transcriptome analysis of a bacterially induced basal and hypersensitive response of medicago...

Transcriptome analysis of a bacterially induced basaland hypersensitive response of Medicago truncatula

Zoltan Bozso Æ Nicolas Maunoury Æ Agnes Szatmari ÆPeter Mergaert Æ Peter G. Ott Æ Laszlo R. Zsıros ÆErika Szabo Æ Eva Kondorosi Æ Zoltan Klement

Received: 26 August 2008 / Accepted: 19 April 2009 / Published online: 24 May 2009

� Springer Science+Business Media B.V. 2009

Abstract Research using the well-studied model legume

Medicago truncatula has largely focused on rhizobium

symbiosis, while little information is currently available for

this species on pathogen-induced transcriptome changes.

We have performed a transcriptome analysis of this species

with the objective of studying the basal (BR, no visible

symptoms) and hypersensitive response (HR, plant cell

death) in its leaves at 6 and at 24 h after infection by HR-

negative (hrcC mutant) and HR-inducing Pseudomonas

syringae pv. syringae strains, respectively. Although there

were no visible symptoms at the BR, the alterations in gene

expression were comparable to those found with the HR.

Both responses resulted in the transcriptional alteration of

hundreds of plant genes; however, the responses in the HR

were usually more intense. The reactions to HR-inducing

and HR-negative bacterial strains were significantly over-

lapping. Parallel up- or down-regulation of genes with the

same function occurred frequently. However, some plant

processes were regulated in one direction; for example,

most of the protein synthesis-related genes were activated

and all of the photosynthetic/chloroplast genes were sup-

pressed during BR. The possible roles of several functional

classes (e.g., cell rescue, signaling, defense, cell death, etc.)

of transcriptionally altered genes are discussed. The results

of the comparison with available mycorrhizal and nodule

expression data show that there is a significant overlap

between nodulation and the leaf defense response and

that during the early stage of the nodulation in roots,

Sinorhizobium meliloti induces a fluctuation in the tran-

scription of BR- and HR-responsive genes.

Keywords Basal resistance � Medicago truncatula �Microarray � Mycorrhiza � Nodulation �Pseudomonas syringae

Introduction

Plants are continuously exposed to infections caused by

different microbes, including bacteria, and have, in

response, developed various recognition mechanisms and

resistance responses. The most conspicuous, effective and,

therefore, the most studied plant defense response is the

plant cell death-associated hypersensitive response (HR),

which is a specific plant reaction to pathogens (Klement

1963). In the case of bacterial induced HR, the plant usu-

ally senses bacterial proteins, called effectors, which are

typically injected into the host cells by the bacterial type III

secretion system (TTSS). The important role of effector

proteins is supported by the fact that the integrity of the

TTSS is crucial for both HR induction in incompatible

interactions (no disease development because of resistance)

and for in planta multiplication of pathogen bacteria in the

compatible interactions (with disease development) (Alf-

ano and Collmer 2004). In the incompatible interactions,

the effectors are directly or indirectly recognized by plant

resistance (R) gene product(s), thereby inducing a signal

Electronic supplementary material The online version of thisarticle (doi:10.1007/s11103-009-9496-8) contains supplementarymaterial, which is available to authorized users.

Z. Bozso (&) � A. Szatmari � P. G. Ott �L. R. Zsıros � E. Szabo � Z. Klement

Plant Protection Institute of the Hungarian Academy of Sciences,

Herman O. 15, P.O. Box 102, Budapest, Hungary

e-mail: [email protected]

N. Maunoury � P. Mergaert � E. Kondorosi

Unite Propre de Recherche 2355, Institut des Sciences du

Vegetal, Centre National de la Recherche Scientifique, Avenue

de la Terrasse Batiment 23, 91198 Gif-sur-Yvette Cedex, France

123

Plant Mol Biol (2009) 70:627–646

DOI 10.1007/s11103-009-9496-8

http://dx.doi.org/10.1007/s11103-009-9496-8

cascade leading to the rapid death of plant cells within 5–

24 h. The HR is accompanied by the accumulation of

reactive oxygen species, including H2O2, and by a number

of other resistance-associated responses, such as the pro-

duction of pathogenesis-related (PR) proteins and phyto-

alexin (Hammond-Kosack and Jones 1996).

In addition to the HR, there is a more general plant

defense response that also recognizes saprophytic bacteria

and bacteria without functional TTSS and subsequently

inhibits their multiplication (Klement et al. 1999, 2003).

There are many synonyms in the literature for this general

recognition and defense system, such as basic, basal, gen-

eral resistance. or innate immunity (Jakobek and Lindgren

1993; de Torres et al. 2003; Gomez-Gomez and Boller

2002). In this paper, we call this general defense system

‘basal resistance’ (BR). The primary elicitors of the BR are

the common components of the microorganisms. These

molecules are also known as pathogen- or microbe-asso-

ciated molecular patterns (PAMPs/MAMPs) (Mackey and

McFall 2006). Flagellin, the protein subunits of flagella,

and the outer membrane-associated lipopolysaccharides

(LPS) of Gram-negative bacteria are the best known sur-

face-derived elicitors of the general response (Dow et al.

2000; Gomez-Gomez and Boller 2002). Disruption of the

cell integrity leading to the leakage of bacterial contents

may also trigger general defense responses. To date, a cold-

shock protein and a bacterial elongation factor have been

identified as endogenous bacterial elicitors of the BR

(Kunze et al. 2004; Felix and Boller 2003). Detection of

bacterial presence induces different defense-associated

physiological and structural changes in plant cells (Best-

wick et al. 1995; Ott et al. 1997; Bozso et al. 2005).

While the BR and HR can be distinguished, this does not

mean that these two plant defense responses are entirely

different. Although their recognition mechanisms and the

final outcome are obviously different, BR and HR use

partly similar or overlapping pathways. Hypersensitive

response-negative or saprophytic bacteria have been found

to be able to activate selected plant defense-related genes

that have been similarly activated by the HR-inducing

strains. The first report demonstrating gene activation

changes by HR-negative bacteria was published by

Jakobek and Lindgren (1993). Thereafter, it was shown that

not only whole bacterial cells but also bacterial compounds

can cause changes in a treated plant’s gene expression

pattern (Dow et al. 2000; Navarro et al. 2004). Genome-

wide transcriptional reprogramming has recently been

described in Arabidopsis thaliana during various plant

responses, including defense reactions and those that are

related to BR following bacterial infection (Thilmony et al.

2006; Truman et al. 2006). However, there is limited

information currently available on changes in gene acti-

vation during BR response in other plants. Our studies have

focused on Medicago truncatula, which has been selected

as a model legume for studying nitrogen-fixing nodule

development induced by the symbiont Sinorhizobium

meliloti. This plant also provides a suitable model for

investigating other plant–bacterial interactions and for

comparing plant reactions to pathogenic, symbiotic, or

mycorrhizal partners.

In this work we report on the transcriptional changes in

BR and HR occurring in M. truncatula leaves at 6 and 24 h

after bacterial inoculation. Our results show that the HR-

negative, BR-inducing Pseudomonas syringae pv. syringae

hrcC mutant elicits a dramatic transcriptional reprogram-

ming of the plant cells, although this reprogramming is less

pronounced than the transcriptional changes in HR induced

by wild-type P. syringae pv. syringae. We discuss the

possible function of particular classes of genes activated

during BR and compare defense and symbiosis related

transcriptional patterns.

Materials and methods

Plant materials and bacteria

Medicago truncatula cv. R108 plants were grown in mixed

soil at 23�C under a 16/8-h light/dark photoperiod in a

growth chamber. Leaves of 4- to 6-week-old plants were

used for infiltration.

Pseudomonas syringae pv. syringae 61 (P. syringae)

HR-positive wild-type strain and P. syringae pv. syringae

61 hrcC (P. syringae hrcC) HR-negative mutant strain

(61-143 1530B, Alan Collmer, Cornell University, Ithaca,

USA) were grown overnight at 27�C on King’s B medium

(King et al. 1954) which, in the case of the P. syringae

hrcC mutant was supplemented with 50 lg/ml kanamycin.

For infiltrations, bacteria were suspended in distilled water

at a density of 108 cells ml-1. The bacterial concentration

of the suspensions was estimated by optical density read-

ings at 600 nm. Infiltrations of M. truncatula leaves with

the bacterial suspension or distilled water were carried out

by injection with a syringe.

Sample preparation, Cy labeling, and microarray

hybridization

The experiments were performed according to the

requirements of the Minimum Information About a

Microarray Experiment (MIAME) (Brazma et al. 2001).

