Research Article

The pan-genome effector-triggered immunity landscape of a host-pathogen interaction

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Science  14 Feb 2020:
Vol. 367, Issue 6479, pp. 763-768
DOI: 10.1126/science.aax4079

A plant pan-genome immunity landscape

Plant pathogens elicit an immune response through effector proteins. In turn, plant genomes encode genes that determine species-specific recognition of these effectors by a process known collectively as effector-triggered immunity (ETI). By examining a range of strains of the pathogen Pseudomonas syringae that infect the model plant Arabidopsis thaliana, Laflamme et al. generated a P. syringae Type III Effector Compendium (PsyTEC) and in turn identified the genes responsible for ETI in Arabidopsis. This pan-genome analysis revealed that relatively few A. thaliana genes are responsible for recognizing the majority of P. syringae effectors. These results provide insight into why most pathogenic microbes only infect specific plant species.

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Effector-triggered immunity (ETI), induced by host immune receptors in response to microbial effectors, protects plants against virulent pathogens. However, a systematic study of ETI prevalence against species-wide pathogen diversity is lacking. We constructed the Pseudomonas syringae Type III Effector Compendium (PsyTEC) to reduce the pan-genome complexity of 5127 unique effector proteins, distributed among 70 families from 494 strains, to 529 representative alleles. We screened PsyTEC on the model plant Arabidopsis thaliana and identified 59 ETI-eliciting alleles (11.2%) from 19 families (27.1%), with orthologs distributed among 96.8% of P. syringae strains. We also identified two previously undescribed host immune receptors, including CAR1, which recognizes the conserved effectors AvrE and HopAA1, and found that 94.7% of strains harbor alleles predicted to be recognized by either CAR1 or ZAR1.

All microbial pathogens face highly adapted and multifaceted host immune systems that constrain their host range. The first layer of plant defense against pathogens is governed by preformed barriers and pattern recognition receptors (PRRs) located on plant cell surfaces. The perception of conserved microbe-associated molecular patterns (MAMPs) by PRRs elicits pattern-triggered immunity (PTI), which can suppress the growth of invading microbes (1, 2). However, many microbes have evolved mechanisms to inject effector proteins into host cells that can suppress PTI or otherwise facilitate pathogen growth (3). Plants have in turn evolved a second layer of immunity, termed effector-triggered immunity (ETI), to respond to this challenge. ETI is of greater amplitude than PTI and is elicited when intracellular nucleotide-binding leucine-rich repeat (NLR) receptor proteins detect the presence or activity of microbial effectors (2, 4). The ETI response is associated with the gene-for-gene model of resistance and a localized, programmed cell death that limits pathogen growth, called the hypersensitive response (HR) (5, 6).

ETI plays a dominant role in protecting specific plant genotypes from specific pathogen races. PTI, in contrast, provides broad-spectrum resistance from the recognition of evolutionarily conserved pathogen epitopes (2, 4, 7). Given the genotype-specific nature of ETI, it is not clear whether it is ubiquitous and broadly effective against a diverse bacterial pathogen species carrying a dynamic suite of effectors (810). Although the first P. syringae “avirulence” gene (i.e., ETI-eliciting effector) was cloned in 1984 (11), only nine P. syringae effector alleles that elicit ETI through A. thaliana NLRs have been identified to date (12, 13), and we still know relatively little about the genetic diversity of effectors across the P. syringae species complex, the range of ETI interactions that they mediate, and whether ETI can contribute to broad-spectrum plant resistance.

To better understand the frequency of ETI interactions between a host plant and the diverse effector repertoire of a pathogenic species complex, we focused on type III secreted effectors that mediate interactions between P. syringae and A. thaliana (14). The diverse P. syringae species complex carries 70 distinct effector families and infects nearly every major agricultural crop, although individual strains only cause disease on a small subset of hosts (9, 13, 15). We hypothesized that surveying the species-wide diversity of effectors would uncover novel ETI responses and provide insight into the role of ETI in determining host specificity.

