Kenichi Tsuda

Comparing signaling mechanisms engaged in pattern-triggered and effector-triggered immunity

Plants employ two modes of their innate immune system to resist pathogen infection. The first mode of immunity is referred to as pattern-triggered immunity (PTI) that is triggered by molecular patterns common to many types of microbes. The second mode is triggered by recognition of pathogen effectors and is called as effector-triggered immunity (ETI). At least some cases of PTI and ETI extensively share downstream signaling machinery, that is, PTI and ETI appear to be mediated by an integrated signaling network. However, activated immune responses in ETI are more prolonged and robust than those in PTI. Furthermore, network analysis has revealed that synergistic relationships among the signaling sectors are evident in PTI, which may amplify the signal, whereas compensatory relationships among the sectors dominate in ETI, explaining the robustness of ETI against genetic and pathogenic perturbations. Thus, plants seem to use a common signaling network differently in PTI and ETI.

Network properties of robust immunity in plants.

Two modes of plant immunity against biotrophic pathogens, Effector Triggered Immunity (ETI) and Pattern-Triggered Immunity (PTI), are triggered by recognition of pathogen effectors and Microbe-Associated Molecular Patterns (MAMPs), respectively. Although the jasmonic acid (JA)/ethylene (ET) and salicylic acid (SA) signaling sectors are generally antagonistic and important for immunity against necrotrophic and biotrophic pathogens, respectively, their precise roles and interactions in ETI and PTI have not been clear. We constructed an Arabidopsis dde2/ein2/pad4/sid2-quadruple mutant. DDE2, EIN2, and SID2 are essential components of the JA, ET, and SA sectors, respectively. The pad4 mutation affects the SA sector and a poorly characterized sector. Although the ETI triggered by the bacterial effector AvrRpt2 (AvrRpt2-ETI) and the PTI triggered by the bacterial MAMP flg22 (flg22-PTI) were largely intact in plants with mutations in any one of these genes, they were mostly abolished in the quadruple mutant. For the purposes of this study, AvrRpt2-ETI and flg22-PTI were measured as relative growth of Pseudomonas syringae bacteria within leaves. Immunity to the necrotrophic fungal pathogen Alternaria brassicicola was also severely compromised in the quadruple mutant. Quantitative measurements of the immunity levels in all combinatorial mutants and wild type allowed us to estimate the effects of the wild-type genes and their interactions on the immunity by fitting a mixed general linear model. This signaling allocation analysis showed that, contrary to current ideas, each of the JA, ET, and SA signaling sectors can positively contribute to immunity against both biotrophic and necrotrophic pathogens. The analysis also revealed that while flg22-PTI and AvrRpt2-ETI use a highly overlapping signaling network, the way they use the common network is very different: synergistic relationships among the signaling sectors are evident in PTI, which may amplify the signal; compensatory relationships among the sectors dominate in ETI, explaining the robustness of ETI against genetic and pathogenic perturbations.

Arabidopsis lysin-motif proteins LYM1 LYM3 CERK1 mediate bacterial peptidoglycan sensing and immunity to bacterial infection.

Recognition of microbial patterns by host pattern recognition receptors is a key step in immune activation in multicellular eukaryotes. Peptidoglycans (PGNs) are major components of bacterial cell walls that possess immunity-stimulating activities in metazoans and plants. Here we show that PGN sensing and immunity to bacterial infection in Arabidopsis thaliana requires three lysin-motif (LysM) domain proteins. LYM1 and LYM3 are plasma membrane proteins that physically interact with PGNs and mediate Arabidopsis sensitivity to structurally different PGNs from Gram-negative and Gram-positive bacteria. lym1 and lym3 mutants lack PGN-induced changes in transcriptome activity patterns, but respond to fungus-derived chitin, a pattern structurally related to PGNs, in a wild-type manner. Notably, lym1, lym3, and lym3 lym1 mutant genotypes exhibit supersusceptibility to infection with virulent Pseudomonas syringae pathovar tomato DC3000. Defects in basal immunity in lym3 lym1 double mutants resemble those observed in lym1 and lym3 single mutants, suggesting that both proteins are part of the same recognition system. We further show that deletion of CERK1, a LysM receptor kinase that had previously been implicated in chitin perception and immunity to fungal infection in Arabidopsis, phenocopies defects observed in lym1 and lym3 mutants, such as peptidoglycan insensitivity and enhanced susceptibility to bacterial infection. Altogether, our findings suggest that plants share with metazoans the ability to recognize bacterial PGNs. However, as Arabidopsis LysM domain proteins LYM1, LYM3, and CERK1 form a PGN recognition system that is unrelated to metazoan PGN receptors, we propose that lineage-specific PGN perception systems have arisen through convergent evolution.

