Abstract
The production of reactive oxygen species (ROS) is one of the first defense reactions induced in Arabidopsis in response to infection by the pectinolytic enterobacterium Dickeya dadantii. Previous results also suggest that abscisic acid (ABA) favors D. dadantii multiplication and spread into its hosts. Here, we confirm this hypothesis using ABA-deficient and ABA-overproducer Arabidopsis plants. We investigated the relationships between ABA status and ROS production in Arabidopsis after D. dadantii infection and showed that ABA status modulates the capacity of the plant to produce ROS in response to infection by decreasing the production of class III peroxidases. This mechanism takes place independently of the well-described oxidative stress related to the RBOHD NADPH oxidase. In addition to this weakening of plant defense, ABA content in the plant correlates positively with the production of some bacterial virulence factors during the first stages of infection. Both processes should enhance disease progression in presence of high ABA content. Given that infection increases transcript abundance for the ABA biosynthesis genes AAO3 and ABA3 and triggers ABA accumulation in leaves, we propose that D. dadantii manipulates ABA homeostasis as part of its virulence strategy.
Introduction
Abscisic acid (ABA) is well-known as the major phytohormone accumulating in response to abiotic stress such as drought, salt, osmotic or cold stresses, and is involved in plant adaptation to these unfavorable conditions (Nambara and Marion-Poll, 2005). For over a decade, the implication of ABA in plant–pathogen interactions has also been clear (Ton et al., 2009; ). As ABA serves as a signal in such a diversity of plant responses to environmental factors, many recent studies have focused on its role in crosstalk between biotic and abiotic stress responses (). When faced with multiple stresses, plants have to prioritize their adaptive responses and, in many cases, ABA promotes abiotic stress responses at the expense of defense reactions to pathogens (Robert-Seilaniantz et al., 2007). ABA mainly exerts this negative role in post-invasive defense, as exemplified by the inhibition of callose deposition and PAMP-induced gene expression elicited by the bacterial pathogen Pseudomonas syringae pv. tomato (). Nevertheless, ABA also promotes stomatal pre-invasive resistance to foliar bacterial pathogens () and stimulates callose accumulation in papillae in response to the fungal necrotrophic pathogen Leptosphaeria maculens (Ton et al., 2009; ). Thus, ABA exhibits contrasted roles in plant defense depending on infection phase and pathogen lifestyle. This highlights the importance of studying each interaction and its kinetics individually.
Abscisic acid modulates plant defense to pathogens through direct and indirect mechanisms. In Arabidopsis, ABA directly decreases phytoalexins, lignin, and salicylic acid (SA) levels by inhibiting expression of many genes important for phenylpropanoid biosynthesis, as PAL1 encoding a phenylalanine ammonia lyase (). Recent studies highlighted the major involvement of ABA in the regulation network of plant defense. It induces the accumulation of HLS1, an histone acetyltransferase that regulates epigenetically defense responses (), enhances expression of defense genes through the down-regulation of many miRNAs () and its effects on cell wall composition and structure influence resistance to pathogens (; Sánchez-Vallet et al., 2012). All these data would explain the negative impact of ABA on pathogen defense in some pathosystems (). ABA may also act through mutualistic antagonism with SA and jasmonic acid (JA)/ethylene (ET) signaling pathways. This seems to be a major mechanism leading to ABA-induced susceptibility to many pathogens (Robert-Seilaniantz et al., 2007; ). Interestingly, modulation of ABA levels has also been described as part of the virulence strategy of plant pathogens. Indeed P. syringae pv. tomato DC3000 induces ABA accumulation and production of ABA signaling components in Arabidopsis, thus favoring bacterial multiplication and disease progression (). Moreover, some pathogenic fungi, such as Botrytis cinerea and Magnaporthe grisea, directly produce ABA, thereby improving the efficiency of the infection process ().