The Pseudomonas syringae Type III Effector Compendium (PsyTEC)

We created the P. syringae Type III Effector Compendium (PsyTEC) to study global effector diversity. We queried the genome sequences of 494 P. syringae strains isolated from more than 100 plant hosts from 28 countries with P. syringae type III effector protein sequences assembled from public databases using BLASTP. From this we identified 14,613 sequences, of which 4636 were unique at the amino acid level and 5127 were unique at the nucleotide level. We delimited these effectors into 70 homology families and 89 subfamilies using stringent homology criteria, which reflected accepted family designations of the sequences in the majority of cases (table S1) (9). Finally, we clustered the diversity within each effector family into PsyTEC clades of highly similar sequences using UCLUST with a percent identity cutoff of 95%. After discarding the 271 singleton PsyTEC clades to avoid screening potential pseudogenes, we were left with a total of 622 multisequence PsyTEC clades spanning the 70 families (table S2).

We constructed PsyTEC by identifying and synthesizing a single representative effector for each multisequence PsyTEC clade on the basis of the following criteria: (i) The effector sequence contained the conserved upstream hrp box promoter sequence within 10 kbp of the start codon, (ii) the effector sequence and upstream region leading up to the hrp box contained no ambiguous bases, and (iii) the effector hrp box and the 25 bp upstream of the hrp box contained no ambiguous bases and did not run into the end of a contig. The presence of hrp boxes and the absence of ambiguous sequences were crucial for accurate expression and synthesis of the representative effectors, respectively. We were able to identify a suitable effector in 529 of the 622 multisequence effector clades. Each PsyTEC representative allele shared at least 95% amino acid identity with the cluster seed for its clade. We synthesized each representative effector with its corresponding native hrp box, including all intergenic sequences between the hrp box and the effector that did not contain other coding regions. Desired priming sites, cloning sites, a unique barcode, and a hemagglutinin epitope tag were also included with each synthesized representative (fig. S1A). Each fragment was then cloned into the pBBR1-MCS2 vector to be mated into P. syringae recipient strains for phenotypic screening (16). This subset of 529 representative effectors spans the P. syringae pan-genome effector diversity and allows us to screen for ETI responses induced by effectors from both host-adapted and non–host-adapted strains (table S1 and figs. S2 and S3).

Given the nonuniform distribution and diversity of most effector families across P. syringae strains (8), we assessed the level of completeness of the PsyTEC library. Analysis of all protein sequences showed that most genomes carry a number of singleton effectors (i.e., effector found in only one strain), with the rarefaction analysis identifying an average of 5.63 singleton effectors per additional genome and a decay parameter (α) of 0.33 (fig. S1B). In contrast, when we clustered effectors sharing ≥95% protein identity, we found an average of only 0.60 new clades per genome (α = 0.68; fig. S1C). This rarefaction plateau was amplified when we considered only multisequence effector clades, yielding an average of only 0.04 new multi-effector clades per additional genome (α = 0.76; fig. S1D). Thus, although further sampling of P. syringae strains will likely continue to reveal novel effector diversity, our analysis has effectively saturated the diversity of the broadly distributed P. syringae effector families.

Widespread recognition of P. syringae effectors by A. thaliana

Our next objective was to identify all P. syringae effectors that elicit an ETI response in the A. thaliana accession Col-0. We first confirmed that spray inoculation of wild-type P. syringae pv. tomato DC3000 (hereafter PtoDC3000) (17) onto A. thaliana resulted in yellow chlorotic disease symptoms within 7 days, whereas plants inoculated with PtoDC3000 expressing the ETI-eliciting effector HopZ1a (1821) remained relatively green and healthy (fig. S4, A and B). We also confirmed this qualitative measurement of overall plant health with quantitative measurements of in planta bacterial growth (fig. S4C) and plant disease symptoms (fig. S4D), as measured by plant immunity and disease image-based quantification (PIDIQ) (22). After transforming all 529 PsyTEC effectors into PtoDC3000, we also assessed the hrp-induced protein expression of each effector via Western blot and observed expression for 402 of the 529 (76.0%) effectors (fig. S5 and table S3). When we excluded effectors with a length of less than half the effector family average, 84.2% of effectors were detected. A small number of the expressed effectors (26) had unexpected sizes, which may reflect the use of alternative start codons (table S3). Effectors whose expression could not be confirmed included all or most representatives from certain effector families (e.g., HopAG1, HopAS1, HopAX1) as well as some truncated effectors. All effectors were ultimately screened, although it is possible that this subset is not expressed.

