Phytopathology最新文献

Osthole exhibits strong inhibitory activity against phytopathogenic fungi; however, its antifungal mechanism remains unclear. This study assessed osthole's inhibitory effects on several phytopathogenic fungi, revealing a half-maximal effective concentration of 73.03 μg/ml against the hyphal growth of Botrytis cinerea. Micromorphological analysis showed that osthole caused abnormalities in the hyphae, including unclear organelle boundaries and organelle dissolution. Integrated transcriptomic and metabolomic assays and correlation analysis indicated that osthole induced differentially expressed genes and differentially abundant metabolites, which were enriched particularly in the pathways of glyoxylate and dicarboxylate metabolism, tyrosine metabolism, glycerophospholipid metabolism, fructose and mannose metabolism, citrate cycle, biosynthesis of unsaturated fatty acids, and ABC transporters. Molecular docking and molecular dynamics simulation assays demonstrated that osthole binds stably to amidase, a key enzyme in energy metabolism, with a relatively lower binding energy of -8.5 kcal/mol compared with osthole's analogs, suggesting that amidase may be a potential target protein in the fungus. A microscale thermophoresis assay indicated that the dissociation constant (Kd) value for osthole binding to amidase was significantly lower compared with that of osthole's analog 7-methoxycoumarin. Overall, this study demonstrates that osthole disrupts energy metabolism, nitrogen metabolism, substance transport, and the metabolism of the hyphal cell wall and cell membrane, potentially targeting the amidase of B. cinerea. These findings highlight the potential of osthole for controlling gray mold.

How host genotype shapes pathogen tissue tropism remains poorly understood. Vascular and nonvascular tissues represent distinct habitats within a plant for bacteria to colonize. Host plants often utilize different mechanisms to defend themselves against vascular and nonvascular pathogens, and mechanisms of resistance employed by the host can vary by organ. Xanthomonas vasicola pv. vasculorum (Xvv) is an emerging bacterial maize pathogen, and this pathosystem offers an opportunity to study how host resistance differs in response to the vascular and nonvascular lifestyles exhibited by a single bacterial phytopathogen. We used different inoculation techniques to induce vascular and nonvascular disease and evaluated maize populations using both techniques to map resistance to vascular and nonvascular disease caused by Xvv. Xvv can colonize both vascular and nonvascular tissues, depending on the genotype. Different inoculation techniques can be used to induce vascular or nonvascular colonization. Independent loci control variation in resistance to Xvv during vascular and nonvascular pathogenesis. We confirmed the role of those regions in resistance to vascular and nonvascular infection. This study offers insights into how host resistance shapes how bacterial pathogens adapt to both vascular and nonvascular lifestyles. We show that host genotype can dictate which tissues a pathogen can infect. This system can serve as a model to understand tissue-specific host resistance to plant pathogens and tissue specificity in pathogens.

Xanthomonas oryzae pv. oryzae (Xoo) causes bacterial leaf blight (BLB), a major rice disease causing up to 70% yield loss in Asia and West Africa. First described in Japan in 1884 and later reported in West Africa in the 1970s, BLB recently emerged in East Africa, with an epidemic reported in Tanzania in 2019. Remarkably, the disease was detected for the first time in Madagascar the same year, representing a serious threat to food security. To investigate the origin of BLB in Madagascar, we isolated 73 Xoo strains from symptomatic rice leaves collected between 2019 and 2023. MLVA genotyping revealed 19 haplotypes forming a single clonal complex, indicating low diversity and a likely recent introduction. In order to come up with disease control strategies, IRBB-based race-typing was achieved and identified four resistance genes (Xa8, xa13, Xa21, Xa23) that confer resistance to all Malagasy strains tested, while the 19 Malagasy varieties assessed were susceptible. The analysis of SWEET knock-out lines confirmed that Malagasy strains rely on the susceptibility gene OsSWEET11 for full virulence. Whole-genome sequencing and TALEs repertoire analyses of two strains allowed the identification of a PthXo1 ortholog predicted to induce OsSWEET11. SNP-based phylogenetic analyses clustered Malagasy strains within Asian lineages, most closely related to strains originated from India. Malagasy strains did not cluster with recently reported Tanzanian Xoo, suggesting independent introductions. Overall, our study demonstrates that BLB in Madagascar results from a recent and single introduction from Asia and identifies effective resistance genes for deployment.

