Epidemiology of healthcare-associated Pseudomonas aeruginosa in intensive care units: Are sink drains to blame?

BACKGROUND: Pseudomonas aeruginosa (PA) is a common cause of healthcare-associated infections (PA-HAI) in the intensive care unit (ICU). We aimed to describe the epidemiology of PA-HAI in ICUs in Ontario, Canada, and determine whether we could identify episodes of sink-to-patient PA transmission. METHODS: This was a prospective cohort study of patients in six ICUs from 2018-2019, with retrieval of PA clinical isolates, and PA-screening of antimicrobial resistant organism surveillance rectal swabs, and of sink drain, air, and faucet samples. All PA isolates underwent whole genome sequencing. PA-HAI was defined using US National Healthcare Safety Network criteria. ICU-acquired PA was defined as PA isolated from specimens obtained >48 hours after ICU admission in those with prior negative rectal swabs. Sink-to-patient PA transmission was defined as ICU-acquired PA with close genomic relationship to isolate(s) previously recovered from sinks in a room/bedspace occupied 3-14 days prior to the relevant patient isolate. RESULTS: Over ten months, 72 PA-HAI occurred among 60/4263 admissions. The rate of PA-HAI was 2.40 per 1000 patient-ICU days; higher in patients who were PA-colonized on admission. PA-HAI was associated with longer stay (median 26 vs 3 days uninfected, p<0.001) and contributed to death in 22/60 cases (36.7%). Fifty-eight admissions with ICU-acquired PA were identified, contributing 35/72 (48.6%) PA-HAI. Four patients with five PA-HAI (6.9%) had closely related isolates previously recovered from their room/bedspace sinks. CONCLUSIONS: Nearly half of PA causing HAI appeared to be acquired in ICUs, and 7% of PA-HAI were associated with sink-to-patient transmission. Sinks may be an underrecognized reservoir for HAIs.

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.

Towards integrative plant pathology.

The field of plant pathology has revealed many of the mechanisms underlying the arms race, providing crucial knowledge and genetic resources for improving plant health. Although the host-microbe interaction seemingly favors rapidly evolving pathogens, it has also generated a vast evolutionary history of largely unexplored plant immunodiversity. We review studies that characterize the scope and distribution of genetic and ecological diversity in model and non-model systems with specific reference to pathogen effector diversity, plant immunodiversity in both cultivated species and their wild relatives, and diversity in the plant-associated microbiota. We show how the study of evolutionary and ecological processes can reveal patterns of genetic convergence, conservation, and diversification, and that this diversity is increasingly tractable in both experimental and translational systems. Perhaps most importantly, these patterns of diversity provide largely untapped resources that can be deployed for the rational engineering of durable resistance for sustainable agriculture.

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.

The spatial and temporal distribution of SARS-CoV-2 from the built environment of COVID-19 patient rooms: A multicentre prospective study.

BACKGROUND: SARS-CoV-2 can be detected from the built environment (e.g., floors), but it is unknown how the viral burden surrounding an infected patient changes over space and time. Characterizing these data can help advance our understanding and interpretation of surface swabs from the built environment. METHODS: We conducted a prospective study at two hospitals in Ontario, Canada between January 19, 2022 and February 11, 2022. We performed serial floor sampling for SARS-CoV-2 in rooms of patients newly hospitalized with COVID-19 in the past 48 hours. We sampled the floor twice daily until the occupant moved to another room, was discharged, or 96 hours had elapsed. Floor sampling locations included 1 metre (m) from the hospital bed, 2 m from the hospital bed, and at the room's threshold to the hallway (typically 3 to 5 m from the hospital bed). The samples were analyzed for the presence of SARS-CoV-2 using quantitative reverse transcriptase polymerase chain reaction (RT-qPCR). We calculated the sensitivity of detecting SARS-CoV-2 in a patient with COVID-19, and we evaluated how the percentage of positive swabs and the cycle threshold of the swabs changed over time. We also compared the cycle threshold between the two hospitals. RESULTS: Over the 6-week study period we collected 164 floor swabs from the rooms of 13 patients. The overall percentage of swabs positive for SARS-CoV-2 was 93% and the median cycle threshold was 33.4 (interquartile range [IQR]: 30.8, 37.2). On day 0 of swabbing the percentage of swabs positive for SARS-CoV-2 was 88% and the median cycle threshold was 33.6 (IQR: 31.8, 38.2) compared to swabs performed on day 2 or later where the percentage of swabs positive for SARS-CoV-2 was 98% and the cycle threshold was 33.2 (IQR: 30.6, 35.6). We found that viral detection did not change with increasing time (since the first sample collection) over the sampling period, Odds Ratio (OR) 1.65 per day (95% CI 0.68, 4.02; p = 0.27). Similarly, viral detection did not change with increasing distance from the patient's bed (1 m, 2 m, or 3 m), OR 0.85 per metre (95% CI 0.38, 1.88; p = 0.69). The cycle threshold was lower (i.e., more virus) in The Ottawa Hospital (median quantification cycle [Cq] 30.8) where floors were cleaned once daily compared to the Toronto hospital (median Cq 37.2) where floors were cleaned twice daily. CONCLUSIONS: We were able to detect SARS-CoV-2 on the floors in rooms of patients with COVID-19. The viral burden did not vary over time or by distance from the patient's bed. These results suggest floor swabbing for the detection of SARS-CoV-2 in a built environment such as a hospital room is both accurate and robust to variation in sampling location and duration of occupancy.