Production of reactive oxygen species (ROS) is another early general response of plants to pathogen attacks. It has both an anti-microbial effect, including cell-wall reinforcement through protein crosslinking, and a signaling role in SA response, systemic acquired resistance (SAR) establishment and hypersensitive response (). Perception of pathogen associated molecular patterns (PAMPs), or bacterial effectors, induces a transduction cascade including ion fluxes and protein kinase activation that in turn enhances ROS production. Plasma membrane-bound NADPH oxidases (RBOH) play a major role in this oxidative burst but apoplastic peroxidases and some apoplast-, chloroplast-, peroxisome-, or mitochondrion-located oxidases have also been implicated in ROS production during plant–pathogen interaction (; ). Interestingly, different mechanisms link ABA levels and redox homeostasis in Arabidopsis seedlings. First, ABA induces the transcription of genes involved in the ROS-scavenging ascorbate-glutathione cycle (). Second, ABA biosynthesis from the carotenoid pigment violaxanthin indirectly lowers the use of the antioxidant ascorbate and decreases ROS levels. Indeed, de-epoxidation of violaxanthin into zeaxanthin in the xanthophyll cycle requires the oxidation of ascorbate into de-hydro ascorbate. This metabolic process would explain why ABA deficient mutants have lower ascorbate contents and accumulate ROS (Ton et al., 2009). proposed another interesting molecular mechanism to explain the inhibition of ROS accumulation in response to ABA. ABA may induce the expression of genes encoding ROS-detoxifying enzymes, through the stabilization of DELLA proteins, which are key regulators in integrating hormone and environmental signals (; Yang et al., 2012). Nonetheless, the inverse effect of ABA has also been described with ABA-overproducer transgenic tobacco plants accumulating ROS in mesophyll cells (Zhang et al., 2009).
Dickeya dadantii (formerly Erwinia chrysanthemi) is a pectinolytic enterobacterium responsible for soft rot on a wide host range of plants including the model plants tomato and Arabidopsis. Soft rot is mainly characterized by disintegration of plant tissues that is due to the production and secretion of cell wall degrading enzymes. These are pectinases and a cellulase secreted by the Out type II secretion system (T2SS) and proteases secreted by the Prt type I secretion system (T1SS). The injection of effectors into host cells by the type III secretion system (T3SS) plays only a minor role in D. dadantii virulence, in contrast to type III dependent bacteria such as P. syringae or Xanthomonas campestris. Before appearance of the ultimate maceration symptom, other virulence factors are required for infection and colonization of plant tissues. Adherence, aggregate formation and motility onto the leaf surface are needed for penetration of the leaf surface. Once inside the apoplast, bacteria encounter environmental stresses such as low iron availability, low apoplastic pH, microaerophilic conditions and the presence of antimicrobial peptides. Perception of and adaptation to these conditions allow bacterial density reaches a sufficient threshold for growth into plant tissues and the production of cell wall degrading enzymes. Of all the stresses bacteria have to cope with, it should be noted that the high concentrations of ROS produced by plants are the first line of defense. Bacteria achieve ROS detoxification with antioxidant enzymes such as superoxide dismutase and through the production of the ROS scavenger blue pigment indigoidine. Bacterial mutants impaired in each of these antioxidant processes exhibit a dramatic loss of virulence demonstrating their major role in infection (see ; Reverchon and Nasser, 2013 for reviews).
Analysis of host plant responses to D. dadantii infection focused mainly on tomato and Arabidopsis defense reactions. Induction of JA and SA pathways (), iron transport and storage (, ) and ROS production associated with cell wall protein cross-linking (; ; ) have been demonstrated. We have also shown that the bacterium induces necrosis around the maceration zone in Arabidopsis leaves, which can stop disease progression (), highlighting the importance of bacterial spread into healthy tissues before the symptoms appear. Phenotypic analyses of plant mutants have, however, shown that in most cases disruption of a single defense reaction has only a weak, if any, effect on disease development. Two notable exceptions are illustrated by the much higher susceptibility of JA-related and AtRbohD Arabidopsis mutants (). Notwithstanding, this broad host-range bacterium is able to bypass the multifactorial defense process induced after infection.
We have previously shown that ABA-deficient tomato mutants exhibit a resistant phenotype () and that ABA-hypersensitive Arabidopsis mutants, identified from a hot-leaf phenotype, are highly susceptible to D. dadantii (Plessis et al., 2011). This revealed that ABA-related modifications of plant physiology strongly influence bacterium multiplication and spread into the leaves of both hosts. In tomato, ABA down-regulates the apoplastic peroxidase activity that generates ROS. This correlates with an ABA-induced susceptibility of tomato plants to D. dadantii (). To date, the effect of ABA on peroxidases and ROS production has not been investigated during infection of Arabidopsis by D. dadantii, a pathosystem where the efficient ROS producing enzyme involved in plant defense has been identified as the RBOHD NADPH oxidase (). In order to investigate the relationships between ABA-related responses and oxidative stress in detail during Arabidopsis infection by D. dadantii, we have studied the implication of ABA during the first stages of Arabidopsis infection. We analyzed ABA status and the regulation of its biosynthesis genes. We have investigated the relationships between plant hormonal status and the bacterial expression of virulence genes using ABA-deficient and ABA-overproducer plants. Finally, using a double mutant deficient for both ABA biosynthesis and RBOHD-related ROS production, our study indicates that, in Arabidopsis as in tomato, ABA modulates oxygen peroxide production via the control of peroxidase activity level. These data highlight the diversity of ROS sources during plant–bacteria interactions.