Trichoderma Gene Prediction Web server (TGP-WEB) is designed for accurate gene prediction in genomes of Trichoderma species, the biological control agents and the plant-beneficial microorganisms. It employs a hybrid gene prediction strategy, combining ab initio (Augustus and GeneMark) and homology-based (Braker utilizing fungal protein sequences from NCBI Refseq database) methods. Predictions are integrated and prioritized using a ranking framework, followed by functional assessment via domain annotation. After uploading a single-genome FASTA file, users can download TGP-WEB prediction results (including GFF3 files with gene locations, and FASTA files for both the predicted nucleotide and amino acid sequences) within ~4 hours. TGP-WEB demonstrates high accuracy in gene prediction across 177 genomes. When benchmarked against 42 published genomes with annotated gene sets available on NCBI, it recovers more than 90.00% of reported genes in 37 (88.00%) genomes. For 135 previously unannotated genomes, TGP-WEB generates complete gene sets, now available on the web server. BUSCO evaluation shows greater than 97.00% completeness for 94.92% (168/177) of genomes. TGP-WEB predictions enable the identification of 2100 single-copy genes from Trichoderma genomes. These genes are used to construct a robust phylogenetic tree, which clarifies the taxonomy of 49 strains. The robust performance of TGP-WEB prediction will contribute to the increasing studies of Trichoderma genomes, and it is freely available from www.fungalgenomics.cn/geneprediction.

The family Caulimoviridae comprises plant-infecting pararetroviruses that replicate by reverse transcription and encapsidate a circular double-stranded DNA genome. They can occur as episomal (encapsidated and replicative forms) and endogenous forms integrated into the host genome. Some endogenous sequences can give rise to episomal forms. In this study, we report and characterize a new badnavirus infecting Pelargonium × hortorum. We propose the name Pelargonium vein banding virus (PVBV). The episomal genome is 7,586 bp in length. Endogenous PVBV (ePVBV) DNA was identified in healthy plants and characterized. Southern blotting and PCR suggest that in many cultivars, the ePVBV consists of a tandem array of the complete PVBV genome. The ePVBV tandem array was not detected in 'Maverick White'. The major parents of P. × hortorum hybrids are P. zonale and P. inquinans. P. zonale contained ePVBV, but P. inquinans did not. The sequence of ePVBV recovered from the cultivar 'BullsEye Salmon' was >99% identical to the episomal sequence. Agroinoculation experiments demonstrated that ePVBV is infectious. Bacilliform-shaped virions with a modal particle length of 144 nm and 33 nm in diameter were recovered from leaves of agroinfected Maverick White exhibiting mosaic symptoms and chlorosis surrounding the veins. P. zonale and P. × hortorum varieties with full ePVBV genomes were not infected. Interestingly, P. inquinans, which does not contain ePVBV, was also not infected.

Plant-pathogenic bacteria cause great damage to global agriculture by infecting economically important crops and reducing yield. Among them, Xanthomonas spp. are a particularly important group of plant pathogens, as they have the ability to colonize hundreds of plant species. These pathogens exhibit a dual lifestyle, existing both epiphytically on plant surfaces and endophytically within host tissues. To establish infection, Xanthomonas must adapt to a range of abiotic and biotic stresses, including temperature, light, osmotic changes, oxidative stress, and host immune responses. The bacteria rely on sophisticated environmental sensing mechanisms, including chemotaxis mediated by methyl-accepting chemotaxis proteins, which help them detect host-derived chemical signals and navigate toward infection sites. Limited availability of nutrients, such as iron and magnesium within host tissues, acts as a cue that further modulates bacterial physiology and virulence. Xanthomonas has evolved efficient strategies to scavenge and store these nutrients, integrating these signals through tightly regulated gene networks. A central regulatory system involves diffusible signal factor (DSF)-mediated quorum sensing, which coordinates community-level behaviors such as motility, extracellular polysaccharide production, and secretion of virulence effectors. This review discusses recent advances in understanding how Xanthomonas integrates environmental and host-derived signals to regulate its pathogenicity. It emphasizes the role of DSF signaling, chemotaxis, and micronutrient acquisition in disease progression and host-pathogen interactions. Insights into these adaptive and regulatory mechanisms offer promising avenues for developing targeted strategies to control Xanthomonas-induced plant diseases and improve crop protection. [Formula: see text] Copyright © 2026 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Syndrome "Basses Richesses" (SBR) is a rapidly emerging sugar beet disease in central Europe that has a severe economic impact on the sugar beet industry and thus requires control. The cultivation of tolerant varieties is a promising method to reduce SBR. Digital plant phenotyping can support the screening process for tolerant varieties by characterizing traits of interest and quantifying tolerance. This research provides foundational work for digitally phenotyping SBR. Morphological and spectral traits were analyzed with machine learning, supporting disease monitoring and screening for tolerant varieties under controlled conditions. A susceptible sugar beet variety was infected with the dominant causal agent of SBR, 'Candidatus Arsenophonus phytopathogenicus' (ARSEPH). Hyperspectral images of the canopy were recorded weekly between 20 and 62 days after inoculation and segmented by leaves and petioles. Sixty-seven days after inoculation, each leaf was two-dimensionally (2D) and each taproot three-dimensionally (3D) imaged by angle-corrected 2D imaging and structured-light 3D scans, respectively. The results indicated substantial decreases in leaf area (19.7%), leaf length (6.9%), leaf blade length (13.1%), and leaf blade width (12.1%) resulting from ARSEPH infection. The most important wavelengths for machine learning classification of ARSEPH-infected sugar beet were from the petioles (97% accuracy) in the range 623 to 659 nm and 421 to 432 nm. The 22 most relevant taproot 3D parameters were evaluated with Boruta-SHAP based on their importance to characterize SBR-induced taproot deformation. Certain value and spatial regions were characteristic, indicating thresholds for 3D parameters and taproot regions to analyze when comparing varieties. [Formula: see text] Copyright © 2026 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

