Phytopathology®

Ralstonia pseudosolanacearum (Rps) belongs to the Ralstonia solanacearum species complex (RSSC). It is a vascular pathogen that causes lethal bacterial wilt disease in many plants, including tomato and eggplant. In this study, we infiltrated tomato leaves with the phytopathogenic bacterium at 109 CFU/mL and observed the development of necrotic scars in the infiltrated area at 48 hours post-infiltration. Interestingly, this response was followed by petiole bending toward the ground of the compound leaf. This was followed by the gradual senescence of the infiltrated leaflet only. In addition, the terminal leaflet infiltrated with the pathogen exhibited epinasty. None of the above symptoms were observed in leaves infiltrated with the known virulent deficient hrpB::{Omega} mutant. Surprisingly, all of the above symptoms were observed in leaves infiltrated with another well-known virulence-deficient mutant phcA::{Omega}. It indicated that the necrotic lesion caused in tomato leaves was hrp-dependent. Infiltration in eggplant leaves caused necrotic scarring and leaf senescence, which were relatively delayed. Necrotic scarring without petiole bending or senescence in tomato leaves was also observed due to infiltration of Pseudomonas aeruginosa SPT08, a tomato endophyte having plant growth promotion activity. The patho-phenotypes such as petiole bending, epinasty, and senescence observed in the case of tomato in this study were not reported earlier. We believe these phenotypes produced in tomato after leaf infiltration may be useful to study the virulence of this pathogen.

Soft rot Pectobacteriaceae (SRP) are among the most economically important plant pathogenic bacteria and are especially known to be problematic in potato production. The epidemiology of disease transmission has been investigated for almost a century, and several aspects have been highlighted as plausible infection routes. However, it is generally accepted that the major source of disease is the latently infected mother tuber, but several parameters are still influencing disease prevalence including contaminated equipment, soil water status as well as temperature. Management of the disease is limited to hygiene practices, dry storage and seed certification systems but several studies have also proven biocontrol agents such as bacteriophages (phages) as promising tools. Despite the severity of SRP on potato production, little is known about the genetic diversity of SRPs in Denmark, and since only few isolates are available, the possibility to design a broadly effective phage cocktail is limited. Here we describe a three-year field study utilizing an agri-citizen science approach where Danish farmers provided symptomatic potato plants or tubers, together with metadata such as date, location, potato variety and origin. By using whole genome sequencing (Illumina and Nanopore) together with metadata we were able to investigate and monitor the epidemiological disease spread across the country using 103 complete genomes, sampled across all three years. In this study we provide epidemiological evidence of disease origins and a suite of phages that could be used as a biocontrol tool for early disease intervention. Our results revealed several clonal clades across diverse locations (SNPs < 20) which strongly indicate common origin. A total of 17 Pectobacterium phages were tested and did target > 80% of clonal clades. Based on the clonality across the soft rot isolates we propose the possibility to set in early on using phages targeting strains relevant for soft rot development, with the possibility of a surveillance program together with customizing the phage preference.

Whitebark pine (Pinus albicaulis), a wide-ranging high-elevation conifer in western North America, is listed as threatened in the U.S. and as endangered in Canada. A major threat to whitebark pine is the non-native, invasive white pine blister rust disease, caused by the fungal pathogen Cronartium ribicola. In many pathosystems (including white pine blister rust), seedling inoculation trials are used to identify parent trees with genetic resistance. However, many of these trials use only one spore density for inoculation, and little information exists on the effectiveness of quantitative disease resistance (QDR) under varying spore densities and the corresponding implications for field performance. In this study, we examine the levels of infection and survival present within six whitebark pine seedling families previously rated for QDR (three susceptible and three resistant families) under six widely varying inoculum densities. The susceptible families showed very high infection and mortality at all inoculum densities, while performance of the resistant families varied with spore density treatment. The information gathered from the study will be useful in updating the projections of the future of whitebark pine populations under field conditions in areas of different rust hazard. The results also serve as a caution to those working in other pathosystems where seedling inoculation trials based on one spore density level are used to rate the resistance level of parent trees and their associated progeny.

