Scalable metabolic reconstruction for metagenomic data and the human microbiome

1. Scalable metabolic reconstructionfor metagenomic dataand the human microbiome SaharAbubucker, Nicola Segata, Johannes Goll,Alyxandria Schubert, Beltran Rodriguez-Mueller, Jeremy Zucker, the Human Microbiome Project Metabolic Reconstruction team,the Human Microbiome Consortium, Patrick D. Schloss, Dirk Gevers, MakedonkaMitreva,Curtis Huttenhower 04-14-11 Harvard School of Public Health Department of Biostatistics

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

3. The Human Microbiome Project for a normal population Multifaceted analyses Multifaceted data 300 People/15(18) Body Sites • >12,000 samples • >50M 16S seqs. • 4.6Tbp uniquemetagenomicsequence • >1,900 referencegenomes • Full clinicalmetadata • Human population • Microbial population • Novel organisms • Biotypes • Viruses • Metabolism 2 clin. centers, 4 seq. centers, data generation,technology development, computational tools, ethics…

4. 15+ Demonstration Projects for microbial communities in disease Urogenital Skin Gastrointestinal • Obesity • Crohn’s disease • Ulcerative colitis • Autoimmunity • Cancer • Necrotizing enterocolitis • Psoriasis • Acne • Atopic dermatitis • Bacterialvaginosis • STDs • Reproductive health All include additional subjects and technology development

5. What to do with your metagenome? Reservoir of gene and protein functional information Comprehensive snapshot of microbial ecology and evolution Who’s there? What are they doing? What do functional genomic data tell us about microbiomes? What can our microbiomes tell us about us? (x1010) Public health tool monitoring population health and interactions Diagnostic or prognostic biomarker for host disease

6. Metabolic/Functional Reconstruction: The Goal Intervention/perturbation Healthy/IBD BMI Diet Biological story? Independent sample Batch effects? Populationstructure? Cross-validate Geneexpression Taxon abundances Enzyme family abundances Pathway abundances SNPgenotypes Niches &Phylogeny Test forcorrelates Confounds/stratification/environment Featureselectionp >> n Multiplehypothesiscorrection

7. HMP: Metabolic reconstruction Functional seq. KEGG + MetaCYC CAZy, TCDB,VFDB, MEROPS… 300 subjects 1-3 visits/subject ~6 body sites/visit 10-200M reads/sample 100bp reads BLAST HUMAnN:HMP UnifiedMetabolic AnalysisNetwork http://huttenhower.sph.harvard.edu/humann Smoothing Witten-Bell BLAST → Genes Genes → Pathways MinPath(Ye 2009) WGS reads Genes(KOs) Taxonomic limitation Rem. paths in taxa < ave. ? Pathways(KEGGs) Pathways/modules Xipe Distinguish zero/low(Rodriguez-Mueller in review) Gap filling c(g) = max( c(g), median )

8. HMP: Metabolic reconstruction Pathway coverage Pathway abundance

9. HUMAnN: Validating gene and pathwayabundances on synthetic data Individual gene families • Validated on individual gene families, module coverage, and abundance • 4 synthetic communities:Low (20 org.) and high (100 org.) complexity Even and lognormal abundances • Few false negatives: short genes (<100bp), taxonomically rare pathways • Few false positives: large andmulticopy (not many in bacteria) ρ=0.86

10. Functional modules in 741 HMP samples • Zero microbes (of ~1,000) are core among body sites • Zero microbes are core among individuals • 19 (of ~220) pathways are present in every sample • 53 pathways are present in 90%+ samples PF O(BM) S O(SP) O(TD) RC AN ← Samples → Coverage ← Pathways→ Abundance • Only 31 (of 1,110) pathways are present/absent from exactly one body site • 263 pathways are differentially abundant in exactly one body site

