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.

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.

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.

Maternal Diet and Infant Feeding Practices Are Associated with Variation in the Human Milk Microbiota at 3 Months Postpartum in a Cohort of Women with High Rates of Gestational Glucose Intolerance.

BACKGROUND: Human milk contains a diverse community of bacteria believed to play a role in breast health and inoculation of the infant's gastrointestinal tract. The role of maternal nutrition and infant feeding practices on the human milk microbiota remains poorly understood. OBJECTIVE: Our aim was to explore the associations between maternal diet (delivery to 3 mo postpartum), infant feeding practices, and the microbial composition and predicted function in milk from women with varied metabolic status. METHODS: This was an exploratory analysis of a previously completed prospective cohort study of women with varying degrees of gestational glucose intolerance (NCT01405547). Milk samples (n = 93 mothers) were collected at 3 mo postpartum. Maternal dietary information (validated food-frequency questionnaire) and infant feeding practices (human milk exclusivity, frequency of direct breastfeeding per day) were collected. V4-16S ribosomal RNA gene sequencing (Illumina MiSeq) was conducted to determine microbiota composition. RESULTS: Intake of polyunsaturated fat [ß estimate (SE): 0.036 (0.018), P = 0.047] and fiber from grains [0.027 (0.013), P = 0.048] were positively associated with ɑ-diversity (Shannon index) of human milk. Overall microbial composition of human milk clustered based on human milk exclusivity (weighted UniFrac R2 = 0.034, P = 0.015; Bray-Curtis R2 = 0.041, P = 0.007), frequency of direct breastfeeding per day (Bray-Curtis R2 = 0.057, P = 0.026), and maternal fiber intake from grains (Bray-Curtis R2 = 0.055, P = 0.040). Total fiber, fiber from grains, dietary fat, and infant feeding practices were also associated with a number of differentially abundant taxa. The overall composition of predicted microbial functions was associated with total fiber consumption (Bray-Curtis R2 = 0.067, P = 0.036) and human milk exclusivity (Bray-Curtis R2 = 0.041, P = 0.013). CONCLUSIONS: Maternal consumption of fiber and fat, as well as mother's infant feeding practices, are important determinants of the human milk microbiota. Understanding whether these microbial changes impact an infant's overall health and development requires future study.

Oligosaccharides and Microbiota in Human Milk Are Interrelated at 3 Months Postpartum in a Cohort of Women with a High Prevalence of Gestational Impaired Glucose Tolerance.

BACKGROUND: Human milk is a rich source of human milk oligosaccharides (HMOs) and bacteria. It is unclear how these components interact within the breast microenvironment. OBJECTIVES: The objectives were first, to investigate the association between maternal characteristics and HMOs, and second, to assess the association between HMOs and microbial community composition and predicted function in milk from women with high rates of gestational glucose intolerance. METHODS: This was an exploratory analysis of a previously completed prospective cohort study (NCT01405547) where milk samples (n = 107) were collected at 3 mo postpartum. Milk microbiota composition was analyzed by V4-16S ribosomal RNA gene sequencing and HMOs by rapid high-throughput HPLC. Data were stratified and analyzed by maternal secretor status phenotype and associations between HMOs and microbiota were determined using linear regression models (ɑ-diversity), Adonis (B-diversity), Poisson regression models (differential abundance), and general linear models (predicted microbial function). RESULTS: Prepregnancy BMI, race, and frequency of direct breastfeeding, but not gestational glucose intolerance, were found to be significantly associated with a number of HMOs among secretors and non-secretors. Fucosyllacto-N-hexaose was negatively associated with microbial richness (Chao1) among secretors [B-estimate (SE): -9.3 × 102 (3.4 × 102); P = 0.0082] and difucosyllacto-N-hexaose was negatively associated with microbiota diversity (Shannon index) [-1.7 (0.78); P = 0.029] among secretors. Lacto-N-neotetraose (LNnT) was associated with both microbial B-diversity (weighted UniFrac R2 = 0.040, P = 0.036) and KEGG ortholog B-diversity (Bray-Curtis R2 = 0.039, P = 0.043) in secretors. Additionally, difucosyllactose in secretors and disialyllacto-N-hexaose and LNnT in non-secretors were associated with enrichment of predicted microbial genes encoding for metabolism- and infection-related pathways (P-false discovery rate < 0.1). CONCLUSIONS: HMOs are associated with the microbial composition and predicted microbial functions in human milk at 3 mo postpartum. Further research is needed to investigate the role these relations play in maternal and infant health.

