Insects are an integral part of the biodiversity in virtually all terrestrial ecosystems, making them very important for environmental impact assessment. The cereal leaf beetle (CLB, Oulema melanopus) is a serious agricultural pest that causes significant damage to agricultural production. Recent advances in next-generation sequencing (NGS) have made it possible to study microbial communities with unprecedented resolution. However, these advances in data generation have created new challenges for researchers attempting to analyse and visualise these data.

The aim of this talk is to present statistical methods to characterise the bacterial communities associated with CLB larvae and imagoes collected from different cereal host species and locations. Identification of CLB-associated bacteria was performed by 16S rRNA gene sequencing at the V3-V4 hypervariable region.

To test which factors influence the microbial composition at each taxonomic level, the abundance of the bacterial community can be modelled with a negative binomial hurdle model (hNB GLMM). Methods for checking the appropriateness of the choice of hurdle model, evaluating parameter estimation and assessing fit of the model will be presented. In addition, permutational procedures for assessing the importance of variables will be discussed. Next, the term top biome will be introduced to provide information on which taxa have an abundance that is significantly different from the overall mean abundance of all taxa. Methods for determining of bacterial biodiversity will be presented. Different identifiers for alpha and beta biodiversity will be discussed.

The methods presented can contribute to a better understanding of the microbiome composition, diversity, and the main factors influencing the content of insect-associated bacteria, and can be successfully applied in other ecological studies.