Materials and Methods
Plant Material and Bacterial Strains
All Arabidopsis mutants used in this study are in the Col-0 background. The ABA-deficient mutant aba3-1 () and the ABA-overproducer transgenic plant 35S::NCED6 () were kindly provided by Annie Marion-Poll (INRA, Versailles, France) and the AtrbohD mutant impaired in a NADPH oxidase-encoding gene (Torres et al., 2002) was provided by Mathilde Fagard (INRA, Versailles, France). Plants were grown under short day conditions at 24°C/19°C (8 h day/16 h night). The seeds were sown by batch in soil and grown for 3 weeks. Seedlings were then transplanted, three plants per pot, to 7 cm × 7 cm pots and grown for a further 3 weeks. The 6 week-old plants were incubated in small transparent containers with abundant watering to maintain 100% humidity 16 h before inoculation and throughout the infection process.
Dickeya dadantii strains used in this study derived from the 3937 wild type (WT) strain and were previously described (). The secretion mutants prtE, outC, and hrcC are respectively impaired in the type I, type II, and type III protein secretion systems. All strains were grown at 30°C in Luria-Bertani LB medium. For plant inoculation, an aliquot of bacterial stock was streaked onto LB solidified medium (1.5% Difco agar) and grown for 2 days. A single colony of each strain was then used to inoculate 5 mL liquid cultures. After 8 h of growth, 100 μL of these cultures were plated on agar medium and incubated overnight. The bacteria were re-suspended in the inoculation buffer (50 mM KPO4, pH 7) to an OD600 of 0.1, corresponding to a concentration of 108 cfu ml-1 and then diluted to the indicated concentrations.
Infection Methods and Symptom Scoring
Symptom progression analysis was performed as described in . Bacteria were diluted in the inoculation buffer to a concentration of 104 bacteria per ml and inoculation was performed by wounding one leaf per plant with a needle and depositing a 5 μl droplet of this bacterial suspension (i.e., around 50 bacteria) onto the wound. This method allows the scoring of individual symptom progression and wounding is necessary to obtain high rates of synchronized disease initiation. Between 20 and 30 plants were tested for each assay. Progression of symptoms was scored for 7 days using the following four stage symptom scale: stage 0, no symptom; stage 1, maceration around the bacterial droplet; stage 2, maceration spreading on the leaf limb; stage 3, maceration of the whole limb. Significance of the observed differences was established using the Fisher’s exact test (two sided p-value).
For RNA isolation, 6 week-old Arabidopsis plants were infected by rapid immersion in a bacterial suspension (5.107 cfu ml-1) in inoculation buffer containing 0.01% (v/v) of the Silwet L-77 surfactant (van Meeuwen Chemicals BV, Weesp, The Netherlands). Aerial plant tissues were collected at different time points post-inoculation and ground in liquid nitrogen to a fine powder. This infection procedure, close to a natural leaf infection by splashing, was compatible with short studies of infection rate and avoided wound-related transcriptional responses ().
The infection by immersion described above did not allow us to detect any hormonal changes during disease progression (data not shown). In order to amplify the plant hormonal response to infection, ABA content was analyzed after syringe-infiltration with about 20 μl of a bacterial suspension (105 or 107 cfu ml-1) of all developed leaves for each plant. This classical infection method (; ) bypasses the bacterial penetration step of leaf infection and greatly increases the number of plant cells directly in contact with bacteria.
RNA Extraction and Analysis
Total RNAs were purified as described in . Briefly, RNAs were extracted in a guanidium isothiocyanate extraction buffer and pelleted by centrifugation on a cesium chloride cushion. Pellets were washed twice with 70% RNAse-free ethanol and dissolved in RNAse-free water. RNA samples were treated with RNAse-free DNAse I (Invitrogen) to remove any DNA contamination. First-strand cDNAs were then synthesized from 2 μg of total RNA using M-MLV reverse transcriptase and oligo(dT20) or random primers for plant and bacterial genes analysis respectively, following the manufacturer’s instructions (Invitrogen).
