2-D DIGE analysis of UV-C radiation-responsive proteins in globe artichoke leaves

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2-D DIGE analysis of UV-C radiation-responsive proteins in globe artichoke leaves / Falvo S.; Di Carli M.; Desiderio A.; Benvenuto E.; Moglia A.; America T.; Lanteri S.; Acquadro A.. - In: PROTEOMICS. - ISSN 1615-9853. - 12(3)(2012), pp. 448-460.

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2-D DIGE analysis of UV-C radiation-responsive proteins in globe artichoke leaves

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DOI:10.1002/pmic.201100337

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Proteomics 2012, 12, 448–460

DOI 10.1002/pmic.201100337

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2-D DIGE analysis of UV-C radiation-responsive proteins in globe artichoke leaves

Falvo, S.1,2_{, Di Carli, M.} 3_{, Desiderio, A.}3_{, Benvenuto, E.}3_{, Moglia, A.}1_{, America, T.}4_{, Lanteri, S.}1_{, Acquadro, A.}1

1_{DIVAPRA, University of Turin, via L. da Vinci 44, 10095 Grugliasco (TO) - Italy}

2_{Bioindustry Park Silvano Fumero S.p.A., via Ribes 5, 10010 Colleretto Giacosa (TO) - Italy.}

3_{Biotechnology Laboratory, UTBIORAD, ENEA, Casaccia Research Center, via Anguillarese 301, 00123 Roma - Italy}

4_{Plant Research International, Droevendaalsesteeg 1, 6708PB, Wageningen - The Netherlands}

KEYWORDS. globe artichoke, UV-C stress, 2D-DIGE technology, leaf proteome, protein-protein

network.

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ABSTRACT

Plants respond to ultraviolet stress inducing a self-defence through the regulation of specific gene family members. The UV acclimation is the result of biochemical and physiological processes, such as enhancement of the antioxidant enzymatic system and accumulation of UV-absorbing phenolic compounds (e.g.: flavonoids). Globe artichoke is an attractive species for studying the protein network involved in UV stress response, being characterized by remarkable levels of inducible antioxidants. Proteomic tools can assist the evaluation of the expression patterns of UV–responsive proteins and we applied the Difference In-Gel Electrophoresis (DIGE) technology for monitoring the globe artichoke proteome variation at four time-points following an acute UV-C exposure. A total of 145 UV-C modulated proteins were observed and 119 were identified by LC-MS/MS using a ~144,000 customised

Compositae protein database, which included about 19,000 globe artichoke unigenes. Proteins were GO

categorised, visualised on their pathways and their behaviour was discussed. A predicted protein interaction network was produced and highly connected hub-like proteins were highlighted. Most of the proteins differentially modulated were chloroplast located, involved in photosynthesis, sugar metabolisms, protein folding and abiotic stress. The identification of UV-C-responsive proteins may contribute to shed light on the molecular mechanisms underlying plant responses to UV stress.

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1 INTRODUCTION

Solar radiation is the principal factor influencing plant productivity. In particular, the ultraviolet component, characterized by high-energy mutagen waves, affects plant tissue structures, primarily chloroplasts, and impairs main physiological pathways, leading to photoinhibition, production of reactive oxygen species (ROS) with consequent oxidative damages, and finally plant death [1]. Plants respond to UV stress through biochemical, physiological and morphological acclimations [2], including the synthesis of secondary metabolites such as phenylpropanoids (PPs), which are involved in ROS scavenging and carotenoids which dissipate light energy into heat.

The progressive ozone depletion, observed since the late 1970s and quantified as a decline of about 4% per decade in the total volume of ozone in Earth's stratosphere, can be associated to a less effective protection against UV radiation [3]. UV-C rays are screened by the ozone layer [4], although under specific environmental conditions (e.g. high mountain locations), can reach for short periods the earth surface [5]. UV-C radiation effects on biological systems are considered more dramatic than UV-B effects, even though both UV wavelengths induce very similar photoproducts accumulation. For these reasons, results obtained from UV-C studies are indicative of plant response to ultraviolet stress [6] [7]. So far, most of data are related to molecular responses involved in oxidative stress defence to UV-B chronical exposure [8-12]. As opposite, plant response/acclimation to UV-C acute exposure is still poorly explored and deserves further investigations.

Globe artichoke (Cynara cardunculus L. var. scolymus) is an important crop for the Mediterranean rural economy rich in bio-molecules of pharmaceutical and nutraceutical interest [13]. It represents a model species for photo-stress analyses due to the capacity to effectively activate antioxidant responses [14]. Many of the globe artichoke health-promoting properties rely on specific PPs, along with flavonoid compounds of pharmaceutical use, which contribute to a multiplicity of plant functions [15]. In a previous work, we established a standardised UV-C stress induction system which consistently increases the amount PPs in leaves [14]. Gene regulation following UV-C exposure have been documented in globe artichoke [16-19], and preliminary information are known on protein dynamic adaptation in response to this stress [20].

The proteomic approach offers the possibility to evaluate the effects of environmental stimuli on plant, allowing to fine measure the quantitative relationships among proteins in directing physiological response during stress acclimation. The great potential of the high-throughput proteomic analysis has

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been well established for plant model species [21-23] and for studying a wide range of abiotic stress [24-26]. In spite of the lack of genomic information for non-model species, such as the globe artichoke, proteomics represents an effective tool to reveal and assess phenomena associated to crop productivity [27-30].

The aim of this work was to analyse the globe artichoke leaf proteome in response to UV-C by monitoring, for the first time, the protein modulation in a time-course analysis by two-dimensional differential in gel electrophoresis (DIGE) technology [31]. The functional role of the modulated proteins referred as to Gene Ontology cellular compartments and biochemical pathways and their predicted protein interaction network (PPIN; [32-33]) are discussed.

2 MATERIALS AND METHODS

2.1 Plant materials and experimental procedure

Seeds of globe artichoke F1 hybrid ‘Concerto’ (Nunhems) were germinated and grown at 20°C in a phytotron under a 16 h day/8 h night regimen (light intensity 120 µmol m-2 s-1). After 12 weeks, the fully expanded sixth leaf was collected from 3 independent plants, each leaf representing a biological replicate for UV stress assay. The system, depicted in the supporting information (Figure S1), was set up to allow for: i) the increase of the number of time points, ii) the simple treatment of the replicas and iii) the generation of a large array of data, as performed elsewhere [34]. From each of the collected leaves, 16 disks (2 cm diameter) were produced. Eight of them were exposed to UV-C light (254 nm) for 20 min, through a 16 W germicidal lamp (Koninklijke Philips Electronics N.V, Eindhoven, NL), at a distance of 20 cm from light source (3.2 mW/cm2), as previously described [14]. Disks were dipped in double distilled water, under a 16 h light/8 h dark regimen, and grounded in liquid nitrogen after 6, 12, 18 and 24 h. The remaining eight disks of each leaf were processed in the same way as before, with the lamp off (four not treated disks for each time point). Wound effects were subtracted by directly comparing data deriving from a ‘treated disk set’ with data deriving from ‘untreated disk set’, each considered at the same time point [17].

2.2 Protein extraction

Total artichoke leaf proteins were extracted using a Mg/NP-40 based protocol [28]. Briefly, 2 grams of powdered leaf tissues were homogenized in 10 mL of cold Mg/NP-40 buffer. The slurry was centrifuged

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at 12,000 x g for 15 min at 4°C, and the proteins contained in the supernatant were precipitated using the TCA/acetone method. The protein extract was air-dried re-suspended in UTC buffer (7M Urea, 2M Thiourea, 4% CHAPS) and then re-centrifuged at 20,000 x g to remove insoluble cell debris. The supernatant was purified using Clean-Up kit (GE Healthcare); the resulting pellet was resuspended in UTC buffer and stored at –80°C. Three independent extractions were performed for each status (treated/untreated) of the four time points (Figure S1).

