Characterization of the expression of transcriptionally silent loci during the plant response against Pseudomonas syringae

Nataša Hulak TESIS DOCTORAL 2014 Characterization of the expression of transcriptionally silent loci during the plant response against Pseudomonas syringae Nataša Hulak TESIS DOCTORAL 2014 Universidad de Málaga-CSIC Departamento de Biología Celular, Genética y Fisiología Instituto de Hortofruticultura Subtropical y Mediterránea (IHSM) AUTOR: Nataša Hulak EDITA: Publicaciones y Divulgación Científica. Universidad de Málaga Esta obra está sujeta a una licencia Creative Commons: Reconocimiento - No comercial - SinObraDerivada (cc-by-nc-nd): Http://creativecommons.org/licences/by-nc-nd/3.0/es Cualquier parte de esta obra se puede reproducir sin autorización pero con el reconocimiento y atribución de los autores. No se puede hacer uso comercial de la obra y no se puede alterar, transformar o hacer obras derivadas. Esta Tesis Doctoral está depositada en el Repositorio Institucional de la Universidad de Málaga (RIUMA): riuma.uma.es Nataša Hulak Characterization of the expression of transcriptionally silent loci during the plant response against Pseudomonas syringae TESIS DOCTORAL Málaga, 2014 Memoria presentada por Nataša Hulak para optar al grado de Doctora por la Universidad de Málaga Characterization of the expression of transcriptionally silent loci during the plant response against Pseudomonas syringae Directores: Dra. Carmen R. Beuzón López Dra. Araceli Castillo Garriga Área de Genética Departamento de Biología Celular, Genética y Fisiología. Instituto de Hortofruticultura Subtropical y Mediterránea “La Mayora” (IHSM) Universidad de Málaga IHSM-UMA-CSIC Málaga, 2014 Este trabajo ha sido financiado por el proyecto P07-CVI-2605 de “Junta de Andalucía” (co-financiado por FEDER) y por la Beca para la Formación de Personal Investigador, JAE-Pre-111 (2009-2013), concedida por Consejo Superior de Investigaciones Científicas, CSIC. Área de Genética. Departamento de Biología Celular, Genética y Fisiología. Instituto de Hortofruticultura Subtropical y Mediterrénea (IHSM). Universidad de Málaga-Consejo Superior de Investigaciones Científicas. La Dra. Araceli Castillo Garriga, Profesor Contratado Doctor, y la Dra. Carmen R. Beuzón López, Profesor Titular, del Área de Genética del Departamento de Biología Celular, Genética y Fisiología INFORMAN: Que la tesis doctoral titulada “Characterization of the expression of transcriptionally silent loci during the plant response against Pseudomonas syringae.”, presentada por Natasa Hulak en esta memoria para optar al título de Doctor por la Universidad de Málaga, ha sido realizada bajo su dirección y supervisión en el Área de Genética, y de que reúne los requisitos exigidos para su defensa pública. Y para que así conste y tenga los efectos que correspondan en cumplimiento de la legislación vigente, extienden el presente informe. En Málaga a 7 de noviembre de 2014 Araceli Castillo Garriga Carmen R. Beuzón López Index Introduction 1 1. Pseudomonas syringae 3 1.1. The type III secretion system 4 2. The plant response against P. syringae 5 2.1. Pattern recognition receptors and pathogen-associated molecular patterns 6 2.2. Effector-mediated suppression of PAMP-triggered immunity 7 2.3. Effector-triggered immunity and suppression of effector-triggered immunity 8 2.4. The role of salicylic acid and coronatine during plant interaction with Pto 10 3. Epigenetic mechanisms: DNA methylation in plants 11 4. Role of DNA methylation and demethylation in response to pathogen attack 14 Objectives 17 Material and methods 21 1. Bacterial strains and growth conditions 23 2. Motility test (swimming) 23 3. Plasmids and cloning procedures 23 4. Generation of knockout mutants in Pseudomonas syringae pv. tomato 26 5. Plant material, growth, and treatment conditions 26 6. Bacterial inoculation procedure in plants 27 7. Mixed infection assay (Competitive Index, CI) 28 8. Southern blot 29 8.1. Chemiluminescence (Digoxigenin) 30 8.2. Radioactivity (radioisotope alpha phosphate 32P) 31 9. Plant genome methylation status by Chop-PCR 32 10. RNA extraction, qRT-PCR and semi-quantitative RT-PCRs 33 11. Histochemical staining of GUS activity 34 Chapter 1: Pseudomonas syringae pathovar tomato induces changes on Arabidopsis DNA methylation pattern and up-regulates transcriptionally silent loci 43 1.1. Arabidopsis thaliana infections with Pto DC3000 45 1.2. DNA hypomethylation upon Pto DC3000 infection 46 1.3. Transcriptional activation of silent loci upon Pto DC3000 infection 56 1.4. Changes on AtSN1 methylation levels by Chop-PCR 62 1.5. Activation of a transcriptionally silent GUS transgene upon Pto DC3000 infection 65 Chapter 2: Role of bacterial virulence determinants in the transcriptional activation of the retrotransposon AtSN1 67 2.1. Role of the T3SS in determining AtSN1 transcript levels 69 2.2. Identification of type III effector proteins potentially involved in the transcriptional activation of the retrotransposon AtSN1 71 2.3. Generation of type III secretion system single mutant effectors from Pseudomonas syringae pv. tomato. 74 Chapter 3: AtSN1 transcript accumulation during different plant defence responses against P. syringae 83 3.1 AtSN1 transcript accumulation during basal defence response against P. syringae 85 3.2 AtSN1 transcript accumulation is enhanced during effector-triggered immunity against P. syringae 88 Chapter 4: Role of key genes in establishing and maintaining plant DNA methylation levels in the plant defence response against Pto DC3000 93 4.1 Analysis of the impact of Pto DC3000 infection on the expression of plant methylases and demethylases 95 4.2 Bacterial entry and development of disease in plant DNA methylation mutants 96 4.3 Bacterial replication in DNA methylation mutant plants 102 4.4 Analysis of the role of ROS1 in activation of AtSN1 during the infection 108 Concluding remarks 111 Conclusions 119 References 123 Resumen de la tesis en español 133 Notes 151 Introduction Introduction 1. Pseudomonas syringae Pseudomonas syringae is a rod shaped, Gram-negative, hemibiotrophic bacterium with polar flagella, which elicits a wide variety of symptoms in plants, including blights, leaf spots and galls (Figure 1). The species is divided into pathogenic variants (pathovars) which vary in host range (Peñaloza-Vazquez et al., 2000). There are more than 50 different pathovars described, some of which are further divided into races based on host range among cultivars of the host species (González et al., 2000; Hirano and Upper, 2000). Pseudomonas syringae survives on the leaf surfaces of plants as an epiphyte before it enters into the intercellular space, through natural openings such as stomata or wounds, to initiate the infection process (Hirano and Upper, 2000). P. syringae pv. tomato (hereafter Pto) DC3000, the main model strain for studying P. syringae interaction with the host, is the causing agent of bacterial speck in tomato, and is also capable of causing disease in the model plant Arabidopsis thaliana. Figure 1. Symptoms exhibited by Arabidopsis leaves infected with Pseudomonas syringae pv. tomato strain DC3000. Water-soaked areas of collapsed tissue are surrounded by chlorotic tissue 48 hours after initial infection. The Pto DC3000 genome (6.5 megabases) contains a circular chromosome and two plasmids, which collectively encode 5,763 ORFs (Collmer et al., 2002). The genetic basis of pathogenicity and virulence in P. syringae is complex and includes global regulators (Hrabak and Willis, 1992; Kitten et al., 1998; Rich et al., 1994), the hrp cluster, which encodes a type III secretion system (T3SS), as well as virulence factors such as phytotoxins (e.g. coronatine) and exopolysaccharides (Bender et al., 1999; Yu et al., 1999). Once inside its host, P. syringae survives and proliferates within the intercellular spaces between plant cells, the apoplast, where through the action of the Hrp T3SS translocates a set of highly specialized proteins, called effectors, across the host cell wall into the neighbouring plant cells. Once 3 Introduction inside the host cytosol, the effector proteins work to suppress the plant immune system, allowing bacterial growth within the apoplast (Göhre and Robatzek, 2008). Mutant derivatives unable to translocate effectors, i.e. T3SS mutants, are severely restricted for growth within the host by the plant immune system and do not cause disease (Mohr et al., 2008). 1.1. The type III secretion system The T3SS is a complex secretion apparatus composed of approximately 30 different proteins. This sophisticated apparatus couples secretion across the bacterial inner and outer membranes with translocation across eukaryotic cytoplasmic membranes, as well as across the cell wall in the case of T3SS from plant pathogenic bacteria (Nguyen et al., 2000). T3SS are essential for pathogenicity (Cunnac et al., 2009). The genes encoding type III secretion systems—especially those genes which encode the secretion apparatus—are clustered. In some organisms, these gene clusters are located on plasmids which are unique to the pathogen and are not found in non-pathogenic relatives (Yersinia spp., Shigella flexneri, and Ralstonia solanacearum) (Galán and Collmer, 1999). In other pathogens (Salmonella typhimurium, Enteropathogenic E. coli (EPEC), Pseudomonas aeruginosa, P. syringae, Erwinia amylovora, and Xanthomonas campestris) (Orth et al., 2000), the T3SS gene clusters are located on the chromosome and often appear to have been acquired by horizontal transfer, since related non-pathogenic bacteria lack these pathogenicity islands but share the corresponding adjacent sequences. The function of the T3SS apparatus involves three different protein classes; (i) Structural proteins: build the base, the inner rod and the needle, (ii) Effector proteins: get secreted into the host cell and promote infection through suppressing host cell defences, (iii) Chaperones: bind effectors in the bacterial cytoplasm, protect them from aggregation and degradation and direct them towards the needle complex (Anderson et al., 2010). P. syringae strains also encode some helper proteins, type III-secreted proteins which assist effectors to translocate across the plant cell membrane, but do not enter themselves into the cytoplasm of the host cell, and harpins, proteins 4 Introduction secreted in a type III–dependent manner that remain outside the host cell where they can elicit host responses (Choi et al., 2013). Functional analysis of the Pto DC3000 genome showed several clusters of genes jointly encoding type III effectors (T3Es), 31 confirmed, and 19 predicted (Collmer et al., 2002). The Pto DC3000 T3Es, known as Hop (HR and pathogenicity outer protein) or Avr (avirulence) proteins based on the phenotype by which they were discovered (Collmer et al., 2002), have been comprehensively analyzed and 28 of them have been shown to be well-expressed and deployed during infection (Lindeberg et al., 2006). T3Es are collectively essential for pathogenicity, but individually dispensable for the bacteria to defeat defences, grow, and produce symptoms in plants. Eighteen of the Pto DC3000 effector genes are clustered in six genomic islands/islets (Collmer et al., 2009). Members of effector gene paralogous families are scattered around the genome and have an unusually low G+C content, indicating that such families may have been acquired by sequential horizontal acquisitions (Collmer et al., 2002). 2. The plant response against P. syringae Plants react to pathogen attack using layered defence responses which mostly differ in the type of molecules from the pathogen that each one detects, and the speed and intensity of the resulting responses. The first layer of defence is activated upon pathogen detection through the action of pattern recognition receptors. 5 Introduction 2.1. Pattern recognition receptors and pathogen-associated molecular patterns Plants are capable of restricting colonization and growth of a very large number of microbial pathogens. This successful outcome is mostly due to the activation of receptors located on the plant cell surface called Pattern Recognition Receptors (PRRs). These receptors are proteins that recognize well-conserved microbe-specific molecules known as pathogen-associated molecular patterns (PAMPs, or microbe-associated molecular pattern or MAMPs, depending on the authors). Arabidopsis encodes numerous PRRs (47 identified to date). One of the best characterized PRR is FLS2, which perceives flagellin, the main component of the bacterial flagella (Boller and Felix, 2009). FLS2 is highly conserved among plants species (Zipfel et al., 2004) and is capable of alerting the plant of an incoming intruder, even before the bacteria penetrate into the leaf (Melotto et al., 2006). Many pathogen bacteria possess flagella, which is mostly formed by a polymer of flagellin. Even though the entire flagellin is considered to acts as a PAMP, only a conserved 22 amino acid segment from the N-terminus is required for recognition (Felix et al., 1999). This 22 amino acid peptide is commercially available and is known as flg22. Most mutations that allows flagellin to avoid recognition by FLS2 render non-motile bacteria (Naito et al., 2008). Upon recognition of these conserved microbial features or PAMPs, the plant triggers an immune response, which involves activation of MAPK (mitogenactivated protein kinase) signalling and downstream signalling cascades that lead to the induction of defence genes (pathogen-response genes), production of reactive oxygen species in an oxidative burst, and callose deposition at the sites of infection to reinforce the cell walls, all of which contribute to restrict bacterial growth (Schwessinger and Zipfel, 2008). This process is known as PAMP-triggered immunity or PTI (Figure 2). PTI activation is a slow process and the intensity of the response builds up with time. This slow activation is befitting of an immune response that does not discriminate between pathogenic and non-pathogenic microorganisms and allows the plant to prevent colonization by most microbes. However, the slow initial kinetics of its activation can be exploited by adapted pathogens, which have evolved to 6 Introduction acquire additional functions that specifically target and suppress PTI, preventing the response from reaching enough intensity to effectively protect the plant. 