Cooperative virulence via the collective action of secreted pathogen effectors.

Although virulence is typically attributed to single pathogenic strains, here we investigated whether effectors secreted by a population of non-virulent strains could function as public goods to enable the emergence of collective virulence. We disaggregated the 36 type III effectors of the phytopathogenic bacterium Pseudomonas syringae strain PtoDC3000 into a 'metaclone' of 36 coisogenic strains, each carrying a single effector in an effectorless background. Each coisogenic strain was individually unfit, but the metaclone was collectively as virulent as the wild-type strain on Arabidopsis thaliana, suggesting that effectors can drive the emergence of cooperation-based virulence through their public action. We show that independently evolved effector suits can equally drive this cooperative behaviour by transferring the effector alleles native to the strain PmaES4326 into the conspecific but divergent strain PtoDC3000. Finally, we transferred the disaggregated PtoDC3000 effector arsenal into Pseudomonas fluorescens and show that their cooperative action was sufficient to convert this rhizosphere-inhabiting beneficial bacterium into a phyllosphere pathogen. These results emphasize the importance of microbial community interactions and expand the ecological scale at which disease may be attributed.

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.

Detection of Covid-19 Outbreaks Using Built Environment Testing for SARS-CoV-2.

Built Environment Testing for SARS-CoV-2Wastewater testing has proven to be a valuable tool for forecasting Covid-19 outbreaks. Fralick et al. now report that swabbing of surfaces (i.e., floors) for SARS-CoV-2 may provide a similar benefit for predicting outbreaks in long-term care homes.

Pseudomonas aeruginosa aggregation and Psl expression in sputum is associated with antibiotic eradication failure in children with cystic fibrosis.

We previously demonstrated that P. aeruginosa isolates that persisted in children with cystic fibrosis (CF) despite inhaled tobramycin treatment had increased anti-Psl antibody binding in vitro compared to those successfully eradicated. We aimed to validate these findings by directly visualizing P. aeruginosa in CF sputum. This was a prospective observational study of children with CF with new-onset P. aeruginosa infection who underwent inhaled tobramycin eradication treatment. Using microbial identification passive clarity technique (MiPACT), P. aeruginosa was visualized in sputum samples obtained before treatment and classified as persistent or eradicated based on outcomes. Pre-treatment isolates were also grown as biofilms in vitro. Of 11 patients enrolled, 4 developed persistent infection and 7 eradicated infection. P. aeruginosa biovolume and the number as well as size of P. aeruginosa aggregates were greater in the sputum of those with persistent compared with eradicated infections (p < 0.01). The amount of Psl antibody binding in sputum was also greater overall (p < 0.05) in samples with increased P. aeruginosa biovolume. When visualized in sputum, P. aeruginosa had a greater biovolume, with more expressed Psl, and formed more numerous, larger aggregates in CF children who failed eradication therapy compared to those who successfully cleared their infection.

ZAR1: Guardian of plant kinases.

A key facet of innate immunity in plants entails the recognition of pathogen "effector" virulence proteins by host Nucleotide-Binding Leucine-Rich Repeat Receptors (NLRs). Among characterized NLRs, the broadly conserved ZAR1 NLR is particularly remarkable due to its capacity to recognize at least six distinct families of effectors from at least two bacterial genera. This expanded recognition spectrum is conferred through interactions between ZAR1 and a dynamic network of two families of Receptor-Like Cytoplasmic Kinases (RLCKs): ZED1-Related Kinases (ZRKs) and PBS1-Like Kinases (PBLs). In this review, we survey the history of functional studies on ZAR1, with an emphasis on how the ZAR1-RLCK network functions to trap diverse effectors. We discuss 1) the dynamics of the ZAR1-associated RLCK network; 2) the specificity between ZRKs and PBLs; and 3) the specificity between effectors and the RLCK network. We posit that the shared protein fold of kinases and the switch-like properties of their interactions make them ideal effector sensors, enabling ZAR1 to act as a broad spectrum guardian of host kinases.

Invariant natural killer T cells minimally influence gut microbiota composition in mice.

Invariant Natural Killer T (iNKT) cells are unconventional T cells that respond to glycolipid antigens found in microbes in a CD1d-dependent manner. iNKT cells exert innate-like functions and produce copious amounts of cytokines, chemokines and cytotoxic molecules within only minutes of activation. As such, iNKT cells can fuel or dampen inflammation in a context-dependent manner. In addition, iNKT cells provide potent immunity against bacteria, viruses, parasites and fungi. Although microbiota-iNKT cell interactions are not well-characterized, mounting evidence suggests that microbiota colonization early in life impacts iNKT cell homeostasis and functions in disease. In this study, we showed that CD1d-/- and Vα14 Tg mice, which lack and have increased numbers of iNKT cells, respectively, had no significant alterations in gut microbiota composition compared to their littermate controls. Furthermore, specific iNKT cell activation by glycolipid antigens only resulted in a transient and minimal shift in microbiota composition when compared to the natural drift found in our colony. Our findings demonstrate that iNKT cells have little to no influence in regulating commensal bacteria at steady state.Abbreviations: iNKT: invariant Natural Killer T cell; αGC: α-galactosylceramide.

