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Plant immunity: how plants detect the presence of pathogenic microbes and generate the immune response
As a source of nutrients to most species, plants are exposed to many pathogenic microorganisms ranging from bacteria, viruses, fungi, and oomycetes. Depending on how they extract nutrients from plants, pathogenic microorganisms are divided into three categories, namely biotrophs, hemibiotrophs, and necrotrophs. While biotrophs thrive on living tissues by blocking host defenses and sustaining feeding processes, necrotrophs degrade the plant cell-walls using hydrolytic enzymes and feed on dead tissues. Hemibiotrophs exhibit an in-between pattern where they start as biotrophs and then end up killing the plant cells (Glazebrook, 2005).
Plants have developed several complex mechanisms to fight off pathogenic microbes. These mechanisms include constitutive defenses mediated by preformed physical barriers and phytoanticipins, which prevent pathogen entry, and inducible defenses, which are activated by sensing the presence of the pathogen by specialized receptors.
Constitutive defenses
Epidermal cells, which make the outermost cell layer of plants, are overlaid with a waxy cuticle. Then, all plant cells are interlocked in a complex cell wall matrix, which pathogens must navigate through to access the host cells’ plasma membrane (PM) (Ziv et al., 2018). The apoplast, the space between cell walls and the PM, is physiologically unhospitable for microbial pathogens. Indeed, plants constitutively synthesize precursors of phytoanticipins, such as glucosinolates and saponins in the apoplast (Piasecka et al., 2015). Upon detection of pathogens, phytoanticipins are converted to antimicrobial compounds to ward off pathogens (Piasecka et al., 2015). These barriers drastically decrease the number of possible entry points for pathogens. However, some pathogens developed several strategies to overcome the physical barriers of plants. For instance, fungal pathogens employ specialized infection structures, called appressoria, to generate a focused turgor pressure and penetrate the cell wall (Ryder & Talbot, 2015). Bacteria use natural openings such as stomata and hydathodes to penetrate the intercellular space of plants (Huang, 2003). Necrotrophic pathogens, on the other hand, degrade host cell walls by producing a cocktail of cell wall-degrading enzymes (Rodriguez-Moreno et al., 2018; Wilson, 2008), and viruses enter plant cells through wounds (Gergerich & Dolja, 2006).
Inducible defenses
A pathogen that successfully breaches the physical barriers encounters a whole other complex immune system including receptors, signaling components, hormones, and resistance proteins, all contributing to the thickening of cell walls by the secretion of callose/papillae, to the secretion of antimicrobial compounds, and eventually to localized programmed cell death (PCD) aimed at limiting the pathogen to the infected area. All these processes require a coordinated response of the plant and fine-tuned regulations to induce an adequate response.
The inducible immune system of plants has been described as two-layered (Jones & Dangl, 2006). The first layer relies on PM-resident receptor-like kinases (RLKs) and receptor-like proteins (RLPs), which enable the detection of surrounding extracellular pathogens. Pattern-recognition receptors (PRRs), RLKs and RLPs, recognize pathogen-associated molecular patterns (PAMPs), which represent a molecular signature among a class of microbes, including specific proteins, lipopolysaccharides, and pathogen-associated cell wall components commonly found in microbes (Zhang et al., 2010). Upon detecting PAMPs, RLKs and RLPs trigger a pattern-triggered immune response, termed pattern-triggered immunity (PTI) (Jones & Dangl, 2006).
In the second layer, the recognition of microbes occurs in the intracellular space by specific receptors, commonly known as resistance (R) proteins, and was developed against more adapted pathogens that can secrete virulence factors, also known as effectors inside the host’s cells. Although effectors are initially intended to suppress PTI (Toruño et al., 2016), plants can sense their presence, through R proteins, and induce an immune response. This second effector-mediated immune response, termed effector-triggered immunity (ETI), was developed by repeated exposure to the above-described virulent pathogens (Jones & Dangl, 2006). ETI and PTI share several signaling components and responses; however, the former is more intense and long-lasting (Tsuda & Katagiri, 2010).
Although previously described as independent, PTI and ETI share several responses and signaling pathways (Tsuda & Katagiri, 2010). In addition, recent studies indicate that the components of the two layers of immunity cooperate to initiate an efficient immune response (more detail will be provided in section 1.2.6) (Yuan et al., 2021).
