Network organization of the plant immune system: from pathogen perception to robust defense induction.

The plant immune system has been explored essentially through the study of qualitative resistance, a simple form of immunity, and from a reductionist point of view. The recent identification of genes conferring quantitative disease resistance revealed a large array of functions, suggesting more complex mechanisms. In addition, thanks to the advent of high-throughput analyses and system approaches, our view of the immune system has become more integrative, revealing that plant immunity should rather be seen as a distributed and highly connected molecular network including diverse functions to optimize expression of plant defenses to pathogens. Here, we review the recent progress made to understand the network complexity of regulatory pathways leading to plant immunity, from pathogen perception, through signaling pathways and finally to immune responses. We also analyze the topological organization of these networks and their emergent properties, crucial to predict novel immune functions and test them experimentally. Finally, we report how these networks might be regulated by environmental clues. Although system approaches remain extremely scarce in this area of research, a growing body of evidence indicates that the plant response to combined biotic and abiotic stresses cannot be inferred from responses to individual stresses. A view of possible research avenues in this nascent biology domain is finally proposed.

Robustness of plant quantitative disease resistance is provided by a decentralized immune network.

Quantitative disease resistance (QDR) represents the predominant form of resistance in natural populations and crops. Surprisingly, very limited information exists on the biomolecular network of the signaling machineries underlying this form of plant immunity. This lack of information may result from its complex and quantitative nature. Here, we used an integrative approach including genomics, network reconstruction, and mutational analysis to identify and validate molecular networks that control QDR in Arabidopsis thaliana in response to the bacterial pathogen Xanthomonas campestris To tackle this challenge, we first performed a transcriptomic analysis focused on the early stages of infection and using transgenic lines deregulated for the expression of RKS1, a gene underlying a QTL conferring quantitative and broad-spectrum resistance to XcampestrisRKS1-dependent gene expression was shown to involve multiple cellular activities (signaling, transport, and metabolism processes), mainly distinct from effector-triggered immunity (ETI) and pathogen-associated molecular pattern (PAMP)-triggered immunity (PTI) responses already characterized in Athaliana Protein-protein interaction network reconstitution then revealed a highly interconnected and distributed RKS1-dependent network, organized in five gene modules. Finally, knockout mutants for 41 genes belonging to the different functional modules of the network revealed that 76% of the genes and all gene modules participate partially in RKS1-mediated resistance. However, these functional modules exhibit differential robustness to genetic mutations, indicating that, within the decentralized structure of the QDR network, some modules are more resilient than others. In conclusion, our work sheds light on the complexity of QDR and provides comprehensive understanding of a QDR immune network.

Two-way mixed-effects methods for joint association analysis using both host and pathogen genomes.

Infectious diseases are often affected by specific pairings of hosts and pathogens and therefore by both of their genomes. The integration of a pair of genomes into genome-wide association mapping can provide an exquisitely detailed view of the genetic landscape of complex traits. We present a statistical method, ATOMM (Analysis with a Two-Organism Mixed Model), that maps a trait of interest to a pair of genomes simultaneously; this method makes use of whole-genome sequence data for both host and pathogen organisms. ATOMM uses a two-way mixed-effect model to test for genetic associations and cross-species genetic interactions while accounting for sample structure including interactions between the genetic backgrounds of the two organisms. We demonstrate the applicability of ATOMM to a joint association study of quantitative disease resistance (QDR) in the Arabidopsis thaliana-Xanthomonas arboricola pathosystem. Our method uncovers a clear host-strain specificity in QDR and provides a powerful approach to identify genetic variants on both genomes that contribute to phenotypic variation.

In situ relationships between microbiota and potential pathobiota in Arabidopsis thaliana.

A current challenge in microbial pathogenesis is to identify biological control agents that may prevent and/or limit host invasion by microbial pathogens. In natura, hosts are often infected by multiple pathogens. However, most of the current studies have been performed under laboratory controlled conditions and by taking into account the interaction between a single commensal species and a single pathogenic species. The next step is therefore to explore the relationships between host-microbial communities (microbiota) and microbial members with potential pathogenic behavior (pathobiota) in a realistic ecological context. In the present study, we investigated such relationships within root-associated and leaf-associated bacterial communities of 163 ecologically contrasted Arabidopsis thaliana populations sampled across two seasons in southwest of France. In agreement with the theory of the invasion paradox, we observed a significant humped-back relationship between microbiota and pathobiota α-diversity that was robust between both seasons and plant organs. In most populations, we also observed a strong dynamics of microbiota composition between seasons. Accordingly, the potential pathobiota composition was explained by combinations of season-specific microbiota operational taxonomic units. This result suggests that the potential biomarkers controlling pathogen's invasion are highly dynamic.

Author Correction: Intermediate degrees of synergistic pleiotropy drive adaptive evolution in ecological time.

In the version of this Article previously published, there was a typographical error ('4' instead of '2') in the equations relating F ST and effective population size (N e) in the Methods section 'Genome-wide scan for selection based on temporal differentiation'. The correct equations are given below.[Formula: see text] [Formula: see text].

Intermediate degrees of synergistic pleiotropy drive adaptive evolution in ecological time.