2.3 DIGE analysis

Protein samples were labelled using the CyDyes DIGE Fluors (GE Healthcare), according to the manufacturer’s instructions [31]. Briefly, protein extracts (50 μg) were mixed with Cy2, Cy3, or Cy5 (200 pmoles) for 30 min in the dark [35]. Cy3- ,Cy5- and Cy2-labelled samples, were mixed together (Figure S1) and an equal volume of 2X sample buffer (UTC supplemented with 20 mM DTT and 1% IPG buffer) was added. Samples resuspended in rehydration buffer (UTC supplemented with 2 mM DTT and 0.5% IPG buffer) were loaded on a 18 cm 3-11 non linear gradient IPGstrip (GE Healthcare) and passively rehydrated overnight at room temperature. IEF was performed on an IPGphor unit (GE Healthcare) at 20°C with a 50 μA current limit per strip following these parameters: 10 h at 30 V, 1 h at 200 V, 30 min at 3500 V gradient, 3 h at 3500 V step and hold, 2 h at 8000 V gradient, 8 h at 8000 V step and hold.

After IEF, the IPG strips were incubated in 10 mL of equilibration buffer (6 M urea, 30% w/v glycerol, 2% w/v SDS, traces of bromophenol blue, 50 mM Tris pH 8.8) containing 1% w/v DTT for 15 min, and subsequently in 10 mL of the same buffer containing 2.5% w/v iodoacetamide for 15 min. The second dimension was carried out on 12.5% polyacrylamide gels, using an Ettan DALT twelve unit (GE Healthcare), by applying 5 W/gel for 15 min and 180 W for the remaining 4-5 h. Preparative gels, obtained loading 1 mg of protein extract, were silver stained [28].

Labelled proteins were visualized by scanning with a Typhoon 9410 imager (GE Healthcare) at the appropriate wavelengths for each dye. All gels were scanned at 100 μm resolution and the photomultiplier tube was set between 500 and 700 V; DIGE images were then processed using the Decyder V6.5 software (GE Healthcare). One-way analysis of variance (ANOVA) was performed applying the false discovery rate [36] and differentially expressed protein spots were selected according to the statistically significant parameters (p-value ≤ 0.05; fold change threshold ≥ 1.3; presence in the 70% of the spot maps). Preparative silver stained gels were scanned using a CCD camera (Perkin Elmer

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Life Sciences, Boston, MA, USA), and matched with the master gel in order to assign the right correspondence for spot picking.

2.4 Identification of proteins by MS/MS

Differentially expressed spots were excised from gels. In-gel digestion, reduction and alkylation of proteins were performed as described elsewhere [37] and nano LC-nanospray MS/MS analyses were performed by coupling an HP 1100 nanoHPLC system to an XCT-Plus nanospray-ion trap mass spectrometer (Agilent). Mascot Daemon v2.2.2 (Matrix Science) was employed for protein identification, searching against a customized database, representative of the Compositae family. Briefly, contig databases from Cynara cardunculus [38], Lactuca sativa, Lactuca serriola, Heliantus

annuus, Hevea spp. were downloaded from NCBI (http://www.ncbi.nlm.nih.gov/) and TGI

(http://compbio.dfci.harvard.edu/tgi/) databases (November, 2009) and the nucleotide sequences were translated into aminoacid sequences by using NucToProt tool (Plant Research International - PRI, Wageningen, NL). FastaFileMerger software (PRI) was used to merge the databases along with a keratin-trypsin database subset, and to remove any redundant entries (based on 100% sequence similarity). The merged Compositae protein database was uploaded in Mascot Daemon, and search was performed using the following parameters: (i) trypsin: one missed cleavage allowed, (ii) fixed modification: carbamidomethyl (C), (iii) variable modifications: deamidated (NQ) and oxidation (M), (iv) peptide tolerance: ± 1.2 Da, (v) MS/MS tolerance: ± 0.6 Da, (vi) peptide charge: +1, +2, +3 (monoisotopic), (vii) instrument type: ESI-TRAP. Only significant hits, as defined by the MASCOT probability analysis (p≤0.05), were accepted and single peptide protein identifications were not considered in our analysis.

2.5 Multivariate analysis

Common unsupervised algorithms were used for clustering the expression vectors of the UV-C responsive spots passing one-way analysis of variance (ANOVA). Each protein fold change (Fc) was calculated according the following formula: Fc (spoti, timen) = log [(spoti, timen, UV gel) / (spoti, timen,

control gel)]. Hierarchical clustering (HCL) was adopted, grouping both proteins and experiments with average linkage method. Side by side, k-means (KM) algorithm was applied using Euclidean distance. The number of clusters was considered from k = 1 to k = 20, and predictive power was analyzed with

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the figure of merit (FOM). All cluster analyses and visualizations were performed using the stand-alone version of Genesis (http://genome.tugraz.at, [39]).

2.6 Interactome prediction

The prediction of a small scale globe artichoke interactome was performed transferring annotation with the Arabidopsis genome and considering orthologous genes [38]. Regulated proteins were analysed with the Search Tool for the Retrieval of Interacting Genes (STRING v. 9.0, http://www.string-db.org/) a database of known and predicted protein interactions. Proteins without known neighbours were omitted from the graph. A cluster (k-means) analysis was performed considering k=6, and groups were annotated. Putative hub proteins were predicted filtering the interactomic map for proteins with high number of interactions (>15).

2.7 Protein annotation/categorisation

Gene Ontology (GO) terms were derived from the Blast2GO v.2.3.6 bioinformatic tool (www.blast2go.org), following the workflow suggested by Conesa et al. [40] to retrieve gene annotation, the enzyme codes, and GO terms. The “Classification Super Viewer” tool, available at the Bio-Array Resource (http://bar.utoronto.ca), was used to search for over/under-representation of the searched proteins adopting the AGI codes as input. A ranking score for each functional class was calculated, using a bootstrap analysis. MapMan software v3.0 (http://mapman.gabipd.org) was employed, to produce customised globe artichoke pathways and to visualize the responsive proteins on them.

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3 RESULTS and DISCUSSION

3.1 Time course analysis of globe artichoke leaf proteome

The DIGE analysis allowed to evaluate proteome variation after UV-C radiation and to investigate plant stress response. The proteome of UV-C treated leaves was compared to the corresponding untreated sample at each of the four experimental time points (Figure S1). An average of 1688 (19% coefficient of variation) protein spots were resolved (MW range: 10-200 kDa; pI range: 3-10). A total of 151 spots were differentially regulated at the four time points, emphasizing a stronger effect of UV-C on foliar proteome during the early (6 h and 12 h of recovery) than the late (18 h and 24 h) response (Figure 1), presumably due to the plant adaptation response to stress. A comparable result was previously obtained analysing the globe artichoke PEG-fractionated proteome [19], although limited to just one experimental time point (e.g. 24 h after the stimulus). Besides, the time-course DIGE analysis permitted to highlight a number of UV-C modulated proteins four fold higher. Among the 151 selected spots, 145 were successfully picked up and 119 were identified (Table 1, Table S2). Eighty-one spots resulted in unique identification (Table 1), whereas 38 showed multiple identities (Table S2) and therefore were excluded from further analyses.

3.2 Multivariate analysis and GO categorisation

Hierachical clustering (HCL - Figure 2A) gave an overview on protein modulation throughout the four different time points analysed and grouped proteins in eight main clusters, two of which showed a marked up-regulation on the early response (cluster 6 and 7, Table 1). Non-hierarchical clustering (Figure 2B) reflected HCL classification and six of the major clusters included the higher number of proteins (88.1 %). The majority of clusters showed an over-representation of proteins expressed in chloroplast (Figure 3A, Figure S2), where oxygen radicals are produced, and four of them showed general bias towards proteins involved in “response to abiotic stimulus” (clusters 2, 3, 7, 10). Some other specific GO categories were over-represented; such as photosynthesis (GO0015979), energy metabolisms (GO0046961), chloroplast stroma (GO0009570), chloroplast envelop (GO0009941) and Tic (traslocon inner complex, GO0031897). Many ontologies related to stress response (GO0009266, GO0009268, GO0006950, GO0050896) were found to be over-represented in many clusters, even though exhibiting unlike expression vector trends (e.g.: cluster 3 vs cluster 7), presumably as a result of

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complex regulations due to the post-translational modifications occurring in cellular stress conditions [41].

