where theest poplar gene model (JGI Populus ProteinID) correspond-

ng to cDNA is detailed according to the P. trichocarpa genomeebportal at the Joint Genome Institute (http://genome.jgi-sf.org/Poptr1 1/Poptr1 1.home.html). For hybridization withDNA macroarrays, a series of three independent biological repli-ates were obtained from P. deltoides roots grown hydroponicallyn standard conditions (control) and roots exposed to either 30r 60 �M Cu for 12 and 24 h after stress treatment. Labelling ofeverse transcribed cDNA with [33P]-dCTP, hybridization of cDNArrays with the radiolabelled probes and image acquisition wereerformed as previously described (Gupta et al., 2005).

Because the experimental design included different levelsithin factors (Cu concentration and incubation time) and inter-

ctions, the identification of genes differentially expressed waserformed by using an approach based on linear mixed modelsWolfinger et al., 2001). Briefly, the approach considers the usef two interconnected linear models, which allow separating thexperiment-wide systematic effects (normalization model) fromffects related directly with the variation of each gene includedithin array (gene by gene model). The statistical analysis was

mplemented using the MIXED procedure of the software SAS 8eSAS Institute Inc., 2000) and expression ratios with a p-value ≤ 0.05

ere considered as significant in the study. A Venn’s diagram

nalysis was performed on the set of genes significantly up orown regulated in order to distinguish genes that are part ofhe general plant response to Cu stress from those that are spe-ific of a dose or exposition time. In the same sense, an analysis

ig. 1. Damages on aerial tissues of Populus plants exposed for 48 h to Cu stress (100 �Msensitive (P. trichocarpa × deltoides) × P. trichocarpa hybrid (panels b and d) are shown.

imental Botany 67 (2009) 335–344 337

using the wCluto profiling tools (http://cluto.ccgb.umn.edu/cgi-bin/wCluto/wCluto.cgi; Rasmussen et al., 2003) was carried out toidentify specific expression profiles. The direct clustering methodwas used on the wCluto webpage in order to derive 7 consensusclusters with the cosine similarity function. All materials and pro-cedure descriptions comply with MIAME standards set for arraydata (Brazma et al., 2001). The complete expression dataset andsamples details are available in series GSE9748 described in theGEO at NCBI.

2.6. RNA blot analyses

For RNA blot analyses, electrophoresis under denaturing condi-tions was performed with 1% agarose gel containing formaldehydewith 8 �g of RNA extracted from P. deltoides root samples (control;30 and 60 �M Cu for 12 and 24 h exposure) from a different set ofbiological replicates than the ones used for cDNA-array hybridiza-tion. Gels were blotted onto Nylon membranes as recommendedby the manufacturer (Hybond-N+; GE Healthcare, USA). RNA blotanalyses were carried out with specific P. deltoides cDNA productscorresponding to genes encoding an Al induced protein (ALIP; JGI P.trichocarpa ProteinID, 800516), a Kunitz trypsin inhibitor 3 (KTI3;JGI P. trichocarpa ProteinID, 826324), a metallothionein (MT1b; JGIP. trichocarpa ProteinID, 744962) and cationic peroxidase (PX; JGIP. trichocarpa ProteinID, 647567). The cDNA were recovered from

total RNA after reverse transcription with the ThermoScript RT-PCR System (Invitrogen, USA). Complementary DNA was used asthe template to amplify selected cDNA using specific primers (seeSupplemental Table S1). The PCR parameters used were: 94 ◦C for4 min; 94 ◦C for 1 min, 60 ◦C (annealing temperature) for 1 min, and

CuSO4). The stress effects on a tolerant Populus deltoides clone (panels a and c) and

3 Experimental Botany 67 (2009) 335–344

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Fig. 3. Copper content (�g g−1 DW) in different tissues of Populus deltoides plants

38 F. Guerra et al. / Environmental and

2 ◦C for 1 min for 30 cycles; and a final step at 72 ◦C for 7 min.he PCR products were visualized on agarose gel and isolated withhe E.Z.N.A gel extraction kit (Omega Bio-Tek Inc., USA). cDNAroducts were labeled with [32P]-dCTP using the RadPrime DNAabeling System (Invitrogen, USA) according to the manufacturer’snstructions and finally hybridized on membranes. The hybridiza-ion signal was detected utilizing the FLA-5000 imaging systemFujifilm, Japan).

