1. 16S RNA sequencing analysis
Bioinformatics and
16S RNA sequencing analysis

2. Three 16S rRNA Sequencing Questions to Answer
Why would we want to do it?
How
is it performed?
What is
16S rRNA sequencing?

3. What is bioinformatics?
Terms to Define
Biology
Computer
Science
Math/Statistics
What is bioinformatics?

5. What is Amplicon Sequencing?
When a particular gene or gene fragment is amplified and the sequence determined to achieve insight when studying microbiomes (all microorganisms in a particular environment).

6. Metagenome-the genomes of the total microbiota in a community.
Metagenomics allows us to extract DNA sequences from a microbial community in nature bypassing the need for cultures.

7. What is the 16S gene and why us it?
16S – named because rate at which it sediments in ultracentrifuge (Svedberg)
Protein found in small subunit of ribosome (Present in all species)
Ubiquitous - Highly conserved because mutation would probably be deleterious
Extreme sequence conservation useful for primers
Variable regions for organism identification
Well annotated reference databases

8. Variable and conserved regions within the 16S rRNA gene
Adapted from: Kevin E. Ashelford et al. Appl. Environ. Microbiol. 2005;71:
Illustrating variable regions within the 16S rRNA gene and location of chimeric breakpoints. (A) The frequency of occurrence of the most common nucleotide residue at each base position within the 16S rRNA gene, as determined from RDP-listed 4,383 type strains, with E. coli U00096 as a reference. These frequencies are measures of variability within the gene. (B) Smoothing the data, by taking the mean frequency within a window of 50 bases, moving one base at a time along the gene, creates the plot shown in panel B. The locations of the hypervariable regions are labeled, with gray bars on the x axis defining these regions as V1 to V9 (the Comparative RNA Web Site [ (C) Histogram of all chimera breakpoints identified in this study and that of Hugenholtz and Huber (8).
Fry and Ellis, Patent Publication number WO A2
Example of primers

9. Variation in rRNA gene copy number
Valdivia-Anistro, J.A., et al., Front. Microbiol. 05 January 2016|
Most bacteria contain more than one rRNA operon, and copy number varies
Can affect abundance estimates
And some bacteria have high levels of sequence divergence in the rRNA operons
This can inflate diversity estimates
Can attempt to correct this (PICRUSt, CopyRighter)

10. 16S pipeline Prepping Sample Extracting DNA Sampling Bioinformatics
Sampling
Extracting DNA
Prepping Sample
Bioinformatics
Sequencing

11. Which sequencing chemistry to use?
Kuczynski et al., Nat. Rev. Genet. 13: 4-58 (2012)

12. Sequencing by Synthesis and Basecalling

13. Illumina Inc. Video Illustrating Prepping and Sequencing by Synthesis
Illumina Sequencing Technology
Intro to Sequencing by Synthesis: Industry-leading Data Quality

14. Bioinformatics

15. Workflow for deep sequencing of 16S rRNA gene amplicons
Schematic overview of the workflow involved to analyze the microbiota composition by deep sequencing of 16S rRNA gene amplicons.
Ines Yang et al. FEMS Microbiol Rev 2013;37:

16. Operational Taxonomic Units (OTUs) and Annotation - MiSeq Reporter
Operational taxonomic unit-extant taxon
Cluster of similar amplicon sequences
97% identity commonly used
Pre-clustering to collapse all identical sequences into one category speeds analysis
OTU determination
De novo methods cluster by similarity with no reference to outside sequences
Taxonomy-based methods cluster based on similarity to known sequences-uses ClassifyReads, a proprietary algorithm
Combined taxonomy + de novo methods
Known sequence databases
Ribosomal Database Project (
GreenGenes (

17. Statistically Speaking and Interpreting the Data

18. Species Diversity Results
Species richness
Number of species present in a sample
Determined by the number of OTUs present
Influenced by sequencing depth
Species evenness
How close in numbers each species is in a sample
Species diversity
Composite of species richness and species evenness

19. α-diversity and Shannon’s diversity index
Diversity within a sample
Measures the amount of information needed to describe every member of the community
Shannon’s diversity index in an information statistic index
If pi is the proportion of individuals of species i, then the diversity (H’) is:
From this, one can calculate evenness, which is the ratio of the actual H’ to the maximum value (and so ranges from 0 to 1)
Adapted from:

20. Species Diversity Results
Species richness
Number of species present in a sample
Determined by the number of OTUs present
Influenced by sequencing depth
Species evenness
How close in numbers each species is in a sample
Species diversity
Composite of species richness and species evenness

21. Flower species Field 1 Field 2 Daisy 300 20 Dandelion 335 49
Flower species Field 1 Field 2
Daisy
Dandelion
Buttercup
Total
Which field is more diverse?
Field 1

22. Hierarchical Clustering Dendrogram
Dendrogram: a tree diagram
Topology- how closely sample related
The two samples (clusters) most similar are clustered together forming a new cluster.
At each step, the next closest sample is clustered with the new cluster.

23. What is a Principle Coordinate Analysis (PCoA)
Graphically represents similarities or dissimilarities of data.
Begins with a distance matrix ends with computation of Eigen values and vectors.
Objects ordinated closer to one another are more similar than those ordinated further away.

24. Why do 16S rRNA sequencing?

25. Scheme for studying the “normal” human microbiome.
Bacterial distribution by body site. This figure shows the distribution by body site of bacteria that have been sequenced under the HMP or are in the sequencing pipelines.
The NIH HMP Working Group, Peterson J, Garges S, et al. The NIH Human Microbiome Project. Genome Research. 2009;19(12): doi: /gr

26. α Diversity rarefaction curves of cutaneous microbiota in psoriasis (lesion), unaffected and control specimens. (A) Taxonomical richness trends towards decreasing α diversity in unaffected and lesion specimens relative to control, with no statistically significant differences between skin types. (B) Shannon index is significantly different (decreases from control to unaffected to lesion) among skin types at all taxonomic levels (P <0.05), except at the operational taxonomical unit (OTU) level. (C) Analysis of taxa sharing. Taxa present in <3 samples excluded from the analysis. Taxa that are only observed in one clinical skin type are denoted as ‘unique’. Taxa that are present in two types of skin are denoted as ‘shared’. The data show that nearly all taxa are represented in all three types of skin. The shading represents the relative distribution (heatmap) for each column number (green = low, yellow = intermediate, red = high).
Alekseyenko AV, Perez-Perez GI, De Souza A, et al. Community differentiation of the cutaneous microbiota in psoriasis. Microbiome. 2013;1:31. doi: /

28. Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences Morgan G I Langille, et al. Nature Biotechnology 31, 814–821 (2013) doi: /nbt.2676 (2013).

30. Shannon Species Diversity Number of Species Identified
Site 1
Site 2
Site 4
Site 3
Site 5
Site 6
Sample
Shannon Species Diversity
Number of Species Identified
St. James Place
2.625
653
53rd Street
2.553
1490
44th Street West
2.571
1478
44th Street East
2.659
1178
38th Street
2.727
1545
Coombs Road
2.826
462

31. Summary What? How? Why? Bioinformatics
Amplicon sequencing and metagenomics
16S gene
How?
Pipeline and Different Sequencing Platforms
Bioinformatic’s Step
Operational Taxonomic Units
Statistical Terms
Alpha Diversity and Shannon Index
Species Diversity, Richness and Evenness
Hierarchical Clustering Dendrogram and PCoA
Why?
Human Microbiome Project – Microbiota in Psoriasis Demonstration Project
Cameron University’s Wolf Creek Microbial Diversity Project