Would it work?

Using gut microbes as a "mine" for enzymes using a metagenomic library approach is a fairly novel idea. This concept does raise some questions.

Is it even possible?

How different are microbiomes to begin with, will different animals have different microbiomes?

What enzymes are we likely to find in what animals?

Are the enzymes found in each animal predictable?

These questions guided our proof of concept experiments and allowed us to gather some evidence for our approach. This page will answer the questions raised above and will act to provide some of evidence to the feasibility of our approach.

How did we find evidence?

The Integrated Microbiome Resource at Dalhousie does 16S and metagenomic DNA sequencing and is a bioinformatic hub at the University. With their support we sequenced the 16S rRNA genes found in the environmental DNA extracted from feces of 21 mammals at the Shubenacadie Wildlife Park. With this information we were able to address a few of the questions that were mentioned above. We then chose the porcupine, beaver, arctic wolf and coyote samples to sequence in replicate, and then applied a bioinformatic tool called PICRUSt (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States) to obtain information of microbial gene content found in these fecal samples. These animals were chosen because the beaver microbiome is similar to the porcupine microbiome according to our 16S data, and the arctic wolf and coyote microbiomes are similar to each other but different from the beaver and porcupine microbiomes. Our goal is to use microbial diversity and gene content in fecal samples as an approximation of the microbiomes of the mammals at the wildlife park. With this approximation we can determine what enzymes we are likely to find in the microbiomes of particular animals.

Results

These are the results of our sequencing and bioinformatic analysis separated by section and tool:

Initial 16S Sequencing

The initial 16S sequencing provided us with an overall picture of species diversity and similarity, and allowed us to create beta-diversity plots that compare the similarities of the microbiomes that were sequenced. The first figure below shows a bar graph (shown on the left) that was constructed from the 16S data:

This bar graph shows us two things. The first is that the microbiomes of these different animals are very diverse. There is significant differences between each sample and their is tons of diversity. This is important because we would want a diverse representation of genetic content to start with when building a metagenomic library. The second thing is that you can notice similarities between the samples. The porcupine and beaver samples share a microbe that is of the family S24-7 and the order Bacteroidales, which is denoted by THIS COLOR. You can also notice that the red deer, moose and elk share a large BROWN bar that matches up to the order Bacteriodales. This is by far an exhaustive list of similarites, but these two function to illustrate these similarities. To further show similarities, we built a beta-diversity plot (seen on the right) that allows us to see how similar or how different each sample is.

Bar Graph Legend here