Experimental design

Medicago leaf samples injected with water or with the

bacterial suspension were harvested 6 and 24 h post

628 Plant Mol Biol (2009) 70:627–646

123

inoculation (hpi). For RNA preparation, approximately

100 mg leaf tissue was collected from four different plants,

frozen in liquid nitrogen, and stored at -70�C for future

analysis. Two independent experiments were performed on

leaves of different plant generations, with a 2-week interval

between leaf harvests.

RNA extraction and labeling

Total RNA purification was carried out using the plant total

RNA purification kit (Viogene Biotek, Taipei, Taiwan).

RNA quality was checked on agarose gels. cDNA synthesis

and labeling were performed using the Stratagene Fairplay

II Kit (Statagene, La Jolla, CA) according to the manu-

facturer’s instructions. The bacterial and water-treated

samples were labeled with Cy5 and Cy3, respectively. The

labeled probes were concentrated to 10 ll by means of a

vacuum concentrator. The efficiency of labeling was

checked by running 1 ll samples on a mini agarose gel,

which was photographed in a laser scanner (LS4; Genomic

Solutions, Huntingdon, UK).

Arrays

The M. truncatula 16 kOLI-1 array was used (produced

by the Department of Genetics, Institute of Genome

Research, Bielefeld University, Germany; www.genetic.

uni-bielefeld.de) and prepared for hybridization according

to the manufacturer’s instructions. This array represents

16,086 tentative consensus sequences of the TIGR M.

truncatula Gene index 5 and contains 70-mer oligonu-

cleotide probes in duplicate.

Hybridization conditions

The labeled cDNA samples (9 ll) were diluted with

hybridization buffer (Micromax; Perkin-Elmer, Foster

City, CA) to 120 ll, heated to 95�C for 1 min, loaded on

the prepared array slides, and then processed using an

automated hybridization station (GeneMachines HybSta-

tion; Genomic Solutions, Holliston, MA). The hybridiza-

tion was carried out at 65�C for 3 h, then at 55�C for 3 h,

and finally at 50�C for 12 h. This was followed by a

medium-stringency wash, a high-stringency wash, and a

wash with post-wash buffer at 42�C, each at room tem-

perature for 5 min. Wash buffers were from Genomic

Solutions.

Measurements

The hybridization signals were measured by scanning the

slides with a GenePix 4000B scanner piloted with GenePix

Pro software (Molecular Devices, Sunnyvale, CA).

Normalization

Data processing and normalization were performed with

Midas software (Saeed et al. 2003). Before data analysis,

the data files produced by GenePix Pro were converted

with an Express Converter (from the TIGR website) to a

MIDAS compatible tav file. After local background sub-

tractions, the signal intensities were normalized by the

Lowess (Lockfitt) method using default parameters of the

software (block mode, smoothing parameter 0.33, refer-

ence Cy3).

Data analysis

The spots that showed low intensity in both channels

(\5000; this level was about 50% more intense than the

values of the highest level of the empty control spots) were

omitted from further analyses because these spots usually

show high expression variability and, therefore, are a major

cause of inconsistencies in microarray results. The expres-

sion data of duplicated probes were averaged for both

channels and the expression ratios determined. Using the

results from duplicated experiments, we further analyzed

those genes showing at least a twofold up- or down-regu-

lation in both replicates (Supplementary Table 1) To con-

firm the result of differentially expressed genes, we

performed Rank Products analysis using the appropriate

software (from the Glasgow Microarray Analysis website).

The Rank Products Method gives reliable and consistent

results even in the case of a reduced number of repeats

(Breitling et al. 2004). Because at 6 hpi those genes that had

been activated or repressed in both P. syringae hrcC- and

P. syringae-injected leaves changed their activity exclu-

sively in the same direction, the two independent data sets

of these treatments (four data sets) could be used as a repeat

and analyzed in terms of significance. Ten random permu-

tations were used for estimating false discovery rates

(FDR). The genes that were above the selection limit (10%

FDR) by the rank analysis were compared to the list of the

genes that showed at least a twofold up- or down-regulation

in both wild-type P. syringae- and hrcC mutant-injected

leaves. The results of the analyses showed that at 10% FDR

almost all (96%) common genes that were scored as dif-

ferentially expressed on the basis of fold-method (C2,

B0.5) were also scored as being differentially regulated by

the Rank Product analyses (Supplementary Table 2).

Quantitative RT-PCR analysis of gene expression

Total RNA (2.5 lg) was used for the synthesis of 20 ll

cDNA (RevertAid H Minus First Strand cDNA Synthesis

kit; Fermentas, Vilnius, Lithuania). Specific primers were

designed for both up- and down-regulated genes expressed

Plant Mol Biol (2009) 70:627–646 629

123

http://www.genetic.uni-bielefeld.de

http://www.genetic.uni-bielefeld.de

at different levels. The primers and cycling parameters for

real-time PCR are given in Supplementary Table 3. For the

PCR analyses, 2.5 ll from a tenfold dilution of the cDNA

stock were used (prepared as described above) in 15-ll

reactions. The final concentrations of the primers was

3 lM. The PCR was performed using the iQ SYBR Green

2x Supermix (Bio-Rad, Hercules, CA) on the DNA Engine

Opticon 2 (MJ Research, Waltham, MA). Measured C(T)

values were always normalized to actin (accession no.

TC81607) internal control values. Each sample was mea-

sured at least twice, and standard deviations were calcu-

lated. Values of the water-inoculated controls were given

the arbitrary value of 1; other sample values were corre-

lated to the water controls.

Results and discussion

Experimental design and data analysis

To obtain an overall view of the transcriptional changes

that occur during BR and HR induced by bacteria in plant

cells, we performed microarray experiments with M.

truncatula 16 kOLI chips. Medicago truncatula leaves

were injected with the HR-negative TTSS mutant P.

syringae hrcC, which induces only BR, and the wild-type

P. syringae, which triggers both BR and HR. The response

of the leaves to the injected bacterial samples was com-

pared to the water-infiltrated control samples. To discrim-

inate plant responses related to mechanical stress caused by

the infiltration procedure, we also compared the response

of the water-infiltrated leaves to non-inoculated leaf sam-

ples. The leaf samples were collected at 6 and at 24 hpi,

except for leaves infiltrated with the wild-type P. syringae,

which could only be harvested at 6 hpi as thereafter (at

about 7–8 hpi) a tissue collapse occurred due to the HR.

Infiltration of P. syringae hrcC induced no visible symp-

toms. The leaf RNA samples were hybridized to 16k M.

truncatula microarrays. Following data normalization and

filtering (see Materials and methods), those genes showing

at least a twofold change in expression, either activation or

repression (C2, B0.5), as a consequence of the treatments

were selected as being differentially expressed (Supple-

mentary Table 1).

Bacterial infiltration resulted in major changes in gene

activities while water infiltration resulted in only minor

changes. The number of overlapping genes up- or down-

regulated by the bacterial and water-injected samples were

low (e.g., at 6 hpi, only 27 common genes were found

between the water- and P. s. hrcC-infiltrated samples),

which showed that most of the changes were caused by the

bacterial treatments (data not shown). The results obtained

by the microarray analysis were confirmed with real-time

PCR for 15 selected genes (Supplementary Table 4).

Although there were differences between microarray and

PCR data in terms of the intensity of the transcriptional

alterations, the direction of changes was consistent, which

confirmed the reliability of the microarray results.

Comparison of the different bacterial treatments

Despite the absence of symptoms, the injection of the HR-

minus P. syringae hrcC provoked a dramatic change in the

transcription profile by activating 781 genes and repressing

1116 ones at 6 hpi; this response was comparable to

the changes induced by the HR-positive bacteria, which

triggered the up-regulation of 705 genes and the down-

regulation of 845 genes (Table 1). At 6 hpi, the up- or

down-regulated genes of these treatments represented

about 10–12% of the genes present on the microarray; in

comparison, approximately 38–40% of the genes did not

show any significant changes in their activity and 50%

were undetectable in our experimental conditions. There

was a significant overlap (700 genes at 6 hpi) between BR

and HR. Moreover, the directions of these gene expression

modifications were the same during both response, with the

exception of three genes: TC 87010, TC 77756 and

TC86996 (Figs. 1a, 2). Among the genes that showed

modified activation only after a particular treatment could

be the genes that are specific for HR or BR. However, more

detailed time course experiments would be required to

confirm their specificity for HR or BR.

The decline of the numbers of significantly modified

genes (Table 1) and that of the fold-change of genes

(Fig. 1b) revealed that the transcriptional response

decreased from 6 to 24 hpi in leaves injected with P. sy-

ringae hrcC. Several genes showed significant changes in

activity at both 6 and 24 hpi (Figs. 1b, 2).