. Results

.1. Screening of Populus genotypes under Cu stress

A screening test was performed to analyze the phenotypicalariation in the response to Cu stress of nine Populus genotypes anddentify those with differential tolerance. Four week plants grownn a hydroponic media were subjected to 100 or 1000 �M Cu for8 h. Analysis of the necrosis presence in aerial tissues indicatedhat P. deltoides genotype was the less damaged (Figs. 1a, c and 2).n the other hand, analysis of the length of the longest root

LLR) showed a significant effect of genotype (p-value < 0.001) buteither by dose (p-value = 0.9621) nor genotype × dose factor (p-alue = 0.8136). Near to 44 percent of total variation of LLR wasxplained by this significant effect (variance component 0.3532).o significant variation was observed in the increment of LLR asonsequence of stress treatment (data not shown). Genotypes withhe higher and the lower mean LLR were P. deltoides (18.7 ± 3.9 cm)nd (P. trichocarpa × maximowiczii) × P. maximowiczii (7.7 ± 3.0),espectively. P. deltoides was selected for the second experimen-al stage in which both the Cu distribution in the plant and the rootranscriptome were studied.

.2. Copper accumulation in tissues of the Cu tolerant genotype

We assessed the concentration of this metal in different tis-ues of the selected P. deltoides clone to study the way in whichu is distributed within stressed plants. Copper concentration was

ig. 2. Clustering of damage in aerial tissues of Populus genotypes subjectedo 100 or 1000 �M Cu for 48 h. The presence of damage signals (necrosis)t the end of experiment was assessed in each plant by a binomial qualifi-ation. A cluster analysis (Ward’s minimum variance analysis) was applied tolassify the nine genotypes. D: P. deltoides; TxM: P. trichocarpa × maximowiczii;DxD: (P. trichocarpa × deltoides) × P. deltoides; TDxT: (P. trichocarpa × deltoides) × P.richocarpa; TMxM: (P. trichocarpa × maximowiczii) × P. maximowiczii; TDxTD: (P. tri-hocarpa × deltoides) × (P. trichocarpa × deltoides); TxT: P. trichocarpa × trichocarpa;DxTN: (P. trichocarpa × deltoides) × (P. trichocarpa × nigra).

in control conditions or after 24 h exposure to two levels of copper stress (nutrientsolution plus 30 or 60 �M CuSO4). Values represent means ± standard error (n = 4).For each tissue, bars labeled with different letters were different at p-Value ≤ 0.05.

determined for roots, cuttings and leaves collected from plants pre-viously cultivated 4 weeks and later exposed for 24 h to 30 or 60 �MCu. In control plants Cu was mainly present in roots (200 �g/g DW),followed by leaves (47 �g/g DW) and cuttings (23 �g/g DW) (Fig. 3).Under the stress treatments to 30 or 60 �M Cu, levels observed bothin leaves and cuttings did not change significantly, keeping similarconcentrations to those observed at control. In contrast, concen-trations in roots increased to 5000 and 6000 �g/g DW at 30 and60 �M, respectively.

3.3. Identification of genes differentially expressed by Cu stress inroots

An approach based on the use of 4.6 k cDNA arrays was appliedto analyze the variations in mRNA expression levels observed inroots of the P. deltoides clone exposed to Cu stress. Comparisonof transcript levels in the control plants to Cu-exposed plants incombination of two Cu doses (30 and 60 �M) and two expositiontimes (12 and 24 h), allowed us to identify a set of 776 genes thatwere significantly differentially expressed (Supplemental TableS2). Among these genes, 118 (15%) were up or down regulated inall stress conditions simultaneously, as part of the general responseof roots to Cu excess, whereas the remaining ones were inducedor repressed in specific treatments or interactions (Fig. 4). A pos-itive tendency was observed between the number of up or downregulated genes and the level of stress, with the highest numberin treatment with Cu 60 �M and 24 h. Table 1 presents a list ofselected transcripts that were significantly and highly changed inone or several points of our experiment. Considering the studiedtreatments, the highest Cu-induced expression ratios (≥10-fold) atthe studied treatments were observed for some genes encodingproteins related to defense response such as the pathogenesis-related (PR) protein PR10 (JGI P. trichocarpa ProteinID 747930), theKunitz trypsin inhibitor TI3 (JGI P. trichocarpa ProteinIDs 739067

and 826324) and the osmotin-like protein osm34 precursor (JGI P.trichocarpa ProteinID 180318). We also observed genes encodingproteins associated to amino acid biosynthesis like the aluminum-induced protein Wali7 domain (JGI P. trichocarpa ProteinID 800516)