PATTERN-TRIGGERED IMMUNITY (PTI)
PRRs: the main players of PTI
As stated above, PRRs recognize PAMPs, which represent a molecular signature among a class of microbes (Yu et al., 2017). PRRs can be RLKs or RLPs depending on the nature of their intracellular domain, which mediates downstream signal transduction (Macho & Zipfel, 2014; Zipfel, 2008). Additionally, each PRR contains a specific ligand-binding extracellular domain (Wan et al., 2019). Based on the structure of the extracellular domain, RLPs and RLKs have been further classified into several types, including leucine-rich repeat (LRR) receptors, lysine motifs (LysM) receptors, lectin-domain receptors, and others (Wan et al., 2019). Examples of LRR receptors include the RLK flagellin-sensing 2 (FLS2), which binds an N-terminal 22-amino acid epitope of bacterial flagellin (flg22) (Chinchilla et al., 2006), and the RLP, RLP23, which recognizes the Necrosis and ethylene-inducing peptide 1-like protein (NLP) 20 (nlp20), NLPs are found in a wide range of bacteria, fungi, and oomycetes (Albert et al., 2015). Examples of LysM extracellular domain receptors include the chitin sensors chitin-elicitor receptor kinase 1 (CERK1) and the lysin motif receptor kinase 5 (LYK5) (Cao et al., 2014; Liu et al., 2012). Upon detecting the related PAMPs, PRRs transduce the signal from the cell surface to the intracellular compartments to generate a PTI. PTI can also be induced and amplified by damage-associated molecular patterns (DAMPs) produced by the plant as a result of pathogen-induced cell wall breakdown. DAMPs are detected by certain PRRs, which trigger additional downstream responses (Hou et al., 2019). For example, pectin fragments or oligogalacturonides (OGs) derived from the degradation of cell walls are recognized by the PRR wall-associated kinase 1 (WAK1), which subsequently activates a PTI (Brutus et al., 2010). The DAMP Plant elicitor peptide 1 (Pep1), a 23-amino acid peptide generated from the precursor protein PROPEP1, is recognized by the (LRR) RLK perception of the Arabidopsis danger signal peptide 1 (PEPR1), which subsequently induces defense responses (Huffaker et al., 2006; Krol et al., 2010).
Signaling downstream of PRRs
Upon PAMP binding, RLKs and RLPs dimerize or associate with other receptors such as somatic embryogenesis receptor kinases (SERKs) and activate downstream receptor-like cytoplasmic kinases (RLCKs) to trigger downstream responses (Macho & Zipfel, 2014). For example, the chitin receptor CERK1 forms a complex with ligand-binding receptor LYK5 and activates RLCK VII proteins to activate downstream signaling (Rao et al., 2018).
A well-documented PRR example is the perception of bacterial flagellin by the receptor FLS2 (Chinchilla et al., 2006). The flg22–FLS2 ligand-receptor interaction has been used as a model to decipher early signaling events occurring downstream of PAMP perception.
In the absence of flg22, FLS2 is associated with the receptor-like cytoplasmic kinase (RLCK) botrytis-induced kinase 1 (BIK1) (Lu et al., 2010). Immediately upon flg22 perception, FLS2 forms a PRR complex with brassinosteroid insensitive 1 (BRI1)-associated kinase 1 (BAK1/SERK3) (Chinchilla et al., 2007). Following that, BAK1 phosphorylates BIK1, which in turn phosphorylates FLS2 and BAK1 (Lu et al., 2010). This results in the dissociation of BIK1 from the FLS2-BAK1 PRR complex and enables BIK1 to trigger the generation of reactive oxygen species (ROS) via phosphorylation of the PM nicotinamide adenine dinucleotide phosphate (NADPH) oxidase known as respiratory burst oxidase homolog D (RBOHD) (figure 1.1) (Kadota et al., 2014; Li et al., 2014).
Signaling downstream of PRRs involves several intermediates, the earliest being Ca2+ and ROS (Couto & Zipfel, 2016). Following that, MAPKs and CDPKs transduce the signal to multiple intracellular defense responses, including a transcriptional reprogramming which is crucial for launching a robust and effective defense response (Tena et al., 2011) (figure 1.1). Several other components are involved in signaling during PTI and are discussed in detail by Bigeard et al. (2015) The recognition of PAMPs or DAMPs by their cognate PRRs results in transcriptional reprogramming of a set of common genes with distinct temporal dynamics. In fact, numerous genes are commonly increased by treatment with flg22 or fungal chitin or with OGs (Denoux et al., 2008). Thus, it is likely that various MAMPs/DAMPs trigger similar signaling pathways that result in similar transcriptional modifications with different dynamics and amplitude (Cole & Tringe, 2021).