Classification of transcriptionally modified genes

induced during BR

Those genes that significantly changed their activity during

BR were classified into functional groups based on the

classification of the Institute for Genomic Research TC

annotation and the MENS (Medicago EST Navigation Sys-

tem) on-line databases. The largest group is composed of

genes without known functions or similarities to other genes

(e.g., 35% at 6 hpi in hrcC mutant-injected leaves). Most

groups contain both activated and repressed genes. However,

certain groups, such as photosynthesis/chloroplast and

ribosomal/protein synthesis genes, changed their transcrip-

tional activity specifically in one direction. At 6 hpi in leaves

injected with P. syringae hrcC, all photosynthesis/chlor-

oplast-related genes (188) were down-regulated (except for

one, ferrodoxin, TC77615; data not shown). In contrast, in

630 Plant Mol Biol (2009) 70:627–646

123

these samples, most of the ribosomal/protein synthesis-

related genes were activated (75 activated and seven

repressed) (Supplementary Table 5). The tendency of these

changes was in agreement with the results obtained after

comparable bacterial treatments in other plants, such as

Arabidopsis and tomato (Mysore et al. 2002; Truman et al.

2006). Certain of the responsive genes behaved as expected,

based on knowledge from other screening methods and other

pathosystems, such as PR genes, receptor-like kinases rec-

ognizing MAMPS, transcription factors, among others.

Cell signaling

The recognition of infecting bacteria by plant cells occurs

in at least two steps. The first step is the fast recognition of

bacterial MAMPs by cell-surface receptors. The second

step is the sensing of the injected bacterial effector proteins

inside the plant cells. The period required for building up

the TTSS system of bacteria is the primary determinant of

the length of this second step. In the case of P. syringae

strain 61, the length of this period (the so-called bacterial

induction time), is about 0.5–1 h (Bozso et al. 1999).

Although our samples were taken after these recognition

events, there were numerous changes in the expression of

signaling genes (Table 2). Transcriptional regulation of

signaling components could be a mechanism for enhancing

or weakening the intensity of defense reactions.

Kinase genes were the most abundant and the most

activated genes in this functional class at 6 hpi for both

types of bacterial treatments, suggesting that the kinases

8

10

8

10(A)

1

P.s. at 6 hpi(B)

1

P.s. hrcC at 24 hpi

4

6

8

4

6

8

-2

0

2

-10 -8 -6 -4 -2 0 2 4 6 8 10

-2

0

2

-10 -8 -6 -4 -2 0 2 4 6 8 10

P.s. hrcC at 6 hpi P.s. hrcC at 6 hpi

-8

-6

-4

-8

-6

-4

-10-103 4 3 4

2 2

Fig. 1 Comparison of the intensity and the directions of gene

expression changes induced by different treatments. The X- and Y-axes show the average log2 transcription activation or repression for the

given treatments compared to water-injected control. a Pseudomonassyringae hrcC at 6 h post-inoculation (hpi) vs. P. syringae at 6 hpi.

b P. syringae hrcC at 6 hpi vs. P. syringae hrcC at 24 hpi. Points in

quadrants 2 and 4 show those genes activated and repressed in the same

direction in both treatments, respectively. Points in quadrants 1 and 4

show those genes activated and repressed in the opposite direction in the

two treatments. The comparisons are for common genes that agreed

with the selection limit (C2 or B0.5) after both treatments. The figure

shows the results of the average of duplicated experiments

Table 1 Number of significantly (C2 or B0.5) activated or repressed genes after different treatments

Treatments 6 hpi 24 hpi

Activateda Represseda Activated Repressed

P. syringae hrcCb 781 1,116 206 167

P. syringaeb 705 845 –c –

Waterd 57 42 108 235

a Criteria for gene selection are described in the textb Control for these treatments were water infiltrationc By 24 hpi the P. syringae infiltrated tissues were collapsedd Control for this treatment was non-infiltrated leaves

Plant Mol Biol (2009) 70:627–646 631

123

are one of the most important regulators of these resistance

responses. Several phosphatase genes were also up- or

down-regulated. While, at 6 hpi in P. syringae hrcC-

injected leaves, different phosphatase 2A subunits were

found to be activated, protein phosphatase 2C genes were

repressed. Phosphatase 2A (PP2Ac) in tomato and tobacco

is a negative regulator of plant defense responses by

influencing the PR-protein level and the development of

cell death (He et al. 2004). Protein phosphatase 2C proteins

can be negative regulators of stress-induced MAPK path-

ways, abscisic acid (ABA) signaling, and receptor signal-

ing (Schweighofer et al. 2004). Activated phosphatases

may have a role in feed-back regulation, whereas the

repression of other phosphatases may be required for the

activation of other plant defense responses.

Many receptor-like protein kinases were found among

the up- and down regulated genes. These receptors may

play a key role in sensing the presence of the bacterial

cells. In Arabidopsis, FLS2 (At5g64330) is responsible for

the recognition of a conserved region of bacterial flagellin

(Gomez-Gomez and Boller 2002). The probable homolog

of FLS2 in M. truncatula, TC89068 (67% of identity), was

activated at 6 hpi in P. syringae hrcC-treated leaves. Some

members of the S receptor-like kinase (self-incompatibil-

ity) gene family showed transcriptional activation in tissues

infected with HR-negative bacteria, suggesting that they

may be involved in the development of BR (Pastuglia et al.

2002). Although the activated M. truncatula S receptor-like

kinase TC93750 does not show close similarity to the

above-mentioned S gene receptors (data not shown), it

could have a role in pathogen perception.

Pseudomonas syringae hrcC treatments also activated

receptor-like genes of the yeast pheromone class. These

types of G protein-coupled receptors are peptide hormone-

sensing molecules in yeast (Bardwell 2005). The two

activated M. truncatula pheromone receptor-like genes

(TC7717, TC87246) are similar (E value = 1e-18 and

3e-38, respectively) to two Arabidopsis genes (At2g26530

and At2G15760), which complemented the yeast phero-

mone receptor mutants (Hirayama et al. 1997). The

microarray data of these Arabidopsis genes (data from

Genevestigator website) and the MtGI expressed sequence

tag (EST) data of the Medicago homologs (data from

M. truncatula gene index website) indicate the activation

of these genes during different defense-related processes

(data not shown).Thus, it can not be excluded that the

pheromone receptor-like genes may have signaling roles in

resistance responses that include the BR.

Transcription factors

Several members of WRKY, MYB, NAC/NAM, bZIP, and

AP2 transcription factors (TFs) were activated, and other

MYB, MYB-like, bZIP, and bHLH TFs were repressed in

P. syringae hrcC-infiltrated leaves at 6 hpi (Table 3).

These types of TFs are involved in various pathogen- or

elicitor-induced resistance reactions (Eulgem 2005).

To determine whether the transcriptional changes are

conserved among different plant species, we compared the

expression of M. truncatula and Arabidopsis TF homologs.

The Arabidopsis homologs of the Medicago TFs were

identified by BlastTX (available from the TAIR website)

(Table 3). The expression of these Arabidopsis genes in

response to various treatments was collected with the

Genevestigator website (Zimmermann et al. 2004). Table 3

shows that the Arabidopsis homologs were activated or

repressed after various microbial infections and other bio-

logical stresses and that they mostly changed in the same

direction as their M. truncatula homologs. Pseudomonas and

Agrobacterium triggered similar responses in Arabidopsis,

which suggests the general nature of the BR. The plant cell

death-inducing necrotroph fungi Alternaria brassicola and

Botrytis cinerea—but not the biotrophic Erysiphe species—

activated many of these TF homologs, implying that the

plant response after bacterial infection resembles, to a cer-

tain extent, the reaction to necrotroph pathogens.

Most of the Arabidopsis homologs of down-regulated

M. truncatula TFs were also repressed in response to

bacterial treatments, and no homologs were regulated in

Fig. 2 Quantitative comparison of gene expression showing the

number of transcriptionally modified genes in wild-type P. syringae(P.s. 6 hpi) and in P. syringae hrcC mutant (P.s. hrcC 6 and 24 hpi)

infiltrated tissues. Numbers indicate the number of genes influenced in

common (overlapped areas) or separately (not overlapping areas).