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.

A genome-wide association analysis reveals a potential role for recombination in the evolution of antimicrobial resistance in Burkholderia multivorans.

Cystic fibrosis (CF) lung infections caused by members of the Burkholderia cepacia complex, such as Burkholderia multivorans, are associated with high rates of mortality and morbidity. We performed a population genomics study of 111 B. multivorans sputum isolates from one CF patient through three stages of infection including an early incident isolate, deep sampling of a one-year period of chronic infection occurring weeks before a lung transplant, and deep sampling of a post-transplant infection. We reconstructed the evolutionary history of the population and used a lineage-controlled genome-wide association study (GWAS) approach to identify genetic variants associated with antibiotic resistance. We found the incident isolate was basally related to the rest of the strains and more susceptible to antibiotics from three classes (ß-lactams, aminoglycosides, quinolones). The chronic infection isolates diversified into multiple, distinct genetic lineages and showed reduced antimicrobial susceptibility to the same antibiotics. The post-transplant reinfection isolates derived from the same source as the incident isolate and were genetically distinct from the chronic isolates. They also had a level of susceptibility in between that of the incident and chronic isolates. We identified numerous examples of potential parallel pathoadaptation, in which multiple mutations were found in the same locus or even codon. The set of parallel pathoadaptive loci was enriched for functions associated with virulence and resistance. Our GWAS analysis identified statistical associations between a polymorphism in the ampD locus with resistance to ß-lactams, and polymorphisms in an araC transcriptional regulator and an outer membrane porin with resistance to both aminoglycosides and quinolones. Additionally, these three loci were independently mutated four, three and two times, respectively, providing further support for parallel pathoadaptation. Finally, we identified a minimum of 14 recombination events, and observed that loci carrying putative parallel pathoadaptations and polymorphisms statistically associated with ß-lactam resistance were over-represented in these recombinogenic regions.

Examining the relationship between maternal body size, gestational glucose tolerance status, mode of delivery and ethnicity on human milk microbiota at three months post-partum.

BACKGROUND: Few studies have examined how maternal body mass index (BMI), mode of delivery and ethnicity affect the microbial composition of human milk and none have examined associations with maternal metabolic status. Given the high prevalence of maternal adiposity and impaired glucose metabolism, we systematically investigated the associations between these maternal factors in women ≥20 years and milk microbial composition and predicted functionality by V4-16S ribosomal RNA gene sequencing (NCT01405547;  https://clinicaltrials.gov/ct2/show/NCT01405547 ). Demographic data, weight, height, and a 3-h oral glucose tolerance test were gathered at 30 (95% CI: 25-33) weeks gestation, and milk samples were collected at 3 months post-partum (n = 113). RESULTS: Multivariable linear regression analyses demonstrated no significant associations between maternal characteristics (maternal BMI [pre-pregnancy, 3 months post-partum], glucose tolerance, mode of delivery and ethnicity) and milk microbiota alpha-diversity; however, pre-pregnancy BMI was associated with human milk microbiota beta-diversity (Bray-Curtis R2 = 0.037). Women with a pre-pregnancy BMI > 30 kg/m2 (obese) had a greater incidence of Bacteroidetes (incidence rate ratio [IRR]: 3.70 [95% CI: 1.61-8.48]) and a reduced incidence of Proteobacteria (0.62 [0.43-0.90]) in their milk, compared to women with an overweight BMI (25.0-29.9 kg/m2) as assessed by multivariable Poisson regression. An increased incidence of Gemella was observed among mothers with gestational diabetes who had an overweight BMI versus healthy range BMI (5.96 [1.85-19.21]). An increased incidence of Gemella was also observed among mothers with impaired glucose tolerance with an obese BMI versus mothers with a healthy range BMI (4.04 [1.63-10.01]). An increased incidence of Brevundimonas (16.70 [5.99-46.57]) was found in the milk of women who underwent an unscheduled C-section versus vaginal delivery. Lastly, functional gene inference demonstrated that pre-pregnancy obesity was associated with an increased abundance of genes encoding for the biosynthesis of secondary metabolites pathway in milk (coefficient = 0.0024, PFDR < 0.1). CONCLUSIONS: Human milk has a diverse microbiota of which its diversity and differential abundance appear associated with maternal BMI, glucose tolerance status, mode of delivery, and ethnicity. Further research is warranted to determine whether this variability in the milk microbiota impacts colonization of the infant gut.