F. Guerra et al. / Environmental and Experimental Botany 67 (2009) 335–344 339

Table 1Expression ratios of selected significantly up or down regulated Cu-stress responsive transcripts from Populus deltoides measured with a 4.6 k Populus cDNA expression arrayin roots subjected to two levels of Cu stress (nutrient solution plus 30 or 60 �M Cu) compared to control conditions (only nutrient solution) after 12 and 24 h exposition tothe stress treatment. FC, fold-change; ns, non-significant.

cDNA IDa P. trichocarpa Best blast hitc Clusterd 30 �M Cu 60 �M Cu

ProteinID no.b 12 h 24 h 12 h 24 h

FCe p-Valuee FCe p-Valuee FCe p-Valuee FCe p-Valuee

Cell rescue, defense and virulenceR32A01 747930 Pathogenesis-related PR10, ribonuclease 2 17.46 <.0001 6.07 0.0012 13.78 <.0001 4.88 0.0032R11C08 826324 Kunitz trypsin inhibitor TI3 3 10.84 <.0001 19.5 <.0001 14.57 <.0001 13.34 <.0001R77E11 739067 Kunitz trypsin inhibitor TI3 2 9.35 ns 21.24 0.0219 33.26 0.0104 14.98 0.0386R08E07 769807 Basic vacuolar glucan

endo-1,3-beta-glucosidase2 7.32 0.0005 2.07 ns 5.21 0.0021 1.44 ns

R20F09 820835 Glutathione S-transferase gst 18 2 5.81 0.0003 4.28 0.0014 3.41 0.0048 3.47 0.0043RA01E01 831333 Basic chitinase 3 5.45 0.0026 10.85 0.0002 8.78 0.0004 13.65 <.0001R39A07 278770 Cytochrome P450 monooxygenase 2 4.78 0.0253 4.02 0.043 7.43 0.0063 4.02 0.0431R52E04 416437 Harpin inducing protein hin1 2 2.58 ns 2.1 ns 4.74 0.0053 3.93 0.0117R37B02 663332 Thioredoxin H 3 1.87 ns 4.03 0.006 2.38 ns 3.03 0.022RA01C07 180318 Osmotin-like protein osm34 precursor 3 1.84 ns 9.82 0.0334 17.93 0.0099 13.64 0.0173R51H02 595511 Cu/Zn-superoxide dismutase 6 −1.75 ns −3.82 0.002 −2.26 0.0368 −4.52 0.0008R52G11 719862 Major latex-like protein 6 −1.99 ns −4.61 0.0007 −3.16 0.0055 −5.79 0.0002R54C01 256724 Cytosolic ascorbate peroxidase 5 −2.62 0.0262 −1.24 ns −3.35 0.0075 1.12 nsR02F07 647567 Cationic peroxidase 6 −10.34 <.0001 −18.79 <.0001 −12.19 <.0001 −16.57 <.0001

Cellular communication/signal transduction mechanismsR55B05 667122 EF-hand Ca2+-binding protein (caltractin) 2 8.37 0.0027 3.06 ns 4.8 0.0177 8.29 0.0028R24C04 413165 Cytochrome c biogenesis protein CcmE family 2 4.85 <.0001 3.07 0.0012 3.59 0.0004 4.19 0.0001R26C08 666641 Calmodulin 3 2.7 0.0193 4.11 0.0021 2.59 0.024 3.46 0.0053R03F10 829645 RAB GTP-binding protein 6 −2.42 0.005 −3.51 0.0003 −2.76 0.0018 −5.1 <.0001R42B03 834267 WD40 G-beta protein, activated protein kinase

c receptor, rack16 −2.45 0.0001 −1.95 0.0018 −2.37 0.0002 −3.27 <.0001

R04H06 818910 GTP-binding RAB2A 5 −3.89 0.0223 −2.26 ns −5.88 0.0048 −6.63 0.003R32H06 676382 Extensin-like protein 6 −8.9 0.0023 −27.53 <.0001 −9.91 0.0016 −27.31 <.0001R14F08 831233 V-snare atvti1a 2 3.47 0.0002 2.63 0.0015 4.3 <.0001 2.66 0.0014R74G09 724520 Aquaporin PIP1 5 −3.26 0.0008 −2.71 0.0029 −4.46 <.0001 −2.89 0.0018

