Gut microbial metabolism drives transformation of MSH2-deficient colon epithelial cells.

The etiology of colorectal cancer (CRC) has been linked to deficiencies in mismatch repair and adenomatous polyposis coli (APC) proteins, diet, inflammatory processes, and gut microbiota. However, the mechanism through which the microbiota synergizes with these etiologic factors to promote CRC is not clear. We report that altering the microbiota composition reduces CRC in APC(Min/+)MSH2(-/-) mice, and that a diet reduced in carbohydrates phenocopies this effect. Gut microbes did not induce CRC in these mice through an inflammatory response or the production of DNA mutagens but rather by providing carbohydrate-derived metabolites such as butyrate that fuel hyperproliferation of MSH2(-/-) colon epithelial cells. Further, we provide evidence that the mismatch repair pathway has a role in regulating ß-catenin activity and modulating the differentiation of transit-amplifying cells in the colon. These data thereby provide an explanation for the interaction between microbiota, diet, and mismatch repair deficiency in CRC induction. PAPERCLIP:

Gut Microbiome Composition Is Associated With Future Onset of Crohn's Disease in Healthy First-Degree Relatives.

BACKGROUND & AIMS: The cause of Crohn's disease (CD) is unknown, but the current hypothesis is that microbial or environmental factors induce gut inflammation in genetically susceptible individuals, leading to chronic intestinal inflammation. Case-control studies of patients with CD have cataloged alterations in the gut microbiome composition; however, these studies fail to distinguish whether the altered gut microbiome composition is associated with initiation of CD or is the result of inflammation or drug treatment. METHODS: In this prospective cohort study, 3483 healthy first-degree relatives (FDRs) of patients with CD were recruited to identify the gut microbiome composition that precedes the onset of CD and to what extent this composition predicts the risk of developing CD. We applied a machine learning approach to the analysis of the gut microbiome composition (based on 16S ribosomal RNA sequencing) to define a microbial signature that associates with future development of CD. The performance of the model was assessed in an independent validation cohort. RESULTS: In the validation cohort, the microbiome risk score (MRS) model yielded a hazard ratio of 2.24 (95% confidence interval, 1.03-4.84; P = .04), using the median of the MRS from the discovery cohort as the threshold. The MRS demonstrated a temporal validity by capturing individuals that developed CD up to 5 years before disease onset (area under the curve > 0.65). The 5 most important taxa contributing to the MRS included Ruminococcus torques, Blautia, Colidextribacter, an uncultured genus-level group from Oscillospiraceae, and Roseburia. CONCLUSION: This study is the first to demonstrate that gut microbiome composition is associated with future onset of CD and suggests that gut microbiome is a contributor in the pathogenesis of CD.

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. syringae's 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), 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.

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 assigned 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 used gradient boosting machine learning to predict each strain's virulence on bean based on whole genome k-mers, type III secreted effector k-mers, 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 strengthens the hypothesis that P. syringae PG2 strains have evolved a different lifestyle than other P. syringae strains as reflected in their lower level of host specificity. It also acts as a proof-of-principle to demonstrate the power of machine learning for predicting host specific adaptation.

Pseudomonas syringae coffee blight is associated with the horizontal transfer of plasmid-encoded type III effectors.

The emergence of new pathogens is an ongoing threat to human health and agriculture. While zoonotic spillovers received considerable attention, the emergence of crop diseases is less well studied. Here, we identify genomic factors associated with the emergence of Pseudomonas syringae bacterial blight of coffee. Fifty-three P. syringae strains from diseased Brazilian coffee plants were sequenced. Comparative and evolutionary analyses were used to identify loci associated with coffee blight. Growth and symptomology assays were performed to validate the findings. Coffee isolates clustered in three lineages, including primary phylogroups PG3 and PG4, and secondary phylogroup PG11. Genome-wide association study of the primary PG strains identified 37 loci, including five effectors, most of which were encoded on a plasmid unique to the PG3 and PG4 coffee strains. Evolutionary analyses support the emergence of coffee blight in PG4 when the coffee-associated plasmid and associated effectors derived from a divergent plasmid carried by strains associated with other hosts. This plasmid was only recently transferred into PG3. Natural diversity and CRISPR-Cas9 plasmid curing were used to show that strains with the coffee-associated plasmid grow to higher densities and cause more severe disease symptoms in coffee. This work identifies possible evolutionary mechanisms underlying the emergence of a new lineage of coffee pathogens.

Predictive modeling of antibiotic eradication therapy success for new-onset Pseudomonas aeruginosa pulmonary infections in children with cystic fibrosis.