11. A portrait of the human microbiome:Who’s there? With Jacques Izard, Susan Haake, Katherine Lemon

12. A portrait of the human microbiome:What are they doing? Pathway coverage

13. HMP: How do microbes vary within each body site across the population?

14. HMP: How do body sites compare between individuals across the population?

15. HMP: Penetrance of species (OTUs)across the population Data from Pat Schloss

16. HMP: Penetrance of genera (phylotypes)across the population Data from Pat Schloss

17. HMP: Penetrance of pathwaysacross the population KEGG Metabolic modules M00001: Glycolysis (Embden-Meyerhof) M00002: Glycolysis, core module M00003: Gluconeogenesis M00004: Pentose phosphate cycle M00007: Pentose phosphate (non-oxidative) M00049: Adenine biosynthesis M00050: Guanine biosynthesis M00052: Pyrimidine biosynthesis M00053: Pyrimidinedeoxyribonuleotide biosynthesis M00120: Coenzyme A biosynthesis M00126: Tetrahydrofolate biosynthesis M00157: F-type ATPase, bacteria M00164: ATP synthase M00178: Ribosome, bacteria M00183: RNA polymerase, bacteria M00260: DNA polymerase III complex, bacteria M00335: Sec (secretion) system M00359: Aminoacyl-tRNA biosynthesis M00360: Aminoacyl-tRNA biosynthesis, prokaryotes M00362: Nucleotide sugar biosynthesis, prokaryotes M00006: Pentose phosphate (oxidative) M00051: Uridinemonophosphate biosynthesis M00125: Riboflavin biosynthesis M00008: Entner-Doudoroff pathway M00239: Peptides/nickel transport system M00018: Threonine biosynthesis M00168: CAM (Crassulacean acid metabolism), dark M00167: Reductive pentose phosphate cycle • Human microbiome functional structure dictated primarily by microbial niche, not host (in health) • Huge variation among hosts in who’s there; small variation in what they’re doing • Note: definitely variation in how these functions are implemented • Does not yet speak in detail to host environment (diet!), genetics, or disease

18. Population summary statistics population biology ← Individuals → Posterior fornix, ref. genomes Lactobacillus iners Lactobacillus crispatus Gardnerellavaginalis Lactobacillus jensenii Lactobacillus gasseri ← Species → Posterior fornix, functional modules Essential amino acids Basic biology, sugar transport ← Pathways → Urea cycle, amines, aromatic AAs

19. LEfSe: Metagenomic classcomparison and explanation LEfSe LDA +Effect Size Nicola Segata http://huttenhower.sph.harvard.edu/lefse

20. LEfSe: Evaluation on synthetic data Their FP rate Our FP rate

21. Microbes characteristic of theoral and gut microbiota

22. Aerobic, microaerobic and anaerobic communities • High oxygen: skin, nasal • Mid oxygen: vaginal, oral • Low oxygen: gut

23. LEfSe: The TRUC murine colitis microbiota With Wendy Garrett

24. Microbial biomolecular function and biomarkers in the human microbiome: the story so far? • Who’s there changes • What they’re doing doesn’t (as much) • How they’re doing it does • The data so far only scratch the surface • Only 1/3 to 2/3 of the reads/sample map to cataloged gene families • Only 1/3 to 2/3 of these gene families have cataloged functions • Very much in line with MetaHIT study of gut microbiota • Job security! • Looking forward to functional reconstruction… • In environmental communities • With respect to host environment + genetics • With respect to host disease

25. Thanks! Human Microbiome Project George Weinstock Jennifer Wortman Owen White MakedonkaMitreva Erica Sodergren Mihai Pop VivienBonazzi Jane Peterson Lita Proctor SaharAbubucker Yuzhen Ye Beltran Rodriguez-Mueller Jeremy Zucker QiandongZeng MathangiThiagarajan Brandi Cantarel Maria Rivera Barbara Methe Bill Klimke Daniel Haft Dirk Gevers Jacques Izard Nicola Segata PinakiSarder Ramnik Xavier HMP Metabolic Reconstruction Wendy Garrett Bruce Birren Mark Daly Doyle Ward Eric Alm Ashlee Earl Lisa Cosimi Levi Waldron LarisaMiropolsky Interested? We’re recruiting graduate students and postdocs! http://huttenhower.sph.harvard.edu http://huttenhower.sph.harvard.edu/humann http://huttenhower.sph.harvard.edu/lefse