The human microbiome talk by Jonathan Eisen @phylogenomics for SciFoo 2007


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Presentation by Jonathan Eisen on the human microbiome for SciFoo 2007

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  • Phylogenetic analysis of rRNAs led to the discovery of archaea
  • Functional prediction using a gene tree is just like predicting the biology of a species using a species tree
  • Extension of rRNA analysis to uncultured organisms using PCR
  • Metagenomic analysis led to the discovery of a new form of phototrophy in the ocean
  • This is a tree of a rRNA gene that was found on a large DNA fragment isolated from the Monterey Bay. This rRNA gene groups in a tree with genes from members of the gamma Proteobacteria a group that includes E. coli as well as many environmental bacteria. This rRNA phylotype has been found to be a dominant species in many ocean ecosystems. clone from the Sargasso Sea. This shows that this
  • The human microbiome talk by Jonathan Eisen @phylogenomics for SciFoo 2007

    1. 1. Humans are Microbial Carrying Vessels
    2. 2. Some Microbial Trivia• Microbes rule the planet• There are 100x more microbial cells in the human body than human cells• Microbes are really small• Human health may be determined more by microbes than environment or genes• Most microbes in/on humans are beneficial - known as commensals
    3. 3. Top Known Benefits of Human Commensals• Preventing infection by pathogens• Development of the immune system• Digestion of food• Vitamin production• Toxin degradation• Appearance and odor
    4. 4. Why Study Commensals?• Diagnostic for health status• Disturbed by antibiotics• Colonization disrupted by C-sections• Imbalances may cause disease (autoimmune, IBS, obesity)• Probiotics and prebiotics could improve health• Likely have many as of yet unknown functions
    5. 5. Microbes are Very Small• Makes them hard to study• Even when examined in microscopes - appearance is not a reliable indicator of microbial type or biology• Culturing allows biology to be studied in detail in the lab• Genome sequencing of cultured species very informative
    6. 6. Studying the microbiome - series of eras
    7. 7. Studying Microbiome Era I Microscopy
    8. 8. Human Commensals• Skin• Conjunctiva• Oral cavity• Intestinal tract• Upper respiratory tract• Urogenital tract Table 14.1c
    9. 9. Studying Microbiome Era II - Culturing
    10. 10. Guide to the Normal Bacterial Flora of Humans Clostridia• Members of the genus Clostridium• Found in the the intestinal tract Clostridium difficile. Clostridia are anaerobic endospore-forming bacteria, found mainly in the large intestine.
    11. 11. BACTERIA COMMONLY FOUND ON THE SURFACES OF THEHUMAN BODY Lower AnteriorBACTERIUM Skin Conjunctiva Nos e Pharynx Mouth Vagina Intestine urethraStaphylococcus ++ + ++ ++ ++ + ++ ++epidermidis (1)Staphylococcus + +/- + + + ++ +/- +aureus* (2)Streptococcus + ++ +/- + +miti sStreptococcus ++ ++salivariusStreptococcus + ++mutans* (3)Enterococcus +/- + ++ + +faecalis * (4)Streptococcus +/- +/- + + +/-pneumoniae* (5)Streptococcus +/- +/- + + +/- +/-pyogenes* (6)Neisseria sp. (7) + + ++ + + +Neisseria + ++ + +meningitidis * (8)Veillonella e sp. + +/-Enterobacteriaceae*(Escherichia col i) +/- +/- +/- + ++ + +(9)Proteus sp. +/- + + + + + +
    12. 12. BACTERIA COMMONLY FOUND ON THE SURFACES OF THEHUMAN BODY Lower AnteriorBACTERIUM Skin Conjunctiva Nos e Pharynx Mouth Vagina Intestine urethraPseudomon asaeruginosa* +/- +/- + +/-(10)Haemophilus +/- + + +influenzae* (11)Bacteroides ++ + +/-sp.*Bifidobacterium ++bifidum (12)Lactobacillus + ++ ++ ++sp. (13)Clostridium +/- ++sp.* (14 )Clostridium +/-tetani (15)Corynebacteria ++ + ++ + + + + +(16)Mycobacteria + +/- +/- + +Actinomycetes + +Spirochetes + ++ ++Mycoplasmas + + + +/- +
    13. 13. Once Cultured ….• Experimental biology• Place on a tree of life• Genome sequencing• Genetic engineering
