Microbiomics Dacus vertebratus (Diptera, Tephritidae)
This study first characterizes the bacterial communities of Dacus vertebratus, a widespread agricultural pest of Cucurbitaceae in Tanzania. We sampled Tephritidae larvae from infested watermelons in seven sites in the Morogoro area. In two of these sites, part of a more extensive experimental setup, we explored possible microbial shifts promoted by agroecological or pesticide-based farming. All larvae collected were identified via DNA barcoding and subjected to 16S rRNA metabarcoding. The analysis of the microbial communities of 43 larvae of D. vertebratus produced 2,552 filtered ASVs assigned to 22 phyla, 212 families, and 465 bacterial genera. More than 99.8% of ASVs belonged to 10 phyla; Bacteroidota (50.1%) and Proteobacteria (33.5%) dominated the community. The 10 most abundant bacterial families contributed to 88.4% of the ASVs, with Rhizobiaceae (30.78%) and Weeksellaceae (20.62%) being the dominant taxa. More than 75.4% of the ASVs belonged to 10 genera, with Sphingobacterium (15.2%) and Flaschrobactrum (14.2%) as the most abundant taxa. Our screening reveals that 14% of all microbiome functions of D. vertebratus are metabolic. Amino acid metabolism, carbohydrate metabolism, and metabolism of co-factors and vitamins are the most common pathways observed, representing 3.1%, 2.9%, and 2.3% of all metabolic functions. A more in-depth analysis of the functional profiles shows that peptidases, oxidative phosphorylation, and purine metabolism are among the highest contributors to the metabolic functions of the microbiome of D. vertebratus. We observed significant differences between the microbiome and the bacterial metabolic functions of D. vertebratus and other fruit flies feeding on watermelon (D. bivittatus, D. ciliatus, and Zeugodacus cucurbitae) in the Morogoro area. We did not detect substantial differences in the microbiome of D. vertebratus from agroecological or pesticide-based agriculture. Regardless, we cannot exclude that larger experimental setups might allow the detection of more subtle effects promoted by agricultural practices.