Title

Re-Analysis of 16S rRNA Gene Sequence Data Sets Uncovers Disparate Laboratory-Specific Microbiomes Associated with the Yellow Fever Mosquito (Aedes aegypti)

Document Type

Article

Publication Date

1-2022

Abstract

Host-microbiome dynamics occurring in the yellow fever mosquito (Aedes aegypti) contribute to host life history traits, and particular bacterial taxa are proposed to comprise a “core” microbiota that influences host physiology. Laboratory-based studies are frequently performed to investigate these processes; however, experimental results are often presumed to be generalizable across laboratories, and few efforts have been made to independently reproduce and replicate significant findings. A recent study by Muturi et al. (FEMS Microbiol Ecol 95 (1):213, 2019) demonstrated the food source imbibed by laboratory-reared adult female mosquitoes significantly impacted the host-associated microbiota—a foundational finding in the field of mosquito biology worthy of independent evaluation. Here, we coalesce these data with two additional mosquito-derived 16S rRNA gene sequence data sets using a unifying bioinformatics pipeline to reproduce the characterization of these microbiota, test for a significant food source effect when independent samples were added to the analyses, assess whether similarly fed mosquito microbiomes were comparable across laboratories, and identify conserved bacterial taxa. Our pipeline characterized similar microbiome composition and structure from the data published previously, and a significant food source effect was detected with the addition of independent samples, increasing the robustness of this previously discovered component of mosquito biology. However, distinct microbial communities were identified from similarly fed but independently reared mosquitoes, and surveys across all samples did not identify conserved bacterial taxa. These findings demonstrated that while the main effect of the food source was supported, laboratory-specific conditions may produce inherently differential microbiomes across independent laboratory environments.

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