3.3 Interactome prediction

Interaction-ortholog (“interolog”) mapping is a method for the prediction of interactomes [32], which has been used to foresee protein interaction on the premise that orthologous proteins, being evolutionary conserved, would tend to have conserved interactions [33]. We identified 863 predicted functional interactions for 49 globe artichoke UV-C responsive proteins (Figure 3B). The analysis highlighted networks for photosynthesis, photorespiration, proteasome and chloroplast biogenesis (Fig. 3B), and data were in accord with the GO term enrichment findings (Figure 2S). For each globe artichoke protein, the number of total interaction within the network was computed and putative hubs highlighted (Table 2). We found some highly interacting proteins (>50 interactions: ATP synthase, HSPs and PRXs), which were categorised as “Binding proteins” or “chaperones”. Some of them (translocon complex) were stress-related proteins involved in protein import into chloroplasts. A group of proteins was observed acting in the “proteasome complex” (Fig. 3B), suggesting the presence of a physiological network response, likely addressing protein turnover following UV-stress as reported for UV stress in human [42]. Many interologs were nuclear-encoded genes, but chloroplast-localized (23 out of 58; 40%), as expected for a light-based stimulus. From the protein list, 13 chloroplast-located interolog pairs (22%) revealed components of a number of well characterized plant metabolic pathways, which have either chloroplast-, mitochondrial- and peroxisome-located versions or known to be mitochondrial or cytosolic in yeast and animals.

3.4 Functional classification

Functional annotation of proteins confirmed their chloroplasts localisation and their role in abiotic stress response (Figure 3, S2). All the findings will be discussed in details below.

Photosynthesis and energy metabolism related proteins. Among the enzymes involved in photosyntesis

reactions, many players of the ‘light reaction’ (LHC-II, PS-I, PSII, cytochrome b6/f, and ferredoxin NADP+_{oxido-reductase) were found to be modulated at 6 h with a uneven expression, at 12 h with a}

negative expression, while the expression at 18 and 24 h is stably regulated (Figure 3, Table 1). In particular, LHC-II chlorophyll a/b-binding protein appeared to be present in some isoforms, for the most

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part, negatively expressed. LHC-II phosphorylation is a system for balancing the excitation energy between the two photosystems under stress, or changing light conditions [43], to increase light capture efficiency and avoid damages due to the over-reduction of the photosynthetic apparatus (PSI and PSII) [44]: the latter is the primary and most sensitive target of UV radiation [45] and our data confirmed this trend; indeed, LHC-II phosphorylation in globe artichoke stressed leaves still requires a deeper investigation.

The regulation of the electron flow is strictly related to the proton gradient required for the production of ATP and reducing power. Actually, several responsive ATP synthase isoforms appeared to be prevalently induced by UV-C radiation, suggesting the need of maintaining photosynthesis to retrieve ATP. Some spots, corresponding to other ATP synthase isoforms, were found to be alternatively repressed or induced during the time course experiment (Table 1), suggesting they may be otherwise regulated (e.g. PTMs).

A prevalent up-regulation of the Calvin cycle (‘dark reaction’) enzymes and carbon allocation was observed (Table 1, Fig 3B) as reported for ozone stress [46]. Most of these enzymes are also involved in glycolysis and gluconeogenesis pathways, strictly associated each other and to the pentose phosphate shunt. Intriguingly, Henkes and co-workers [47] found that, when the transketolase enzyme was repressed in tobacco, both photosynthesis and phenylpropanoid metabolisms were negatively affected, likely due to the limited flux of erythrose-4-phosphate into the shikimate pathway. Since TKs were prevalently up-regulated in globe artichoke, a key role of TKs in linking primary sugar metabolism with phenylpropanoid biosynthesis might be assumed.

Photorespiration in plants is not a wasteful process at all [48] as it makes a key contribution to cellular redox homeostasis and energy dissipation, preventing photoinhibition [49],[50]. In globe artichoke, most of the photorespiration enzymes were found to be positively regulated after UV-C exposure, suggesting that RuBisCO tends to respond to light stress with both carboxylase and oxygenase activities. Different isoforms of glycolate oxidase were found to be modulated (Figure 3): all were induced at 12 h, whereas spot 1242 was repressed at 6 h. Glycolate oxidase is located in peroxisomes and is responsible for glycolate oxidation to yield glyoxylate and peroxisomal H2O2 generation.

Aminomethyltransferase, up-regulated at 6 h, is involved in the transamination of glyoxylate to yield glycine, which is in turn oxidised in mitochondria by glycine dehydrogenase P-protein 1 (GLDP1). The latter, found at 6 h in three up-regulated isoforms, play a major role in plant metabolism and stress responses and, along with serine hydroxymethyltransferase (SHMT; mixed spot, Table S2), is essential

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for biosynthesis of methionine, pyrimidines, and purines. At the end, the CO2 released by the action of

the GLDP1 is lost, while the ammonia produced is likely rescued by glutamine synthase (mixed spot, Table S2).

Proteins involved in redox reactions and other metabolisms. Peroxiredoxins (PRXs) are the most

recently identified group of hydrogen peroxide decomposing enzymes, with a quadruple role in plant cell biology: (i) antioxidant, (ii) modulator of cell signalling pathways, (iii) redox sensor and (iv) molecular chaperone under oxidative stress conditions [51]. Globe artichoke peroxiredoxins were found in spots 1889 and 1919. At 6 h, spot 1889 appeared to be up-regulated, while its putative reduced counterpart (1919) showed to be down regulated; the opposite trend was revealed at 12 h. Reductive regeneration of PRX is accomplished by different thioredoxin isoforms, among which peptidyl-prolyl-cis-trans isomerase (PPI), regarded as protein folding catalysts, was found to be significantly induced at 12 h.

All the methionine synthase isoforms, involved in the cellular organic sulphur turnover, were up-regulated after UV-C stress (except spot 446), suggesting that the synthesis of methionine might have a role in preserving protein conformation, by increasing free methionine levels in the cells. Methionine can be readily oxidized and this residue oxidation on native proteins has been generally considered to be the ‘last chance’ antioxidant defence [52]. The sulfolipid sulfoquinovosyl diacylglycerol (SQD) is an abundant sulfur-containing non-phosphorous glycerolipid, specifically associated with photosynthetic membranes of higher plants and photosynthetic organisms [53]. Globe artichoke treated leaves may request sulfur for the synthesis of the proteins involved in the UV-C stress response and thus, SQD cellular degradation might be attempted. In our study, the UDP-sulfoquinovose synthase was found down-regulated at 6 h. It has also been demonstrated that SQD and phosphatidylglycerol (PG) contribute to the construction and/or functioning of PSI and PSII complexes [54], which indeed tended to be preserved at a steady state in globe artichoke (PSII, 1605 and 1547) to keep enhanced the activity of photosystems and thus, cope with the stress.

Chloroplast biogenesis. Chloroplast biogenesis network appeared modulated following UV-C stress.

Three isoform of the cpn60b chloroplast chaperons were found as UV-C responsive and all of them were induced at 12 h. It is known that heat shock proteins may interact with a wide range of

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co-chaperone proteins, cooperating in the regulation of activities or in the folding of specific substrate proteins [55] or in proteins trafficking towards chloroplast. Tic (Translocon Inner Complex) system, together with Toc (Translocon Inner Complex), facilitates import of pre-proteins into chloroplasts. We observed tic110, a part of the protein channel, which was down-modulated at 6 and up-modulated at 12h. The same trend was observed for the Clp1 (spot 368), a chloroplast ATP-dependent Clp protease, which facilitates the turnover of stromal enzymes and regulatory proteins. Indeed, it has been observed that, for chloroplast multimeric complexes, the regulation/absence of one protein subunit by proteolysis, can lead to the degradation of the other subunits, a common regulatory phenomenon in chloroplast [56]. Altogether, at 12h, protein related to chloroplast biogenesis were increased in content and this could be consistent with the request of a protein turnover, boosted by Calvin cycle up-regulation at 6 and 12h, likely requiring the import of new protein in the chloroplast stroma to uphold protein activity.

