Integrated Biological Control of the Sugar Beet Weevil Asproparthenis punctiventris with the Fungus Metarhizium brunneum: New Application Approaches.

The mass occurrence of the sugar beet weevil (Asproparthenis punctiventris, previously Bothynoderes punctiventris) has been endangering sugar beet cultivation in Austria for centuries. Exacerbated by climatic and political changes (warmer, drier spring and limited access to chemical pesticides), new approaches are needed to counter the problem. The aim of our work was to test whether the bioinsecticide Metarhizium brunneum Ma 43 (formerly M. anisopliae var. anisopliae BIPESCO 5/F52) can be used as a sustainable plant protection product against the sugar beet weevil. Our goal was to control the pest in all its development stages through multiple applications. Therefore, GranMetTM-P, a granular formulation of M. brunneum Ma 43, was applied in spring to establish the fungus in the soil, whereas GranMetTM-WP, a liquid formulation of the production strain, was used in early summer on trap ditches and leaves to target the adult weevils. Soil and plant samples as well as weevils were collected during the planting season from the trial sites to evaluate the development of the fungus and the mycosis of the treated weevils. In addition, data on hibernating weevils and their emigration from untreated field sites was collected. In all field sites, the Metarhizium spp. abundance increased above the background level (<1000 CFU g−1 soil dry weight) after application of the product. With an increasing number of treatments per plot, and thus an increased contact possibility between pest and the fungus, a rise in the mycosis rate was observed. In conclusion, the various Metarhizium application strategies, which are already available or in testing, must be implemented to ensure control in both old and new sugar beet fields. Metarhizium is a further asset in the successful control of this sugar beet pest.

Unraveling metabolic patterns and molecular mechanisms underlying storability in sugar beet.

BACKGROUND: Sugar beet is an important crop for sugar production. Sugar beet roots are stored up to several weeks post-harvest waiting for processing in the sugar factories. During this time, sucrose loss and invert sugar accumulation decreases the final yield and processing quality. To improve storability, more information about post-harvest metabolism is required. We investigated primary and secondary metabolites of six sugar beet varieties during storage. Based on their variety-specific sucrose loss, three storage classes representing well, moderate, and bad storability were compared. Furthermore, metabolic data were visualized together with transcriptome data to identify potential mechanisms involved in the storage process. RESULTS: We found that sugar beet varieties that performed well during storage have higher pools of 15 free amino acids which were already observable at harvest. This storage class-specific feature is visible at harvest as well as after 13 weeks of storage. The profile of most of the detected organic acids and semi-polar metabolites changed during storage. Only pyroglutamic acid and two semi-polar metabolites, including ferulic acid, show higher levels in well storable varieties before and/or after 13 weeks of storage. The combinatorial OMICs approach revealed that well storable varieties had increased downregulation of genes involved in amino acid degradation before and after 13 weeks of storage. Furthermore, we found that most of the differentially genes involved in protein degradation were downregulated in well storable varieties at both timepoints, before and after 13 weeks of storage. CONCLUSIONS: Our results indicate that increased levels of 15 free amino acids, pyroglutamic acid and two semi-polar compounds, including ferulic acid, were associated with a better storability of sugar beet taproots. Predictive metabolic patterns were already apparent at harvest. With respect to elongated storage, we highlighted the role of free amino acids in the taproot. Using complementary transcriptomic data, we could identify potential underlying mechanisms of sugar beet storability. These include the downregulation of genes for amino acid degradation and metabolism as well as a suppressed proteolysis in the well storable varieties.

Correction to: Integrative transcriptomics reveals genotypic impact on sugar beet storability.

In the above mentioned publication, part of Fig. 6B was distorted (extra diagonal lines appeared). The original article has been corrected and the proper version of Fig. 6B is also published here.

Integrative transcriptomics reveals genotypic impact on sugar beet storability.

KEY MESSAGE: An integrative comparative transcriptomic approach on six sugar beet varieties showing different amount of sucrose loss during storage revealed genotype-specific main driver genes and pathways characterizing storability. Sugar beet is next to sugar cane one of the most important sugar crops accounting for about 15% of the sucrose produced worldwide. Since its processing is increasingly centralized, storage of beet roots over an extended time has become necessary. Sucrose loss during storage is a major concern for the sugar industry because the accumulation of invert sugar and byproducts severely affect sucrose manufacturing. This loss is mainly due to ongoing respiration, but changes in cell wall composition and pathogen infestation also contribute. While some varieties can cope better during storage, the underlying molecular mechanisms are currently undiscovered. We applied integrative transcriptomics on six varieties exhibiting different levels of sucrose loss during storage. Already prior to storage, well storable varieties were characterized by a higher number of parenchyma cells, a smaller cell area, and a thinner periderm. Supporting these findings, transcriptomics identified changes in genes involved in cell wall modifications. After 13 weeks of storage, over 900 differentially expressed genes were detected between well and badly storable varieties, mainly in the category of defense response but also in carbohydrate metabolism and the phenylpropanoid pathway. These findings were confirmed by gene co-expression network analysis where hub genes were identified as main drivers of invert sugar accumulation and sucrose loss. Our data provide insight into transcriptional changes in sugar beet roots during storage resulting in the characterization of key pathways and hub genes that might be further used as markers to improve pathogen resistance and storage properties.

Microbiome-driven identification of microbial indicators for postharvest diseases of sugar beets.

BACKGROUND: Sugar loss due to storage rot has a substantial economic impact on the sugar industry. The gradual spread of saprophytic fungi such as Fusarium and Penicillium spp. during storage in beet clamps is an ongoing challenge for postharvest processing. Early detection of shifts in microbial communities in beet clamps is a promising approach for the initiation of targeted countermeasures during developing storage rot. In a combined approach, high-throughput sequencing of bacterial and fungal genetic markers was complemented with cultivation-dependent methods and provided detailed insights into microbial communities colonizing stored roots. These data were used to develop a multi-target qPCR technique for early detection of postharvest diseases. RESULTS: The comparison of beet microbiomes from six clamps in Austria and Germany highlighted regional differences; nevertheless, universal indicators of the health status were identified. Apart from a significant decrease in microbial diversity in decaying sugar beets (p ≤ 0.01), a distinctive shift in the taxonomic composition of the overall microbiome was found. Fungal taxa such as Candida and Penicillium together with the gram-positive Lactobacillus were the main disease indicators in the microbiome of decaying sugar beets. In contrast, the genera Plectosphaerella and Vishniacozyma as well as a higher microbial diversity in general were found to reflect the microbiome of healthy beets. Based on these findings, a qPCR-based early detection technique was developed and confirmed a twofold decrease of health indicators and an up to 10,000-fold increase of disease indicators in beet clamps. This was further verified with analyses of the sugar content in storage samples. CONCLUSION: By conducting a detailed assessment of temporal microbiome changes during the storage of sugar beets, distinct indicator species were identified that reflect progressing rot and losses in sugar content. The insights generated in this study provide a novel basis to improve current or develop next-generation postharvest management techniques by tracking disease indicators during storage.