Calcium Ca2+
Almost immediately after flg22 perception, a Ca2+ influx occurs in the cytosol (Yuan et al., 2017). BIK1 operates as an effector kinase in several PRR complexes and is necessary for flg22-induced cytosolic Ca2+ increase and stomatal closure (Couto & Zipfel, 2016; Li et al., 2014). Recent investigations have demonstrated that BIK1 directly activates Ca2+ channels during PTI. Upon flg22 treatment, BIK1 phosphorylates the cyclic nucleotide-gated channel (CNGC) CNGC4 to activate the calcium channel formed by CNGC4 and CNGC2 (Tian et al., 2019). The calcium-permeable-channel OSCA1.3 is also activated by BIK1 in a kinase activity-dependent way to initiate a Ca2+ influx (Thor et al., 2020). Additionally, it was demonstrated that OSCA1.3 and its phosphorylation by BIK1 are critical for flg22-induced stomatal closure (Thor et al., 2020). As a result of these findings, BIK1 appears to be the link between pathogen sensing by PRRs and calcium signaling. The increase in cytosolic Ca2+ concentration is associated with PM depolarization and extracellular alkalization by an influx of H+ and efflux of Cl−, NO3−, and K+ (Jeworutzki et al., 2010). Calcium influx activates many calcium sensors, including CDPKs, calmodulins (CaMs), calcineurin B-like (CBls), and calcium- and calmodulin-dependent protein kinases (CCaMKs) (Boudsocq & Sheen, 2013). These sensors trigger various reactions, including gene expression and enzyme activity (Boudsocq & Sheen, 2013). CDPKs promote defenses in response to a range of PAMPs and DAMPs, including flg22 and OGs, mainly through phosphorylation of substrates such as transcription factors (TFs) and proteins involved in hormone processes (Yip Delormel & Boudsocq, 2019). Notably, CPK4, CPK5, CPK6, and CPK11 phosphorylate RBOHD to induce ROS accumulation in response to flg22 recognition (Boudsocq et al., 2010; Dubiella et al., 2013; Gao et al., 2013; Kadota et al., 2014). The cpk5 cpk6 double mutant and the cpk5 cpk6 cpk11 triple mutant show a compromised immune response to Pseudomonas syringae pv. tomato (Pst) DC3000 (Boudsocq et al., 2010). Conversely, transgenic lines overexpressing CPK5 (P35::CPK5) showed enhanced resistance to Pst DC3000 (Dubiella et al., 2013). Interestingly, a recent study discovered that the phosphorylation of the chitin-binding PRRs LYK5 and LYK6 by CPK5 and CPK6 is required to activate immune responses downstream chitin perception (Huang et al., 2020). This work demonstrates that CPK5 and CPK6 are engaged in early signaling, at the PRR level, during PTI.
ROS
ROS regulate various physiological responses in plants (Manna et al., 2019). Although ROS are produced in several subcellular organelles, including chloroplasts, mitochondria, and peroxisomes, most of the research on PTI-induced ROS was focused on ROS produced by the plasma membrane RBOHs (Janků et al., 2019). Besides being phosphorylated by BIK1 and CDPKs, RBOHD undergoes direct regulations by Ca2+. Indeed, Ca2+ ions bind to the N-terminal region of RBOHD and induce a conformational change on its EF-hand motifs (Ogasawara et al., 2008). Phosphorylation by BIK1 and CDPKs and Ca2+ regulations on RBOHD are required for its activity (Ogasawara et al., 2008).
Few minutes after PAMP perception, a ROS burst mediated by RBOHD is detected after approximately 2 minutes (min) and reaches a peak after about 10 min (Nühse et al., 2007). RBOHD produces membrane-impermeable superoxide O2.− ions in the apoplast. O2. − is then dismutated into membrane-permeable hydrogen peroxide, H2O2, which can be relocated to the cytosol and organelles to trigger cellular responses (Suzuki et al., 2011) (figure 1.1). ROS accumulation in the cytosol leads to an altered cell’s redox state, which is believed to trigger the oxidation of components of hormonal signaling pathways, thus modifying their activity (Noctor et al., 2018). As an example, the modified redox state of the cell during pathogen infection contributes to the activation of non-expresser of pathogenesis-related (PR) genes 1 (NPR1), a key protein in salicylic acid (SA) signaling (Mou et al., 2003). In response to PAMPs, RBOHD-dependent ROS generation induces callose deposition to reinforce cell walls and stomatal closure to prevent further pathogen entrance (Kadota et al., 2014; Liu & He, 2016).
