Multilevel analysis of Insect-Bacteria Interaction for Symbiotic COntrol implementation -2022R5B3LT

The need to reduce agricultural economic losses due to insect pests while limiting the use of pesticides makes the implementation of sustainable approaches for their control a priority, in line with the EU request of reducing the use of chemical pesticides. Control strategies based on the elimination of obligate bacterial symbionts were proposed as a sustainable option to control insect pests; the best candidates for such control strategies are insects characterized by the vertical transmission of their symbiont through an extracellular environmental route. This transmission mode is predominant in the family Pentatomidae, where the application on egg masses of commercial products with an antimicrobial activity is known to cause a high nymphal mortality. While different efficiency was observed depending on populations, the current knowledge suggests the potential use of these approaches for the control of several species, including Nezara viridula. This project aims to develop sustainable pest control protocols - specifically tailored to be used across different areas of Italy - by investigating the influence of different biotic factors (the insect genotype, the genotype of its obligate symbiont and the associated gut microbiota) on the insect susceptibility to symbiotic control strategies. Research activities will be carried out through the joint effort of 2 Research Units (RUs): these have the complementary expertise required to successfully carry out the planned work, which is organized in four Work Packages (WPs). Different N. viridula populations will be collected and reared (WP1), and their population genetic structure characterized using genotyping-by-sequencing approach (WP2). A characterization of the bacterial primary symbiont of the insect will also be performed, through whole-genome sequencing, and coupled with gut microbiota characterization (WP3). Concurrently, symbiotic control experiments will be conducted under laboratory conditions, by treating the egg surface derived from different N. viridula populations with commercial products with recognized anti-symbiont activity (WP4). A combination of machine learning methods and more traditional multivariate statistics will be then used to model and understand the interplay between the treatment, the analysed holobiont components and environmental factors in order to identify the parameters affecting the insect response to the proposed treatment. By using commercially available products used for Integrated Pest Management, the newly developed strategies can be easily integrated with current control measures. This allows the development of ad hoc environmental-friendly tool to control this insect pest of primary economic relevance that can be finely tuned according with local conditions, at different spatial scales. Such approaches pave the ground to the application of a new precision agriculture approaches, focused on insect-symbiont interactions, in full agreement with the EU requests.