For quantitative Real-Time PCR analysis, cDNAs were amplified using Maxima® SYBR Green/ROX qPCR Master Mix (Fermentas) according to manufacturer’s license in an Applied Biosystems 7300 Real Time PCR System using the following conditions: 10 min at 95°C followed by 40 amplification cycles each consisting of 15 s at 95°C and 60 s at 60°C. Results were analyzed with the Applied Biosystems Sequence Detection Software v1.3.1.
To normalize the expression data, the Arabidopsis ß-6 TUBULIN gene (TUB6) and the D. dadantii ß subunit of RNA polymerase-encoding gene (RpoB) were used as internal constitutive controls. The comparative quantitation method (ΔΔCt) was used to contrast the different conditions (). Ct values quantify the number of PCR cycles necessary to amplify a template to a chosen threshold concentration, ΔCt values quantify the difference in Ct values between a test and a control gene for a given sample, and ΔΔCt values are used for the comparison between two samples. ΔΔCt values were transformed to absolute values with 2-ΔΔCt to obtain relative transcript levels. References for relative transcript levels were set to one. All primers used for transcript quantification are listed in Table 1.
Table 1
| Name | AGI ID | Forward | Reverse |
|---|---|---|---|
| Primers for plant gene expression studies | |||
| AAO3 | AT2G27150 | AAATCTCCACACCCACTTCG | CCCCATTAACTGCAAACTCC |
| ABA3 | AT1G16540 | AAGAGCAAGCGGTGGATG | GCCAAGCCCAGTAGGATAAC |
| TUB6 | AT5G12250 | TGGATCATGAGTGAGTGAAAAGA | ACCGACCAAACGAAAAGAAG |
| Name | ASAP ID | Forward | Reverse |
| Primers for bacterial gene expression studies | |||
| indC | ABF-0016081 | TCGCTCTGGCTCGTTATCTT | GGCGTCATCCAGGTCATTAT |
| pelI | ABF-0014586 | TGGCGACTATCAGTGGTCTG | ACAGTTGGTGGTGTCCCATT |
| prtC | ABF-0020371 | TGAGCTTTGTGCAGGATCAG | CCAGGAAGTCTACCGAGCTG |
| rpoB | ABF-0014902 | GAATTGGTTACCTGCCGTAGCA | AACGTCCATGTAGTCAACCTGATC |
Primers used for quantitative real-time RT-PCR.
Primer efficiency (E) was calculated from standard curve slope according to E = (10 (-1/slope) – 1) × 100. Primers were selected in a range of 100 ± 5% efficiency.
ABA Content Measurement
The mature leaves of nine plants per time point were infiltrated with a bacterial suspension or with the inoculation buffer. After harvest, leaves were directly frozen in liquid nitrogen and freeze-dried. Pooled dried leaves were ground in a ball mill (Mixer Mill MM200, Retsch) and 100 mg of the powder obtained used for ABA content determination as described by Plessis et al. (2011). Briefly, 2 mL of extraction solvent (acetone, water, acetic acid, 80/19/1, v/v/v) containing 30 ng of 2H-ABA (-)-5,8′,8′,8′-d4 ABA purchased from Irina Zaharia (Plant Biotechnology Institute – National Research Council, Canada) as internal standard were added to the leaf powder and carefully mixed. The supernatant was recovered by centrifugation and the pellet was rinsed with 1 mL of extraction solvent. The extraction solvent was evaporated and the residue was resuspended in 0.5 mL of HPLC solvent (acetonitrile, water, acetic acid, 50/50/0.05, v/v/v). ABA was quantified using LC-ESI-MS-MS system (Quattro LC, Waters1) in positive ionization and multiple reaction monitoring mode. The differences in ABA content between the different samples were assessed using the non-parametric Kruskal–Wallis analysis of variance for each time point. A p-value of ≤0.05 was considered statistically significant.
H2O2 Detection in Leaves
Detection of H2O2 using 3,3′-diaminobenzidine (DAB, Sigma) staining was performed as described by Torres et al. (2002). Twenty to 30 individual plants for each genotype were inoculated on a single leaf with 5 μL of a 5.107 cfu ml-1 bacterial suspension by the wounding method. To compare the different genotypes at the same stage of disease, we selected 12 leaves of each genotype exhibiting a stage 1 symptom (maceration around the bacterial droplet) for staining 24 h post-inoculation.