Rapid phenotypic evolution of quantitative traits can occur within years, but its underlying genetic architecture remains uncharacterized. Here we test the theoretical prediction that genes with intermediate pleiotropy drive adaptive evolution in nature. Through a resurrection experiment, we grew Arabidopsis thaliana accessions collected across an 8-year period in six micro-habitats representative of that local population. We then used genome-wide association mapping to identify the single-nucleotide polymorphisms (SNPs) associated with evolved and unevolved traits in each micro-habitat. Finally, we performed a selection scan by testing for temporal differentiation in these SNPs. Phenotypic evolution was consistent across micro-habitats, but its associated genetic bases were largely distinct. Adaptive evolutionary change was most strongly driven by a small number of quantitative trait loci (QTLs) with intermediate degrees of pleiotropy; this pleiotropy was synergistic with the per-trait effect size of the SNPs, increasing with the degree of pleiotropy. In addition, weak selection was detected for frequent micro-habitat-specific QTLs that shape single traits. In this population, A. thaliana probably responded to local warming and increased competition, in part mediated by central regulators of flowering time. This genetic architecture, which includes both synergistic pleiotropic QTLs and distinct QTLs within particular micro-habitats, enables rapid phenotypic evolution while still maintaining genetic variation in wild populations.

An essential role for the VASt domain of the Arabidopsis VAD1 protein in the regulation of defense and cell death in response to pathogens.

Several regulators of programmed cell death (PCD) have been identified in plants which encode proteins with putative lipid-binding domains. Among them, VAD1 (Vascular Associated Death) contains a novel protein domain called VASt (VAD1 analog StAR-related lipid transfer) still uncharacterized. The Arabidopsis mutant vad1-1 has been shown to exhibit a lesion mimic phenotype with light-conditional appearance of propagative hypersensitive response-like lesions along the vascular system, associated with defense gene expression and increased resistance to Pseudomonas strains. To test the potential of ectopic expression of VAD1 to influence HR cell death and to elucidate the role of the VASt domain in this function, we performed a structure-function analysis of VAD1 by transient over-expression in Nicotiana benthamiana and by complementation of the mutant vad1-1. We found that (i) overexpression of VAD1 controls negatively the HR cell death and defense expression either transiently in Nicotiana benthamania or in Arabidopsis plants in response to avirulent strains of Pseudomonas syringae, (ii) VAD1 is expressed in multiple subcellular compartments, including the nucleus, and (iii) while the GRAM domain does not modify neither the subcellular localization of VAD1 nor its immunorepressor activity, the domain VASt plays an essential role in both processes. In conclusion, VAD1 acts as a negative regulator of cell death associated with the plant immune response and the VASt domain of this unknown protein plays an essential role in this function, opening the way for the functional analysis of VASt-containing proteins and the characterization of novel mechanisms regulating PCD.

Quantitative disease resistance to the bacterial pathogen Xanthomonas campestris involves an Arabidopsis immune receptor pair and a gene of unknown function.

Although quantitative disease resistance (QDR) is a durable and broad-spectrum form of resistance in plants, the identification of the genes underlying QDR is still in its infancy. RKS1 (Resistance related KinaSe1) has been reported recently to confer QDR in Arabidopsis thaliana to most but not all races of the bacterial pathogen Xanthomonas campestris pv. campestris (Xcc). We therefore explored the genetic bases of QDR in A. thaliana to diverse races of X. campestris (Xc). A nested genome-wide association mapping approach was used to finely map the genomic regions associated with QDR to Xcc12824 (race 2) and XccCFBP6943 (race 6). To identify the gene(s) implicated in QDR, insertional mutants (T-DNA) were selected for the candidate genes and phenotyped in response to Xc. We identified two major QTLs that confer resistance specifically to Xcc12824 and XccCFBP6943. Although QDR to Xcc12824 is conferred by At5g22540 encoding for a protein of unknown function, QDR to XccCFBP6943 involves the well-known immune receptor pair RRS1/RPS4. In addition to RKS1, this study reveals that three genes are involved in resistance to Xc with strikingly different ranges of specificity, suggesting that QDR to Xc involves a complex network integrating multiple response pathways triggered by distinct pathogen molecular determinants.

An atypical kinase under balancing selection confers broad-spectrum disease resistance in Arabidopsis.

The failure of gene-for-gene resistance traits to provide durable and broad-spectrum resistance in an agricultural context has led to the search for genes underlying quantitative resistance in plants. Such genes have been identified in only a few cases, all for fungal or nematode resistance, and encode diverse molecular functions. However, an understanding of the molecular mechanisms of quantitative resistance variation to other enemies and the associated evolutionary forces shaping this variation remain largely unknown. We report the identification, map-based cloning and functional validation of QRX3 (RKS1, Resistance related KinaSe 1), conferring broad-spectrum resistance to Xanthomonas campestris (Xc), a devastating worldwide bacterial vascular pathogen of crucifers. RKS1 encodes an atypical kinase that mediates a quantitative resistance mechanism in plants by restricting bacterial spread from the infection site. Nested Genome-Wide Association mapping revealed a major locus corresponding to an allelic series at RKS1 at the species level. An association between variation in resistance and RKS1 transcription was found using various transgenic lines as well as in natural accessions, suggesting that regulation of RKS1 expression is a major component of quantitative resistance to Xc. The co-existence of long lived RKS1 haplotypes in A. thaliana is shared with a variety of genes involved in pathogen recognition, suggesting common selective pressures. The identification of RKS1 constitutes a starting point for deciphering the mechanisms underlying broad spectrum quantitative disease resistance that is effective against a devastating and vascular crop pathogen. Because putative RKS1 orthologous have been found in other Brassica species, RKS1 provides an exciting opportunity for plant breeders to improve resistance to black rot in crops.