MetabolismR05B10 800516 Aluminum-induced protein Wali7 domain 2 21.82 <.0001 9.55 <.0001 16.91 <.0001 7.33 <.0001R67F08 575509 Glutamate dehydrogenase 2 (gdh 2) 2 8.74 <.0001 3.4 0.0027 10.33 <.0001 4.72 0.0004R21B10 832869 ATP-citrate-lyase 2 5.86 <.0001 3.84 0.0002 3.53 0.0004 2.69 0.0028R31D01 666464 Carbonate dehydratase 3 5.37 0.01 8.59 0.0019 4.66 0.0164 3.75 0.0347R01A07 829702 Asparagine synthetase, type II 2 4.9 0.031 7.79 0.0079 8.55 0.006 3.7 nsR23G09 556417 Fatty acid hydroperoxide lyase 2 4.6 0.0001 3.04 0.0021 6.82 <.0001 2.67 0.0051R52B01 568257 Polyphenol oxidase (catechol oxidase) 2 4.42 0.0128 2.3 ns 6.45 0.003 2.82 nsR29G09 199105 S-adenosylmethionine decarboxylase 3 3.65 <.0001 5.47 <.0001 4.23 <.0001 4.41 <.0001R02A12 660167 Mevalonate diphosphate decarboxylase 2 3 <.0001 1.91 0.0028 2.43 0.0002 1.82 0.0048R33E05 737826 Xylose isomerase 2 2.99 0.0003 3.14 0.0002 3.58 <.0001 1.79 0.0222R24G03 836268 Monodehydroascorbate reductase (NADH) 3 2.76 0.015 3.54 0.0039 2.65 0.0188 1.87 nsR18C06 582552 Alkaline alpha galactosidase I 3 2.57 ns 8.41 0.0057 3.07 ns 3.1 nsR25D07 564333 S-adenosylmethionine synthetase 6 −1.59 ns −3.41 0.0029 −1.2 ns −4.07 0.0011R77E04 821843 Glyceraldehyde-3-phosphate dehydrogenase 6 −1.64 ns −3.69 0.0005 −1.56 ns −3.76 0.0004R34F01 733934 Glycine decarboxylase complex h-protein 6 −1.78 ns −2.9 0.0052 −2.23 0.0259 −3.27 0.0025R32D08 724846 Chalcone-flavonone isomerase b 6 −2.13 ns −1.39 ns −1.86 ns −3.25 0.0117R01B07 732181 Nonspecific lipid transfer protein 6 −2.74 0.0026 −6.83 <.0001 −2.92 0.0017 −7.24 <.0001R52G05 410110 Nucleoside diphosphate kinase (NDP kinase) 6 −2.93 0.0066 −4.72 0.0004 −3.05 0.0052 −3.98 0.0011R09C06 815626 NAD-dependent epimerase/dehydratase

family protein6 −3.56 ns −6.34 0.0261 −5.22 0.0431 −8.72 0.0113

RA01F05 575307 Cytosolic glyceraldehyde 3-phosphatedehydrogenase

6 −4.09 0.0294 −6.2 0.0072 −2.38 ns −3.01 ns

R42D10 578576 Plasma membrane ATPase 4 (Proton pump 4) 5 −5.54 <.0001 −3.29 0.0018 −3.77 0.0008 −1.85 ns

Protein synthesisR57C05 556400 40S ribosomal protein S19 6 −1.9 ns −5.41 0.0002 −2.57 0.0134 −5.69 0.0001R08G02 655943 Elongation factor EF1-alpha 6 −3.17 0.0044 −2.44 0.0201 −2.93 0.0069 −5.5 0.0002

Protein with binding function or cofactor requirementR39E10 744962 Metallothionein 1b 6 −6.2 0.0003 −15.86 <.0001 −13.55 <.0001 −20.04 <.0001R39G06 558075 Plant metallothionein, family 15 5 −8.05 <.0001 −6.85 <.0001 −13.85 <.0001 −9.47 <.0001R56E10 677329 Metallothionein 1a 5 −12.73 0.0002 −16.73 <.0001 −15.27 <.0001 −12.53 0.0002