Aphanomyces euteiches, the causative agent of Aphanomyces root rot (ARR), is of major concern for pea and other legume crops globally. This oomycete pathogen causes substantial decreases in crop yields, is unaffected by most fungicides, and persists in the soil for many years via its resilient oospores. Given the significance of pea crops in sustainable agriculture, namely the ability to fix nitrogen and act as a sustainable protein source, solutions to ARR are of high importance. We used RNA-seq in a novel strain of Pseudomonas donghuensis to identify two biosynthetic gene clusters under GacA/S control that are involved in producing bioactive molecules capable of inhibiting A. euteiches. Based on similarity to other reported clusters in Pseudomonas, the first is predicted to encode for a pseudoiodinine compound, while the second is predicted to produce the siderophore 7-hydroxytropolone. Individual knockouts of each cluster showed loss of inhibitory action of P. donghuensis NRC29 against A, euteiches in vivo. This is the first report highlighting the potential of P. donghuensis and the products of the two identified biosynthetic pathways as biocontrol agents for A. euteiches. Further investigations into the efficacy of P. donghuensis NRC29 and its metabolites in inhibiting A. euteiches in field trials will be of high value in developing sustainable strategies for ARR mitigation. ImportanceModern fungicidal treatments for control of root rot in pulse crops are ineffective for control of A. euteiches, leaving limited strategies for management of A. euteiches infected fields. We describe a novel P. donghuensis strain with potential for biocontrol against this persistent pathogen. Given the economic value of peas and other pulses globally, further work into harnessing the bioactive metabolites produced by this strain into a practical in-field treatment will be valuable.

Soybean (Glycine max [L.] Merr.) productivity is frequently compromised by soil-borne pathogens. Macrophomina phaseolina (Mp), the causal agent of charcoal rot, can produce important soybean yield losses especially when hot and dry weather prevails. Integrating biological control agents with chemical seed treatments represents a promising strategy for improving disease management. This study aimed to (i) assess the in vitro compatibility of Trichoderma koningiopsis with commercial fungicide seed treatments, and (ii) evaluate the field performance of T. koningiopsis, alone or combined with compatible fungicides, across three soybean growing seasons. Compatibility assays revealed fungicide-specific effects, with Acronis(R) classified as non-fungitoxic and Topseed Extra as moderately fungitoxic. Across field seasons, Mp inoculation reduced seedling emergence, while several seed treatments improved emergence compared to the inoculated control, however, treatment effects varied markedly among years. Disease severity did not differ significantly among treatments in any season, and yield responses were strongly modified by environmental conditions rather than treatment effects. Temperature-response assays showed that T. koningiopsis exhibited optimal growth between 28 to 30{degrees}C and complete inhibition above 40{degrees}C, indicating high thermal sensitivity. The results demonstrate that T. koningiopsis can be integrated with compatible fungicides and may enhance early stand establishment under favorable conditions, but its field performance is strongly limited by high temperatures. These findings highlight the importance of environmental conditions when biological seed treatments are used.

There is disagreement on whether secondary endosymbionts are found in the major cereal pest aphid, Rhopalosiphum padi. Some papers report a diversity of secondary bacterial endosymbionts while others have failed to find evidence of these bacteria in this species. Here we revisit this issue by summarizing the relevant literature and through additional sampling of the species in Australia, China and Denmark using a combination of molecular approaches. We find a general absence of secondary endosymbionts beyond the obligate endosymbiont Hamiltonella defensa in R. padi. While the inconsistency in survey results may reflect rapid changes in endosymbiont turnover in populations and/or the impact of ecological factors such as host plant type on endosymbiont diversity, we are concerned that technical issues may be at least partly responsible for inconsistencies in the literature. This leads us to emphasize the importance of multiple sources of evidence required to establish and characterize endosymbiont infections, including PCR and qPCR assays, DNA Sanger sequencing and 16SrRNA gene metabarcoding. We note that several major aphid pests show a low incidence of secondary endosymbionts which raises issues about the importance of these endosymbionts in aphids that constitute pests, even though endosymbionts can in some cases increase host fitness and therefore pest impact.

