Biology subjects

Desveaux, D.

Publications and source records attributed to Desveaux, D..

8 recordsLinked to original sources

bioRxiv2026

Effector-triggered stomatal immunity prevents leaf invasion by bacterial pathogens

The phytopathogen Pseudomonas syringae must enter the leaf interior through natural openings such as stomata to cause disease. Plants restrict pathogen entry into the leaf upon non-self recognition-driven closure of their stomata. P. syringae counters this stomatal immunity by deploying a range of toxins and effectors. Here, we show that stomatal immunity in Arabidopsis thaliana is reinforced upon recognition of the ubiquitous P. syringae type III effector AvrE1 by the resistance protein CAR1. CAR1 expression is enriched in guard cells, and its activation prolongs the effective duration of stomatal immunity. We also show that CAR1 prevents the invasion of leaf tissue by natural isolates of P. syringae, demonstrating that CAR1-mediated stomatal immunity against the conserved effector AvrE1 provides a broadly significant barrier to host accessibility by P. syringae.

plant biology↗

bioRxiv2023

The leucine-rich repeat receptor kinase QSK1 is a novel regulator of PRR-RBOHD complex and is employed by the bacterial effector HopF2Pto to modulate plant immunity

Plants detect pathogens using cell-surface pattern recognition receptors (PRRs) like EFR and FLS2, which recognize bacterial EF-Tu and flagellin, respectively. These PRRs, belonging to the leucine-rich repeat receptor kinase (LRR-RK) family, activate the production of reactive oxygen species via the NADPH oxidase RBOHD. The PRR-RBOHD complex is tightly regulated to prevent unwarranted or exaggerated immune responses. However, certain pathogenic effectors can subvert these regulatory mechanisms, thereby suppressing plant immunity. To elucidate the intricate dynamics of the PRR-RBOHD complex, we conducted a comparative co-immunoprecipitation analysis using EFR, FLS2, and RBOHD. We identified QSK1, an LRR-RK, as a novel component of the PRR-RBOHD complex. QSK1 functions as a negative regulator of PRR-triggered immunity (PTI) by downregulating the abundance of FLS2 and EFR. QSK1 is targeted by the bacterial effector HopF2Pto, a mono-ADP ribosyltransferase, resulting in the reduction of FLS2 and EFR levels through both transcriptional and transcription-independent pathways, thereby inhibiting PTI. Furthermore, HopF2Pto reduces transcript levels of PROSCOOP genes encoding important stress-regulated phytocytokines and their receptor MIK2. Importantly, HopF2Pto requires QSK1 for its accumulation and virulence functions within plants. In summary, our results provide novel insights into the mechanism by which HopF2Pto employs QSK1 to desensitize plants to pathogen attack. One Sentence SummaryQSK1, a novel component in the plant immune receptor complex, downregulates these receptors and phytocytokines, and is exploited by bacterial effector HopF2Pto to desensitize plants to pathogen attack.

plant biology↗

bioRxiv2021

Metaeffector interactions modulate the type III effector-triggered immunity load of Pseudomonas syringae

The bacterial plant pathogen Pseudomonas syringae requires type III secreted effectors (T3SEs) for pathogenesis. However, a major facet of plant immunity entails the recognition of a subset of P. syringaes T3SEs by intracellular host receptors in a process called Effector- Triggered Immunity (ETI). Prior work has shown that ETI-eliciting T3SEs are pervasive in the P. syringae species complex raising the question of how P. syringae mitigates its ETI load to become a successful pathogen. While pathogens can evade ETI by T3SE mutation, recombination, or loss, there is increasing evidence that effector-effector (a.k.a., metaeffector) interactions can suppress ETI. To study the ETI-suppression potential of P. syringae T3SE repertoires, we compared the ETI-elicitation profiles of two genetically divergent strains: P. syringae pv. tomato DC3000 (PtoDC3000) and P. syringae pv. maculicola ES4326 (PmaES4326), which are both virulent on Arabidopsis thaliana but harbour largely distinct effector repertoires. Of the 529 T3SE alleles screened on A. thaliana Col-0 from the P. syringae T3SE compendium (PsyTEC) [1], 69 alleles from 21 T3SE families elicited ETI in at least one of the two strain backgrounds, while 50 elicited ETI in both backgrounds, resulting in 19 differential ETI responses including two novel ETI-eliciting families: AvrPto1 and HopT1. Although most of these differences were quantitative, three ETI responses were completely absent in one of the pathogenic backgrounds. We performed ETI suppression screens to test if metaeffector interactions contributed to these ETI differences, and found that HopQ1a suppressed AvrPto1m-mediated ETI, while HopG1c and HopF1g suppressed HopT1b-mediated ETI. Overall, these results show that P. syringae strains leverage metaeffector interactions and ETI suppression to overcome the ETI load associated with their native T3SE repertoires.