In vitro Class III Peroxidase Activity Assays
The in vitro peroxidase activity assay was adapted from . Inoculation was performed in the same conditions as described for H2O2 detection and 10 leaves of each genotype exhibiting a stage 1 symptom were harvested and frozen in liquid nitrogen 24 h post-inoculation for enzymatic activity assay. Pooled frozen leaves were grounded to a fine powder using a ball mill and soluble proteins were extracted from tissue, corresponding to about 300 mg of fresh weight, in 1 mL of extraction buffer [100 mM KPO4 pH 7.8; 0.5% v/v Triton X-100; 2% w/v poly(vinylpolypyrrolidone)] by vortexing. Extracts were centrifuged (30 min, 20000 × g, 4°C), supernatants were gel-filtrated though Sephadex G25 columns (PD miditrap G25, GE Healthcare) and eluted with 1.5 mL of 100 mM KPO4 buffer (pH 7.8). The extracts were then concentrated to 50–100 μL using Amicon ultra-4 Centrifugal Filter units (Ultracel-10 membrane) and protein concentrations were determined using the Bio-Rad protein assay. The peroxidase activity assay (200 μL) contained 10 μg proteins, 50 mM Na acetate (pH 5), 8.26 mM guaiacol and 0.03% (v/v) H2O2. OD470mn was followed during 15 min (25°C) in a microplate reader Spectramax 190 (Molecular Devices). Enzyme activity was calculated from plot gradients as the production rate of tetraguaiacol (ε = 26.6 mM-1 cm-1) expressed as μmol min-1 mg-1 total proteins. In all experiments, flat plots were obtained in the absence of H2O2 or protein extract and confirmed the specificity of the assay. The differences in peroxidase activity between all genotypes were assessed by the non-parametric Kruskal–Wallis analysis of variance. The differences that resulted when comparing two genotypes were assessed by the Wilcoxon test. A p-value of ≤0.05 was considered statistically significant.
Results
ABA Enhances Susceptibility of Arabidopsis thaliana to Dickeya dadantii
We have previously shown that ABA hypersensitive mutants of Arabidopsis exhibit an increased susceptibility to D. dadantii indicating a role for ABA in the Arabidopsis resistance response (Plessis et al., 2011). To confirm this hypothesis, we followed symptom occurrence and disease progression after inoculation of D. dadantii WT strain (3937) on the WT genotype Col-0, the ABA-deficient mutant aba3-1 and the ABA-overproducing 35S::NCED6 transgenic plants. Symptoms were scored each day over the first 4 days and then 7 days post-inoculation (dpi) (Figure 1 and Supplementary Table S1). As early as 2 dpi, the aba3-1 mutant had less leaves with symptoms and maceration was not as widespread compared to the WT, whereas the ABA-overproducing genotype had very few healthy leaves and more severe symptoms. Similarly, at the end of the infection process (7 dpi), all maceration had stopped on the ABA-deficient mutant resulting in less severe symptoms than on WT leaves, while ABA-overproducing transgenic plants exhibited complete maceration of most inoculated leaves (Figure 1). These results demonstrate unambiguously the involvement of the phytohormone ABA in both disease initiation and progression during D. dadantii infection of Arabidopsis leaves. This observation led us to hypothesize that D. dadantii may manipulate ABA-content as part of its virulence strategy.
FIGURE 1
Dickeya dadantii Induces ABA Production in Arabidopsis Leaves and Transcription of the Biosynthesis Genes AAO3 and ABA3
We measured ABA levels in Arabidopsis leaves over 24 h after infiltration with a bacterial suspension containing 105 or 107 bacteria per mL (Figure 2). The lowest concentration led to very little maceration 24 h post-inoculation (hpi) while we observed clear symptoms 24 hpi using the highest concentration. We observed a strong increase in ABA levels in infected leaves, but only after 24 hpi with the highest inoculum. Increases in ABA-content were, therefore, only detected once bacterial cell wall degrading enzymes were secreted and the first maceration symptoms observed.
