Thirty years of resistance: Zig-zag through the plant immune system

Abstract

Understanding the plant immune system is crucial for using genetics to protect crops from diseases. Plants resist pathogens via a two-tiered innate immune detection-and-response system. The first plant Resistance (R) gene was cloned in 1992 . Since then, many cell-surface pattern recognition receptors (PRRs) have been identified, and R genes that encode intracellular nucleotide-binding leucine-rich repeat receptors (NLRs) have been cloned. Here, we provide a list of characterized PRRs and NLRs. In addition to immune receptors, many components of immune signaling networks were discovered over the last 30 years. We review the signaling pathways, physiological responses, and molecular regulation of both PRR- and NLR-mediated immunity. Recent studies have reinforced the importance of interactions between the two immune systems. We provide an overview of interactions between PRR- and NLR-mediated immunity, highlighting challenges and perspectives for future research.

Figure 1

Nomenclatures in plant immunity and the evolution of plant immune receptors. A, Terminology for plant immune responses. Tabular summary of the different terms used to describe plant immune responses. Definitions, advantages, and disadvantages for each of these are included. B, Number of LRR–RLKs, LRR–RLPs, and NLRs in different plant species. Phylogenetic tree illustrating different plant species with the corresponding numbers of LRR–RLKs, LRR–RLK XII (class or subgroup XII), LRR–RLPs, and NLRs. Red heatmap indicates the number of LRR–RLK XIIs, purple heatmap indicates the number of LRR–RLPs, and blue heatmap indicates the number of NLRs. The phylogenetic tree was generated using phyloT (https://phylot.biobyte.de/) based on the NCBI taxonomy database and visualized by iTOL (https://itol.embl.de/). LRR–RLK data were obtained from Dufayard et al. (2017), LRR–RLP data were obtained from Ngou et al. (2022), and NLR data were obtained from Baggs et al. (2020).

Figure 2

PRRs involved in plant immunity. Characterized PRRs with known elicitors from (A) bacteria, (B) fungi, (C) oomycetes, (D) self-molecules, (E) parasitic plants, (F) viruses, and (G) herbivores. H, PRR co-receptors. Abbreviations for plant species: A. thaliana, At; S. lycopersicum, Sl; O. sativa, Os; N. benthamiana, Nb; L. japonicus, Lj; B. napus, Bn; M. truncatula, Mt; V. vinifera, Vv; L. japonicus, Lj; P. sativum, Ps; T. aestivum, Ta; S. microdontum, Sm; P. japonicum, Pj; V. unguiculata, Vu. Abbreviation for pathogens: F. oxysporum, Fo; P. parasitica, Pp. Number of LRR repeats in the LRR–RLKs and LRR–RLPs were predicted by phytoLRR (Chen, 2021). The full name of these PRR genes can be found in Supplemental Data Set 1.

Figure 3

NLRs involved in plant immunity. Characterized NLRs with known effectors from (A) bacteria, (B) fungi, (C) oomycetes, (D) self-molecules, (E) parasitic plants, (F) viruses, (G) herbivores, and (H) Helper NLRs. Abbreviations for plant species: G. max, Gm; H. vulgare, Hv; C. annuum, Ca; Nicotiana attenuate, Niatt; N. tabacum, Nitab; Nicotiana tomentosiformis, Ntom; S. tuberosum, St; Z. mays, Zm; C. chacoense, Cch; C. melo, Cm; L. usitatissimum, Lu; P. vulgaris, Pv; Triticum monococcum, Tm; S. cereale, Sc; S. bicolor, Sb; S. americanum, Sa; S. bulbocastanum, Sbu; S. chacoense, Sch; S. demissum, Sd; Solanum hjertingii, Sh; Solanum mochicense, Smo; Solanum nigrescens, Ssn; Solanum × edinense, Sxe; S. stoloniferum, Sst; S. venturi, Sv; C. baccatum, Cb; C. chinense, Cchi; C. frutescens, Cf; N. sylvestris, Ns; S. acaule, Sac; N. glutinosa, Ng; A. tauschii, Ata; P. cerasifera, Pc. Number of LRR repeats in the NLRs were predicted by LRRpredictor (Martin et al., 2020a). The full list of NLRs can be found in Supplemental Data Set 2.

