I recently put together a short interactive teaching module on microbial community change in health and disease. Students reacted well to the exercise, so I thought I’d share it here (see below for materials). The basic idea is that after a short introduction getting folks excited about the microbiome, students break up into small groups and try to figure out what kinds of community changes might underly some disease scenarios. The group then discusses these ideas together, and relates each scenario to a real example.
The main goal of the lesson is to introduce many core ideas in microbial ecology, like alpha-diversity, beta-diversity, richness, evenness, etc. in a very short period of time, using examples that will be relevant to many folks. A secondary goal is to introduce the utility of tables of bacterial abundance across samples for sorting out these different patterns. A natural follow-on would be to actually convert those tables to electronic form and have students use them in microbial community analysis tools, or write their own python scripts to quantify these patterns (which could be improved with statistical tests later on).
So, for example, this first example illustrates a case where there is one microbe (the red dots) that is present in all the diseased samples, but none of the healthy ones. This might represent a classic bacterial disease caused by a single pathogen, and a likely candidate for fulfillment of Koch’s Postulates.
Several of the easier scenarios, like this one, also have microbe-microbe interactions embedded in them. For example, in the above scenario, the aqua and blue microbes are strongly negatively correlated in samples from both healthy and diseased patients. These bonus patterns can give groups that quickly get a solid idea about what might be causing disease something more meaty to explore while other groups continue thinking about their scenarios. They also introduce an alternative way of looking at microbial communities that will be important later on. Finally, these microbe-microbe interactions also help illustrate the utility of tables for spotting and quantifying patterns in microbial communities.
In this case, a table of the microbes across samples isn’t really needed to see the main trend with disease (red dots, bottom row) , but might help identify microbe-microbe interactions that are harder to spot visually. Here, the aqua and blue microbes (2nd and 3rd rows) trade off in abundance across samples.
Here’s a handout summarizing the different scenarios from the lesson:
Here are the lesson materials:
Overview and Guide: Perspectives_on_Microbial_Communities_Exercise_Overview_r2
Lesson Powerpoint (via SlideShare): [link]
Handouts: All handout files, including the original Illustrator files (16 MB download) as a single zip. [link]. The files includes all of the scenarios without tables, their associated tables alone (basically an OTU table for each scenario), or the diagram with the table. The summary handout image is also included.