FIGURE 2
Transcriptional activation of ABA biosynthesis genes, mainly 9-cis-epoxycarotenoid dioxygenase (NCED2, NCED3, NCED5), abscisic aldehyde oxidase (AAO3) and molybdenum cofactor sulfurase (ABA3) encoding genes, contribute to increases in ABA levels in response to stress (Nambara and Marion-Poll, 2005). Transcript abundance was determined for these five genes during the first 24 hpi. Of these, only AAO3 and ABA3 exhibited detectable increased transcript levels in response to infection by the WT bacterial strain (3937) as compared to the buffer treatment (Figure 3 and Supplementary Table S2). For both genes, differential transcript accumulation started as early as 6 hpi and increased until 24 hpi.
FIGURE 3
This increase in AAO3 and ABA3 transcripts levels was detected very early during the infection process, before ABA content increased and symptoms appeared, and coincided with the induction of bacterial virulence factor encoding genes, that takes place around 12 hpi (). This suggests that specific bacterial signals could induce ABA accumulation through transcriptional activation of its biosynthesis. We tested this hypothesis by analyzing the expression of ABA biosynthesis genes after inoculation of the prtE, outC, and hrcC bacterial mutants impaired in the secretion of proteases, pectinases and cellulase, and type III effectors respectively (Figure 3). The hrcC mutant induced the AAO3 and ABA3 genes in a manner comparable to the WT strain. Interestingly, the prtE and outC mutants appeared unable to induce AAO3 expression, since the corresponding expression kinetics are not significantly different from that obtained with the buffer inoculation (Supplementary Table S2), and triggered a weak increase in ABA3 transcripts level compared to the WT strain. Indeed, ABA3 expression kinetics obtained after infection by prtE and outC are not significantly or weakly significantly different from that obtained after buffer inoculation (p-value = 0.0830 and 0.0411, respectively) in contrast to the highly significant differences between the WT strain (p-value = 0.0004) or the hrcC mutant (p-value = 0.0006) and the buffer (Figure 3 and Supplementary Table S2). These data indicate that infecting bacteria must secrete both proteases and cell wall degrading enzymes in order to induce ABA biosynthesis gene expression and thereby induce ABA accumulation.
ABA Status in Plant Modulates the Production of Virulence Factors in Bacteria
The positive correlation between symptom severity and ABA contents could relate to a modulation of plant defense by ABA and/or to the influence of the physiological status of the plant tissues on bacterial virulence. To test this latter hypothesis, we analyzed the expression of some bacterial virulence factors encoding genes in the WT bacterial strain inoculated on the WT plant Col-0, the ABA-deficient aba3-1 mutant and the ABA-overproducing 35S::NCED6 transgenic plant. The expression of PelA, PelC, and PelD pectinase-encoding genes was induced about 10 to 30-fold during the infection process (), and showed similar profiles after infection of the different plant genotypes (Supplementary Figure S1). In contrast, the approximately fivefold increase in the accumulation of indC transcripts, involved in the production of the ROS-scavenger indigoidine, observed during the infection of WT (Figure 4A) was abolished in the aba3-1 mutant at 24 and 30 hpi (Figure 4B). To a lesser extent, the 30- and 8-fold increase in expression of pelI and prtC genes, encoding the PelI pectinase and the PrtC protease respectively, observed after Col-0 infection (Figure 4A) were 2- to 5-fold weaker 24 h and 30 h after infection of the aba3-1 mutant (Figure 4B). Accumulation of ABA in Arabidopsis plants infected with D. dadantii is thus an important metabolic modification that is required to fully induce the expression of some bacterial virulence genes. No reproducible increase (i.e., >2) was observed, however, in the expression of virulence factor encoding genes during infection of ABA-overproducing 35S::NCED6 transgenic plants compared to WT (Figure 4), despite D. dadantii provoking more severe disease symptoms in this genotype.
FIGURE 4
ABA Inhibits Infection-Induced Hydrogen Peroxide Accumulation and Decreases Peroxidase Activity in Leaves
The ABA status dependent expression of the oxidative stress-related bacterial indC gene coupled with previous work highlighting the importance of H2O2 production in Arabidopsis-D. dadantii interactions (
FIGURE 5

Rates of progression of soft rot symptoms in ATRBOHD NADPH oxidase deficient genotypes. A single leaf per plant was inoculated with a 5 μL drop of 104 cfu ml-1 bacterial WT strain (3937) suspension onto a needle wound. The number of plants scored for each genotype is indicated and corresponds to the sum of three independent experiments. Significance of the observed differences was established using the Fisher’s exact test (two sided p-value) (see Supplementary Table S1 for statistical values).
