Integrative analysis of gut microbiota composition, cecal gene expression as consequence of
dietary change, age, and genotype
All animals’ intestinal tracts―from worms to fish to humans―are lined with a tremendous variety of
bacteria which can help the organism digest food and respond to environmental challenges, but
which can also lead to disease when unbalanced. Therefore, it is essential to find the correlation
between host metabolism and host microbiota. It will provide clues for a better understanding of
human aging and may inspire new theraputic strategies for many diseases which are influenced by
the host microbiota.
The composition of this complex system, called the gut microbiota, responds to changes in our diet,
our environment, our age, and according to individuals’ genetics. Individuals with metabolic diseases,
such as inflammatory bowel syndrome and obesity, tend to have common features in the profiles of
their microbiota, such as a common increase in Firmicutes in obese individuals. We have followed a
population of 597 mice which vary according to genetics (56 different inbred strains), diet (299 low
fat, 298 high fat), and age (6 to 24 months). The mice are evenly distributed by age between 6 to 18
months, with a gradual drop-off from 18-24 months as many mice do not live that long. In this
population, we will measure the DNA and RNA and compare this against the different phenotypes
observed in the population. Thus, we intend to identify and prove causal relationships between the
microbiota, host genetics, and dietary responses leading to metabolic disease.
RNA and DNA from about 50 frozen cecum samples were extracted and separated to analyze gene
expression of both host tissues and microbiome. The mRNA, metatranscriptomics and metagenomics
sequencing results have been obtained. I will analysis the omics-data and try to find some interesting
point on what are the effects of diet and age on the cecum and how do these microbiome gene
expression changes link to changes in the mouse.
Keywords: Microbiota; Cecum; Metatranscriptomics; Metagenomics