The areas are proportional to the respective numbers. Numbers inparentheses represent activated and repressed genes, respectively,

followed by oppositely influenced genes, when applicable. The figure

represents the results of duplicated experiments. Criteria for gene

selection are described in the text

632 Plant Mol Biol (2009) 70:627–646

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Table 2 Selected Medicago truncatula signaling genes up- or down-regulated in bacterially treated leaves

Identification Homology P.s. hrcC 6 hpia P.s. 6 hpib P.s. hrcC 24 hpi

Kinases

TC87606 Avr9/Cf-9 rapidly elicited kinase 5.1c 4.7 3.2

TC87719 Wall-associated kinase 4.4 4.8 2.2

TC80300 Protein kinase 4.3

TC79721 Serine/threonine-specific protein kinase 3.4

TC77188 Calcineurin B-like-interacting protein kinase 2.6

TC91104 Serine/threonine protein kinase 2.4

TC77246 SNF1 like protein kinase 1.9

TC79545 Serine/threonine-specific protein kinase 1.7

TC81285 Calcium-dependent protein kinase 1.6 2.3

TC85165 Ser/Thr protein kinase 1.6

TC77179 Calcium-dependent protein kinase 1.5 2.0

TC79936 Serine/threonine specific protein kinase 1.3

TC91386 Serine/threonine kinase -1.3

TC78167 Mitogen-activated protein kinase -1.6

TC92501 Protein kinase -2.6 -1.8

Receptor kinases

TC82239 Leucine-rich repeat receptor-like protein kinase 3.5

TC83247 Receptor protein kinase 3.4

TC92430 Receptor-type protein kinase 3.3 3.6

TC81205 Receptor-like protein kinase 3.2

TC84236 CLAVATA1 receptor kinase 3.2

TC89679 Receptor-like protein kinase 3.1 4.7



TC93750 S-receptor kinase 2.6

TC77173 Yeast pheromone receptor protein 2.5 1.6

TC92198 Receptor-interacting serine-threonine kinase 2.5

TC87312 Calcium/calmodulin-regulated receptor kinase 2.3 2.2

TC91131 Receptor-like protein kinase 1.8

TC80500 Receptor protein kinase 1.6 1.9

TC87246 Yeast pheromone receptor protein 1.5


TC88451 Receptor protein kinase -1.3

TC93764 Receptor protein kinase -1.6

TC76454 Receptor-like protein kinase -1.7 -1.8

TC88669 Receptor-like protein kinase -1.8 -2.6 -1.4

TC8967 Receptor-like protein kinase -2.3

TC79649 Lectin-like receptor kinase -2.4

TC84193 Receptor-like protein kinase -2.6

Phosphatases

TC79408 Protein phosphatase 2A regulatory subunit B 2.1

TC79962 Protein phosphatase 2A regulatory subunit B 1.7 2.1

TC87276 Protein phosphatase 2A regulatory subunit A 1.4

TC90359 Protein phosphatase 2C -1.7 -3.3

TC83336 Protein phosphatase 2C -1.9

a Bacterial treatments: P.s. hrcC, Pseudomonas syringae hrcC; P.s., P. syringaeb Table does not contain those genes that were induced or repressed only after the P. s. treatmentc Average log2 transcription compared to water-injected control

Plant Mol Biol (2009) 70:627–646 633

123

the opposite direction. Thus, TFs involved in defense

mechanisms against different pathogens may be conserved.

Cell rescue

One of the most important challenges for a plant cell after

microbial infection is to eliminate the various induced and

harmful processes that may damage cell integrity. Gluta-

thione S-transferases (GSTs) and epoxide hydrolases (EHs)

are key enzymes of detoxification (Sheehan et al. 2001;

Newman et al. 2005). Both activated and repressed GSTs

and EHs were found, and the GSTs were particularly

abundant (Table 4). It has been reported that the levels of

GST isoenzymes are regulated both transcriptionally and

translationally during bacterially induced BR and HR

(Jones et al. 2004). At 6 hpi, 10 and 11 GST isoenzyme

genes were activated by P. syringae and P. syringae hrcC

respectively, and the activation was stronger in the first

case. On the other hand, only 2 and 3 (P. syringae and P.

syringae hrcC respectively) GST isoenzyme genes were

repressed. Epoxide hydrolases play a critical role in

detoxifying reactive metabolites in both plants and animals

(Murray et al. 1993). The tobacco EH gene was found to be

activated during BR after injection of the P. syringae hrcC

mutant (Szatmari et al. 2006) and by tobacco mosaic virus

infection (Guo et al. 1998). Additionally, EHs have also

Table 3 Comparison of the expression of M. truncatula basal resistance-related transcription factors with their Arabidopsis homologs

IDType of transcription

factorArabidopsis

homolog genes E-value A. b

rass

icio

la a

A. t

umef

acie

ns

B. c

iner

ea

E. c

icho

race

arum

E. o

ront

ii

F. o

ccid

enta

lis

M. p

ersi

cae

nem

atod

e

P. i

nfes

tans

P. r

apae

P.

tom

ato

hrcC

b

P.

tom

atob

P.

tom

ato

avrR

pm1b

P.

phas

eoli

cola

P.s

.hrc

C

6 hp

i

P.s

. 6

hpi

Activation or repression of TF’s after different treatments TF’s activated in P.s. hrcC injected

leaves of M. truncatula in Arabidopsis in M.

truncatulaTC78376 WRKY AT1G80840 1,00E-51 Ac A A R A A A A A A ATC80208 WRKY AT4G18170 4,00E-39 A A A A A A A A A A A A A ATC86084 WRKY AT2G24570 5,00E-87 A A A A A A

TC89937 AP2 AT5G61890 2,00E-28 A A A A A A A A TC87696 AP2 AT4G23750 9,00E-28 A A R R R R R R R A TC88428 MYB AT1G66230 2,00E-73 R R R A R R A A TC86588 MYB AT1G06180 2,00E-63 A A A A A A A ATC78189 NAC/NAM AT1G01720 1,00E-97 A A R A A A A A TC88609 NAC/NAM AT1G69490 3,00E-85 R A A R R A R A A A A ATC81706 Zinc finger AT3G28210 5,00E-64 A A A A A A A ATC77581 bHLH AT1G32640 2,00E-64 R A A R A A A A TC80273 At-hook AT5G49700 2,00E-52 A A A R A R A A A A ATC85773 bZIP AT4G34590 1,00E-29 A A R A A

TC77604 SAR AT5G27120 0.0 A ATF’s repressed in P.s. hrcC

injected leaves of M. truncatula

TC80810 ccaat-box binding AT5G63470 1,00E-71 A R R RTC89017 Zinc finger AT1G68520 2,00E-33 R A R R R R R RTC87014 golden2-like AT2G20570 2,00E-28 R R R R R R RTC87249 bHlH AT4G00050 3,00E-22 R R R R RTC88329 squamosa AT2G47070 2,00E-85 R R RTC80869 bZIP AT1G49720 5,00E-35 A R

TC86792 pseudo-response

regulator AT5G02810 e-128 R R R R R TC77052 MYB AT1G74840 1,00E-44 R RTC78276 MYB AT3G46130 4,00E-52 R R R R R R R R R

BR, Basal resistance; TF, transcription factorsa A. brassiciola, Alternaria brassiciola; A. tumefaciens, Agrobacterium tumefaciens; B. cinereas, Botrytis cinerea; E. cichoracearum, Erysiphecichoracearum; E. orontii, Erysiphe orontii; F. occidentalis, Frankliniella occidentalis (thrips); M. persicae, Myzus persicae (aphids); nema-tode, Heterodera. schachti; P. infestans, Phytophthora. infestans; P. rapae, Pieris rapae (caterpillars); P. tomato hrcC, P. syringae pv. tomatoDC3000 hrcC; P. tomato, P. syringae pv. tomato DC3000; P. tomato avrRpm1, P. syringae pv. tomato DC3000 avrRpm1; P. phaseolicola,

P. savastanoi pv. phaeolicola; P.s. hrcC, P. syringae pv. syringae 61 hrcC; P.s., P. syringae pv. syringae 61b In the case of P. s. tomato, the given gene is considered as activated or repressed if the particular gene showed up- or down-regulation at least

at one presented time point (2, 6, 24 hpi)c A, Activated (C2); R, repressed (B0.5). Gray shading indicates if the direction of transcription of Arabidopsis genes was the same as that of the

M. truncatula TFs

634 Plant Mol Biol (2009) 70:627–646

123

been assigned a role in cutin biosynthesis (Pinot et al.

1993). Therefore, GSTs and EHs are promising candi-

dates as genes involved in various types of resistance

responses.

Similar to the results obtained in M. truncatula cell

culture treated with invertase elicitor (Tellstrom et al.