2.2. Effector-mediated suppression of PAMP-triggered immunity Effectors have evolved to contribute to the virulence capacity of the pathogen and to overcome the host. A mayor function of the T3SS in plant pathogenic bacteria is to suppress PTI in the host (Figure 2). PTI suppressing activity has been demonstrated for many T3 secreted effectors (T3Es), although the molecular mechanisms involved are their suppression is still to be determined for most of them. In recent years, many reports have shown different ways in which pathogens are able to overcome the host basal defences. There are three main strategies by which pathogens overcome PTI: (a) suppressing the PTI activation through the action of effectors, (b) circumnavigating PTI activities through the production of toxin type effectors or (c) degrading bioactive products of PTI through sophisticated detoxification mechanisms (Anderson and Singh, 2011). There are several examples of pathogen effectors capable of suppressing specific aspects of the plant’s defence. One of these examples in Arabidopsis, is the suppression of the activation of PTI following perception of flg22 by T3Es AvrPto, AvrPtoB and HopAI1. These Pto effectors have been shown to suppress PTI by blocking MAPK activation (De Torres et al., 2006; He et al., 2006; Zhang et al., 2007). In addition to suppression of host defences, some effectors may also assist the pathogen in evading detection by PRRs by suppressing signalling directly downstream of PRR (Boller and He, 2009). Thus, adapted pathogens use effectors to effectively overcome the PTI and as a result the pathogen can proliferate and the plant undergoes a process known as effector-triggered susceptibility or ETS (Figure 2). ETS leads to the development of disease as an outcome from the pathogen interaction with the host. This is also known as a compatible interaction. However, during plantpathogen co-evolution, plants have evolved resistance (R) genes that allows them to detect pathogen effectors (or the effect of the effectors on a plant 7 Introduction 4. Role of DNA methylation and demethylation in response to pathogen attack In the last few years works with mammalian pathogens have demonstrated that histone modifications and chromatin remodelling regulate gene expression and are thus key targets for mammalian pathogen manipulation during infection (Hamon and Cossart, 2008). One such obvious target is the host’s immune system. In recent years, the epigenetic modulation of the host’s transcriptional program linked to host defence genes has emerged as a relatively common event of pathogenic viral and bacterial infections (GómezDíaz et al., 2012; Paschos and Allday, 2010). In plants, less is known about how pathogens alter the host epigenome and its consequences. It has been proposed that cytosine methylation is one of the major host defence mechanisms against plant DNA viruses, such as geminiviruses, and therefore these viruses have evolved different suppressor proteins to interfere with repressive methylation and transcriptional silencing of viral DNA (Raja et al., 2010). By interfering with the proper functioning of the plant methylation machinery, geminiviral proteins implicated in suppression of cytosine methylation can reverse transcriptional gene silencing (TGS) at transgenic and endogenous loci repressed by cytosine methylation (Raja et al., 2010; Rodríguez‐Negrete et al., 2013; Zhang et al., 2011) confirming that plant pathogens modify the plant epigenome during infection. Studies using phytopatogenic bacteria have brought increasing evidence that bacterial plant pathogens alter the host epigenome during their interaction with the plant and that plants have evolved specific defences against the TGS suppression orchestrated by pathogens. Pavet and collaborators were the first to report that infection with Pto DC3000 induces rapid DNA hypomethylation at pericentromeric repeats, including repeats such as the 180-bp unit and Athila retrotransposon, and decondensation of chromocentres on Arabidopsis (Pavet et al., 2006). The authors showed that these responses occur 24 hours after the inoculation and that the DNA hypomethylation induced by Pto was not associated to DNA 14 Introduction replication, suggesting that it involves an active demethylation process (Pavet et al., 2006). A second study that profiled the entire Arabidopsis DNA methylation status, revealed that many genomic regions enriched in transposon sequences become differentially methylated on infection by virulent and avirulent Pto, or following treatment with exogenous SA. Moreover, many of these changes in methylation affect expression of neighbouring protein-coding genes, including defence-related genes (Dowen et al., 2012). In addition, they demonstrated that bacterial growth of avirulent or non pathogenic P. syringae strains was restricted in mutants presenting genome-wide changes in DNA methylation, such as met1-3 (null allele of the CG maintenance DNA methyltransferase, MET1) or ddc (triple mutant drm1-2 drm2-2 cmt3-11, affected on DRM1, DRM2 and CMT3 DNA methyltransferases) mutants, indicating that loss of DNA methylation enhances resistance to bacteria in an unspecific manner. A third study revealed that treatment of Arabidopsis plants with the flagellin peptide flg22, causes a rapid and transient downregulation of key RdDM pathway components, including AGO4 and the RNA polymerase IV (Pol IV) subunit NUCLEAR RNA POLYMERASE D 1A (Yu et al., 2013). This downregulation occurred as early as 3 hours post-treatment and was sufficient to reactivate several well-characterized endogenous RdDM target loci such as the transposons Onsen, EVADE and AtSN1, as well as a transposon-based reporter transgene undergoing TGS. This effect was reversible, as DNA methylation and TGS were already restored to previous levels, 9 hours after flg22 treatment. This response induced by flg22 was facilitated by the DNA glycosylase ROS1, which is the main de novo demethylase in vegetative tissues. A mild enhanced bacterial growth was observed in ros1-infected plants, but not in the DEMETER-like 2 (dml2) and dml3-infected loss-of-function mutants, supporting a role for ROS1dependent DNA demethylation in antibacterial resistance (Yu et al., 2013). Spontaneous HR and increased SA-mediated signalling observed in RdDM mutants are all indicative of the constitutive activation of R genes, suggesting that RdDM might negatively regulate the expression of at least some R genes. Yu and collaborators demonstrated that at least two R genes, RESISTANCE 15 Introduction METHYLATED GENE 1 (RMG1) in wild-type plants and WRKY22 in flg22treated plants, are subjected to extensive RdDM and were overexpressed in RdDM mutants (Yu et al., 2013). These recent studies with phytopatogenic bacteria suggest that RNA-directed DNA methylation (RdDM) and transcriptional gene silencing (TGS) have an important role in plant disease (Pumplin and Voinnet, 2013). Dampening defence gene expression through RdDM could provide an effective mode of regulation since RdDM can be rapidly reversed by biotic and abiotic stresses. The rapid activation of plant defences would require the presence of RdDMprone genomic segments (transposons and repeats) in the vicinity of defencerelated genes and the involvement of active demethylation pathways to ensure optimal and rapid defence gene induction upon pathogen attack. In addition, the dampening of RdDM and the resulting defence gene activation occurs only transiently, to prevent the prolonged induction of these stressresponsive plant genes. This feature is foreseeably advantageous in the case of defence-related genes whose continuous expression reduces plant fitness. 16 Objectives Objectives • To analyse changes in Arabidopsis thaliana DNA methylation levels during its interaction with Pseudomonas syringae and their implication on the activation of transcriptionally silenced loci (TGS loci). • To determine the role of P. syringae virulence determinants in the activation of TGS loci in Arabidopsis. • To analyse the transcriptional state of Pto DC3000-activated TGS loci in Arabidopsis during different defence responses. • To investigate the role of genes involved in establishing and maintaining plant DNA methylation in the defence responses of Arabidopsis against P. syringae. 19 Material and methods Materials and methods 1. Bacterial strains and growth conditions Bacterial strains used in this work are listed in Table M1. Bacteria were grown at 37ºC (Escherichia coli) or 28ºC (Pto DC3000 and its derivative strains) in Lennox Broth (LB), a modification of Luria-Bertani broth with the NaCl concentration halved (tryptone 20 g/L, yeast extract 10 g/L, NaCl 10 g/L, bacteriological agar 16 g/L) (Lennox, 1955) or SOB liquid medium (tryptone 20 g/L, yeast extract 5 g/L, NaCl 0.5 g/L, 10 ml/L of 250 mM of KCl, pH adjusted to 7.0 using 5 M NaOH) (Hanahan, 1983). King’s B (KB) medium (King et al., 1954) (29 g/L of bactoproteose peptone, 1.5 g/L of K2HPO4, 8 ml/L of glycerol, pH adjusted to 5.7 with KOH) was used for motility assays. When needed, media were supplemented with antibiotics at the concentrations detailed in Table M2. 2. Motility test (swimming) Strains were grown at 21ºC for 72 hours on LB plates. Bacterial lawns were re-suspended in 10 mM MgCl2 to reach an OD600 of 2. Two µL of bacterial suspension were deposited at the centre of a soft agar plate containing KB medium supplemented with 2.5 g/L of agar. Five ml/L of sterile 1 M MgSO4 was additionally added after autoclaving, to avoid the medium from becoming cloudy. The diameter of the bacterial growth halo was assessed after 2-3 days of incubation in darkness at 25ºC. 3. Plasmids and cloning procedures Vectors used in this project were pGEM-T Vector System (Promega; Madison, WI, USA), pKD4 (Datsenko and Wanner, 2000) and pBluescript SK(+) (pBSSK+) (Agilent Technologies, Inc. 2010). To generate pGEMT -CMP (CMP, repetitive centromeric sequences, 180-bp repeats) and pGEMT -Athila, a PCR was performed using genomic DNA from Arabidopsis as a template, and the corresponding primers listed in Table M3. PCR for pGEMT -CMP was performed as follows: 94ºC for 3 min, followed by 30 cycles at 94ºC for 20 s, 60ºC for 30 s, and 72ºC for 30 s, and followed by 7 min at 72ºC. PCR for pGEMT -Athila was performed as follows: 94ºC for 3 min, followed by 33 cycles at 94ºC for 30 s, 58ºC for 50 s, and 72ºC for 1 23 Materials and methods 8.1. Chemiluminescence (Digoxigenin) Genomic DNA extraction of Pto was carried out using Jet Flex Extraction Kit (Genomed; Löhne, Germany). Two µg of genomic DNA was digested. The reactions were left overnight at the corresponding temperature in a volume of 50 µL. The restriction enzymes were selected by detailed analysis of the DNA sequence flanking the deletion sites, using the DNAStar suite (DNASTAR Inc., USA) or an online tool for restriction analysis, such as WatCut (WatCut: An on-line tool for restriction analysis, silent mutation scanning and SNP-RFLP analysis, http://watcut.uwaterloo.ca/template.php). Samples were run in a 0.8% agarose gel at 60 V for 4-5 hours, and stained with EtBr for visualization. Gels were treated with HCl 0.25 M during 15 min, washed 3 times with distilled water, then treated for 30 minutes with denaturing buffer (1.5 M NaCl, 0.5 M NaOH), and neutralized (3 M NaCl, 0.5 Tris, pH 7) for 30 min. DNA transfer was done by setting 15-20 kitchen paper towels, 3 Whatman papers, previously sunken into SSC 20x buffer (3 M NaCl, 0.3 M C6H5Na3O7 (sodium citrate), the agarose gel, a Nylon membrane (Sigma, 0.45 µm pore size), and 3 Whatman papers, previously sunken in SSC 20x buffer and 15-20 kitchen paper towels under a weight, and let the transfer take place overnight. The membrane was cross-linked using UV light at 1,200 J/m2. Prehybridization of the membrane was done for 2 hours at 65ºC with the corresponding prehybridization buffer ( SSC 5x, 1% of blocking reagent, 0.1 % N-lauryl sarcosine (p/v), 0.1% NaCl (p/v), 0.02% SDS (p/v)). Hybridization with the probe (previously denatured and diluted into prehybridization buffer), was performed at 65ºC, overnight. A fragment containing the nptII kanamycin resistance gene was used as a probe and labelled by PCR using the chemiluminescent digoxigenin-dNTPs DIG Labelling Mix (Roche; Mannheim, Germany), plasmid pKD4 (GenBank AY048743) as a template and primers P1 and P2 (Table M3). After incubation with the probe, the membrane was rinsed with SSC1x (0.30 M NaC6H5O7, 0.030 M NaCl buffer), and incubated twice for 5 min at room temperature with 0.1% SDS. The membrane was then incubated three times with SSC 0.5% and 0.1% SDS for 10 min at 65ºC, and finally washed with Washing buffer (70 mM maleic acid, 150 mM NaCl, pH 7.5 and 0.3% Tween 20) for 5 30 Materials and methods min. The membrane was then incubated for 30 min with Buffer 2 (70 mM maleic acid, 150 mM NaCl, pH 7.5, 1% blocking reagent (w/v)), previously warmed up to 60ºC . The membrane was then incubated for 1h and 30 min in a solution containing the anti-digoxigenin antibody (dilution of 1:10,000 of DIG DNA Labelling Mix, 10x., Roche Diagnostics GMBH, Germany, in Buffer 2), at room temperature. The membrane was washed twice for 15 min at room temperature with Washing buffer and for 5 min with 20 mL of Buffer 3 (0.1 M Tris, 10 mM NaCl, 50 mM MgCl2, pH 9.5). Finally, the membrane was incubated at 37ºC for 15 min in CSPD, a substrate that belongs to the group of the dioxetane phenyl phosphates that upon dephosphorylation by alkaline phosphatase, forms an intermediate that when decomposed results in light emission which can be recorded on X-ray film (Roche, Mannheim, Germany). 8.2. Radioactivity (radioisotope alpha phosphate 32P) Arabidopsis genomic DNA was extracted using Jet Flex Extraction Kit (Genomed; Löhne, Germany). Three to five micrograms were digested with Sau3AI. Sau3AI is a type II endonuclease that cleaves GATC sequences. Its activity is inhibited by cytosine C5-methylation. The reaction was performed in a final volume of 200 µL for 2 h 30 min at 37ºC. The DNA was precipitated (NaOAc 3 M, pH 5.2, 1 µL glycogen) with 2 volumes of ice-cold 100% ethanol, incubated at -20ºC for 20 min, and centrifuged for 20 min at 5,000 g. The pellet was washed with 500 µL of ice-cold 70% ethanol, centrifuged for 5 more min at 5,000 g and dried for 5 min at 65ºC. The pellet was resuspended in 50 µL of miliQ water and left at 4ºC overnight. Samples were run in 1.2% agarose gels at 80 V for 5 h. The gel was treated for 10 min with 0.25M HCl, rinse 3 times with dH20, then denatured for 30 minutes (1.5 M NaCl, 0.5 M NaOH), rinsed 3 times with miliQ water, and neutralized (3 M NaCl, 0.5 Tris, pH 7) for 30 minutes followed with 3 rinses in dH20. The DNA in the gel was transferred onto a nylon membrane overnight as described above for digoxigenin labelling. After transfer, the membrane (Sigma, 0.45 µm pore size) was treated in a UV cross-linker at 1,200 J/m2 and left at 70ºC for 3 hours. 31 Materials and methods Probes (CMP or Athila) were denatured by 5 min incubation at 100ºC and kept on ice. Fifty ng of the probe were mixed with 50 µCi of α-32P using Amersham Ready-To-Go DNA Labelling Beads (-dCTP) (GE Healthcare, UK). The mix was incubated at 1 h at 37ºC. Removal of unincorporated nucleotides, prior to hybridization was done by using a ProbeQuantTM G-50 Micro Column, (GE Healthcare, UK) with a sephadex resin. The columns were prepared as recommended by the manufacturers. The sample was purified and 13.5 µL of 2M NaOH added to stop the enzymatic reaction. The labelled probe was added to Church buffer (NaH2PO4 0.25 M, pH 7.2, EDTA 1 mM, SDS 7%) previously incubated at 65ºC with the membrane, and left overnight at 65ºC. After hybridization, the membranes were washed sequentially in 2 x SSC and 2% SDS at 65°C for 3 min and in 0.1 x SSC and 0.1% SDS at 65°C for 10 min twice. Then the membrane was placed into plastic foil and exposed to a Fujifilm BAS-MS3543 Imaging Plate and BAS 4043 IP Cassette, the signal was detected after 4 hours using a FUJIFILM Fluorescent Image Analyzer FLA-3000. The cassette enclosing the membrane and exposed film were kept at -80ºC and the film later developed by placing it into a developing solution (Kodak D76 or Ilford ID11) for 10 seconds in agitation, placing into a stop bath (tap water) for 5 seconds, and finally fixed by incubation into a fixative solution (Kodak Rapid Fixor) for 10 seconds in agitation followed by a rinse in distilled water. 9. Plant genome methylation status by Chop-PCR Arabidopsis leaves were infected with Pto DC3000 as indicated above (section 5) and tissue was collected 0, 3, 9, and 24 hpi. Macerated frozen tissue was used to extract RNA and quantify the accumulation of AtSN1 transcripts (section 10 of Material and Methods) or to extract DNA and perform a chopPCR analysis. For the latter, genomic DNA was extracted using Jet Flex Extraction Kit (Genomed; Löhne, Germany) and 250 ng of genomic DNA were digested (‘chopped’) with McrBC restriction enzyme (a DNA methylationdependent enzyme) in 20 μL of final volume of the reaction mix, at 37°C for 4 hours. After the restriction reaction, the samples were diluted 1:2, and 4 µL of the digested DNA was used as template for qPCR in a 20 μL reaction mix. 32 Materials and methods Primers used for Chop-PCR (Table M3) helped us to monitor the positions 84459 to 84304 of BAC clone T15B3-Accession AL163975 (http://www.arabidopsis.org/), that correspond to AtSN1 site. Primers designed for locus At3g18780 were used as the normalizing control (loci described to be non-methylated (Widman et al., 2009). Error bars represent standard error. Statistics was applied as established by One-way ANOVA (Bonferroni's pos-hoc test). 