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The Microbiome and Metagenomics
Catherine LozuponeCPBS 7711
October 13, 2015
What is the microbiome?• “The ecological community of commensal,
symbiotic, and pathogenic microorganisms that share our body space”
• Microbiota: “collection of organisms” Microbiome: “collection of genes”
• Bacteria, Archaea, microbial eukaryotes (e.g. fungi or protists) and viruses.
• Body Sites– Important roles in health and disease: Gut, Mouth,
Vagina, Skin (diverse sites:Nasal epithelial)– Important roles in disease: Lung, blood, liver, urine
The big tree
Pace, N.R.,The UniversalNature of Biochemistry. PNAS Vol 98(3) pp 805-808.
• Majority of life’s diversity is microbial
• Majority of microbial life cannot be grown in pure culture
The Human Gut Microbiota• 100 trillion microbial cells: outnumber human
cells 10 to 1!• Most gut microbes are harmless or beneficial.
– Protect against enteropathogens– Extract dietary calories and vitamins– Prevent immune disorders
• List of diseases associated with dysbiosis ever growing– Inflammatory Diseases: IBD, IBS– Metabolic Diseases: Obesity, Malnutrition– Neurological Disorders– Cancer
What do we want to understand?• What does a healthy microbiome look like?
– How diverse is it?– What types of bacteria are there?– What is their function?
• How variable is the microbiome?– Over time within an individual?– Across individuals?– Functionally?
• What are driving factors of variability?– Age, culture, physiological state (pregnancy)
• How do changes affect disease?– What properties (taxa, amount of diversity) change with disease?– Cause or affect?– Functional consequences of dysbiosis
• Host Interactions– Evolution/adaptation to the host over time.– Immune system
Culture-independent studies revolutionized our understanding of gut bacteria
• Culture-based studies over-emphasized the importance of easily culturable organisms (e.g. E. coli).
1. Extract DNA from environmental samples.
2.PCR amplify SSU rRNA gene (which species?) Sequence random fragments (which function?)
3. EvaluateSequences
Culture-independent surveys
Gut microbiota has simple composition at the phylum level
Data from: Yatsunenko et. al. 2012. Nature.
Different phyla: Animalsand plants
• Each person harbors > 1000 species.
• Some species are unique (red and blue)
• Some shared (purple)
• We know very little about what most of these species do!
Diversity of Firmicutes in 2 healthy adults
Sequencing technology renaissance enabled more complex study designs
• Sanger Sequencing (thousands)• Pyrosequencing (millions)• Illumina (billions!)
Metagenomics
• The study of metagenomes, genetic material recovered directly from environmental samples.
• Marker gene– PCR amplify a gene of interest – Tells you what types of organisms are there– Bacteria/Archaea (16S rRNA), Microbial Euks (18S
rRNA), Fungi (ITS), Virus (no good marker)• Shotgun
– Fragment DNA and sequence randomly.– Tells you what kind of functions are there.
Small Subunit Ribosomal RNA
• Present in all known life forms
• Highly conserved• Resistant to horizontal
transfer events
16S rRNA secondary structure
Other ‘Omics• MetaTranscriptomics (sequence version of
microarray)– Isolate all RNA– Deplete rRNA– Sequence all transcripts – Sometimes phenotype only seen in activity of the
microbiota• Metabolomics
– What metabolites does a community produce?– E.g. in feces or urine
• MetaProteomics– What proteins does a community produce?
Integrating Data Types• 16S rRNA -> shotgun metagenomics
– What gene differences cannot be explained by 16S?
– Selection by HGT• 16S/ genomics -> transcriptomics->
metabolomics – What species or genes (or combination of species
or genes), when expressed, are responsible for producing a given metabolite?
Sequencing Technologies• Sanger -> 454 Pyrosequencing -> Illumina
Short reads (pyrosequencing) can recapture the result.
• UW UniFrac clustering with Arb parsimony insertion of 100 bp reads extending from primer R357.
• Assignment of short reads to an existing phylogeny (e.g. greengenes coreset) allows for the analysis of very large datasets.
Liu Z, Lozupone C, Hamady M, Bushman FD & Knight R (2007) Short pyrosequencing reads suffice for accurate microbial community analysis. Nucleic Acids Res 35: e120.
Preprocessing pyrosequencing datasets
• Quality filtering: Discard sequences that:– Are too short and too long (200-1000 range)– With low quality scores– With long homopolymers– Can trim poor quality regions from the ends
• PyroNoise and Chimeras– Can greatly inflate OTU counts– Pyronoise algorithm uses SFF files to fix noisy
sequences
• Use barcodes to assign sequences to samples
Defining species: OTU picking
• Cluster sequences based on % identity– 97% id typical for species– CD-HIT, UCLUST
• For Phylogenetic diversity measures need to make a tree– Align sequences: NAST, PyNAST– Denovo tree building: FastTree– Assign reads to sequences in a pre-defined
reference tree
Comparing Diversity
• Overview of methods for evaluating/comparing microbial diversity across samples using 16S rRNA– diversity: Measures how much is there?– diversity: How much is shared?
• Phylogenetic verses taxon based diversity. • Quantitative verses Qualitative diversity.• What types of taxa are driving the patterns? Which
species are associated with measured properties?• Tools: UniFrac/QIIME/Topiary Explorer• Lozupone, C.A. and R. Knight (2008) Species divergence and the
measurement of microbial diversity. FEMS Microbiol Rev. 1-22.