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Volume 6 | N

umber 1 | 2010

Molecular B

ioSystems

Pages 1–276

www.molecularbiosystems.org Volume 6 | Number 1 | January 2010 | Pages 1–276

PAPERDieter Willbold et al.Competitively selected protein ligands pay their increase in specificity by a decrease in affinity

METHODThomas Kodadek et al.Rapid identification of orexin receptor binding ligands using cell-based screening accelerated with magnetic beads

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mbs006001_Cover.indd 5-1 26/11/2009 15:05:22

MolecularBiosystems

View Article OnlineView Journal

Biotrophic

pathogens

SA

Necrotrophic

pathogen

JA

+/-

+/-

Crosstalk between SA- and JA-mediated defence

pathways is investigated for the first time by both

proteomic and transcriptomic approaches.

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Crosstalk between salicylic acid and jasmonate in Arabidopsis investigated by an integrated

proteomic and transcriptomic approach

Silvia Proietti, Laura Bertini, Anna Maria Timperio, Lello Zolla, Carlo Caporale and Carla Caruso*

Department of Ecological and Biological Sciences, Università della Tuscia, Via S. Camillo De

Lellis, Viterbo 01100, Italy

*(�) Corresponding author: Prof. Carla Caruso; mailing address: Department of Ecological and

Biological Sciences, Università della Tuscia, Via S. Camillo De Lellis, 01100 Viterbo, Italy. Phone:

+39 0761357330; Fax: +39 0761357242; E-mail: caruso@unitus.it

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Abstract

Resistance conferred by biotrophic pathogens often requires salicylic acid (SA) signaling,

whereas necrotrophic pathogens or wounding mainly activate the jasmonate/ehtylene (JA/ET)-

dependent pathway. Crosstalk connections between these two independent signaling pathways may

lead to a synergistic or antagonistic behavior.

In order to shed some light on the crosstalk between these two hormones in Arabidopsis plants, a

proteomic approach combined with a transcriptomic analysis has been used to identify molecules

differentially expressed upon single or simultaneous treatment with both phytohormones. Twenty-

five nonredundant differential proteins were revealed upon treatment with SA or JA alone or in

combination, which are involved in general metabolic processes as well as in response to stress, in

developmental process, in protein metabolism and transport.

Interestingly, gene expression study, carried out on genes involved in oxidative stress and in

biotic and/or abiotic stresses, highlighted the correspondence between proteomic and transcriptomic

approaches, here performed by RT-PCR. Our data clearly demonstrate that almost all gene/proteins

involved in oxidative stress as well as in biotic and/or abiotic stresses are mainly induced upon JA

and only a few of them are overexpressed upon SA treatment. Moreover, we found that

substantially negative crosstalk is established upon the combined action of the two hormones and

that generally SA exerts a negative crosstalk over the JA pathway.

Our study corroborate the hypotesis that combination of both phytohormones induce

reprogramming of the plant transcriptome, but at same time highlights the presence of a complex

network of signaling that is far to be completely elucidated.

Keywords

Phytohormones crosstalk; Arabidopsis; proteomics; transcriptomics.

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Introduction

The first detectable response of a plant cell to an invading microorganism is the programmed cell

death (PCD) at the infection site, which is part of the so-called hypersensitive response (HR), and is

generally recognized by the presence of brown lesions at the injury site. The HR deprives the

pathogen of nutrients confining its growth to a small region of the plant. Host cell necrosis is

accompanied by a whole series of events, including changes in oxidative metabolism, accumulation

of toxic compounds and lignifications of cell walls. The initial responses of pathogen-invaded or

elicitor-treated plant cells occur within few minutes and are rapidly followed by local gene

activation. They include rapid and transient changes in inorganic ion fluxes across plasma

membrane, the accumulation of reactive oxygen species (ROSs) referred to as oxidative burst and

changes in the phosphorylation status of various proteins, all of which have been associated with

intracellular signal transduction mechanisms1,2

.

Many studies have shown that the HR is accompanied not only by biochemical changes at the

site of infection but also at distant site in the plant. This form of induced resistance is referred to as

systemic acquired resistance (SAR)3,4

, and this mechanism can be compared to immunization in

animals and humans. Characterisation of SAR in a variety of plant species has suggested the

existence of a complex signaling network that involves many diffusible factors known as second

messengers. Among the best studied endogenous signaling molecules are salicylic acid (SA), nitric

oxide (NO), jasmonic acid (JA) and ethylene (ET), phytohormones that primarily regulate the

protective responses of plant against biotic and abiotic stresses. The pivotal role of plant hormones

in the regulation of plant defense is well documented5-7

. Resistance conferred by biotrophic

pathogens often requires SA signaling, whereas necrotrophic pathogens or wounding mainly

activate the JA/ET-dependent pathway8. Thus, at least two different signal transduction pathways

can be distinguished, either SA- or JA/ET-dependent, which are turned on in response to pathogen

attack9. Large-scale transcriptomic analyses using DNA microarray technology, strongly support

the existence of such a complex signaling crosstalk between different pathways10,11

. Crosstalk

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connections between these two independent signaling pathways may lead to a synergistic or

antagonistic behavior 12,13,6,14,15

.

Among phytohormones involved in signal transduction pathways are also counted abscisic acid

(ABA), auxins and gibberellins, mainly involved in responses to abiotic stresses. In particular ABA

has been a subject of intensive studies that demonstrated its involvement in drought, low

temperature and osmotic stresses. It has been reported that ABA acts as negative regulator of

disease resistance16

; in particular, ABA and ET interact, mostly antagonistically, in several

developmental processes and in vegetative tissues17,18

. In addition, it has been reported that ABA

acts as antagonist also in SA-mediated signal transduction pathway19

. These findings suggest that

all signal pathways mediated from plant phytohormones are able to interact and to cooperate in the

development of plant defence mechanisms. Thus, a crosstalk between biotic and abiotic stress

signaling may converge in similar defence response and the presence of different pathways of

defence response offers a great regulatory potential that contribute to regulate both abiotic stresses

and disease resistance 20-23

. To date, the mechanisms that underlie this crosstalk are still unknown

and many laboratories are engaged in this field of research.

One of the best studied examples of defence-related signal crosstalk is the antagonistic

interaction between the SA and JA, dominant messenger signals in local and systemic induced

defence signaling24-26

. In the last years a highly interconnected signaling network between the

above phytohormones has been reported using mRNA expression profiling27,28

. However,

transcriptional changes do not reflect the complete cellular regulatory processes, since post-

transcriptional processes are not taken into account. Thus, complementary approaches such as

proteome-based expression profiling are needed to obtain a full picture of the regulatory elements in

plant defence response.

Proteome analysis is becoming a powerful tool in the functional characterization of plants. Due

to the availability of vast nucleotide sequence information and based on the progress achieved in

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sensitive and rapid protein identification by mass spectrometry, proteome approaches open up new

perspectives to analyze the complex functions of model plants and crop species at different levels.

Due to the availability of complete genomic sequence information and of large mutant

collections, a number of recent proteome studies have focused on Arabidopsis as a model plant. For

instance, the effect of SA in the establishment of early defence mechanisms in Arabidopsis has been

investigated using this approach29

. The NaCl stress-responsive proteins30

, the fungal elicitor-

induced proteins31

as well as the insect herbivore Plutella xylostella-induced proteins32

in

Arabidopsis have been also investigated with this methodology. Nonetheless, the interplay of more

phytohormones has not been investigated up to now using proteomics.

2D-PAGE, coupled with MS/MS, is one of the most powerful and effective techniques to

undertake proteomic analysis and to identify differentially expressed proteins offering highly

reproducible resolution for protein separation. Indeed, recent advances in mass spectrometry permit

analysis of low amounts of proteins separated in 2D gels. In order to shed some light on the

crosstalk between SA and JA in Arabidopsis, we have used 2D-PAGE coupled with MS/MS to

identify the up- or down-regulated Arabidopsis leaf proteins upon single or simultaneous treatment

with both phytohormones. Furthermore, this study demonstrates the power of 2D nano-HPLC in

combination with nano-electrospray iontrap MS/MS for comparative proteomic studies. In addition,

gene expression studies combined with the results obtained with the proteomic approach have

shown that there is a good correlation between the two experimental procedures.

Results and Discussion

2D protein analysis

It is well recognized that SA and JA induce several effects on plant development and disease. In

order to shed some light on the crosstalk between these two hormones in Arabidopsis plants, a

proteomic approach combined with a transcriptomic analysis has been used to identify

proteins/genes differentially expressed upon treatments with SA or JA alone and in combination. To

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this end, five-week-old Col-0 Arabidopsis plants have been separately treated with both

phytohormones by dipping foliar rosette into solution of SA or JA. Moreover, the combined effect

of SA and JA has been also evaluated by dipping foliar rosette into solution containing both

chemical inducers as reported in Material and Methods section. Plants of the same age were dipped

into distilled water and used as a control. Total soluble proteins prepared from treated leaves as well

as from control plants were separated by 2D gel electrophoresis and, following Coomassie brilliant

blue staining, protein patterns were characterized by image analysis using Progenesis SameSpots

software. The protein maps produced in triplicate from three independent experiments showed a

high level of reproducibility. Using the image analysis software, the 2D representative maps of

protein extracted from SA- (Fig. 1a), JA- (Fig. 1b) and both hormones-treated plants (Fig. 1c) as

well as the 2D representative control map (Fig. 1d) were analyzed. Approximately 700 spots could

be detected on each Coomassie brilliant blue-stained gel and about 500 protein spots matched

between control and sample gels in three independent experiments. Fig. 1e shows the reference map

derived from computerized image analysis performed using Progenesis SameSpots software

showing the protein spots analyzed by mass spectrometry. Quantitative image analysis revealed a

total of about 84 protein spots that changed their abundance (volume %) upon treatments with SA

or JA alone as well as upon treatment with the combination of the two hormones with respect to the

control. We decided to focus our attention on protein spots over- or under-expressed by a factor of

four as compared to the control. On this basis, we found 41 protein spots over-expressed at least

upon one treatment. On the other hand, the level of under-expression was always found less than

four-fold with respect to the control. For this reason only the over-expressed proteins were further

investigated.

Numbers and arrows in panels a, b and c of Fig.1 indicate analyzed spots corresponding to

proteins overexpressed at least four- fold with respect to the control. Differentially abundant spots

(indicated with numbers in the reference map showed in Fig. 1e) were excised from the gels and

digested by trypsin. Peptide mixtures were then analyzed by LC-ESI-MS/MS for protein

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identification. From forty-one gel plugs excised, twenty-eight proteins were successfully identified

by Mascot database searches of the full NCBI protein database.

Fig. 2 shows the expression level of the 28 identified proteins calculated relatively to the control

for each treatment. Fig. 2a shows the expression level of nine protein spots which were found to be

overexpressed by JA treatment but repressed by SA (spots number: 173, 179, 187, 193, 199, 299,

300, 459 and 468), indicating a negative crosstalk of SA over the JA pathway. Eight protein spots

were overexpressed by SA treatment but repressed by JA (spots number: 191, 204, 205, 278, 296,

302, 340 and 523), indicating a negative crosstalk of JA over the SA pathway. Moreover, Fig. 2c

shows seven protein spots overexpressed at least four-fold upon single treatment with SA or JA, but

repressed by a combination of both (spots number: 177, 200, 206, 213, 214, 348 and 423),

indicating antagonistic crosstalk between the two hormones. Finally, Fig. 2d shows the only four

protein spots inducible exclusively upon the combined treatment (spots number: 106, 375, 380 and

475) that suggest a synergistic behavior of SA- and JA-mediated response.