We systematically screened the PsyTEC library on A. thaliana Col-0 by spray inoculation. Disease symptoms induced by each PsyTEC effector were quantified by PIDIQ (22) in comparison to a virulent negative control (PtoDC3000 pBBR1-MCS2 empty vector) and one of two ETI-eliciting positive controls (PtoDC3000 pBBR1-MCS2-HopZ1a or PtoDC3000 pBBR1-MCS2-AvrRpm1). Effectors that reduced chlorosis symptoms by a normalized percentage of at least 55% (<45% yellow across all plants) relative to the controls were classified as ETI elicitors (fig. S6). This conservative cutoff captured effectors from eight P. syringae families that elicit ETI via known A. thaliana Col-0 NLRs (figs. S6 and S7) (12, 13), as well as two ETI elicitors of A. thaliana Col-0 that have recently been identified but not characterized (23, 24). The only previously identified ETI-eliciting effectors we did not recover in our screen were HopAS1 and HopZ5, both of which elicit ETI only when expressed from a heterologous promoter (25, 26). HopAS1 was also one of the effector families for which we could not confirm expression via Western blot.

Our PsyTEC screen on A. thaliana Col-0 identified 59 ETI-eliciting effector alleles out of the total of 529 effector alleles (11.2%) from 19 of the 70 effector families (27.1%) (Table 1, Fig. 1A, table S4, and fig. S6). These elicitors included nine previously unidentified ETI-eliciting effector families. We also found that diversification within ETI-eliciting effector families was critical for determining the outcome of the interaction. Of the 19 effector families carrying ETI-eliciting alleles, 18 also included alleles that lacked the ability to elicit ETI, with the lone exception being the two-member HopBJ1 family (fig. S3). To show that our novel ETI responses were not specific to our screening strain, PtoDC3000, we tested all 59 ETI-eliciting alleles in the phylogroup 5 radish isolate P. syringae pv. maculicola ES4326 (PmaES4326), which is divergent from the phylogroup 1 tomato isolate PtoDC3000. Both of these strains are strong pathogens of Arabidopsis. The PmaES4326 screen found that 91.5% (54 of 59) of ETI-eliciting effectors found in the original PsyTEC screen retained their ability to elicit ETI in this new background (fig. S8). These data suggest that immune elicitation phenotypes are largely conserved across genetic backgrounds.

Table 1 Summary of the PsyTEC ETI-eliciting effector families on A. thaliana Col-0.

We could not identify HopAS1 and HopZ5 as ETI elicitors using their native promoters (25, 26) and therefore they are not listed among effector families.

View this table:
Fig. 1 Phenotypic effects of ETI-eliciting effectors expressed in PtoDC3000.

(A) Plant disease scores for 529 PsyTEC effectors as determined from percentage of yellow chlorotic plant tissue (22), normalized to the negative (virulent; 100% yellow) and positive (ETI-eliciting; 0% yellow) controls for each flat. A cutoff of 45% yellow (dashed line) was used to distinguish ETI elicitors from non–ETI elicitors. Red dots are alleles that do not elicit ETI; blue dots are alleles that elicit ETI with a hypersensitive response (HR); yellow dots are alleles that elicit ETI without HR. Stars highlight the representatives from each ETI-eliciting family that were used for growth assay verification and NLR screening. (B) Representative ETI-eliciting effectors from each family result in variable declines in bacterial growth in planta over 3 days. Box-and-whisker plots show data from a single representative experiment (n = 8) for each representative ETI-eliciting effector and the corresponding empty-vector control (EV, gray). Solid circles represent individual observations; boxes show the first quartile, median, and third quartile of treatment; whiskers extend to the highest and lowest observations that are not identified as outliers (>1.5× interquartile range). Blue boxes indicate ETI-eliciting effectors producing a macroscopic HR; yellow boxes indicate effectors that did not show HR. All effectors significantly reduced bacterial growth (Student t tests with Holm-Bonferroni multiple test correction, P < 0.01). Plant images show representative HR results and the total number of HR responses observed out of 60 leaves assayed. (C) ETI-eliciting effectors producing a macroscopic HR (blue) resulted in significant reductions in bacterial growth relative to those that did not elicit HR (yellow). P = 4.6 × 10–23 (Student t test).