2007), we did not find any activation of important anti-

oxidants, such as superoxide dismutase (SOD) or catalase;

Table 4 Selected M. truncatula cell detoxification and antioxidant genes up- or down-regulated in bacterially treated leaves

ID Homology P.s. hrcC 6 hpia P.s. 6 hpi P.s. hrcC 24 hpi

Glutathione S-transferases

TC86886 Glutathione S-transferase 5.4b 5.6

TC77358 Glutathione S-transferase 3.9 6.5

TC77506 Glutathione S-transferase 3.9 8.8 3.9

TC79559 Glutathione S-transferase 3.5


TC78052 Glutathione S-transferase 3.1 20.9 1.4








TC86955 Glutathione S-transferase -2.0 -2.4

TC80497 Glutathione S-transferase -2.1



TC87002 Glutathione S-transferase

TC80969 Glutathione S-transferase

Antioxidant genes

TC77316 Superoxide dismutase -1.4

TC87275 Superoxide dismutase -1.6

TC93642 Superoxide dismutase

TC78044 Catalase -2.1

Genes of the ascorbate-glutathione cycle

TC85976 L-Ascorbate peroxidase -1.0 -2.3

TC88961 L-Ascorbate peroxidase -1.5 -1.5

TC85162 Dehydroascorbate reductase -1.8

TC76898 Dehydroascorbate reductase -2.1 -2.8

TC87458 Monodehydroascorbate reductase -2.1

TC86967 Glutathione reductase 2.0

Epoxide hydrolases

TC88515 Epoxide hydrolase 4.3

TC77583 Epoxide hydrolase 1.7

TC77525 Epoxide hydrolase -1.1

TC78176 Epoxide hydrolase -1.2

Peroxiredoxins

TC85784 2-Cys peroxiredoxin -1.8

TC85783 2-Cys peroxiredoxin -2.0

TC79043 Peroxiredoxin Q -3.3

a Bacterial treatments: P. syringae hrcC (P.s. hrcC), P. syringae (P.s.)b Average log2 transcription compared to water-injected control

Plant Mol Biol (2009) 70:627–646 635

123

to the contrary, these genes were repressed in the

P. syringae-infiltrated leaves at 6 hpi. Genes of the ascor-

bate–glutathione cycle, which is another important plant

antioxidant system, were also mostly down-regulated at

6 hpi in bacterially infiltrated leaves. At 6 hpi in the

P. syringae hrcC mutant-treated leaves, repression of three

peroxiredoxin genes was also found. Peroxiredoxins can

reduce H2O2 and alkyl peroxides to water and alcohols,

respectively (Dietz 2003). In Arabidopsis leaves, regulation

of peroxiredoxin at the protein level is complex and, sim-

ilarly to that of GSTs, it goes both up and down at the

transcriptional and protein level after bacterial treatments

(Jones et al. 2004). In our experiments, all peroxiredoxin

genes on the Medicago chip were repressed. It is possible

that the different experimental systems (plant and sampling

time) or the absence of the probes of the isoforms on the

16kOLI chip caused this difference with Arabidopsis

results.

Defense-associated genes

A large portion of genes showing altered activation in

response to bacterial treatments demonstrated a similarity

to genes known to be associated directly or indirectly with

plant defense responses (Table 5). In our samples, several

PR-10 and PR-10-like genes were abundantly and strongly

activated. The cytosol localized PR-10 proteins are induced

by phytopathogens and environmental stresses (Breda et al.

1996; Liu and Ekramoddoullah 2006). In addition to their

ribonuclease activity (Bantignies et al. 2000), the PR-10

and PR-10-related proteins can bind plant hormones, such

as brassinosteroids (Markovic-Housley et al. 2003) and

cytokinins (Koistinen et al. 2005). Both hormones can

induce or influence disease resistance (Nakashita et al.

2003; Carimi et al. 2003; Novacky 1972). Thus, the

accumulation of PR-10 may have multiple effects in plant

defense including a role in BR.

Other PR-proteins, such as chitinases, also were up- and

down-regulated in bacterially treated leaves (Table 5).

Some chitinases hydrolyze not only chitin but also bacterial

cell-wall peptidoglycans. The induction of such chitinase–

lysozyme activities in the tobacco cell wall was found to

correlate well with the BR (Ott et al. 2006) and overex-

pression of a particular chitinase gene in pepper, resulting

in enhanced bacterial disease resistance against P. syringae

(Hong and Hwang 2006).

Photoassimilate-responsive (PAR)-like genes (TC77234

and TC77235) are examples of the crosstalk between

sugar metabolism and defense responses against pathogens

that were up-regulated in bacterially infiltrated samples

(Herbers et al. 1995; Takemoto et al. 2003; Szatmari et al.

2006). Genes that are involved in ethylene and polyamine

synthesis (S-adenosyl-L-methionine synthetases) were also

activated both in P. syringae hrcC- and P. syringae-treated

leaves at 6 hpi. Interestingly, other key enzymes of ethyl-

ene synthesis, such as ACC synthase, and ACC oxidase,

were only up-regulated by the HR-inducing strain (data not

shown). Despite the general constitutive nature of R-pro-

teins (resistance genes), some nucleotide binding-type R

proteins were also activated at 6 hpi in Pseudomonas-

infiltrated leaves.

Examples of down-regulated defense-related genes are

genes of the nonspecific lipid-transfer protein (nsLTP)

class which have proven antibacterial and antifungal

activity (Garcia-Olmedo et al. 1995). Their repression

suggests, however, that the nsLTPs have no direct anti-

bacterial role in Medicago BR (data not shown).

Plant cell death-related genes

Plant cell death is the most characteristic response during

HR-type resistance. The cell death process following

elicitor- or pathogen-induced defense is not an uncon-

trolled cell collapse but a genetically determined and pro-

grammed cell death (PCD) (Greenberg and Yao 2004).

At 6 hpi, we found both up- and down-regulated cell

death-associated genes in leaves injected with Pseudomo-

nas strains. The genes of QM-like protein (TC88241) and

pirin (TC88605) were moderately induced in P. syringae

hrcC-treated samples (about three to fivefold), but they

were more induced in tissues undergoing the HR (approx.

30- to 44-fold). The ESTs of the QM-like protein gene in

the MtGI database (M. truncatula gene index website) were

most frequently isolated from elicitor-treated roots, con-

firming the activation of this gene in defense responses.

This protein is also known as 60S ribosomal protein L10.

The high induction of the QM-like gene (about 30-fold

activation during HR), compared to the low induction of

other ribosome structural genes (two- to three-fold activa-

tion; Supplementary Table 5) suggests that this gene may

have additional role(s) besides its ribosomal function. In

animal cells, the QM-like proteins are involved in cell

death via interaction with transcription factors (Oh et al.

2002). A tomato QM-like protein has been found to confer

protection to yeast against oxidative stress, and it can

rescue yeast from the lethality mediated by the mammalian

proapoptotic protein Bax (Chen et al. 2006).

Pirin is conserved from prokaryotic to eukaryotic

organisms, and their homologs play important roles in a

number of different biological processes, including apop-

tosis. In plants, the function of pirin(s) has not yet been

elucidated. A tomato pirin is induced during PCD, while

PCD inhibitors reduce the pirin transcription (Orzaez et al.

2001). Pirin may take part in signaling (Lapik and Kauf-

man 2003) and transcriptional regulation via interaction

with other proteins (Wendler et al. 1997), but it may also

636 Plant Mol Biol (2009) 70:627–646

123

Table 5 Defense-related genes activated or repressed at 6 and 24 hpi in P. syringae hrcC (BR)- and P. syringae (HR)-injected M. truncatulaleaves

Identification Homology P.s. hrcC6 hpia

P.s.6 hpib

P.s. hrcC24 hpi

Notes

TC77234 Photoassimilate-responsive

protein

5.3c,d 5.5 Transcriptionally induced after pathogen

infections

TC106613 PR10-1 protein 5.0 5.0 2.7 Pathogenesis-related protein



TC77235 Photoassimilate-responsive

protein

4.4 5.3 2.5 Transcriptionally induced after pathogen

infections

TC86207 Disease resistance response

protein-like

4.4 4.0 2.7 Dirigent-like sequences, may be involved in

lignifications




TC78408 Chitinase 4.0 5.0 1.3 Pathogenesis-related protein


TC79513 Stellacyanin-like protein 3.9 3.9 2.1 This type of gene is induced by pathogens and

abiotic stresses and different defense-related

signal molecules

TC92969 TIR-similar-domain-containing

protein

3.9 4.4 R-type resistance protein



TC81455 Glucan 1,3-beta-glucosidase 3.7 Pathogenesis-related protein

TC78258 Polygalacturonase inhibiting

protein

3.5 Reduces the hydrolytic activity of

polygalacturonases (PGs), limits the growth of

plant pathogens, and also elicits defense

responses in plant

TC77750 Chitinase 3.5 4.0 Pathogenesis-related protein

TC86208 Disease resistance response

protein-like

3.4 4.9 2.1 Dirigent-like sequences, may involve in

lignifications

TC87019 Avr9/Cf-9 rapidly elicited

protein 31

3.3 2.7 Contains Ca2? binding motif

TC86778 Cyanogenic Beta-Glucosidase 3.2 Releases hydrogen cyanide in response to biotic

and abiotic stresses

TC86776 Cyanogenic Beta-Glucosidase 3.2 Releases hydrogen cyanide in response to biotic