Spot identification by mass spectrometry

The twenty-eight proteins that were successfully identified by Mascot analysis are shown in

Table 1 together with their classification, protein spot number, gene code, identification parameters

and fold change differences among the different treatments. .

Fold changes are based on mean percentage volumes of each spot. It is worthwhile to mention

that two proteins were present on the gel in more than two spots, suggesting the existence of

alternative post-translational modifications or degradation. All proteins have been grouped in four

classes on the basis of their function or their involvement in metabolic response.

Photosynthesis

Rubisco large subunit (AtCg00490) was identified in three protein spots (177, 200, 205). Further

examination of electrophoresis patterns indicated that the inferred isoelectric point values of these

spots differed, due probably to the existence of isoforms or post-translational modification. Two

protein spots (177 and 200), having identical relative mass and differing only moderately in their pI

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(4.3 and 4.25, respectively), were found to be over-expressed upon SA treatment with similar fold

change (around 14 fold induction). On the contrary, the protein spot 205, showing a pI value of 4.8,

was found to be less induced upon SA treatment (4,95 fold induction). We could speculate that SA

is more effective in the induction of the more acidic isoforms of rubisco large subunit than the less

acidic one. Moreover, rubisco isoforms were subjected to a negative crosstalk since the combined

treatment with the two hormones produces an inhibition of the protein expression with respect to

the single treatments.

One more enzyme involved in photosynthesis, namely ribulose bisphosphate carboxylase small

chain 1A (At1g67090, spot 475), was found. It is worth highlighting that neither SA or JA alone

were effective in inducing this protein, but the combined treatment with these hormones is able to

induce its expression by 7,12 fold. These findings suggest that the protein is over-expressed only

during a positive crosstalk between the two signal transduction pathways.

Proteins involved in ATP synthesis

Chloroplast ATP synthase CF1 subunit alpha (AtCg00120) was identified in only one protein

spot (spot 193), whereas the beta subunit (AtCg00480) was identified in two protein spots, namely

213 and 214. It has been recently reported that among proteins responsive to toxic volatile organic

compound (VOC) in Arabidopsis is ATP synthase CF133

. Like other abiotic stress responses, the

VOC-mediated process is possibly linked to the hormonal-mediated stress responses. In fact,

ethylene has been regarded as the best candidate among plant hormones that might play a pivotal

role in the stress response induced by VOC34

. In our experimental conditions, the level of ATP

synthase CF1 alpha subunit was found to be 10,34 fold increased upon JA treatment that follows the

same signaling pathway of ethylene. Interestingly, the protein was no longer induced during the

combined treatment of JA and SA suggesting an antagonistic crosstalk by SA.

Two protein spots accounting for ATP synthase CF1 beta subunit were identified which differs

slightly in their pI. In particular, spot 213, showing a pI of 3.95, was induced by JA 19,87 fold and

by SA 14,76 fold whereas the more acidic isoform (spot 214, pI 3.6) showed 22,14 and 25,70 fold

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induction upon JA or SA treatment, respectively. It is also interesting to highlight that the combined

treatment of the two hormones resulted in a negative crosstalk as evidenced by low level of fold

change (2,02 for spot 213 and 4,79 for spot 214) with respect to the control.

Phosphoglycerate kinase (Atlg79550) was identified as spot 523. Phosphoglycerate kinase

(PGK) transfers a phosphate group from 1,3-bisphosphglycerate to ADP forming ATP and 3-

phopshoglycerate. This reaction is essential in most cells for the generation of ATP in aerobes, for

fermentation in anaerobes and for carbon fixation in plants. It has been reported that PGK levels are

greatly enhanced in Arabidopsis germinating seed treated with SA29

. According with this evidence,

we found that spot 523 is increased 6,91 fold in Arabidopsis plant treated with SA, whereas it is not

influenced by JA. However, the protein was no longer induced during the combined treatment of JA

and SA suggesting that JA is responsible of an antagonistic crosstalk. Unfortunately, it is not

possible at the moment to unravel the SA-transduction pathways involved in the central metabolism

regulation, nevertheless it is interesting to highlight that JA seems to be not involved in such a

regulation.

Oxidative stress

Abiotic stresses can cause many metabolic changes and are known to increase ROS levels in

plant tissue35,36

producing several changes in many biological processes. For instance, H2O2, one of

the most studied marker of oxidative stress, may be involved in signaling by other hormone or

stress responses37-40

. As shown in Table 1, several proteins involved in oxidative stress have been

identified. In particular, 14 protein spots were found to be involved in the production of ROS or

their detoxification as well as protein involved in central metabolism or photorespiration following

oxidative stress. Among them are two glycolate oxidase (GOX) isoforms, namely MOA2.2

(At3g14420, spot 299) and MOA2.13 (At3g1445, spot 300), that are peroxisomal enzymes that

catalyze the conversion of glycolate and oxygen to glyoxylate and hydrogen peroxide which is

related to photorespiration41

. Both isoforms were found to be highly induced by JA with respect to

the control (8,87 and 14,59 fold change, respectively), but they were subjected to a negative

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crosstalk by SA on JA pathway. It is well known that methyl jasmonate treatment of tomato plants

results in the accumulation of hydrogen peroxide that in turns acts as second messenger leading to

the induction of defense genes42

. According with this finding, we could suggest that the JA-

dependent increased level of H2O2 might be ascribed to increased levels of GOX. It is worthwhile to

mention that also Arabidopsis plants overexpressing GOX in chloroplasts accumulate both

glyoxylate and hydrogen peroxide, thus making the GOX plants a challenging model in which to

study the action of plastid-produced H2O2 as a signal molecule43

. Glyoxylate produced by GOX is

one of the two substrates of glutamate:glyoxylate amino transferase (GGAT) that is one of the best

studied enzyme involved in photorespiration in leaf peroxisome44

. Photorespiratory transamination

of glyoxylate, which is mediated by GGAT and serine glyoxylate aminotransferase (SGAT), is

believed to play an important role in the biosynthesis and metabolism of major amino acids. Our

results demonstrated the presence of GGAT1 in spot 179 that is induced by JA (6,01 fold change)

and it is repressed in combination of both phytohormones, displaying to be involved in an

antagonistic crosstalk by SA on JA pathway. Moreover, it has been recently reported that

glyoxylate may be converted in glycine also through the action of the gamma-aminobutirrate

transaminase (GABA-T), suggesting a potential interaction between GABA metabolism and

photorespiration45

. In this study we found GABA-T (At3g22200) in spot 191 that is induced both

by JA (2,97 fold change) and SA (5,27 fold change) when used alone. On the contrary, our results

highlight an antagonistic behavior when the two hormones were used in combination.

As mentioned above, an increased level of hydrogen peroxide is produced during respiration;

H2O2 is then detoxified by the action of the peroxisomal catalase which catalyses the breakdown of

H2O2 in water and oxygen. Two protein spots were found to be associated with catalase, namely

spot 187 (catalase3, CAT3, At1g20620) and spot 199 (catalase2, CAT2, At4g35090). According

with the expression induction of glycolate oxidase, both CAT2 and CAT3 were found to be induced

by JA (16,68 and 8,46 fold induction, respectively).

It is well documented that high levels of ROSs lead to cellular damage and are involved in

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programmed cell death (PCD) at the site of infection46,47

. In particular, PCD events are best

described during incompatible plant-pathogen interactions that form the basis for HR48

. During

evolution plants developed fine tune mechanisms to cope with temporary shift in the intracellular

redox state. In particular, photorespiration forms part of the dissipatory mechanisms of plants to

minimize production of ROS mitigating photooxidative damage49

. Among the enzymes involved in

such a pathway is also serine hydroxymethyl transferase (SHMT) that plays a crucial role in

controlling cell damage provoked by biotic and abiotic stresses50

. Our results showed that SHMT 1

(spot 173, At4g37930) and SHMT 4 (spot 206, At4g13930) are both induced by JA with 4,84 and

15,02 fold change, respectively. Interestingly, SHMT 1 is induced only by JA, whereas SHMT 4

was found to be induced also by SA (11,20 fold induction). In our experimental conditions both

enzymes are subjected to a negative crosstalk.

Other enzymes involved in mechanisms of attenuation of antioxidant response associated with

basal defense are carbonic anhydrases (CAs). These enzymes play a role in carbon fixation in C4

photosynthetic plants and in particular chloroplast CAs are recognized to expedite CO2 diffusion

during the first steps of Calvin cycle51

. Moreover, chloroplast CA functions as SA-binding protein 3

exhibiting antioxidant activity and plays a role in the HR defense response52

. Recently, it has been

reported that CAs are induced in Plutella-resistant inbred lines of Arabidopsis highlighting their

involvement in limiting ROS damage32

. In our experiments we identified two CA proteins, one

being the product of the At3g01500 gene coding for the chloroplast CA1(spot 468), whereas the

other was the product of the At5g14740 gene, coding for a putative CA2 (spot 459). Both proteins

are induced upon JA treatment (9,63 and 5,2 fold induction, respectively), are insensitive to SA

treatment and are subjected to a negative crosstalk.

One more enzyme that plays a role in mediating oxidative stress and regulating HR cell death is

aconitase (ACO2), found in spot 106. In animals, aconitase displays two different functions: in the

presence of an iron-sulfur cluster in its catalytic center it displays enzymatic activity whereas in its

absence it acquires the ability to bind RNA regulating the stability or translatability of certain

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transcripts. Recently, it has been reported that one member of the aconitase family is able to

specifically bind the 5’ UTR of superoxide dismutase CSD2 (Atg28190) in vitro, affecting its

transcription level53

. These finding corroborate the hypothesis that aconitase mediates resistance to

oxidative stress and regulate cell death by modulating the expression of genes involved in

intracellular ROS level control. Interestingly, in our experimental condition, aconitase 2

(At4g26970, spot 106) is up-regulated upon the combined treatment with SA and JA (4,87 fold

induction), whereas it is not affected by the single hormone treatment. In this case, the protein

expression is significantly induced when a synergistic interaction occurs between the two different

transduction pathways. Moreover, these findings corroborate previous studies highlighting the

hormone-mediated oxidative stress54

.

On the basis of the results presented above, comes evident the role of both SA or JA in

stimulating defense responses related to oxidative stress. Among them are also the induction of

proteins associated to lipid globule, known as fibrillin. Fibrillins are lipid-binding proteins of

plastids that are induced under abiotic stress conditions. Very recently, it has been reported that

Arabidopsis plants with reduced levels of fibrillins are impaired in long-term acclimation to

environmental constrain such as photooxidative stress55

. As a result, their photosynthetic apparatus

shows an abnormal granal and stromal membrane arrangement causing inefficient protection.

Interestingly, all phenotypic effects of lower fibrillin levels were abolished by JA treatment

suggesting a new physiological role for this hormone, such as acclimation of chloroplasts. In

addition, evidence that stress-related JA biosynthesis is conditioned by the accumulation of fibrillin

was also reported55

. According with these results, we found fibrillin in spot 278 (At2g35490) that is

overexpressed upon JA treatment (5,75 fold induction). It is noteworthy that also SA is able to

induce fibrillin expression to an higher extent (10,76 fold induction), while the combined action of

two hormones shows the levels of expression of fibrillin comparable to those observed after

treatment with JA, suggesting a negative crosstalk by SA.