We then quantified in planta bacterial growth on one representative ETI-eliciting effector from each of the 19 ETI-eliciting families. In planta bacterial growth was reduced in all P. syringae strains harboring an ETI-eliciting effector, although the magnitude of these growth reductions varied among families (Fig. 1B). These growth reductions were not due to general bacterial fitness reductions, because no in vitro growth deficits were observed relative to the empty vector control (fig. S9). We also determined that residues required for effector function were also required for ETI elicitation by our PsyTEC alleles for all newly discovered ETI elicitors, indicating that effector activity is being recognized to elicit ETI (fig. S10 and tables S5 and S6).

We assessed what proportion of ETI-eliciting alleles also caused a macroscopic HR, and demonstrated that HR phenotypes were relatively uncommon among ETI-eliciting effectors. No visible macroscopic HR symptoms were observed for 11 of 19 ETI-eliciting effectors (57.9%) despite their impact on plant tissue chlorosis and bacterial growth (Fig. 1B). The lack of HR phenotypes was not due to effector-effector interactions [so-called meta-effector effects (27)], as no additional HR responses were observed when the 19 ETI-eliciting effector families were screened in the effectorless PtoDC3000 D36E background (table S7) (28). We also confirmed that all HRs required the type III secretion system by screening in a type III secretion system mutant (PtoDC3000-ΔhrcC) background (table S7). Interestingly, there was a significant positive association (Student t test, P = 4.6 × 10–23) between the strength of growth reduction and the observation of a visible HR; effectors that elicited a strong HR caused substantial reductions in growth, whereas those that did not elicit a visible HR caused more modest reductions in bacterial growth (Fig. 1, B and C). These data show that strong, macroscopic HRs are a likely exception, not the rule, in this pathosystem, and are associated with greater reductions in bacterial growth. The historic reliance of HR phenotypes for identifying ETI-eliciting effectors likely explains why relatively few of these weak elicitors have been characterized to date.

Finally, we assessed the theoretical prevalence of ETI among a global collection of 494 P. syringae strains. We identified which strains carried a putative ETI-eliciting effector and mapped these strains onto the P. syringae core genome phylogeny (Fig. 2). We found that 478 of 494 (96.8%) P. syringae strains harbor at least one highly similar ortholog of an ETI-eliciting effector (>95% protein identity), whereas 349 (70.7%) strains harbor multiple orthologs of ETI elicitors. This analysis did not change substantially when we excluded putatively nonfunctional truncated alleles (<75% length of the reference sequence). If we assume that all truncated alleles are unrecognized, 455 of 494 (92.1%) P. syringae strains would still harbor at least one full-length ortholog of an ETI-eliciting effector (fig. S11). Furthermore, if we focus exclusively on primary phylogroup strains, which consist of most of the agricultural isolates and type strains (9), all but six strains (470/476; 98.7%) would carry an ortholog of an ETI-eliciting allele.

Fig. 2 The potential for A. thaliana ETI against P. syringae is pervasive and often multi-tiered.

The P. syringae core-genome phylogeny is shown at the bottom, with designated phylogroups (P) indicated. Color bars above the core-genome phylogenetic tree illustrate which P. syringae strains harbor an ETI-eliciting variant of each effector family (blue) and which strains are thereby expected to be recognized via each characterized plant NLR (green). Effectors and NLRs are sorted according to a hierarchical clustering analysis of the plotted elicitation and recognition profiles, respectively (left). Numbers to the right of each color bar indicate the number of P. syringae strains that contain an ortholog of an ETI-eliciting effector, or the number of P. syringae strains that are expected to be recognized by each NLR based on the complement of effectors carried by each strain. HopF1r was formerly HopF2a.

