Human Microbial Metagenomics: Understanding Our Microbial Selves

1. Human Microbial Metagenomics:Understanding Our Microbial Selves Claire M. Fraser-Liggett, Ph.D. University of Maryland School of Medicine Institute of Genome Sciences

2. What is human metagenomics? • Why are these microbial communities important? • How are metagenomics studies different from traditional genomics projects? • Summary of results from recent human metagenomics studies • Looking to the future: • Challenges and opportunities • implications for human health and disease Topics of discussion

3. A new science that seeks to understand biology at the aggregate level, transcending the individual organism to focus on the genes in the community and how they interact to serve a collective function. It is both a set of research techniques AND a research field. It is the science of (microbial) communities. Metagenomics will be the systems biology of the biosphere. The New Science of MetagenomicsNational Research Council Report

4. The Human Microbial Metagenome Microbiome A multi-genus/species community of bacteria that exists within a defined environmental domain Human Microbiome The community of bacteria that live on/in the human host (mucosal surfaces, skin, tooth surface, etc.) Beneficial/neutral/adversarial Metagenomics The culture-independent study of the genomes of many organisms simultaneously in order to understand microbial communities as intact systems

5. The Human Microbial Metagenome Humans are born without any microorganisms Colonization of skin, oral/respiratory tract, genitourinary system and gastrointestinal tract begins immediately at birth Our adult bodies contain 10 times more microbial cells than human cells Human colon contains up to 100 trillion bacteria Numerous studies have suggested that shifts in the populations of microbial communities may be associated with a number of important acute and chronic diseases: inflammatory bowel disease, obesity, cardiovascular disease, eczema and other skin diseases, vaginal infections This presents an opportunity to develop new approaches to therapy as a means of maintaining health

6. The Human Microbial Metagenome Four environments on the human body are the most densely populated with microorganisms: -gastrointestinal tract (800 phylotypes) -oral cavity (500 phylotypes) -vagina (200 phylotypes) -skin (100 phylotypes) Our current focus is on the colon, the oral cavity, and the vagina.

7. How to study the human microbiome?

8. Surveys of community diversity • Gene/genome content – whole genome sequencing • Functional analysis – work in progress • Mapping of community function back to single cells – future goal A Metagenomics Blueprint

9. Molecular fingerprinting (T-RFLP) • Array-based approaches (Affymetrix Phylochip) • 16S rDNA gene amplification and sequencing Assays of community diversity

10. 75 Caucasian T-RFLP analysis of human vaginal microbial communities Forney and Ravel (unpublished) 16 community types were identified among Caucasian women 75 African-American 12 community types were identified among African-American women

11. Version 2.0 of the Affymetrix PhyloChip targets over 30,000 unique 16S rRNA sequences, totaling almost 9,000 distinct taxonomic groups Hybridization-based approaches

12. Firmicutes Bacteroidetes Proteobacteria Actinobacteria Fusobacteria Verrucomicrobia Cyanobacteria VadinBE97 Spirochaeates Synergistes Microbial mat: 1595 sequences 44 divisions 10 of 70 described divisions of Bacteria • Our ‘metagenome’ is a composite of Homo sapiens genes and genes present in the genomes of the trillions of microbes that colonize our adult bodies Setting The Stage 16S rRNA sequence-based enumeration of the adult human distal gut microbiota Eckburg et al. (11,831 sequences) Ley and Gordon (19,653 sequences)

13. 1% 1% 1% 1% 1% 2% 1% 2% 2% 2% 1% 2% 2% 2% 2% 25% 2% 2% 2% 2% 2% 2% 28% 3% 3% 2% 25% 2% 3% 3% 2% 3% 2% 3% 3% 3% 3% 5% 4% 4% 14% 4% 7% 5% 18% 12% 4% 8% 5% 12% 6% 11% 10% 11% 7% 16S rRNA Sequencing – Human Gut Microbiome Taxonomy – 16S r DNA Human 1 Bacteroides Clostridium Bifidobacterium Thermoanaerobacter Bacillus Human 7 Enterococcus Streptococcus Treponema Porphyromonas Human 8 Vibrio Listeria Streptomyces Fusobacterium Lactobacillus Geobacter Methanosarcina Pseudomonas Escherichia Oceanobacillus Heliobacillus

14. Metagenomics can theoretically access 100% of an environment Direct isolation of DNA from the environment Traditional cultivation and genomics can at best access between 1-10% of an environment Isolation and laboratory cultivation DNA Traditional genomics approaches

15. Streptococcus gordonii CH1 50 kb Sequence and assemble amp plasmid amp insert amp plasmid Diversity = 1,000 plasmid 100 kb 4-10 kb insert insert Metagenomics of the Human Microbiome Genomics Sequence and assemble amp plasmid insert amp plasmid amp Diversity = 1 plasmid 4-10 kb insert insert Metagenomics

16. 28 year-old female; 37 year-old male, one a vegetarian; no antibiotics in the previous year • 65,959 and 74,462 reads from random libraries of fecal DNA • Science 312, 1355–1359 (2006)

17. Amount of overlap shared between 19,866 unique blastx database matches for the two random libraries Human-7 Human-8 7,593 5,700 6,573

18. Metagenomics of the Human Colon Microbiome Glycan metabolism The plant polysaccharides we consume are rich in xylan-, pectin- and arabinose-containing carbohydrate structures. The human genome lacks most of the enzymes required for degrading these glycans. At least twenty six different glycoside hydrolase families are encoded in the microbiome, many of which are not present in the human glycobiome. Enrichment for genes in the starch metabolism pathway in the human colonic microbiome. The left and right sides of each boxed EC number indicate whether the microbial gene product is present in human colonic samples 7 and 8, respectively, and to what extent (color scale: white no hits; red ≥17 hits).

