1. The Human Microbiome in Health and Disease Curtis Huttenhower 10-21-11 Harvard School of Public Health Department of Biostatistics

2. What’s metagenomics? 2 Total collection of microorganisms within a community Also microbial community or microbiota Total genomic potential of a microbial community Total biomolecular repertoire of a microbial community Study of uncultured microorganisms from the environment, which can include humans or other living hosts

3. Valm et al, PNAS 2011

4. What to do with your metagenome? 4 Diagnostic or prognostic biomarker for host disease Public health tool monitoring population health and interactions Comprehensive snapshot of microbial ecology and evolution Reservoir of gene and protein functional information Who’s there? What are they doing? Who’s there varies: your microbiota is plastic and personalized. What they’re doing is adapting to their environment: you, your body, and your environment. Who’s there and what they do differ during disease and treatment.

5. The NIH Human Microbiome Project (HMP): A comprehensive microbial survey What is a “normal” human microbiome? 300 healthy human subjects Multiple body sites 15 male, 18 female Multiple visits Clinical metadata www.hmpdacc.org Slides by Dirk Gevers

6. Gene expression SNP genotypes A functional perspective on the human microbiome 6 Healthy/IBD BMI Diet Taxon abundances Enzyme family abundances Pathway abundances Functional seq. KEGG + MetaCYC CAZy, TCDB, VFDB, MEROPS… 100 subjects 1-3 visits/subject ~7 body sites/visit 10-200M reads/sample 100bp reads Metagenomic reads Enzymes and pathways ? HUMAnN HMP Unified Metabolic Analysis Network http://huttenhower.sph.harvard.edu/humann BLAST

7. HUMAnN: Metabolic reconstruction 7 Pathway coveragePathway abundance ← Samples → ← Pathways→ VaginalSkinNaresGutOral (SupP)Oral (BM)Oral (TD) ← Pathways→ ← Samples → VaginalSkinNaresGutOral (SupP)Oral (BM)Oral (TD)

8. ← Subjects → ← Pathway abundance → ← Phylotype abundance → A portrait of the healthy human microbiome: Who’s there vs. what they’re doing 8 VaginalSkinNaresGut Oral (SupP)Oral (BM)Oral (TD) ← Phylotype abundance → ← Subjects → ← Pathway abundance →

9. Linking function to community composition 9 ← Taxa and correlated metabolic pathways → ← 52 posterior fornix microbiomes → F-type ATPase, THF Sugar transport Phosphate and peptide transport AA and small molecule biosynthesis Embden-Meyerhof glycolysis, phosphotransferases Eukaryotic pathways Plus ubiquitous pathways: transcription, translation, cell wall, portions of central carbon metabolism… Lactobacillus crispatus Lactobacillus jensenii Lactobacillus gasseri Lactobacillus iners Gardnerella/Atopobium Candida/Bifidobacterium

10. Linking communities to host phenotype 10 Normalized relative abundance Vaginal pH (posterior fornix) Body Mass Index Top correlates with BMI in stool Vaginal pH, community metabolism, and community composition represent a strong, direct link between phenotype and function in these data. Vaginal pH (posterior fornix)

11. So that’s normal – what about disease? 11 With Matthew Meyerson, Alex Kostic Nicola Segata http://huttenhower.sph.harvard.edu/lefse LEfSe: LDA Effect Size

12. So that’s normal – what about disease? 12 TotalHealthyCDUCMFLeanOv.Ob. Danish86 004244351437 Spanish3813421142418155 Qin 2010 ~1-2Gbp 75bp shotgun reads/sample TotalHealthyCDUCMF<18 18-65 >65 OSCCAR11686147684823849 PRISM112275827615101102 ~1-4K 16S reads/sample Treatments: Antibiotics Immunosup. Mesalamine Steroids Location: Mucosal (biopsy) Luminal (stool) Genetics: ~200 loci, IBD-targeted

13. Microbes and their environment: What’s disease, what’s treatment, and what’s unrelated? 13 ~200 OSCCAR+PRISM individuals Multiple Factor Analysis: Form of Principal Components Analysis Separates individuals by similar patterns of variation in the gut microbiota

14. Microbes and their environment: What’s disease, what’s treatment, and what’s unrelated? 14 ~200 OSCCAR+PRISM individuals ?

