1. Understanding the Gut Superorgan
using Metagenomics
Iddo Friedberg
Miami University
Oxford, Ohio
● Page: iddo-friedberg.net
● Blog: bytesizebio.net
● Twitter: @iddux

2. The Gut Ecosystem
Celiac Crohn's Obesity
Firmicutes
~500-1,000 ribotypes
(97% ID)
Bacteroidetes
47 GB protein coding

3. The Gut Superorgan
Maloy & Powrie Nature (2011)

4. What can we learn and how?

5. Babies are a Good Model for Humans

6. Gut Microbiome Changes over Time
Firmicutes Bacteroidetes Actinobacter Proteobacter Euryachaeota Verrumicrobia Viruses Fungi
0
6
85
92
96
100
118
371
413
441
432
454
Firmicutes dominate Actinobacteria Bacteroidetes:
Fever at day 92? Eat plant matter

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. Effect of Diet on Superorgan
Microbial community Gut epithelial cells
(metagenome) (transcriptome)

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. 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. Who is there (phyla)?
16S vs. GreenGenes
Firmicutes Actinobacteria Proteobacteria Bacteoidetes Verrumicrobia
PhymmBL
Firmicutes Actinobacteria Proteobacteria Bacteoidetes Verrumicrobia
Schwartz, Friedberg et al. in revision

12. Who is there?
● Variance in breastfed
infants is larger than
in formula-fed
● Firmicutes dominate
in FF, Bacteroidetes &
Actinobacteria in BF

13. What are they doing?

14. What are they doing?

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. Meanwhile, in the gut epithelium...
(BF+FF)/2 (BF+FF)/2

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. CCA for Gut Superorgan
Bacterial DNA
Function Annotation
CCA
Expression levels
Epithelial mRNA

19. Gut mRNA expression vs.
Microbiome Function

20. Highly Expressed Host Genes in
Correlation with Virulence
Gene Role
REL* General transcription factor Proto-oncogene that may play a role in differentiation
and lymphopoiesis. Component of NF-kB heterodimer RELA/p65-c-Rel
ALOX5* Leukotriene synthesis. Leukotrienes are mediators of some inflammatory and
allergic conditions
NDST1 Participates in biosynthesis of heparan sulfate that can ultimately serve as L-
selectin ligands, thereby playing a role in inflammatory response
AOC3 participates in lymphocyte recirculation.
VAV2** Vascular endothelial cell migration
DUOX2 lactoperoxidase-mediated antimicrobial defense at
the surface of mucosa

21. GO Enrichment Analysis of
Differential Epithelial Transcripts
Enrichment Score: 3.799
Term
GO:0002768~immune response-regulating cell surface receptor signaling pathway
GO:0002764~immune response-regulating signal transduction
GO: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. 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. 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: iddo-friedberg.net
● Jennifer Goldsby (TAMU) (Baby gut)
● Alexandra Schnoes (UCSF) (CAFA) ● Blog: bytesizebio.net
(poster 82)
● Steven Brenner (UC Berkeley) (CAGI) ● Twitter: @iddux
● Miami University Supercomputing team
Postdocs and students:
friedberg.lab.jobs@gmail.com

24. END SLIDE

25. Results: microbiome

26. Correlations

27. Host Metabolomics

28. Microbiome Metabolomics

29. Superorgan metabolomics

30. Gut and Immunity
David Artis Nature Reviews Immunology 8, 411-420 (June 2008)

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. Virulence and immunity