Table of contents :
CHAPTER I – INTRODUCTION
1. Plant immunity: how plants detect the presence of pathogenic microbes and generate the immune response
1.1. PATTERN-TRIGGERED IMMUNITY (PTI)
1.1.1. PRRs: the main players of PTI
1.1.2. Signaling downstream of PRRs
1.2. EFFECTOR-TRIGGERED IMMUNITY (ETI)
1.2.1. ETI, the second layer of defense against more adapted pathogens
1.2.2. Resistance proteins: the main players of ETI
1.2.3. The guard and decoy model of effector perception by NLRs
1.2.4. Regulations of R proteins
1.2.5. Regulation of NLRs downstream signaling
1.2.6. ETI outputs: a continuity of PTI responses?
2. Mitogen-activated Protein Kinases (MAPKs): hubs with an essential role in immune signaling
2.1. MAPKs in Arabidopsis
2.1.1. MAPKKKs
2.1.2. MAPKKs
2.1.3. MAPKs
2.2. Mechanisms regulating MAPK modules specificity, substrate specificity, and signaling
2.2.1. Mechanisms regulating MAPK module specificity
2.2.2. Mechanisms regulating MAPK substrate specificity
2.2.3. Mechanisms regulating MAPK signaling
2.3. The role of MPK3, MPK4, and MPK6 in immunity
2.3.1. MAPKKK3/MAPKKK5-MKK4/MKK5-MPK6/MPK3 pathway
2.3.2. MEKK1-MKK1/MKK2-MPK4 pathway
2.3.3. MAPKs are targets of pathogenic effectors
2.3.4. MAPKs in ETI
3. The role of hormones in immunity
3.1. SA pathway
3.1.1. SA biosynthesis
3.1.2. SA metabolism
3.1.3. Regulation of SA biosynthesis
3.1.4. Signaling downstream of SA
3.1.5. SAR
3.2. JA pathway
3.2.1. JA biosynthesis
3.2.2. JA perception and downstream signaling
3.2.3. Regulation of the JA pathway
3.3. Ethylene pathway
3.3.1. ET biosynthesis
3.3.2. ET perception and signaling
3.3.3. ET pathway regulation
3.4. Crosstalk between defense hormones
3.4.1. JA-ET
3.4.2. JA-SA
4. The importance of membrane trafficking in plant immunity
4.1. Overview of the trafficking pathways in plants
4.1.1. The secretory and vacuolar pathway
4.1.2. The endocytic pathway
4.2. The involvement of membrane trafficking in plant immunity
4.2.1. The importance of the secretory machinery in plant immunity
4.2.2. Unconventional secretory pathways in plant immunity
4.2.3. The role of the endocytic pathway in plant immunity
4.3. SNAREs: Very conserved proteins and the main executors of membrane fusion processes in the endomembrane system of plants
4.3.2. SNAREs are involved in plant immunity: the case of SYP121 and its interacting SNARE partners
4.3.3. SNAP33 is a SNAP25-like gene with an intriguing trait
5. Objectives of my Ph.D.
CHAPTER II – RESULTS
1. Characterization of the lesion-mimic phenotype of snap33 mutants
1.1. Isolation of novel snap33 mutants
1.2. snap33 knock-out mutants display constitutive cell death and H2O2 accumulation
1.3. MPK3, MPK4, and MPK6 activation upon flg22 treatment is more intense in the snap33 mutants
1.4. High temperatures partially suppress the dwarf phenotype of snap33
1.5. Transcriptomic analyses of the snap33-1 mutant confirm that SNAP33 mutation results in constitutive expression of defense-related genes
1.5.1. Experimental design
1.5.2. Analyses of the differentially expressed genes
1.6. snap33 ‘s phenotype is related to constitutive defense signaling
1.6.1. The SA, JA, and ET marker genes are up-regulated in the snap33 mutants
1.6.2. SA, JA, and ET levels are higher in the snap33-1 mutant
1.6.3. snap33-1’s phenotype is partially reverted by mutations in the JA and SA pathways