TC81700 Lipoxygenase 2.9 Lipidperoxidation of membranes, involvement in

lipid signaling

TC81042 Resistance gene-like 2.9 R-type resistance protein

TC90083 Immediate-early fungal elicitor

protein

2.9 Contains ubiquitin-protein ligase motif (U-box

protein)

TC86652 Syringolide-induced protein

13-1-1

2.9 Contains ubiquitin-protein ligase motif (U-box

protein)

TC85874 1,3-Beta-glucanase 2.8 3.6 Pathogenesis-related protein

TC88172 Avr9/Cf-9 rapidly elicited

protein 132

2.8 1.9 Contains ubiquitin-protein ligase motif (U-box

protein)

TC91970 Chitinase 2.7 Pathogenesis-related protein

TC85264 Lipoxygenase 2.6 3.8 Lipidperoxidation of membranes, involvement in

lipid signaling


13-1-1

2.6 2.7 Contains ubiquitin-protein ligase motif

(U-box protein)

Plant Mol Biol (2009) 70:627–646 637

123

Table 5 continued


P.s.6 hpib

P.s. hrcC24 hpi

Notes


B13-1-9

2.5 2.9 Similar to NDR1/HIN1-like protein

TC76694 Thaumatin-like protein PR-5b 2.5 2.0 Pathogenesis-related protein

TC85810 12-Oxophytodienoic acid 10

11-reductase

2.4 6.4 Jasmonate synthesis

TC84993 TIR-similar-domain-containing

protein

2.4 R-type resistance protein

TC82984 Beta-1,3-glucanase 2.4 Pathogenesis-related protein


B13-1-1

2.3 Similar to L-ascorbate oxidase

TC79273 Polygalacturonase inhibitor

protein

2.2 2.7 Reduces the hydrolytic activity of

polygalacturonases (PGs), limits the growth of

plant pathogens, and also elicits defense

responses in plant


B13-1-9

2.0 Similar to NDR1/HIN1-like protein

TC83711 Ethylene-induced esterase 1.9 6.0 Similar to a/b-hydrolase fold proteins, induced

by pathogens (e.g., Stuhlfelder et al. 2004)


14-1-1

1.9 5.0 Unknown

TC78169 Glutamate decarboxylase 1.7 4.6 GABA synthesis

TC77085 Putative disease resistance

protein

1.5 Similar to LRR containing R proteins

TC78347 Glutamate decarboxylase 1.4 3.4 GABA synthesis

TC106384 S-adenosyl-L-methionine

synthetase

1.3 Ethylene, polyamine synthesis

TC86521 Allene oxide synthase 1.2 3.9 Jasmonate synthesis

TC77401 Glucan-endo-1,3-beta-

glucosidase precursor

-1.1 Pathogenesis-related protein

TC85023 Pre-hevein-like -1.4 PR-4, Pathogenesis-related protein

TC85176 Lipoxygenase -1.4 Lipidperoxidation of membranes, involved in

lipid signaling

TC81887 1-Aminocyclopropane-1-

carboxylate synthase

-1.4 Ethylene synthesis

TC80461 Thaumatin-like protein -1.5 Pathogenesis-related protein

TC100171 Lipoxygenase -1.6 -3.3 Lipidperoxidation of membranes, involved in

lipid signaling

TC85444 Chitinase -1.7 Pathogenesis-related protein


lipid signaling


lipid signaling


lipid signaling

TC85168 Lipoxygenase -2.1 Lipid peroxidation of membranes, involved in

lipid signaling

TC89520 Major allergen Mal d 1 -2.2 Pathogenesis-related protein (PR-10 related)

TC86064 Glutamate decarboxylase -2.2 -2.4 GABA synthesis

TC87138 Lipoxygenase -2.2 -2.2 Lipideroxidation of membranes, involved in lipid

signaling

TC84912 Methylesterase -2.3 -0.9 -1.6 Methyl jasmonate-cleaving enzyme (Stuhlfelder

et al. 2004)

638 Plant Mol Biol (2009) 70:627–646

123

have an enzymatic role in biological redox reactions (Pang

et al. 2004). Constitutively expressed pirin in epithelial

cells showed that pirin up-regulation is associated with

apoptosis (Gelbman et al. 2007).

Plant cysteine proteases are implicated in regulating the

cell death process. Cystatin is a cysteine protease inhibitor

induced during defense responses to biotic and abiotic

stresses (Sanmartin et al. 2005). Pharmacological cysteine

protease (caspase) inhibitors as well as an overexpression

of cystatin can reduce the degree of plant cell death

(Belenghi et al. 2003). In our experiments, cystatin

(TC77459) was found to be activated during P. syringae

mutant-induced BR (approx. 219); comparatively, it was

activated at even higher levels in tissues undergoing HR

(approx. 459).

The transcription of a Medicago ACD2 homolog

(TC78693) was repressed in P. syringae hrcC-infiltrated

tissues at 6 hpi (about 0.3-fold). In Arabidopsis, an ACD2

mutation has an accelerated cell death phenotype. ACD2 is

involved in chlorophyll breakdown, and the cell death

phenotype of this mutant is the consequence of an accu-

mulation of a toxic chlorophyll intermediate (Mach et al.

2001). The ACD2 mutation in plants cause enhanced dis-

ease resistance and salicylic acid accumulation.

The bax inhibitor-like protein, (BI-1), was activated at 6

hpi during HR. BI-1, which is conserved in animals and

plants and involved in the development of and responses to

biotic and abiotic stresses, can suppress cell death induced

by mitochondrial dysfunction, reactive oxygen species, or

elevated cytosolic Ca2? levels (Huckelhoven 2004).

The transcriptional changes of the above presented cell-

death related genes do not completely explain the result of

the reactions (i.e. cell death or symptomless reaction). The

outcome of such interactions is likely to depend on the

balance of these processes. In HR, the balance may be in

favor of PCD, while in BR, the repressing PCD pathway

may prevail. Since the regulation of PCD is very complex,

other factors not detected by our experiments may also

influence the process.

Protein synthesis-related genes

The need for increased protein synthesis during the BR

response at 6 hpi was indicated by the high number of

activated of ribosomal and protein synthesis genes (75

activated and seven repressed; Supplementary Table 5).

This activation did not last until 24 hpi. Only a few of the

same ribosomal genes were up-regulated by HR-inducing

P. syringae, while another set of these genes was repressed

(one activated and 30 repressed genes; Supplementary

Table 5). The reason for this general repression during HR

could be the dismantling of the protein synthesis apparatus

or, alternatively, a specific regulation during cell collapse.

None of the genes that were induced during BR were

repressed in HR, and the repressed genes in wild-type

infiltrated tissue were not activated in BR. Thus, the

Table 5 continued


P.s.6 hpib

P.s. hrcC24 hpi

Notes

TC89179 Lipoxygenase -2.3 -3.2 Lipideroxidation of membranes, involved in lipid

signaling

TC91861 Hydroperoxide lyase -2.3 -3.2 Oxylipin signaling


lipid signaling

TC85801 Cyanogenic beta-glucosidase -2.5 Releases hydrogen cyanide in response to biotic


TC76502 Cyanogenic beta-glucosidase -2.6 Releases hydrogen cyanide in response to biotic



lipid signaling

TC76779 Aminotransferase 2 -2.7 -3.8 Enhanced expression of this type of enzyme

confers an ability to resist infection by

pathogens (Taler et al. 2004)


lipid signaling

a Bacterial treatments: P. syringae hrcC (P. s. hrcC), P. syringae (P. s.)b Table does not contain those genes that were induced or repressed only after the P. s. treatmentc Average log2 transcription compared to water-injected controld Genes were ordered on the basis of average log2 fold changes

Plant Mol Biol (2009) 70:627–646 639

123

repression may not be the simple result of developing HR

and cell destruction, but rather a regulated process that is

different during BR and HR. Our previous observations

showed that temporal inhibition of protein synthesis is able

to block or delay the development of BR and allow non-

pathogenic bacteria to grow or survive (Bozso et al. 1999;

Klement et al. 2003). The above-described results are

corroborating these earlier observations and show that

intense translation is crucial for developing BR.