Chronic Pseudomonas aeruginosa (Pa) lung infections are the leading cause of mortality among cystic fibrosis (CF) patients; therefore, the eradication of new-onset Pa lung infections is an important therapeutic goal that can have long-term health benefits. The use of early antibiotic eradication therapy (AET) has been shown to clear the majority of new-onset Pa infections, and it is hoped that identifying the underlying basis for AET failure will further improve treatment outcomes. Here we generated machine learning models to predict AET outcomes based on pathogen genomic data. We used a nested cross validation design, population structure control, and recursive feature selection to improve model performance and showed that incorporating population structure control was crucial for improving model interpretation and generalizability. Our best model, controlling for population structure and using only 30 recursively selected features, had an area under the curve of 0.87 for a holdout test dataset. The top-ranked features were generally associated with motility, adhesion, and biofilm formation.

Population genomics of bacterial host adaptation.

Some bacteria can transfer to new host species, and this poses a risk to human health. Indeed, an estimated 60% of all human pathogens have originated from other animal species. Similarly, human-to-animal transitions are recognized as a major threat to sustainable livestock production, and emerging pathogens impose an increasing burden on crop yield and global food security. Recent advances in high-throughput sequencing technologies have enabled comparative genomic analyses of bacterial populations from multiple hosts. Such studies are providing new insights into the evolutionary processes that underpin the establishment of bacteria in new host niches. A better understanding of the genetic and mechanistic basis for bacterial host adaptation may reveal novel targets for controlling infection or inform the design of approaches to limit the emergence of new pathogens.

Publisher Correction: An extracellular network of Arabidopsis leucine-rich repeat receptor kinases.

In this Letter, an incorrect version of the Supplementary Information file was inadvertently used, which contained several errors. The details of references 59-65 were missing from the end of the Supplementary Discussion section on page 4. In addition, the section 'Text 3. Y2H on ICD interactions' incorrectly referred to 'Extended Data Fig. 4d' instead of 'Extended Data Fig. 3d' on page 3. Finally, the section 'Text 4. Interaction network analysis' incorrectly referred to 'Fig. 1b and Extended Data Fig. 6' instead of 'Fig. 2b and Extended Data Fig. 7' on page 3. These errors have all been corrected in the Supplementary Information.

An extracellular network of Arabidopsis leucine-rich repeat receptor kinases.

The cells of multicellular organisms receive extracellular signals using surface receptors. The extracellular domains (ECDs) of cell surface receptors function as interaction platforms, and as regulatory modules of receptor activation. Understanding how interactions between ECDs produce signal-competent receptor complexes is challenging because of their low biochemical tractability. In plants, the discovery of ECD interactions is complicated by the massive expansion of receptor families, which creates tremendous potential for changeover in receptor interactions. The largest of these families in Arabidopsis thaliana consists of 225 evolutionarily related leucine-rich repeat receptor kinases (LRR-RKs), which function in the sensing of microorganisms, cell expansion, stomata development and stem-cell maintenance. Although the principles that govern LRR-RK signalling activation are emerging, the systems-level organization of this family of proteins is unknown. Here, to address this, we investigated 40,000 potential ECD interactions using a sensitized high-throughput interaction assay, and produced an LRR-based cell surface interaction network (CSILRR) that consists of 567 interactions. To demonstrate the power of CSILRR for detecting biologically relevant interactions, we predicted and validated the functions of uncharacterized LRR-RKs in plant growth and immunity. In addition, we show that CSILRR operates as a unified regulatory network in which the LRR-RKs most crucial for its overall structure are required to prevent the aberrant signalling of receptors that are several network-steps away. Thus, plants have evolved LRR-RK networks to process extracellular signals into carefully balanced responses.

Habitats Within the Plant Root Differ in Bacterial Network Topology and Taxonomic Assortativity.

The root microbiome is composed of distinct epiphytic (rhizosphere) and endophytic (endosphere) habitats. Differences in abiotic and biotic factors drive differences in microbial community diversity and composition between these habitats, though how they shape the interactions among community members is unknown. Here, we coupled a large-scale characterization of the rhizosphere and endosphere bacterial communities of 30 plant species across two watering treatments with co-occurrence network analysis to understand how root habitats and soil moisture shape root bacterial network properties. We used a novel bootstrapping procedure and null network modeling to overcome some of the limitations associated with microbial co-occurrence network construction and analysis. Endosphere networks had elevated node betweenness centrality versus the rhizosphere, indicating greater overall connectivity among core bacterial members of the root endosphere. Taxonomic assortativity was higher in the endosphere, whereby positive co-occurrence was more likely between bacteria within the same phylum while negative co-occurrence was more likely between bacterial taxa from different phyla. This taxonomic assortativity could be driven by positive and negative interactions among members of the same or different phylum, respectively, or by similar niche preferences associated with phylum rank among root inhabiting bacteria across plant host species. In contrast to the large differences between root habitats, drought had limited effects on network properties but did result in a higher proportion of shared co-occurrences between rhizosphere and endosphere networks. Our study points to fundamentally different ecological processes shaping bacterial co-occurrence across root habitats. [Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Mediterranean-Like Dietary Pattern Associations With Gut Microbiome Composition and Subclinical Gastrointestinal Inflammation.