Systematic profiling of the chicken gut microbiome reveals dietary supplementation with antibiotics alters expression of multiple microbial pathways with minimal impact on community structure.

BACKGROUND: The emergence of antimicrobial resistance is a major threat to global health and has placed pressure on the livestock industry to eliminate the use of antibiotic growth promotants (AGPs) as feed additives. To mitigate their removal, efficacious alternatives are required. AGPs are thought to operate through modulating the gut microbiome to limit opportunities for colonization by pathogens, increase nutrient utilization, and reduce inflammation. However, little is known concerning the underlying mechanisms. Previous studies investigating the effects of AGPs on the poultry gut microbiome have largely focused on 16S rDNA surveys based on a single gastrointestinal (GI) site, diet, and/or timepoint, resulting in an inconsistent view of their impact on community composition. METHODS: In this study, we perform a systematic investigation of both the composition and function of the chicken gut microbiome, in response to AGPs. Birds were raised under two different diets and AGP treatments, and 16S rDNA surveys applied to six GI sites sampled at three key timepoints of the poultry life cycle. Functional investigations were performed through metatranscriptomics analyses and metabolomics. RESULTS: Our study reveals a more nuanced view of the impact of AGPs, dependent on age of bird, diet, and intestinal site sampled. Although AGPs have a limited impact on taxonomic abundances, they do appear to redefine influential taxa that may promote the exclusion of other taxa. Microbiome expression profiles further reveal a complex landscape in both the expression and taxonomic representation of multiple pathways including cell wall biogenesis, antimicrobial resistance, and several involved in energy, amino acid, and nucleotide metabolism. Many AGP-induced changes in metabolic enzyme expression likely serve to redirect metabolic flux with the potential to regulate bacterial growth or produce metabolites that impact the host. CONCLUSIONS: As alternative feed additives are developed to mimic the action of AGPs, our study highlights the need to ensure such alternatives result in functional changes that are consistent with site-, age-, and diet-associated taxa. The genes and pathways identified in this study are therefore expected to drive future studies, applying tools such as community-based metabolic modeling, focusing on the mechanistic impact of different dietary regimes on the microbiome. Consequently, the data generated in this study will be crucial for the development of next-generation feed additives targeting gut health and poultry production. Video Abstract.

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.

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.

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.

Diversity, Evolution, and Function of Pseudomonas syringae Effectoromes.

Pseudomonas syringae is an evolutionarily diverse bacterial species complex and a preeminent model for the study of plant-pathogen interactions due in part to its remarkably broad host range. A critical feature of P. syringae virulence is the employment of suites of type III secreted effector (T3SE) proteins, which vary widely in composition and function. These effectors act on a variety of plant intracellular targets to promote pathogenesis but can also be avirulence factors when detected by host immune complexes. In this review, we survey the phylogenetic diversity (PD) of the P. syringae effectorome, comprising 70 distinct T3SE families identified to date, and highlight how avoidance of host immune detection has shaped effectorome diversity through functional redundancy, diversification, and horizontal transfer. We present emerging avenues for research and novel insights that can be gained via future investigations of plant-pathogen interactions through the fusion of large-scale interaction screens and phylogenomic approaches.

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.

The Arabidopsis effector-triggered immunity landscape is conserved in oilseed crops.

The bacterial phytopathogen Pseudomonas syringae causes disease on a wide array of plants, including the model plant Arabidopsis thaliana and its agronomically important relatives in the Brassicaceae family. To cause disease, P. syringae delivers effector proteins into plant cells through a type III secretion system. In response, plant nucleotide-binding leucine-rich repeat proteins recognize specific effectors and mount effector-triggered immunity (ETI). While ETI is pervasive across A. thaliana, with at least 19 families of P. syringae effectors recognized in this model species, the ETI landscapes of crop species have yet to be systematically studied. Here, we investigated the conservation of the A. thaliana ETI landscape in two closely related oilseed crops, Brassica napus (canola) and Camelina sativa (false flax). We show that the level of immune conservation is inversely related to the degree of evolutionary divergence from A. thaliana, with the more closely related C. sativa losing ETI responses to only one of the 19 P. syringae effectors tested, while the more distantly related B. napus loses ETI responses to four effectors. In contrast to the qualitative conservation of immune response, the quantitative rank order is not as well-maintained across the three species and diverges increasingly with evolutionary distance from A. thaliana. Overall, our results indicate that the A. thaliana ETI profile is qualitatively conserved in oilseed crops, but quantitatively distinct.

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.