Comparison of early (6 hpi) versus late (24 hpi)

transcriptional responses in BR

Some of the plant responses were maintained from 6 to 24

hpi, but there were a number of significant alterations in the

transcriptome as well that are summarized here. (1) The

repression of photosynthesis/cloroplast-related genes was

decreased (188 vs. 29 at 6 and 24 hpi, respectively), sug-

gesting that the recovery of plant photosynthetic capacity

and chloroplast-related metabolic processes are important

for effective long-lasting defense (data not shown). (2) No

activated ribosome/protein synthesis-related genes were

found at 24 hpi, implying the decreased requirement of

protein synthesis during this phase of defense. (3) Only few

early transcription factors and genes involved in signal

transduction retained their altered activation, while new

ones were found to be up- or down-regulated at 24 hpi

(data not shown). These factors may regulate the BR

response at a later phase. (4) The defense-related and

phenylpropanoid/flavonoid synthesis genes that were

highly up-regulated at 6 hpi were also activated at 24 hpi,

and only a few newly up- or down-regulated genes from

these classes were found. It seems that these pathways are

continuously activated and may be regulated by those TFs

and/or other signal components that also show permanent

activity during different BR stages. (5) At 24 hpi, cell-wall

fortification genes were still activated (data not shown); in

particular, the repetitive proline-rich protein-encoding

genes and the lignification genes (e.g., genes of dirigent

and laccase-like proteins).

Comparison of resistance responses in leaves

with responses to root symbionts

A comparison of the different types of plant–microbe

interactions may help identify common responses and

specific ones for a particular interaction. In this respect,

M. truncatula is a model for both pathogenic and symbiotic

interactions. We therefore compared our leaf defense

expression data with some published symbiotic transcrip-

tion results. Several papers describe transcriptional changes

during rhizobial and arbuscular mycorrhizal interactions of

M. truncatula. These studies are based either on in silico

analysis of different EST databases or on microarray

experiments in which transcriptional responses to Glomus

fungi inducing arbuscular mycorrhiza and to S. meliloti

bacteria forming nitrogen-fixing nodules are described

(e.g., Fedorova et al. 2002; Liu et al. 2003, 2007; Mergaert

et al. 2003; Brechenmacher et al. 2004; El Yahyaoui et al.

2004; Hohnjec et al. 2005).

Comparison of BR and arbuscular mycorrhizal (AM)

fungi-induced transcriptional changes

Our dataset of the Pseudomonas-infiltrated leaf samples (6

and 24 dpi) was compared with the ones of roots infected

with Glomus mosseae or G. intraradices at 28 days after

infection (Hohnjec et al. 2005). This latter dataset was

produced with the same type of microarrays as the ones

presented here, thus facilitating a comparison between the

sets of data. The comparison of our leaf BR and HR results

with at least twofold Glomus-activated genes in root results

in 36 common genes (Table 6). Most of the Glomus-

activated genes (24 of 36 genes) were repressed at 6 hpi in

either or both BR and HR responses to Pseudomonas.

Examples of these counter-regulated genes were cell wall-

related genes and some TFs. The opposite regulation of

these genes suggests that cell-wall modifications may differ

at this phase of the symbiotic and defense interactions. Of

the 50 most strongly mycorrhizal repressed genes pub-

lished by Hohnjec et al. (2005), 12 showed significant

transcriptional alteration—eight in the same and four in the

opposite direction—at 6 hpi in P. syringae-infiltrated

leaves (Table 6). The four counter-regulated genes can be

part of plant defense reactions suppressed by the fungus to

avoid the plant resistance (e.g., the thaumatin-like genes

that may have antimicrobial activity).

It is assumed that defense- and other stress-related

genes are up-regulated at the initial phase of the AM

fungi–plant interaction (Brechenmacher et al. 2004;

Deguchi et al. 2007). Therefore, our leaf expression data

were also compared with early (6 hpi and 8 dpi) AM

fungi-induced transcriptional changes published by Si-

ciliano et al. (2007) and Liu et al. (2003). These com-

parisons resulted in a limited number of commonly up-

regulated genes—seven of 104 and four of 14, respec-

tively (data not shown). The restricted similarity between

the transcriptional alteration of a bacterially induced leaf

resistance response and a fungal symbiotic interaction

implies that—at least in these phases of interactions—

basically other sets of genes are required. However, more

detailed time course analyses of both interactions could

reveal additional common genes, especially at early

phases of infections.

640 Plant Mol Biol (2009) 70:627–646

123

Table 6 Comparing the direction of M. truncatula gene expressions in P. syringae injected leaves and in S. meliloti induced nodules to the

mycorhizzally activated or repressed genes in roots

ID Homology P.s. hrcC 6 hpi P.s. 6hpi Nodule 20 dpi

Glomus activated genes at 28 dpi

Cell wall

TC87796 Proline-rich protein R R R

TC88957 Polygalacturonase R – A

TC85575 Arabinogalactan R – –

TC87560 Alpha-D-xylosidase R – R

TC80800 Pectate lyase R –

Transport

TC86110a Multifunctional Nodulin 26-like aquaporin Aa – Aa

TC88701 Manganese transporter MtZIP7 – R A

TC77763a Proton pump interactor Aa Aa –

TC77798 Hexose transporter – R –

TC93498a 33 kDa secretory protein Aa – R

Chlorophyll/plastid

TC76657 Photosystem II oxygen-evolving complex protein 2 R R –

TC80501 Chlorophyll b synthase R – –

Cell rescue/antioxidant

TC85394a Endoplasm. reticulum HSC70-cognate binding protein – Aa –

TC78334aL-Ascorbate oxidase Aa – Aa

Signal trasduction/transcription regulation

TC77052 Myb-family transcription factor R R –

TC80104 LRR receptor-like protein kinase – R –

TC86792 Putative two-component response regulator R R –

TC78355 TINY-like protein – R –

Protein synthesis/degradation

TC79071a Serine carboxypeptidase Aa – R

TC86655a 40S Ribosomal protein S12 Aa – R

TC90126a Peptidase Aa Aa Aa

TC80768 Prolyl oligopeptidase R – –

TC78396 Putative ubiquitin C-terminal hydrolase – R –

Others

TC81478 UDP-glucoronosyl/UDP-glucosyl transferase R – –

TC88442 Beta-hydroxyacyl-ACP dehydratase – R –

TC87200 Acetylornithin aminotransferase – R –

TC86231 Protein disulphide isomerase – R –

TC85778 NFU1 iron-sulfur cluster assembly factor R R –

TC86035a Triacylglycerol lipase Aa – –

TC78048 Gibberellin-regulated protein GASA4 R – R

TC78620a Cytochrome P450 – Aa –

TC77051a Mevalonate disphosphate decarboxylase – Aa –

TC79248 Zinc-finger protein – R A

TC76661 Albumin 1 (leginsulin) R – R

TC87973a Putative hydrolase – Aa Aa

TC89053 Hypothetical protein – R –

Glomus repressed genes at 28 dpi

Phenylpropanoid/flavonoid synthesis

TC83381a Caffeic acid O-methyltransferase Ra Ra A

TC77268a Cinnamoyl-CoA reductase Ra Ra –

Plant Mol Biol (2009) 70:627–646 641

123

Comparison of BR and rhizobial-induced transcriptional

changes during nodulation

We compared our BR and HR data with expression results

obtained from the early and late phase of S. meliloti-

induced nodulation published by Lohar et al. (2006) and

Hohnjec et al. (2005), respectively. This comparison

showed that the relationship between symbiotic and BR

gene transcription changes is considerable, but a very

complex one.

By considering only those genes with at least twofold

transcriptional changes detected by Hohnjec et al. (2005)

using the same type of microarrays as the ones presented

here, we identified 434 genes that were common to BR and

late (20 dpi) nodulation (Supplementary Table 6). Four

categories were created for these genes: Group A com-

prises genes activated during both nodulation and leaf BR;

Group B comprises genes repressed during both nodulation

and leaf BR; Group C comprises genes activated during

nodulation and repressed in leaf BR; Group D comprises

genes repressed during nodulation and activated in leaf BR.

Some defense-related genes were activated both in leaf

defense responses and in nodules (group A), such as

resistance gene-like (TIR-NBS type R gene), Avr9/Cf-9

rapidly elicited protein, immediate-early fungal elicitor

protein, syringolide-induced protein, among others. Other

resistance-associated responses were down-regulated in

nodules but activated during leaf defense (group D). For

example, repression of the PR-10 homologs in nodules was

typical. The up- and down-regulation of PR-10 class genes

in nodules has been described by Sikorski et al. (1999) and

Ruiz-Lozano et al. (1999). Further members of group D

were some of the key enzymes of the phenylpropanoid

pathway.

The comparison of our early BR and HR leaf defense-

related data with transcriptional responses in early (1–72

hpi) steps of nodulation (Lohar et al. 2006) showed an

interesting fluctuation in the number of expressed BR and

HR-responsive genes in roots during nodulation (Fig. 3;

Supplementary Table 7). The numbers of the common

genes that showed similar or opposite direction of

expression at 6 hpi in BR and HR samples and at the

certain time points of nodulation (1–72 hpi) were grouped

(see above) and counted (Fig. 3). Since the outcomes of the

comparison between BR and HR have proved to be very

similar, we have concentrated on mostly discussing the

results obtained with BR in the following paragraphs. Two

phases (1 and 24 hpi) of the early nodulation response were

found to be related to leaf defense responses for different

reasons.