4 CONCLUDING REMARKS

In our time course experiment, proteomic changes in globe artichoke leaves were related to progressive acclimation following UV-C exposure. A strong effect of UV-C on the foliar proteome was observed during the early responses (6 and 12 h of recovery), while a lower number of modulated proteins were detectable after 18 and 24 h. This result is in accordance with data reviewed elsewhere [41] and highlights a plant response compensating the detrimental effect of stress through the hold-up of physiological activity in order to minimize cell damage. After a period that varies depending on the nature of the stress and the plant species, a gradual physiological adjustment occurs, defined as acclimation. The acclimation is associated to the active synthesis of proteins/metabolites aimed to re-establish the control level in the new environmental conditions [57]. The protein modulation observed at 6 h after UV-C exposure can be ascribed to the start of this process in globe artichoke leaves, particularly evident for processes associated to the dark phase of the photosynthesis and photorespiration-related proteins as observed in other abiotic stresses [46]. Other compensation mechanisms, such as restoration of proteins of light phase of photosynthesis (mostly repressed at 6 and 12h) and the induction of chaperons, mostly active in the chloroplast biogenesis, were shown to be induced later, or partially overlapped in time.

Previous metabolic analysis following UV-C exposure showed antioxidant PPs accumulation [16] [20]. In contrast, results hereby reported evidenced that most of the modulated proteins were related to primary and stress-related metabolism, while no proteins directly involved in the CQAs pathway

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resulted differentially expressed. This might be due to some intrinsic limits of proteomic analysis in detecting low abundance proteins (i.e.: some enzymes involved in secondary metabolites synthesis). Overall, our data suggest a predominant role of the primary metabolism (e.g.: Calvin cycle, penthose phosphate shunt) in counterbalancing UV-C effects during progressive acclimation of the plant, driving out metabolites from adjacent primary metabolisms to secondary pathways [58]. Some identified

proteins (e.g.: TK, PRX, PPI) might be used as benchmarks in studies of the molecular events associated

to ultraviolet stress recovery and our proteomic results could be helpful to build an improved view of biochemical processes involved in stress response.

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ACKNOWLEDGMENTS

This research has been enabled by a grant from “Progetto Lagrange-Fondazione CRT”. The research was performed in the context of the project iTECHPLAT Intervention, co-financed by the EU on the Measure 3.4 of the Regione Piemonte Docup 2000/2006, supported and implemented by Polo di Innovazione Provinciale of the Province of Turin 2009. Special thanks are due to Davide Corpillo and Alessandra Giuliano Albo for LC-MS/MS analyses.

CONFLICT OF INTEREST

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5 REFERENCES

[1] Stapleton, A., Ultraviolet-radiation and plants - burning questions. Plant Cell 1992, 1353-1358. [2] Jenkins, G. I., Signal Transduction in Responses to UV-B Radiation. Annual Review of Plant

Biology 2009, 60, 407-431.

[3] Björn, L. O., McKenzie, R. L., in: Springer (Ed.), Photobiology: the science of life and light. 2008, pp. 503-530.

[4] Ballare, C., Rousseaux, M., Searles, P., Zaller, J., et al., Impacts of solar ultraviolet-B radiation on terrestrial ecosystems of Tierra del Fuego (southern Argentina) - An overview of recent progress.

Journal of Photochemistry and Photobiology B-Biology 2001, 62, 67-77.

[5] Hader, D. P., Kumar, H. D., Smith, R. C., Worrest, R. C., Effects of solar UV radiation on aquatic ecosystems and interactions with climate change. Photochemical & Photobiological Sciences 2007, 6, 267-285.

[6] Danon, A., Gallois, P., UV-C radiation induces apoptotic-like changes in Arabidopsis thaliana. Febs

Letters 1998, 131-136.

[7] Conconi, A., Smerdon, M. J., Howe, G. A., Ryan, C. A., The octadecanoid signalling pathway in plants mediates a response to ultraviolet radiation. Nature 1996, 383, 826-829.

[8] Du, H. M., Liang, Y., Pei, K. Q., Ma, K. P., UV Radiation-Responsive Proteins in Rice Leaves: A Proteomic Analysis. Plant and Cell Physiology 2011, 52, 306-316.

[9] Casati, P., Zhang, X., Burlingame, A. L., Walbot, V., Analysis of leaf proteome after UV-B irradiation in maize lines differing in sensitivity. Molecular & Cellular Proteomics 2005, 4, 1673-1685. [10] Xu, C. P., Sullivan, J. H., Garrett, W. M., Caperna, T. J., Natarajan, S., Impact of solar Ultraviolet-B on the proteome in soybean lines differing in flavonoid contents. Phytochemistry 2008, 69, 38-48. [11] Kaspar, S., Matros, A., Mock, H.-P., Proteome and flavonoid analysis reveals distinct responses of epidermal tissue and whole leaves upon UV-B radiation of barley (Hordeum vulgare L.) seedlings. J

Proteome Res 2010, 9, 2402-2411.

[12] Singh, A., Sarkar, A., Singh, S., Agrawal, S. B., Investigation of supplemental ultraviolet-B-induced changes in antioxidative defense system and leaf proteome in radish (Raphanus sativus L. cv Truthful): an insight to plant response under high oxidative stress. Protoplasma 2010, 245, 75-83. [13] Lattanzio, V., Kroon, P. A., Linsalata, V., Cardinali, A., Globe artichoke: A functional food and source of nutraceutical ingredients. Journal of Functional Foods 2009, 1, 131-144.

[14] Moglia, A., Lanteri, S., Comino, C., Acquadro, A., et al., Stress-induced biosynthesis of dicaffeoylquinic acids in globe artichoke. Journal of Agricultural and Food Chemistry 2008, 56, 8641-8649.

[15] Boudet, A., Evolution and current status of research in phenolic compounds. Phytochemistry 2007,

68, 2722-2735.

[16] Moglia, A., Lanteri, S., Comino, C., Acquadro, A., et al., Stress-induced biosynthesis of dicaffeoylquinic acids in globe artichoke. J Agric Food Chem 2008, 56, 8641-8649.

[17] Moglia, A., Comino, C., Portis, E., Acquadro, A., et al., Isolation and mapping of a C3'H gene (CYP98A49) from globe artichoke, and its expression upon UV-C stress. Plant Cell Reports 2009, 28, 963-974.

[18] Comino, C., Hehn, A., Moglia, A., Menin, B., et al., The isolation and mapping of a novel hydroxycinnamoyltransferase in the artichoke chlorogenic acid pathway. BMC Plant Biology. 9:30 2009.

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[19] Menin, B., Comino, C., Moglia, A., Dolzhenko, Y., et al., Identification and mapping of genes related to caffeoylquinic acid synthesis in Cynara cardunculus L. Plant Science 2010, 338-347.

[20] Falvo, S., Acquadro, A., Giuliano Albo, A., America, T., Lanteri, S., Proteomic analysis of PEG-fractionated UV-C stress-response proteins in globe artichoke. Plant Molecular Biology Reporter 2010, doi: 10.1007/s11105-011-0325-2.

[21] Wienkoop, S., Baginsky, S., Weckwerth, W., Arabidopsis thaliana as a model organism for plant proteome research. Journal of Proteomics 2010, 73, 2239-2248.

[22] Reiland, S., Grossmann, J., Baerenfaller, K., Gehrig, P., et al., Integrated proteome and metabolite analysis of the de-etiolation process in plastids from rice (Oryza sativa L.). Proteomics 2011, 11, 1751-1763.