Accumulation of genetic variants associated with immunity in the selective breeding of broilers.

BACKGROUND: To satisfy an increasing demand for dietary protein, the poultry industry has employed genetic selection to increase the growth rate of broilers by over 400% in the past 50 years. Although modern broilers reach a marketable weight of ~ 2 kg in a short span of 35 days, a speed twice as fast as a broiler 50 years ago, the expedited growth has been associated with several negative detrimental consequences. Aside from heart and musculoskeletal problems, which are direct consequences of additional weight, the immune response is also thought to be altered in modern broilers. RESULTS: Given that identifying the underlying genetic basis responsible for a less sensitive innate immune response would be economically beneficial for poultry breeding, we decided to compare the genomes of two unselected meat control strains that are representative of broilers from 1957 and 1978, and a current commercial broiler line. Through analysis of genetic variants, we developed a custom prioritization strategy to identify genes and pathways that have accumulated genetic changes and are biologically relevant to immune response and growth performance. Our results highlight two genes, TLR3 and PLIN3, with genetic variants that are predicted to enhance growth performance at the expense of immune function. CONCLUSIONS: Placing these new genomes in the context of other chicken lines, reveal genetic changes that have specifically arisen in selective breeding programs that were implemented in the last 50 years.

Global Analysis of the Fungal Microbiome in Cystic Fibrosis Patients Reveals Loss of Function of the Transcriptional Repressor Nrg1 as a Mechanism of Pathogen Adaptation.

The microbiome shapes diverse facets of human biology and disease, with the importance of fungi only beginning to be appreciated. Microbial communities infiltrate diverse anatomical sites as with the respiratory tract of healthy humans and those with diseases such as cystic fibrosis, where chronic colonization and infection lead to clinical decline. Although fungi are frequently recovered from cystic fibrosis patient sputum samples and have been associated with deterioration of lung function, understanding of species and population dynamics remains in its infancy. Here, we coupled high-throughput sequencing of the ribosomal RNA internal transcribed spacer 1 (ITS1) with phenotypic and genotypic analyses of fungi from 89 sputum samples from 28 cystic fibrosis patients. Fungal communities defined by sequencing were concordant with those defined by culture-based analyses of 1,603 isolates from the same samples. Different patients harbored distinct fungal communities. There were detectable trends, however, including colonization with Candida and Aspergillus species, which was not perturbed by clinical exacerbation or treatment. We identified considerable inter- and intra-species phenotypic variation in traits important for host adaptation, including antifungal drug resistance and morphogenesis. While variation in drug resistance was largely between species, striking variation in morphogenesis emerged within Candida species. Filamentation was uncoupled from inducing cues in 28 Candida isolates recovered from six patients. The filamentous isolates were resistant to the filamentation-repressive effects of Pseudomonas aeruginosa, implicating inter-kingdom interactions as the selective force. Genome sequencing revealed that all but one of the filamentous isolates harbored mutations in the transcriptional repressor NRG1; such mutations were necessary and sufficient for the filamentous phenotype. Six independent nrg1 mutations arose in Candida isolates from different patients, providing a poignant example of parallel evolution. Together, this combined clinical-genomic approach provides a high-resolution portrait of the fungal microbiome of cystic fibrosis patient lungs and identifies a genetic basis of pathogen adaptation.

The Arabidopsis ZED1 pseudokinase is required for ZAR1-mediated immunity induced by the Pseudomonas syringae type III effector HopZ1a.