Finally, two proteins involved in disease resistance and antioxidant metabolism were found in

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spots 340 and 380, namely ankyrin repeat-containing protein 2 (AKR2) (At4g35450) and

peroxisomal NAD-malate dehydrogenase (PMDH2) (At5g09660), respectively. Reduced

expression of AKR2 results in activation of HR and higher production of H2O2, similar to the

response of plants to pathogen infection. Moreover, AKR2 also interact with the ascorbate

peroxidase 3 that scavenges H2O2 in plant cell. These findings suggest that AKR2 is probably

involved in the regulation of antioxidant metabolism that is shared by both disease resistance and

stress response56

. The protein is highly inducible by SA (10,75 fold change) but is also induced by

JA, even to a lesser extent (5,86 fold change). Noteworthy, the combined treatment with the two

hormones results in a further decrease of AKR2 expression level (3,48 fold change) suggesting a

negative crosstalk between the two different transduction pathways. On the contrary, the combined

treatment of the two signal molecules results in the induction of PMDH2 expression (6,49 fold

induction), whereas the single treatments were totally ineffective. In this case a positive crosstalk

can be inferred to affect the protein expression.

Biotic and/or abiotic stress

Plant ability to cope with environmental stresses is essential for their survival. During evolution

plants have developed a complex variety of defence mechanisms that activate a highly coordinated

resistance response upon recognition of a potential risk. Signal transduction pathways leading to

defence are highly interconnected and often act simultaneously regulating gene expression via

synergistic or antagonistic actions. Besides SA, JA, ET and ABA, also the less studied hormones

such as brassinosteroid (BR) and gibberellic acid (GA) are involved in signaling cascade triggered

by biotic or abiotic stresses57,58

. It has been recently reported that BR-mediated stress tolerance in

Arabidopsis shows interactions with ABA, ET and SA pathways59

. How BR regulates gene

expression is currently understood for only a small number of genes. However, the involvement of a

plasma membrane-localized leucine-rich repeat receptor-like kinase (LRR-RLK), named BRI1, has

been widely recognized59

. In addition, it has been demonstrated that a plant homolog of TGF-beta

receptor interacting protein 1 (TRIP1) can be phosphorylated in vitro by BRI1 and that it is

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regulated by BR59

. In this study we prove evidence that transcript level of TRIP1, found in spot 302

(At2g46280), is induced by SA (4,44 fold induction) reinforcing the idea that BR and SA

transduction pathways may have some players in common.

As mentioned above, GA pathway plays crucial roles in plant growth and development as well as

stress responses. It has been recently reported that exogenous application of GA3 is able to reverse

the inhibitory effect of different stress conditions in seed germination and seedling establishment

and also increases SA biosynthesis, suggesting that GAs are implicated in plant responses to abiotic

stress by modulating SA levels58

. Among the protein overexpressed by SA treatment is calreticulin

1b (CRT1b), found in spot 204 (At1g09210), which belongs to a protein family of still poor

understood physiological function. Calreticulin has been shown to be involved in plant growth and

development as well as biotic and abiotic stress response. In fact, it has been reported that it is

involved in response to drought stress in wheat60

and in ABA-induced salt tolerance in potato61

.

Calreticulin is also overexpressed in response to pathogen attack62

as well as upon TMV infection63

.

Moreover, CRT gene expression is regulated by exogenous application of GA in barley aleuronic

cells64

indicating that crosstalk between CRT-mediated pathway and phytohormones-dependent

signaling might be one of the major mechanism triggering plant responses to different stresses.

These findings are in agreement with our results highlighting that CRT1b is induced by SA (4,26

fold change) that mimics biotic stress mediated by biotrophic pathogens and to JA (2,95 fold

change) that mimics biotic stress mediated by necrotrophic pathogen and insects as well as abiotic

stress.

As already stated above, ABA is not only able to regulate essential growth and developmental

processes in plants but it also plays an important role in freezing tolerance highlighting its

involvement in abiotic stresses. In our work we evidenced two proteins highly regulated by ABA:

the chloroplast RNA binding (CRB) protein, found in spot 296, and a NAD dependent

epimerase/dehydratase, found in spot 423. RNA binding proteins have been described as

component of ABA signaling during germination and drought tolerance65

. Besides these functions,

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CRB proteins mediate changes in mRNA synthesis, transport, translation and degradation. In

particular, chloroplast CRB proteins play an important role in flowering control and light-regulation

of protein supply in chloroplasts66

. In our work, CRB protein (At1g09340) was found to be induced

by SA (5,10 fold induction) but its expression was not influenced by JA. Interestingly, the

simultaneous treatment with the two phytohormones suppresses the SA-mediated enhancement,

suggesting a negative crosstalk of JA on SA. A NAD-dependent epimerase/dehydratase was found

to be induced by either JA (6,3 fold induction) or SA (7,78 fold induction), but its expression level

remains almost unchanged with respect to the control when the two hormones were used in

combination. In this case we can speculate that the two transduction pathways negatively influence

each others. It is well recognized that NAD-dependent epimerase/dehydratase are related to a Small

Ubiquitin-like Modifier (SUMO) conjugating enzyme that is a component of the sumoylation

pathway in Arabidopsis67

. It is worthwhile to mention that sumoylation is implicated in ABA-

mediated inhibition of root growth68

. Moreover, it has been proposed that regulation of the

sumoylation-dependent ABA signaling pathway is possibly achieved by tyrosine phosphorylation69

.

On the basis of our results and those reported in the literature we can hypothesize that ABA, JA and

SA signaling pathways may have some player in common. However, how these signals interact

each other remains an unanswered question.

As reported in Fig. 2, protein spot 348 (At4g02450) is by far the protein that undergoes the largest

change in expression following treatment with SA, exhibiting 166 fold induction. A substantial

increase in its levels of expression is also reported after treatment with JA (47.5 fold induction). It is

interesting to note that the combined treatment with the two hormones reduces the levels of protein

expression compared to those seen after treatment with individual hormones (29.4 fold induction).

As reported in Table 1, MASCOT analysis revealed the presence of a HSP20-like chaperone in spot

348. Heat shock proteins are molecular chaperones that regulate the folding, localization,

accumulation, and degradation of protein molecules in both plant and animal species70

. The

pathways leading to the elucidation of the molecular mechanisms of HSP20 induction are still far

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from being fully understood, but involve temperature perception mechanisms coupled with other

signal transduction pathways triggered by abiotic signals71

. Besides their chaperone activity, it is

possible that HSP20 limit damage resulting from accumulation of reactive oxygen species, which

are generated under a wide range of stress conditions72

. For instance, there is evidence that HSPs

may protect against reactive oxygen species in both plant and animal species73

. Moreover, it has

been reported that several HSP20 genes are induced in Arabidopsis upon wounding which usually

follows similar transduction pathway as JA74

. This hypothesis results very intriguing considering

the highly interconnected mechanisms of signaling.

In this paper we also prove evidence that an elongation factor 1B alpha-subunit2 (eEF1 B alpha

2) (spot 375, At5g19510) is significantly induced only upon the combined treatment with SA and

JA (6,07 fold induction). Worth of note is that single treatment with SA or JA was unable to

promote protein induction. This protein plays a crucial role in translational machinery leading to the

synthesis of several proteins involved in different cell response, independently from physiological

or stress condition. However, it has been reported that eEF1 B alpha 2 was specifically induced in

Arabidopsis upon inoculation with Pseudomonas syringae pv tomato DC3000 in response to the

pathogen effector (PAMP) T3Es75

. Our results corroborate the evidence that translational process is

of the outmost importance especially under biotic or abiotic stresses.

Gene expression studies

In order to deepen knowledge on the transcriptomic profile of the genes coding for the

differentially expressed proteins illustrated above, RT-PCR analyses were performed. We focused

our attention on all proteins involved in the oxidative stress and those involved in biotic and/or

abiotic stresses since their expression is more meaningful to unravel signal transduction pathways.

To this end, specific primers listed in Table 2 were designed for all genes and specific primers

for ubiquitin (At4g05320) were utilized for the amplification of the housekeeping gene ubiquitin,

used for quantity control.

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As reported in Fig. 3, the expression of genes involved in oxidative stress or related to biotic and/or

abiotic stresses correlates with the expression of the coded proteins (Fig. 2 and Table 1). In fact, we

found perfect correlation between transcript profiling and proteome analysis. Semi-quantitative RT-

PCR proved useful not only to study the expression of the selected genes upon single treatment with

SA or JA, but also to highlight the expression following the combined treatment with the two

phytohormones. In particular, genes induced only after the combined action of SA and JA were

found to be aconitase 2 (ACO2) and peroxisomal NAD-malate dehydrogenase 2 (PMDH2),

suggesting a synergism between the two hormones. This result is in good agreement with the

expression levels of the corresponding proteins as evidenced with proteomic analysis. However,

whether the two proteins participate to the same signal transduction pathway is still to be unraveled.

Almost all genes reported in Fig. 3 were found to be negatively modulated after the combined

treatment with SA or JA, suggesting a negative crosstalk. Interestingly, nine out of twelve genes

involved in the oxidative stress were overexpressed upon JA treatment, namely SHM1, GGAT1,

CAT3, CAT2, SHM4, MOA2.2, MOA2.13, CA1 and CA2. Almost all of the above-mentioned

genes are involved in the photorespiration process, as indicated in Fig. 4. Through H2O2 production,

detoxified by catalases, photorespiration makes a key contribution to cellular redox homeostasis. In

so doing, it influences multiple signaling pathways, in particular, those that govern plant hormonal

responses controlling growth, environmental and defense responses, and programmed cell

death76,77

. In our experimental conditions, both CAT2 and CAT3 were overexpressed upon JA

treatment (16,68 and 8,46 fold change, respectively) as well as upon SA challenge, even to a lesser

extent (5,76 and 2,29 fold change, respectively). Interestingly, CAT3 expression was drastically

reduced upon treatment with the combined hormones (1,20 fold change), whereas CAT2 exhibited a

lesser pronounced inhibition (13,44 fold change). Our results are in agreement with previous reports

on the SA-dependent inhibition of CAT activity78-80

. However, why and how SA antagonize the JA-

mediated pathway is still matter of debate.

Among genes overexpressed after JA treatment are also carbonic anhydrase coding genes (CA1 and

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CA2). For all these genes a negative effect of SA over the JA signaling can be inferred as evidenced

in Fig. 2 and Fig. 3 as well as in Table 1. Even though it remains unclear how ROS accumulation

determines the extent of SA/JA-dependent signals, it is clear that signals elicited by ROS cross-

communicate with other signaling components to determine the final outcome of the defense

reaction.

GABA-T, FIBR and AKR were overexpressed upon SA or JA treatments. Despite the

overexpression of all genes, a negative effect of JA on SA pathway has been evidenced. On the

contrary, all genes involved in biotic and/or abiotic stresses with the exception of EF1B proved to

be induced by SA while being all inhibited by the combination of the two phytohormones.

Taken together, these observations do not clarify how antagonism is exerted but add knowledge on

the existing picture15

of the major players in molecular crosstalk.

Concluding remarks

The present study revealed that several proteins are induced upon treatment with SA or JA alone

or in combination. The combined proteomic/transcriptomic approaches we used proved to be useful

to study the expression patterns of proteins and genes induced in response to different stimuli and

also to highlight crosstalk between two different transduction pathways. Moreover, our results add

significance in the research field on SA and JA signalling pathway and on crosstalk between two

phytohormones.