plant biology↗

bioRxiv2021

RecPD: A Recombination-Aware Measure of Phylogenetic Diversity

A critical step in studying biological features (e.g., genetic variants, gene families, metabolic capabilities, or taxa) underlying traits or outcomes of interest is assessing their diversity and distribution. Accurate assessments of these patterns are essential for linking features to traits or outcomes and understanding their functional impact. Consequently, it is of crucial importance that the metrics employed for quantifying feature diversity can perform robustly under any evolutionary scenario. However, the standard metrics used for quantifying and comparing the distribution of features, such as prevalence, phylogenetic diversity, and related approaches, either do not take into consideration evolutionary history, or assume strictly vertical patterns of inheritance. Consequently, these approaches cannot accurately assess diversity for features that have undergone recombination or horizontal transfer. To address this issue, we have devised RecPD, a novel recombination-aware phylogenetic-diversity metric for measuring the distribution and diversity of features under all evolutionary scenarios. RecPD utilizes ancestral-state reconstruction to map the presence / absence of features onto ancestral nodes in a species tree, and then identifies potential recombination events in the evolutionary history of the feature. We also derive a number of related metrics from RecPD that can be used to assess and quantify evolutionary dynamics and correlation of feature evolutionary histories. We used simulation studies to show that RecPD reliably identifies evolutionary histories under diverse recombination and loss scenarios. We then apply RecPD in a real-world scenario in a preliminary study type III effector protein families secreted by the plant pathogenic bacterium Pseudomonas syringae and demonstrate that prevalence is an inadequate metric that obscures the potential impact of recombination. We believe RecPD will have broad utility for revealing and quantifying complex evolutionary processes for features at any biological level. AUTHOR SUMMARYPhylogenetic diversity is an important concept utilized in evolutionary ecology which has extensive applications in population genetics to help us understand how evolutionary processes have distributed genetic variation among individuals of a species, and how this impacts phenotypic diversification over time. However, existing approaches for studying phylogenetic diversity largely assume that the genetic features follow vertical inheritance, which is frequently violated in the case of microbial genomes due to horizontal transfer. To address this shortcoming, we present RecPD, a recombination-aware phylogenetic diversity metric, which incorporates ancestral state reconstruction to quantify the phylogenetic diversity of genetic features mapped onto a species phylogeny. Through simulation experiments we show that RecPD robustly reconstructs the evolutionary histories of features evolving under various scenarios of recombination and loss. When applied to a real-world example of type III secreted effector protein families from the plant pathogenic bacterium Pseudomonas syringae, RecPD reveals that horizontal transfer has played an important role in shaping the phylogenetic distributions of aa substantial proportion of families across the P. syringae species complex. Furthermore, we demonstrate that the traditional measures of feature prevalence are unsuitable as a metric for comparing feature diversity.

genomics↗

bioRxiv2021

Predictive Modeling of Pseudomonas syringae Virulence on Bean using Gradient Boosted Decision Trees