[23] Agrawal, G., Rakwal, R., Rice proteomics: A move toward expanded proteome coverage to comparative and functional proteomics uncovers the mysteries of rice and plant biology. Proteomics 2011, 11, 1630-1649.

[24] Kosova, K., Vitamvas, P., Prasil, I. T., Renaut, J., Plant proteome changes under abiotic stress - Contribution of proteomics studies to understanding plant stress response. Journal of Proteomics 2011, 74, 1301-1322.

[25] Aghaei, K., Ehsanpour, A. A., Komatsu, S., Proteome Analysis of Potato under Salt Stress. Journal

of Proteome Research 2008, 7, 4858-4868.

[26] Pang, Q., Chen, S., Dai, S., Chen, Y., et al., Comparative Proteomics of Salt Tolerance in

Arabidopsis thaliana and Thellungiella halophila. Journal of Proteome Research 2010, 9, 2584-2599.

[27] Carpentier, S., Panis, B., Vertommen, A., Swennen, R., et al., Proteome analysis of non-model plants: A challenging but powerful approach. Mass Spectrometry Reviews 2008, 27, 354-377.

[28] Acquadro, A., Falvo, S., Mila, S., Albo, A., et al., Proteomics in globe artichoke: Protein extraction and sample complexity reduction by PEG fractionation. Electrophoresis 2009, 30, 1594-1602.

[29] Bianco, L., Lopez, L., Scalone, A., Di Carli, M., et al., Strawberry proteome characterization and its regulation during fruit ripening and in different genotypes. Journal of Proteomics 2009, 72, 586-607. [30] Abril, N., Gion, J., Kerner, R., Muller-Starck, G., et al., Proteomics research on forest trees, the most recalcitrant and orphan plant species. Phytochemistry 2011, 72, 1219-1242.

[31] Unlu, M., Morgan, M., Minden, J., Difference gel electrophoresis: A single gel method for detecting changes in protein extracts. Electrophoresis 1997, 18, 2071-2077.

[32] Lehner, B., Fraser, A., A first-draft human protein-interaction map. Genome Biology 2004, 5, (9), R63.

[33] Yu, H., Luscombe, N., Lu, H., Zhu, X., et al., Annotation transfer between genomes: Protein-protein interologs and Protein-protein-DNA regulogs. Genome Research 2004, 1107-1118.

[34] Bos, J., Prince, D., Pitino, M., Maffei, M., et al., A Functional Genomics Approach Identifies Candidate Effectors from the Aphid Species Myzus persicae (Green Peach Aphid). Plos Genetics 2010. [35] Di Carli, M., Villani, M., Renzone, G., Nardi, L., et al., Leaf Proteome Analysis of Transgenic Plants Expressing Antiviral Antibodies. Journal of Proteome Research 2009, 838-848.

[36] Benjamini, Y., Discovering the false discovery rate. Journal of the Royal Statistical Society Series

B-Statistical Methodology 2010, 405-416.

[37] Shevchenko, A., Tomas, H., Havlis, J., Olsen, J., Mann, M., In-gel digestion for mass spectrometric characterization of proteins and proteomes. Nature Protocols 2006, 2856-2860.

[38] Scaglione, D., Acquadro, A., Portis, E, Taylor, CA., Lanteri, S. and Knapp, SJ., Ontology and diversity of transcript-associated microsatellites mined from a globe artichoke EST database. BMC

(19)

[39] Sturn, A., Quackenbush, J., Trajanoski, Z., Genesis: cluster analysis of microarray data.

Bioinformatics 2002, 207-208.

[40] Conesa, A., Gotz, S., Garcia-Gomez, J., Terol, J., et al., Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research. Bioinformatics 2005, 21, 3674-3676.

[41] Timperio, A., Egidi, M., Zolla, L., Proteomics applied on plant abiotic stresses: Role of heat shock proteins (HSP). Journal of Proteomics 2008, 391-411.

[42] Catalgol, B., Ziaja, I., Breusing, N., Jung, T., et al., The Proteasome Is an Integral Part of Solar Ultraviolet A Radiation-induced Gene Expression. Journal of Biological Chemistry 2009, 284, 30076-30086.

[43] Liu, X., Shen, Y., NaCl-induced phosphorylation of light harvesting chlorophyll a/b proteins in thylakold membranes from the halotolerant green alga, Dunaliella salina. Febs Letters 2004, 337-340. [44] Booij-James, I., Dube, S., Jansen, M., Edelman, M., Mattoo, A., Ultraviolet-B radiation impacts light-mediated turnover of the photosystem II reaction center heterodimer in Arabidopsis mutants altered in phenolic metabolism. Plant Physiology 2000, 1275-1283.

[45] Kim, Y., Lim, S., Han, S., Lee, J., et al., Differential expression of 10 sweetpotato peroxidases in response to sulfur dioxide, ozone, and ultraviolet radiation. Plant Physiology and Biochemistry 2007, 908-914.

[46] Ahsan, N., Nanjo, Y., Sawada, H., Kohno, Y., Komatsu, S., Ozone stress-induced proteomic changes in leaf total soluble and chloroplast proteins of soybean reveal that carbon allocation is involved in adaptation in the early developmental stage. Proteomics 2010, 2605-2619.

[47] Henkes, S., Sonnewald, U., Badur, R., Flachmann, R., Stitt, M., A small decrease of plastid transketolase activity in antisense tobacco transformants has dramatic effects on photosynthesis and phenylpropanoid metabolism. Plant Cell 2001, 535-551.

[48] Reumann, S., Toward a definition of the complete proteome of plant peroxisomes: Where experimental proteomics must be complemented by bioinformatics. Proteomics 2011, 1764-1779. [49] Osmond, B., Badger, M., Maxwell, K., Bjorkman, O., Leegood, R., Too many photos: Photorespiration, photoinhibition and photooxidation. Trends In Plant Science 1997, 119-121.

[50] Kozaki, A., Takeba, G., Photorespiration protects C3 plants from photooxidation. Nature 1996, 557-560.

[51] Dietz, K., Jacob, S., Oelze, M., Laxa, M., et al., The function of peroxiredoxins in plant organelle redox metabolism. Journal of Experimental Botany 2006, 1697-1709.

[52] Levine, R., Berlett, B., Moskovitz, J., Mosoni, L., Stadtman, E., Methionine residues may protect proteins from critical oxidative damage. Mechanisms of Ageing and Development 1999, 323-332.

[53] Benning, C., Biosynthesis and function of the sulfolipid sulfoquinovosyl diacylglycerol. Annual

Review of Plant Physiology and Plant Molecular Biology 1998, 53-75.

[54] Sugimoto, K., Midorikawa, T., Tsuzuki, M., Sato, N., Upregulation of PG synthesis on sulfur-starvation for PSI in Chlamydomonas. Biochemical and Biophysical Research Communications 2008, 660-665.

[55] Wang, W., Vinocur, B., Shoseyov, O., Altman, A., Role of plant heat-shock proteins and molecular chaperones in the abiotic stress response. Trends In Plant Science 2004, 244-252.

[56] Adam, Z., Clarke, A., Cutting edge of chloroplast proteolysis. Trends in Plant Science 2002, 7, 451-456.

[57] Lambers, H., Chapin, F. S. I., Pons, T. L., Chapin, F. S., Plant physiological ecology, Springer Verlag 2008.

[58] Sanchez, A., Shin, J., Davis, S. J., Abiotic stress and the plant circadian clock. Plant signaling &

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FIGURE LEGENDS

Fig. 1. A) Localization of the UV-C modulated protein in globe artichoke leaf extracts. Up- and

down-regulated proteins are labelled in red and white, respectively. The total number of differential protein spots for each time point is indicated. B) Number of up- and down-regulated proteins at the different time points.