Note that these predictions of ETI prevalence are made on the basis of the presence of an ETI-eliciting effector or its ortholog (ETI potential) and that the actual outcome of an interaction could be influenced by three potential variables: (i) Meta-effector interactions within a specific strain may modulate ETI responses and the outcome of the interaction. (ii) Chromosomally expressed effectors may not have the same ETI-eliciting activity as effectors expressed from plasmids. This appears to be the case for at least some AvrE effectors; however, even if we exclude all AvrE effectors from our analysis, we still see that 78.8% of primary phylogroup strains harbor an ETI-eliciting effector. (iii) There is as much as 5% amino acid divergence within each PsyTEC clade (technically, up to 95% identity to the cluster seed for each clade), and some of this diversity may result in differential ETI outcomes. Although we did not systematically address this, we did look at 11 cases in which we synthesized multiple alleles from the same PsyTEC clade. In all of these cases, we observed the same ETI response among alleles from the same clade.

A. thaliana resistance to P. syringae is conferred by a small number of NLRs

We searched for NLRs associated with the ETI-eliciting effectors by screening a representative effector from each of the 19 ETI-eliciting families against a suite of A. thaliana Col-0 NLR mutants, including those from our A. thaliana R gene T-DNA insertion collection (table S8) (20). Specifically, PtoDC3000 strains bearing each ETI-eliciting effector were spray-inoculated on the collection of NLR mutant plants to identify loss-of-ETI mutants (Fig. 3A). We subsequently confirmed each NLR-effector pair via quantitative measurements of plant chlorosis (Fig. 3B) and in planta bacterial growth (Fig. 3C). Finally, we confirmed that the same NLR was required for all ETI-eliciting alleles within families (fig. S13).

Fig. 3 NLR specificity for each ETI-eliciting effector family.

(A) Representative plant images after bacteria expressing each ETI-eliciting effector (left) were spray-inoculated onto wild-type (WT) or mutant A. thaliana Col-0 plants lacking a single NLR (top). Red boxes indicate loss-of-ETI interactions (HopF1r was formerly HopF2a). (B) Heat map of the plant disease scores calculated as proportion of yellow chlorotic plant tissue in each treatment (22). Each effector was sprayed on a total of six corresponding A. thaliana NLR mutant plants (table S8) and six A. thaliana Col-0 wild-type plants. The proportion of yellow tissue in the NLR mutant plants corresponding to each cognate ETI-eliciting effector was significantly greater than the proportion of yellow tissue in the wild-type plants in all cases. **P < 0.01, ***P < 0.001 (Student t tests with Holm-Bonferroni multiple test correction). (C) Empty vector (EV) levels of in planta bacterial growth were restored for all novel effector-NLR combinations when strains harboring ETI-eliciting effectors were grown in plants lacking their cognate NLR. Error bars represent SE across eight replicates. Letters above bars represent significance groups at P < 0.05 (Student t tests with Holm-Bonferroni multiple test correction).

Our screen confirmed all previously characterized NLR-effector pairs (20, 2935) (Fig. 3, A and B). We also identified two new NLRs involved in the recognition of novel ETI-eliciting effectors: The Toll/interleukin-1 receptor NLR At5g18360 was required for recognition of HopB (HopB-Activated Resistance 1, BAR1), and the coiled-coil NLR At1g50180 was required for recognition of AvrE and HopAA1 (CEL-Activated Resistance 1, CAR1). Both AvrE and HopAA1 are encoded in the P. syringae conserved effector locus, which is a highly conserved region that flanks the genomic island encoding the type III secretion system (36). We confirmed the requirement of CAR1 for recognition of both AvrE and HopAA1 using an independent CAR1 mutant generated by CRISPR-Cas9 mutagenesis (car1-2; fig. S14). The number of ZAR1-dependent ETI responses identified in the screen was also notable in that we identified novel ZAR1-dependent ETI responses against the HopO, HopX, and HopBA families, in addition to the previously characterized ZAR1-dependent ETI responses against HopZ1a (20) and HopF2a (34). ZAR1 is also known to be required for the recognition of the Xanthomonas campestris effector AvrAC (37). The recognition of HopBA1 by ZAR1 was also surprising given that its recognition in another A. thaliana accession, Ag-0, is governed by the TIR-only protein RBA1 (23).