1.6.4. R protein signaling is constitutively induced in the snap33-1 mutant
1.6.5. snap33-1’s phenotype is partially dependent on CPK5 and TN2
1.7. Discussion
1.7.1. The phenotype of snap33 resembles that of several lesion-mimic mutants
1.7.2. The SA sector is dominant in the snap33 mutant
1.7.3. snap33 mutants mimic ETI responses
1.7.4. Is the snap33 phenotype only related to auto-immunity?
1.8. Conclusion and perspectives
2. Studying the relationship between SNAP33 and the MEKK1-MKK2-MPK4 MAPK module
2.1. SNAP33 PTMs and interactions
2.1.1. SNAP33 PTMs
2.1.2. SNAP33 interactions
2.2. Is SNAP33 an interacting partner of MEKK1-MKK2-MPK4 MAPK module?
2.2.1. SNAP33 interacts with MEKK1, MKK2, and MPK4 in vivo by BiFC
2.2.2. SNAP33 does not interact with MEKK1, MKK2, and MPK4 by Y2H
2.2.3. SNAP33 does not interact with MKK2 and MPK4 by in vitro pull-down assays
2.2.4. SNAP33 does not interact with MKK2 and MPK4 by co-immunoprecipitation assays in vivo
2.3. Is SNAP33 a substrate of the MEKK1-MKK2-MPK4 MAPK module?
2.3.1. Kinase assays using the in vitro produced recombinant proteins
2.3.2. Kinase assay using the in vivo purified MPK4 and MKK2
2.4. Is there a genetic relationship between SNAP33 and the MAPK module?
2.4.1. snap33-1 phenotype is not suppressed by the summ2-8 mutation
2.4.2. snap33-1 phenotype is not suppressed by the smn1 mutation
2.5. Discussion
2.5.1. Is SNAP33 an interacting partner of the MAPK module?
2.5.2. Is SNAP33 a substrate of MPK3, MPK4, and MPK6?
2.5.3. SNAP33 is not involved in the same pathway as that of the MEKK1-MKK2-MPK4 MAPK module
CHAPTER III – GENERAL CONCLUSIONS AND PERSPECTIVES
1. Summary of my results
2. Perspectives
CHAPTER IV – MATERIALS AND METHODS
1. Materials
1.1. Plant material
1.2. AGI number of the main genes
1.3. Bacterial strains
1.4. Yeast strains
1.5. Growth media
1.5.1. Plant growth media
1.5.2. Bacteria and yeast growth media
1.6. Vectors
1.7. Primers
1.7.1. Cloning primers
1.7.2. Genotyping primers
1.7.3. Quantitative PCR primers
1.7.4. RT PCR primers
1.8. Antibiotics
1.9. Antibodies
1.9.1. Primary antibodies
1.9.2. Secondary antibodies
2. Methods
2.1. Plant methods
2.1.1. Plant growth
2.1.2. Hormone quantification
2.1.3. BiFC experiments
2.1.4. Stainings
2.2. Protoplast methods
2.2.1. Protoplast’s isolation
2.2.2. Protoplast’s transformation
2.3. Bacteria methods
2.3.1. Bacterial transformation
2.3.2. Agrobacterium transformation
2.4. Yeast methods
2.4.1. Yeast transformation
2.4.2. Yeast two-hybrid (Y2H) analysis for protein-protein interaction
2.5. DNA methods
2.5.1. Plasmid DNA isolation
2.5.2. Plant DNA extraction for genotyping
2.5.3. PCRs
2.5.4. dCAPS genotyping
2.5.5. Cloning PCRs
2.5.6. DNA migration
2.5.7. DNA digestion
2.5.8. DNA sequencing
2.5.9. Cloning
2.6. RNA methods
2.6.1. RNA isolation
2.6.2. cDNA synthesis
2.6.3. Quantitative PCRs
2.6.4. Transcriptomic analyses
2.7. Protein methods
2.7.1. Native protein extraction
2.7.2. Bradford protein dosage
2.7.3. Recombinant protein expression and purification
2.7.4. Co-immunoprecipitation assays for protein-protein interactions
2.7.5. Pull-down assays
2.7.6. Kinase assays
2.7.7. SDS- PAGE and immunoblotting
2.8. Plotting, data interpretation and statistical analyses
REFERENCES
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