Since AtRBOHD was described as the major source of ROS accumulation during Arabidopsis-D. dadantii interaction (
FIGURE 6

Effects of ABA content and AtrbohD mutation on oxidative stress in infected leaves. H2O2 accumulation was analyzed by Diaminobenzidine-staining of WT Col-0, aba3-1, 35S::NCED6, AtrbohD and AtrbohD-aba3-1 leaves 24 hpi. Infection was performed by depositing 5 μL of a 5.107 cfu ml-1 WT bacterial strain (3937) suspension onto a needle-wound. Stage 1 symptoms (see Materials and Methods and Figure 1) were selected for staining comparison. Buffer inoculation was used as control. The experiment was performed three times with similar results and three representative leaves are presented from at least 12 analyzed.
The class III peroxidases enzymes are involved in H2O2 production in response to biotic stresses (
FIGURE 7

Effects of ABA content and AtrbohD mutation on total peroxidase activity in Arabidopsis leaves. Inoculation was performed by depositing 5 μL of a 5.107 cfu ml-1 WT bacterial strain (3937) suspension or buffer onto a needle-wound. Leaves with stage 1 symptoms (see Materials and Methods and Figure 1) were selected for comparison of enzymatic activity. Proteins were extracted, gel-filtrated and concentrated prior to spectrophotometric measurement of total class III peroxidase activity, using guaiacol as substrate. Data represent the mean of 3 replicates ± standard deviation. Non-infected leaves were also analyzed twice for each genotype and the results were equivalent to those of buffer inoculations. The p-value associated with the global multigroup comparison, including the five genotypes (Kruskal–Wallis test) is p = 0.0005 and letters indicate differences (p < 0.05) between genotypes (Wilcoxon test).
Discussion
The virulence determinants of D. dadantii have been extensively studied combining mutant analyses and molecular approaches (
Manipulation of ABA Level and Dickeya dadantii Virulence
Using ABA-deficient or overproducing plants, we have demonstrated that Arabidopsis resistance to the soft rot bacterium D. dadantii is negatively correlated with the accumulation of ABA (Figure 1). Moreover, ABA contents increased in WT plants in response to inoculation (Figure 2), probably establishing favorable physiological conditions for disease progression. We detected this increase only after infiltration of leaves with quite a high inoculum density (107 cfu ml-1) (Figure 2) that introduces many bacterial cells into a broad leaf volume and not with a lower inoculum density (105 cfu ml-1) or when using the immersion method that allows penetration of few bacteria at discrete sites. A similar dependence of increases in ABA levels with infiltrated inoculum concentration has also been observed for interactions between P. syringae and Arabidopsis using equivalent bacterial concentrations (
Several studies described an enhanced production of ABA upon infection by necrotrophic fungi as B. cinerea, Plectosphaerella cucumerina (
A Central Place for ABA in the Interaction between Arabidopsis and Dickeya dadantii
To determine the role of ABA-status in the interaction between Arabidopsis and D. dadantii, we also examined the expression of bacterial virulence factors encoding genes during infection of plants with modified ABA contents. Induction of the expression of three bacterial genes, namely indC, pelI and prtC, was lower at 24 and 30 hpi for infected ABA-deficient aba3-1 plants compared to WT. In contrast, no significant effect was observed on bacterial gene expression from ABA overproduction in 35S::NCED6 plants. We could thus hypothesize that in infected WT plants the induction of ABA biosynthesis was already at a sufficiently high threshold for full induction of bacterial virulence.