Choosing only the proteins that are overexpressed at least four times after treatment with

individual hormones or with the combination of the two, we highlighted the presence of proteins

that can be broadly categorized according to biological processes in which they are involved. Fig. 5

shows that about 25% of the proteins are involved in cellular processes, while 20% are synthesized

in response to stress and an equal amount are involved in general metabolic processes. According

with the signal molecules utilized, about 13% of the proteins are involved in biotic or abiotic

stimuli. Less percentage of the proteins are involved in developmental process (4,5%), protein

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metabolism (2,2%) and transport. Proteins participating in cell organization and biogenesis or in

electron transport and energy pathways account for less than 1%.

Furthermore, we proved evidence that proteomic approaches can be as successful as

transcriptomics to highlight the effect of signal molecules on the rate of cellular metabolism of

Arabidopsis.

Our data clearly demonstrate that almost all gene/proteins involved in oxidative stress as well as

in biotic and/or abiotic stresses are mainly induced upon JA and only few of them are

overexpressed upon SA treatment. Moreover, we found that substantially negative crosstalk is

established upon the combined action of the two hormones and that generally SA exerts a negative

crosstalk over the JA pathway. It is generally recognized that SA mimics the effect of biotrophic

pathogens, whereas JA is involved in necrotrophic pathogen-associated response. In nature, plants

often deal with simultaneous invasion by multiple aggressors, which can influence the primary

induced defense response of the host plant. The crosstalk is thought to provide the plant with a

powerful regulatory potential that helps deciding which defensive strategy to follow, depending on

the type of attacker encountered81

. It appears that attackers have evolved ways to manipulate plants

for their own benefit by affecting induced defenses via modulation of the plant signaling network.

On the basis of our results, we can speculate that when a simultaneous infection by necrotrophic

and biotrophic pathogens occurs, the latter might prevent necrosis antagonizing the signaling

pathway induced by necrotrophs. This strategy allows the biotroph to colonize living host tissues.

Our study corroborate and reinforce literature data on the effect of phytoormones in

reprogramming the plant transcriptome and highlights the presence of a complex network of

signaling that is far to be completely elucidated. However, our data could represent a good starting

point to design new mutants of SA or JA pathways in order to unravel the complex network of

signaling.

Functional analyses of the identified proteins, together with post-translational modification

studies, should extend our understanding of the whole picture of cell response to stress and give an

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invaluable molecular basis of the plant defense mechanisms. However, further studies are required

with Arabidopsis mutants in signaling pathways to identify nodal genes that are expressed in

multiple signaling pathways mediated by different stimuli.

Experimental

Cultivation of Arabidopsis plants and treatments

Seeds of Arabidopsis accession Col-0 were sown in quartz sand. After 2 weeks, seedlings were

transferred to 60 ml pots containing sand/potting soil mixture that was autoclaved twice for 20 min

with a 24 h interval82

. Plants were cultivated in a growth chamber with a 12/12 h (200 mE m-2

s-

1) day/night cycle, temperature of 21°C and 70% relative humidity for another 3 weeks. Plants were

watered on alternate days. Chemical induction treatments of Arabidopsis were performed by

dipping leaves of 5-week-old plants in a solution of 1 mM SA, 100 µM MeJA or a combination of

both chemicals at same concentration (Sigma, Schnelldorf, Germany). Control plants were treated

with water only. Leaf rosettes from five plants for each treatment (around 20 leaves) were harvested

24 h after treatment, immediately frozen in liquid nitrogen and then stored at -80 °C before further

analysis. Three biologically independent replicates were prepared at separate times.

Protein extraction

Frozen leaf tissue (2 g fresh weight) was crushed in a pre-cooled mortar with liquid nitrogen

with a pestle. The resulting fine powder was dissolved in a extraction buffer containing 50 mM

HEPES (pH 7.2), 150 mM NaCl, 1 mM EDTA, 1mM PMSF, 1% PVP (Sigma, Schnelldorf,

Germany). The supernatant was separated from the insoluble fraction by centrifugation at 9000 rpm

for 30 min and protein concentration was measured according to Bradford83

. Bovine serum albumin

was used as a standard.

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Semi-quantitative IEF–SDS PAGE

Proteins were precipitated from a desired volume (containing 900 µg of proteins) of each sample

with cold (4 °C) acetone (80% v/v) over-night, then centrifuged at 13500 rpm at 4°C for 15 min.

The supernatant was removed and the pellet was air-dried and then solubilized in the focusing

solution 8 M urea, 4% (w/v) CHAPS, 0.5% (w/v) pH 4-7 carrier ampholyte (Bio-lyte; Bio-Rad,

Hercules, CA, USA) and 40 mM Tris base with continuous stirring.

Proteins were subsequently reduced (10 mM tributylphosphine, 1 h) and alkylated (40 mM IAA,

1h). To prevent over-alkylation, iodoacetamide (IAA) excess was destroyed by adding 10 mM

DTE. Isoelectrofocusing (IEF) was performed using Biorad Multiphore II and ready–to–use

Immobiline Dry–Strips linear pH gradient 3–10 length 18 cm (BioRad, Hercules, CA, USA) and the

in gel sample rehydration method. IEF was run on a BioRad Protean IEF and the total product time

× voltage applied was 70000 V h for each strip at 20 °C. After IEF, the IPG gel strips were

incubated at room temperature for 30 min in 6 M urea, 30% w/v glycerol, 2% w/v SDS, 5 mM

Tris–HCl, pH 8.6.

The strips were sealed at the top of a 1.0 mm vertical second dimensional gel (BioRad, Hercules,

CA, USA) with 0.5% agarose in 25 mM Tris, 192 mM glycine, 0.1% SDS, pH 8.3. SDS–PAGE

was carried out on homogeneous running gel 16 cm × 20 cm, 12% acrylamide.

The running buffer was 25 mM Tris, 192 mM glycine, 0.1% SDS, pH 8.3; running conditions

were 40 mA/gel until the bromophenol blue reached the bottom of the gel; the molecular weight

marker was Wide Range SigmaMarkerTM

(Sigma, St. Louis, MO, USA). Gels were automatically

stained with Brilliant Blue G colloidal (Sigma, St. Louis, MO, USA) following the manufacturer’s

instructions. Three technical replicates per sample and three biological replicates were performed

for each plant treatment, for a total of 36 gels. The 2D image analysis was carried out and spots

were detected and quantified using the Progenesis SameSpots software v.2.0.2733.19819 software

package (Nonlinear Dynamics, Newcastle UK). Each gel was analysed for spot detection and

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background subtraction. Within-group comparison of protein spot numbers was determined by

repeated measure.

Image analysis

Two dimension gel images were digitized using a flatbed scanner (model ImageScanner-II, GE

Healthcare, Uppsala, Sweden) with a resolution of 300 dpi and 16-bit greyscale pixel depth. Image

analysis was carried out with Progenesis SameSpots software vers. 2.0 (Nonlinear Dynamics, UK),

which allows spot detection, background subtraction, and protein spot OD intensity quantification

(spot quantity definition). The gel image showing the highest number of spots and the best protein

pattern was chosen as a reference template, and spots in a standard gel were then matched across all

gels. Spot quantity values were normalized in each gel dividing the raw quantity of each spot by the

total quantity of all the spots included in the standard gel. For each protein spot, the average spot

quantity value and its variance coefficient in each group was determined. One-way analysis of

variance (ANOVA) was carried out at p < 0.05 in order to assess for absolute protein changes

among the different treatments; only 4-fold or higher quantitative variations were taken into

consideration. Principal component analysis (PCA) was also calculated according to Valledor and

Jorrín84

and it is included in the SameSpots software package. The least significant difference

(LSD) test was used to determine significant differences among group means.

In-Gel Digestion

Spots from 2–DE maps were carefully excised from the gels and subjected to in–gel trypsin

digestion according to Shevchenko et al.85

with minor modifications. The gel pieces were swollen

in a digestion buffer containing 50 mM NH4HCO3 and 12.5 ng/ml trypsin (modified porcine

trypsin, sequencing grade, Promega, Madison, WI, USA) in an ice bath. After 30 min, the

supernatant was removed and discarded; then 20 ml of 50 mM NH4HCO3 was added to the gel

pieces and digestion was allowed to proceed overnight at 37°C. The supernatant containing the

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peptide mixture was removed and acidified with 5% formic acid before injection in the mass

spectrometer.

Protein Identification by MS/MS

Peptide mixtures were separated using Ultimate–Switchos–Famos HPLC system (LC Packings,

Amsterdam, The Netherlands). A sample volume of 14 µl was loaded by the autosampler onto a

homemade 2 cm fused silica precolumn (75 µm I.D.; 375 µm O.D) Reprosil C18–AQ, 3 µm

(GmBH, Ammerbuch–Entringen, DE) at a flow rate of 2 µl/min. Sequential elution of peptides was

accomplished using a flow rate of 200 nl/min and a linear gradient from Solution A (2%

acetonitrile; 0.1% formic acid) to 50% of Solution B (98% acetonitrile; 0.1% formic acid) in 40

minutes over the precolumn in–line with a homemade 10–15 cm resolving column (75 µm I.D.; 375

µm O.D.; Reprosil C18–AQ, 3 µm, Dr. Maisch GmbH, Ammerbuch–Entringen, Germany).

Peptides were eluted directly into a High Capacity ion Trap HCTplus (Bruker–Daltonik, Bremen,

Germany). Capillary voltage of 1.5–2 kV and a dry gas flow rate of 10 L/min were used at a

temperature of 230 °C. The scan range used was from 300 to 1800 m/z. Protein identification was

performed by searching in the National Centre for Biotechnology Information non–redundant

database (NCBInr, version 20081128, www.ncbi.nlm.nih.gov) using the MASCOT software in–

house version 2.2 (Matrix Science, London, UK). The following parameters were adopted for

database searches: complete carbamidomethylation of cysteines and partial oxidation of

methionines, peptide Mass Tolerance ±1.2 Da, Fragment Mass Tolerance ±0.9 Da, missed

cleavages 2. Only result scores [−10 x Log(P)] over the significance threshold level (P < 0.05) were

identified as positive. Even when high MASCOT scores were obtained (values >60), if proteins

were identified only by a single peptide, a combination of automated database search and a manual

interpretation of peptide fragmentation spectra was used to validate protein assignments. The mass

error, the presence of fragment ion series and the expected prevalence of C–terminus containing

ions (Y–type) in the high mass range were all taken into account in the verification procedure.

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Gene expression studies

RNA extraction was performed from 70 mg of the powder with a "NucleoSpin®

RNA Plant"

(MACHEREY-NAGEL) kit following the manufacturer's instructions. The quality and concentration of

RNA samples were examined by GelRed (BIOLINE) stained agarose gel electrophoresis and

spectrophotometric analysis.

One µg of total RNA was reverse-transcribed using oligo (dT)20 primers (Invitrogen), 0,5 mM

dNTPs and 200 U of ImProm-IITM

reverse transcriptase (PROMEGA) according to the

manufacturer’s instructions. cDNA amplification was performed over 25 cycles in a Progene

Termal cycler using BIOTAQTM

(BIOLINE) DNA Polymerase according to the manufacturer's

instructions under the following conditions: denaturation at 95 °C for 1 min, annealing for 1 minute

at different temperatures, depending on the primers used, and elongation at 72 °C for 1 min. The

specific primers were designed according to their known sequence (Table 2). To normalize the

quantity of RNA used for cDNA synthesis, cDNA was amplified with specific primers for UBI10,

according to the above protocol. The primers for UBI10 expression were used also to identify

possible contamination of RNA by genomic DNA. All the products of RT-PCR amplification were

analyzed on agarose gel 1.5% (w/v) according to the protocol proposed by Sambrook et al.86

.