Accurate and reproducible assessment of foliar disease severity is essential for evaluating the performance of heterogeneous plant communities and understanding host-pathogen interactions. However, traditional visual scoring methods remain subjective, with limited precision, and difficult to scale in large phenotyping experiments. Here, we present a semi-automated image analysis workflow designed to quantify multiple foliar disease symptoms simultaneously on wheat flag leaves sampled from varietal mixtures. The workflow combines three methodological components: (i) a standardized protocol for leaf sampling and imaging, (ii) supervised machine learning segmentation using Random Forest implemented in Ilastik to classify multiple symptoms (powdery mildew and yellow rust), and (iii) a graphical user interface facilitating pipeline deployment by non-specialist operators. To evaluate the influence of image representation on classification performance, four color spaces (RGB, HSV, HLS, LAB) were systematically compared. The approach was validated using images of durum wheat flag leaves collected from a field experiment assessing eight-way varietal mixtures under natural fungal pressure. Cross-validation against manually annotated images demonstrated high segmentation accuracy across all symptom. Comparison among color spaces revealed only minor differences in performance. Overall, this workflow offers a cost-effective, annotation-efficient and reproducible alternative to deep learning approaches, leveraging open-source and actively maintained tools while requiring limited training data and enabling objective, reproducible and scalable disease phenotyping.

O_LIHost specialization is a major driver of genetic structure in fungal plant pathogens, but it remains unclear whether specialization on different cereal hosts prevents sexual recombination when mating-type compatibility is retained. We addressed this question in stripe rust, caused by Puccinia striiformis, by crossing wheat-adapted P. striiformis f. sp. tritici and barley-adapted P. striiformis f. sp. hordei, two divergent host-adapted forms that share common barberry (Berberis vulgaris) as a sexual host. C_LIO_LIControlled reciprocal crosses on barberry produced 18 aeciospore-derived progeny, demonstrating that wheat- and barley-adapted Puccinia striiformis can undergo sexual recombination despite strong host specialization during asexual infection. Chromosome-scale parental assemblies placed the homeodomain (HD) mating-type locus, containing bW-HD1 and bE-HD2, on chromosome 2 and the pheromone receptor (PR) mating-type locus, containing STE3 and mfa genes, on chromosome 6. HD restriction genotyping showed biparental inheritance in all progeny, with each progeny carrying one HD haplotype from each parent. Together with conservation of PR-associated coding sequences and amplification of STE3-associated markers in progeny, these results are consistent with retention of tetrapolar mating across the two host-adapted lineages. C_LIO_LIHost interaction phenotypes were assessed across wheat and barley differentials, near-isogenic lines and wild relatives. The parental isolates retained contrasting wheat- and barley-restricted profiles, whereas progeny did not reproduce either parental virulence profile, but instead showed recombinant infection patterns, including compatibility with both wheat and barley genotypes. C_LIO_LIThese findings indicate that host specialization in Puccinia striiformis does not necessarily prevent sexual compatibility on a shared alternate host. Together with retention of tetrapolar mating, alternate-host sexual reproduction may provide a route for genetic exchange between host-specialized pathogen populations, enabling recombination to generate new combinations of host-interaction traits when divergent pathogen lineages mate on a shared alternate host. C_LI