We predicted which, if any, NLRs would be responsible for an ETI response against each P. syringae strain from that strain’s complement of putative ETI-eliciting effectors and then mapped these “resistance NLRs” across the phylogeny (Fig. 3). Remarkably, we found that A. thaliana is predicted to have near-complete immunity to P. syringae, mediated by a very small number of resistance NLRs. Indeed, as few as eight resistance NLRs are predicted to recognize 96.6% of P. syringae strains (72.7% excluding AvrE), whereas just ZAR1 and CAR1 can potentially recognize 94.7% of strains (43.9% excluding AvrE). Further, 68.0% of strains have multiple resistance NLRs stacked against them.

A single ETI response can determine host accessibility

Finally, we tested whether an individual NLR can limit the ability of P. syringae strains to grow on A. thaliana based on the presence of their cognate effectors. When analyzing the distribution of ETI-eliciting effectors, we observed that the strong A. thaliana pathogen PmaES4326 and the closely related strain (based on the core genome phylogeny) P. syringae pv. maculicola YM7930 (PmaYM7930; also radish pathogen) differed in their suites of ETI-eliciting effector profiles by only the presence of HopAR1 in PmaYM7930; this observation provided a model for testing whether ETI can determine host accessibility. Spray inoculation growth assays showed that PmaYM7930 produces negligible disease symptoms and reaches a final in planta density approximately two orders of magnitude lower than PmaES4326 on A. thaliana Col-0 (Fig. 4). We hypothesized that the presence of HopAR1 in PmaYM7930, which is recognized by A. thaliana NLR RPS5 (35), was the major cause of this limited virulence. When we infected PmaYM7930 on A. thaliana Col-0 rps5 mutant plants, we found that in planta growth of this strain was elevated to the level of PmaES4326, with a corresponding increase in disease symptoms (Fig. 4).

Fig. 4 ETI governs host specificity on A. thaliana.

The P. syringae isolate PmaYM7930 harbors one additional ETI-eliciting effector (HopAR1, which induces ETI via the RPS5 NLR) that is not present in the closely related and highly virulent strain PmaES4326. (A) Visual symptoms of representative wild-type Col-0 and rps5 mutant plants sprayed with PmaYM7930 compared to Col-0 sprayed with PmaES4326 using a standard no-flash setting. (B) Same photos as in (A) but with a green-pass filter to enhance the difference between diseased and healthy tissue. (C and D) In planta bacterial growth assays (C) and plant disease scores based on the proportion of yellow chlorotic plant tissue (D) illustrate that the recognition of HopAR1 by RPS5 significantly reduces bacterial growth and disease symptoms. Letters above bars represent significance groups at P < 0.05 (Student t tests with Holm-Bonferroni multiple test correction).

Although these findings illustrate that the loss of the HopAR1 ETI-eliciting effector enables PmaYM7930 to achieve the same high level of virulence as PmaES4326, this does not appear to be the case for strains that are more distantly related to known A. thaliana pathogens. For example, P. syringae pv. maculicola ICMP2744 (PmaICMP2744, phylogroup 1 mustard pathogen) and P. syringae pv. cannabina (PcbICMP2821, phylogroup 5 hemp pathogen) both carry only one putative ETI-eliciting effector: PmaICMP2744 carries AvrRpm1, which is recognized by RPM1; PcbICMP2821 carries HopA1, which is recognized by RPS6. Growth assays with PmaICMP2744 on A. thaliana rpm1 mutant plants and PcbICMP2821 on A. thaliana rps6 mutant plants were compared to PtoDC3000 and PmaES4326, which are in phylogroups 1 and 5, respectively, but divergent from the tested strains. PmaICMP2744 showed a marginal but significant increase in bacterial growth when grown on rpm1 mutant plants, whereas no difference was observed with PcbICMP2821 growth on wild-type and rps6 mutant plants (fig. S15). Collectively, these results support the idea that a single NLR-effector interaction has the potential to change the outcome of a specific host-pathogen interaction, but this may not be sufficient to determine host accessibility.