Acknowledgements

This research was supported by the Ministero dell’Istruzione, Università e Ricerca Scientifica

(MIUR), project MIUR-FIRB (RBNE01KZE7).

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References

1 E. Kombrink and E. Schmelzer, European J Plant Pathol, 2001, 107, 69-78.

2 K. Apel and H. Hirt, Annu Rev Plant Biol, 2004, 55, 373-399.

3 L. Sticher, B. Mauch-Mani and Métraux JP, Annu Rev Plant Pathol, 1997, 35, 235-270.

4 J.A. Ryals, U.H. Neuenschwander, M.G. Willits, A. Molina, H.Y. Steiner and M.D. Hunt, Plant

Cell, 1996, 8, 1809-1819.

5 R. Bari and J.D.G. Jones, Plant Mol Biol, 2009, 69, 473-488.

6 C.M.J. Pieterse, A. Leon-Reyes, S. Van der Ent and S.C.M. Van Wees, Nat Chem Biol, 2009, 5,

308-316.

7 A. Verhage, S.C.M. van Wees and C.M.J. Pieterse, Plant Physiol, 2010, 154, 536-540.

8 J. Glazebrook, Annual Review of Phytopathology, 2005, 43, 205-227.

9 A. Leon-Reyes, Y. Du, A. Koornneef, S. Proietti, A.P. Korbes, J. Memelink, C.M.J. Pieterse and

T. Ritsema, Mol Plant-Microbe Interact, 2010, 23, 187-197.

10 P.M. Schenk, K. Kazan, I. Wilson, J.P. Anderson, T. Richmond, S.C. Somerville and J.M.

Manners, Proc Natl Acad Sci USA, 2000, 97, 11655-11660.

11 Y.H. Cheong, H.S. Chang, R. Gupta, X. Wang, T. Zhu and S. Luan, Plant Physiol, 2002,129,

661-677.

12 R.M. Bostock, Annu Rev Phytopath, 2005, 43, 545-580.

13 S.H. Spoel and X. Dong, Cell Host & Microbe, 2008, 3, 348-351.

14 M.R. Grant and J.D.G. Jones, Science, 2009, 324, 750-752.

15 C.M.J. Pieterse, D. Van der Does, C. Zamioudis, A. Leon-Reyes and S.C.M. Van Wees, Annu

Rev Cell Dev Biol, 2012, 28, 489-521.

16 B. Mauch-Mani and F.Mauch, Curr Opin Plant Biol. 2005, 8, 409-414.

17 N. Beaudoin, C. Serizet, F. Gosti and J. Giraudat, Plant Cell, 2000, 12, 1103-1115.

18 M. Ghassemian, E. Nambara, S. Cutler, H. Kawaide, Y. Kamiya and P. McCourt, Plant Cell,

Page 26 of 48Molecular BioSystems

Mo

lecu

lar

Bio

Sys

tem

s A

ccep

ted

Man

usc

rip

t

Dow

nloa

ded

by S

tate

Uni

vers

ity o

f N

ew Y

ork

at B

uffa

lo o

n 15

/04/

2013

19:

58:2

2.

Publ

ishe

d on

10

Apr

il 20

13 o

n ht

tp://

pubs

.rsc

.org

| do

i:10.

1039

/C3M

B25

569G

View Article Online

26

2000, 12, 1117-1126.

19 C.J. Jiang, M. Shimono, S. Sugano, M. Kojima, K. Yazawa, R. Yoshida, H. Inoue, N. Hayashi,

H. Sakakibara and H. Takatsuji, Mol Plant-Microbe Interact, 2010, 23, 791-798.

20 M. Fujita, Y. Fujita, Y. Noutoshi, F. Takahashi, Y. Narusaka, K. Yamaguchi-Shinozaki and

Shinozaki K, Curr Opin Plant Biol, 2006, 9, 436-442.

21 M. De Torres-Zabala, M.H. Bennett, W.H. Truman and M.R. Grant, Plant Journal, 2009, 59,

375-38.

22 D. De Vleesschauwer, Y. Yang, C.V. Cruz and M. Hofte, Plant Physiol, 2010, 152, 2036-2052.

23 J. Ton, V. Flors and B. Mauch-Mani, Trends Plant Sci, 2009, 14, 310-317.

24 M.J. Pozo, L.C. Van Loon and C.M.J. Pieterse, J Plant Growth Regul, 2004, 23, 211-222.

25 L.C. Van Loon, B.P.J. Geraats and H.J.M. Linthorst, Trends Plant Sci, 2006, 11, 184-191.

26 G. Loake and M. Grant, Curr Opin Plant Biol, 2007, 10, 466-472.

27 J. Glazebrook, W. Chen, B. Estes, H-S Chang, C. Nawrath, J-P Metraux, T. Zhu and F. Katagiri,

Plant Journal, 2003, 31, 217–228.

28 F. Katagiri, Curr Opin Plant Biol, 2004, 7, 506-511.

29 L. Rajjou, M. Belghazi, R. Huguet, C. Robin, A. Moreau, C. Job and D. Job, Plant Physiol,

2006, 141, 910-923.

30 Y. Jiang, B. Yang, N.S. Harris and M.K. Deyholos, J Exp Bot, 2007, 4, 1-17.

31 S. Chivasa, J.M. Hamilton, R.S. Pringle, B.K. Ndimba, W.J. Simon, K. Lindsey, A.R. and

Slabas, J Exp Bot, 2006, 57 (7), 1553-1562.

32 R.M. Collins, M. Afzal, D.A. Ward, M.C. Prescott, S.M. Sait, H.H. Rees and A.B. Tomsett,

PLoS One, 2010, 5 (4), 1-14.

33 Park M.A., Seo J.H., Park J.S. and M. Kwon, Plant Cell Rep, 2009, 28, 1603-1614.

34 J.N. Cape, Environ Pollut, 2003, 122, 145-157.

35 C.H. Foyer and G. Noctor, Physiol Plant, 2003, 119, 355-364.

36 C.H. Foyer and G.Noctor, Plant Cell, 2005, 17, 1866-1875.

Page 27 of 48 Molecular BioSystems

Mo

lecu

lar

Bio

Sys

tem

s A

ccep

ted

Man

usc

rip

t

Dow

nloa

ded

by S

tate

Uni

vers

ity o

f N

ew Y

ork

at B

uffa

lo o

n 15

/04/

2013

19:

58:2

2.

Publ

ishe

d on

10

Apr

il 20

13 o

n ht

tp://

pubs

.rsc

.org

| do

i:10.

1039

/C3M

B25

569G

View Article Online

27

37 C.C.C. Chang, L. Ball, M.J. Fryer, N.R. Baker, S. Karpinski and P.M. Mullineaux, Plant J,

2004, 38, 499-511.

38 I.C. Mori and J.I. Schroeder, Plant Physiol, 2004, 135, 702-708.

39 R. Shin and D.P. Schachtman, Proc Natl Acad Sci USA, 2004, 101, 8827-8832.

40 J.M. Kwak, I.C. Mori, Z-M Pei, N. Leonhardt, M.A. Torres, J.L. Dangl, R.E. Bloom, S. Bodde,

J.D.G. Jones and J.I. Schroeder, EMBO J, 2003, 22, 2623-2633.

41 M. Nishimura, Y.D. Akhmedov, K. Strzalka and T. Akazawa, Arch Biochem Biophys, 1983,

222, 397-402.

42 M.L. Orozco-Cardenas, J. Narvaez-Vasquez and C.A. Ryan, Plant Cell, 2001,13, 179-191.

43 H. Fahnenstich, T.E. Scarpeci, E.M. Valle, U-I Flugge, V.G. Maurino, Plant Physiol, 2008, 148,

719-729.

44 S. Reumann, in Plant Peroxisomes: Biochemistry, Cell Biology and Biotechnological

Applications ed. A. Baker and I.A. Graham, Kluwer Academic Publishers, Dordrecht, 2002, pp.

141-189.

45 B.J. Shelp , R.T. Mullen and J.C. Waller. Trends Plant Sci., 2012, 17(2), 57-9.

46 V. Pavet, E. Olmos, G. Kiddle, S. Mowla, S. Kumar, J. Antoniw, M.E. Alvarez and C.H. Foyer.

Plant Physiol, 2005, 139,1291-1303.

47 F. Van Breusegem and J.F. Dat. Plant Physiol, 2006, 141, 384-390.

48 R.I. Pennell and C. Lamb. Plant Cell, 1997, 9, 1157-1168.

49 J. Zeier, B. Pink, M.J. Mueller and S. Berger. Planta, 2004, 219, 673-683.

50 J.I. Moreno, R. Martin and C. Castresana. Plant Journal, 2005, 41, 451-463.

51 J.A. Jebanathirajah and J.R. Coleman. Planta, 1998, 204, 177-182.

52 D.H. Slaymaker, D.A. Navarre, D. Clark, O. Del Pozo, G.B. Martin and D.F. Klessig. Proc Natl

Acad Sci USA, 2002, 99, 11640-11645.

53 W. Moeder, O. Del Pozo, D.A. Navarre, G.B. Martin and D.F. Klessig. Plant Mol Biol, 2007, 63

(2), 273-287.

Page 28 of 48Molecular BioSystems

Mo

lecu

lar

Bio

Sys

tem

s A

ccep

ted

Man

usc

rip

t

Dow

nloa

ded

by S

tate

Uni

vers

ity o

f N

ew Y

ork

at B

uffa

lo o

n 15

/04/

2013

19:

58:2

2.

Publ

ishe

d on

10

Apr

il 20

13 o

n ht

tp://

pubs

.rsc

.org

| do

i:10.

1039

/C3M

B25

569G

View Article Online

28

54 L.A. Mur, P. Kenton, R. Atzorn, O. Miersch and C. Wasternack. Plant Physiol, 2006, 140, 249-

262.

55 A. Youssef, Y. Laizet, M.A. Block, E. Maréchal, J.P. Alcaraz, T.R. Larson, D. Pontier, J. Gaffé

and M. Kuntz. Plant Journal, 2010, 61, 436-445.

56 J. Yan, J. Wang and H. Zhang. Plant Journal, 2002, 29, 193-202.

57 P. Krishna. J Plant Growth Regulat, 2003, 22, 289-297.

58 A. Alonso-Ramirez, D. Rodriguez, D. Reyes, J.A. Jimenez, G. Nicolas, M. Lopez-Climent, A.

Gomez-Cadenas and C. Nicolas, Plant Physiol, 2009, 150, 1335-1344.

59 U.K. Divi, T. Rahman and P. Krishna, BMC Plant Biol, 2011, 10, 151-164.

60 X.Y. Jia, C.Y. Xu, R.L. Jing, R.Z. Li, X.G. Mao, J.P. Wang and X.P. Chang, J Exp Bot, 2008,

59, 739-751.

61 J. Shaterian, F. Georges, A. Hussain, D. Waterer, H.D. Jong and K.K. Tanino, Environ Exp Bot,

2005, 53, 323-332.

62 E.P. Jelitto-Van Dooren, S. Vidal and J. Denecke, Plant Cell, 1999, 11, 1935-1944.

63 F. Chen, P.M. Hayes, D.M. Mulrooney and A. Pan, Plant Cell, 1994, 6, 835-843.

64 J. Denecke, L.E. Carlsson, S. Vidal, A.S. Hoglund, B. Ek, M.J. van Zeijl, K.M. Sinjorgo and

E.T. Palva, Plant Cell, 1995, 7, 391-406.