Pseudomonas syringae is a genetically diverse bacterial species complex responsible for numerous agronomically important crop diseases. Individual P. syringae isolates are typically given pathovar designations based on their host of isolation and the associated disease symptoms, and these pathovar designations are often assumed to reflect host specificity although this assumption has rarely been rigorously tested. Here we developed a rapid seed infection assay to measure the virulence of 121 diverse P. syringae isolates on common bean (Phaseolus vulgaris). This collection includes P. syringae phylogroup 2 (PG2) bean isolates (pathovar syringae) that cause bacterial spot disease and P. syringae phylogroup 3 (PG3) bean isolates (pathovar phaseolicola) that cause the more serious halo blight disease. We found that bean isolates in general were significantly more virulent on bean than non-bean isolates and observed no significant virulence difference between the PG2 and PG3 bean isolates. However, when we compared virulence within PGs we found that PG3 bean isolates were significantly more virulent than PG3 non-bean isolates, while there was no significant difference in virulence between PG2 bean and non-bean isolates. These results indicate that PG3 strains have a higher level of host specificity than PG2 strains. We then employed machine learning to investigate if we could use genomic data to predict virulence on bean. We used gradient boosted decision trees to model the virulence using whole genome kmers, type III secreted effector kmers, and the presence/absence of type III effectors and phytotoxins. Our model performed best using whole genome data and was able to predict virulence with high accuracy (mean absolute error = 0.05). Finally, we functionally validated the model by predicting virulence for 16 strains and found that 15 (94%) had virulence levels within the bounds of estimated predictions. This study demonstrates the power of machine learning for predicting host specific adaptation and strengthens the hypothesis that P. syringae PG2 strains have evolved a different lifestyle than other P. syringae strains. AUTHOR SUMMARYPseudomonas syringae is a genetically diverse Gammaproteobacterial species complex responsible for numerous agronomically important crop diseases. Strains in the P. syringae species complex are frequently categorized into pathovars depending on pathogenic characteristics such as host of isolation and disease symptoms. Common bean pathogens from P. syringae are known to cause two major diseases: the halo blight disease, which is characterized by large necrotic lesions surrounded by a chlorotic zone or halo of yellow tissue; and the bacterial spot disease, which is characterized by brown leaf spots. While halo blight can cause serious crop losses, bacterial spot disease is generally of minor agronomic concern. The application of statistical genetic and machine learning approaches to genomic data has greatly increased our power to identify genes underlying traits of interest, such as host specificity. Machine learning models can be used to predict outcomes from new samples or to identify the genetic feature(s) that carry the most importance when predicting a particular phenotype. Here, we implemented a rapid method for screening a proxy of virulence for P. syringae isolates on common bean, and used this screen to assess virulence of P. syringae strains on bean. We found that halo blight pathogens display a stronger degree of host specificity compared to brown spot pathogens, and that genomic kmers and virulence factors can be used to predict the virulence of P. syringae isolates on bean using machine learning models.

genomics↗

bioRxiv2019

Perturbations of a Kinase-Pseudokinase Module Activate Plant Immunity

The Pseudomonas syringae acetyltransferase HopZ1a is delivered directly into host cells by the type III secretion system to promote bacterial growth. However, in the model plant host Arabidopsis thaliana, HopZ1a activity results in an effector-triggered immune response (ETI) that limits bacterial proliferation. HopZ1a-triggered immunity requires the nucleotide-binding, leucine-rich repeat domain (NLR) protein, ZAR1, and the ZED1 pseudokinase. Here we demonstrate that HopZ1a can acetylate members of a family of receptor-like cytoplasmic kinases (RLCK family VII; also known as PBS1-like kinases, or PBLs) and promote their interaction with ZED1 and ZAR1 to form a ZAR1/ZED1/PBL ternary complex. Interactions between ZED1 and PBL kinases are determined by the pseudokinase features of ZED1, and mutants designed to restore ZED1 kinase motifs can (1) bind to PBLs, (2) recruit ZAR1, and (3) trigger immunity in planta, all independently of HopZ1a. Our results suggest that interactions between these two RLCK families are promoted by perturbations of structural features that distinguish active from inactive kinase domain conformations. We propose that effector-induced interactions between ZED1/ZRK pseudokinases (RLCK family XII) and PBL kinases (RLCK family VII) provide a sensitive mechanism for detecting perturbations of either kinase family and activating ZAR1-mediated ETI. AUTHOR SUMMARYAll plants must ward off potentially infectious microbes, and those grown in large-scale crop operations are especially vulnerable to the rapid spread of disease by successful pathogens. Although many bacteria and fungi can supress plant immune responses by producing specialized virulence proteins called effectors, these effectors can also trigger immune responses that render plants resistant to infection. We studied the molecular mechanisms underlying one such effector-triggered immune response elicited by the bacterial effector HopZ1a in the model plant host Arabidopsis thaliana. We have shown that HopZ1a promotes binding between a ZED1, a pseudokinase required for HopZ1a-triggered immunity, and several true kinases (known as PBLs) that are likely targets of HopZ1a activity in planta. HopZ1a-induced ZED1-PBL interactions also recruit ZAR1, an Arabidopsis resistance protein previously implicated in HopZ1a-triggered immunity. Importantly, ZED1 mutants that restore degenerate kinase motifs can bridge interactions between PBLs and ZAR1 (independently of HopZ1a) and trigger immunity in planta. Our results suggest that equilibria between active and inactive kinase domain conformations regulate ZED1-PBL interactions and formation of ternary complexes with ZAR1. Improved models describing molecular interactions between immunity determinants, effectors and effector targets will inform efforts to exploit natural diversity for development of crops with enhanced disease resistance.

