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Microbiome diversity and composition in Bemisia tabaci SSA1-SG1 whitefly are influenced by their host's life stage

El Hamss H., Maruthi M.N., Omongo C.A., Wang H.L., van Brunschot S., Colvin J., Delatte H.. 2023. Microbiological Research, 278 : 10 p..

DOI: 10.1016/j.micres.2023.127538

Within the Bemisia tabaci group of cryptic whitefly species, many are damaging agricultural pests and plant-virus vectors, conferring upon this group the status of one of the world's top 100 most invasive and destructive species, affecting farmers' income and threatening their livelihoods. Studies on the microbiome of whitefly life stages are scarce, although their composition and diversity greatly influence whitefly fitness and development. We used high-throughput sequencing to understand microbiome diversity in different developmental stages of the B. tabaci sub-Saharan Africa 1 (SSA1-SG1) species of the whitefly from Uganda. Endosymbionts (Portiera, Arsenophonus, Wolbachia, and Hemipteriphilus were detected but excluded from further statistical analysis as they were not influenced by life stage using Permutational Multivariate Analysis of Variance Using Distance Matrices (ADONIS, p = 0.925 and Bray, p = 0.903). Our results showed significant differences in the meta microbiome composition in different life stages of SSA1-SG1. The diversity was significantly higher in eggs (Shannon, p = 0.024; Simpson, p = 0.047) than that in nymphs and pupae, while the number of microbial species observed by the amplicon sequence variant (ASV) was not significant (n(ASV), p = 0.094). At the phylum and genus levels, the dominant constituents in the microbiome changed significantly during various developmental stages, with Halomonas being present in eggs, whereas Bacillus and Caldalkalibacillus were consistently found across all life stages. These findings provide the first description of differing meta microbiome diversity in the life stage of whiteflies, suggesting their putative role in whitefly development.

Mots-clés : bemisia tabaci; vecteur de maladie; stade de développement; méthode statistique; ouganda; afrique au sud du sahara; afrique

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