65 J.M. Kuhn and J.I. Schroeder, Curr Opin Plant Biol, 2003, 6, 463-469.

66 S. Raab, Z. Toth, C. de Groot, T. Stamminger and S. Hoth, Planta, 2006, 224, 900-914.

67 J. Kurepa, J.M. Walker, J. Smalle, M.M. Gosink, S.J. Davis, T.L. Durham, D-Y Sung, R.D.

Vierstra, J Biol Chem, 2003, 278, 6862-6872.

68 L.M. Lois, C.D. Lima and N-H. Chua, Plant Cell, 2003, 15, 1347-1359.

69 T. Ghelis, G. Bolbach, G. Clodic, Y. Habricot, E. Miginiac, B. Sotta and E. Jeannette, Plant

Physiol, 2008,148 (3), 1668-1680.

70 M.E. Feder and G.E. Hofmann, Annu Rev Physiol, 1999, 61, 243-282.

71 J. Larkindale, J.D. Hall, M.R. Knight and E.Vierling, Plant Physiol, 2005, 138, 882-897.

Page 29 of 48 Molecular BioSystems

Mo

lecu

lar

Bio

Sys

tem

s A

ccep

ted

Man

usc

rip

t

Dow

nloa

ded

by S

tate

Uni

vers

ity o

f N

ew Y

ork

at B

uffa

lo o

n 15

/04/

2013

19:

58:2

2.

Publ

ishe

d on

10

Apr

il 20

13 o

n ht

tp://

pubs

.rsc

.org

| do

i:10.

1039

/C3M

B25

569G

View Article Online

29

72 G.M. Pastori and H. Foyer, Plant Physiol, 2002, 129, 460-468.

73 U. Härndahl, R.B. Hall, K.W. Osteryoung, E. Vierling, J.F. Bornman and C. Sundby, Cell Stress

Chaperones, 1999, 4, 129-138.

74 W. Swindell, M. Hebner and A.P. Weber, BMC Genomics, 2007, 8, 125.

75 J.D.G. Jones and J.I. Schroeder, EMBO J, 2003, 22, 2623-2633.

76 H.Foyer, J. Bloom, G. Queval and G.Noctor, Annu Rev of Plant Biol, 2009, 60, 455- 484.

77 S. Kangasjärvi, J. Neukermans, S. Li, E.-M. Aro and G. Noctor, J Exp Bot, 2012, 63 (4), 1619-

1636.

78 U. Conrath, Z. Chen, J.R. Ricigliano and D.F. Klessig, Proc Natl Acad Sci USA, 1995, 92, 7143-

7147;

79 J. Durner and D.F. Klessig, J Biol Chem, 1996, 271, 28492-28501.

80 Z. Chen, S. Iyer, A. Caplan, D.F. Klessig and B. Fan, Plant Physiol, 1997, 114, 193-201.

81 P. Reymond and E.E. Farmer, Curr Opin Plant Biol, 1998, 1, 404-411.

82 C.M.J. Pieterse, S.C.M. Van Wees, J.A. Van Pelt, M. Knoester, R. Laan, H. Gerrits, P.J.

Weisbeek and L.C. Van Loon, Plant Cell, 1998, 10, 1571-1580.

83 M.M. Bradford, Analyt Bioch, 1976, 72, 248-254.

84 L. Valledor and J. Jorrin, J Proteomics, 2011, 74, 1-18.

85 A. Shevchenko, M. Wilm, O. Vorm and M. Mann, Anal Chemi, 1996, 68, 850-858.

86 J. Sambrook, E.F. Fritsch and T. Maniatis, in Molecular Cloning: A Laboratory Manual, ed.

Cold Spring Harbor Laboratory Press, Cold Spring Harbor, NY, USA, 2nd edn, 1989.

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Legends to figures

Fig. 1

2D-SDS PAGE of Arabidopsis leaf proteins. Equal amount (900 µg) of total proteic extract from

SA- (a), JA- (b) or SA/JA- (c) treated plants as well as of control plants (d) were loaded into 12%

acrylamide SDS gels as reported in Experimental section. Numbers and arrows in a, b and c

indicate analyzed spots corresponding to proteins overexpressed at least four- fold with respect to

the control. Fig. 1e shows the reference map derived from computerized image analysis performed

by using Progenesis SameSpots software.

Fig. 2

Level of expression of protein spots analyzed by LC-ESI-MS/MS. For each selected spot the

expression level upon each treatment has been calculated relatively to the control. Arabidopsis

plants treated with SA (white dotted bars) or JA (black bars) alone or in combination (grey bars).

Proteins are grouped on the basis on their involvement in the crosstalk between SA and JA. Panels

show proteins involved in: negative crosstalk by SA on JA pathway (a), negative crosstalk by JA on

SA pathway (b), antagonistic (c) and synergistic (d) crosstalk between SA and JA.

Fig. 3

Semi-quantitative RT-PCR analysis of genes coding for the proteins involved in oxidative stress

and biotic and/or abiotic stress listed in Table 1.

ACO2 (aconitase 2); SHM1 (serine hydroxymethyl transferase 1); GGAT1 (glutamate:glyoxylate

aminotranferase 1); CAT3 (catalase 3); GABA-T (gamma-aminobutyrate transaminase); CAT2

(catalase 2); SHM4 (serine hydroxymethyl transferase 4); FIBR (fibrillin); MOA2.2 ((S)-2-

hydroxy-acid oxidase, peroxisomal, putative/glycolate oxidase); MOA2.13 ((S)-2-hydroxy-acid

oxidase, peroxisomal, putative/glycolate oxidase); AKR (ankyrin repeat-containing protein 2);

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PHMD2 (peroxisomal NAD-malate dehydrogenase 2); CA2 (carbonic anhydrase 2); CA1 (carbonic

anhydrase 1); CTR1B (calreticulin 1B); CRB (chloroplast RNA binding); TRIP1 (TGF-beta

receptor interacting protein 1); HSP20 (HSP20-like chaperone); EF1B (elongation factor 1B alpha-

subunit 2); NADEPI (NAD-dependent epimerase/dehydratase)

Fig. 4

First steps of the photorespiratory metabolism. Enzymes involved in catalyzing the reactions are

indicated in red.

Fig. 5

Gene ontology categorization: Biological process in which are involved the identified proteins

listed in Table 1

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2D-SDS PAGE of Arabidopsis leaf proteins. Equal amount (900 µg) of total proteic extract from SA- (a), JA- (b) or SA/JA- (c) treated plants as well as of control plants (d) were loaded into 12% acrylamide SDS gels

as reported in Experimental section. Numbers and arrows in a, b and c indicate analyzed spots

corresponding to proteins overexpressed at least four-fold with respect to the control. Fig. 1e shows the reference map derived from computerized image analysis performed by using Progenesis SameSpots

software. 254x338mm (300 x 300 DPI)

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Level of expression of protein spots analyzed by LC-ESI-MS/MS. For each selected spot the expression level upon each treatment has been calculated relatively to the control. Arabidopsis plants treated with SA (white dotted bars) or JA (black bars) alone or in combination (grey bars). Proteins are grouped on the basis on

their involvement in the crosstalk between SA and JA. Panels show proteins involved in: negative crosstalk by SA on JA pathway (a), negative crosstalk by JA on SA pathway (b), antagonistic (c) and synergistic (d)

crosstalk between SA and JA. 254x338mm (300 x 300 DPI)

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Semi-quantitative RT-PCR analysis of genes coding for the proteins involved in oxidative stress and biotic and/or abiotic stress listed in Table 1.

ACO2 (aconitase 2); SHM1 (serine hydroxymethyl transferase 1); GGAT1 (glutamate:glyoxylate

aminotranferase 1); CAT3 (catalase 3); GABA-T (gamma-aminobutyrate transaminase); CAT2 (catalase 2); SHM4 (serine hydroxymethyl transferase 4); FIBR (fibrillin); MOA2.2 ((S)-2-hydroxy-acid oxidase,

peroxisomal, putative/glycolate oxidase); MOA2.13 ((S)-2-hydroxy-acid oxidase, peroxisomal, putative/glycolate oxidase); AKR (ankyrin repeat-containing protein 2); PHMD2 (peroxisomal NAD-malate

dehydrogenase 2); CA2 (carbonic anhydrase 2); CA1 (carbonic anhydrase 1); CTR1B (calreticulin 1B); CRB (chloroplast RNA binding); TRIP1 (TGF-beta receptor interacting protein 1); HSP20 (HSP20-like chaperone);

EF1B (elongation factor 1B alpha-subunit 2); NADEPI (NAD-dependent epimerase/dehydratase)

121x176mm (300 x 300 DPI)

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First steps of the photorespiratory metabolism. Enzymes involved in catalyzing the reactions are indicated in red

121x176mm (300 x 300 DPI)

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Gene ontology categorization: Biological process in which are involved the identified proteins listed in Table 1

121x176mm (300 x 300 DPI)

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Table 1: Identification of differentially expressed proteins from plant treated by SA, JA and SA/JA

Spot Gene code Gene name start-end Matched peptides in database Mascot

score

Sequence

coverage

Obs

mass/p.I.

Theo

mass/p.I.

Fold difference

JA SA SA/JA

Photosynthesis

177 AtCg00490 RBCL, LARGE

SUBUNIT OF

RUBISCO

22 - 32

33 - 41 129 - 134

135 - 146

147 - 159

165 - 177

178 - 183

202 - 213

228 - 236

237 - 252

286 - 295

296 - 303

320 - 334

335 - 350

340 - 350

351 –358

432 - 446

436 - 446

451 - 463

K.LTYYTPEYETK.D

K.DTDILAAFR.V K.ALAALR.L

R.LEDLRIPPAYTK.T

K.TFQGPPHGIQVER.D

K.YGRPLLGCTIKPK.L

K.LGLSAK.N

K.DDENVNSQPFMR.W Oxid (M)

K.SQAETGEIK.G

K.GHYLNATAGTCEEMIK.R Oxid (M)

R.DNGLLLHIHR.A

R.AMHAVIDR.Q Oxid (M)

R.LSGGDHIHAGTVVGK.L

K.LEGDRESTLGFVDLLR.D

R.ESTLGFVDLLR.D

R.DDYVEKDR.S

R.NEGRDLAVEGNEIIR.E

R.DLAVEGNEIIR.E

K.WSPELAAACEVWK.E

38

65 29

26

89

33

37

82

59

64

54

42

56

28

66

29

23

66

79

41% 58.0/4.3 53.4/5.88 +9.43 +13.97 +3.51

200 AtCg00490 RBCL, LARGE

SUBUNIT OF

RUBISCO

9 - 14 22 - 32

33 - 41

129 - 134 129 - 139

135 - 146

K.ASVGFK.A K.LTYYTPEYETK.D

K.DTDILAAFR.V

K.ALAALR.L K.ALAALRLEDLR.I

R.LEDLRIPPAYTK.T

15 47

54

42 22

37

42% 58.2/4.25 53.4/5.88 +8.76 +13.13 +2.98

Page 39 of 48 Molecular BioSystems

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140 - 146

147 - 159

165 - 177

178 - 183

188 - 194

195 –201

202 - 213

228 - 236

237 - 253

286 - 295

296 - 303 320 - 334

340 - 350

351 - 358 436 - 446

451 - 463

R.IPPAYTK.T

K.TFQGPPHGIQVER.D

K.YGRPLLGCTIKPK.L

K.LGLSAK.N

R.AVYECLR.G

R.GGLDFTK.D

K.DDENVNSQPFMR.W

Oxid (M)