10. RNA extraction, qRT-PCR and semi-quantitative RT-PCRs Leaves from 5-6 week old Arabidopsis plants, were infected with Pto DC3000 as indicated above (section 5). Tissue was collected, macerated in liquid nitrogen and kept at -80ºC. Three rosette leaves were used per biological replicate and a minimum of three biological replicates were performed on each experiment. Following the manufacturer’s manual for extraction of RNA with TRIzol® (Invitrogen, Carlsbad, USA), 100 mg of tissue was used and homogenized into 1 mL of TRIzol, and centrifuged at 14,000 g for 10 min at 4ºC. Supernatant was then recovered and mixed with 200 µL of chloroform by vortexing. Samples were centrifuged at 14,000 g for 15 min at 4ºC and the upper soluble fraction was recovered. An extra 300 µL of chloroform was added to the fraction and the procedure repeated (an extra step to purify the sample from TRIzol). The 500 µL fraction recovered was added to 500 µL of 2propanol and centrifuged at 14,000 g for 15 min at 4ºC. The pellet was washed with 1 mL of 75% ethanol, carefully dried and resuspended in 30 µL of RNAse-free commercial water (Qiagen, Hilden, Germany). Any DNA contaminants were eliminated after digestion with RNAse-free DNAse (Takara, Otsu, Japan). Two µg of total RNA were treated with the enzyme in a final volume of 20 µL. The reaction was incubated at 37ºC for 45 min and the enzyme inactivated by incubating at 80ºC for 15 min. A control PCR using Actin primers (Table M3) was carried out using the RNA extraction as a template to confirm the absence of DNA prior to cDNA synthesis. For the first-strand cDNA synthesis we used the instructions provided by the manufacturer for SuperScript II reverse transcriptase reagent (Invitrogen, Carlsbad, USA). The first mix contained (dNTPs, dT17:Random primers in 1:1 33 Materials and methods amount) and 1 µg of RNA with miliQ water up to 17.5 µL. The reaction was placed in the thermocycler (65ºC-3 min, 4ºC-3 min) then the second mix was added (buffers DDT, ES and enzyme SSII and RRI (Takara, Otsu, Japan) and the synthesis continued (42ºC-90 min, 70ºC-15 min, 4ºC-stop). For RT-qPCR, the reaction mixture consisted of cDNA first-strand template, primer mix, forward and reverse (10 μmol each) and SsoFast EvaGreen® Supermix, (BIO-RAD) in a total volume of 20 µL. The PCR conditions were as follows: 30 s at 95ºC, 35 cycles (for actin), 45 cycles (for AtSN1) of 10 s at 95ºC and 15 s at 60ºC. The reactions were performed using a MyiQ real time cycler (Bio-Rad, USA.). The data was analyzed using the BIO-RAD software. A relative quantification RT-qPCR method was used to compare gene expression versus control samples (using ∆∆Ct). Actin signal was used to normalize samples. Each data point is a mean value from 2-3 independent experiments (3-6 biological replicate per experiment). Error bars represent standard error. Statistics was applied as established by One-way ANOVA, (Bonferroni's pos-hoc test) and/or Student’s t-test. All semi-quantitative RT-PCRs were performed by using Taq DNA Polymerase (Thermo Scientific, USA) with the appropriate primers (Table M3), and containing 0.64 mM, dNTP mix, 1x Buffer MIX with MgCl2, 0.5 μM corresponding primers, 10 ng cDNA, and commercial water (Nalgene; Rochester, NY, USA) per reaction. The programme used was: 94ºC for 3 min, followed by 2224 cycles (Actin), 3033 cycles (AtSN1), 1920 cycles (PR1), 2528 cycles (At1g13470), 25-27 cycles (PHI-1), 33-35 cycles (Ulp-like) and 36-37 cycles (CACTA) at 94ºC for 30 s, 58ºC for 45 s, and 72ºC for 50 s, and followed by 5 min at 72ºC. PCR products were analyses by electrophoresis into a 1.5% agarose gel with EtBr. Primers for RT-qPCR were designed using Primer 3 software (http://frodo.wi.mit.edu/primer3/); and can be found in Table M3. Designed primers generate an amplicon of 100-300 bp. 11. Histochemical staining of GUS activity GUS staining was performed according to the protocol previously described by (Ranjan et al., 2012) with minor modifications. Plant tissues were 34 Materials and methods immersed in histochemical GUS staining buffer (100 mM NaPO4 pH 7, 0.5 mM K3[Fe(CN)6, 0.5 mM K4[Fe(CN)6], 20% Methanol, 0.3% Triton X-100 and 0.1% mg mL 5-bromo-4-chloro-3-indolyl-b-D-glucuronide (X-gluc) (Duchefa Biochemie, Nederlands) on plates (Corning Synthemax-R surface multiwell plates, SIGMA-ALDRICH), vacuum-infiltrated (75 cm Hg) for 10 min three times, and then wrapped in aluminium foil and incubated at 37°C for 12 h. Samples were then washed several times with 95% ethanol until complete tissue clarification. Then stored in 50% glycerol and photographed. 35 Materials and methods Table M1. Bacterial strains used in this thesisa. Strain Description Source of reference Antibiotic resistance DH5α F-endA1 hsdR17 supE44 thi-1 recA1 gyrA96 relA1 ∆lacU189 f80 ∆- lacZDM15 (Hanahan, 1983) DH5α pGEMT-Athila, AmpR This work AmpR DH5α pGEMT-CMP (180 bp repeats) This work AmpR DH5α pGEMT-KmFRT-EcoRI (pGEMT derivative containing Km resistance gene flanked by FRT and EcoRI sites Dr. Zumaquero A and Dr. Beuzón C.R. unpublished results) AmpRKmR DH5α pGEMT-KmFRT-BamHI (pGEMT derivative containing Km resistance gene flanked by FRT and BamHI sites Dr. Zumaquero A and Dr. Beuzón C.R. unpublished results) AmpRKmR DH5α pGEMT derivative containing the ∆hopO1-2::KmFRT knockout allele This work AmpRKmR DH5α pGEMT derivative containing the ∆hopX1::KmFRT knockout allele This work AmpRKmR DH5α pGEMT derivative containing the ∆hopA1::KmFRT knockout allele This work AmpRKmR DH5α pGEMT derivative containing the ∆hopAA1-2::KmFRT knockout allele This work AmpRKmR DH5α pGEMT derivative containing the ∆hopD1::KmFRT knockout allele This work AmpRKmR DH5α pGEMT derivative containing the ∆hopV1::KmFRT knockout allele This work AmpRKmR DH5α pGEMT derivative containing the ∆hopR1::KmFRT knockout allele This work AmpRKmR DH5α pGEMT derivative containing the ∆avrPto1::KmFRT knockout allele This work AmpRKmR DH5α pGEMT derivative containing the ∆hopB1::KmFRT knockout allele This work AmpRKmR DH5α pGEMT derivative containing the ∆hopAM1-2::KmFRT knockout allele This work AmpRKmR DH5α pGEMT derivative containing the ∆hopT1-2::KmFRT knockout allele This work AmpRKmR DH5α pGEMT derivative containing the ∆hrpL::KmFRT knockout allele This work AmpRKmR 1448a Pseudomonas syringae pv. phaseolicola (Pph), wild type strain, Race6 (Taylor et al., 1996) DC3000 P. syringae pv. Tomato (Pto), wild type strain (Cuppels, 1986) RifR DC3000 ∆hrcV DC3000 derivative, ∆hrcV ::Tn3Gus7 (Ronald et al., 1992), (Mudgett and Staskawicz, KmR 36 Materials and methods Strain Description Source of reference Antibiotic resistance 1999) DC3000 ∆hop01-2 DC3000 derivative, ∆hop01-2 (knockout mutant) This work KmR DC3000 ∆hopX1 DC3000 derivative, ∆hopX1 (knockout mutant) This work KmR DC3000 ∆hopA1 DC3000 derivative, ∆hopA1 (knockout mutant) This work KmR DC3000 ∆hopAA1-2 DC3000 derivative, ∆hopAA1-2 (knockout mutant) This work KmR DC3000 ∆hopD1 DC3000 derivative, ∆hopD1 (knockout mutant) This work KmR DC3000 ∆hopV1 DC3000 derivative, ∆hopV1 (knockout mutant) This work KmR DC3000 ∆hopR1 DC3000 derivative, ∆hopR1 (knockout mutant) This work KmR DC3000 ∆avrPto1 DC3000 derivative, ∆ avrPto1 (knockout mutant) This work KmR DC3000 ∆hopB1 DC3000 derivative, ∆hopB1 (knockout mutant) This work KmR DC3000 ∆hopAM1-2 DC3000 derivative, ∆hopAM1-2 (knockout mutant) This work KmR DC3000 ∆hopT1-2 DC3000 derivative, ∆hopT1-2 (knockout mutant) This work KmR DC3000 ∆hrpL DC3000 derivative, ∆hrpL (knockout mutant) This work KmR DC3000 COR - DC3000-DB29 cmaA::Tn5 uidA Sm/Spr; cfa6::Tn5 uidA Km r (CFA – CMA – COR – ) (Brooks et al., 2004) KmR DC3000 ∆ fliC DC3000 derivative, ∆fliC (Kvitko et al., 2009) DC3000 ∆28E CUCPB5500 DC3000 derivative, ∆28E ( ∆cluster I,II,III,IV,V,VI,VII,VIII, IX,pDC3000A, pDC3000B)b ΔhopU1-hopF2 ΔhopC1-hopH1::FRT ΔhopD1hopR1::FRT ΔavrE-shcN ΔhopAA1-2-hopG1::FRT pDC3000A− pDC3000B− (Kvitko et al., 2009) 37 Materials and methods Strain Description Source of reference Antibiotic resistance DC3000 CUCPB5459 (∆cluster I,II,IV, IX,pDC3000A, pDC3000B) b ∆hopU1-hopF2 ∆hopC1-hopH1::FRT ∆hopD1-hopR1::FRT ∆hopAA1-2-hopG1::FRT pDC3000A2B2 (Kvitko et al., 2009) DC3000 CUCPB5451 (∆cluster II,IV, IX)b ∆hopC1-hopH1::FRT ∆hopD1-hopR1::FRT ∆hopAA1-2-hopG1::FRT (Wei et al., 2007) DC3000 hopZ1a pAME30 pAMEx nptII::hopZ1a (Macho et al., 2010) AmpR, KmR DC3000 avrRpm1 pAME31 pAMEX-nptII::avrRpm1 (Macho et al., 2010) AmpR, KmR DC3000 avrRps4 pAME32 pAMEX-nptII::avrRps4 (Macho et al., 2010) AmpR, KmR DC3000 avrRpt2 pAME8 pAME4-nptII:: avrRpt2 (Macho et al., 2010) AmpR, KmR a RifR, SpcR, and KmR indicate resistance to rifampicin, spectinomycin and kanamycin. 38 Materials and methods Table M2. Antibiotics used in this study. Antibiotic E. coli P. syringae Ampicillin 100 µg/ml 300 µg/ml Kanamycin 50 µg/ml 15 µg/ml (liquid medium), 25 µg/ml (solid medium) Rifampicin n.a. 15 µg/ml Nitrofurantoin n.a. 30 µg/ml Cycloheximide* n.a. 2 µg/ml *Cycloheximide was used as fungicide when growing P. syringae isolated from plant tissues. n. a. (not applicable). Table M3. Oligonucleotides used in this thesis. Name Sequence 5' - 3' Observation Restriction site PCR amplification, Southern blot probe Reference 180bp 1 a gatcmagtcatattcgactcc This work 180bp 2 b gatctcatgtgtatgattgag This work 180bp 3a gattgatcaagtcatattcgactcc This work, nested PCR 180bp 4b gacttgatctcatgtgtatgattgag This work, nested PCR Athila a ttcttctccaactccagg (Pavet et al., 2006) Athilab taccctttgttggagccg (Pavet et al., 2006) Allelic exchange Localization hopO1-2-A ccctatagtgagtcgaattcatgatcaaaacagtcagcg chromosome EcoRI hopO1-2-B gaattcgactcactatagggcagcgtctcttatagtcc chromosome EcoRI hopO1-2-2 cttgccaatctgttcacg chromosome EcoRI hopO1-2-3 gagtttcccttggtcacc chromosome EcoRI hopX1-A ccctatagtgagtcgaattccgttaagaataagcgccc plasmid EcoRI hopX1-B gaattcgactcactatagggcatgctagctatgtcgtc plasmid EcoRI hopX1-2 tgatcctccacacacgtc plasmid EcoRI hopX1-3 tattcccaaggtctgccg plasmid EcoRI hopA1-A ccctatagtgagtcgaattcatcgagagtcttaaggcg chromosome EcoRI hopA1-B gaattcgactcactatagggaagtgcagcgattctgag chromosome EcoRI hopA1-2 acccgcaaatcaaaaccc chromosome EcoRI hopA1-3 ctgtctcttctggtcagc chromosome EcoRI hopAA1-2-A ccctatagtgagtcgaattcattccctctcgttctacg chromosome BamHI hopAA1-2-B gaattcgactcactatagggaagtgcagcgattctgag chromosome BamHI hopAA1-2-2 acccgcaaatcaaaaccc chromosome BamHI hopAA1-2-3 ctgtctcttctggtcagc chromosome BamHI hopD1-A ccctatagtgagtcgaattctcccggatgaagtaatcg chromosome EcoRI hopD1-B gaattcgactcactataggggatctactggacttcacg chromosome EcoRI hopD1-2 gcctttgtattctgtggc chromosome EcoRI hopD1-3 atagtgacaaaggaggcg chromosome EcoRI hopV1-A ccctatagtgagtcggatccggtctgaagtaggcatcg chromosome BamHI 39 Chapter 1 Figure 1.1. Bacterial (Pto DC3000) proliferation is not altered if the inoculum is harvested directly from the plate or liquid culture. Arabidopsis plants (Col-0) were grown in a short day conditions and infiltrated with an inoculation dose of 5x104 cfu/ml. Three disc leaves per plant were collected and processed just after the inoculation (0 dpi), and 4 days after (4 dpi). Bacterial colonies were counted and represented in logarithmical scale. Each colour bar represents an independent experiment and for each experiment 4 plants were used. Error bars represent the standard error. 1.2. DNA hypomethylation upon Pto DC3000 infection In order to corroborate if plant genome methylation levels are reduced during Pto DC3000 infection, we obtained Southern blot probes similar to the ones used by Pavet et al. (2006). First, we amplified by Nested-PCR and the appropriate primers (Table M3), AL1a (GenBank X04322), a homologue to the centromeric 180-bp repeat (Figure 1.2A). The final PCR product was cloned into pGEM-T Vector. Transformants were analyzed by restriction (SacI + ApaI) to confirm the fragment size (289 pb) (Figure 1.2B) and two of the recombinant clones were sequenced. Both clones showed homology to the centromeric 180-bp repeat but only one (clone 180.2) contained the complete sequence (Figure 1.2C). We used clone 180.2 (from now on would be referred to as CMP, centromeric probe) as a probe for Southern blot hybridization. Second, Athila probe was generated using the primers described in Pavet et al. (2006) (Table M3). 46 Chapter 1 Figure 1.2. Generation of the centromeric repeat probe (CMP) for Southern blot analysis. (A) To generate the CMP probe a first PCR was carried out using primers 180bp1+180bp2 and Arabidopsis genomic DNA as template. The following Nested PCR was performed using primers 180bp3+180bp4 and the band obtained in the previous PCR as a template. The band of approximately 200 bp obtained in the first PCR was purified prior to its use as template. The fragment of 200 bp obtained from the second PCR was cloned into pGemT-Vector. (B) Restriction analysis (SacI + ApaI) of transformants of the pGEM-T ligation to the 200 bp fragment. A fragment of 289 bp was generated in the correct recombinant clones. The clones marked with asterisks were confirmed by DNA sequencing. (C) Clone 180.2 contains identical nucleotide sequences (indicated with asterisk) of centromeric satellite repeat homologues up to 180bp repeats, called AL1 AL1a (X04322), and was therefore used as probe for Southern blot analysis. 47 Chapter 1 The 509 bp PCR fragment obtained (Figure 1.3A) was also cloned into pGEM-T Vector, and the transformants analyzed as described for CMP (Figure 1.3B). The two clones contained a 509 pb Athila fragment (Figure 1.3C) and clone A1, was used as a probe for Southern blot hybridization. In order to corroborate that Arabidopsis centromeric DNA is hypomethylated during infection with Pto DC3000 (Pavet et al., 2006), we performed a Southern blot using the CMP probe. Arabidopsis plants were infiltrated with Pto DC3000 grown in rich media, either liquid (King´s B) or solid (LB). Although we had previously described that the source of inoculum had no impact on the bacterial replication efficiency (Figure 1.1), we wanted to rule out any possible impact of the source of inoculum on Pto DC3000 effect on plant DNA methylation. We inoculated two sets of plants with different bacterial dilutions from the same inoculum: a first set inoculated with 5x104 cfu/ml used to check bacterial replication, and a second inoculated with 5x106 cfu/ml used for the Southern blot analysis. Growth 4 dpi confirmed bacteria were growing as expected displaying a 104-fold increaseregardless of the source of the inoculum (Figure 1.4A), a requirement for analysing the second set of plants and test their DNA methylation levels at 24 hpi. Genomic DNA was isolated from naïve, mock (infiltrated with MgCl2) and infected leaves, digested with Sau3AI, a methylation-sensitive restriction enzyme which does not cut if DNA is methylated in GAT5mC, and separated on an agarose gel. Genomic DNA from ddm1 plants was used as a positive control as this mutant shows genome-wide hypomethylation (Vongs et al., 1993). DDM1 (DECREASED IN DNA METHYLATION 1) is a chromatin remodeler required for maintenance of DNA methylation as it facilitates access of DNA methyltransferases to heterochromatin (Law and Jacobsen, 2010). The blot was hybridized with the CMP probe and as shown on Figure 1.4B, we did not observed an increase on small size bands on Pto-infected plants (with either type of inoculum), and no differences were detected either between Ptoinfected plants and mock or naïve plants, while a clear increase on the intensity of smaller bands, in keeping with reduce levels of DNA methylation, was clearly observed in the ddm1 mutant. 48 Chapter 1 Figure 1.3. Generation of the Athila probe for Southern blot analysis. (A) The Athila probe was generated using primers designed from the accession X81801.1, (Trompa et al., 2002). The 509 bp amplified PCR fragment was cloned into pGEM-T Vector. (B) Two clones were analyzed by restriction analysis (SacI + ApaI), and the fragment of 589 bp was generated. The clones were confirmed by DNA sequencing. (C) Sequence of clone A1 shows homology to Athila sequence (identical nucleotides are marked with asterisk) and thus used as a probe for Southern blot analysis. 49 Chapter 1 Figure 1.4. Southern blot analysis of plants infected with inocula from different sources. (A) In planta bacterial replication was analysed in Arabidopsis (Col-0) plants infiltrated with a lower concentration (5x104 cfu/ml ) of the same bacterial solution used for Southern blot experiment (Fig. 1.4B). Plant tissue was processed at day 0 and day 4 post inoculation (0 dpi and 4 dpi). Three disc leaves per plant were collected and processed just after the inoculation (0 dpi), and at 4 dpi. Bacterial colonies were counted and represented in logarithmical scale. Bars represent the mean values from 3 plants per time point. Error bars represent the standard error. (B) Southern blot of genomic DNA obtained from Arabidopsis (Col-0) plants infected with 5x106 cfu/ml of Pto DC3000 previously grown in either liquid or solid LB medium. Samples were collected at 24 hours post infection (24 hpi). Three leaves per plant were harvested and processed for each sample. Genomic DNA was digested with the methylation-sensitive endonuclease Sau3AI and hybridized with the CMP probe. Genomic DNA from naïve and mock-inoculated plants (plants infiltrated with 10mM MgCl2 and harvested 24hpi), as well as undigested genomic DNA from naive plants (ND) were used as a reference. Arabidopsis ddm1 mutant was used as a positive control, as it displays genome-wide hypomethylation. 