Metagenomics Biocuration 2013


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Metagenomics Biocuration 2013

  1. 1. Understanding the Gut Superorgan using Metagenomics Iddo Friedberg Miami University Oxford, Ohio ● Page: ● Blog: ● Twitter: @iddux
  2. 2. The Gut EcosystemCeliac Crohns Obesity Firmicutes ~500-1,000 ribotypes (97% ID) Bacteroidetes 47 GB protein coding
  3. 3. The Gut Superorgan Maloy & Powrie Nature (2011)
  4. 4. What can we learn and how?
  5. 5. Babies are a Good Model for Humans
  6. 6. Gut Microbiome Changes over Time Firmicutes Bacteroidetes Actinobacter Proteobacter Euryachaeota Verrumicrobia Viruses Fungi 0 6 85 92 96100118371413441432454Firmicutes dominate Actinobacteria Bacteroidetes: Fever at day 92? Eat plant matter
  7. 7. Breastfeeding vs. Bottle Feeding Benefits Not always possible Improved immune health Economic Fewer infections Social Reduced SIDS Medical Less obesity Beneficial to mothers too
  8. 8. Effect of Diet on Superorgan Microbial community Gut epithelial cells (metagenome) (transcriptome)
  9. 9. Microbial community Gut epithelial cells(metagenome) (transcriptome) 454 sequencing Clean & RT poly-A Who? (Phylogenetic analysis) Codelink chip What? (functional analysis) What? (functional analysis)
  10. 10. Correlations● Goals: ● understand effects of breast feeding and formula feeding on gut microbiota ● Understand effect on gut epithelium● Method: find correlations between bacterial gene presence and host gene expression Diet Epithelial Microbiome transcriptome
  11. 11. Who is there (phyla)?16S vs. GreenGenes Firmicutes Actinobacteria Proteobacteria Bacteoidetes VerrumicrobiaPhymmBL Firmicutes Actinobacteria Proteobacteria Bacteoidetes Verrumicrobia Schwartz, Friedberg et al. in revision
  12. 12. Who is there?● Variance in breastfed infants is larger than in formula-fed● Firmicutes dominate in FF, Bacteroidetes & Actinobacteria in BF
  13. 13. What are they doing?
  14. 14. What are they doing?
  15. 15. What are they doing?● More virulence-related genes in microbiome of breast-fed babies● Major contribution: “secretion systems”, and “miscellaneous” Type III Secretion System
  16. 16. Meanwhile, in the gut epithelium... (BF+FF)/2 (BF+FF)/2
  17. 17. Gut / Microbiome gene correlations● Goal: establish a significant covariance between epithelium expression and microbiome frequency● Many genes: multivariate assessment● Canonical Correlation Analysis (CCA) determines if a global relationship between 2 types of data-sets exists
  18. 18. CCA for Gut Superorgan Bacterial DNA Function Annotation CCA Expression levels Epithelial mRNA
  19. 19. Gut mRNA expression vs. Microbiome Function
  20. 20. Highly Expressed Host Genes in Correlation with VirulenceGene RoleREL* General transcription factor Proto-oncogene that may play a role in differentiation and lymphopoiesis. Component of NF-kB heterodimer RELA/p65-c-RelALOX5* Leukotriene synthesis. Leukotrienes are mediators of some inflammatory and allergic conditionsNDST1 Participates in biosynthesis of heparan sulfate that can ultimately serve as L- selectin ligands, thereby playing a role in inflammatory responseAOC3 participates in lymphocyte recirculation.VAV2** Vascular endothelial cell migrationDUOX2 lactoperoxidase-mediated antimicrobial defense at the surface of mucosa
  21. 21. GO Enrichment Analysis ofDifferential Epithelial TranscriptsEnrichment Score: 3.799TermGO:0002768~immune response-regulating cell surface receptor signaling pathwayGO:0002764~immune response-regulating signal transductionGO:0046649~lymphocyte activation Enrichment Score: 2.365 Term GO:0046635~positive regulation of alpha-beta T cell activation GO:0046634~regulation of alpha-beta T cell activation GO:0050870~positive regulation of T cell activation GO:0050863~regulation of T cell activation
  22. 22. Conclusions● Host: ● 11 Immunity related genes correlated with microbiome virulence genes ● Up-regulated in breast-fed infants● Microbiome: ● scavenging mechanisms, resistance to antibiotics and toxic compounds, Type III, Type IV, ESAT secretion systems, Type VI secretion systems all more frequent in breastfed infants.● Future Work: ● RNASeq analysis for host ● Metaproteomics? ●
  23. 23. People & Funding● Staff ● Rajeswari Swaminatham (Programmer)● Graduate students ● David Ream (Operon evolution) ● Funding ● Andrew Oberlin (Mycoplasma Genome Database) ● Ashwani Kumar ● NIH● Collaborators ● Mitchell Balish (MU) (Mycoplasma) ● NSF ● Predrag Radivojac (IU) (CAFA ) ● Robb Chapkin (TAMU) (Baby gut) ● Interwebs: ● Sharon Donovan (UIUC) (Baby gut) ● Scott Schwarz (TAMU) (Baby gut) ● Page: ● Jennifer Goldsby (TAMU) (Baby gut) ● Alexandra Schnoes (UCSF) (CAFA) ● Blog: (poster 82) ● Steven Brenner (UC Berkeley) (CAGI) ● Twitter: @iddux ● Miami University Supercomputing team Postdocs and students:
  24. 24. END SLIDE
  25. 25. Results: microbiome
  26. 26. Correlations
  27. 27. Host Metabolomics
  28. 28. Microbiome Metabolomics
  29. 29. Superorgan metabolomics
  30. 30. Gut and ImmunityDavid Artis Nature Reviews Immunology 8, 411-420 (June 2008)
  31. 31. The Trouble with Triples● Problem: too many genes – few samples● Reduce number of variables by grouping genes in triples● Triples that come up
  32. 32. Virulence and immunity