9.4 Try it Question 1 - How sensitive is microbial diversity to variables like diet, age and gender

Alpha diversity is a measure that estimates how the distribution of microbes changes due to a variable (or metadata category). Alpha diversity measures changes in the richness (the number of different organisms or ASVs) and evenness (how evenly are these organisms distributed in terms of their abundance). Using the “MISO” study dataset we will use Simpson (or specifically, Gini-Simpson) alpha diversity to evaluate changes in microbial diversity in individuals due to different metadata variables.

Approach: Plot Simpson alpha diversity using plot_richness() command in phyloseq and assess the impact of different study variables on changes in microbial diversity. Identify the variables that impact alpha diversity. Visible shifts in alpha diversity measure suggests a shift in microbial diversity, and higher alpha diversity value indicates an increase in alpha diversity.

Note, when plotting this data you may get a warning below. That is ok!

Warning: The data you have provided does not have any singletons. This is highly suspicious. Results of richness estimates (for example) are probably unreliable, or wrong, if you have already trimmed low-abundance taxa from the data.We recommended that you find the un-trimmed data and retry.
  • Refer to the “alpha diversity” section of the “Analyze 16S rRNA Data with phyloseq” tutorial for help using the plot_richness() function.

9.4.1 Step 1A. Plot alpha diversity of the full MISO dataset by subject (individuals).

  • subject is on the x-axis
  • Color is by subject
  • Use the following code as a template:
plot_richness(miso_counts, x="fill in the blank", 
              color="subject", 
              measures= "Simpson")
1A-1. Paste your plot below:

1A-2. Examine the alpha diversity plot you made. Are the points for an individual highly clustered or far apart?

1A-3. Is the alpha diversity metric for one individual similar to another’s?

1A-4. When the points for an individual are highly clustered, this means their gut microbiome has the same level of biodiversity over the length of the experiment (although the exact community of microbes may not be the same). Conversely, when the points are farther apart, their gut microbiome’s biodiversity has changed through the experiment. What does it mean to see a varied pattern of clustering across individuals in the study?

1A-5. Do you think a healthy microbiome has a high or low alpha diversity? Why or why not?

9.4.2 Step 1B. Plot alpha diversity of the full MISO dataset by diet

  • diet is on the x-axis
  • Color is by subject
  • Use the following code as a template:
plot_richness(miso_counts, x="fill in the blank", 
              color="fill in the blank", 
              measures= "Simpson")
1B-1. Paste your plot below:

1B-2. Based on the plot above, does diet change the overall alpha diversity metric of the gut microbiome (ex. Are the points higher or lower overall in one diet versus the others?)

1B-3. Based on the plot above does diet change how varied the alpha diversity is between individuals? (ex. Are the points more spread out in one diet versus the others?)

1B-4. Do you think diet has an impact on gut microbial alpha diversity?

9.4.3 Step 1C. Plot alpha diversity of the full MISO dataset by age.

  • age is on the x-axis
  • Color is by subject
  • Use the following code as a template:
plot_richness(miso_counts, x="fill in the blank", 
              color="fill in the blank", 
              measures= "Simpson")
1C-1. Paste your plot below:

1C-2. Do younger or older individuals have a higher alpha diversity of the gut microbiome overall (ex. Which group has an overall higher alpha diversity measure)?

1C-3. Do younger or older individuals have a more consistent alpha diversity of the gut microbiome (ex. Are points clustered more closely in younger or older subjects)?

1C-4. What do you think the impact of age on the alpha diversity of the gut microbiome is?

9.4.4 Step 1D. Plot alpha diversity of the full MISO dataset by gender.

  • gender is on the x-axis
  • Color is by subject
  • Use the following code as a template:
plot_richness(miso_counts, x="fill in the blank", 
              color="fill in the blank", 
              measures= "Simpson")
1D-1. Paste your plot below:

1D-2. Do males or females have a higher alpha diversity of the gut microbiome overall (ex. Which group has an overall higher alpha diversity measure)?

1D-3. Do males or females have a more consistent alpha diversity of the gut microbiome (ex. Are points clustered more closely in males or females)?

1D-4. What do you think the impact of gender on the alpha diversity of the gut microbiome is?

9.4.5 Step 2. Plot alpha diversity of the full MISO dataset, grouping based on levels for 5 different metabolites: Creatinine, PCS, IS, HIPP, PAG.

Plot alpha diversity for the 5 metabolites independently then choose your favorite metabolite (e.g. one with most difference) and show plot below.

  • metabolite on the x-axis (one at a time: Creatinine, PCS, IS, HIPP, PAG)
  • Color is by subject
  • Use the following code as a template:
plot_richness(miso_counts, x="fill in the blank metabolite name", 
              color="fill in the blank", 
              measures= "Simpson")
2A-1. Paste your metabolite plot(s) below:

2A-2. Which metabolite did you choose to show and why?

2A-3. Are there any trends in alpha diversity as this metabolite increases in level?

9.4.6 Footnotes

9.4.6.2 Contributions and affiliations

  • Valeriya Gaysinskaya, Johns Hopkins University
  • Gauri Paul, Clovis Community College
  • Frederick Tan, Johns Hopkins University
  • Sayumi York, Notre Dame of Maryland University
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