Genome-Wide Identification of B-Box Gene Family and Expression Analysis Suggest Its Roles in Responses to Cercospora Leaf Spot in Sugar Beet (Beta Vulgaris L.).

The B-box (BBX) protein, which is a zinc-finger protein containing one or two B-box domains, plays a crucial role in the growth and development of plants. Plant B-box genes are generally involved in morphogenesis, the growth of floral organs, and various life activities in response to stress. In this study, the sugar beet B-box genes (hereafter referred to as BvBBXs) were identified by searching the homologous sequences of the Arabidopsis thaliana B-box gene family. The gene structure, protein physicochemical properties, and phylogenetic analysis of these genes were systematically analyzed. In this study, 17 B-box gene family members were identified from the sugar beet genome. A B-box domain can be found in all sugar beet BBX proteins. BvBBXs encode 135 to 517 amino acids with a theoretical isoelectric point of 4.12 to 6.70. Chromosome localization studies revealed that BvBBXs were dispersed across nine sugar beet chromosomes except chromosomes 5 and 7. The sugar beet BBX gene family was divided into five subfamilies using phylogenetic analysis. The gene architectures of subfamily members on the same evolutionary tree branch are quite similar. Light, hormonal, and stress-related cis-acting elements can be found in the promoter region of BvBBXs. The BvBBX gene family was differently expressed in sugar beet following Cercospora leaf spot infection, according to RT-qPCR data. It is shown that the BvBBX gene family may influence how the plant reacts to a pathogen infection.

Histopathological Investigation of Varietal Responses to Cercospora beticola Infection Process on Sugar Beet Leaves.

Cercospora leaf spot (CLS) is the most destructive foliar disease in sugar beet (Beta vulgaris). It is caused by Cercospora beticola Sacc., a fungal pathogen that produces toxins and enzymes which affect membrane permeability and cause cell death during infection. In spite of its importance, little is known about the initial stages of leaf infection by C. beticola. Therefore, we investigated the progression of C. beticola on leaf tissues of susceptible and resistant sugar beet varieties at 12-h intervals during the first 5 days after inoculation using confocal microscopy. Inoculated leaf samples were collected and stored in DAB (3,3'-diaminobenzidine) solution until processed. Samples were stained with Alexa Fluor-488-WGA dye to visualize fungal structures. Fungal biomass accumulation, reactive oxygen species (ROS) production, and the area under the disease progress curve were evaluated and compared. ROS production was not detected on any variety before 36 h postinoculation (hpi). C. beticola biomass accumulation, percentage leaf cell death, and disease severity were all significantly greater in the susceptible variety compared with the resistant variety (P < 0.05). Conidia penetrated directly through stomata between 48 to 60 hpi and produced appressoria on stomatal guard cells at 60 to 72 hpi in susceptible and resistant varieties, respectively. Penetration of hyphae inside the parenchymatous tissues varied in accordance with time postinoculation and varietal genotypes. Overall, this study provides a detailed account to date of events leading to CLS disease development in two contrasting varieties.

Cercospora leaf spot disease of sugar beet.

Leaf spot disease caused by Cercospora beticola Sacc. is the most damaging foliar disease threatening sugar beet production worldwide. The wide spread of disease incurs a reduction of yield and economic losses. The in-depth knowledge of disease epidemiology and virulence factor of pathogen is crucial and basic for preventing fungal disease. The integrated control strategies are needed for an efficient and sustainable disease management. The rotation of fungicides and crop could reduce the initial inoculum and delay the emergence of resistant pathogens. Spraying fungicides under the guide of forecasting models and molecular detecting techniques may hinder the onset of disease prevalence. The resistant varieties of sugar beet to cercospora leaf spot could be obtained by combining classical and molecular breeding methods. More effective approaches are supposed to develop for prevention and control for fungal disease of sugar beet.

Sugar Beet Root Storage Properties Are Unaffected by Cercospora Leaf Spot.

