The Effects of Longevity and Diet on the Microbiome in Drosophila melanogaster

Abstract

The microbiome has been discovered to impact many aspects of health in a variety of organisms from Drosophila melanogaster to humans. Recently many studies have been conducted examining the microbiome in an effort to better understand how it interacts with the environment and host genotype to influence expressed phenotypes. Here, I investigate how longevity and diet influence the abundance of microbes and the community composition of the microbiome in Drosophila melanogaster. I answered this question by establishing three treatment groups; control young, control old, and high sugar old and examining the differences between them. qPCR analyses were performed to quantify bacterial abundance to visual the differences in bacterial abundance and variance between the three treatment groups. I found that high sugar old flies had both the highest bacterial abundance and variance, control old had both the lowest bacterial abundance and variance, and the control young treatment group had an intermediate bacterial abundance and variance when compared to the two other treatment groups. 16s rRNA sequencing was performed to gain insight into the community composition of the three treatment groups. I found that there were noticeable differences in the composition of the microbiome between the three treatment groups given Acetobacter was the most prevalent species in the control young group, Commensalibacter was the most prevalent species in the high sugar old treatment group, and both Lactobacillus and Commensalibacter were the most prevalent species in the control old treatment group. Overall, I found no significant difference in bacterial abundance or variance between treatment groups but found that both age and diet were significant in explaining the variation in community composition. My results suggest that there is a link between both age and diet and the composition of the microbiome. I suggest that further studies need to be conducted to better understand the mechanism behind the observed trend with the ultimate goal of discovering therapeutic treatment options to treat disease in humans and other organisms.