Tomato fruit blotch virus (ToFBV) is an emerging multipartite positive-sense RNA virus associated with blotchy symptoms on tomato fruits and classified within the genus Blunervirus (family Kitaviridae). Despite its increasing agricultural relevance, the study of ToFBV has been hindered by the lack of mechanical transmissibility and the difficulty in reproducing infections under controlled conditions. In this work, we report a preliminary step toward the development of the first infectious agroclone system for ToFBV, based on full-length cDNA copies of its four genomic RNAs. We demonstrate that the cloned viral genome is capable of initiating cell autonomous replication in Nicotiana benthamiana, as indicated by the accumulation of negative-sense RNA intermediates in infiltrated tissues. To further validate the system, RNA3 was engineered to express GFP, enabling visualization of infection foci and confirming active viral replication in both N. benthamiana and tomato. Functional assays of RNA4-encoded proteins demonstrated that it encodes a movement protein capable of complementing movement-deficient viral vectors and a putative suppressor of post-transcriptional gene silencing (PTGS). Together, these results establish a versatile reverse genetics platform for ToFBV, providing new insights into the replication and functional organization of blunerviruses and enabling future studies on virus-host interactions, pathogenicity, and control strategies.

Common bean (Phaseolus vulgaris) is an important crop in Canada and globally. Like other legumes, common bean (Phaseolus vulgaris) establishes symbiotic interactions with nitrogen fixing bacteria called rhizobia. However, nitrogen fixation by rhizobia in association with common bean is often suboptimal, constraining its productivity and necessitating the application of nitrogen fertilizer. To support the development of high-performing, locally adapted rhizobial inoculants for Ontario common bean growers, we isolated 216 common bean-nodulating rhizobia from southern Ontario soils using a nodule trapping approach with four common bean cultivars. Whole genome sequencing followed by phylogenomic analyses of the 216 rhizobial isolates revealed substantial diversity, assigning them to 11 Rhizobium species, including two novel species. Nearly all isolates belong to the symbiovar phaseoli, spanning the nodC {gamma}-a, {gamma}-b, and alleles, with four isolates belonging to the symbiovar gallica. Soil origin had a significant impact on the species-level community composition recovered during the nodule trapping experiments, indicative of biogeographical structuring of common bean-nodulating rhizobia across southern Ontario. In contrast, host trapping cultivar had only a minor influence of the recovered Rhizobium population diversity. Greenhouse assays demonstrated that one of the novel Rhizobium species exhibited the highest average symbiotic effectiveness, although high-quality isolates were found across multiple species. Together, these results revealed a diverse and genomically variable Rhizobium community capable of forming effective symbioses with common bean in southern Ontario soils. Importantly, our genome-sequenced Rhizobium collection will serve as a valuable resource for identifying competitive and high-quality strains for the development of inoculants tailored to Ontario common bean production. IMPORTANCECommon bean is a globally important food crop, yet its productivity is often limited by suboptimal nitrogen fixation, forcing growers to rely on synthetic fertilizers. Consequently, identifying high-performing, locally adapted inoculant strains is essential for reducing dependence on synthetic nitrogen fertilizers and improving the sustainability of temperate agroecosystems. Our study provides a genome-sequenced collection of common bean-nodulating Rhizobium from southern Ontario, revealing substantial species and genomic diversity across sampling locations. Greenhouse studies allowed us to identify multiple isolates, including isolates from a novel Rhizobium species, that consistently fix nitrogen with, and enhance the growth of, common bean plants. Our findings highlight strong biogeographical structuring of rhizobial communities and demonstrate that Ontario soils already harbour strains with high symbiotic potential. In addition, our Rhizobium collection represents a foundational resource to support future inoculant development and enables future work on the ecology, evolution, and applied optimization of legume-rhizobium symbioses.