Cercospora leaf spot (CLS; causal agent Cercospora beticola Sacc.) is endemic in many sugar beet production regions due to the widespread distribution of C. beticola and the inability of current management practices to provide complete control of the disease. Roots harvested from plants with CLS, therefore, are inevitably incorporated into sugar beet root storage piles, even though the effects of CLS on root storage properties are largely unknown. Research was conducted to determine the effects of CLS on storage properties including root respiration rate, sucrose loss, invert sugar accumulation, loss in recoverable sucrose yield, and changes in sucrose loss to molasses with respect to CLS disease severity and storage duration. Roots were obtained from plants with four levels of CLS severity in each of three production years, stored at 5°C and 95% relative humidity for up to 120 days, and evaluated for storage characteristics after 30, 90, and 120 days storage. No significant or repeatable effects of CLS on root respiration rate, sucrose loss, invert sugar accumulation, loss in recoverable sucrose yield, or change in sucrose loss to molasses were detected after 30, 90, or 120 days storage regardless of the severity of CLS disease symptoms. Therefore, no evidence was found that CLS accelerates sugar beet storage losses, and it is concluded that roots harvested from plants with CLS can be stored without additional or specialized precaution, regardless of CLS symptom severity.

Disease Incidence and Severity of Cercospora Leaf Spot in Sugar Beet Assessed by Multispectral Unmanned Aerial Images and Machine Learning.

Disease incidence (DI) and metrics of disease severity are relevant parameters for decision making in plant protection and plant breeding. To develop automated and sensor-based routines, a sugar beet variety trial was inoculated with Cercospora beticola and monitored with a multispectral camera system mounted to an unmanned aerial vehicle (UAV) over the vegetation period. A pipeline based on machine learning methods was established for image data analysis and extraction of disease-relevant parameters. Features based on the digital surface model, vegetation indices, shadow condition, and image resolution improved classification performance in comparison with using single multispectral channels in 12 and 6% of diseased and soil regions, respectively. With a postprocessing step, area-related parameters were computed after classification. Results of this pipeline also included extraction of DI and disease severity (DS) from UAV data. The calculated area under disease progress curve of DS was 2,810.4 to 7,058.8%.days for human visual scoring and 1,400.5 to 4,343.2%.days for UAV-based scoring. Moreover, a sharper differentiation of varieties compared with visual scoring was observed in area-related parameters such as area of complete foliage (AF), area of healthy foliage (AH), and mean area of lesion by unit of foliage ([Formula: see text]). These advantages provide the option to replace the laborious work of visual disease assessments in the field with a more precise, nondestructive assessment via multispectral data acquired by UAV flights.[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.

Bacterial endophytes as indicators of susceptibility to Cercospora Leaf Spot (CLS) disease in Beta vulgaris L.

The fungus Cercospora beticola causes Cercospora Leaf Spot (CLS) of sugar beet (Beta vulgaris L.). Despite the global importance of this disease, durable resistance to CLS has still not been obtained. Therefore, the breeding of tolerant hybrids is a major goal for the sugar beet sector. Although recent studies have suggested that the leaf microbiome composition can offer useful predictors to assist plant breeders, this is an untapped resource in sugar beet breeding efforts. Using Ion GeneStudio S5 technology to sequence amplicons from seven 16S rRNA hypervariable regions, the most recurring endophytes discriminating CLS-symptomatic and symptomless sea beets (Beta vulgaris L.ssp. maritima) were identified. This allowed the design of taxon-specific primer pairs to quantify the abundance of the most representative endophytic species in large naturally occurring populations of sea beet and subsequently in sugar beet breeding genotypes under either CLS symptomless or infection stages using qPCR. Among the screened bacterial genera, Methylobacterium and Mucilaginibacter were found to be significantly (p < 0.05) more abundant in symptomatic sea beets with respect to symptomless. In cultivated sugar beet material under CLS infection, the comparison between resistant and susceptible genotypes confirmed that the susceptible genotypes hosted higher contents of the above-mentioned bacterial genera. These results suggest that the abundance of these species can be correlated with increased sensitivity to CLS disease. This evidence can further prompt novel protocols to assist plant breeding of sugar beet in the pursuit of improved pathogen resistance.