50 Chapter 1 Pavet et al. (2006) reported that hypomethylation of plant centromeric DNA took place regardless of the inoculation dose (from 105 cfu/ml to 5x107 cfu/ml) and time (24 and 48 hpi). To test whether these differences could have an impact on our experiments explaining the results obtained in Figure 1.4B, we repeated the infection of Arabidopsis plants inoculating Pto DC3000 at either 5x106 cfu/ml or 5x107 cfu/ml, and collected samples both at 24 and 48 hpi (Figure 1.5). Bacterial replication assays were carried out in parallel as before and confirmed bacterial growth as expected (Figure 1.5A). Southern blot analysis of these samples was carried out as before. The hybridization with the CMP probe did not show any increase on small size bands on Pto-infected plants at either 24 or 48 hpi, with either dose of inoculation, and no differences could be detected either between Pto-infected and mock or naïve plants, while it was clearly displayed in the ddm1 mutant plants (Figure 1.5B). A similar result was obtained when the same genomic samples were digested with Sau3AI and the Southern blot hybridization performed using another centromeric probe, the Athila retrotransposon (Pavet et al., 2006), Figure 1.5C). At the highest inoculation dose, the plant tissue was severely damaged by 48 hpi (Figure 1.5D) but no symptoms could be observed at 24 hpi. As high molecular bands displayed a slight reduction in leaves inoculated with Pto DC3000 at 5x107 cfu/ml at 24 hpi, we selected these conditions for the following assays. We also tested whether the effect on centromeric DNA hypomethylation reported by Pavet et al. (2006) could be occurring at earlier times in our laboratory conditions, infecting Arabidopsis leaves with 5x107 cfu/ml Pto DC3000 and collecting samples at 0, 12 and 24 hpi (Figure 1.6). A Southern blot carrying Sau3AI-digested genomic DNA from these samples was hybridized with Athila probe. No significant changes on band intensity, consistent with DNA hypomethilation, could be detected in infected leaves at 12 hpi compared with 0 hpi, but a slight reduction of the signal from the higher molecular bands, accompanied by an increase of the signal from the 500 pb-lower band could be observed again in the 24 hpi samples (Figure 1.6A). As in prior experiments, bacterial replication was also tested (Figure 1.6B). 51 Chapter 1 Figure 1.5. Southern blot analysis of Pto-infected plants with different inoculation dose. (A) In planta bacterial replication was analysed in Arabidopsis (Col-0) plants infiltrated with 5x104 cfu/ml of the same bacterial solution used for the Southern blot experiment (Fig. 1.5B and 1.5C). Plant tissue was processed at day 0 and day 4 post inoculation (0 dpi and 4 dpi). Three disc leaves per plant were collected and processed just after the inoculation (0 dpi), and at 4 dpi. Bacterial colonies were counted and represented in logarithmical scale. Bars represent the mean values from 3 plants per time point. Error bars represent the standard error. (B) Southern blot of genomic DNA obtained from Arabidopsis (Col-0) plants infected with 5x106 cfu/ml and 5x107 cfu/ml of Pto DC3000 previously grown in solid LB medium. Samples were collected at 24 and 48 hours post infection (24 hpi and 48 hpi). Three leaves per plant were harvested and processed for each sample. Genomic DNA was digested with the methylation-sensitive endonuclease Sau3AI and hybridized with the CMP probe. Genomic DNA from naïve and mock-inoculated plants (plants infiltrated with 10 mM MgCl2), as well as undigested genomic DNA from naive plants (ND) were used as a reference. Arabidopsis ddm1 mutant was used as a positive control, as it displays genome-wide hypomethylation. (C) Southern blot of samples 1, 3, 4, 6, 7, 9, 10 and 11, mock and ddm1 used on Figure 1.5B. Genomic DNA was digested with the methylationsensitive endonuclease Sau3AI and hybridized with Athila probe. (D) Symptoms of Arabidopsis Col-0 plants inoculated with 5 x 107 cfu/ml of Pto DC3000. Image shown was taken 48 hpi. Arrows indicate disease symptoms. 52 Chapter 1 Figure 1.6. Southern blot analysis of plants infected during different time frames. (A) Southern blot of genomic DNA obtained from Arabidopsis (Col-0) plants infected with 5x107 cfu/ml of Pto DC3000 previously grown in solid LB medium. Samples were collected at 0, 12 or 24 hours post infection (0, 12 and 24 hpi). Three leaves per plant were harvested and processed for each sample. Genomic DNA was digested with the methylation-sensitive endonuclease Sau3AI and hybridized with Athila probe. Genomic DNA from Arabidopsis ddm1 mutant was used as a positive control, as it displays genome-wide hypomethylation. (B) In planta bacterial replication was analysed in Arabidopsis (Col-0) plants infiltrated with 5x104 cfu/ml of the same bacterial solution used for Southern blot experiment (Fig. 1.6A). Plant tissue was processed at day 0 and day 4 post inoculation (0 dpi and 4 dpi). Three disc leaves per plant were collected and processed just after the inoculation (0 dpi), and at 4 dpi. Bacterial colonies were counted and represented in logarithmical scale. Bars represent the mean values from 3 plants per time point. Error bars represent the standard error. 53 Chapter 1 Bhardwaj and collaborators showed that Arabidopsis has a circadian clockmediated variation in resistance to Pto DC3000 (Bhardwaj et al., 2011). Plants were less susceptible to infection in the subjective morning than in the subjective night as a result of a clock-mediated modulation of pathogen associated molecular pattern (PAMP)-triggered immunity. Due to this temporal variation in susceptibility to Pto infection, we decided to infect Arabidopsis at different circadian stages: just before the evening, what we called “night infection”, as after the inoculation the plants were immediately placed for 16 hours in the dark followed by 8 hours of light, or just before the morning, what we called “day infection” as after the inoculation the plants were immediately placed for 8 hours with light followed by 16 hours of darkness. For each condition samples were taken at 0 and 24 hpi from three leaves from two to five Arabidopsis plants infiltrated with 5x107 cfu/ml Pto DC3000 or a MgCl2 solution (mock). Two independent set of plants for “day infection” and “night infection” were infiltrated with the same inoculum whose replication rate in the plant was also measured (Figure 1.7A). Genomic DNA was digested with Sau3AI, separated on an agarose gel and the blot was hybridized with Athila probe. In “day infection” samples (Figure 1.7B), we could detect a clear increase on the intensity of the 500 bp-lower band, accompanied by a decrease on the signal of higher molecular bands on Pto-infected samples at 24 hpi, compared to the 0 hpi and mock samples. These differences were even clearer on “night infection” conditions (Figure 1.7C) indicating that hypomethylation of centromeric DNA was easier to detect when the plant is more susceptible to the bacteria and thus confirming the data presented by Pavet and collaborators (2006). 54 Chapter 1 Figure 1.7. Southern blot analysis of Pto-infected plants in the subjective morning or in the subjective night. (A) In planta bacterial replication was analysed in Arabidopsis (Col-0) plants infiltrated with 5x104 cfu/ml of the same bacterial solution used for the Southern blot experiments (Fig. 1.7B and 1.7C). Plant tissue was processed at day 0 and day 4 post inoculation (0 dpi and 4 dpi). Three disc leaves per plant were collected and processed just after the inoculation (0 dpi), and at 4 dpi. Bacterial colonies were counted and represented in logarithmical scale. Bars represent the mean values from 3 plants per time point. Error bars represent the standard error. (B) Southern blot of genomic DNA obtained from Arabidopsis (Col-0) plants infected in the subjective morning (day infection) with 5x107 cfu/ml of Pto DC3000 previously grown in solid LB medium. Samples were collected at 0 and 24 hours post infection (0 hpi and 24 hpi). Two independent infections were performed with the same inoculum (Set 1 and Set 2). Three leaves per plant were harvested and processed for each sample. Genomic DNA was digested with the methylation-sensitive endonuclease Sau3AI and hybridized with Athila probe. Genomic DNA from mock-inoculated plants (plants infiltrated with 10mM MgCl2 and harvested 24 hpi) was used as a reference. Arabidopsis ddm1 mutant was used as a positive control, as it displays genome-wide hypomethylation. (C) The same as (B) but Arabidopsis (Col-0) plants were infected in the subjective night (night infection) with 5x107 cfu/ml of Pto DC3000 previously grown in solid LB medium. 55 Chapter 1 Transcriptional regulation of Athila depends on DDM1, whereas the involvement of AGO4 (ARGONAUTE 4, silencing effector involved in RNAdependent DNA methylation, RdDM) in its regulation has not been determined (Keith Slotkin, 2010). On the other hand, AtSN1 activation has been shown to de dependent on AGO4 (Agorio and Vera, 2007), and our results demonstrate that it also depends on DDM1 (Figure 1.10). Thus, we analysed the transcriptional activation of these two loci in Arabidopsis Col-0, ddm1, ago4-2 and met1-3 mutants using RT-qPCR (Figure 1.11B), and found that whereas the transcriptional regulation of Athila does not depend on AGO4 or MET1, that of AtSN1 depends on AGO4, DDM1, and perhaps to a lesser extent on MET1. 1.4. Changes on AtSN1 methylation levels by Chop-PCR Our results and others (Dowen et al., 2012; Yu et al., 2013) showed that several TGS-loci are transcriptionally activated during Pto-infection. Transcriptional activation of many of these loci is due to reduce DNA methylation levels, including that of Athila or AtSN1, the two loci displaying the strongest activation. To confirm that transcriptional activation of TGS loci was also due to DNA hypomethylation in our system, we used chop-PCR to analyse any changes on the DNA methylation status of AtSN1 on Pto-infected plants. Chop-PCR is an assay in which genomic DNA is subjected to digestion with a methylation-sensitive or methylation-dependent restriction endonuclease and then tested as a template for PCR amplification using primers flanking the restriction sites (Earley et al., 2010; Oakes et al., 2009). McrBC is a restriction enzyme widely used for this type of analysis. It recognizes the two half-sites of the form 5′-G/AmC-3′ that can be separated up to 2kb (5´…PumC (N40-2000) PumC…3´), with an optimal separation of 55103 bp. McrBC is methylation-dependent and thus cuts methylated but not unmethylated DNA. The McrBC enzyme only requires two methylated halfsites within the PCR-amplified region to cleave DNA, despite the methylation status of other sites. If a genomic region becomes hypomethylated, the enzyme will cut to a lesser extend and this will increase the amount of DNA that can be amplified by PCR. Ten Arabidopsis plants were infiltrated with 62 Chapter 1 Pto DC3000 (5x107 cfu/ml, night infection) and samples were taken at 0 and 24hpi. Mock samples were included to determine wild-type levels of DNA methylation of AtSN1 and samples from ago4-2 plants were analysed as a positive control as this transposon becomes hypomethylated in this mutant (Agorio and Vera, 2007). Three leaves from each plant were independently macerated and frozen tissue was split in two to extract RNA and DNA. RNA was used to confirm transcriptional activation of AtSN1 by RT-qPCR, and genomic DNA used to perform the chop-PCR assay. Genomic DNA was digested with McrBC and a qPCR performed using primers flanking the region of AtSN1 that has been previously described to be most intensely methylated (Agorio and Vera, 2007; Xie et al., 2004; Yu et al., 2013). Although we could detect the transcriptional activation of AtSN1 on Pto-infected plants by 24 hpi (Figure 1.12A), we found no evidence of hypomethylation for the transposon on the same infected plants (Figure 1.12B). To rule out the possibility that DNA hypomethylation was taking place at an earlier time on the infection process, we repeated these assays analysing samples at 3 and 9 hpi. No evidence for hypomethylation of AtSN1 during Pto infection could be detected at these time points either (Figure 1.12C). This failure to detect DNA hypomethylation of AtSN1 during Pto infection could be due to technical reasons, i.e. a low sensitivity of the chop-PCR assay, which could perhaps be solved by using other methylation-sensitive enzymes and other primers for AtSN1 flanking their corresponding restriction sites, or due to the nature of the assay. This later possibility is supported by the small differences in methylation levels found for AtSN1 by Yu and collaborators (Yu et al., 2013) following flg22 treatment. Flg22 treatment is expected to induce stronger changes than those taking place during infection since higher amounts of flagellin are thus presented to the plant. Furthermore, Yu and collaborators proposed that changes due to interaction with Pto occurs only in cells adjacent to bacteria, leading to leaf samples including cells with altered, as well as cells with normal DNA methylation levels, thus potentially diluting the changes and reducing the sensitivity of the assay. Any of these reasons could explain our negative results. 63 Chapter 1 Figure 1.12. DNA methylation status of AtSN1 in Pto DC3000-infected Arabidopsis plants by Chop-PCR. (A and B) Arabidopsis plants were infected with Pto DC3000 and samples were harvested at 0 and 24 hours post-inoculation (0 hpi and 24 hpi). Mock-inoculated plants (10 mM MgCl2) and ago4-2 were included as negative and positive controls, respectively. Macerated tissue was split in two and samples were processed for RT-qPCR on (A) and for chop-PCR on (B). (A) Accumulation of AtSN1 transcripts was analysed using RT-qPCR. Transcript levels were normalised to actin and the results presented as relative transcript accumulation compared to levels detected in plants inoculated with Pto DC3000 at 0 hpi. (B) Genomic DNA was digested with the methylation-dependent enzyme McrBC and an AtSN1 fragment was amplified by PCR. A fragment from locus At3g18780 known to be nonmethylated (Widman et al., 2009), was used to normalize the PCR amplified levels. The experiment was performed two times and one representative biological replicate is shown. Bars represent the mean values from 1 experiment with 3 (mock), 4 (0 hpi) and 10 (24 hpi) plants. Error bars represent the standard error. Mean values marked with the same letter were not significantly different from each other as established by One-way ANOVA, Benferroni PosHoc test (99% confidence intervals). (C) Arabidopsis plants were infected with Pto DC3000 and samples were harvested at 3 and 9 hours postinoculation (3 hpi and 9 hpi). Mock-inoculated plants (10 mM MgCl2) and ago4-2 were included as negative and positive controls, respectively. Genomic DNA was digested with the methylationdependent enzyme McrBC and an AtSN1 fragment was amplified by PCR. A fragment from locus At3g18780 known to be non-methylated, was used to normalize the PCR amplified levels. Bars represent the mean values from 1 experiment with 3-4 plants. Error bars represent the standard error. Mean values marked with the same letter were not significantly different from each other as established by One-way ANOVA, Benferroni PosHoc test (99% confidence intervals). 64 Chapter 1 1.5. Activation of a transcriptionally silent GUS transgene upon Pto DC3000 infection Yu et al. (2013) generated an Arabidopsis transgenic line named AtGP1 LTR:GUS, which contains the β-glucuronidase GUS reporter gene fused to the LTR (long-terminal repeat) of AtGP1, a gypsy retrotransposon strongly targeted by siRNA-directed DNA methylation. The expression of GUS in this line is restored upon application of a DNA methyltransferase inhibitor, supporting transcriptionally silencing for this reporter transgene (Yu et al., 2013). Expression of AtGP1 LTR:GUS is activated after treating Arabidopsis leaves with flg22. In order to determine if during infection with Pto DC3000 this transcriptionally silent GUS transgene was also activated, we infected leaves of AtGP1 LTR:GUS plants (5x107 cfu/ml) and stained them to detect GUS signal at 0, 3 and 9 hpi. The presence of Pto DC3000 in the apoplast rapidly activates GUS expression as Pto-infected but not mock-infected leaves at 0 hpi displayed intense GUS staining, suggesting that activation of the transgene occurs immediately upon bacteria recognition by the plant. Ptoinfected leaves displayed an even stronger GUS staining at 3 hpi with a small decrease at 9 hpi, indicating that the transgene becomes additionally activated during the initial hours of the interaction with Pto DC3000 (Figure 1.13). The changes occurring at the chromatin level in this transgenic line should be addressed in a future. 65 Chapter 1 Figure 1.13. GUS staining of Pto DC3000-infected Arabidopsis transgenic line AtGP1 LTR:GUS. Six week-old Arabidopsis transgenic line AtGP1 LTR:GUS, which contains the β-glucuronidase GUS reporter gene fused to the LTR (long-terminal repeat) of AtGP1, was infiltrated with 5x107 cfu/ml of Pto DC3000. In each experiment three leaves per 3 plants were infiltrated and leaves were GUS histologically stained at 0, 3 and 9 hours post-infiltration (0, 3, 9 hpi). Mock-inoculated plants (10 mM MgCl2) were included as controls for the basal GUS expression level. The experiment was performed 3 times and the images correspond to a representative GUS histologically stained infiltration experiment. The graph summarizes the GUS staining intensity for that representative experiment. 