15. Microbes and their environment: What’s disease, what’s treatment, and what’s unrelated? 15 ~200 OSCCAR+PRISM individuals Proteobacteria (Enterobacteriaceae) Firmicutes (Clostridia) Bifidobacteria

16. Environment and disease: You are your microbes’ environment: age, sampling, and treatment 16 ~200 OSCCAR+PRISM individuals Firmicutes Stool vs. biopsy Bifidobacterium Age Antibiotics Dorea Immunosuppresion Escherichia

17. But what about IBD? 17 Roseburia Ruminococcus Eggerthella In this cohort, main effects are a superset of previous findings Eggerthella in UC, weaker eff. than CD Willing 2010 Roseburia (Lachnospiraceae) down Frank 2007, Willing 2010 Ruminococcus down Willing 2010, Joossens 2011 Also correctly classify environment Proteobacteria up (immunosup.) Frank 2007, Willing 2010 Faecalibacterium down (ileal) Willing 2010, Frank 2011, Joossens 2011 And hey, what about… Diet? Sample handling? Assay?

18. But what about functional detail? IBD in the MetaHIT cohort 18 UC Up in CD Down in CD DNA maintenance CC + growth Sugar utilization Signaling + secretion Iron + drug transport MetaHIT seqs. → HUMAnN → pathway abundances

19. What about the host? A preview of host genetics 19 Genotyped microbiomes: 98 women (twin pairs + mothers) vaginal microbiomes + HPV phenotypes With GwangPyo Ko All linked to the same family of Clostridiales glycoprotein innate immune sensor extracellular signal transduction unch. TF glycoprotein Host genetics matter when not trumped by additional environment

20. A model for host genetics and the microbiome 20 A few genes exert strong control over a few bugs. Many genes exert strong distal control over many bugs due to founder effects. Many genes exert indirect control over many bugs due to polygenic immunity and disease phenotypes. Environment exerts strong proximal control over many bugs. A few bugs and many functions are strong proximal indicators or controllers of disease.

21. Ask both what you can do for your microbiome and what your microbiome can do for you

22. Matthew Meyerson Alex Kostic Ramnik Xavier Harry Sokol Thanks! 22 Nicola SegataLevi Waldron Fah Sathira Human Microbiome Project HMP Metabolic Reconstruction George Weinstock Karen Nelson Joe Petrosino Owen White Mihai Pop Pat Schloss Makedonka Mitreva Erica Sodergren Vivien Bonazzi Jane Peterson Lita Proctor Sahar Abubucker Yuzhen Ye Beltran Rodriguez-Mueller Jeremy Zucker Qiandong Zeng Mathangi Thiagarajan Brandi Cantarel Maria Rivera Barbara Methe Bill Klimke Daniel Haft Dirk Gevers Bruce BirrenMark Daly Doyle WardEric Alm Ashlee EarlLisa Cosimi http://huttenhower.sph.harvard.edu Joseph Moon Vagheesh Narasimhan Tim Tickle Xochi Morgan Josh Reyes Jeroen Raes Karoline Faust Jacques Izard Shuji Ogino Charlie Fuchs Wendy Garrett Michelle Rooks Interested? We’re recruiting graduate and rotation students!

24. Proteoglycan degradation by the gut microbiota 24 AA core Glycosaminoglycans (Polysaccharide chains)

25. Proteoglycan degradation: From pathways to enzymes 25 10 -3 10 -8 Enzyme relative abundance Heparan sulfate degradation missing due to the absence of heparanase, a eukaryotic enzyme Other pathways not bottlenecked by individual genes HUMAnN links microbiome-wide pathway reconstructions → site-specific pathways → individual gene families

26. ← Pathway abundance→ ← ~700 HMP communities→ Niche specialization in human microbiome function 26 Metabolic modules in the KEGG functional catalog enriched at one or more body habitats 16 (of 251) modules strongly “core” at 90%+ coverage in 90%+ individuals at 7 body sites 24 modules at 33%+ coverage 71 modules (28%) weakly “core” at 33%+ coverage in 66%+ individuals at 6+ body sites Contrast zero phylotypes or OTUs meeting this threshold! Only 24 modules (<10%) differentially covered by body site Compare with 168 modules (>66%) differentially abundant by body site 16 (of 251) modules strongly “core” at 90%+ coverage in 90%+ individuals at 7 body sites 24 modules at 33%+ coverage 71 modules (28%) weakly “core” at 33%+ coverage in 66%+ individuals at 6+ body sites Contrast zero phylotypes or OTUs meeting this threshold! Only 24 modules (<10%) differentially covered by body site Compare with 168 modules (>66%) differentially abundant by body site

27. Patterns of variation in human microbiome function by niche 27

28. Patterns of variation in human microbiome function by niche 28 Three main axes of variation Eukaryotic exterior Low-diversity vaginal Gut metabolism Oral vs. tooth hard surface Only broad patterns: every human-associated habitat is functionally distinct!

29. LEfSe: the TRUC murine colitis microbiota 29 With Wendy Garrett

30. But what about functional detail? IBD in the MetaHIT cohort 30 UC Up in CD Down in CD