Puccinia striiformis f. sp. tritici, causing stripe rust, is one of the most prominent pathogens of wheat worldwide. The biotrophic and obligate fungus is capable of rapidly developing new virulent races that can overcome race-specific resistance in host plants. The traditional virulence characterization of the pathogen requires strict conditions for testing isolates on wheat differentials with specific resistance genes, which is time-consuming. Developing molecular markers for avirulence genes could provide an efficient method for monitoring virulence changes in the pathogen population. In this study, secreted protein gene-based single-nucleotide polymorphism markers previously identified to be associated with avirulence genes of the pathogen were converted to kompetitive allele-specific PCR (KASP) markers. The KASP markers were screened with a diverse panel of 192 isolates selected from various countries based on their virulent races and molecular genotypes. The markers significantly correlated with the avirulence/virulence phenotypic data of the 192 isolates were further validated with 845 isolates collected from the United States in 2019 to 2021. Based on the results of both the screening and validation data, 21 KASP markers significantly associated with different avirulence genes were developed. Seventeen of the 21 markers were significantly associated with two or more avirulence genes, and except AvrYr10, and the remaining 15 avirulence genes had two or more markers. Different combinations of up to three markers could be used for specific detection of 16 avirulence genes in monitoring the pathogen population.

Highbush blueberries (Vaccinium corymbosum) are an important fruit crop worldwide, and Michigan is one of the largest producers within the United States. Botrytis blossom blight and fruit rot are major diseases in this region. Although Botrytis cinerea has long been considered the primary causal agent, a recent study identified a novel species in Michigan. In this article, we describe a new species, B. michiganensis, as an additional pathogen causing blossom blight. This study aimed to characterize B. michiganensis through multilocus phylogenetic analysis (G3PDH, HSP60, RPB2, NEP1, and NEP2), morpho-cultural traits, and fungicide sensitivity. Phylogenetic analyses, using both individual and concatenated gene sequences, placed B. michiganensis in a distinct clade closely related to B. fabiopsis, B. caroliniana, and B. galanthina. The isolates exhibited diverse cultural and morphological characteristics on potato dextrose agar, ranging from white to gray fluffy/cottony mycelia. None of the isolates produced conidia on artificial media but developed typical Botrytis-like conidiophores and conidia on inoculated plant tissues, characterized by hyaline to pale brown, elliptical to ovoid conidia and branching conidiophores. Pathogenicity tests on blueberry tissues, green grapes, and white rose petals confirmed its ability to cause Botrytis blossom blight and fruit rot, with disease severity comparable to B. cinerea. Fungicide sensitivity assays revealed that B. michiganensis isolates were sensitive to all tested fungicides except cyprodinil. These findings provide new insights into the Botrytis species complex affecting blueberries and highlight the need for further diversity studies.

The economic value of cultivars resistant to disease is of great interest, but how growers change their fungicide use in response to host resistance may be nuanced. We draw upon a well-described data set of the incidence of hop plants with powdery mildew and associated production metadata and demonstrate the utility of Bayesian networks as a framework for quantifying causal relationships for fungicide use and cost in response to host resistance. Conditional Gaussian Bayesian network models applied to cultivars differing in race-specific resistance to powdery mildew revealed cultivar resistance to powdery mildew influenced disease levels in early spring, which had a causal effect on how often and what fungicides growers later applied. Annual costs depended on not only the number of applications made but also the specific types of fungicides growers selected. Fungicide costs were little changed on cultivars that possessed race-specific resistance to only one of two extant strains of the pathogen. For cultivars with resistance to both pathogen strains, annual costs of fungicides were reduced commensurate with the level of resistance. Predicted values from the Bayesian networks and simulation indicate that growers apply a baseline level of fungicide, independent of cultivar resistance. Fungicide cost savings result from how fungicide inputs differentially scale with the incidence of powdery mildew and the type of fungicides used. Our analyses indicate that for a high-value crop, deployment of disease resistance may cause complex and unexpected changes in growers' fungicide use patterns that may not be obvious in simplified randomized controlled trials.