Effector-Triggered Immunity: From Pathogen Perception to Robust Defense

In plant innate immunity, individual cells have the capacity to sense and respond to pathogen attack. Intracellular recognition mechanisms have evolved to intercept perturbations by pathogen virulence factors (effectors) early in host infection and convert it to rapid defense. One key to resistance success is a polymorphic family of intracellular nucleotide-binding/leucine-rich-repeat (NLR) receptors that detect effector interference in different parts of the cell. Effector-activated NLRs connect, in various ways, to a conserved basal resistance network in order to transcriptionally boost defense programs. Effector-triggered immunity displays remarkable robustness against pathogen disturbance, in part by employing compensatory mechanisms within the defense network. Also, the mobility of some NLRs and coordination of resistance pathways across cell compartments provides flexibility to fine-tune immune outputs. Furthermore, a number of NLRs function close to the nuclear chromatin by balancing actions of defense-repressing and defense-activating transcription factors to program cells dynamically for effective disease resistance.

Arabidopsis CaM Binding Protein CBP60g Contributes to MAMP-Induced SA Accumulation and Is Involved in Disease Resistance against Pseudomonas syringae

Salicylic acid (SA)-induced defense responses are important factors during effector triggered immunity and microbe-associated molecular pattern (MAMP)-induced immunity in plants. This article presents evidence that a member of the Arabidopsis CBP60 gene family, CBP60g, contributes to MAMP-triggered SA accumulation. CBP60g is inducible by both pathogen and MAMP treatments. Pseudomonas syringae growth is enhanced in cbp60g mutants. Expression profiles of a cbp60g mutant after MAMP treatment are similar to those of sid2 and pad4, suggesting a defect in SA signaling. Accordingly, cbp60g mutants accumulate less SA when treated with the MAMP flg22 or a P. syringae hrcC strain that activates MAMP signaling. MAMP-induced production of reactive oxygen species and callose deposition are unaffected in cbp60g mutants. CBP60g is a calmodulin-binding protein with a calmodulin-binding domain located near the N-terminus. Calmodulin binding is dependent on Ca(2+). Mutations in CBP60g that abolish calmodulin binding prevent complementation of the SA production and bacterial growth defects of cbp60g mutants, indicating that calmodulin binding is essential for the function of CBP60g in defense signaling. These studies show that CBP60g constitutes a Ca(2+) link between MAMP recognition and SA accumulation that is important for resistance to P. syringae.

Understanding the Plant Immune System

Plant immunity is controlled by a complex signaling network. Here, we discuss how the complexity of the network affects our views and approaches in studying the plant immune network. We propose that the mode of plant immunity is mainly determined by how the shared signaling network is used rather than by a signaling machinery specific to each mode, that balancing the robustness of immunity and the negative effect of immunity on plant fitness is a key driver in evolution of the immune network, that comparisons of plant mutant to wild-type phenotypes may not be very effective in elucidating the underlying signaling mechanisms, and that mechanistic understanding of the network can improve our ability to predict the performance of immunity.

Network Modeling Reveals Prevalent Negative Regulatory Relationships between Signaling Sectors in Arabidopsis Immune Signaling

Biological signaling processes may be mediated by complex networks in which network components and network sectors interact with each other in complex ways. Studies of complex networks benefit from approaches in which the roles of individual components are considered in the context of the network. The plant immune signaling network, which controls inducible responses to pathogen attack, is such a complex network. We studied the Arabidopsis immune signaling network upon challenge with a strain of the bacterial pathogen Pseudomonas syringae expressing the effector protein AvrRpt2 (Pto DC3000 AvrRpt2). This bacterial strain feeds multiple inputs into the signaling network, allowing many parts of the network to be activated at once. mRNA profiles for 571 immune response genes of 22 Arabidopsis immunity mutants and wild type were collected 6 hours after inoculation with Pto DC3000 AvrRpt2. The mRNA profiles were analyzed as detailed descriptions of changes in the network state resulting from the genetic perturbations. Regulatory relationships among the genes corresponding to the mutations were inferred by recursively applying a non-linear dimensionality reduction procedure to the mRNA profile data. The resulting static network model accurately predicted 23 of 25 regulatory relationships reported in the literature, suggesting that predictions of novel regulatory relationships are also accurate. The network model revealed two striking features: (i) the components of the network are highly interconnected; and (ii) negative regulatory relationships are common between signaling sectors. Complex regulatory relationships, including a novel negative regulatory relationship between the early microbe-associated molecular pattern-triggered signaling sectors and the salicylic acid sector, were further validated. We propose that prevalent negative regulatory relationships among the signaling sectors make the plant immune signaling network a “sector-switching” network, which effectively balances two apparently conflicting demands, robustness against pathogenic perturbations and moderation of negative impacts of immune responses on plant fitness.

