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High-ThroughputSequencing of the HumanMicrobiomeJesse StombaughBiofrontiers InstituteUniversity of Colorado at Boulder
Viewing the human microbiome through anRNA lens
There are as many E. coli in yourgut...
As there are humans on the Earth!                            =However, only a tiny fraction of the gutmicrobes are E.coli…
You are covered with microbes on and in yourbody: How human are we?                                Micah Hamady, PhD Thesi...
Where do our microbes come from?
It’s important to remember that our   world...NASA: Earth from Apollo
...is a microbial world.                                                             o Multicellular lineages             ...
Decline in cost of sequencing
As the cost of sequencing declines...
…quantitative differences become qualitativedifferences
Need to interpret vast amounts of data
Problem: Big trees hard to understand and  analyzeExample: 5088 mouse gutand 11,831 human colonbacterial sequences•See man...
QIIME: Analysis of Hundreds of Samples            Hamady et al. 2008 Nature Methods 5:235; Caporaso et al. 2010 Nature Met...
QIIME: Analysis of Hundreds of Samples            Hamady et al. 2008 Nature Methods 5:235; Caporaso et al. 2010 Nature Met...
QIIME: Analysis of Hundreds of Samples            Hamady et al. 2008 Nature Methods 5:235; Caporaso et al. 2010 Nature Met...
QIIME: Analysis of Hundreds of Samples            Hamady et al. 2008 Nature Methods 5:235; Caporaso et al. 2010 Nature Met...
QIIME: Analysis of Hundreds of Samples            Hamady et al. 2008 Nature Methods 5:235; Caporaso et al. 2010 Nature Met...
QIIME: Analysis of Hundreds of Samples            Hamady et al. 2008 Nature Methods 5:235; Caporaso et al. 2010 Nature Met...
Comparing Microbial Communities• What is there?• How much is there?  • α (i.e., within sample) diversity• How similar or d...
Sampling of the microbiota 20 minutesafter birth             9 Mothers and 10 children                                    ...
Phylogenetic Diversity (PD) of the infant  gut microbiota over time                         Peas + formula introduced     ...
Community composition changes over time    conform to a smooth temporal gradient•   Time and PC1 from a    PCoA of bacteri...
Human oral, gut, and plaque microbiota inpatients with Atherosclerosis                       •   Samples collected from 15...
Mean Phylum Abundances by Body Habitat for Patients and Controls• Plotted values are mean sequence  abundances in each phy...
Correlations between the Abundances of Different    Genera and Disease Markers                                        Oral...
Microbial biogeography of public restroom   surfaces             12 University of Colorado Restrooms (6 men and 6 women)Li...
Microbial biogeography of public restroomsurfaces                                Flores et al. (2012) Plos One
Principal Investigators:Rob Knight (CU)                                  AcknowledgementsNoah Fierer (CU)Ruth Ley (Cornell...
Technologies like MIxS enable everyone tocontribute     Minimal Information about     any (x) Sequence
Direct environmental sequencing sees the “other” 99% of microbes 1. Get samples            1. Sequence    and extract    D...
Direct environmental sequencing sees the “other” 99% of microbes 1. Get samples            1. Sequence          1. Align, ...
Gut community changes across time andgeography    531 Subjects and 3 Countries (USA, Malawi and Venezuala)                ...
UPGMA Clustering of Samples Using theUnweighted Unifrac Distanceso Branches are colored by  body site, and numbers  in lab...
Differences in Abundance between Body   Sites(A) Shrunken differences for the 10 genera accounting for the differences amo...
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High-Throughput Sequencing of the Human Microbiome, Rob Knight Research Group, University of Colorado at Boulder, Jesse Stombaugh, Copenhagenomics 2012

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At CPHx Jesse Stombaugh presented a talk about High-Throughput Sequencing of the human microbiome.