Seedborne Cercospora beticola Can Initiate Cercospora Leaf Spot from Sugar Beet (Beta vulgaris) Fruit Tissue.

Cercospora leaf spot (CLS) is a globally important disease of sugar beet (Beta vulgaris) caused by the fungus Cercospora beticola. Long-distance movement of C. beticola has been indirectly evidenced in recent population genetic studies, suggesting potential dispersal via seed. Commercial sugar beet "seed" consists of the reproductive fruit (true seed surrounded by maternal pericarp tissue) coated in artificial pellet material. In this study, we confirmed the presence of viable C. beticola in sugar beet fruit for 10 of 37 tested seed lots. All isolates harbored the G143A mutation associated with quinone outside inhibitor resistance, and 32 of 38 isolates had reduced demethylation inhibitor sensitivity (EC50 > 1 µg/ml). Planting of commercial sugar beet seed demonstrated the ability of seedborne inoculum to initiate CLS in sugar beet. C. beticola DNA was detected in DNA isolated from xylem sap, suggesting the vascular system is used to systemically colonize the host. We established nuclear ribosomal internal transcribed spacer region amplicon sequencing using the MinION platform to detect fungi in sugar beet fruit. Fungal sequences from 19 different genera were identified from 11 different sugar beet seed lots, but Fusarium, Alternaria, and Cercospora were consistently the three most dominant taxa, comprising an average of 93% relative read abundance over 11 seed lots. We also present evidence that C. beticola resides in the pericarp of sugar beet fruit rather than the true seed. The presence of seedborne inoculum should be considered when implementing integrated disease management strategies for CLS of sugar beet in the future.

Alternative products to control late season diseases in soybeans / Produtos alternativos para o controle de doenças de final de ciclo na soja

In the last crop seasons, the complex of late season diseases (CLSD) of soybean (Glycine max L. (Merrill)), has been causing considerable reductions in the crop yield. Currently, there are no cultivars resistant to all pathogens that causes CLSD. The present study evaluated the effect of applying the acibenzolar-S-methyl resistance inducer, alternative products and fungicide on the severity of CLSD in the soybean cultivar BMX Potência RR during the 2013/2014 and 2014/2015 crops, in the field. The treatments for the experiments were: 1 - control (water); 2 - acibenzolar-S-methyl; 3 - calcium; 4 - micronutrients: copper, manganese and zinc; 5 - micronutrients: manganese, zinc and molybdenum; 6 - nitrogen-potassium fertilizer; 7 - Ascophyllum nodosum and 8 - azoxystrobin + cyproconazole with the addition of the adjuvant. Four applications of alternative products and two of fungicide were carried out in both harvests. A diagrammatic scale assessed the severity of CLSD at the phenological stage R7.1. The acibenzolar-S-methyl resistance inducer, alternative products (macro and micronutrients) and A. nodosum had no effect on the severity of CLSD in the two harvests. The fungicide (azoxystrobin + cyproconazole) reduced the severity of CLSD and prevented damage to productivity in both experiments.