Pairwise analysis of genomic and spatial data offers opportunities to identify and estimate the associations between covariates and the transmission of pathogens between individuals. However, such pairwise analyses are computationally intensive, and may not be feasible to conduct given the high dyad count in even moderately sized datasets. Here we compare two approaches to increase the efficiency of pairwise analysis for large datasets. We quantify and compare the performance of divide-and-conquer Bayesian model fitting and pairwise case-control approaches for estimating associations between individual- and pair-level covariates and shared membership in a transmission cluster. We utilize a large dataset (n=4,154) of spatially-referenced, genomically-sequenced Mycobacterium tuberculosis isolates collected from a single city for this analysis. We find that the case-control approach produces unbiased estimates of effect sizes with expected credible interval coverage and is more robust than the divide-and-conquer method when effect sizes are large. Thus, we recommend using the case-control approach with at least three controls per case to downscale datasets for pairwise analysis when analysis of the entire dataset is not possible. This approach mitigates the computational challenges of pairwise Bayesian modeling on datasets that require significant computational resources while maintaining desired inferential properties. Author SummaryPairwise analyses of large datasets to study pathogen transmission are computationally demanding because they typically require simultaneous analysis of each possible pair of individuals in a dataset; as datasets become larger these analyses often are not feasible to conduct even with access to high-performance computing resources. In this work, we compare a case-control approach and divide-and-conquer approaches for more efficient pairwise analysis of large datasets. Using a large dataset of Mycobacterium tuberculosis isolates including genetic and spatial data, we investigate the performance of each method for estimating the associations between host covariates and genetic clustering of isolates. We find that the case-control approach is generally preferred over methods which first divide the data into subsets and then combine results. While additional extensions of these analyses are needed to test the generality of these findings to other data settings, this work provides a practical way forward for the pairwise analysis of large datasets to study pathogen transmission.

Meloidogyne incognita is a major plant-parasitic nematode responsible for substantial yield losses in tomato worldwide. Current control strategies rely heavily on chemical nematicides, which raise environmental concerns and face increasing regulatory restrictions, underscoring the need for sustainable alternatives. Here, we show that foliar application of an aqueous extract from cavalcade (Centrosema pascuorum) enhances tomato resistance against M. incognita. Pre-inoculation treatment with cavalcade extract prior to inoculation with root-knot nematodes (RKN) significantly reduced root gall formation, delayed nematode development, and limited second-stage juvenile penetration compared with untreated infected controls, whereas post-inoculation application conferred partial protection. Transcriptomic analyses revealed the activation of multiple defense-related pathways, including salicylic acid- and jasmonic acid-associated signaling and phenylpropanoid metabolism, supported by the upregulation of PR1 and PAL. Additional induction of lipid transfer proteins, leucine-rich repeat receptor-like kinases, resistance proteins, mitochondrial calcium uniporter, and GA2ox5 suggests coordinated activation of pathogen recognition, calcium signaling, and hormone-regulated defense networks. These findings demonstrate that cavalcade extract primes broad-spectrum defense responses in tomato and highlight its potential as an environmentally sustainable strategy for nematode management.

Key message Characterized and unknown septoria nodorum blotch susceptibility/resistance genes were identified in contemporary U.S. hard winter wheat. The necrotrophic fungus Parastagonospora nodorum is the causal agent of septoria nodorum blotch (SNB) of wheat. To determine the prevalence of SNB sensitivity genes in a contemporary U.S. hard winter wheat (HWW), we evaluated a panel of 619 breeding lines and cultivars against five P. nodorum isolates and five necrotrophic effectors (NEs), SnToxA, SnTox1, SnTox3, SnTox267 and SnTox5, and genotyped the panel using genotyping-by-sequencing (GBS) markers and diagnostic Kompetetive-allele specific PCR (KASP) markers for the sensitivity genes Tsn1-B1, Snn1-B1, and Snn3-B1/B2. GBS analysis identified 34,357 GBS-single nucleotide polymorphism (SNP) markers. Evaluations against P. nodorum isolates showed that 40-67% of the genotypes were susceptible in the panel. Toxin infiltration assays showed that 54%, 2%, 37%, 13%, and 15% of the genotypes were sensitive to SnToxA, SnTox1, SnTox3, SnTox267, and SnTox5, respectively. Diagnostic KASP markers for Tsn1-B1, Snn1-B1, and Snn3-B1/B2 showed prediction accuracies of 98%, 75%, and 92% for the corresponding effectors SnToxA, SnTox1, and SnTox3, respectively. Genome-wide association studies (GWAS) not only confirmed the presence of the previously characterized sensitivity genes Tsn1-B1, Snn1-B1, Snn2, Snn3-B1/B2, and Snn5-B1, but also identified new loci to be associated with responses to P. nodorum isolates and NEs. Of which, Qsnb.osu-2AS on chromosome 2AS was associated with responses to all five isolates. We developed KASP markers KASP_S4B_643615365, KASP_ S2D_16184991, and KASP_S2A_9833162 linked to Snn5-B1, Snn2, and Qsnb.osu-2AS, respectively. These findings should guide breeding for SNB resistance in hard winter wheat.