TranscriptionR40E06 705907 I-box Myb binding factor-like protein 3 4.94 0.0001 5.19 <.0001 3.64 0.0007 4.76 0.0001R52E10 648871 Zinc finger-like protein 2 4.08 <.0001 1.06 ns 4.81 <.0001 1.57 ns

Transport facilitationR42F06 721309 Ferredoxin 5 −3.78 <.0001 −2.3 0.0034 −2.68 0.0009 −2.49 0.0017R06E12 804667 High affinity nitrate transporter Ntr2;1 5 −6.17 0.0002 −3.17 0.0065 −4.47 0.001 −5.54 0.0003

340 F. Guerra et al. / Environmental and Experimental Botany 67 (2009) 335–344

Table 1 (Continued).

cDNA IDa P. trichocarpa Best blast hitc Clusterd 30 �M Cu 60 �M Cu

ProteinID no.b 12 h 24 h 12 h 24 h

FCe p-Valuee FCe p-Valuee FCe p-Valuee FCe p-Valuee

OthersR14H10 180857 Ubiquitin extension protein 6 UBQ6, ribosomal

protein S27A 753 3.25 ns 14.12 0.0025 2.33 ns 5.45 0.0335

R07H09 680477 Hypothetical protein 3 2.85 ns 19.93 0.0003 1.83 ns 10.29 0.0025R77D01 no hit Hypothetical protein 4 1.59 ns 2.79 ns 1.97 ns 22.98 0.0224R74F04 280896 Heat shock protein 70 6 −1.09 ns −3.57 0.0055 −1.41 ns −4.28 0.0022R62E08 717022 Histone H2a 6 −1.68 0.0138 −3.59 <.0001 −1.73 0.0102 −2.92 <.0001R42A01 820375 Auxin induced nonspecific lipid transfer

protein5 −4.44 0.0074 −2.21 ns −6.71 0.0013 −6.16 0.0019

R51D06 649433 Organ specific tissue protein 2 6 −7.49 0.0006 −17.41 <.0001 −6.68 0.001 −15.99 <.0001

a cDNA Probe ID number on the Populus 4.6 k cDNA array (NCBI GEO platform GPL4887).b Protein ID number of corresponding best gene model in the P. trichocarpa ‘Nisqually-1’ genome sequence (version 1.1) at http://genome.jgi-

psf.org/Poptr1 1/Poptr1 1.home.html.

scriptr cDNA

a(sraacw6

3s

<gtoMT

Ftttdd

c Best database match obtained with a BLASTX query at NCBI.d The cluster column indicates the corresponding cluster number in Fig. 5.e Expression ratios (and associated p-Value) calculated between normalized tran

oots (no copper) after 12 h and 24 h of stress exposure obtained with Populus 4.6 k

nd hypothetical proteins (e.g. JGI P. trichocarpa ProteinID 830905)Table 1). On the other hand, the highest levels of Cu repres-ion (≤−10-fold) were observed for transcripts coding for proteinselated to metal chelation, such as different members of the met-llothionein family (JGI P. trichocarpa ProteinIDs 677329, 558075nd 744962), as well as proteins involved in redox regulation like aationic peroxidase (JGI P. trichocarpa ProteinID 647567), and a cellall associated extensin-like protein (JGI P. trichocarpa ProteinID

76382) (Table 1).

.4. Cluster analysis of gene expression in roots exposed to Cutress

The expression data of a subset of 597 genes (fold-change−2.5 or >2) were clustered using the wCluto software to define

ene groups having similar expression patterns. Fig. 5 showshe seven consensus clusters obtained by wCluto and a full listf genes included in each is given in Supplemental Table S2.ost of genes (94%) were grouped in clusters (C) 2–6 (Fig. 5,

able 1). For these, time-dependent profiles were observed when

ig. 4. Venn’s diagram displaying the overlaps between poplar gene responses towo levels of copper stress (nutrient solution plus 30 or 60 �M CuSO4) as well as twoimes of exposition to Cu stress (12 and 24 h). The number of significantly differen-ially expressed genes (p-Value ≤ 0.05) in assessed treatments and interactions areetailed in the overlaps. Numbers in parenthesis indicate the total number of up orown regulated genes in each treatment.

concentration of P. deltoides roots subjected to 30 or 60 �M of Cu stress and controlarray and three biological replicates.