At 1 hpi, the number of genes activated both during

nodulation and BR (group A) were relatively high (13/40,

33%, Fig. 3) and even higher if nodulation and HR data

were compared (23/43; 53%, data not shown), which

suggests a rapid defense-like response in roots after

S. meliloti infection. In addition, this group contains sev-

eral defense-associated genes, such as isoflavonoid syn-

thesis and PR-10 genes, and a FLS2-flagellin receptor

Table 6 continued

ID Homology P.s. hrcC 6 hpi P.s. 6hpi Nodule 20 dpi

TC82770a Chalcone reductase Ra Ra A

Defense-associated

TC85429a Nonspecific lipid-transfer protein Ra Ra

TC86847 Thaumatin-like protein – A

Abiotic stress responses

TC76537a Cold acclimation responsive protein Ra – Ra

TC85949a Seed maturation protein LEA 4 Ra –

Others

TC88609 NAC domain protein NAC2 A –

TC90076a RAB1 GTP-binding protein Ra A

TC90894 Anthocyanin 5-aromatic acyltransferase-like protein A A R

TC78918 Suc synthase MtSucS2 – A A

TC86064a Glutamate decarboxylase Ra Ra

Genes that showed significant activation at 28 dpi in mycorhizza [Glomus mosseae- or G. intraradices-infected root (C2) and the most repressed

50 (Hohnjec et al. 2005) genes were compared with genes that were up- or down-regulated at 6 hpi in leaves after P. syringae hrcC (P.s. hrcC)

and P. syringae (P. s.) infiltration (data from this study) and with genes that were activated or repressed (C2 or B0.5) in mature S. meliloti-infected nodule (Nodule) at 20 dpi (data from Supplementary Table 3 of Hohnjec et al. 2005)

A, activated; R, represseda Genes that changed their activation to the same direction both in mycorhizza-infected roots and in either types of P. syringae treatments

642 Plant Mol Biol (2009) 70:627–646

123

homologous gene (TC89068). At 6 hpi, the number of

genes repressed during nodulation but activated during BR

is high (group D) (34/65, 52%; Fig. 3) which suggests the

weakening of defense-associated processes activated at 1

hpi.

At 24 hpi in the nodule, the pronounced high number of

commonly regulated genes (group A: 44/105, 42%; group

B: 41/105, 39%; Fig. 3) together with relative low inver-

sely regulated genes (both groups C and D: 10/105 9.5%;

Fig. 3) suggests that the nodulation response is going in the

same direction as BR. However, there were only a few

genes (namely, isoflavonoid pathway genes) among the

commonly activated ones (group A) that can be directly

linked to defense reactions. This coincides with the inter-

pretation of Lohar et al. (2006), who suggested that, during

nodulation, a cell proliferation process rather than a

defense-related response occurs at 24 hpi .

At later time points (48 and 72 hpi), the number of genes

in all groups (A, B, C, D) were low, suggesting that at these

times there is no strong relationship between the nodulation

response and BR. Comparison of early nodulation genes

and late BR genes (24 hpi) showed less similarity (only 19

common genes; data not shown).

Conclusions

In this paper we focused on transcriptional changes in

plants that occurred during BR in M. truncatula. The BR

seems to be the first resistance response of plant cells

activated by the presence of microorganisms. In the case of

bacterial pathogens, BR induction precedes HR since the

elicitor(s) of BR are present on the bacterial cells even

before TTSS effectors translocate. The BR constitutes the

first line of defense against all invading microorganisms,

including saprophytic bacteria. It is also possible that BR

was the first defense system that evolved and subsequently

formed the base of subsequent resistance responses (e.g.,

HR). Thus, this evolution may be responsible for the sig-

nificant transcriptional overlap between HR and BR. The

quantitative theory of resistance says that there is no

essential, qualitative difference between phenotypically

diverse reactions and that most of the difference can be

explained quantitatively, since only the intensity and tem-

poral pattern of the genes are distinct (Tao et al. 2003). As

such, the extensive overlap between BR and HR observed

here was not unexpected because the HR-inducing bacteria

also first activate BR as well. Thereafter, the HR-related

processes accelerate and intensify the plant response.

However, this does not exclude that HR-specific genes do

exist, such as genes that regulate the cell death processes.

Our comparison of both the activation of M. truncatula

TFs and their Arabidopsis homologs and of the defense and

symbiotic responses confirmed the general nature of BR.

For example, Medicago TFs and their Arabidopsis homo-

logs had a similar transcription pattern after bacterial

infections (Table 4). This implies that there are sets of

ancient core genes that are well conserved in various plant

species. In addition to similarities, specific plant reactions

that activated in one model plant but not in the other may

also exist. For example, in Arabidopsis, no evidence has

been found at the transcriptional level for the induction of

flavanone biosynthetic pathways (Truman et al. 2006),

while in M. truncatula (Bozso, unpublished data) and in

bean (Jakobek and Lindgren 1993), several genes of this

pathway have been found to be up-regulated.

The functional classification of the transcriptionally

modified genes during BR suggests that complex and well-

organized plant reactions must work towards the develop-

ment of an effective defense response. In general, we found

both activated and repressed genes in almost all groups.

Furthermore, in many cases, there were oppositely regu-

lated genes with the same known function in the same

sample. This suggests that fine-tuning of plant response

0

20

40

60

80

100

120

1 6 12 24 48 72

time after S. meliloti root infection (hpi)

R Nodule-A Leaf BR

A Nodule-R Leaf BR

R Nodule-R Leaf BR

A Nodule-A Leaf BR0

10

20

30

40

50

0 12 24 36 48 60 72 84

time after S. meliloti root infection (hpi)nu

mb

er o

f th

e co

mm

on

gen

es in

dif

fere

nt

cate

go

ries

nu

mb

er o

f th

e co

mm

on

gen

es in

d

iffe

ren

t ca

teg

ori

es

Fig. 3 Comparison of M. truncatula transcriptional changes in roots

during early nodulation response and in leaves during P. syringaehrcC-induced early BR (6 hpi). The early nodulation data (induced by

Sinorhizobium meliloti) are derived from Supplementary Tables 2–7

of the article published by Lohar et al. (2006). The transcriptional data

of P. syringae hrcC obtained at 6 hpi were compared to data of early

nodulation (collected at 1, 6,12, 24, 48, 72 hpi). Four categories were

created: Group A, genes activated during both nodulation and leaf BR

(A Nodule–A Leaf); Group B, genes repressed during both nodulation

and leaf BR (R Nodule–R Leaf); Group C, genes activated during

nodulation and repressed in leaf BR (A Nodule–R Leaf); Group D,

genes repressed during nodulation and activated in leaf BR (RNodule–A Leaf). The number of genes in various categories were

scored and plotted. The inset represents the same data by a different

chart type, showing the fluctuation of the defense (BR)-associated

genes during early nodulation better. Filled diamond Activated during

both nodulation and leaf BR, filled square repressed during both

nodulation and leaf BR, filled triangle activated during nodulation and

repressed in leaf BR, filled circle repressed during nodulation and

activated in leaf BR

Plant Mol Biol (2009) 70:627–646 643

123

involving activation or repression of the proper isoenzymes

should be important for the efficient establishment of

defense responses.

Our comparison of the transcriptome changes induced

by BR or HR and mycorrhizal/rhizobial gene alterations

showed that there is a significant overlap of genes involved

in defense and symbiotic plant responses. High similarities

were found with the early phase of S. meliloti infection,

which confirms that this period of symbiotic interaction is

similar to defense reactions and that the suppression of

these responses must be essential for successful coloniza-

tion. However, transcriptional alteration of a gene during

both the resistance response and symbiotic interaction does

not automatically indicate a direct defense function during

symbiosis. It may also imply other more general functions

of the gene that are activated after various stress responses.

The greatest challenge facing researchers in the field is

to isolate and identify the key components for the BR

response in the vast number of transcriptionally modified

genes. There are several approaches that can be used for

this purpose. A candidate gene approach or the identifica-

tion of the genes affected (either induced or repressed) by

bacterial BR suppressors is a promising method by which

to find important BR-related genes. In addition, the tran-

scriptome analysis of legume plants (including Medicago)

during different defense reactions against various patho-

gens and elicitors and a comparison of these data with the

results of other types of plants and with symbiotic

responses will facilitate in the determination of the function

of the genes.

Acknowledgments This research was supported by grants of the

Hungarian National Science Foundation, AT-049318 and K68386.

We thank the GODMAP platform (Gif-sur-Yvette, France) for the use

of their microarray facilities.

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