Norway spruce (Picea abies) responds to attacks by the spruce bark beetle (Ips typographus) through the rapid activation of local defense mechanisms, but field studies can be difficult to standardize due to variable attack pressure and environmental heterogeneity. Here, we developed a phytotron-based assay that mimics early beetle-associated stress using insect-derived protein extracts, enabling reproducible molecular analyses under controlled conditions. Ten-week-old spruce seedlings were stem-treated with mock buffer or beetle protein extracts, followed by transcriptomic analyses of stem tissues and targeted metabolomic profiling of needles at 2 and 48 h post-inoculation. RT-qPCR analysis revealed rapid transcriptional activation of signaling and defense genes in Norway spruce, with NP-40-based protein extracts producing the most consistent early response. RNA-seq analysis revealed transcriptional dynamics, with 488 differentially expressed genes detected at 2 h and 84 at 48 h post-inoculation relative to mock-treated controls. Early responses at 2 h were characterized by activation of genes associated with immune perception and signal transduction. By 48 h, the response shifted toward accumulation of transcripts encoding defense proteins such as chitinases, defensins, proteinase inhibitors, and pathogenesis-related (PR) proteins. Importantly, a substantial proportion of differentially expressed genes overlapped with those previously identified in mature Norway spruce trees during pioneer bark beetle attack under field conditions, supporting the biological relevance of the assay. In contrast, targeted analyses of secondary metabolites performed in needle tissue revealed limited systemic changes across time points, suggesting that early induced defenses may remain largely localized to the stem. Together, these results demonstrate that beetle-derived proteins trigger a rapid and temporally structured defense response in Norway spruce seedlings and establish a reproducible elicitor-based platform for dissecting conifer immune responses and screening spruce genotypes for bark beetle resistance. HighlightBark beetle protein elicitors trigger temporally structured immune responses in Norway spruce seedlings that overlap with responses observed in mature trees, with rapid immune signaling at 2 h followed by defense protein accumulation at 48 h.

Tomato brown rugose fruit virus (Tobamovirus fructirugosum) is an emerging virus that affects tomatoes, capsicum, and chili. Since its first detection in Jordan in 2015, the virus was reported in more than 40 countries across all the continents. In Morocco, the virus was reported for the first time in October 2021. However, its genetic diversity remains unexplored. In this work, we used a collection of tomato fruits from local markets to investigate the variability of the virus in the country. We explored the different pressures acting on the N-terminus of the RNA-dependent RNA polymerase, the movement protein, and the coat protein genes. Then, we used haplotype network analyses to reveal the population structure within the Moroccan isolates and studied their relationships with the ones from the world. We found that genetic diversity is low, which is consistent with the global situation. No signatures of diversifying selection were detected across the analyzed genes. However, the virus sequences from Morocco showed a clear geographic structure, suggesting that geographic factors probably combined with agricultural practices may contribute to shaping the population structure of ToBRFV in Morocco.

