BIOM25: 16S Practical
22 Jan 2016BIOM25: 16S Practical
In this practical we will analyse datasets from several studies, some very important, others perhaps just a little silly.
At first, we will go through a dataset together, this is from a pioneering paper:
- The Human Microbiome in Space and Time.
After that, in groups, we will analyse one of three different datasets:
- CSI: Microbiome. Can you determine who has been using a keyboard from the microbiome that is left behind? Do keyboards have a core microbiome??
- The microbiome of restroom surfaces (toilets!)
- Development of the infant gut microbiome.
Please watch this video for a useful demonstration of how principal component analysis works: https://www.youtube.com/watch?v=BfTMmoDFXyE
General questions
Q: What is the difference between alpha- and beta-diversity?
Human microbiome in space and time
Paper: http://www.microbesng.uk/filedist/16stutorial/spacetime/nihms245011.pdf
Supplementary material: http://www.sciencemag.org/cgi/content/full/1177486/DC1
Let’s have a look at the results.
Fields of importance: HOST_INDIVIDUAL, SEX, BODY_HABITAT, BODY_SITE, COMMON_NAME
Results:
Alpha diversity: http://www.microbesng.uk/filedist/16stutorial/spacetime/core/arare_max500/alpha_rarefaction_plots/rarefaction_plots.html
Bar plots by sample site: http://www.microbesng.uk/filedist/16stutorial/spacetime/core/taxa_plots_COMMON_SAMPLE_SITE/taxa_summary_plots/bar_charts.html
PCoA analysis: http://www.microbesng.uk/filedist/16stutorial/spacetime/core/bdiv_even500/unweighted_unifrac_emperor_pcoa_plot/index.html
Q: Is there evidence of natural clusters being formed?
Q: Do samples cluster by individual? If not, how do they cluster?
Q: What are the most dominant taxa in stool, skin, urine? Look at different taxonomic levels down to genus.
Q: Are these sites similar or different? What are the major differences in taxonomic profile between these three sites?
##CSI: Microbiome
Original paper: http://www.microbesng.uk/filedist/16stutorial/keyboard/keyboard_paper.pdf
Q: Skim read the introduction of the paper to get a feel for what they are trying to find out.
Q: Look at the Methods section and put the primer selection into TestPrime:
http://www.arb-silva.de/search/testprime
Results: http://www.microbesng.uk/filedist/16stutorial/keyboard/core2/
Important metadata fields for this project:
- Description_duplicate - the key from any keyboard
- HOST_SUBJECT_ID - the person each keyboard belongs to
Hint: M1, M2 and M9 are the three participants referred to in the paper.
Q: What are the most abundant taxa?
Q: Check the PCA plots, do samples cluster by key, or by subject (hint: HOST_SUBJECT_ID, )
Q: Go back to the taxa barplots, can you figure out which taxa are driving the variation producing grouping?
Q: Which of these taxa are part of the normal skin microbiome? Are any out of plcae? Where might they come from?
Q: Do you think this technique will really be usable for forensics? What are the challenges? What other techniques might work better for studying the microbiome?
Q: Now, read the paper in more detail and prepare a short summary to present the context for the study, the methods employed and the results found.
##Restroom surfaces
Paper: http://www.microbesng.uk/filedist/16stutorial/restrooms/pone.0028132.pdf
Q: Skim read the introduction of the paper to get a feel for what they are trying to find out.
Q: Look at the Methods section and put the primer selection into TestPrime:
Now, look at the output of QIIME:
Results: http://www.microbesng.uk/filedist/16stutorial/restrooms/core/
Fields of importance: Floor, Level, SURFACE, BUILDING
Q: What surfaces have the greatest amount of diversity? Is this expected?
Q: What do the profiles of stool, etc. look like?
Q: Are there any natural looking clusters in the data?
Q: Which sources of samples are most similar to others?
Q: Is there any clustering between different floors of the building?
Q: Compare the weighted vs unweighted Unifrac results, do the clusters look more natural in one or the toher?
Q: Which surfaces have the most diversity? Least?
Q: Now, read the paper in more detail and prepare a short summary to present to the whole group. Consider: the context for the study, the methods that were employed and the results found. What did you think? What are the limitations of the study?
Infant gut metagenome
Paper: http://www.microbesng.uk/filedist/16stutorial/infant_time_series/PNAS-2011-Koenig-4578-85.pdf
Q: Skim read the introduction of the paper to get a feel for what they are trying to find out.
Q: Look at the Methods section and put the primer selection into TestPrime:
Now, look at the output of QIIME:
Results: http://www.microbesng.uk/filedist/16stutorial/infant_time_series/core/
Fields of importance:
- SampleID - age in days of infant
- SOLIDFOOD
- FORMULA
- COWMILK
- BREASTMILK
- COLORDESCRIPTION
- HOST_SUBJECT_ID
Q: Is there any evidence of a gradient? (Key: use SampleID and turn gradient colours on)
Q: How do the taxa change over time?
Q: Which infant samples do the maternal stool most look like?
Q: Is the colour of stools associated with their bacterial diversity?
Q: Now, read the paper in more detail and prepare a short summary to present to the whole group. Consider: the context for the study, the methods that were employed and the results found. What did you think? What are the limitations of the study?
##Instructor notes on building this tutorial
- Download from QIIME db site or the BEAST
- Get greengenes tree file
- core_diversity_analyses.py -i study_1335_closed_reference_otu_table.biom -o core -m study_1335_mapping_file.txt -e 1000 -t ../gg.tree -c “GENDER,FLOOR,BUILDING,SURFACE”
- core_diversity_analyses.py -i study_232_closed_reference_otu_table.biom -ocore2 -m study_232_mapping_file.txt -e 1000 -t gg.tree -c “HOST_SUBJECT_ID,Description_duplicate”
- core_diversity_analyses.py -i study_232_closed_reference_otu_table.biom -ocore2 -m study_232_mapping_file.txt -e 1000 -t gg.tree -c “HOST_SUBJECT_ID,Description_duplicate”