    14. 14. ORF00100 ORF00714 ORF00927 ORF00940 phosphate AMP,ADP,dAMP, dADP,ATP,dATP,ITP, glycerol-3P dITP,IMP,XMP,GMP,GDP,dGDP,dGTP,dGMP ADP ATP fructose-1,6-P2 WD1142 WD0661 (2?) WD1238 WD1305 WD1183 WD0731 WD1023 WD0197 Purine Metabolism WD0786 WD0089 WD0867 WD0195 dihydroxyacetone-P WD0091 glyceraldehyde-3P WD0337 WD0439 WD0786 WD0197 WD0451 PRPP WD1109,WD0763,WD0029,WD0913,WD1018,WD1024 Thiamine metabolismglycerol-3-phosphate/ WD0036hexose-6-phosphate 1,3-bisphosphoglycerate phosphate WD0619 WD1167 ribose-5P sedoheptulose-7P metabolite? WD0470 H + 3-phosphoglycerate glyceraldehyde-3P ATP metabolite? WD0868 WD0712 drugs ribulose-5P xylulose-5P WD1033 H + ADP WD0400 WD0551 2-phosphoglycerate WD0387 drugs metabolite? erythrose-4P WD0249 H+ WD0494 WD0387 H+ WD0248 glyceraldehyde-3P drugs phosphoenolpyruvate fructose-6P H+ Non-oxidative Pentose Phosphate Pathway WD0056 WD0690 drugs WD0695 putrescine pyruvate mannose-1P mannose-6P H+ WD0957 MALATE WD0488 WD1177 WD0384 ornithine WD0416 WD0684 drugs WD1295 WD0473 Amino Acid catabolism WD0895glutamate/aspartate WD0751 WD0325 WD0230 H+ WD0997 WD1239 WD1320 WD0211 Na+ WD0985, WD0650, WD1083, WD1170, WD0085 CYSTEINE alanine WD0228 ? Fatty Acid Biosynthesis acetyl-CoA WD1322 WD0461glutamate/aspartate GLUTAMATE glutamine UMP H+ WD0099 WD0229 Na+ GLUTAMINE WD0535 glutamate UDP ? WD0103 proline/betaine WD1151 citrate PROLINE glutamate H+ WD0621 WD1035 WD0168 H + SERINE glycine oxaloacetate WD0105 WD0617,WD0617 proline/betaine THREONINE glycine WD0414 WD1121 H+ isocitrate alanine/glycine malate TCA WD1046 Na+ CYCLE WD0791 WD0492 alanine/glycine WD0786 WD1047 Na+ adenylosuccinate fumarate oxaloacetate WD1029 aspartate WD0960 WD0954 aspartate semialdehyde WD0437 alanine/glycine WD0727 WD1309 F-type WD1221 WD0544 WD0330 Na+ WD1222 WD0751 ATPase succinate WD1209 suc-CoA WD1210 ADP ATP ADP ATP ADP ATP ATP ADP H+ H+ K + Mg2+ H+ Na+ H+ Na+ H+ Na+ H+ Zn2+/Cd2+ Zn2+ Fe3+ heme WD1233 WD1107 WD0203 WD1249 WD0375 WD0316 WD0407 WD1042 WD0362 WD1136 WD0411 WD0204 Wu et al., PLoS Biology 2004 WD1299 WD0938 WD0153 WD1093 WD1300 WD0427 WD0937 WD0897 WD0340 WD1391 WD0428 WD0816 WD0429 WD0765 WD0655 WD0656
    15. 15. Limitations of Culturing• Can’t perfectly mimic niche• Can’t mimic communities• Great plate count anomaly
    16. 16. The Uncultured Majority• Vast majority of microbes have never been cultured (total numbers and phylogenetic diversity)• Particularly true for endosymbionts and extremophiles• Main questions – Who is out there? – What are they doing? – Connect who and what.
    17. 17. Great Plate Count Anomaly Culturing Microscope Count Count
    18. 18. Great Plate Count Anomaly Culturing Microscope Count <<<< Count
    19. 19. Great Plate Count Anomaly Solution DNA Culturing Microscope Count <<<< Count
    20. 20. PCR Saves the Day
    21. 21. rRNA Phylotyping • Extract DNA • Run rDNA PCR • Sequence products • Infer evolutionary tree
    22. 22. rRNA and Uncultured Microbes Eisen et al. 1992
    23. 23. Majority of Microbes are “Uncultured” Numbers and Diversity
    24. 24. Phylotyping Can Be Used to Count Phylotyping Diversity Indices Hugenholtz 2002 Bohannan and Hughes 2003
    25. 25. Zoetendal, Erwin G., Vaughan, Elaine E. & de Vos, Willem M.A microbial world withinus.Molecular Microbiology ハ 59 ハ (6), ハ 1639-1650.doi: 10.1111/j.1365-
    26. 26. Rawls et al. 2006
    27. 27. Palmer et al 2007
    28. 28. Palmer et al. 2007
    29. 29. Mouth Diversity
    30. 30. GI Tract
    31. 31. Problems with rRNA PCR• Doesn’t predict biology of organisms well• Doesn’t work for viruses• Not very quantitative
    32. 32. Genome-Scale Methods and Uncultured Species• High throughput rDNA PCR (e.g., Sogin, Eisen)• rDNA “phylochips” (e.g., Brown, Anderson)• Virus chip (e.g., Derisi)• Metagenomics – Large inserts (e.g., Delong) – Environmental shotgun sequencing (Venter, Banfield, everyone doing because of power of random sampling)• Single cell genomics
    33. 33. Environmental Shotgun Sequencing shotgunWarner Brothers, Inc. sequence
    34. 34. Using a rRNA anchor allowed the identification of a new form of phototrophy: ProteorhodopsinBeja et al. 2000
    35. 35. rRNA Phylotypes Venter et al., 2004
    36. 36. taxonomic content per SHOTGUN 16S100%90%80%70%60%50%40%30%20%10% 0% G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G G S- S- S- S- S- S- S- S- S- S- S- S- S- S- S- S- S- S- S- S- S- S- S- S- S- S- S- S- S- S- S- S- S- S- 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 23 25 26 27 28 29 30 31 32 33 34 35 36 Station
    37. 37. Shotgun Sequencing Detects More Diversity than PCR-methods
    38. 38. What Next?• Selected as new NIH Roadmap Initiative• Current state of knowledge incredibly limited• 100s of body locations, and likely variation across people, places, diets, ages, etc need to be surveyed• New molecular and informatics methods needed
    39. 39. Binning in More Complex Systems?A TB UC VD WE XF YG Z
    40. 40. Metagenomic Challenges (Examples)• Fragmentary data• Sparse sampling• Parasitizing methods from standard genome analysis• Structure of communities unknown• Analyses frequently cover multiple levels and multiple fields of methods