Outbreak-driven differences in the microbiome composition and diversity of two cassava whitefly Bemisia tabaci mitotypes SSA1-SG1 and SSA1-SG2 - El Hamss, Hajar; Ally, Hadija M.; Delatte, Hélène; Omongo, Christopher A.; Colvin, John; Maruthi, M. N. (Frontiers in Microbiology, 2025)
Since the 1990s, outbreaking populations of the whitefly Bemisia tabaci species complex (Sub-Saharan Africa 1 and 2) have heavily infested cassava in Uganda and eastern Africa. These superabundant SSA1 whiteflies from outbreaking areas carry microbiomes that might influence their fitness. Nonetheless, the factors contributing to the surge of these populations and their connection to the whitefly microbiome remain uncertain. To explore microbiome structure, diversity, and potential contributions to outbreaks of B. tabaci SSA1 species, we performed 16S rDNA amplicon sequencing. Endosymbionts (excluding Portiera) and the meta-microbiome were analyzed separately across 56 SSA 1 samples identified using a partial fragment of the mtCOI gene from 8 sites (32 outbreakings and 24 non-outbreakings). Two mitochondrial profiles were obtained within the samples named here as mitotypes SSA1-SG1 and SSA1-SG2. We investigated microbiome differences at two levels: (i) between two mitochondrial mitotypes, SSA1-SG1 and SSA1-SG2, and (ii) between outbreaking and non-outbreaking whitefly populations. Our results showed that the two mitotypes exhibited significantly different endosymbiont diversity (p < 0.0001), structures (p < 0.01, determined by ADONIS and Capscale), and co-occurrence networks. At the population level, significant differences in microbiome diversity were observed between outbreaking and non-outbreaking populations (Simpson index: p = 0.007; Shannon index: p = 0.006), with outbreaking populations showing reduced microbial diversity. Community structure also differed significantly (p = 0.001), as revealed by ADONIS and Capscale analyses using Bray–Curtis metrics. Outbreaking SSA1-SG1 whiteflies showed the highest microbial richness (mean = 63 ASVs), compared to an overall average of 45 ASVs across all samples. Co-occurrence patterns were highly structured, indicating non-random microbial interactions and shifts. Overall, our findings highlight the microbiome as a key factor in local invasions and epidemic emergence. Future research should focus on identifying specific bacterial contributors to better understand their role in outbreak dynamics.