66 Chapter 2 Role of bacterial virulence determinants in the transcriptional activation of the retrotransposon AtSN1 Chapter 2 2.1. Role of the T3SS in determining AtSN1 transcript levels Pavet and collaborators (2006) showed that hypomethylation of Arabidopsis DNA during Pto DC3000 infection requires a functional hrpL gene. HrpL activates the transcription of the genes necessary for coronatine production as well as the genes encoding the type III secretion system (T3SS). We chose to use the retrotransposon AtSN1, the TGS-locus displaying the strongest activation during infection with Pto DC3000 (Figures 1.10 and 1.11), as a reporter to analyse the role of different bacterial virulence determinants, including HrpL and the T3SS, in the modification of the plant epigenome. We analysed AtSN1 transcript levels in plants infected with either Pto DC3000 or its mutant derivatives. The mutants analysed included: a Pto DC3000 carrying a knockout mutation in hrcV, encoding an inner membrane component of the T3SS (Figure 2.1A), a double mutant (cfa6::Tn5 cma::Tn5) COR-, which fails to synthesize the toxin coronatine (Figure 2.1B), and a ∆hrpL mutant. Mutants in hrcV lack a functional T3SS and are thus not capable of delivering effector proteins inside of the host cell, do not cause infection in susceptible hosts, nor do they induce the HR in resistant hosts (Alfano and Collmer, 1997). No significant accumulation of AtSN1 transcript was detected in Arabidopsis plants inoculated with either the ∆hrpL or the ∆hrcV mutants at 24 hpi. Plants inoculated with a CORmutant accumulated significantly higher levels of AtSN1 transcript than those inoculated with either ∆hrpL or ∆hrc mutants (Figure 2.1B), although this level was significantly lower than that accumulated in plants inoculated with the wild type strain. To further confirm the differences found between the levels of AtSN1 transcript accumulated following the inoculation with these strains, we analyzed the three mutant strains (∆hrpL, ∆hrcV and COR-) side by side (Figure 2.1C). Thus, our results indicate that the lack of transcriptional activation of AtSN1 observed in plants inoculated with the hrpL mutant can be fully explained by its failure to secrete effectors. However, they also indicate that in the context of a fully functional T3SS, the synthesis of coronatine is necessary for full activation of AtSN1. 69 Chapter 2 Figure 2.1. Accumulation of AtSN1 transcript 24 hours post-inoculation with Pto DC3000 requires HrpL and a functional T3SS, and is partially dependent on coronatine synthesis. (A-C) Accumulation of AtSN1 transcript was analysed using RT-qPCR in Col-0 plants 24 hours postinoculation with Pto DC3000, Pto T3SS mutants (∆hrpL and ∆hrcV) or CORmutant. Naïve plants as well as plants mock-inoculated, were collected at 24 hpi and included as controls. Bars represent the mean values from 3 independent experiments with 3-6 plants per sample and experiment. Error bars represent the standard error. Samples represented in (C) were analyzed side by side within the same experiment. AtSN1 transcript levels were normalised to actine and the results presented as relative transcript accumulation compared to the levels detected in Pto DC3000-infected plants 0 hpi. Mean values marked with the same letter were not significantly different from each other as established by One-way ANOVA, Benferroni PosHoc test (99% confidence intervals). 70 Chapter 2 2.2. Identification of type III effector proteins potentially involved in the transcriptional activation of the retrotransposon AtSN1 Pto DC3000 actively deploys at least 28 bona fide effectors and several other proteins associated with extracellular functions of the T3SS (Schechter et al., 2006). The majority of these well-expressed DC3000 type III effectors are encoded within six clusters in the DC3000 genome (Wei et al., 2007) (Table 2.1). The genome also harbours 12 putative effector pseudogenes and 7 effector genes that appear only weakly expressed (Chang et al., 2005). To determine the role of the T3SS translocated effectors (T3Es) in the activation of AtSN1 transcription during Pto DC3000 infection, we analysed AtSN1 transcript accumulation in plants inoculated with a series of mutants in multiple effector genes, carrying deletions of different groups of Pto DC3000 effector genes. Growth within the plant of Pto ∆28E, a Pto DC3000 mutant derivative which lacks all 28 well expressed effector genes, is severely reduced in Arabidopsis and is not accompanied by lesion formation in the plant (Wei et al., 2007). We found that AtSN1 transcript levels did not increase in plants inoculated with the Pto ∆28E mutant strain, being those observed at 24 hpi not significantly different from the levels displayed by plants inoculated with the ∆hrcV T3SS defective mutant (Figure 2.2A). This indicates that the transcriptional activation of AtSN1 requires one or several of the 28 effectors translocated by the Pto DC3000 T3SS and supports the result obtained for ∆hrcV and ∆hrcL mutants which lack a functional T3SS (Figure 2.1). We also analysed mutant strains lacking different clusters of effector genes in order to determine which effectors are involved in AtSN1 transcriptional activation. As a first step, we analysed plants inoculated with two mutant strains: strain CUCPB5459, missing clusters I, II, IV, IX and X and therefore lacking 9 well expressed effectors and 3 putative pseudogenes, and strain CUCPB5451, missing clusters II, IV and IX, and lacking 15 well expressed effectors and 3 putative pseudogenes (Figure 2.2B). The level of AtSN1 transcripts accumulated in plants inoculated with the CUCPB5459 strain was not significantly different from that accumulated in plants inoculated 71 Chapter 2 Figure 2.4. Accumulation of AtSN1 transcript 24 hours post-inoculation with Pto DC3000 is significantly reduced in plants inoculated with ∆hopC1. Accumulation of AtSN1 transcript was analysed using RT-qPCR in Col-0 plants 24 hours post-inoculation with Pto DC3000, or its ∆hopC1 and ∆hopAO1 mutant derivatives. Mock-inoculated plants were collected at 24 hpi and included as controls. Bars represent the mean values from 2 independent experiments with 3-6 plants per sample and experiment. Error bars represent the standard error. AtSN1 expression levels were normalised to actin and the results presented as relative transcript accumulation compared to levels detected in Pto DC3000-infected plants 0 hpi. Mean values marked with the same letter were not significantly different from each other as established by One-way ANOVA, Benferroni PosHoc test (95% confidence intervals). Both, hopAO1 and hopC1 are missing in Pto ∆28E, CUCPB5459 and CUCPB5451. Thus, to directly compare AtSN1 transcript accumulation after infection with all these strains, we analyzed all of them side by side (Figure 2.5). ANOVA did not show statistically significant differences between the intermediate accumulation of AtSN1 transcript in plants 24 hpi with ∆hopC1 in this experiment, and those inoculated with either Pto DC3000, or its CUCPB5459 or ∆28E mutant derivatives. However, Student’s t-test indicate that the levels of AtSN1 transcript in plants 24 hpi with ∆hopC1 is significantly lower than those displayed by plants inoculated with either Pto DC3000 (99% confidence interval), CUCPB5451 (99% confidence interval), CUCPB5459 (95% confidence interval), or ∆hopAO1 (99% confidence interval), and significantly higher than the levels displayed by plants inoculated with ∆28E (99% confidence interval). Since all CUCPB5451, CUCPB5459 and Pto ∆28E mutants lack both hopAO1 and hopC1, these results imply that there 78 Chapter 2 must be other effector(s) directly or indirectly involved in determining the accumulation of AtSN1 transcript, both increasing it and suppressing it. Effector(s) candidate(s) that increase AtSN1 transcripts accumulation could be encoded by cluster I (which includes effector genes hopU1 and hopF2) or cluster X (which includes effector genes hopAM1-2, hopX1, hopO1-1, and hopT1-1). All these effectors genes (cluster I and X) are present in CUCPB5451 and are deleted in strains CUCPB5459 and ∆28E. Preliminary testing of mutants in either hopU1 or hopF2 show higher transcript levels by 24 hpi than those displayed by Pto DC3000, but these differences right in the limit of being statistically significant, perhaps due to functional redundancy (Fig. 2.6). Experiments analysing the accumulation of AtSN1 transcript in plants inoculated with double (hopU1 hopF2) or triple mutants (hopU1 hopF2 hopC1) in these genes could shed light on their role in this process. Nevertheless, the individual contribution of each effector is AtSN1 expression is still complicated to clarify, because of the potentially complex and probable cross-talk between them. It is clear that several effectors directly or indirectly play a role in the determination of AtSN1 transcript levels, although it is interesting and quite unexpected how, deletion of just one effector gene (e.g. hopAO1) can have a severe effect on the levels of transcript of this retrotransposon. 79 Chapter 2 Figure 2.5. Experimental and statistical analysis of the effector protein mutants used to confirm differences in accumulation of AtSN1 transcript. Accumulation of AtSN1 transcript was analysed using RT-qPCR in Col-0 plants 24 hpi with Pto DC3000, or its CUCPB5451 (missing clusters II, IV and IX), CUCPB5459 (missing clusters I, II, IV, IX and X), ∆hopC1, ∆hopAO1, and ∆28E mutant derivatives. Bars represent one experiment with 5 plants per strain. Error bars represent the standard error. AtSN1 transcript levels were normalised to actin and the results presented as relative transcript accumulation compared to levels detected in Pto DC3000-infected plants 0 hpi . Mean values marked with the same letter were not significantly different from each other as established by One-way ANOVA, Benferroni PosHoc test. The values of each 24 hpi were compared to each other as well, as established by Student’s T-test, (*95%, **99% confidence intervals). 80 Chapter 2 Figure 2.6. Accumulation of AtSN1 transcript 24 hours post-inoculation with Pto DC3000 is significantly different in comparison to all single mutants used except of ∆hopC1. Accumulation of AtSN1 transcript was analysed using RT-qPCR in Col-0 plants 24 hpi Pto DC3000, ∆hopC1, ∆hopAO1, ∆hopU1 or ∆hopF2 mutant derivatives. Bars represent the mean values from 2 independent experiments with 5-8 plants per sample and experiment. Error bars represent the standard error. AtSN1 expression levels were normalised to actin and the results presented as relative mRNA accumulation compared to levels detected in Pto DC3000-infected plants 0 hpi. Mean values marked with the asterisk were significantly different from each other as established by Student T-test (95% confidence interval). 81 Chapter 3 AtSN1 transcript accumulation during different plant defence responses against P. syringae Chapter 3 3.1 AtSN1 transcript accumulation during basal defence response against P. syringae The first line of defence against pathogens, the PAMP-triggered response or PTI, can be triggered by non-host pathogens, T3SS-deficient pathogen mutants (e.g., ∆hrcV, ∆hrcC, ∆hrpL) or externally applied PAMPs, such as flagellin. To determine if transcript levels for the retrotransposon AtSN1 are also altered during PTI, we used the model bean pathogen P. syringae pv. phaseolicola 1448A (hereafter Pph 1448A), a non-host pathogen in Arabidopsis that causes no visible symptoms in Col-0 plants due to its triggering a strong, unsuppressed, PTI. No significant accumulation of AtSN1 transcript was detected in plants 24 hpi with Pph 1448a (Figure 3.1), being this level not significantly different to those displayed by naïve, mockinoculated or inoculated plants at 0 hpi, and clearly different from those displayed 24 hpi with Pto DC3000. These results are in keeping with our hypothesis of AtSN1 transcript accumulation being the result of direct or indirect T3 effector activity. Figure 3.1. AtSN1 transcript does not accumulate following inoculation with the non-host pathogen Pph 1448A. Accumulation of AtSN1 transcript was analysed using RT-qPCR in Col-0 plants 24 hpi with Pto DC3000 or Pph 1448A. Mock-inoculated plants were collected at 24 hpi and served as a control for mechanical damage. Bars represent the mean values from 3 independent experiments with 3-5 plants per sample and experiment. Error bars represent the standard error. AtSN1 transcript levels were normalised to actin and the results presented as relative transcript accumulation compared to levels detected in Pto DC3000-infected plants 0 hpi. Mean values marked with the same letter were not significantly different from each other as established by One-way ANOVA, Benferroni PosHoc test (99% confidence intervals). 85 Chapter 3 FLS2 (Flagellin Sensing 2) senses the flagellin-derived peptide flg22, and triggers a signalling cascade which affects the expression of hundreds of genes (Boller and Felix, 2009; Navarro et al., 2004; Zipfel et al., 2004). Recently, it has been reported by Yu et al., (2013) that flg22 depresses RNAdirected DNA Methylation (RdDM) in Arabidopsis leaves. RdDM is a plant regulatory mechanism that involves the biosynthesis of siRNAs that guide DNA methylation of transposons and repeats. These authors reported that external application of the flg22 peptide to Arabidopsis leaves induced the transcription of several transposons such as EVD, Onsen or AtSN1. To determine the role of flagellin in the transcriptional activation of transposons that takes place during infection with Pto DC3000, we analyzed the accumulation of AtSN1 transcript in plants inoculated with a Pto DC3000 ∆fliC mutant derivative, which does not produce flagellin (Material and methods, Table M1). Since this strain does not carry any antibiotic resistance we confirmed the deletion of the fliC gene by PCR using primers listed in Table M4 (Figure 3.2A), and confirmed its motility defect using a swimming assay (Figure 3.2B). As expected, the ∆fliC mutant is non-motile. When AtSN1 transcript levels were measured 24 hpi in a ∆fliC mutant strain, we observed a significant accumulation of AtSN1 transcript compared to 0 hpi, although this accumulation was significantly smaller than that detected in plants 24 hpi with Pto DC3000 (Figure 3.2C). Thus, we can conclude that in the context of an infection by Pto DC3000, flagellin also contributes to the transcriptional activation of AtSN1 transcript, although it does not do so to the same extent than the T3SS. Moreover, transcriptional activation of AtSN1 is not a general feature of all PTI responses since that triggered against Pph 1448a does not activate this transposon. 86 Chapter 3 Figure 3.2. Accumulation of AtSN1 transcript 24 hours post-inoculation with Pto DC3000 is partially dependent on flagellin. (A) PCR confirmation of the deletion of fliC in the ∆fliC strain. Genomic DNA of Pto DC3000 was used as a control. (B) Motility (swimming) assay. Bacterial strains were incubated for 2 days at 23°C on soft agar, King’s B containing 10 mM MgCl2 plate. The image shows 3 independent biological replicates for each strain (Pto DC3000; a1, a2, a3 and ∆fliC; b1, b2, b3) (C) Accumulation of AtSN1 transcript was analysed using RT-qPCR in Col-0 plants 24 hpi with Pto DC3000 or Pto ∆fliC. Mock-inoculated plants collected at 24 hpi, were included as controls. Bars represent the mean values from 2 independent experiments with 3-5 plants per sample and experiment. Error bars represent the standard error. AtSN1 transcript levels were normalised to actin and the results presented as relative transcript accumulation compared to levels detected in Pto DC3000-infected plants 0 hpi. Each time 0 hpi sample was compared to its 24 hpi. The values of each 24 hpi were compared to each other as well, and were shown to be statistically different as established by Student’s T-test, (95% confidence intervals). 