Nas últimas safras, o complexo de doenças de final de ciclo (DFC) da soja (Glycine max L. (Merrill)), vem provocando reduções consideráveis no rendimento da cultura. Atualmente, não há variedades resistentes a todos os patógenos causadores das DFC. O objetivo do presente trabalho foi avaliar o efeito da aplicação do indutor de resistência acibenzolar-S-methyl, produtos alternativos e fungicida na severidade de DFC na cultivar de soja BMX Potência RR durante as safras 2013/2014 e 2014/2015, em campo. Os tratamentos para os experimentos foram: 1 - testemunha (água); 2 - acibenzolar-S-methyl; 3 - cálcio; 4 - micronutrientes: cobre, manganês e zinco; 5 - micronutrientes: manganês, zinco e molibdênio; 6 - adubo NK; 7 - Ascophyllum nodosum e 8 - azoxistrobina + ciproconazol com adição do adjuvante. Foram realizadas quatro aplicações dos produtos alternativos e duas do fungicida, nas duas safras. A severidade de DFC foi avaliada por escala diagramática no estádio fenológico R7.1. O indutor de resistência acibenzolar-S-methyl, os produtos alternativos (macro e micronutrientes) e A. nodosum não apresentaram efeito sobre a severidade das DFC nas duas safras. O fungicida (azoxistrobina + ciproconazol) reduziu a severidade das DFC e evitou danos a produtividade nos dois experimentos.

Characterization of the Mycovirome from the Plant-Pathogenic Fungus Cercospora beticola.

Cercospora leaf spot (CLS) caused by Cercospora beticola is a devastating foliar disease of sugar beet (Beta vulgaris), resulting in high yield losses worldwide. Mycoviruses are widespread fungi viruses and can be used as a potential biocontrol agent for fugal disease management. To determine the presence of mycoviruses in C. beticola, high-throughput sequencing analysis was used to determine the diversity of mycoviruses in 139 C. beticola isolates collected from major sugar beet production areas in China. The high-throughput sequencing reads were assembled and searched against the NCBI database using BLASTn and BLASTx. The results showed that the obtained 93 contigs were derived from eight novel mycoviruses, which were grouped into 3 distinct lineages, belonging to the families Hypoviridae, Narnaviridae and Botourmiaviridae, as well as some unclassified (-)ssRNA viruses in the order Bunyavirales and Mononegavirales. To the best of our knowledge, this is the first identification of highly diverse mycoviruses in C. beticola. The novel mycoviruses explored in this study will provide new viral materials to biocontrol Cercospora diseases. Future studies of these mycoviruses will aim to assess the roles of each mycovirus in biological function of C. beticola in the future.

Development of a Sequential Sampling Plan using Spatial Attributes of Cercospora Leaf Spot Epidemics of Table Beet in New York.

Sampling strategies that effectively assess disease intensity in the field are important to underpin management decisions. To develop a sequential sampling plan for the incidence of Cercospora leaf spot (CLS), caused by Cercospora beticola, 31 table beet fields were assessed in the state of New York. Assessments of CLS incidence were performed in six leaves arbitrarily selected in 51 sampling locations along each of three to six linear transects per field. Spatial pattern analyses were performed, and results were used to develop sequential sampling estimation and classification models. CLS incidence (p) ranged from 0.13 to 0.92 with a median of 0.31, and beta-binomial distribution, which is reflective of aggregation, best described the spatial patterns observed. Aggregation was commonly detected (>95%) by methods using the point-process approach, runs analyses, and autocorrelation up to the fourth spatial lag. For Spatial Analysis by Distance Indices, or SADIE, 45% of the datasets were classified as a random pattern. In the sequential sampling estimation and classification models, disease units are sampled until a prespecified target is achieved. For estimation, the goal was sampling CLS incidence with a preselected coefficient of variation (C). Achieving the C = 0.1 was challenging with <51 sampling units, and only observed on datasets with incidence >0.3. Reducing the level of precision, i.e., increasing C to 0.2, allowed the preselected C to be achieved with a lower number of sampling units and with an estimated incidence ([Formula: see text]) close to the true value of p. For classification, the goal was to classify the datasets above or below prespecified thresholds (pt) used for CLS management. The average sample number, or ASN, was determined by Monte Carlo simulations, and was between 20 and 45 at disease incidence values close to pt, and approximately 11 when far from pt. Correct decisions occurred in >76% of the validation datasets. Results indicated these sequential sampling plans can be used to effectively assess CLS incidence in table beet fields.