19. COG analysis reveals enrichment for archaeal metabolism. (A) Five archaeal COGs are significantly enriched (p<1e-5). (B) STRING protein map of COGs (colored) and predicted interactors (grey). (C) Location and role of each enzyme in methanogenesis. STRING lines indicate neighborhood (green) and co-occurence (blue) connections.

20. HMP Human Gut Microbiome Initiative • Goal: Deep draft assemblies of 100 cultured representatives of the divisions represented in the adult microbiota; Scaffolds to help interpret metagenomic datasets • Approach: Initial selection based on cultured representatives of phylotypes in 16S rRNA datasets [public input on choices; straincollections] • Development of ways for faster/cheaper sequencing (multiple platforms); new assembly tools (hybrid assemblies); improved annotation schemes; creation of integrated databases

21. Metagenomics of the Human Colon Microbiome Genome diversity –”Pan”-microbial genomes? Bifidobacterium longum Methanobrevibacter smithii

22. Genomic diversity genomic halo(strain-specific) core core non essential non essential CLOSED Pan-genomeConsistent with more isolated lifestyle and limited access to global microbial gene pool OPEN Pan-genomeConsistent with colonization of multiple environments and opportunity for multiple mechanisms of DNA exchange

23. Collaboration with Jeffrey Gordon (Washington University) and Robin Knight (University of Colorado Boulder) • Study subjects will be lean and obese Caucasian and African-American twin pairs and their mothers • New insights about the role of the gut microbiome in regulating energy balance in humans • New strategies for targeting the microbiome for intentional manipulation to treat obesity Human Gut Microbiome and Energy Balance

24. Evidence for a link between gut microbial communities and adiposity • Colonization of adult germ-free mice with a gut microbial community from conventionally-raised mice produces a rapid and marked increase in adiposity without an increase in food consumption • Equivalent response in males and females from several inbred lines • Does not require a functional innate or adaptive immune system • Mechanism: increased fermentation of otherwise indigestible dietary polysaccharides; microbial regulation of host genes that regulate storage of extracted calories in adipocytes

25. Bacteroidetes Identification of a linkage between adiposity and microbial ecology in mice Genetic (ob/ob) Diet-induced Genetic and diet-induced mouse models of obesity both exhibit increased abundance of Firmicutes

26. Following an initial loss of ~5% body weight, there is a progressive, statistically significant, division-wide shift towards more Bacteroidetes and fewer Firmicutes as more weight is lost • Changes occur independent of diet Linkage between gut ecology and adiposity in humans

27. Crohn’s disease (Robert Hettich and Janet Jannson) • Necrotizing enterocolitis (Steven Zeichner) • Role of the immune system in regulating GI microbial composition (HIV patients and patients undergoing chemotherapy) Other Gastrointestinal Studies

28. Do we all share an identifiable core ‘microbiome’ surrounded by a shell of diversity? Is this best defined by species, gene content, or functional capabilities? • Should differences in our microbiome be viewed, along with our immune and nervous systems, as features of our biology that are profoundly affected by both our genotypes and by our individual environmental exposures? • How is the human microbiome evolving (within and between individuals) over varying time scales as a function of age, diets, disease, lifestyle, and biosphere? • Are changes in community composition the cause of disease or a read-out of a disease process? Human Microbial Metagenomics: Grand Challenges

29. How do we define “normal” when there appears to be a great deal of inter-individual variability? • What are the appropriate meta-data to collect? • How often should communities be sampled? • What is the best approach for sample archiving? • What are the best surrogates for longitudinal monitoring of communities? __________________________________________ • Better tools for deep community sampling • Better tools for measuring function at both the single-cell and community level • Better tools for measuring metabolite and gene flow in situ • Better ways of storing and analyzing disparate data sets Human Microbial Metagenomics: Technical Issues

30. Microbial Genomics Group Jonathan Eisen Rob Fleischmann Steve Gill John Heidelberg Barbara Methe Garry Myers Karen Nelson Scott Peterson David Rasko Jacques Ravel Herve Tettelin Naomi Ward Robert DeBoy Emmanuel Mongodin Bioinformatics Group Owen White Neil Hall Jennifer Wortman Collaborators Jeffrey Gordon (Washington University) David Relman (Stanford University) Rob Knight (University of Colorado Boulder) Acknowledgements