87 Chapter 4 4.1 Analysis of the impact of Pto DC3000 infection on the expression of plant methylases and demethylases Yu and collaborators (2013) previously reported that treatment of Arabidopsis leaves with the flagellin peptide flg22 represses RdDM (RNA-directed DNA methylation) activity by down-regulating some of the key components of this pathway, such as the Argonaute protein AGO4, the Nuclear RNA Polymerase D2 (NRPD2), the Nuclear RNA Polymerase E5 (NRPE5), or the chromatinremodelling factor DRD1 (Defective in RNA-directed DNA methylation 1). Unexpectedly, this report did not include the analysis of the effects of flg22 treatment on the transcript levels of DRM2, a de novo DNA methyltansferase known to be involved in RdDM, reporting instead down-regulation of the maintenance DNA methyltransferase MET1. In addition, MET1 and the chromatin remodeler DDM1 are both down-regulated in response to Pto infection or salicylic acid treatment (Dowen et al., 2012). To gather additional insight on the effect of the infection with Pto on the plant DNA methylation machinery, we monitored transcript levels of the plant DNA methyltransferases, DRM2, MET1 and CMT3 as well as the demethylase ROS1 (a DNA glycosylase that removes methylcytosines from DNA, (Penterman et al., 2007)), during infection with Pto DC3000. Arabidopsis plants inoculated with Pto DC3000, showing activation of the retrotransposon AtSN1 24 hpi (Figure 4.1), displayed significant downregulation of MET1 and ROS1 transcript levels. These results are in agreement with previous reports since ROS1 is known to be robustly downregulated in DNA methylation-defective mutants (Martínez-Macías et al., 2012; Mathieu et al., 2007). We did not find evidence of Pto DC3000 infection having any impact on CMT3 transcript levels, but detected a robust upregulation of DRM2 (de novo DNA methyltransferase) not previously reported (Figure 4.1). 95 Chapter 4 Figure 4.1. Expression of the plant DNA methyltransferases and demethylases upon Pto DC3000 infection. Normalized transcript levels of the retrotransposon AtSN1, de novo DNA methyltransferase (DRM2), the maintenance DNA methyltransferases (MET1 and CMT3) and the DNA demethylase (ROS1) were determined by reverse transcription quantitative PCR (RT-qPCR) in Pto DC3000-infected Arabidopsis Col-0 plants 0 and 24 hpi. Mock-inoculated plants (m, 10 mM MgCl2) were included as a control for the basal transcript levels. Transcript levels were normalised to actin and the results presented as relative transcript accumulation compared to levels detected in plants 0 hpi with Pto DC3000. Bars represent the mean values from 2 independent experiments with 2-5 plants per sample and experiment. Error bars represent the standard error. Asterisks indicate samples that are statistically different from 0 hpi sample as determined by Student’s t-test with the 99% (**) or the 95% (*) confidence interval. 4.2 Bacterial entry and development of disease in plant DNA methylation mutants Microbial entry into the host tissue is a critical first step of the infection process in both animals and plants. In plants, microscopic surface openings (such as stomata or hydathodes) or wounds, serve as ports of bacterial entry during infection (Melotto et al., 2006). Upon detection of incoming bacteria the plant triggers stomata closure as part of the innate immunity response to prevent entry of the pathogen. These initial steps of the bacteria-plant interaction are bypassed when plants are inoculated by infiltration, an inoculation procedure that artificially delivers bacteria directly underneath the epidermis. However, natural infection, including these early steps, can be 96 Chapter 4 mimicked through dip or spray inoculation. These means of inoculation are less efficient and more variable but can provide additional information about the relevance of the early steps on the different outcomes of the plantpathogen interaction. Previous reports have demonstrated that the loss of DNA methylation enhances resistance to bacteria inoculated by infiltration (Agorio and Vera, 2007; Dowen et al., 2012). Thus, we considered of interest to analyse how the methylation status of the plant affects the interaction with spray-inoculated bacteria. We spray-inoculated plants with bacterial strains carrying mutations on genes relevant to the early steps of the infection process, i.e. a mutant defective in flagellin or coronatine production, as well as with wild type and wild type expressing the avirulence determinant AvrRpt2, as controls. We analysed their interaction with plants carrying each one of the following mutations: met1-3, ago4-2, ddc, and ros1-4. Symptom development was monitored after spray-inoculating 1 x 107 cfu/ml of the different strains, an inoculation dose sufficient to induce stomata closure at 1 hpi and coronatine-mediated stomata reopening at 3 hr in wild type infections (Melotto et al., 2006). Wild-type Col-0 plants inoculated with Pto DC3000 developed yellow necrotic lesions typical of disease development by 8 dpi, whereas those inoculated with Pto DC3000 expressing AvrRpt2 looked healthier, in keeping with AvrRpt2 triggering immunity (Figure 4.2). Plants inoculated with a CORmutant, expected to be severely attenuated when inoculated onto the leaf surface, but not when infiltrated directly into the apoplast (Brooks et al., 2004; Mittal and Davis, 1995), displayed symptoms more similar to mockedinoculated plants than to plants inoculated with the wild-type strain. Interestingly, plants inoculated with a ∆fliC mutant, which does not trigger FLS2-mediated PTI, displayed stronger disease symptoms that those inoculated with the wild-type strain (Figure 4.2). Although the role of FLS2mediated PTI in plant defence against P. syringae is undisputed (Jones and Dangl, 2006), this has been established using exogenously applied flg22 and the interaction between strains deficient in flagellin production and the plant has never been previously characterised. 97 Chapter 4 Figure 4.2. Plant genotypes affected in DNA methylation differentially affect disease development following spray-inoculation. Symptom development was monitored and documented in Col-0 wild type, met1-3, ddc, ago4-2, and ros1-4 spray-inoculated with 0.02% of Silwet and 1x107 cfu/ml of either Pto DC3000, Pto DC3000 expressing AvrRpt2, ∆fliC, or COR¯. Images shown were taken 8 dpi and are representative of 6 replicates per bacterial strain and plant genoptype. The experiment was repeated 3 times with similar results. When met1-3 plants were inoculated, we obtained similar results to those displayed by wild-type plants for all inoculated strains. When the triple mutant strain ddc was surveyed, plants inoculated with wild type, and remarkably with COR-, but not ∆fliC or Pto DC3000 expressing AvrRpt2 displayed stronger symptoms than the corresponding wild-type plants (Figure 4.2), suggesting than defences different from FLS2-mediated PTI, or RPS2-mediated ETI, may be compromised in this plant genotype. The fact that clear symptoms can be observed in ddc mutants inoculated with CORraises the interesting possibility of these plants being impaired for stomata closure upon pathogen detection. 98 Chapter 4 The ago4-2 mutant displayed stronger disease symptoms than wild type when inoculated with Pto DC3000, Pto DC3000 expressing AvrRpt2 or ∆fliC (Figure 4.2), in keeping with previous reports indicating than these plants are more susceptible to Pto DC3000 regardless of whether they are in a compatible or an incompatible interaction (Agorio and Vera, 2007). However, the fact that ago4-2 plants inoculated with CORdo not display any symptoms support the notion that, regardless of their general defect on defences, they are still capable of closing stomata upon pathogen detection. Finally, when ros1-4 plants were analysed, enhanced symptoms could be observed for all strain tested, including CORwas used (Figure 4.2). These results are very interesting since they suggest the implication of ROS1 in both ETI and PTI defences, including stomata closure. However, the difference in plants inoculated with ∆fliC were not as clear. In order to obtain a clearer view on this issue, we spray-inoculated 3 week old plants (1 week older than those showed in Figure 4.2), five plants per pot (total of 25 plants), of each Col-0 and ros1-4 genotypes with either Pto DC3000 or ∆fliC strains (Figure 4.3). By 14 dpi, ros1-4 mutant plants inoculated with Pto DC3000 showed more susceptibility, displayed as stunted growth and stronger yellowing, than Col-0 plants inoculated with Pto DC3000. Moreover, in keeping with the results shown in Figure 4.2, wild-type plants inoculated with the ∆fliC mutant strain displayed stronger symptoms than those inoculated with wild type bacteria. This increase in the severity of the symptoms developed upon inoculation with the ∆fliC strain was also apparent when ros1-4 plants were analyzed. Thus, the results indicate that the increased susceptibility observed in ros1-4 mutant inoculated with the wild-type strain is not due to a failure to establish flagellin-mediated PTI. This is of particular relevance considering that Yu and collaborators (Yu et al., 2013) recently reported that treatment with flg22 triggers local hypomethylation and activation of transcriptionally silenced loci in a ROS1dependent manner, and therefore support the involvement of ROS1 in more than one type of defence response. 99 Chapter 4 Figure 4.3. Mutant ros1-4 shows increased susceptibility to wild type and ∆ fliC bacteria. Symptoms development was monitored and documented in Col-0 wild type and ros1-4 spray-inoculated with 0.02% of Silwet and 1x107 cfu/ml of either Pto DC3000 or ∆fliC. Images shown were taken 14 dpi and are representative of 3 independent experiments with 15 plant replicates per bacterial strain and plant genotype. The experiment was repeated 3 times with similar results. 100 Chapter 4 To further explore the link between ROS1 and antibacterial defence, we tested the resistance of the ros1-4 mutant to proliferation of infiltrated Pto DC3000. By 4 dpi, we could observe a mild, although significant increase in wild type bacterial growth in ros1-4 plants compared to growth observed in wild type plants (Figure 4.4A). These results are in keeping with a role of ROS1-dependent DNA demethylation in antibacterial resistance. Since Yu and collaborators described this role as flagellin-dependent, but our results suggest its additional involvement in flagellin-independent defence responses, including stomata closure, we also tested growth of the ∆fliC and CORin ros1-4 plants. Both mutant strains grew significantly better in ros1-4 than in Col-0 plants indicating that the effect of ros1-4 on bacterial growth still takes place in the absence of flagellin, so it is not flagellin-dependent, and it also takes place in the absence of coronatine, so it is not coronatinedependent either. Finally, we also analysed whether the effects of ros1-4 on bacterial growth would also affect growth of a ∆hrcV mutant, which lacks a type III secretion system (Figure 4.4B). Although in this experiment the effect of ros1-4 in growth of Pto DC3000 was below statistical significance, the increase in growth of both the ∆fliC and CORmutants was clearly observed. Surprisingly, growth of the ∆hrcV was not increased but significantly decreased in comparison to the growth observed in Col-0 wild type plants. This bacterial strain lacks a functional T3SS and does not translocate any effector inside the host cell, but produces coronatine and possesses all functional elicitors of PTI (e.g. flagellin), which in the absence of effectors are not suppressed (Katagiri and Tsuda, 2010). 101 Chapter 4 Figure 4.4. Bacterial replication is increased in the DNA methylation mutant ros1-4. Plants of Col-0 and ros1-4 were inoculated with 5x104 cfu/ml of either Pto DC3000 (A and B), ∆fliC (A and B), ∆ hrcV (B) or COR- (A and B). Three disc leaves per plant were collected and processed just after the inoculation (0 dpi), and by 4 dpi. Bacterial colonies were counted and represented in logarithmical scale. Error bars represent the standard error. Mean cfu values obtained from ros1-4 plants were compared to the corresponding value obtained for the same strain and time point from Col-0 wild type plants. Asterisks indicate significant differences as established by Student t-test, with 95% (*), 99% (**) confidence interval difference. Experiment was repeated twice with similar results. 4.3 Bacterial replication in DNA methylation mutant plants Some plant genotypes with altered DNA methylation levels (met1-3, ddc, ddm1, drd1, nrpd1a, etc.) have been previously reported to differentially affect growth of P. syringae (Agorio and Vera, 2007; Dowen et al., 2012; Yu et al., 2013)). Among the mutants analysed in this work, ros1-4, ago4-2 and met1-3 have been previously tested for growth of P. syringae. Whereas Pto DC3000 has been reported to grow more in an ago4-2 and ros1-4 mutant than in wild-type plants (Agorio and Vera, 2007, Yu et al., 2013), it was reported to growth less in a met1-3 mutant (Dowen et al., 2012). While the results reported for ago4-2 plants are in keeping with the results shown in Figure 4.2 where ago4-2 plants displayed stronger disease symptoms following inoculation with Pto DC3000 than wild type, those reported for met1-3 mutant are not so clear, since no changes in the development of symptoms associated to Pto DC3000 infection could be observed in these 102 Chapter 4 plants when compared to wild type plants (Figure 4.2). To gather additional insight on the effect of these two plant genotypes in our system and experimental conditions, we analysed growth of P. syringae strains using two different approaches, individual and mixed infections. First, Pto DC3000 was inoculated by infiltration into wild type, ago4-2 and met1-3 plants and bacterial growth was analysed 2 and 4 dpi (Figure 4.5). In keeping with previous results and reports, the changes in methylation of the ago4-2 mutant benefit the pathogen, since a significant increase in growth could be already detected by 2 dpi. By 4 dpi, replication levels in the mutant were almost 10-fold higher than those reached in wild type Col-0 plants (Figure 4.5). When bacterial growth was analyzed in met1-3 plants we observed a significant decrease in bacterial growth in comparison to that found in wild-type plants (Figure 4.5). By 4 dpi, replication levels in the mutant were almost 10-fold higher than those reached in wild type Col-0 plants (Figure 4.5). When bacterial growth was analyzed in met1-3 plants, we observed a significant decrease in bacterial growth in comparison to that found in wild-type plants (Figure 4.5). This result is in keeping with previous reports and supports a role for MET1 in disease development, since in its absence bacterial growth is impaired. 103 Concluding remarks Concluding remarks Pseudomonas syringae pv. tomato (Pto) strain DC3000 in its interaction with Arabidopsis constitutes a well characterized model system. The ability of these bacteria to infect Arabidopsis depends on the Hrp T3SS, and the role of the T3SS and that of its translocated effectors in suppressing the plant defence have been the focus of many recent reports. However, the particular mechanisms by which different T3Es interfere with the plant defences are still largely unknown. When this work begun there was one report that indicated that the plant DNA methylation status changed during infection with Pto (Pavet et al., 2006). Interference with the host DNA methylation status and/or with other epigenetic mechanisms have been shown to be an important virulence mechanism in mammalian pathogens (Gómez-Díaz et al., 2012; Hamon and Cossart, 2008; Paschos and Allday, 2010). Although less was known in plants, plant viruses do suppress repressive methylation and transcriptional silencing of viral, transgenic and endogenous loci during the infection (Raja et al., 2010; Rodríguez‐Negrete et al., 2013; Zhang et al., 2011). Thus, the report by Pavet and collaborators (2006) raised the interesting possibility of plant pathogenic bacteria also altering the host epigenome during infection. Such was the initial interest of these observations that gave raise to the objectives of this thesis. Pavet and collaborators reported that infection with Pto induced rapid DNA hypomethylation at pericentromeric chromatin (by 24 hpi), including repeats such as the 180-bp unit and Athila retrotansposon, and that this hypomethylation was not associated to DNA replication, suggesting the involvement of an active demethylation process. The initial work of this thesis encountered many technical difficulties in reproducibly replicating the results presented by Pavet and collaborators, probably due to the fact that epigenetic changes do not take place in all plant cells on the inoculated tissue but only in those adjacent to the invading bacteria. However, these difficulties allowed us to make some interesting observations such as, the fact that plant DNA hypomethylation is clearer when the initial stages of the infection take place at a subjective night (under night conditions, i.e. the inoculation takes place immediately before the 16 h dark period). We also established that accompanying these changes, which 113 Concluding remarks occur during the first 24 hours of Pto infection, TGS loci become transcriptionally active. Among other loci, we could detect the transcriptional activation of the retrotransposon AtSN1 but direct demonstration of its hypomethylation has evaded us, probably also due to its being restricted to bacteria-adjacent cells and thus diluted in the inoculated tissue analysed. AtSN1 was later shown to become transcriptionally active through DNA hypomethylation upon treatment with exogenous bacterial flagellin (flg22), supporting that its activation during Pto infection is probably due to plant DNA hypomethylation (Yu et al., 2013). The use of the highly activated TGS locus AtSN1 as a reporter has been greatly useful in the analysis of the role that Pto virulence determinants have in altering the transcriptional status of TGS loci, and probably in altering plant DNA methylation levels. Thus, we showed that as could be expected from the work of Pavet and collaborators (2006), transcriptional activation of AtSN1 requires the transcriptional activator of T3SS genes, HrpL. We also established that this is due to the requirement of a functional T3SS since a mutant in a gene encoding one of the structural components, which does not translocate any effectors, also fails to activate transcription of AtSN1. Interestingly, in the context of a fully functional T3SS, coronatine is also necessary for full activation of AtSN1 transcription supporting that functional redundancy is a common element between plant pathogenic virulence determinants. Analysis of mutants lacking one or more effectors has also proven interesting. We have shown that one or more of the 28 bona fide Pto DC3000 effectors is required to activate AtSN1. Moreover, we have found that deletion of different groups of effectors may lead to either a failure to activate AtSN1, or an enhanced activation, indicating that effectors are involved in both triggering the transcriptional activation of AtSN1 and in suppressing it. One candidate effector involved in triggering its activation is HopC1, although the difficulties for reproducibly and further support the involvement of more than one effector in the process. Similarly HopAO1 is a candidate effector to suppress activation of AtSN1 but again functional redundancy is expected. 