Identification and characterization of Cercospora beticola necrosis-inducing effector CbNip1.

Cercospora beticola is a hemibiotrophic fungus that causes cercospora leaf spot disease of sugar beet (Beta vulgaris). After an initial symptomless biotrophic phase of colonization, necrotic lesions appear on host leaves as the fungus switches to a necrotrophic lifestyle. The phytotoxic secondary metabolite cercosporin has been shown to facilitate fungal virulence for several Cercospora spp. However, because cercosporin production and subsequent cercosporin-initiated formation of reactive oxygen species is light-dependent, cell death evocation by this toxin is only fully ensured during a period of light. Here, we report the discovery of the effector protein CbNip1 secreted by C. beticola that causes enhanced necrosis in the absence of light and, therefore, may complement light-dependent necrosis formation by cercosporin. Infiltration of CbNip1 protein into sugar beet leaves revealed that darkness is essential for full CbNip1-triggered necrosis, as light exposure delayed CbNip1-triggered host cell death. Gene expression analysis during host infection shows that CbNip1 expression is correlated with symptom development in planta. Targeted gene replacement of CbNip1 leads to a significant reduction in virulence, indicating the importance of CbNip1 during colonization. Analysis of 89 C. beticola genomes revealed that CbNip1 resides in a region that recently underwent a selective sweep, suggesting selection pressure exists to maintain a beneficial variant of the gene. Taken together, CbNip1 is a crucial effector during the C. beticola-sugar beet disease process.

Cercospora beticola: The intoxicating lifestyle of the leaf spot pathogen of sugar beet.

Cercospora leaf spot, caused by the fungal pathogen Cercospora beticola, is the most destructive foliar disease of sugar beet worldwide. This review discusses C. beticola genetics, genomics, and biology and summarizes our current understanding of the molecular interactions that occur between C. beticola and its sugar beet host. We highlight the known virulence arsenal of C. beticola as well as its ability to overcome currently used disease management strategies. Finally, we discuss future prospects for the study and management of C. beticola infections in the context of newly employed molecular tools to uncover additional information regarding the biology of this pathogen. TAXONOMY: Cercospora beticola Sacc.; Kingdom Fungi, Phylum Ascomycota, Class Dothideomycetes, Order Capnodiales, Family Mycosphaerellaceae, Genus Cercospora. HOST RANGE: Well-known pathogen of sugar beet (Beta vulgaris subsp. vulgaris) and most species of the Beta genus. Reported as pathogenic on other members of the Chenopodiaceae (e.g., lamb's quarters, spinach) as well as members of the Acanthaceae (e.g., bear's breeches), Apiaceae (e.g., Apium), Asteraceae (e.g., chrysanthemum, lettuce, safflower), Brassicaceae (e.g., wild mustard), Malvaceae (e.g., Malva), Plumbaginaceae (e.g., Limonium), and Polygonaceae (e.g., broad-leaved dock) families. DISEASE SYMPTOMS: Leaves infected with C. beticola exhibit circular lesions that are coloured tan to grey in the centre and are often delimited by tan-brown to reddish-purple rings. As disease progresses, spots can coalesce to form larger necrotic areas, causing severely infected leaves to wither and die. At the centre of these spots are black spore-bearing structures (pseudostromata). Older leaves often show symptoms first and younger leaves become infected as the disease progresses. MANAGEMENT: Application of a mixture of fungicides with different modes of action is currently performed although elevated resistance has been documented in most employed fungicide classes. Breeding for high-yielding cultivars with improved host resistance is an ongoing effort and prudent cultural practices, such as crop rotation, weed host management, and cultivation to reduce infested residue levels, are widely used to manage disease. USEFUL WEBSITE: https://www.ncbi.nlm.nih.gov/genome/11237?genome_assembly_id=352037.