Plant and animal pathogenic bacteria can suppress host immunity by injecting type III secreted effector (T3SE) proteins into host cells. However, T3SEs can also elicit host immunity if the host has evolved a means to recognize the presence or activity of specific T3SEs. The diverse YopJ/HopZ/AvrRxv T3SE superfamily, which is found in both animal and plant pathogens, provides examples of T3SEs playing this dual role. The T3SE HopZ1a is an acetyltransferase carried by the phytopathogen Pseudomonas syringae that elicits effector-triggered immunity (ETI) when recognized in Arabidopsis thaliana by the nucleotide-binding leucine-rich repeat (NB-LRR) protein ZAR1. However, recognition of HopZ1a does not require any known ETI-related genes. Using a forward genetics approach, we identify a unique ETI-associated gene that is essential for ZAR1-mediated immunity. The hopZ-ETI-deficient1 (zed1) mutant is specifically impaired in the recognition of HopZ1a, but not the recognition of other unrelated T3SEs or in pattern recognition receptor (PRR)-triggered immunity. ZED1 directly interacts with both HopZ1a and ZAR1 and is acetylated on threonines 125 and 177 by HopZ1a. ZED1 is a nonfunctional kinase that forms part of small genomic cluster of kinases in Arabidopsis. We hypothesize that ZED1 acts as a decoy to lure HopZ1a to the ZAR1-resistance complex, resulting in ETI activation.

Seasonal community succession of the phyllosphere microbiome.

The leaf microbiome is influenced by both biotic and abiotic factors. Currently, we know little about the relative importance of these factors in determining microbiota composition and dynamics. To explore this issue, we collected weekly leaf samples over a 98-day growing season from multiple cultivars of common bean, soybean, and canola planted at three locations in Ontario, Canada, and performed Illumina-based microbiome analysis. We find that the leaf microbiota at the beginning of the season is very strongly influenced by the soil microbiota but, as the season progresses, it differentiates, becomes significantly less diverse, and transitions to having a greater proportion of leaf-specific taxa that are shared among all samples. A phylogenetic investigation of communities by reconstruction of unobserved states imputation of microbiome function inferred from the taxonomic data found significant differences between the soil and leaf microbiome, with a significant enrichment of motility gene categories in the former and metabolic gene categories in the latter. A network co-occurrence analysis identified two highly connected clusters as well as subclusters of putative pathogens and growth-promoting bacteria. These data reveal some of the complex ecological dynamics that occur in microbial communities over the course of a growing season and highlight the importance of community succession.

Genomic analysis of the Kiwifruit pathogen Pseudomonas syringae pv. actinidiae provides insight into the origins of an emergent plant disease.

The origins of crop diseases are linked to domestication of plants. Most crops were domesticated centuries--even millennia--ago, thus limiting opportunity to understand the concomitant emergence of disease. Kiwifruit (Actinidia spp.) is an exception: domestication began in the 1930s with outbreaks of canker disease caused by P. syringae pv. actinidiae (Psa) first recorded in the 1980s. Based on SNP analyses of two circularized and 34 draft genomes, we show that Psa is comprised of distinct clades exhibiting negligible within-clade diversity, consistent with disease arising by independent samplings from a source population. Three clades correspond to their geographical source of isolation; a fourth, encompassing the Psa-V lineage responsible for the 2008 outbreak, is now globally distributed. Psa has an overall clonal population structure, however, genomes carry a marked signature of within-pathovar recombination. SNP analysis of Psa-V reveals hundreds of polymorphisms; however, most reside within PPHGI-1-like conjugative elements whose evolution is unlinked to the core genome. Removal of SNPs due to recombination yields an uninformative (star-like) phylogeny consistent with diversification of Psa-V from a single clone within the last ten years. Growth assays provide evidence of cultivar specificity, with rapid systemic movement of Psa-V in Actinidia chinensis. Genomic comparisons show a dynamic genome with evidence of positive selection on type III effectors and other candidate virulence genes. Each clade has highly varied complements of accessory genes encoding effectors and toxins with evidence of gain and loss via multiple genetic routes. Genes with orthologs in vascular pathogens were found exclusively within Psa-V. Our analyses capture a pathogen in the early stages of emergence from a predicted source population associated with wild Actinidia species. In addition to candidate genes as targets for resistance breeding programs, our findings highlight the importance of the source population as a reservoir of new disease.

A bacterial acetyltransferase destroys plant microtubule networks and blocks secretion.

The eukaryotic cytoskeleton is essential for structural support and intracellular transport, and is therefore a common target of animal pathogens. However, no phytopathogenic effector has yet been demonstrated to specifically target the plant cytoskeleton. Here we show that the Pseudomonas syringae type III secreted effector HopZ1a interacts with tubulin and polymerized microtubules. We demonstrate that HopZ1a is an acetyltransferase activated by the eukaryotic co-factor phytic acid. Activated HopZ1a acetylates itself and tubulin. The conserved autoacetylation site of the YopJ / HopZ superfamily, K289, plays a critical role in both the avirulence and virulence function of HopZ1a. Furthermore, HopZ1a requires its acetyltransferase activity to cause a dramatic decrease in Arabidopsis thaliana microtubule networks, disrupt the plant secretory pathway and suppress cell wall-mediated defense. Together, this study supports the hypothesis that HopZ1a promotes virulence through cytoskeletal and secretory disruption.