Transcriptional networks in plant immunity

Next to numerous abiotic stresses, plants are constantly exposed to a variety of pathogens within their environment. Thus, their ability to survive and prosper during the course of evolution was strongly dependent on adapting efficient strategies to perceive and to respond to such potential threats. It is therefore not surprising that modern plants have a highly sophisticated immune repertoire consisting of diverse signal perception and intracellular signaling pathways. This signaling network is intricate and deeply interconnected, probably reflecting the diverse lifestyles and infection strategies used by the multitude of invading phytopathogens. Moreover it allows signal communication between developmental and defense programs thereby ensuring that plant growth and fitness are not significantly retarded. How plants integrate and prioritize the incoming signals and how this information is transduced to enable appropriate immune responses is currently a major research area. An important finding has been that pathogen-triggered cellular responses involve massive transcriptional reprogramming within the host. Additional key observations emerging from such studies are that transcription factors (TFs) are often sites of signal convergence and that signal-regulated TFs act in concert with other context-specific TFs and transcriptional co-regulators to establish sensory transcription regulatory networks required for plant immunity.

Layered pattern receptor signaling via ethylene and endogenous elicitor peptides during Arabidopsis immunity to bacterial infection

Recognition of molecular patterns characteristic of microbes or altered-self leads to immune activation in multicellular eukaryotes. In Arabidopsis thaliana, the leucine-rich-repeat receptor kinases FLAGELLIN-SENSING2 (FLS2) and EF-TU RECEPTOR (EFR) recognize bacterial flagellin and elongation factor EF-Tu (and their elicitor-active epitopes flg22 and elf18), respectively. Likewise, PEP1 RECEPTOR1 (PEPR1) and PEPR2 recognize the elicitor-active Pep epitopes conserved in Arabidopsis ELICITOR PEPTIDE PRECURSORs (PROPEPs). Here we reveal that loss of ETHYLENE-INSENSITIVE2 (EIN2), a master signaling regulator of the phytohormone ethylene (ET), lowers sensitivity to both elf18 and flg22 in different defense-related outputs. Remarkably, in contrast to a large decrease in FLS2 expression, EFR expression and receptor accumulation remain unaffected in ein2 plants. Genome-wide transcriptome profiling has uncovered an inventory of EIN2-dependent and EFR-regulated genes. This dataset highlights important aspects of how ET modulates EFR-triggered immunity: the potentiation of salicylate-based immunity and the repression of a jasmonate-related branch. EFR requires ET signaling components for PROPEP2 activation but not for PROPEP3 activation, pointing to both ET-dependent and -independent engagement of the PEPR pathway during EFR-triggered immunity. Moreover, PEPR activation compensates the ein2 defects for a subset of EFR-regulated genes. Accordingly, ein2 pepr1 pepr2 plants exhibit additive defects in EFR-triggered antibacterial immunity, compared with ein2 or pepr1 pepr2 plants. Our findings suggest that the PEPR pathway not only mediates ET signaling but also compensates for its absence in enhancing plant immunity.

Dual Regulation of Gene Expression Mediated by Extended MAPK Activation and Salicylic Acid Contributes to Robust Innate Immunity in Arabidopsis thaliana

Network robustness is a crucial property of the plant immune signaling network because pathogens are under a strong selection pressure to perturb plant network components to dampen plant immune responses. Nevertheless, modulation of network robustness is an area of network biology that has rarely been explored. While two modes of plant immunity, Effector-Triggered Immunity (ETI) and Pattern-Triggered Immunity (PTI), extensively share signaling machinery, the network output is much more robust against perturbations during ETI than PTI, suggesting modulation of network robustness. Here, we report a molecular mechanism underlying the modulation of the network robustness in Arabidopsis thaliana. The salicylic acid (SA) signaling sector regulates a major portion of the plant immune response and is important in immunity against biotrophic and hemibiotrophic pathogens. In Arabidopsis, SA signaling was required for the proper regulation of the vast majority of SA-responsive genes during PTI. However, during ETI, regulation of most SA-responsive genes, including the canonical SA marker gene PR1, could be controlled by SA-independent mechanisms as well as by SA. The activation of the two immune-related MAPKs, MPK3 and MPK6, persisted for several hours during ETI but less than one hour during PTI. Sustained MAPK activation was sufficient to confer SA-independent regulation of most SA-responsive genes. Furthermore, the MPK3 and SA signaling sectors were compensatory to each other for inhibition of bacterial growth as well as for PR1 expression during ETI. These results indicate that the duration of the MAPK activation is a critical determinant for modulation of robustness of the immune signaling network. Our findings with the plant immune signaling network imply that the robustness level of a biological network can be modulated by the activities of network components.