Interestingly, among the virulence genes differentially expressed during aba3-1 and Col-0 infection, were prtC and pelI genes that encode proteins secreted through the type I and the type II secretion systems, respectively, and these secretion systems are both required for increased expression of ABA biosynthesis genes (Figures 3, 4). It is thus tempting to speculate that a positive feedback exists during infection between ABA biosynthesis and the production of bacterial enzymes. Interestingly, ABA mutants have been shown to exhibit modified cell wall composition and structure in tomato and Arabidopsis. The aba1-6 mutant of Arabidopsis has lower cellulose content and more cell wall-associated uronic acid than the corresponding WT (Sánchez-Vallet et al., 2012) whereas the sitiens mutant of tomato exhibits, mainly, a higher degree of pectin methylation (
Induction of the indigoidine biosynthesis gene indC expression is also suppressed in infected aba3-1 plants. Indigoidine biosynthesis allows D. dadantii to counter the oxidative burst produced by infected plant tissues (Reverchon et al., 2002). indC expression is only weakly induced by ROS in in vitro-cultured cells, but highly activated in planta (Reverchon et al., 2002;
Peroxidase Activity, Oxidative Stress, and ABA-Induced Susceptibility to Dickeya dadantii
Analysis of plant susceptibility to D. dadantii and DAB-staining performed in this work confirm the strong correlation between resistance and H2O2 production in leaves (Figures 5, 6;
Class III peroxidases are glycoproteins located in vacuoles and cell walls that could catalyze the formation of the superoxide radical ion, which undergoes dismutation to H2O2, as part of plant defense (
Our results suggest that H2O2 accumulation in infected plants that are ABA-deficient could be linked to their high peroxidase activity. In all the genotypes tested, however, infection with the WT D. dadantii strain 3937 failed to increase peroxidase activity in vitro compared to buffer-inoculation, even though the oxidative burst was specific to bacteria-infected leaves (Figures 6, 7). The peroxidase activity we quantified in vitro after protein extraction reflected the amount of class III peroxidases present in the leaf tissues irrespective of their effective activity in vivo. According to
A Likely Direct Effect of ABA on Susceptibility
Abscisic acid increases plant susceptibility to many bacterial and fungal pathogens interacting with the SA-dependent pathway (
In conclusion, we demonstrate here that ABA content in Arabidopsis leaves is a strong determinant of D. dadantii virulence. Our results reinforce that ABA plays a pivotal role during the plant–bacteria interaction through the stimulation of virulence factor expression in invading bacteria and the inhibition of ROS production in plant tissues. This latter effect of ABA appears to result from its negative control of the production of class III peroxidases. The opposite results obtained using ABA deficient or ABA overproducing plants support our conclusions. Thus, manipulation of ABA homeostasis in plants, through the up-regulation of genes involved in the last step of ABA-biosynthesis, is part of the virulence strategy of D. dadantii. Interestingly, ABA would appear to modulate a sentinel process that participates in the basal defense, consisting of the production of a threshold level of peroxidases that are specifically activated in response to pathogen attack.
Statements
Author contributions
FVG, JP, and YK designed the research, interpreted the data and wrote the manuscript. YK, OP, RG, ES-C, AM-G, and PP performed experiments and analyzed data. LB performed statistical analysis for Figure 3.
Acknowledgments
We gratefully acknowledge Helen North for constructive comments, critical reading of the manuscript and English improvement. We thank Marie-Anne Barny and Annie Marion-Poll for their interest to this project and helpful discussions, Mathilde Fagard for providing the AtrbohD seeds and Annie Marion-Poll for the gift of the aba3-1 and 35S::NCED6 genotypes. We also thank Xavier Raynaud for helpful discussions on statistical analyses. Special thanks go to Pierrette Malfatti for her technical support.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Supplementary material
The Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fpls.2017.00456/full#supplementary-material
Footnotes
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Summary
Keywords
abscisic acid, peroxidases, oxidative stress, plant defense, bacterial virulence genes, Dickeya dadantii, Arabidopsis thaliana
Citation
Van Gijsegem F, Pédron J, Patrit O, Simond-Côte E, Maia-Grondard A, Pétriacq P, Gonzalez R, Blottière L and Kraepiel Y (2017) Manipulation of ABA Content in Arabidopsis thaliana Modifies Sensitivity and Oxidative Stress Response to Dickeya dadantii and Influences Peroxidase Activity. Front. Plant Sci. 8:456. doi: 10.3389/fpls.2017.00456
Received
17 November 2016
Accepted
15 March 2017
Published
03 April 2017
Volume
8 - 2017
Edited by
Víctor Flors, Jaume I University, Spain
Reviewed by
Mario Serrano, Center for Genomic Sciences (UNAM), Mexico; Antonio Molina, Universidad Politécnica de Madrid, Spain
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© 2017 Van Gijsegem, Pédron, Patrit, Simond-Côte, Maia-Grondard, Pétriacq, Gonzalez, Blottière and Kraepiel.
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*Correspondence: Yvan Kraepiel, yvan.kraepiel@upmc.fr
†Present address: Frédérique Van Gijsegem, Jacques Pédron, and Yvan Kraepiel, iEES Paris, Paris, France
This article was submitted to Plant Microbe Interactions, a section of the journal Frontiers in Plant Science
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