Fig. 2. Multivariate analysis of the 151 differentially modulated proteins in each time point. A) Heat

map of the hierarchical analysis representing the Euclidean distance; groups with different expression trends after UV-C treatment were numbered (1-8). B) k-means representation in the 11 clusters obtained from the non-hierarchical analysis.

Fig. 3. A) GOs over-representations; proteins were categorized according to their biological role,

molecular function and subcellular localization. Normalised mean of the observed frequency for each GO category is reported (a ± y-error placed on the bar is the standard deviation value). B) MapMan snapshot on photosynthesis- and photorespiration-related proteins. C) Predicted protein interaction network visualisation. Hub proteins having more than 3 interologs are reported.

TABLE LEGENDS

Table 1. Protein spot annotation and expression analyses (multivariate and clustering). For each spot are

reported: i) protein annotation; ii) Arabidopsis orthologs (AGI code); iii) Enzymatic Code (E.C.) numbers and iv) clustering position (k-means analysis). Expression values in the four experimental times are reported as average logarithmic ratio between treated and untreated samples taken at the same experimental point. Non-significant fold change is reported as fold=1.00.

Table 2: Hub categorisation of UV-C responsive protein spots. Minor (3-5 interactions), small (6-10

interactions) medium (11-50 interactions), major (51-100) and super (>150 interactions) hub proteins are listed together with their annotation information.

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Supporting informations:

Figure S1: A. Set up of the experimental design. B. 2-D DIGE labelling design.

Figure S2: GO enrichments found in clusters obtained by K-means analysis.

Table S3: Comprehensive protein identification table reporting i) matched peptide sequences, peptide

score, number of matched queries and protein coverage. “Protein id” is the univoque code for proteins present in the custom Compositae protein database. The table reports all the spots which show multiple

protein identities.

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Table 1.

Spot ID Protein annotation acronym ortholog

(AGI code) E.C. Cluster 6h 12h 18h 24h

Photosynthesis-related proteins

409 ATP synthase cf1 alpha subunit ATPA AtCg00120 EC:3.6.3.14 3 1.50 1.40 1.00 1.00

417 ATP synthase cf1 alpha subunit ATPA AtCg00120 EC:3.6.3.14 3 1.49 1.32 1.00 1.00

635 ATP synthase cf1 alpha subunit ATPA AtCg00120 EC:3.6.3.14 10 1.41 1.77 1.00 -1.40

772 ATP synthase cf1 alpha subunit ATPA AtCg00120 EC:3.6.3.14 7 -1.41 -1.09 1.00 1.00

570 Vacuolar ATP synthase subunit A VHA-A At1G78900 EC:3.6.3.14 3 1.38 1.33 1.00 1.00

1973 ATP synthase delta-subunit ATPD At4G09650 EC:3.6.3.14 1 -2.25 1.30 1.00 1.00

1976 ATP synthase delta-subunit ATPD At4G09650 EC:3.6.3.14 1 -1.74 1.24 1.00 1.30

592 RubiscoL RBCL AtCg00490 EC:4.1.1.39 6 1.62 2.32 1.89 3.09

507 Transketolase TKL At2G45290 EC:2.2.1.1 3 2.03 1.44 1.00 1.00

513 Transketolase TKL At2G45290 EC:2.2.1.1 2 1.68 1.02 -1.60 1.00

1124 FBP aldolase FBA At4G26530 EC:4.1.2.13 3 2.15 1.23 1.00 1.00

1273 FBP aldolase FBA2 At4g38970 EC:4.1.2.13 3 1.65 1.75 1.00 1.00

1290 FBP aldolase FBA2 At4g38970 EC:4.1.2.13 8 1.00 1.41 1.00 1.00

1444 Ferredoxin-NADP+ oxidoreductase FNR1 At5g66190 EC:1.18.1.2 9 1.00 -1.50 1.00 1.00

1449 Ferredoxin-NADP+ oxidoreductase - At1G54870 EC:1.18.1.2 2 1.32 1.37 -1.90 1.00

1547 Photosystem II subunit O2 PSBO2 At3G50820 - 6 1.00 1.46 1.84 3.17

1605 Photosystem II subunit O2 PSBO2 At3G50820 - 9 1.35 -1.10 1.00 1.00

2265 Photosystem I subunit E1 PSAE1 At4g28750 - 9 1.65 -1.44 1.36 1.00

2306 Photosystem I subunit E1 PSAE1 At4g28750 - 11 1.00 -2.50 1.00 1.57

1768 LHC-II Chlorophyll a/b-binding protein LHCB2.2 At2g05100 EC:5.3.1.6 1 -1.69 1.88 1.00 1.00 1819 LHC-II Chlorophyll a/b-binding protein LHCB2.2 At2g05100 EC:5.3.1.6 1 -1.35 1.40 1.00 1.40 1874 LHC-II Chlorophyll a/b-binding protein LHCB2.2 At2g05100 EC:5.3.1.6 7 -2.01 -1.02 1.00 1.00 1949 LHC-II Chlorophyll a/b-binding protein LHCB2.2 At2g05100 EC:5.3.1.6 7 -1.43 -1.04 1.00 1.34 1942 LHC-II Chlorophyll a/b-binding protein LHCB2.2 At2g05100 EC:5.3.1.6 8 1.00 1.32 1.00 1.00 1944 LHC-II Chlorophyll a/b-binding protein LHCB2.2 At2g05100 EC:5.3.1.6 8 1.00 1.38 1.00 1.00

1061 Phosphoglycerate kinase - At1G56190 EC:2.7.2.3 3 1.40 1.49 1.00 1.00

1115 Glyceraldehyde-3-P dehydrogenase B subunit GAPB At1g42970 EC:1.2.1.13;EC:1.2.1.12 9 1.39 -1.40 1.00 1.82

1759 Triose-phosphate isomerase TIM At2G21170 EC:5.3.1.1 8 1.00 1.43 1.00 1.30

2067 Photosynthetic electron transfer-like protein PETC At4G03280 EC:1.10.2.2;EC:1.10.99.1 9 1.00 -1.82 1.00 1.00 Photorespiration-related proteins

273 Glycine dehydrogenase P-protein1 GLDP1 At4G33010 EC:1.4.4.2 3 1.70 1.00 1.00 1.00

337 Glycine dehydrogenase P-protein1 GDCSP At2g26080 EC:1.4.4.2 3 1.34 1.00 1.00 1.00

340 Glycine dehydrogenase P-protein1 GDCSP At2g26080 EC:1.4.4.2 3 1.43 1.00 1.00 1.00

1156 Glycine cleavage system P-protein GCST At1G11860 EC:2.6.1.0;EC:2.1.2.10 9 1.31 -1.30 1.00 1.00

1433 Malate dehydrogenase PMDH2 At5G09660 - 8 1.00 1.33 1.00 1.00

1242 Glycolate oxidase GO At3G14415 EC:1.1.3.15 1 -1.31 1.82 1.00 1.00

1250 Glycolate oxidase GO At3G14420 EC:3.4.24.0 8 1.00 1.77 1.00 1.00

1251 Glycolate oxidase GO At3G14420 EC:3.4.24.0 8 1.00 1.84 1.00 1.00

972 Alanine-glyoxylate aminotransferase 2 AGT2 At4g39660 EC:2.6.1.44 9 1.00 1.00 1.86 1.43

1573 Carbonic anhydrase CA1 At3G01500 EC:4.2.1.1 10 1.09 1.12 -1.30 -1.50

1728 Carbonic anhydrase CA1 At3G01500 EC:4.2.1.1 3 3.46 1.17 1.00 1.00

Redox processes-related proteins

446 Methionine synthase ATMS2 At5G17920 EC:2.1.1.14 10 1.89 1.67 1.00 -1.40

465 Methionine synthase ATMS2 At5G17920 EC:2.1.1.14 3 1.84 1.65 1.00 1.00

478 Methionine synthase ATMS2 At5G17920 EC:2.1.1.14 9 1.37 -1.10 1.00 1.00

883 SAM synthase SAM2 At4G01850 EC:2.5.1.6 10 1.00 1.66 1.00 -2.00

998 SAM synthase SAM2 At4G01850 EC:2.5.1.6 8 1.36 1.82 1.00 1.00

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Spot ID Protein annotation Acronym Ortholog