BACKGROUND & AIMS: Case-control studies have shown that patients with Crohn's disease (CD) have a microbial composition different from healthy individuals. Although the causes of CD are unknown, epidemiologic studies suggest that diet is an important contributor to CD risk, potentially via modulation of bacterial composition and gut inflammation. We hypothesized that long-term dietary clusters (DCs) are associated with gut microbiome compositions and gut inflammation. Our objectives were to identify dietary patterns and assess whether they are associated with alterations in specific gut microbial compositions and subclinical levels of gut inflammation in a cohort of healthy first-degree relatives (FDRs) of patients with CD. METHODS: As part of the Genetic, Environmental, Microbial (GEM) Project, we recruited a cohort of 2289 healthy FDRs of patients with CD. Individuals provided stool samples and answered a validated food frequency questionnaire reflecting their habitual diet during the year before sample collection. Unsupervised analysis identified 3 dietary and 3 microbial composition clusters. RESULTS: DC3, resembling the Mediterranean diet, was strongly associated with a defined microbial composition, with an increased abundance of fiber-degrading bacteria, such as Ruminococcus, as well as taxa such as Faecalibacterium. The DC3 diet was also significantly associated with lower levels of subclinical gut inflammation, defined by fecal calprotectin, compared with other dietary patterns. No significant associations were found between individual food items and fecal calprotectin, suggesting that long-term dietary patterns rather than individual food items contribute to subclinical gut inflammation. Additionally, mediation analysis demonstrated that DC3 had a direct effect on subclinical inflammation that was partially mediated by the microbiota. CONCLUSIONS: Overall, these results indicated that Mediterranean-like dietary patterns are associated with microbiome and lower intestinal inflammation. This study will help guide future dietary strategies that affect microbial composition and host gut inflammation to prevent diseases.

Altered Gut Microbiome Composition and Function Are Associated With Gut Barrier Dysfunction in Healthy Relatives of Patients With Crohn's Disease.

BACKGROUND & AIMS: The gut microbiome has been suggested to play a role in gut barrier hemostasis, but data are scarce and limited to animal studies. We therefore aimed to assess whether alterations in gut microbial composition and functional pathways are associated with gut barrier function in a cohort of healthy first-degree relatives of patients with Crohn's disease. METHODS: We used the Crohn's and Colitis Canada Genetic Environmental Microbial (CCC-GEM) cohort of healthy first-degree relatives of patients with Crohn's disease. Gut barrier function was assessed using the urinary fractional excretion of lactulose-to-mannitol ratio (LMR). Microbiome composition was assessed by sequencing fecal 16S ribosomal RNA. The cohort was divided into a discovery cohort (n = 2472) and a validation cohort (n = 655). A regression model was used to assess microbial associations with the LMR. A random forest classifier algorithm was performed to assess microbial community contribution to barrier function. RESULTS: Individuals with impaired barrier function (LMR >0.025) had reduced alpha-diversity (Chao1 index, P = 4.0e-4) and altered beta-diversity (Bray-Curtis dissimilarity index, R2 = 0.001, P = 1.0e-3) compared with individuals with an LMR ≤0.025. When taxa were assessed individually, we identified 8 genera and 52 microbial pathways associated with an LMR >0.025 (q < 0.05). Four genera (decreased prevalence of Adlercreutzia, Clostridia UCG 014, and Clostridium sensu stricto 1 and increased abundance of Colidextribacter) and 8 pathways (including decreased biosynthesis of glutamate, tryptophan, and threonine) were replicated in the validation cohort. The random forest approach revealed that the bacterial community is associated with gut barrier function (area under the curve, 0.63; P = 1.4e-6). CONCLUSIONS: The gut microbiome community and pathways are associated with changes in gut barrier function. These findings may identify potential microbial targets to modulate gut barrier.