plants were subjected to Cu stress. These profiles were simi-lar for treatment with 30 and 60 �M of Cu (Fig. 5). Cluster 2and C5 included genes whose induction/repression levels werehigher at 12 than 24 h, whereas the opposite tendency wasobserved for C3, C4 and C6. Some genes grouped within C2 andC5 encodes proteins related to aminocid biosynthesis (aluminum-induced protein Wali7 domain, glutamate dehydrogenase 2),defense (pathogenesis-related PR10 ribonuclease, glutathione S-transferase 18), metal chelation (metallothionein family 15) andtransport (high affinity nitrate transporter Ntr2, aquaporin PIP1,plasma membrane ATPase 4). On the other hand, some genesincluded in clusters with a higher regulation at 24 than 12 h (C3,C4 and C6) encodes proteins also associated to defense (kunitztrypsin inhibitor TI3, basic chitinase), secondary metabolism(S-adenosylmethionine decarboxylase), redox control (cationic

peroxidase), cell wall formation (extensin-like protein), metalchelation (metallothionein 1b), transport (aquaporin TIP), andsome unknown functions (e.g. organ specific tissue protein 2),among others.

Fig. 5. Clustering of expression profiles of P. deltoides transcripts in root tissuesat 12 and 24 h during time-course exposition to 30 or 60 �M of Cu stress. Fold-change was calculated according to control root tissues (only nutrient solution). Thecluster view shows the mean pattern of expression of the transcript in that cluster.Clustering analysis was carried out on the 597 significantly differentially expressed(fold-change <−2.5 or >2) with the wCluto clustering tool using the direct clusteringoption. The number of transcripts in each cluster is indicated.

F. Guerra et al. / Environmental and Exper

Fig. 6. RNA blot analysis for validation of cDNA arrays. Hybridization of 4 poplarcDNA probes to total RNAs extracted from Populus deltoides grown in control condi-tions (lanes 1 and 4), or exposed to two levels of Cu stress (30 �M CuSO4, lanes 2 and5; 60 �M CuSO4, lanes 3 and 6) at 12 and 24 h after stress exposure. Total RNAs iso-lseM

3

NebdgAKaPep

4

ClimCbto

smi(itrecs

ated from roots of P. deltoides in control or stress conditions were hybridized withelected 32P-labeled cDNA inserts. rRNAs on gel are shown as quality control forlectrophoresis. KTI3: Kunitz trypsin inhibitor 3; ALIP: aluminum-induced protein;T1b:metallothionein 1b; PX: cationic peroxidase.

.5. RNA blot analyses

Results obtained using the cDNA arrays were validated usingorthern blot analysis. We selected a set of genes with the high-st up or down expression ratios and tested them with a northernlot analysis, which gives a good indication of the transcript abun-ances in the various treatments (Fig. 6). RNA blot analyses forenes correlated with expression levels observed in the cDNA array.n increase in the transcript abundance was observed for genesTI3 and ALIP when treatments were compared with controls. Inn opposite way, a decreasing pattern was observed for MT1b andX. Thus, the usefulness of nylon-based cDNA arrays for global genexpression profiling in identifying genes with specific expressionatterns was confirmed.

. Discussion

In this study, we analyzed the Populus root transcriptome underu stress. We aimed to have a global insight about the molecu-

ar mechanisms underlying the plant response to Cu excess andmprove our understanding of the interaction of poplars and heavy

etals. We selected a Cu tolerant P. deltoides clone, determined theu content in its tissues, and carried out a transcriptomic analysisy cDNA macroarrays. Relatively high levels of stress were appliedo the plants during a limited experimental period to avoid effectsf aging and to obtain a pronounced stress effect.

Quantification of Cu contents in different tissues collected fromtressed plants of P. deltoides clone showed that the metal isainly accumulated in roots (Fig. 3). A Cu concentration higher

n roots than other organs has been reported previously for poplarsLaureysens et al., 2004; Borghi et al., 2007). Accumulation of Cun roots demonstrates that this metal has a low mobility within

he plant and suggests the action of an exclusion mechanismestricting metal uptake and/or root to shoot transport (Sebastianit al., 2004). On the other hand, Cu content in leaves did nothange significantly when plants were stressed. In some genotypesuch as (P. trichocarpa × maximowiczii) × P. maximowiczii or (P. tri-

imental Botany 67 (2009) 335–344 341

chocarpa × deltoides) × P. trichocarpa, leaf necrosis was observed(Figs. 1 and 2), although leaf Cu remained constant and lower thanthe P. deltoides clone (unpublished data). This suggests that leafdamage would be not a direct effect of Cu. Long-distance signalinginvolving abscisic acid and ethylene can mediate the communica-tion between roots and shoots in response to metals such as Cd andCu, producing alterations in growth and symptoms of water deficit(Polle and Schützendübel, 2003). Leaf necrosis (full or partial) in Cusensitive poplars could be the effect of the crosstalk among stresssignaling pathways triggering differential control of water balance,oxidative burning or cell death programs. Further analysis will beneeded to clarify the specific participating mechanisms.