(AGI code) E.C. Cluster 6h 12h 18h 24h

1889 2cys-peroxiredoxin BAS1 At3G11630 EC:1.11.1.15 5 1.96 -2.00 1.00 1.00

1919 2cys-peroxiredoxin BAS1 At3G11630 EC:1.11.1.15 1 -1.60 1.55 1.00 1.00

Chaperons and binding-related proteins

540 Glycyl-tRNA synthetase - At1g29880 EC:6.1.1.14 3 1.54 1.40 1.00 1.00

399 heat shock cognate 70 kDa protein 3 HSC70-3 At3G12580 - 10 1.00 1.06 1.00 -1.40

502 heat shock cognate 70 kDa protein 2 HSC70-2 At5G02500 - 3 1.38 1.00 1.00 1.00

1721 NAD-dependent epimerase - At2G37660 - 8 1.00 1.30 1.00 1.36

1726 NAD-dependent epimerase - At2G37660 - 1 -1.69 1.72 1.00 1.33

1697 NAD-dependent epimerase - At2G37660 - 7 -1.72 -1.52 -1.37 1.35

1261 mRNA-binding protein (CSP41A) CSP41A At3G63140 - 3 1.48 1.48 1.00 1.00

2003 Translationally controlled tumor protein TCTP At3G16640 - 8 1.00 1.62 1.00 1.00

2255 Peptidyl prolyl isomerase PPI At5G13120 EC:5.2.1.8 8 1.00 1.46 1.00 1.00

Chloroplast biogenesis-related proteins

521 Hsp70 cpHsc70-1 At4G24280 - 3 1.45 1.33 1.00 1.00

1753 Chaperonin20 ( Cpn20) CPN20 At5G20720 - 8 1.00 1.84 1.00 1.00

660 Chaperonin60beta ( Cpn60b) LEN1 At1G55490 EC:1.1.1.37 8 1.00 1.44 1.00 1.00

674 Chaperonin60beta ( Cpn60b) LEN1 At1G55490 EC:1.1.1.37 8 1.00 1.61 1.00 1.00

662 Chaperonin60beta ( Cpn60b) LEN1 At1G55490 EC:1.1.1.37 10 1.00 1.66 1.00 -1.50

242 Chloroplast inner envelope Tic110 At1G06950 - 1 -1.32 1.33 1.00 1.00

364 Chloroplast inner envelope Tic110 At1G06950 - 10 -1.31 1.42 1.00 -1.41

368 ATP-dependent Clp protease CLPC At5G50920 EC:3.6.1.15 1 -1.30 1.03 1.00 1.00

Proteasome-related proteins

1899 20S proteasome B subunit PBG1 At1G56450 EC:3.4.25.0 1 -1.65 1.15 1.00 1.47

1052 glutathione dehydrogenase ADH2 At5G43940 EC:1.1.1.1; EC:1.1.1.284 3 2.04 1.06 1.00 1.00

1067 glutathione dehydrogenase ADH2 At5G43940 EC:1.1.1.1; EC:1.1.1.284 3 1.60 1.27 1.00 1.00

Other proteins

1550 30S ribosomal protein S5 - At2g33800 EC:3.6.5.3 10 1.58 1.80 1.00 -1.40

1559 30S ribosomal protein S5 - At2g33800 EC:3.6.5.3 10 1.00 1.66 1.00 -1.40

190 Metalloendopeptidase ATPREP1 At3G19170 EC:3.4.24.0 1 -1.87 1.44 1.32 1.47

238 SEC14 (cytosolic factor) SEC14 At1G14820 - 3 1.44 1.00 1.00 1.00

728 Ketol-acid reductoisomerase - At3G58610 EC:1.1.1.86 3 -1.64 -1.02 1.00 1.00

997 Elong Ation factor Tu ATRABE1B At4G20360 EC:3.6.5.3 5 2.12 -1.40 1.00 1.00

1059 Actin ACT8 At5g09810 - 8 1.00 1.58 1.00 1.00

2120 50S ribosomal protein RPL21 At1G35680 EC:3.6.5.3 9 1.43 -1.04 1.00 1.00

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Table 2.

Spot Ortholog (AGI code) Annotation Cluster Edges Hub classification

1550 At2g33800 30S ribosomal protein S5 10 (11-50) medium

399 At3g12580 HSP70 10 (51-100) major

1061 At1g56190 PGK 3 (6-10) small

540 At1g29880 ATP-dependent Clp protease 3 (6-10) small

570 At1g78900 ATP synthase 3 (11-50) medium

1124 At4g26530 FBP aldolase 3 (3-5) minor

1433 At5g09660 Malate dehydrogenase 8 (51-100) major

1759 At2g21170 TIM 8 (6-10) small

2255 At5g13120 Peptidyl prolyl isomerase 8 (6-10) small

1251 At3g14420 Glycolate oxidase 8 (6-10) small

1156 At1g11860 Aminomethyltransferase 7 (6-10) small

1889, 1919 At3g11630 Peroxiredoxin 1, 5 (>150) 176 super

1899 At1g56450 Proteasome subunit alpha 1 (6-10) small

728 At3g58610 Ketol-acid reductoisomerase 3 (6-10) small

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FIGURE 1 0 10 20 30 40 50 60 70 80 6h 12h 18h 24h UP DOWN

TIME POINT 6h

111 regulated spots 154 190 238 242 273 337 340 364 368 409417 ₄₆₅ 472468 473 475477476 492484478493 500 502 507 506 505 509 512513 521 524 540 542 562 570 589 596 598 624635 667 722 728 980985 995 990 996 997 998 1052 10571061 1067 1081 1083 1115 1107 1123 11241147 1156 1242 12561273 126112691277 1299 1366 1449 1471 1530 1550 1605 1623 1678 16971726 1728 1699 1731 1739 17681769_17701778 1793 1815 1819 1835 1871 1874 1889 1899 1919 1949 1967 19731976 2068 1989 2120 ₂₁₇₈ 2265 2268 592 1000 491446 154 190 238 242 273 337 340 364 368 409417 ₄₆₅ 472468 473 475477476 492484478493 500 502 507 506 505 509 512513 521 524 540 542 562 570 589 596 598 624635 667 722 728 980985 995 990 996 997 998 1052 10571061 1067 1081 1083 1115 1107 1123 11241147 1156 1242 12561273 126112691277 1299 1366 1449 1471 1530 1550 1605 1623 1678 16971726 1728 1699 1731 1739 17681769_17701778 1793 1815 1819 1835 1871 1874 1889 1899 1919 1949 1967 19731976 2068 1989 2120 ₂₁₇₈ 2265 2268 592 1000 491446 3 pI 11 150 11 MW

TIME POINT 12h

96 regulated spots 190 242 359 409 364 417 465 472468 475 476 477 500 505 507 512 521 542540 570 592598₅₉₆589612 624 635 660 662674 680 980985 995 996 997 998 1057 1059 1061 1081 1083 1101 1115 1107 1123 1144 1207 12611269 1242_{1250 1251}1254 12731290 1277 1413 1433 1444 1449 1471 1547 1550 16971726 1731 17531759 1768 1769 1770 1782 18151819 1871 1889 1919 1942 1944 1973 1989 2003 2067 2068 2092 2161 2178 2197 2229 ₂₂₅₅ 2265 2268 2306 1835 190 242 359 409 364 417 465 472468 475 476 477 500 505 507 512 521 542540 570 592598₅₉₆589612 624 635 660 662674 680 980985 995 996 997 998 1057 1059 1061 1081 1083 1101 1115 1107 1123 1144 1207 12611269 1242_{1250 1251}1254 12731290 1277 1413 1433 1444 1449 1471 1547 1550 16971726 1731 17531759 1768 1769 1770 1782 18151819 1871 1889 1919 1942 1944 1973 1989 2003 2067 2068 2092 2161 2178 2197 2229 ₂₂₅₅ 2265 2268 2306 1835 190 242 359 409 364 417 465 472468 475 476 477 500 505 507 512 521 542540 570 592598₅₉₆589612 624 635 660 662674 680 980985 995 996 997 998 1057 1059 1061 1081 1083 1101 1115 1107 1123 1144 1207 12611269 1242_{1250 1251}1254 12731290 1277 1413 1433 1444 1449 1471 1547 1550 16971726 1731 17531759 1768 1769 1770 1782 18151819 1871 1889 1919 1942 1944 1973 1989 2003 2067 2068 2092 2161 2178 2197 2229 ₂₂₅₅ 2265 2268 2306 1835 3 pI 11 150 11 MW

