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Updated: Apr 11, 2026

Rearing the Fruit Fly Drosophila melanogaster Under Axenic and Gnotobiotic Conditions
Published on: July 30, 2016
Life-Stage-Dependent Variation in Gastrointestinal Microbial Communities of Drosophila melanogaster
Arnau Rocabert1, Laia Pareras1, Raquel Egea1
1Group of Mutagenesis, Department of Genetics and Microbiology, Faculty of Biosciences, Universitat Autònoma de Barcelona, Campus of Bellaterra, Cerdanyola del Vallès, Barcelona, 08193, Spain.
Abstract:
Drosophila melanogaster has been a useful biological model since its first use, more than 100 years ago. Mainly due to its genetic similarity with humans, as it allowed it to be an accurate representation of how different biological systems work, such as immune function, illness related pathways, gene inheritance, egg development and, in this case, the microbial ecosystem. Age-related changes in the gut microbiota of D. melanogaster offer valuable insights into the dynamic relationship between a host and its microorganisms across lifespan and can be extrapolated to other organisms. This study focusses on the potential changes that microbiota undergoes across the several stages of the fly life cycle, generating robust and high-resolution data using MinION nanopore sequencing as a cutting-edge approach to microbiota analysis Our findings highlight the highly dynamic nature of the gut microbiota across the D. melanogaster lifespan and underscore the necessity of explicitly accounting for developmental stage and chronological age in microbiota-focused studies. Moreover, a clearer understanding of these temporal microbial shifts provides valuable insight into how host-microbiota interactions are shaped during development, maintained during adulthood, and ultimately altered during aging. Currently, the gut microbiota stabilized following post-eclosion establishment, while age-associated dysbiosis and immune decline have not yet emerged. Consequently, using flies around 1-week-old maximizes experimental consistency and sensitivity, making them an optimal model for investigating microbiota-targeted interventions.