Figure 4

Plant immune signaling pathways. A, PRR signaling pathway. Ligand perception by PRRs activates multiple kinases, which leads to calcium influx to the cytosol, ROS production, transcriptional reprogramming, and callose deposition. B, Singleton NLR signaling pathway. The ZAR1/RKS1 heterodimer detects the effector AvrAC via association with uridylylated PBL2 by AvrAC. This leads to the activation and oligomerization of ZAR1. The ZAR1 resistosome localizes to the PM and triggers calcium influx, which leads to the HR and cell rupture. C, Helper-NLR-dependent sensor NLR signaling pathway. Recognition of ATR1 by the TNL RPP1 leads to oligomerization and the induced proximity of TIR domains. The TIR domain exhibits NADase activity and produces v-cADPR, which might activate EP-proteins and the helper NLRs (RNLs). Following TNL activation, EP-proteins and RNLs associate with each other and activate downstream immune responses, likely via cation channel activity from the helper NLRs. Timeline on the right indicates the order and duration of each signaling event following ligand/effector perception. Numbers indicate the corresponding signaling events in the figure on the left. Note that the activation of ETI is usually preceded by PTI activation, and the strength and duration of each event vary and are dependent on the PRRs/NLRs that are activated.

Figure 5

Signaling components and physiological responses activated by different modes of action of immune receptors. (Left) Tabular summary of signaling components and physiological responses activated by RLKs, RLPs, CNLs, TNLs, and coactivation of PRRs and NLRs. Green (weak or strong activation) and white (no activation) shading represent confirmed responses from publications. Gray shading indicates predicted responses. Purple shading represents unclear responses that cannot be predicted. Asterisks indicate inoculation with the bacterial pathogen P. syringae pv. maculicola (Psm) leads to NHP accumulation (Wang et al., 2018c; Liu et al., 2020). (Right) PRR and NLR signaling network. Activation of PRRs (red) and NLRs (blue) lead to the activation of downstream signaling components (orange) and physiological responses (yellow), which result in resistance against pathogens (pink). Note that the activation of physiological responses can vary between immune receptors and are dependent on specific PRRs/NLRs.

Figure 6

Regulation and suppression of immunity by plant proteins and pathogen-derived effectors. (Left; red shading) regulation of the PRR signaling pathway by host proteins. Protein abundance and PTMs of PRRs and PRR signaling components are tightly regulated. (Middle; yellow shading) suppression of immunity by pathogen effectors. Many identified effectors suppress PTI via multiple mechanisms. Very few effectors that target the NLR signaling pathway have been identified so far. (Right; blue shading) regulation of the NLR signaling pathway by host proteins. Both the transcript and protein level of NLRs are tightly regulated by multiple processes. The regulation of signaling events post-NLR activation has not been well characterized. Numbers indicate the corresponding mechanisms of immune regulation.

Figure 7

Interactions between PRR- and NLR-mediated immunity. A, NLRs guarding the PRR-signaling pathway. Multiple PRR-signaling components are suppressed by effectors. NLRs guard these signaling components and reverse susceptibility triggered by these effectors. Question marks indicate unidentified effectors or NLRs. B, Tabular summary of signaling components required for PRR- and NLR-mediated immunity. Green shading represents confirmed requirement from publications. Gray shading indicates predicted requirement. Purple shading represents unclear requirement that cannot be predicted. C, Mechanisms involved in the mutual potentiation between PRR- and NLR-mediated immunity. Transcriptomic data were obtained from previously published data (Bjornson et al., 2021; Ngou et al., 2021a). Numbers indicate the corresponding mechanisms to potentiate PRR- or NLR-mediated immunity to achieve robust resistance against pathogens.

Figure 8

Historic overview of PTI and ETI and future challenges. A, Discoveries in PTI (left) and ETI (right) in the past 30 years. Bar charts represent the number of “plant biology” publications that mentioned “pattern-trigger immunity” (red) and “effector-triggered immunity” (blue). Data obtained from Dimensions (https://www.dimensions.ai/). B, Future challenges and outlook in plant immunity research.