Expression analysis allowed identifying a series of genes encod-ing defense proteins, which were significantly up regulated inall stress treatments (Table 1, Supplemental Table S2). The accu-mulation of transcripts encoding trypsin inhibitors (TIs) or PRproteins has been reported in poplar subjected to biotic and abi-otic stress agents including insects (Ralph et al., 2006; Major andConstabel, 2008), pathogenic fungus (Rinaldi et al., 2007), wound-ing (Christopher et al., 2004) and ozone (Gupta et al., 2005). SpecificCu-induction of PR10 proteins has been also reported for birch(Utriainen et al., 1998). Heavy metal stress-induction of genes par-ticipating to biotic stress responses may result from a crosstalkamong the stress-related signaling pathways (Metwally et al.,2005). Stress-activated cytoplasmic Ca2+ increases, ROS produc-tion, synthesis of signaling molecules such as NO or salicylate(SA), are major points of interaction between pathogen elicitedresponses and toxic effects of different metal ions (Poschenriederet al., 2006). In this study, a variety of genes encoding proteins par-ticipating to signal transduction pathways were significantly up ordown regulated (Table 1, Supplemental Table S2). Evidences aboutthe participation of Ca2+ dependent signaling proteins (calmod-ulin and EF-proteins), MAP kinases and Rab small G protein (RABGTP-binding protein) were detected in all treatments. Accumula-tion of transcripts coding enzymes such as catechol oxidase, alleneoxide synthase, 1-aminocyclopropane-1-carboxylate oxidase andsome ethylene responsive elements suggests participation of SA,jasmonic acid (JA) and ethylene in the response. Evidences of Cudependent regulation of Ca sensor genes (Inoue et al., 2005), MAPkinase genes (Jonak et al., 2004) and signaling pathways mediatedby SA, JA or ethylene (Xiang and Oliver, 1998) has also been reportedfor species such as Arabidopsis and tobacco.

Defense genes induced or repressed by Cu stress also includeddifferent enzymes of the antioxidant system. Peroxidases, Cu/Zn-superoxide dismutase and catalase genes showed lower transcriptslevels (Table 1, Supplemental Table S2), suggesting a modulationof hydrogen peroxide contents during Cu applications. Peroxideis a signaling molecule that under stress conditions induces botha protective response and cellular damages (Foyer and Noctor,2005). In roots of Cd-stressed Populus × canescens, similar enzymeswere inhibited, peroxide was accumulated, and root growth wasdiminished (Schützendübel et al., 2002). Our results also suggestthe regulation of enzymes regenerating the active form of ascor-bic acid (AA). Monodehydroascorbate reductase (MDHAR) was upregulated in almost all treatments, whereas cytosolic ascorbate per-oxidase was down regulated (Table 1). Genes coding enzymes ofthe glutathione (GSH) biosynthesis pathway were up or down reg-ulated as well, indicating a possible increase in the levels of two ofits constituent amino acids: glutamate and glycine (Fig. 7, Table 1and Supplemental Table S2). Studies assessing the effects of Cd orZn on GSH metabolism in Populus euramericana (Di Baccio et al.,

2005) and transgenic P. × canescens (Bittsánszky et al., 2005) haveshown that GSH is important in the response of poplars to Zn. Thegenes coding for glutamylcysteine synthetase and glutathione syn-thetase, directly in charge of GSH biosynthesis from constituentamino acids, were not represented on the macroarrays used in

342 F. Guerra et al. / Environmental and Experimental Botany 67 (2009) 335–344

Fig. 7. Schematic non-stoichiometric depiction of glutathione (GSH) synthesis (adapted from Noctor et al., 1998). Numbers indicate the following enzymes for which transcriptc se (otw e com(

otp

heltrt1i(ipbaomr

nSttu2paplod(rae

en Biotecnología Silvoagrícola (CIBS) and ECOS-CONICYT program

oncentrations were altered under Cu stress: (1) serine:glyoxilate aminotransferahile other oxo acids may accept the serine amino group), (2) glycine decarboxilas

6) O- acetylserine (thiol) lyase.

ur study. An evaluation of these genes at transcriptional or pro-ein level will be necessary to establish the relationship betweenrecursors, GSH levels and antioxidant effects.