114 Concluding remarks The fact that Pto T3Es act both activating and suppressing AtSN1 suggests that one or the other is part of the plant defence response. In this regard, a second report studying the changes on DNA methylation during Pto infection profiled the entire Arabidppsis DNA methylome during the interaction with both virulent and avirulent Pto, revealing that many genomic regions enriched in transposon sequences became differentially methylated, affecting transcription of neighbouring protein-coding genes, including defence-related genes (Dowen et al., 2012). These changes also took place following treatment with exogenous SA. If we also take into account that Yu and collaborators (2013) showed activation of AtSN1 through changes in methylation upon treatment with exogenous bacterial flagellin (flg22) all these results suggest activation of AtSN1 is likely part of the plant defence response against Pto, and thus Pto encodes effector(s) directly or indirectly capable of suppressing this activation. Our results show that this is indeed the case. We found that in keeping with the results presented by Yu and collaborators (2013) activation of AtSN1 is partially dependent on the bacterial production of flagellin, since accumulation of AtSN1 transcript is reduced but not abolished in plants inoculated with a ∆ fliC mutant, thus supporting the involvement of transcriptional activation of TGS loci in PTI. However, this is not a universal feature of flagellin-dependent PTI in Arabidopsis since inoculation with the non-host bacteria P. syringae pv. phaseolicola does not induce accumulation of AtSN1. Furthermore, this is not the only defence response in which activation of TGS loci takes place since levels of AtSN1 transcript are significantly higher during the incompatible interaction of Arabidopsis with Pto expressing the heterologous effectors AvrRpt2, AvrRps4, AvrRpm1 or HopZ1a, and these increased levels require effector recognition dependent on their corresponding R genes, RPS2, RPS4, RPM1 and ZAR1, respectively. Thus our results demonstrate that transcriptional activation of TGS loci also takes place as part of the ETI. In keeping with the relation between the changes in DNA methylation, activation of TGS loci and plant defences, we found that transcription of the genes encoding the maintenance DNA methyltransferase MET1 and the demethylase ROS1 were downregulated during infection with Pto, whereas 115 Concluding remarks transcription of the gene encoding the DNA methyltransferas DRM2 was upregulated. The involvement of the changes in DNA methylation and activation of TGS loci in different types of plant defences is additionally supported when bacterial growth is analysed in plant mutants affected in these processes. We found that the triple mutant ddc (drm1-2 drm2-2 cmt3-11) that presents alteration in DNA methylation mainly at CHG and CHH sites is impaired in defences different from flagellin-triggered PTI or RPS2-triggered ETI, which include stomata closure upon pathogen detection since a CORmutant induces stronger symptoms in this plant mutant. Reversely, flagellintriggered PTI and RPS2-triggered ETI, but not stomata closure were impaired in ago4-2 mutants leading to a significant increase on bacterial growth within this plant genotype. We also found the met1-3 mutant more susceptible to Pto than the wild type, although this is not always clear depending on the virulence assay used. Finally, we also found that a ros1-4 mutant is more susceptible to Pto, in agreement with Yu and collaborators (2013), however this is not only due to a failure to establish an effective PTI since this mutant is also more susceptible to a ∆ fliC mutant, a COR-, and to Pto expressing AvrRpt2. To summarise, the results presented in this thesis support the notion initially proposed by recent studies of RNA-directed DNA methylation (RdDM) and transcriptional gene silencing (TGS) having an important role in plant defence against phytopathogenic bacteria (Pumplin and Voinnet, 2013). Dampening defence gene expression through RdDM could provide an effective mode of regulation because RdDM can be rapidly reversed by biotic and abiotic stress. The rapid activation of plant defences would require the presence of RdDM-prone genomic segments (transposons and repeats) in the vicinity of defence-related genes and the involvement of active demethylation pathways to ensure optimal and rapid defence gene induction on pathogen attack. In addition, the dampening of RdDM and the resulting defence gene activation occurs only transiently, to prevent the prolonged induction of these stress-responsive plant genes. This feature is foreseeably advantageous in the case of defence-related genes whose continuous expression reduces plant 116 Concluding remarks fitness. In such a model, the acquisition of effectors capable of directly or indirectly suppressing this activation would represent a clear advantage for plant pathogenic bacteria. 117 Conclusions References transfer between chromosomes and plasmid transformation. J Microbiol Methods 64, 391-397. Choi, M.S., Kim, W., Lee, C. and Oh, C.S. (2013) Harpins, multifunctional proteins secreted by gram-negative plant-pathogenic bacteria. Molecular Plant-Microbe Interactions 26, 1115-1122. Collmer, A., Lindeberg, M., Petnicki-Ocwieja, T., Schneider, D.J. and Alfano, J.R. (2002) Genomic mining type III secretion system effectors in Pseudomonas syringae yields new picks for all TTSS prospectors. Trends in Microbiology 10, 462-469. Collmer, A., Schneider, D.J. and Lindeburg, M. (2009) Lifestyles of the effector rich: Genomeenabled characterization of bacterial plant pathogens. Plant Physiology 150, 16231630. Cunnac, S., Chakravarthy, S., Kvitko, B.H., Russell, A.B., Martin, G.B. and Collmer, A. (2011) Genetic disassembly and combinatorial reassembly identify a minimal functional repertoire of type III effectors in Pseudomonas syringae. Proceedings of the National Academy of Sciences of the United States of America 108, 2975-2980. Cunnac, S., Lindeberg, M. and Collmer, A. (2009) Pseudomonas syringae type III secretion system effectors: repertoires in search of functions. Current Opinion in Microbiology 12, 53-60. Cuppels, D.A. (1986) Generation and characterization of Tn5 insertion mutations in Pseudomonas syringae pv. tomato. Applied and environmental microbiology 51, 323327. Dangl, J.L. and Jones, J.D.G. (2001) Plant pathogens and integrated defence responses to infection. Nature 411, 826-833. Dangl, J.L., Ritter, C., Gibbon, M.J., Mur, L.A.J., Wood, J.R., Goss, S., Mansfield, J., Taylor, J.D. and Vivian, A. (1992) Functional homologs of the Arabidopsis RPM1 disease resistance gene in bean and pea. Plant Cell 4, 1359-1369. Datsenko, K.A. and Wanner, B.L. (2000) One-step inactivation of chromosomal genes in Escherichia coli K-12 using PCR products. Proceedings of the National Academy of Sciences 97, 6640-6645. De Torres, M., Mansfield, J.W., Grabov, N., Brown, I.R., Ammouneh, H., Tsiamis, G., Forsyth, A., Robatzek, S., Grant, M. and Boch, J. (2006) Pseudomonas syringae effector AvrPtoB suppresses basal defence in Arabidopsis. Plant Journal 47, 368-382. Delaney, T.P., Friedrich, L. and Ryals, J.A. (1995) Arabidopsis signal transduction mutant defective in chemically and biologically induced disease resistance. Proceedings of the National Academy of Sciences of the United States of America 92, 6602-6606. Dowen, R.H., Pelizzola, M., Schmitz, R.J., Lister, R., Dowen, J.M., Nery, J.R., Dixon, J.E. and Ecker, J.R. (2012) Widespread dynamic DNA methylation in response to biotic stress. Proceedings of the National Academy of Sciences 109, E2183–E2191. Earley, K.W., Pontvianne, F., Wierzbicki, A.T., Blevins, T., Tucker, S., Costa-Nunes, P., Pontes, O. and Pikaard, C.S. (2010) Mechanisms of HDA6-mediated rRNA gene silencing: Suppression of intergenic Pol II transcription and differential effects on maintenance versus siRNA-directed cytosine methylation. Genes and Development 24, 1119-1132. Felix, G., Duran, J.D., Volko, S. and Boller, T. (1999) Plants have a sensitive perception system for the most conserved domain of bacterial flagellin. Plant Journal 18, 265276. Feys, B.J.F., Benedetti, C.E., Penfold, C.N. and Turner, J.G. (1994) Arabidopsis mutants selected for resistance to the phytotoxin coronatine are male sterile, insensitive to methyl jasmonate, and resistant to a bacterial pathogen. Plant Cell 6, 751-759. Finnegan, E.J., Peacock, W.J. and Dennis, E.S. (1996) Reduced DNA methylation in Arabidopsis thaliana results in abnormal plant development. Proceedings of the National Academy of Sciences of the United States of America 93, 8449-8454. Freter, R., Allweiss, B., O'Brien, P.C., Halstead, S.A. and Macsai, M.S. (1981) Role of chemotaxis in the association of motile bacteria with intestinal mucosa: in vitro studies. Infect Immun 34, 241-249. Furner, I.J. and Matzke, M. (2011) Methylation and demethylation of the Arabidopsis genome. Current Opinion in Plant Biology 14, 137-141. Galán, J.E. and Collmer, A. (1999) Type III secretion machines: Bacterial devices for protein delivery into host cells. Science 284, 1322-1328. 126 References Gilardi, G.L. (1972) Infrequently encountered Pseudomonas species causing infection in humans. Annals of Internal Medicine 77, 211-215. Glazebrook, J. (2005) Contrasting mechanisms of defense against biotrophic and necrotrophic pathogens. Annual Review of Phytopathology 43, 205-227. Göhre, V. and Robatzek, S. (2008) Breaking the barriers: Microbial effector molecules subvert plant immunity. In: Annual Review of Phytopathology pp. 189-215. Gómez-Díaz, E., Jordà, M., Peinado, M.A. and Rivero, A. (2012) Epigenetics of host–pathogen interactions: the road ahead and the road behind. PLoS pathogens 8, e1003007. Gómez-Gómez, L. and Boller, T. (2002) Flagellin perception: A paradigm for innate immunity. Trends in Plant Science 7, 251-256. González, A.J., Landeras, E. and Mendoza, M.C. (2000) Pathovars of Pseudomonas syringae Causing Bacterial Brown Spot and Halo Blight in Phaseolus vulgaris L. Are Distinguishable by Ribotyping. Applied and environmental microbiology 66, 850-854. Grant, M.R., Godiard, L., Straube, E., Ashfield, T., Lewald, J., Sattler, A., Innes, R.W. and Dangl, J.L. (1995) Structure of the Arabidopsis RPM1 gene enabling dual specificity disease resistance. Science 269, 843-846. Haag, J.R., Pontes, O. and Pikaard, C.S. (2009) Metal A and metal B sites of nuclear RNA polymerases Pol IV and Pol V are required for siRNA-dependent DNA methylation and gene silencing. PLoS One 4, e4110. Hamon, M. and Cossart, P. (2008) Histone modifications and chromatin remodeling during bacterial infections. Cell Host & Microbe 4, 100-109. Hanahan, D. (1983) Studies on transformation of Escherichia coli with plasmids. Journal of Molecular Biology 166, 557-580. Hayat, S., Ali, B. and Ahmad, A. (2007) Salicylic Acid: Biosynthesis, Metabolism and Physiological Role in Plants. In: Salicylic Acid: A Plant Hormone (Hayat, S. and Ahmad, A. eds), pp. 1-14. Springer Netherlands. He, P., Shan, L., Lin, N.C., Martin, G.B., Kemmerling, B., Nürnberger, T. and Sheen, J. (2006) Specific Bacterial Suppressors of MAMP Signaling Upstream of MAPKKK in Arabidopsis Innate Immunity. Cell 125, 563-575. Henderson, I.R. and Jacobsen, S.E. (2007) Epigenetic inheritance in plants. Nature 447, 418-424. Hinsch, M. and Staskawicz, B. (1996) Identification of a new Arabidopsis disease resistance locus, RPS4, and cloning of the corresponding avirulence gene, avrRps4, from Pseudomonas syringae pv. pisi. Molecular Plant-Microbe Interactions 9, 55-61. Hirano, S.S. and Upper, C.D. (2000) Bacteria in the leaf ecosystem with emphasis on Pseudomonas syringae - A pathogen, ice nucleus, and epiphyte. Microbiology and Molecular Biology Reviews 64, 624-653. Holmes, D.S. and Quigley, M. (1981) A rapid boiling method for the preparation of bacterial plasmids. Analytical Biochemistry 114, 193-197. Hrabak, E. and Willis, D.K. (1992) The lemA gene required for pathogenicity of Pseudomonas syringae pv. syringae on bean is a member of a family of two-component regulators. Journal of bacteriology 174, 3011-3020. Jaenisch, R. and Bird, A. (2003) Epigenetic regulation of gene expression: How the genome integrates intrinsic and environmental signals. Nature Genetics 33, 245-254. Johnson, L.M., Bostick, M., Zhang, X., Kraft, E., Henderson, I., Callis, J. and Jacobsen, S.E. (2007) The SRA Methyl-Cytosine-Binding Domain Links DNA and Histone Methylation. Current Biology 17, 379-384. Jones, J.D.G. and Dangl, J.L. (2006) The plant immune system. Nature 444, 323-329. Kakutani, T., Jeddeloh, J.A., Flowers, S.K., Munakata, K. and Richards, E.J. (1996) Developmental abnormalities and epimutations associated with DNA hypomethylation mutations. Proceedings of the National Academy of Sciences of the United States of America 93, 12406-12411. Katagiri, F., Thilmony, R. and He, S.Y. (2002) The Arabidopsis thaliana-Pseudomonas syringae Interaction. The Arabidopsis Book, e0039. Katagiri, F. and Tsuda, K. (2010) Understanding the plant immune system. Molecular PlantMicrobe Interactions 23, 1531-1536. Keith Slotkin, R. (2010) The epigenetic control of the athila family of retrotransposons in Arabidopsis. Epigenetics 5, 483-490. 