K.SQAETGEIK.G

K.GHYLNATAGTCEEMIKR

.A Oxid (M)

R.DNGLLLHIHR.A

R.AMHAVIDR.Q Oxid (M) R.LSGGDHIHAGTVVGK.L

R.ESTLGFVDLLR.D

R.DDYVEKDR.S R.DLAVEGNEIIR.E

K.WSPELAAACEVWK.E

26

89

35

34

32

59

57

70

36

71

43 63

21

53 80

73

205 AtCg00490 RBCL, LARGE

SUBUNIT OF

RUBISCO

22 - 32

33 - 41 129 - 134

147 - 159

165 - 177

188 - 194

195 - 201

202 - 213

218 - 227

228 - 236

237 - 252

237 - 253

286 - 295

296 - 303

304 - 312

K.LTYYTPEYETK.D

K.DTDILAAFR.V K.ALAALR.L

K.TFQGPPHGIQVER.D

K.YGRPLLGCTIKPK.L

R.AVYECLR.G

R.GGLDFTK.D

K.DDENVNSQPFMR.W

R.FLFCAEAIYK.S

K.SQAETGEIK.G

K.GHYLNATAGTCEEMIK.R Oxid (M)

K.GHYLNATAGTCEEMIKR

.A Oxid (M)

R.DNGLLLHIHR.A

R.AMHAVIDR.Q

R.QKNHGMHFR.V Gln-

>pyro-Glu (N-term Q)

47

66 36

85

33

31

53

78

57

53

73

26

27

52

20

42% 57.4/4.8 53.4/5.88 +2.77 +4.95 +1.83

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306 - 312

320 - 334

335 - 350

340 - 350

351 - 358

436 - 446

451 - 463

K.NHGMHFR.V

R.LSGGDHIHAGTVVGK.L

K.LEGDRESTLGFVDLLR.D

R.ESTLGFVDLLR.D

R.DDYVEKDR.S

R.DLAVEGNEIIR.E

K.WSPELAAACEVWK.E

11

60

31

66

37

54

76

475 At1g67090 F5A8.1, F5A8_1,

RBCS1A, F1O19.14,

RIBULOSE

BISPHOSPHATE

CARBOXYLASE

SMALL CHAIN 1A

127 - 140

156 - 163

K.LPLFGCTDSAQVLK.E

R.IIGFDNTR.Q

68

34

12% 24.5/8.1 20.5/8.2 +0.57 +0.84 +7.12

Protein involved in ATP synthesis

193 AtCg00120 ATPA, ATP

SYNTHASE SUBUNIT

ALPHA

95 -107 129 -140

481 -491

K.IAQIPVSEAYLGR.V R.LIESPAPGIISR.R

K.TLTAEAESFLK.E

38 59

61

7% 60.5/8.4 55.3/5.2 +10.34 +1.48 +1.37

213 AtCg00480 PB, ATPB, ATP

SYNTHASE SUBUNIT

BETA

3 - 15

135 -145

146 -154

R.TNPTTSNPEVSIR.E

K.SAPAFIELDTK.L

K.LSIFETGIK.V

10

34

28

6% 56.1/3.6 53.9/5.38 +19.87 +14.76 +2.02

214 AtCg00480 PB, ATPB, ATP

SYNTHASE SUBUNIT

BETA

3 - 15

40 - 50

135 -145

146 -154

168 -178 179 -191

R.TNPTTSNPEVSIR.E

K.MPNIYNALVVK.G

Oxid(M)

K.SAPAFIELDTK.L

K.LSIFETGIK.V

K.IGLFGGAGVGK.T K.TVLIMELINNIAK.A

Oxid (M)

7

24

28

39

16 22

13% 56.1/3.95 53.9/5.38 +22.14 +25.70 +4.79

523 At1g79550 PGK, T8K14.3, T8K14_3,

80 - 96 K.GVTTIIGGGDSVAAVEK.V

93 12% 13.2/4.2 13.3/4.44 +0.75 +6.91 +2.34

Page 41 of 48 Molecular BioSystems

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PHOSPHOGLYCERA

TE KINASE

Oxidative stress

106 At4g26970

CO2, F10M23.310, F10M23_310,

ACONITASE 2

142 -149 945- 962

R.ILLESAIR.N K.VSDIRPGQDVTVTTDS

GK.S

36 43

2% 106.0/6.35

108.9/6.85 +0.75 +1.34 +4.87

173 At4g37930

STM, SHM1, SHMT1,

SERINE HYDROXY-

METHYL

TRANSFERASE 1

102 -110

218 -225 226 -236

237 -242

293 -299

354 -365

366 -373

404 -414

415 -430

431 -439

440 -448 449 -455

456 -462

492 -501

494 -501

502 -510

K.YSEGYPGAR.Y

K.SATLFRPK.L K.LIVAGASAYAR.L

R.LYDYAR.I

R.GAMIFFR.K Oxid (M)

K.AYQEQVLSNSAK.F

K.FAQTLMER.G Oxid (M)

K.VLEAVHIASNK.N

K.NTVPGDVSAMVPGGIR.

M Oxid (M)

R.MGTPALTSR.G Oxid (M)

R.GFVEEDFAK.V K.VAEYFDK.A

K.AVTIALK.V

K.LRHEVEEFAK.Q

R.HEVEEFAK.Q

K.QFPTIGFEK.E

50

29 87

16

42

99

50

88

67

57

58 33

55

45

19

45

26%

61.0/7.7

57.5/8.13

+4.84 +1.53 +1.43

179 At1g23310

GGT1, AOAT1,

GGAT1, F26F24.16,

GLUTAMATE:

GLYOXYLATE

AMINOTRANSFERASE, GLUTAMATE:

GLYOXYLATE

AMINOTRANSFERASE 1, ALANINE-2-

OXOGLUTARATE

AMINOTRANSFERASE 1

91 -107

115 -122

142 -152

142 -152

268 -279

268 -279

269 -279

269 -279

K.HYLSLTSGGLGAYSDSR.

G K.EVAEFIQR.R

K.GVMQILNCVIR.G

K.GVMQILNCVIR.G

Oxid(M) K.KVLMEMGSPFSK.E

K.KVLMEMGSPFSK.E 2

Oxid (M) K.VLMEMGSPFSK.E

K.VLMEMGSPFSK.E

Oxid(M)

84

42

90

43

42

56

84

62

34% 57.2/9.1 53.7/6.5 +6.01 +0.66 +1.91

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280 -291

280 -291

292 -300

301 -312

313 -319

358 -364

369 -378

397 -406

407 -419

411 -419

420 -437 438 -444

K.EVQLVSFHTVSK.G Glu-

>pyro-Glu (N-term E)

K.EVQLVSFHTVSK.G

K.GYWGECGQR.G

R.GGYFEMTNLPPR.V

R.VVEEIYK.V

K.GILESLR.R

R.LMTDGFNSCK.N Oxid

(M)

R.LPTGALQAAK.Q

K.QAGKVPDVFYCLK.L

K.VPDVFYCLK.L

K.LLEATGISTVPGSGFGQK.E K.EGVFHLR.T Glu-

>pyro-Glu (N-term E)

95

68

61

45

48

34

65

71

64

28

25 40

187 At1g20620 CAT3 SEN2, ATCAT3,

CATALASE 3

38 - 50

92 -102 356 -369

406 -417

450 -458

R.GPVLLEDYHLIEK.V

R.APGVQTPVIVR.F R.LGPNYLQLPVNAPK.C

K.VPTPTNSYTGIR.T

R.WVEILSEPR.L

33

43 42

45

74

11% 61.0/7.95 57/8.31 +8.46 +2.29 +1.20

191

At3g22200 HER1, POP2, GABA-T,

MKA23.13, HEXENAL

RESPONSE1, POLLEN-

PISTIL

INCOMPATIBILITY 2,

GAMMA-

AMINOBUTYRATE

TRANSAMINASE

129 -138

139 -148

152 -167

229 -242

404 -416

417 -430

453 -458

R.TTKPSLDLAK.V

K.VLLEMFTANK.M Oxid

(M)

K.AFFTSGGSDANDTQVK.L

R.FHLPGETEEEFSTR.L

K.AFASGSPIIGETR.G

R.GTGLILGTEFVDNK.S

K.HGMLVR.V

38

51

134

68

106

76

36

16% 60.5/7.2 55.5/8.02 +2.97 +5.27 +1.30

199 At4g35090

CAT2, T12J5.2,

CATALASE 2

38 - 50 92 -102

201 -215

356 -369

402 -416

R.GPILLEDYHLVEK.L R.APGVQTPVIVR.F

R.HMDGSGVNTYMLIN

K.A 2 Oxid (M) R.LGPNYLQLPVNAPK.C

R.HAEKYPTPPAVCSGK.R

31 46

33

61

46

20% 59.8/7.4 57.2/6.63 +16.68 +5.76 +13.44

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420 -434

450 -458

486 -492

R.CIIEKENNFKEPGER.Y

R.WIDALSDPR.I

R.LNVRPSI.-

32

55

43

206 At4g13930 SHM4, DL3005C,

FCAALL.160, SERINE

HYDROXYMETHYL-

TRANSFERASE 4

184 -194

320 -332

363 -373

374 -389

390 -398

K.LLICGGSAYPR.D

K.ANAVALGNYLMSK.G Oxid (M)

K.LCDLCSITLNK.N

K.NAVFGDSSALAPGGVR.I

R.IGAPAMTSR.G Oxid (M)

64

91

64

52

48

12% 59.2/7.7 52.2/7.1 +15.02 +11.20 +1.78

278 At2g35490

T32F12.13, T32F12_13,

FIBRILLIN

116 -123

278 -287

325 -333

334 -340

359 -368

R.FMESDPPR.N Oxid (M)

K.EGTLKPPVIK.S Glu->

pyro-Glu (N-term E)

R.ALSGQPPLK.L

K.LPFPGNR.G

R.GDGGLFVLAR.E

30

28

24

38

68

11% 49.0/4.2 40.5/4.45 +5.75 +10.76 +6.60

299 At3g14420

MOA2.2, (S)-2-

HYDROXY-ACID

OXIDASE,

PEROXISOMAL,

PUTATIVE /

GLYCOLATE

OXIDASE, putative

1 - 14

51 - 57

58 - 68

69 - 82

83 - 94

125 -132

135 -142

151 -160 182 -190

215 -224

231 -239 240 -257

280 -289 280 -290

291 -296

-.MEITNVTEYDAIAK.Q

Oxid (M) R.ILIDVSK.I

K.IDMTTTVLGFK.I Oxid(M)

K.ISMPIMVAPTAMQK.M 3

Oxid (M)

K.MAHPDGEYATAR.A

Oxid(M)

R.FFQLYVYK.N

R.NVVEQLVR.R

K.AIALTVDTPR.L K.NFEGLDLGK.M

K.DVQWLQTITK.L

K.GVLTGEDAR.I R.IAIQAGAAGIIVSNHGAR.