TIME POINT 18h

18 regulated spots 2178 1449 1413 2265 2161 1697 1573 1549 1547 972 612 598 596 592 589 513 509 190 2178 1449 1413 2265 2161 1697 1573 1549 1547 972 612 598 596 592 589 513 509 190 3 pI 11 150 11 MW

TIME POINT 24h

39 regulated spots 883 680 154 1573 624 359 662 1000 399 446 635 364 1550 1559 519 1759 1976 1726 1949 1697 1989 1721 1819 2268 972 190 1899 1778 616 2306 447 612 1115 589 596 592 1547 598 2178 1549 883 680 154 1573 624 359 662 1000 399 446 635 364 1550 1559 519 1759 1976 1726 1949 1697 1989 1721 1819 2268 972 190 1899 1778 616 2306 447 612 1115 589 596 592 1547 598 2178 1549 150 11 MW 3 pI 11

A

B

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(27)

FIGURE 3

B

N° interologs: 49 N° neighbour nodes: 863

A

PROTEASOME CHLOROPLAST BIOGENESIS PHOTORESPIRATION PHOTOSYNTHESIS 0 , 0 3 0 , 2 7 3 2 , 1 2 4 , 5 9 1 0 , 9 5 9 , 2 9 , 0 3 7 , 1 5 6 , 1 9 6 , 0 4 5 , 5 3 5 , 2 7 2 , 1 6 2 , 0 7 1 3 , 2 8 1 0 , 1 3 7 , 3 5 6 , 0 7 2 , 5 5 2 , 1 1 , 9 9 1 , 8 7 1 , 2 9 1 , 2 1 4 , 9 9 3 , 3 9 1 , 9 6 1 , 9 1 1 , 5 6 1 , 4 6 1 , 3 9 1 , 2 9 1 , 2 1 , 1 2 0 , 3 1 -5 0 5 10 15 20 25 30 35 40 extracellular plastid ribo so me o ther cyto plasmic co mpo nents chlo ro plast o ther intracellular co mpo nents cell wall mito cho ndria o ther membranes cyto so l nucleus plasma membrane unkno wn cellular co mpo nents electro n transpo rt o r energy pathways respo nse to abio tic o r bio tic stimulus respo nse to stress o ther bio lo gical pro cesses o ther metabo lic pro cesses o ther cellular pro cesses cell o rganizatio n and bio genesis pro tein metabo lism develo pmental pro cesses transpo rt o ther enzyme activity structural mo lecule activity o ther binding transferase activity nucleo tide binding o ther mo lecular functio ns transpo rter activity pro tein binding hydro lase activity DNA o r RNA binding kinase activity nucleic acid binding

Function (GO) Process (GO) Component (GO) En er gy o f m o le cu le s Calvin Cycle Light Reactions Photorespiration Chloroplast Thylacoids Chloroplast Peroxisome Mitochondrion Calvin cycle Glycerate Glycolate Glutamate Glyoxylate Hydroxypyruvate Glycine Glycine Methylene H4-folate Serine Ribulose 1,5-P2 Glutamine 3-phospho-glycerate 2-Glutamate 2-Phosphoglycolate Sugars GAP (X1) GAP (X6) GAP (X5) 3-PGA (X6) Chl Chl Chl+ Chl+ e- e -e -e -H₂0 O2 + H+_H+ photon PC Cyt PQ I Fdx Fdx -ADP + Pi ATP photon Photosystem II Photosystem I Redox chain NADP+ + H+H + NADPH + H+ ATP ADP ATP ADP O2 CO2 2Fdxed 2Fdxox O2 H2O2 H2O + ½ O2 NH₃ NAD+ NADH NAD+NADH NH3 CO2 Ribulose 1,5-2P (X3) Ribulose 5-P Xylulose 5-P Sedoheptulose 7-P Sedoheptulose 1,7-2P Erythrose 4-P Fructose 6-P Fructose 1,6-2P DHAP Carboxylation Reduction ATP ADP ATP ADP NADPH NADP+ (x3) (x3) (x6) (x6) (x6) (x6) (x6) Pi CO2(x3) LHC-II 6h 12h 18h 24h -6 -3 0 3 6 PS-II 6h 12h 18h 24h -6 -3 0 3 6 PS-I 6h 12h 18h 24h -6 -3 0 3 6 ATP synthase 6h 12h 18h 24h -6 -3 0 3 6 Cyt b6/f 6h 12h 18h 24h -6 -3 0 3 6 Fdx Reduttase 6h 12h 18h 24h -6 -3 0 3 6 RuBisCO 6h 12h 18h 24h -6 -3 0 3 6 9 Transketolase 6h 12h 18h 24h -6 -3 0 3 6 GAPA 6h 12h 18h 24h -6 -3 0 3 6 FBP aldolase 6h 12h 18h 24h -6 -3 0 3 6 Glycolate oxidase 6h 12h 18h 24h -6 -30 3 6 En er gy o f m o le cu le s Calvin Cycle Light Reactions Photorespiration Chloroplast Thylacoids Chloroplast Peroxisome Mitochondrion Calvin cycle Glycerate Glycolate Glutamate Glyoxylate Hydroxypyruvate Glycine Glycine Methylene H4-folate Serine Ribulose 1,5-P2 Glutamine 3-phospho-glycerate 2-Glutamate 2-Phosphoglycolate Sugars GAP (X1) GAP (X6) GAP (X5) 3-PGA (X6) Chl Chl Chl+ Chl+ e- e -e -e -H₂0 O2 + H+_H+ photon PC Cyt PQ I Fdx Fdx -ADP + Pi ATP photon Photosystem II Photosystem I Redox chain NADP+ + H+H + NADPH + H+ ATP ADP ATP ADP O2 CO2 2Fdxed 2Fdxox O2 H2O2 H2O + ½ O2 NH₃ NAD+ NADH NAD+NADH NH3 CO2 Ribulose 1,5-2P (X3) Ribulose 5-P Xylulose 5-P Sedoheptulose 7-P Sedoheptulose 1,7-2P Erythrose 4-P Fructose 6-P Fructose 1,6-2P DHAP Carboxylation Reduction ATP ADP ATP ADP NADPH NADP+ (x3) (x3) (x6) (x6) (x6) (x6) (x6) Pi CO2(x3) LHC-II 6h 12h 18h 24h -6 -3 0 3 6 PS-II 6h 12h 18h 24h -6 -3 0 3 6 PS-I 6h 12h 18h 24h -6 -3 0 3 6 ATP synthase 6h 12h 18h 24h -6 -3 0 3 6 Cyt b6/f 6h 12h 18h 24h -6 -3 0 3 6 Fdx Reduttase 6h 12h 18h 24h -6 -3 0 3 6 RuBisCO 6h 12h 18h 24h -6 -3 0 3 6 9 Transketolase 6h 12h 18h 24h -6 -3 0 3 6 GAPA 6h 12h 18h 24h -6 -3 0 3 6 FBP aldolase 6h 12h 18h 24h -6 -3 0 3 6 Glycolate oxidase 6h 12h 18h 24h -6 -30 3 6