Belemia belongs to Nyctaginaceae and comprises two species of delicate vines. Both species are endemic to Brazil. Belemia fucsioides, the type species, described in 1981, occurs in a restricted area of the Atlantic Forest in southeastern Brazil. Belemia cordata, described in 2020, is known from only two records from the same area in the Cerrado of northern Brazil. Here, we describe the taxonomic history of Belemia and provide the first synopsis for the genus. We include species description, distribution map, identification key, and anatomical data. We used field observations over the past decade and modeled anthropogenic changes in the species range to conduct a conservation assessment in accordance with the IUCN Red List criteria. Conservation assessments indicate significant concerns for Belemia, classified as either endangered (B. fucsioides) or critically endangered (B. cordata). The species are threatened primarily by habitat loss to land used for agriculture, forestry, and livestock production. This study contributes to ongoing initiatives exploring plant diversity in the Neotropics and supports efforts to identify threats to biodiversity.

Accurate quantification of leaf lesion severity is essential for plant disease research and phenotyping but is often limited by subjective visual scoring and time-intensive manual image analysis. We present LIME, a fully automated, open-source image analysis pipeline for high-throughput quantification of leaf lesions from disease assay images. LIME integrates zero-shot leaf segmentation using the Segment Anything Model with a convolutional neural network for lesion area estimation. Applied to Arabidopsis thaliana leaves infected with Sclerotinia sclerotiorum, the proposed approach achieved a mean absolute percentage error of 12.9%, comparable to observed intrarater variability in manual scoring. Stratified evaluation across lesion-size groups demonstrated consistent prediction accuracy for small, intermediate, and large lesions, and comparative analysis showed that the deep learning-based model substantially outperformed color-based baseline methods. Under GPU-accelerated execution, LIME processed complete assays containing approximately 200 leaves in 15 minutes, representing an approximate 13-fold reduction in processing time relative to manual annotation. Together, these results indicate that LIME enables objective, reproducible, and scalable quantification of leaf lesion severity in standardized plant pathology assays. The pipeline is released as an open-source tool to support quantitative phenotyping studies.

Stripe rust and leaf rust, caused by Puccinia striiformis f. sp. tritici and P. triticina, respectively, are the most destructive wheat diseases in the southern Great Plains. Green Hammer is a hard red winter wheat (HRWW) cultivar released by Oklahoma State University in 2018 and has demonstrated a stable adult plant resistance to stripe rust and race-specific seedling resistance to leaf rust. To identify and map rust resistance loci, 109 doubled haploid (DH) lines derived from the cross between Green Hammer and another HRWW cultivar, Lonerider, were developed. Lonerider showed adult plant resistance to stripe rust but was susceptible to multiple P. triticina races. The DH lines were evaluated for stripe rust at the adult plant stage in greenhouse and field environments across Oklahoma, Kansas, and Washington, and for leaf rust at the seedling stage against seven U.S. P. triticina races and at the adult plant stage in Oklahoma and Texas. Genotyping-by-sequencing generated 6,078 polymorphic single-nucleotide polymorphisms used for genetic mapping. Quantitative trait loci (QTL) analysis identified 14 stripe rust and 8 leaf rust resistance QTL. For stripe rust, a major QTL in Green Hammer, QYr.osughln-2AS, was identified in the proximity of the 2NvS translocation. Three other major stripe rust resistance QTL were identified in Lonerider on chromosomes 2AL (two QTL) and 2BS (one QTL). For leaf rust, QLr.osughln-1DS and QLr.osughln-2DS.1 were the two major QTL identified in Green Hammer and most likely correspond to the all-stage resistance genes Lr21 and Lr39, respectively. In this study, we identified previously characterized genes as well as unknown genes that can be utilized in wheat breeding programs to enhance resistance to leaf rust and stripe rust.