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) is assessing their diversity and distribution among a sample of individuals. Accurate assessments of these patterns are essential for linking features to traits or outcomes of interest and understanding their functional impact. Consequently, it is of crucial importance that the measures employed for quantifying feature diversity can perform robustly under any evolutionary scenario. However, the standard measures 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 statistic 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 several related measures 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 reconstructs feature evolutionary histories under diverse recombination and loss scenarios. We then applied RecPD in two diverse real-world scenarios including a preliminary study type III effector protein families secreted by the plant pathogenic bacterium Pseudomonas syringae and growth phenotypes of the Pseudomonas genus and demonstrate that prevalence is an inadequate measure 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.

Ethnicity Associations With Food Sensitization Are Mediated by Gut Microbiota Development in the First Year of Life.

BACKGROUND AND AIMS: Increasing evidence supports the role of early-life gut microbiota in developing atopic diseases, but ecological changes to gut microbiota during infancy in relation to food sensitization remain unclear. We aimed to characterize and associate these changes with the development of food sensitization in children. METHODS: In this observational study, using 16S rRNA amplicon sequencing, we characterized the composition of 2844 fecal microbiota in 1422 Canadian full-term infants. Atopic sensitization outcomes were measured by skin prick tests at age 1 year and 3 years. The association between gut microbiota trajectories, based on longitudinal shifts in community clusters, and atopic sensitization outcomes at age 1 and 3 years were determined. Ethnicity and early-life exposures influencing microbiota trajectories were initially examined, and post-hoc analyses were conducted. RESULTS: Four identified developmental trajectories of gut microbiota were shaped by birth mode and varied by ethnicity. The trajectory with persistently low Bacteroides abundance and high Enterobacteriaceae/Bacteroidaceae ratio throughout infancy increased the risk of sensitization to food allergens, particularly to peanuts at age 3 years by 3-fold (adjusted odds ratio [OR] 2.82, 95% confidence interval [CI] 1.13-7.01). A much higher likelihood for peanut sensitization was found if infants with this trajectory were born to Asian mothers (adjusted OR 7.87, 95% CI 2.75-22.55). It was characterized by a deficiency in sphingolipid metabolism and persistent Clostridioides difficile colonization. Importantly, this trajectory of depleted Bacteroides abundance mediated the association between Asian ethnicity and food sensitization. CONCLUSIONS: This study documented an association between persistently low gut Bacteroides abundance throughout infancy and sensitization to peanuts in childhood. It is the first to show a mediation role for infant gut microbiota in ethnicity-associated development of food sensitization.

From Birth to Overweight and Atopic Disease: Multiple and Common Pathways of the Infant Gut Microbiome.

BACKGROUND & AIMS: Few studies, even those with cohort designs, test the mediating effects of infant gut microbes and metabolites on the onset of disease. We undertook such a study. METHODS: Using structural equation modeling path analysis, we tested directional relationships between first pregnancy, birth mode, prolonged labor and breastfeeding; infant gut microbiota, metabolites, and IgA; and childhood body mass index and atopy in 1667 infants. RESULTS: After both cesarean birth and prolonged labor with a first pregnancy, a higher Enterobacteriaceae/Bacteroidaceae ratio at 3 months was the dominant path to overweight; higher Enterobacteriaceae/Bacteroidaceae ratios and Clostridioides difficile colonization at 12 months were the main pathway to atopic sensitization. Depletion of Bifidobacterium after prolonged labor was a secondary pathway to overweight. Influenced by C difficile colonization at 3 months, metabolites propionate and formate were secondary pathways to child outcomes, with a key finding that formate was at the intersection of several paths. CONCLUSIONS: Pathways from cesarean section and first pregnancy to child overweight and atopy share many common mediators of the infant gut microbiome, notably C difficile colonization.

Characterization and predictive functional profiles on metagenomic 16S rRNA data of liver transplant recipients: A longitudinal study.

Long-term survival after Liver Transplantation (LT) is often compromised by infectious and metabolic complications. We aimed to delineate alterations in intestinal microbiome (IM) over time that could contribute to medical complications compromising long-term survival following LT. Fecal samples from LT recipients were collected at 3 months (3 M) and 6 months (6 M) post-LT. The bacterial DNA was extracted using E.Z.N.A. Stool DNA Kit and 16S rRNA gene sequencing at V4 hypervariable region was performed. DADA2 and Phyloseq was implemented to analyze the taxonomic composition. Differentially abundant taxa were identified by metagenomeSeq and LEfSe. Piphillin, an Inferred functional metagenomic analysis tool was used to study the bacterial functional content. For comparison, healthy samples were extracted from NCBI and analyzed similarly. The taxonomic & functional profiles of LT recipients were validated with metagenomic sequencing data from animals exposed to immunosuppressants using Venny. Our findings provide a new perspective on longitudinal increase in specific IM communities post-LT along with an increase in bacterial genes associated with metabolic and infectious disease.