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High-Throughput Sequencing of the Human Microbiome, Rob Knight Research Group, University of Colorado at Boulder, Jesse Stombaugh, Copenhagenomics 2012

  1. 1. High-ThroughputSequencing of the HumanMicrobiomeJesse StombaughBiofrontiers InstituteUniversity of Colorado at Boulder
  2. 2. Viewing the human microbiome through anRNA lens
  3. 3. There are as many E. coli in yourgut...
  4. 4. As there are humans on the Earth! =However, only a tiny fraction of the gutmicrobes are E.coli…
  5. 5. You are covered with microbes on and in yourbody: How human are we? Micah Hamady, PhD Thesis, 2009
  6. 6. Where do our microbes come from?
  7. 7. It’s important to remember that our world...NASA: Earth from Apollo
  8. 8. ...is a microbial world. o Multicellular lineages (red) rare, not diverse as measured by SSU rRNA o Most molecular diversity can be found in microbes o Most (99%+) microbes can’t be cultured: known only from sequencesFigure adapted from Norm Pace, Science (1997) 276:734-740.
  9. 9. Decline in cost of sequencing
  10. 10. As the cost of sequencing declines...
  11. 11. …quantitative differences become qualitativedifferences
  12. 12. Need to interpret vast amounts of data
  13. 13. Problem: Big trees hard to understand and analyzeExample: 5088 mouse gutand 11,831 human colonbacterial sequences•See many clusters ofsequences from eachsample•Significance tests fordifferences, but nophylogenetic metric Ley et al., 2005 PNAS 102:11070
  14. 14. QIIME: Analysis of Hundreds of Samples Hamady et al. 2008 Nature Methods 5:235; Caporaso et al. 2010 Nature Methods 7:335
  15. 15. QIIME: Analysis of Hundreds of Samples Hamady et al. 2008 Nature Methods 5:235; Caporaso et al. 2010 Nature Methods 7:335
  16. 16. QIIME: Analysis of Hundreds of Samples Hamady et al. 2008 Nature Methods 5:235; Caporaso et al. 2010 Nature Methods 7:335
  17. 17. QIIME: Analysis of Hundreds of Samples Hamady et al. 2008 Nature Methods 5:235; Caporaso et al. 2010 Nature Methods 7:335
  18. 18. QIIME: Analysis of Hundreds of Samples Hamady et al. 2008 Nature Methods 5:235; Caporaso et al. 2010 Nature Methods 7:335
  19. 19. QIIME: Analysis of Hundreds of Samples Hamady et al. 2008 Nature Methods 5:235; Caporaso et al. 2010 Nature Methods 7:335
  20. 20. Comparing Microbial Communities• What is there?• How much is there? • α (i.e., within sample) diversity• How similar or different are samples? • β (i.e., between sample) diversity• What relationships exist between a microbial community and characteristics of the sampled environment?
  21. 21. Sampling of the microbiota 20 minutesafter birth 9 Mothers and 10 children Dominguez-Bello et al. (2010) PNAS
  22. 22. Phylogenetic Diversity (PD) of the infant gut microbiota over time Peas + formula introduced Antibiotics (cefdinir) Day before feverPD provides a measure of the diversity within a community based on the extentof the 16S rRNA phylogenetic tree that is represented by that community. Koenig et al. (2010) PNAS
  23. 23. Community composition changes over time conform to a smooth temporal gradient• Time and PC1 from a PCoA of bacterial communities determined from 16S rRNA genes are plotted.• Blue color gradient based on time (days). Mother’s sample is red. Koenig et al. (2010) PNAS
  24. 24. Human oral, gut, and plaque microbiota inpatients with Atherosclerosis • Samples collected from 15 patients with atherosclerosis and 14 healthy patients • Bacterial diversity clustering by body habitat using unweighted UniFrac. Koren et al. (2010) PNAS
  25. 25. Mean Phylum Abundances by Body Habitat for Patients and Controls• Plotted values are mean sequence abundances in each phylum for 1,700 randomly selected sequences per sample.Most Abundant Phyla• Plaque: Proteobacteria/Actinobacteria• Oral: Firmicutes/Bacteroidetes/ Actinobacteria• Gut: Firmicutes/Bacteroidetes Koren et al. (2010) PNAS