molecular biology↗

bioRxiv2018

Molecular Evolution of Pseudomonas syringae Type III Secreted Effector Proteins

Diverse Gram-negative pathogens like Pseudomonas syringae employ type III secreted effector (T3SE) proteins as primary virulence factors that combat host immunity and promote disease. T3SEs can also be recognized by plant hosts and activate an effector triggered immune (ETI) response that shifts the interaction back towards plant immunity. Consequently, T3SEs are pivotal in determining the virulence potential of individual P. syringae strains, and ultimately restrict P. syringae pathogens to a subset of potential hosts that are unable to recognize their repertoires of T3SEs. While a number of effector families are known to be present in the P. syringae species complex, one of the most persistent challenges has been documenting the complex variation in T3SE contents across a diverse collection of strains. Using the entire pan-genome of 494 P. syringae strains isolated from more than 100 hosts, we conducted a global analysis of all known and putative T3SEs. We identified a total of 14,613 T3SEs, 4,636 of which were unique at the amino acid level, and show that T3SE repertoires of different P. syringae strains vary dramatically, even among strains isolated from the same hosts. We also find that dramatic diversification has occurred within many T3SE families, and in many cases find strong signatures of positive selection. Furthermore, we identify multiple gene gain and loss events for several families, demonstrating an important role of horizontal gene transfer (HGT) in the evolution of P. syringae T3SEs. These analyses provide insight into the evolutionary history of P. syringae T3SEs as they co-evolve with the host immune system, and dramatically expand the database of P. syringae T3SEs alleles.

evolutionary biology↗

bioRxiv2018

Yeast Genomic Screens Identify Kinesins as Potential Targets of the Pseudomonas syringae Type III Effector, HopZ1a

Gram-negative bacterial pathogens inject type III secreted effectors (T3SEs) directly into host cells to promote pathogen fitness by manipulating host cellular processes. Despite their crucial role in promoting virulence, relatively few T3SEs have well-characterized enzymatic activities or host targets. This is in part due to functional redundancy within pathogen T3SE repertoires as well as promiscuous individual T3SEs that can have multiple host targets. To overcome these challenges, we conducted heterologous genetic screens in yeast, a non-host organism, to identify T3SEs that target conserved eukaryotic processes. We screened 75 T3SEs from the plant pathogen Pseudomonas syringae and identified 16 that inhibited yeast growth on rich media and eight that inhibited growth on stress-inducing media, including the acetyltransferase HopZ1a. We focused our further analysis on HopZ1a, which interacts with plant tubulin and alters microtubule networks. We first performed a Pathogenic Genetic Array (PGA) screen of HopZ1a against ~4400 yeast carrying non-essential mutations and found 95 and 10 deletion mutants which reduced or enhanced HopZ1a toxicity, respectively. To uncover putative HopZ1a host targets, we interrogated both the genetic- and physical-interaction profiles of HopZ1a by identifying yeast genes with PGA profiles most similar (i.e. congruent) to that of HopZ1a, performing a functional enrichment analysis of these HopZ1a-congruent genes, and by analyzing previously described HopZ physical interaction datasets. Finally, we demonstrated that HopZ1a can target kinesins by acetylating the plant kinesins HINKEL and MKRP1.\n\nARTICLE SUMMARYBacterial pathogens utilize secretion systems to directly deliver effector proteins into host cells, with the ultimate goal of promoting pathogen fitness. Despite the central role that effectors play in infection, the molecular function and host targets of most effectors remain uncharacterized. We used yeast genomics and protein interaction data to identify putative virulence targets of the effector HopZ1a from the plant pathogen Pseudomonas syringae. HopZ1a is an acetyltransferase that induces plant microtubule destruction. We showed that HopZ1a acetylated plant kinesin proteins known to regulate microtubule networks. Our study emphasizes the power of yeast functional genomic screens to characterize effector functions.

microbiology↗