Metal chelators such as MTs have been involved in heavy metalomeostasis and tolerance (Cobbett and Goldsbrough, 2002). How-ver, transcript analysis of Cu-stressed poplar roots suggests aimited participation of this type of metal binding molecules underhe assessed treatments. Surprisingly, MTs genes were highly downegulated in all stress conditions (Table 1). Previous studies in P.richocarpa × deltoides roots have shown a slight increase of Type

MT transcripts in response to Cu stress, suggesting a role moremportant of MTs in metabolism/detoxification of Zn rather than CuKohler et al., 2004). The role of MTs as a ROS scavenger, modulat-ng oxidative signaling required for the induction of defense againstathogens, and associated to an down regulation pattern has alsoeen described in poplar (Smith et al., 2004) and rice (Wong etl., 2004). In this sense, lower MTs transcripts levels detected inur experiments could be associated with a transient ROS accu-ulation, which in turn would be necessary to trigger a general

esistance response.Some genes encoding proteins linked to transport mecha-

isms were differentially expressed under Cu treatments (Table 1,upplemental Table S2). Genes encoding plasmalema (PIP) andonoplast (TIP) aquaporins were down regulated under Cu applica-ion. Regulation of aquaporins transcript levels has been reportednder Ca, Na, Cl and K stresses in Arabidopsis (Maathuis et al.,003), indicating its importance in support for ion fluxes throughrovision of accompanying water flow, and active redirection ofpoplastic/symplastic water flow within tissues and the wholelant. A high affinity nitrate transporter showed lower transcripts

evels under all assessed Cu stress conditions. A Similar repressionf homologous genes has also been observed in roots of nitrogen-

eprived seedlings of Prunus persica after ammonium applicationsNakamura et al., 2007). Nitrogen metabolism is central to theesponse of plants to heavy metals due to diverse N-containingmino acids, peptides and amines that are accumulated duringxposition to metal (Sharma and Dietz, 2006). Therefore, the down

her amino acids may also act as amino donors for glyoxylate or hydroxypiruvate,plex, (3) glutamine synthetase, (4) glutamate synthase, (5) asparagine synthetase,

regulation observed in the case of the P. deltoides clone could berelated to N requirements of cells and/or relocalization for synthesisof N-compounds.

In conclusion, our results indicate that exposure of P. del-toides plants to Cu would increase metal accumulation in roots.Expression analysis also allowed us to identify a set of genes signif-icantly differentially expressed in all stress treatments that likelyplay an important role in the general Cu-stress response. Highlyup or down regulated genes included those encoding defenseproteins (e.g. Kunitz-TIs), enzymes involved in amino acid biosyn-thesis and metal chelating proteins (e.g. MTs). Our results alsoindicate the action of redox control, nitrate transport and waterflux in response to Cu stress. Signaling elements such as Ca2+

and ethylene-related enzymes also showed altered transcript pro-files highlighting the dynamic response to the applied stress. Thiscomprehensive expression study allowed deriving a large set ofcandidate genes of importance in the poplar root response to Cu.Such analysis helped us to draw hypotheses concerning the phys-iological events that take place in root cells to adapt to the metalstress. Further studies focused on specific aspects such as the sub-cellular localization of Cu in cell roots or amino acid/metabolitesvariations will complete the characterization of Cu effects in P. del-toides plants. Suppression or over-expression of selected candidategenes in transformed poplar trees will be required to elucidatethese functions in the context of Cu tolerance and their effects inthe improvement of trees with purposes of phytoremediation.

Acknowledgements

This work was supported by funds from Centro de Investigación

(project C05B06). Authors thank to project FONDEF D04I1027 andCentro Tecnológico del Álamo for supplying the plant material, toJorge Valdés (Universidad Andrés Bello) and to Javier Chilian andFernando Poblete (Universidad de Talca) for collaboration in bioin-formatics and northern hybridizations.

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ppendix A. Supplementary data

Supplementary data associated with this article can be found, inhe online version, at doi:10.1016/j.envexpbot.2009.08.004.

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