Cyclic diguanosine monophosphate (c-di-GMP) is a ubiquitous bacterial second messenger that regulates diverse cellular processes, including colony morphology, motility, biofilm formation, and virulence. It is synthesized by diguanylate cyclases (DGCs) containing the GGDEF domain and degraded by phosphodiesterases (PDEs) containing the EAL domain. However, studies on the genetic and physiological characteristics of c-di-GMP metabolism in Pantoea ananatis are lacking. In this study, we identified 26 predicted c-di-GMP metabolism-related genes in the P. ananatis PA13 genome: 9 encode GGDEF-only domain proteins, 5 encode dual GGDEF/EAL domain proteins, and 12 encode EAL-only domain proteins. We constructed overexpression strains and mutants of 26 DGC- and PDE-encoding genes, and then assessed their Congo Red binding, mucoid and rugose phenotypes, pellicle formation, and swimming motility. We identified 14 of 26 DGC and PDE proteins that affect phenotype changes. Among the 26 DGC- and PDE-overexpressing strains, 13 exhibited the phenotypic changes described above, with some showing alterations in multiple phenotypes simultaneously. Notably, overexpression of dgcM induced changes across all phenotypes. Among the 26 DGC and PDE mutants, the pdeC mutant increased pellicle formation and Congo red binding, the pdeM mutant reduced the mucoid phenotype, and the pdeS mutant, which shows high similarity to ydiV, an anti-FlhD factor, increased swimming motility. Overexpression strains and mutants of 14 DGC and PDE proteins that exhibited phenotypic changes had higher intracellular c-di-GMP levels than the wild type. This study provides important insight into the role of the c-di-GMP network in the plant pathogen P. ananatis. IMPORTANCEPantoea ananatis is a versatile bacterium that causes significant diseases in various economically important plants. To survive and infect hosts, bacteria use a key signaling molecule called c-di-GMP to switch between swimming freely and forming protective communities known as biofilms. Despite its importance, the specific genes governing this signaling network in P. ananatis remained unknown. In this study, we systematically identified and characterized 26 genes responsible for regulating c-di-GMP levels in P. ananatis PA13. By analyzing mutants and overexpressing these genes, we pinpointed 14 critical factors that control essential behaviors such as motility, pellicle formation, and colony appearance. Notably, we discovered specific genes, such as dgcM and pdeS, that act as master regulators of these traits. This comprehensive functional map of the c-di-GMP network provides essential insights into how this pathogen adapts to its environment, offering potential targets to control plant infections.

Bacterial spot is a consistent threat to global tomato and pepper productions; however, Ohios fresh market production currently lacks the updated surveillance data necessary to provide accurate management solutions. While traditional diagnostics focus on identification of a single causal agent, shotgun metagenomic sequencing (MGS) offers a comprehensive view of the infection court. An assignment-first MGS workflow was developed and validated in this study, utilizing Kraken2 databases to extract Xanthomonas species associated with bacterial spot and to characterize the microbial communities of bacterial spot in Ohio production systems. Through in silico spiking experiments, thresholds were established for bacterial spot identification. Species and pathovar identification via average nucleotide identity (ANI) remained accurate at abundance as low as 0.1%. A minimum of 2% Xanthomonas reads were required for high genome completeness (BUSCO >90%) and 3% for reliable type III secretion system (T3SS) effector profiling. Analysis of 63 samples from fresh-market production fields identified Xanthomonas hortorum pv. gardneri, Xanthomonas euvesicatoria pv. euvesicatoria, and Xanthomonas arboricola residing in symptomatic samples, alongside other taxa including Pseudomonas and Stenotrophomonas. Phylogenetic comparisons of metagenome-assembled genomes (MAGs) were comparable to whole genome sequences (WGS) from the same samples, supporting the reliability of culture-independent diagnostics. These results provide a robust framework for utilizing metagenomics as a diagnostic tool, expanding our knowledge of bacterial spot population structure in Ohio, and uncovering the bacterial communities associated with bacterial spot.