  26. 26. Correlations between the Abundances of Different Genera and Disease Markers Oral samples• Pearson correlation coefficients are represented by color ranging from blue, negative correlation (−1), to red, positive correlation (1).• Positive correlations between Fusobacteria with LDL and cholesterol levels• Positive correlation between Streptococcus with HDL cholesterol and Apolipoprotein A-1 (ApoA1), whereas Neisseria was negatively correlated to levels of these two disease markers• Significant correlations are noted by *P < 0.05; **P < 0.01, and ***P < 0.001. Koren et al. (2010) PNAS
  27. 27. Microbial biogeography of public restroom surfaces 12 University of Colorado Restrooms (6 men and 6 women)Light blue indicates low abundance while dark blue indicates high abundance of taxa.B.Skin-associated taxa (Propionibacteriaceae, Corynebacteriaceae, Staphylococcaceae andStreptococcaceae) were abundant on all surfaces.C.Gut-associated taxa (Clostridiales, Clostridiales group XI, Ruminococcaceae, Lachnospiraceae,Prevotellaceae and Bacteroidaceae) were most abundant on toilet surfaces.D.soil-associated taxa (Rhodobacteraceae, Rhizobiales, Microbacteriaceae and Nocardioidaceae) were inlow abundance on all restroom surfaces, they were relatively more abundant on the floor of the restrooms wesurveyed. Flores et al. (2012) Plos One
  28. 28. Microbial biogeography of public restroomsurfaces Flores et al. (2012) Plos One
  29. 29. Principal Investigators:Rob Knight (CU) AcknowledgementsNoah Fierer (CU)Ruth Ley (Cornell)Frederik Backhed (Gothenburg)Jeff Gordon (Wash U.) Support:Knight Lab:Jose Clemente LitranDoug WendelAntonio Gonzalez-PenaJeremy WidmannMeg PirrungTony WaltersDaniel McDonaldCathy LozuponeGreg Caporaso -> Northern Arizona U.Justin Kuczynski -> Second GenomeJens Reeder -> GenetechDan Knights -> HarvardJulia Goodrich -> CornellJesse Zaneveld -> Oregon State U.Chris LauberDonna Berg-LyonsJerry KennedyGail AckermannElizabeth Costello -> StanfordMicah Hamady -> world travelsOther Labs:Jeremy Koenig (Cornell)Omry Koren (Cornell)Ayme Spor (Cornell)
  30. 30. Technologies like MIxS enable everyone tocontribute Minimal Information about any (x) Sequence
  31. 31. Direct environmental sequencing sees the “other” 99% of microbes 1. Get samples 1. Sequence and extract DNA 1. BLAST sequences, group by similarity to GenBank1. PCR amplify (usually SSU rRNA gene)
  32. 32. Direct environmental sequencing sees the “other” 99% of microbes 1. Get samples 1. Sequence 1. Align, build tree and extract DNA X 1. BLAST sequences, group by similarity to GenBank1. PCR amplify (usually SSU rRNA gene)
  33. 33. Gut community changes across time andgeography 531 Subjects and 3 Countries (USA, Malawi and Venezuala) Yatsunenko et al. (2012) Nature
  34. 34. UPGMA Clustering of Samples Using theUnweighted Unifrac Distanceso Branches are colored by body site, and numbers in labels refer to subject numbers in the study.o All atherosclerotic plaque samples are from patients; oral and gut samples from patients are noted with an asterisk. Koren et al. (2010) PNAS
  35. 35. Differences in Abundance between Body Sites(A) Shrunken differences for the 10 genera accounting for the differences among the three body sites. • Plaque: (+) Chyrseomonas/Staphylococcus/Propionibactererineae • Oral: (+) Streptococcus • Gut: (+) Lachnospiraceae/Ruminococcus/Faecalibacterium, (-) Streptococcus(B) Heat map of the abundances of genera (i.e., those driving differences between body sites) Koren et al. (2010) PNAS

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