Despite decades of research, we still have only a limited understanding of the factors that determine plant pathogen host specificity and range, particularly from a species-wide perspective. The foundation of host resistance and ETI rests on cultivar- or accession-specific interactions (7), which can be difficult to reconcile with our current understanding of pathogen diversity. For example, our genomic analysis of 494 P. syringae strains has identified 4636 unique effector protein sequences, with nearly every strain carrying a distinct suite of effectors, whereas the core genome showed pairwise synonymous substitution rates as high as 1.0 between the most divergent strains (9).

Our PsyTEC library leverages a saturated, pan-genome effector analysis to reveal the pervasive role of ETI mediated by a very small number of NLRs that counter a highly diverse and globally important plant pathogen. We have also revealed the underlying genetic basis of these interactions in both the host and the pathogen, yielding numerous new targets for agricultural engineering of broadly resistant crops.

The convergence of ETI responses on a small suite of NLRs is surprising. For example, CAR1, identified in this study, is an NLR that responds to effectors from the P. syringae conserved effector locus. This NLR has the potential to be particularly potent because it is putatively capable of recognizing AvrE alleles found in 351 of the 494 P. syringae strains used in this study (most other strains have AvrE alleles that do not elicit ETI in this system). Likewise, ZAR1 is a powerful antagonist against P. syringae because it can recognize five effector families represented by alleles that are rarely present in the same genetic background, but that are distributed among nearly half of the P. syringae strains analyzed. Given that ZAR1 is also required for the recognition of AvrAC from X. campestris (37), this NLR appears to have particularly broad-spectrum resistance that inhibits a diverse collection of pathogens. Like AvrAC, these P. syringae effectors may target and modify a diverse collection of receptor-like cytoplasmic kinases, leading to the downstream activation of the ZAR1 resistome (3840). Both CAR1 and ZAR1 are conserved among 1135 sequenced A. thaliana ecotypes (41), which suggests that they play a major role in immunity. It will now be interesting to identify further NLRs involved in recognition of other effectors, as they may offer insight into new immune pathways.

Because of the prominence of ETI against P. syringae, we hypothesize that ETI avoidance will be a crucial virulence strategy of successful pathogens, involving the loss and/or modification of ETI-eliciting effectors (42, 43). In addition, meta-effector interactions will also modulate ETI responses, as shown by the loss of recognition of three effectors when expressed in the PmaES4326 background and the well-established interactions between AvrRpt2 and AvrRpm1 (44). Finally, as demonstrated by the differential recognition of AvrE when encoded chromosomally versus on a plasmid (see fig. S12), we hypothesize that effector dosage must be regulated to maximize virulence benefits while avoiding host detection.

Supplementary Materials

Materials and Methods

Figs. S1 to S15

Tables S1 to S8

References (4565)

References and Notes

Acknowledgments: We thank all members of the Guttman and Desveaux labs for helpful discussion and valuable input on this project; H. Kim, L. Li, S. Park, and N. Hoffmann for help with plant assays; and D. Seto for crucial help with CRISPR/Cas9 mutagenesis. Funding: Supported by Natural Sciences and Engineering Research Council of Canada Discovery Grants (D.S.G. and D.D.), a Natural Sciences and Engineering Research Council of Canada Postgraduate Award (B.L. and A.M.), Canada Research Chairs in Comparative Genomics (D.S.G.) and Plant-Microbe Systems Biology (D.D.), and the Center for the Analysis of Genome Evolution and Function (D.S.G. and D.D.). Author contributions: B.L., M.M.D., D.D., and D.S.G. designed the project; M.M.D. and R.N.D.A. assembled, annotated, and quality-controlled the genomes, including hrp box promoter identification; M.M.D. conceived and carried out the pipeline to identify, delimit, and engineer representative effectors; B.L. and A.M. cloned and delivered effectors into P. syringae, performed Western analysis, and performed growth and HR assays; B.L. and A.M. screened effectors for ETI responses; B.L., M.M.D., A.M., and R.N.D.A. analyzed the data; B.L., M.M.D., D.D., and D.S.G. wrote the paper; and all authors reviewed and agreed on the manuscript. Competing interests: The authors declare no competing interests. Data and materials availability: Accession numbers for all genome assemblies used in this study are available in data S1 to S4. All data that support the findings of our study are available in the manuscript or supplementary materials. All strains with International Collection of Microorganisms from Plants (ICMP) designations are available from ICMP at

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