127 References Kim, H.S., Desveaux, D., Singer, A.U., Patel, P., Sondek, J. and Dangl, J.L. (2005) The Pseudomonas syringae effector AvrRpt2 cleaves its C-terminally acylated target, RIN4, from Arabidopsis membranes to block RPM1 activation. Proceedings of the National Academy of Sciences of the United States of America 102, 6496-6501. King, E.O., Ward, M.K. and Raney, D.E. (1954) Two simple media for the demonstration of pyocyanin and fluorescin. The Journal of Laboratory and Clinical Medicine 44, 301307. Kitten, T., Kinscherf, T.G., McEvoy, J.L. and Willis, D.K. (1998) A newly identified regulator is required for virulence and toxin production in Pseudomonas syringae. Molecular microbiology 28, 917-929. Klement, Z. and Lovrekovich, L. (1961) Defence Reactions Induced by Phytopathogenic Bacteria in Bean Pods. Journal of Phytopathology 41, 217-227. Kloek, A.P., Verbsky, M.L., Sharma, S.B., Schoelz, J.E., Vogel, J., Klessig, D.F. and Kunkel, B.N. (2001) Resistance to Pseudomonas syringae conferred by an Arabidopsis thaliana coronatine-insensitive (coi1) mutation occurs through two distinct mechanisms. Plant Journal 26, 509-522. Kunkel, B.N., Bent, A.F., Dahlbeck, D., Innes, R.W. and Staskawicz, B.J. (1993) RPS2, an Arabidopsis disease resistance locus specifying recognition of Pseudomonas syringae strains expressing the avirulence gene avrRpt2. Plant Cell 5, 865-875. Kunkel, B.N. and Brooks, D.M. (2002) Cross talk between signaling pathways in pathogen defense. Current Opinion in Plant Biology 5, 325-331. Kvitko, B.H., Park, D.H., Velásquez, A.C., Wei, C.F., Russell, A.B., Martin, G.B., Schneider, D.J. and Collmer, A. (2009) Deletions in the repertoire of Pseudomonas syringae pv. tomato DC3000 type III secretion effector genes reveal functional overlap among effectors. PLoS Pathogens 5. Law, J.A. and Jacobsen, S.E. (2010) Establishing, maintaining and modifying DNA methylation patterns in plants and animals. Nature Reviews Genetics 11, 204-220. Lennox, E. (1955) Transduction of linked genetic characters of the host by bacteriophage P1. Virology 1, 190-206. Li, X., Lin, H., Zhang, W., Zou, Y., Zhang, J., Tang, X. and Zhou, J.M. (2005) Flagellin induces innate immunity in nonhost interactions that is suppressed by Pseudomonas syringae effectors. Proceedings of the National Academy of Sciences of the United States of America 102, 12990-12995. Lindeberg, M., Cartinhour, S., Myers, C.R., Schlechter, L.M., Schneider, D.J. and Collmer, A. (2006) Closing the circle on the discovery of genes encoding Hrp regulon members and type III secretion system effectors in the genomes of three model Pseudomonas syringae strains. Molecular Plant-Microbe Interactions 19, 1151-1158. Macho, A.P. and Beuzón, C.R. (2010) Insights into plant immunity signalling: the bacterial competitive index angle. Plant signaling & behavior 5, 1590-1593. Macho, A.P., Guevara, C.M., Tornero, P., Ruiz‐Albert, J. and Beuzón, C.R. (2010) The Pseudomonas syringae effector protein HopZ1a suppresses effector‐triggered immunity. New phytologist 187, 1018-1033. Macho, A.P., Ruiz-Albert, J., Tornero, P. and Beuzon, C.R. (2009) Identification of new type III effectors and analysis of the plant response by competitive index. Mol Plant Pathol 10, 69-80. Macho, A.P. and Zipfel, C. (2014) Plant PRRs and the activation of innate immune signaling. Molecular Cell 54, 263-272. Macho, A.P., Zumaquero, A., Ortiz-Martin, I. and Beuzon, C.R. (2007) Competitive index in mixed infections: a sensitive and accurate assay for the genetic analysis of Pseudomonas syringae-plant interactions. Mol Plant Pathol 8, 437-450. Martienssen, R.A. and Richards, E.J. (1995) DNA methylation in eukaryotes. Current Opinion in Genetics and Development 5, 234-242. Martínez-Macías, M.I., Qian, W., Miki, D., Pontes, O., Liu, Y., Tang, K., Liu, R., Morales-Ruiz, T., Ariza, R.R., Roldán-Arjona, T. and Zhu, J.K. (2012) A DNA 3' Phosphatase Functions in Active DNA Demethylation in Arabidopsis. Molecular Cell 45, 357-370. Mathieu, O., Reinders, J., Čaikovski, M., Smathajitt, C. and Paszkowski, J. (2007) Transgenerational Stability of the Arabidopsis Epigenome Is Coordinated by CG Methylation. Cell 130, 851-862. 128 References Matzke, M., Kanno, T., Daxinger, L., Huettel, B. and Matzke, A.J. (2009) RNA-mediated chromatin-based silencing in plants. Current Opinion in Cell Biology 21, 367-376. Matzke, M.A., Mette, M.F. and Matzke, A.J.M. (2000) Transgene silencing by the host genome defense: Implications for the evolution of epigenetic control mechanisms in plants and vertebrates. Plant Molecular Biology 43, 401-415. Matzke, M.A. and Mosher, R.A. (2014) RNA-directed DNA methylation: An epigenetic pathway of increasing complexity. Nature Reviews Genetics 15, 394-408. Melotto, M., Underwood, W., Koczan, J., Nomura, K. and He, S.Y. (2006) Plant Stomata Function in Innate Immunity against Bacterial Invasion. Cell 126, 969-980. Melotto, M., Underwood, W. and Sheng, Y.H. (2008) Role of stomata in plant innate immunity and foliar bacterial diseases. Annual Review of Phytopathology 46, 101122. Mittal, S. and Davis, K.R. (1995) Role of the phytotoxin coronatine in the infection of Arabidopsis thaliana by Pseudomonas syringae pv. tomato. Molecular Plant-Microbe Interactions 8, 165-171. Mohr, T.J., Liu, H., Yan, S., Morris, C.E., Castillo, J.A. and Jelenska, J. (2008) Naturally occurring non-pathogenic isolates of the plant pathogen species Pseudomonas syringae lack a Type III secretion system and effector gene orthologues. J Bacteriol 190, 2858-2870. Mudgett, M.B. and Staskawicz, B.J. (1999) Characterization of the Pseudomonas syringae pv. tomato AvrRpt2 protein: demonstration of secretion and processing during bacterial pathogenesis. Molecular Microbiology 32, 927-941. Naito, K., Taguchi, F., Suzuki, T., Inagaki, Y., Toyoda, K., Shiraishi, T. and Ichinose, Y. (2008) Amino acid sequence of bacterial microbe-associated molecular pattern flg22 is required for virulence. Molecular Plant-Microbe Interactions 21, 1165-1174. Navarro, L., Zipfel, C., Rowland, O., Keller, I., Robatzek, S., Boller, T. and Jones, J.D.G. (2004) The transcriptional innate immune response to flg22. Interplay and overlap with Avr gene-dependent defense responses and bacterial pathogenesis. Plant Physiology 135, 1113-1128. Nawrath, C., Heck, S., Parinthawong, N. and Métraux, J.P. (2002) EDS5, an essential component of salicylic acid-dependent signaling for disease resistance in Arabidopsis, is a member of the MATE transporter family. Plant Cell 14, 275-286. Nguyen, L., Paulsen, I.T., Tchieu, J., Hueck, C.J. and Saier Jr, M.H. (2000) Phylogenetic analyses of the constituents of Type III protein secretion systems. Journal of Molecular Microbiology and Biotechnology 2, 125-144. Oakes, C.C., La Salle, S., Trasler, J.M. and Robaire, B. (2009) Restriction digestion and realtime PCR (qAMP). Methods in molecular biology (Clifton, N.J.) 507, 271-280. Orth, K., Xu, Z., Mudgett, M.B., Bao, Z.Q., Palmer, L.E., Bliska, J.B., Mangel, W.F., Staskawicz, B. and Dixon, J.E. (2000) Disruption of signaling by yersinia effector YopJ, a ubiquitin-like protein protease. Science 290, 1594-1597. Paschos, K. and Allday, M. (2010) Epigenetic reprogramming of host genes in viral and microbial pathogenesis. Trends in Microbiology 18, 439–447. Pavet, V., Quintero, C., Cecchini, N.M., Rosa, A.L. and Alvarez, M.E. (2006) Arabidopsis Displays Centromeric DNA Hypomethylation and Cytological Alterations of Heterochromatin Upon Attack by Pseudomonas syringae. Molecular Plant-Microbe Interactions 19, 577-587. Peñaloza-Vazquez, A., Preston, G.M., Collmer, A. and Bender, C.L. (2000) Regulatory interactions between the Hrp type III protein secretion system and coronatine biosynthesis in Pseudomonas syringae pv. tomato DC3000. Microbiology 146, 24472456. Penterman, J., Zilberman, D., Jin, H.H., Ballinger, T., Henikoff, S. and Fischer, R.L. (2007) DNA demethylation in the Arabidopsis genome. Proceedings of the National Academy of Sciences of the United States of America 104, 6752-6757. Pumplin, N. and Voinnet, O. (2013) RNA silencing suppression by plant pathogens: defence, counter-defence and counter-counter-defence. Nature Reviews Microbiology 11, 745760. Raja, P., Wolf, J.N. and Bisaro, D.M. (2010) RNA silencing directed against geminiviruses: Post-transcriptional and epigenetic components. Biochimica et Biophysica Acta - Gene Regulatory Mechanisms 1799, 337-351. 129 References Ranjan, R., Patro, S., Pradhan, B., Kumar, A., Maiti, I.B. and Dey, N. (2012) Development and functional analysis of novel genetic promoters using DNA shuffling, hybridization and a combination thereof. PLoS One 7, e31931. Reymond, P. and Farmer, E.E. (1998) Jasmonate and salicylate as global signals for defense gene expression. Current Opinion in Plant Biology 1, 404-411. Rich, J.J., Kinscherf, T.G., Kitten, T. and Willis, D.K. (1994) Genetic evidence that the gacA gene encodes the cognate response regulator for the lemA sensor in Pseudomonas syringae. Journal of bacteriology 176, 7468-7475. Rodríguez‐Negrete, E., Lozano‐Durán, R., Piedra‐Aguilera, A., Cruzado, L., Bejarano, E.R. and Castillo, A.G. (2013) Geminivirus Rep protein interferes with the plant DNA methylation machinery and suppresses transcriptional gene silencing. New Phytologist 199, 464-475. Ronald, P.C., Salmeron, J., Carland, F. and Staskawicz, B. (1992) The cloned avirulence gene avrPto induces disease resistance in tomato cultivars containing the Pto resistance gene. Journal of bacteriology 174, 1604-1611. Ronemus, M.J., Galbiati, M., Ticknor, C., Chen, J. and Dellaporta, S.L. (1996) Demethylation-induced developmental pleiotropy in Arabidopsis. Science 273, 654657. Ryals, J.A., Neuenschwander, U.H., Willits, M.G., Molina, A., Steiner, H.Y. and Hunt, M.D. (1996) Systemic acquired resistance. Plant Cell 8, 1809-1819. Ryan, C.A. and Pearce, G. (1998) Systemin: A polypeptide signal for plant defensive genes. In: Annual Review of Cell and Developmental Biology pp. 1-17. Sandegren, L., Lindqvist, A., Kahlmeter, G. and Andersson, D.I. (2008) Nitrofurantoin resistance mechanism and fitness cost in Escherichia coli. Journal of Antimicrobial Chemotherapy 62, 495-503. Schechter, L.M., Vencato, M., Jordan, K.L., Schneider, S.E., Schneider, D.J. and Collmer, A. (2006) Multiple approaches to a complete inventory of Pseudomonas syringae pv. tomato DC3000 type III secretion system effector proteins. Molecular Plant-Microbe Interactions 19, 1180-1192. Schwessinger, B. and Zipfel, C. (2008) News from the frontline: recent insights into PAMPtriggered immunity in plants. Current Opinion in Plant Biology 11, 389-395. Soppe, W.J.J., Jacobsen, S.E., Alonso-Blanco, C., Jackson, J.P., Kakutani, T., Koornneef, M. and Peeters, A.J.M. (2000) The late flowering phenotype of fwa mutants is caused by gain-of-function epigenetic alleles of a homeodomain gene. Molecular Cell 6, 791-802. Stroud, H., Do, T., Du, J., Zhong, X., Feng, S., Johnson, L., Patel, D.J. and Jacobsen, S.E. (2014) Non-CG methylation patterns shape the epigenetic landscape in Arabidopsis. Nature Structural and Molecular Biology 21, 64-72. Takeda, S., Tadele, Z., Hofmann, I., Probst, A.V., Angelis, K.J., Kaya, H., Araki, T., Mengiste, T., Scheid, O.M., Shibahara, K.I., Scheel, D. and Paszkowski, J. (2004) BRU1, a novel link between responses to DNA damage and epigenetic gene silencing in Arabidopsis. Genes and Development 18, 782-793. Taylor, J.D., Teverson, D.M., Allen, D.J. and Pastor-Corrales, M.A. (1996) Identification and origin of races of Pseudomonas syringae pv. phaseolicola from Africa and other bean growing areas. Plant Pathology 45, 469-478. Taylor, R.K., Miller, V.L., Furlong, D.B. and Mekalanos, J.J. (1987) Use of phoA gene fusions to identify a pilus colonization factor coordinately regulated with cholera toxin. Proceedings of the National Academy of Sciences of the United States of America 84, 2833-2837. Tsuda, K., Sato, M., Glazebrook, J., Cohen, J.D. and Katagiri, F. (2008) Interplay between MAMP-triggered and SA-mediated defense responses. Plant Journal 53, 763-775. Underwood, W., Melotto, M. and He, S.Y. (2007) Role of plant stomata in bacterial invasion. Cellular Microbiology 9, 1621-1629. Van Der Biezen, E.A. and Jones, J.D.G. (1998) Plant disease-resistance proteins and the gene-for-gene concept. Trends in Biochemical Sciences 23, 454-456. Vongs, A., Kakutani, T., Martienssen, R.A. and Richards, E.J. (1993) Arabidopsis thaliana DNA methylation mutants. Science 260, 1926-1928. Wei, C.F., Kvitko, B.H., Shimizu, R., Crabill, E., Alfano, J.R., Lin, N.C., Martin, G.B., Huang, H.C. and Collmer, A. (2007) A Pseudomonas syringae pv. tomato DC3000 mutant 130 References lacking the type III effector HopQ1‐1 is able to cause disease in the model plant Nicotiana benthamiana. The Plant Journal 51, 32-46. Widman, N., Jacobsen, S.E. and Pellegrini, M. (2009) Determining the conservation of DNA methylation in Arabidopsis. Epigenetics 4, 119-124. Wierzbicki, A.T., Ream, T.S., Haag, J.R. and Pikaard, C.S. (2009) RNA polymerase v transcription guides ARGONAUTE4 to chromatin. Nature Genetics 41, 630-634. Wildermuth, M.C., Dewdney, J., Wu, G. and Ausubel, F.M. (2001) Isochorismate synthase is required to synthesize salicylic acid for plant defence. Nature 414, 562-565. Xie, Z., Johansen, L.K., Gustafson, A.M., Kasschau, K.D., Lellis, A.D., Zilberman, D., Jacobsen, S.E. and Carrington, J.C. (2004) Genetic and functional diversification of small RNA pathways in plants. PLoS Biology 2. Yu, A., Lepère, G., Jay, F., Wang, J., Bapaume, L., Wang, Y., Abraham, A.L., Penterman, J., Fischer, R.L., Voinnet, O. and Navarro, L. (2013) Dynamics and biological relevance of DNA demethylation in Arabidopsis antibacterial defense. Proceedings of the National Academy of Sciences of the United States of America 110, 2389-2394. Yu, G.-L., Katagiri, F. and Ausubel, F.M. (1993) Arabidopsis mutations at the RPS2 locus result in loss of resistance to Pseudomonas syringae strains expressing the avirulence gene avrRpt2. MOLECULAR PLANT MICROBE INTERACTIONS 6, 434-434. Yu, J., Penaloza-Vázquez, A., Chakrabarty, A.M. and Bender, C.L. (1999) Involvement of the exopolysaccharide alginate in the virulence and epiphytic fitness of Pseudomonas syringae pv. syringae. Molecular Microbiology 33, 712-720. Zemach, A., Kim, M.Y., Hsieh, P.H., Coleman-Derr, D., Eshed-Williams, L., Thao, K., Harmer, S.L. and Zilberman, D. (2013) The Arabidopsis nucleosome remodeler DDM1 allows DNA methyltransferases to access H1-containing heterochromatin. Cell 153, 193205. Zhang, H. and Zhu, J.K. (2012) Active DNA demethylation in plants and animals. Cold Spring Harbor Symposia on Quantitative Biology 77, 161-173. Zhang, X., Dai, Y., Xiong, Y., DeFraia, C., Li, J., Dong, X. and Mou, Z. (2007) Overexpression of Arabidopsis MAP kinase kinase 7 leads to activation of plant basal and systemic acquired resistance. Plant Journal 52, 1066-1079. Zhang, X., Yazaki, J., Sundaresan, A., Cokus, S., Chan, S.W.L., Chen, H., Henderson, I.R., Shinn, P., Pellegrini, M., Jacobsen, S.E. and Ecker, J. (2006) Genome-wide HighResolution Mapping and Functional Analysis of DNA Methylation in Arabidopsis. Cell 126, 1189-1201. Zhang, Z., Chen, H., Huang, X., Xia, R., Zhao, Q., Lai, J., Teng, K., Li, Y., Liang, L. and Du, Q. (2011) BSCTV C2 attenuates the degradation of SAMDC1 to suppress DNA methylation-mediated gene silencing in Arabidopsis. The Plant Cell Online 23, 273288. Zipfel, C., Robatzek, S., Navarro, L., Oakeley, E.J., Jones, J.D.G., Felix, G. and Boller, T. (2004) Bacterial disease resistance in Arabidopsis through flagellin perception. Nature 428, 764-767. Zumaquero, A., Macho, A.P., Rufián, J.S. and Beuzón, C.R. (2010) Analysis of the role of the type III effector inventory of Pseudomonas syringae pv. phaseolicola 1448a in interaction with the plant. Journal of bacteriology 192, 4474-4488. 131 “One of the greatest discoveries a person makes, one of their great surprises, is to find they can do what they were afraid they couldn't do.” ― Henry Ford Resumen de la tesis en español Resumen 1. Pseudomonas syringae Pseudomonas syringae es una bacteria en forma de bacilo, Gram-negativa, hemibiotrófa y con flagelos polares, que provoca una amplia variedad de síntomas en plantas, incluyendo, manchas necróticas y/o cloróticas y agallas. La especie se divide en variantes patógenas (patovares, pv) que difieren en su rango de huéspedes (Peñaloza-Vázquez et al., 2000). Hay más de 50 patovares diferentes descritos, algunas de los cuales se subdividen en razas basándose en el rango de cultivares de la especie huésped que infectan (González et al., 2000; Hirano y Upper, 2000). Pseudomonas syringae sobrevive en las superficies de las hojas de las plantas como una epífita, antes de entrar en el espacio intercelular a través de aberturas naturales como estomas o heridas, para iniciar el proceso de infección (Hirano y Upper, 2000). P. syringae pv. tomate (en adelante Pto) DC3000, la principal estirpe modelo para el estudio de la interacción de P. syringae con el huésped, es el agente causante de la mancha bacteriana en tomate, y también puede causar enfermedad en la planta modelo Arabidopsis thaliana. El genoma de Pto DC3000 (6,5 megabytes) contiene un cromosoma circular y dos plásmidos, que codifican en conjunto 5.763 ORFs (Collmer et al., 2002). La base genética de la patogénesis y la virulencia en P. syringae es compleja e incluye reguladores globales (Hrabak y Willis, 1992; Kitten et al., 1998; Rich et al., 1994), el conjunto de genes hrp, que codifica un sistema de secreción de tipo III (T3SS), así como factores de virulencia, tales como la fitotoxina coronatina, y exopolisacáridos (Bender et al., 1999; Yu et al., 1999). Una vez dentro de su huésped, P. syringae sobrevive y prolifera dentro de los espacios intercelulares, el apoplasto, donde a través de la acción del T3SS introduce un conjunto de proteínas altamente especializados, llamados efectores, a través de la pared en el citosol de la célula huésped. Una vez dentro del citosol, las proteínas efectoras trabajan para suprimir el sistema inmune de la planta, lo que permite el crecimiento del patógeno en el apoplasto (Göhre y Robatzek, 2008). Bacterias mutantes incapaces de introducir efectores en la célula huésped, es decir, mutantes en el T3SS, muestran un crecimiento 135