Pseudomonas aeruginosa Strain-sharing in Early Infection Among Children With Cystic Fibrosis.

BACKGROUND: We previously identified Pseudomonas aeruginosa isolates with characteristics typical of chronic infection in some early infections in children with cystic fibrosis (CF), suggesting that these isolates may have been acquired from other patients. Our objective was to define the extent of P. aeruginosa strain-sharing in early CF infections and its impact on antibiotic eradication treatment failure rates. METHODS: We performed whole genome sequencing on isolates from early pediatric CF pulmonary infections and from the following comparator groups in the same hospital: chronic CF infection, sink drains, sterile site infections, and asymptomatic carriage. Univariate logistic regression was used to assess factors associated with treatment failure. RESULTS: In this retrospective, observational study, 1029 isolates were sequenced. The CF clones strain B and clone C were present. In 70 CF patients with early infections, 14 shared strains infected 29 (41%) patients over 5 years; 16% (n = 14) of infections had mixed strains. In the 70 children, approximately one-third of shared-strain infections were likely due to patient-to-patient transmission. Mixed-strain infections were associated with strain-sharing (odds ratio, 8.50; 95% confidence interval, 2.2-33.4; P = .002). Strain-sharing was not associated with antibiotic eradication treatment failure; however, nosocomial strain transmission was associated with establishment of chronic infection in a CF sibling pair. CONCLUSIONS: Although early P. aeruginosa CF infection is thought to reflect acquisition of diverse strains from community reservoirs, we identified frequent early CF strain-sharing that was associated with the presence of mixed strains and instances of possible patient-to-patient transmission.

Perturbations of the ZED1 pseudokinase activate plant immunity.

The Pseudomonas syringae acetyltransferase HopZ1a is delivered 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 pseudokinase, ZED1. 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 ZAR1-dependent immunity in planta, all independently of HopZ1a. A ZED1 mutant that mimics acetylation by HopZ1a also triggers immunity in planta, providing evidence that effector-induced perturbations of ZED1 also activate ZAR1. Overall, 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 to activate ZAR1-mediated ETI.

Diversity and Evolution of Type III Secreted Effectors: A Case Study of Three Families.

A broad range of Gram-negative bacteria employ a type III secretion system (T3SS) to deliver virulence proteins termed type III secreted effectors directly into the cytoplasm of eukaryotic host cells. While effectors can contribute to the colonization of eukaryotic hosts by bacterial symbionts and pathogens, they can also elicit host immune responses that restrict bacterial growth. These opposing selective pressures have shaped the evolution of effector families and may be responsible for their incredible diversity in biochemical function, mechanism of action, and taxonomic distribution. In this chapter, we focus on three distinct effector families whose members are distributed among both plant and animal pathogens. We first discuss the LRR-NEL and YopJ families of effectors. These two effector families possess ubiquitin ligase and acetyltransferase activity, respectively, which in both cases can be directed against host innate immune signal transduction pathways to promote infection. Finally, we discuss the TALE family of transcription activator-like effectors that serve to reprogram host immunity transcriptional responses. This chapter aims to highlight the diversity within these three effector families that results from the strong and dynamic evolutionary forces shaping the interface between host and bacterium.

Assembly and ecological function of the root microbiome across angiosperm plant species.

Across plants and animals, host-associated microbial communities play fundamental roles in host nutrition, development, and immunity. The factors that shape host-microbiome interactions are poorly understood, yet essential for understanding the evolution and ecology of these symbioses. Plant roots assemble two distinct microbial compartments from surrounding soil: the rhizosphere (microbes surrounding roots) and the endosphere (microbes within roots). Root-associated microbes were key for the evolution of land plants and underlie fundamental ecosystem processes. However, it is largely unknown how plant evolution has shaped root microbial communities, and in turn, how these microbes affect plant ecology, such as the ability to mitigate biotic and abiotic stressors. Here we show that variation among 30 angiosperm species, which have diverged for up to 140 million years, affects root bacterial diversity and composition. Greater similarity in root microbiomes between hosts leads to negative effects on plant performance through soil feedback, with specific microbial taxa in the endosphere and rhizosphere potentially affecting competitive interactions among plant species. Drought also shifts the composition of root microbiomes, most notably by increasing the relative abundance of the Actinobacteria. However, this drought response varies across host plant species, and host-specific changes in the relative abundance of endosphere Streptomyces are associated with host drought tolerance. Our results emphasize the causes of variation in root microbiomes and their ecological importance for plant performance in response to biotic and abiotic stressors.