Q

R.IPVFLDGGVR.R R.IPVFLDGGVRR.G

R.GTDVFK.A

55

41

88

57

39

22

50

70 49

36

67 43

59 33

31

46%

48.5/8.2

40.3/9.16

+8.87 +2.27 +3.31

Page 44 of 48Molecular BioSystems

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345 -351

352 -366

R.SLKEISR.N

R.NHITTEWDTPRPSAR.L

34

11

300

At3g14415

MOA2.13, S)-2-

HYDROXY-ACID

OXIDASE,

PEROXISOMAL,

PUTATIVE /

GLYCOLATE

OXIDASE, putative

1 - 14

51 - 57

58 - 68

69 - 82

83 - 94

125 -132

135 -142

136 -142

151 -160 172 -181

182 -190

215 -230

231 -239

240 -257

258 -274

280 -289

291 -296

332 -344

352 -362

-.MEITNVTEYDAIAK.A Oxid (M)

R.ILIDVNK.I

K.IDMATTVLGFK.I Oxid (M)

K.ISMPIMVAPTAFQK.M 2

Oxid (M)

K.MAHPDGEYATAR.A

Oxid (M)

R.FFQLYVYK.N

R.KVVEQLVR.R

K.VVEQLVR.R

K.AIALTVDTPR.L R.FTLPPNLTLK.N

K.NFEGLDLGK.M

K.DIQWLQTITNMPILVK.G Oxid (M)

K.GVLTGEDAR.I

R.IAIQAGAAGIIVSNHGAR.Q

R.QLDYVPATISALEEVVK.

A Gln->pyro-Glu (N-term Q

R.VPVFLDGGVR.R

R.GTDVFK.A

R.DEFELTMALSGCR.S

Oxid (M)

R.NHIVTEWDTPR.H

95

39

82 59

56

50

26

55

67

32 58

41

59

63

98

27

29

14

52

55%

47.0/8.5

40/8.99

+14.59 +1.89 +2.95

340 At4g35450 AFT, AKR2, AKR2A,

F15J1.20, F15J1_20,

ANKYRIN REPEAT-

CONTAINING

PROTEIN 2

236 -252

253 -265

319 -325 326 -334

335 -342

K.AALASGGNKDEEDSEGR

.T R.TALHFACGYGELK.C

K.TPIDVAK.L K.LNSQLEVVK.L

K.LLEKDAFL.-

68

17

29 85

40

15% 44.2/4.5 37.1/4.5 +5.86 +10.75 +3.48

380 At5g09660 PMDH2, F17I14.150, 113 -119 K.INAGIVK.T 46 15% 38.5/6.85 35.3/7.5 +1.06 +0.54 +6.49

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F17I14_150,

PEROXISOMAL

NAD-MALATE

DEHYDROGENASE 2

163 -173

227 -238

239 -254

255 -261

K.LLGVTTLDVAR.A

R.IQNGGTEVVEAK.A

K.AGAGSATLSMAYAAAK.

F Oxidation (M)

K.FADACLR.G

53

73

31

43

459 At5g14740 CA2, CA18, T9L3.40,

T9L3_40, BETA CA2,

CARBONIC

ANHYDRASE 2,

CARBONIC

ANHYDRASE 18,

BETA CARBONIC

ANHYDRASE 2

139 -151

185 -195

K.YETNPALYGELAK.G

R.NIANMVPPFDK.V

Oxidation (M)

54

53

8% 27.0/8.2

37.1/7.55 +5.2 +0.69 +0.53

468 At3g01500 CA1, SABP3, ATBCA1,

ATSABP3, F4P13.5, F4P13_5, CARBONIC

ANHYDRASE 1, BETA

CARBONIC ANHYDRASE 1

47 - 56

48 - 56 65 - 79

67 - 79 85 - 94

113 -123

113 -125

142 -157

187 -202

228 -233

234 -241

K.KAFDPVETIK.Q

K.AFDPVETIK.Q K.EKYETNPALYGELAK.G

Glu->pyro-Glu (N-term E)

K.YETNPALYGELAK.G K.YMVFACSDSR.V

R.NIANMVPPFDK.V Oxid

(M) R.NIANMVPPFDKVK.Y

Oxid(M)

K.VENIVVIGHSACGGIK.G

K.VISELGDSAFEDQCGR.C

K.GTLALK.G

K.GGYYDFVK.G

53

39 87

99 47

69

43

42

120

33

41

34% 25.2/6.0 29.8/5.54 +9.63 +0.98 +1.18

Biotic and/or abiotic stress

204 At1g09210 CRT1B, ATCRT1B,

T12M4.8, T12M4_8,

CALRETICULIN 1B

115 -123

115 -124

K.LLSGDVDQK.K

K.LLSGDVDQKK.F

42

31

2% 57.5/4.6 48.3/4.37 +2.95 +4.26 +1.47

296 At1g09340 CRB, CSP41B, HIP1.3, 56 - 63 K.ILIMGGTR.F Oxid (M) 51 31% 46.2/7.6 42.7/8.2 +0.63 +5.10 +0.92

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CHLOROPLAST RNA

BINDING,

HETEROGLYCAN-

INTERACTING

PROTEIN 1.3,

CHLOROPLAST

STEM-LOOP BINDING

PROTEIN

OF 41 KDA

109 -116

141 -154

155 -169

187 -200

189 -200

191 -200

252 -265

269 -277

278 -286

291 -305

361 -373

K.ILHLKGDR.K

R.EAEEVEPILEALPK.L

K.LEQYIYCSSAGVYLK.S

R.HKGKLETESLLQSK.G

K.GKLETESLLQSK.G

K.LETESLLQSK.G

K.DLATAFLNVLGNEK.A

R.EIFNISGEK.Y

K.YVTFDGLAK.A

K.AGGFPEPEIVHYNPK.E

K.EADFTTDDMILSK.K

Oxid (M)

34

47

84

27

40

19

28

41

25

13

75

302 At2g46280

TIF3I1, TRIP-1,

T3F17.7,

TGF-BETA

RECEPTOR

INTERACTING

PROTEIN 1

21 - 30

67 - 77 83 - 91

92 - 97

98 - 106 107 -118

202 -215

224 -229 304 -315

R.EGDLLFSCAK.D

R.LITGSADQTAK.L K.SGKELFTFK.F

K.FNAPTR.S

R.SVDFAVGDR.L R.LAVITTDHFVDR.T

K.AADDSHFLTGSLDK.T

R.TLTLLK.T K.SFSSGGEDGYVR.L

26

69 20

41

52 23

28

26 90

27%

45.8/7.7 36.5/6.90

+1.65 +4.44 +0.83

348 At4g02450 T14P8.5, T14P8_5,

HSP20-LIKE

CHAPERONE

9 - 15

16 - 26

30 - 43

44 - 54

55 - 67

61 - 73

68 - 73 74 - 81

93 -101

228 -238 228 -241

K.WAETTEK.I

K.IFLTVVLADTK.D

K.VNLDPEGVFDFSAK.V

K.VGPENHVYELK.L

K.LELADKVNVEESK.I

K.VNVEESKINIGER.S

K.INIGER.S R.SIFCIIEK.A

R.VKKPPHYVK.V

K.APAAEETTSVK.E K.APAAEETTSVKEDK.-

30

69

51

64

87

31

42 37

19

54 71

38% 42.5/4.2 28/4.4 +47.5 +166 +29.4

375 At5g19510

eEF1Balpha2,

ELONGATION

2 - 15

16 - 24

M.AVTFSDLHTEEGVK.S

K.SVEEHLAGK.T

99

48

24% 38.1/4.0 24.2/4.4 +0.63 +1.03 +6.07

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FACTOR 1B ALPHA-

SUBUNIT 2

57 - 67

153 -159

154 -159

160 -172

K.WYESVASQLAK.S

K.KLEEAVR.G

K.LEEAVR.G

R.GVEMPGLFWGASK.L

Oxid (M)

84

35

36

45

423 At5g02240 NAD-DEPENDENT

EPIMERASE/DEHYD

RATASE, SDR_a5

2 – 15

16 - 23

24 - 34

174 -185

M.ANLPTVLVTGASGR.T

R.TGQIVYKK.L

K.LKEGSDKFVAK.G

R.AGGLLDKEGGVR.E

43

20

25

14

17% 32.25/6.4 27.1/6.2 +6.3 +7.78 +1.20

2D-PAGE protein profiles from pooled SA, JA and SA/JA treated plants were compared to controls and differentially expressed proteins identified. Spot numbers refer to

Fig. 1. ‘Gene code’ refers to the unique identifier in the A. thaliana database (www.arabidopsis.org). Identified proteins that were differentially expressed by 4-fold or

more are listed here. Mass/pI values came from NCBI database.

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Table 2

Primer sequences used for gene expression analyses.

Gene name Primer Name Sequence 5' to 3'

ACO2 (At4g26970) ACO2 F TCTAATGGACCGTGGTGTGA

ACO2 R TACTTGCTGCATCGAAAACG

SHM1 (At4g37930) SHM1 F GCAGAGGCCACAATTCTCTC

SHM1 R GGACGAATGGGTTTGTCAAT

GGAT1 (At1g23310) GGAT1F CAATTTCAGTGGCTCTGCTG

GGAT1R GGAGAGTCACGTTCGGTTCT

CAT3 (At1g20620) CAT3 F CCAAAAACTCATGTTTCCTTCC

CAT3 R TGATCCATTTCAGGATTCTCC

GABA-T (At3g22200) GABA-T F TTAAAGCGTTTGCCTCTGGT

GABA-T R CATCAAAATGCCATCACCTG

CAT2 (At4g35090) CAT2 F CATCATGTGGATCTTCTGTGC

CAT2 R TCGACAGCTCTTACGGGATT

SHM4 (At4g13930) SHM4 F AGGCGAAGAGATGAAGATGC

SHM4 R AAACCCATACAAACACACCGTA

FIBRILLIN (At2g35490) FIBR F GGGAGGAGAAATTGGAGGAG

FIBR R TCTCTAACGGAGCCGGAGTA

MOA2.2 (At3g14420) MOA2.2 F GCAGCAACACAGAACCAAAA

MOA2.2 R TCTGGGAATCACAAGAAATTGA

MOA2.13 (At3g14415) MOA2.13 F TATTTGTCCGCATCTCCACA

MOA2.13 R GAGAGAGGAAGGGTGGGACT

AKR2 (At4g35450) AKR2 F AATGGAGAAGCAGTGGCTGT

AKR2 R GACAATGTTGTGGTGGCAAA

PMDH2 (At5g09660) PMDH2 F ACGGGAAAACTGCAGAGCTA

PMDH2 R GACAACAGCTCCAGTGTCCA

CA2 (At5g14740) CA2 F TAAACATGGTCCCCTTTTGG

CA2 R CAGGTGCACCGAAAACAA

CA1 (At3g01500) CA1 F CTGATCTCCGCTTCTCTTCG

CA1 R CTGGCTCGTTACGGATAAGC

CRT1B (At1g09210) CRT1B F TTGTTTCTCTGCTAAGCCAATG

CRT1B R GGACGTTGGACTGTTGGATT

CRB (At1g09340) CRB F GGTAACGAGAAAGCCAGCAG

CRB R CTCCACCGATGCAAAGAAAT

TRIP-1 (At2g46280) TRIP-1 F AGTCTCCCATTCCGGATTTT

TRIP-1 R GCTCGCTCACACATAGAGCA

HSP20-like (At5g19510) HSP20 F TGTTCTAGAGATGATGAAAAACCA

HSP20 R CGTCAAAGCCAAAAATTTCAA

eEF1Bαααα2 (At5g19510) eEF1Bα2 F TCTCAGAGTCTCACAGCTCAGG

eEF1Bα2 R CTCCTCCACGGATTTGACAC

NADEPI (At5g02240) NADEPI F TAAGGAAGGCGGTGTACGAG

NADEPI R GCCTTGAAGTCTTTGGTTGG

UBI 10 (At4g05320) UBI10 F AAAGAGATAACAGGAACGGAAACATAGT

UBI10 R GGCCTTGTATAATCCCTGATGAATAAG

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