The effector-triggered immunity landscape of tomato against Pseudomonas syringae.

Tomato (Solanum lycopersicum) is one of the world's most important food crops, and as such, its production needs to be protected from infectious diseases that can significantly reduce yield and quality. Here, we survey the effector-triggered immunity (ETI) landscape of tomato against the bacterial pathogen Pseudomonas syringae. We perform comprehensive ETI screens in five cultivated tomato varieties and two wild relatives, as well as an immunodiversity screen on a collection of 149 tomato varieties that includes both wild and cultivated varieties. The screens reveal a tomato ETI landscape that is more limited than what was previously found in the model plant Arabidopsis thaliana. We also demonstrate that ETI eliciting effectors can protect tomato against P. syringae infection when the effector is delivered by a non-virulent strain either prior to or simultaneously with a virulent strain. Overall, our findings provide a snapshot of the ETI landscape of tomatoes and demonstrate that ETI can be used as a biocontrol treatment to protect crop plants.

The impact of gestational diabetes on functional capacity of the infant gut microbiome is modest and transient.

Gestational diabetes mellitus (GDM) is a metabolic complication that manifests as hyperglycemia during the later stages of pregnancy. In high resource settings, careful management of GDM limits risk to the pregnancy, and hyperglycemia typically resolves after birth. At the same time, previous studies have revealed that the gut microbiome of infants born to mothers who experienced GDM exhibit reduced diversity and reduction in the abundance of several key taxa, including Lactobacillus. What is not known is what the functional consequences of these changes might be. In this case control study, we applied 16S rRNA sequence surveys and metatranscriptomics to profile the gut microbiome of 30 twelve-month-old infants - 16 from mothers with GDM, 14 from mothers without - to examine the impact of GDM during pregnancy. Relative to the mode of delivery and sex of the infant, maternal GDM status had a limited impact on the structure and function of the developing microbiome. While GDM samples were associated with a decrease in alpha diversity, we observed no effect on beta diversity and no differentially abundant taxa. Further, while the mode of delivery and sex of infant affected the expression of multiple bacterial pathways, much of the impact of GDM status on the function of the infant microbiome appears to be lost by twelve months of age. These data may indicate that, while mode of delivery appears to impact function and diversity for longer than anticipated, GDM may not have persistent effects on the function nor composition of the infant gut microbiome.

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.

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

BACKGROUND: Environmental surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) through wastewater has become a useful tool for population-level surveillance. Built environment sampling may provide a more spatially refined approach for surveillance in congregate living settings. METHODS: We conducted a prospective study in 10 long-term care homes (LTCHs) between September 2021 and November 2022. Floor surfaces were sampled weekly at multiple locations within each building and analyzed for the presence of SARS-CoV-2 using quantitative reverse transcriptase polymerase chain reaction. The primary outcome was the presence of a coronavirus disease 2019 (Covid-19) outbreak in the week that floor sampling was performed. RESULTS: Over the 14-month study period, we collected 4895 swabs at 10 LTCHs. During the study period, 23 Covid-19 outbreaks occurred with 119 cumulative weeks under outbreak. During outbreak periods, the proportion of floor swabs that were positive for SARS-CoV-2 was 54.3% (95% confidence interval [CI], 52 to 56.6), and during non-outbreak periods it was 22.3% (95% CI, 20.9 to 23.8). Using the proportion of floor swabs positive for SARS-CoV-2 to predict Covid-19 outbreak status in a given week, the area under the receiver-operating characteristic curve was 0.84 (95% CI, 0.78 to 0.9). Among 10 LTCHs with an outbreak and swabs performed in the prior week, eight had positive floor swabs exceeding 10% at least 5 days before outbreak identification. For seven of these eight LTCHs, positivity of floor swabs exceeded 10% more than 10 days before the outbreak was identified. CONCLUSIONS: Detection of SARS-CoV-2 on floors is strongly associated with Covid-19 outbreaks in LTCHs. These data suggest a potential role for floor sampling in improving early outbreak identification.