The Human Microbiome Project

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Transcript The Human Microbiome Project

Brie Bibb
David Chong
Julia Cochran
Brandon Crostick
Nick Niland
What makes a human?
 Human metabolic features- combo of human and
microbial traits
 Microbiota- microrganisms that live inside and on
 Microbiome- the genomes of the microbial symbionts
Goals of HMP
 To break down artificial barriers between medical
microbiology and environmental microbiology
 Ultimately to associates differences in communities
with differences in metabolic function and/or disease
Possible questions that may be
answered by the HMP
 How stable and resilient is an individual’s microbiota
throughout one day and during his/her lifespan?
 How similar are microbiomes between members of a
family, community or across communities in different
 Do all humans have an identifiable “core” microbiome and
how is it acquired and transmitted?
 What affects the genetic diversity of the microbiome and
how does this diversity affect adaptation by the
microrganism and the host to markedly different lifestyles
and to various physiological or pathophysiological states?
 Sampling:
 temporal (over course of time) scales
 Biogeography: spatial scales
Microbiomes will need to be characterized by comparing
limited data types collected from a limited set of individuals
What do we know about the
human microbiome?
 From comparative metagenomics
 uncovered functional attributes of the microbiome
Functional contributions of gut
 Synthesis of vitamins and harvest of otherwise
inaccessible nutrients
 Metabolism of xenobiotics and other metabotypes
 Renewal of gut epithelial cells
 Development and activity of the immune system
 Cardiac size?
 Locomotion
Needs for success
 How do you define a “healthy” individual?
 How do you get rid of those darn host cells?
Connecting gene fragments to organisms
 Classification without using phylogenetic marker
 Markov-based model:
 Uses frequency of short nucleotide sequences (relatively
insensitive for short sequences and heterogeneous genomes)
 Homology-based sequencing:
 Accurate and provides additional advantage of placing each
sequence in the context of multiple alignment and a
phylogenetic tree
 Combination is the best for determining functions
associated with the genome
Key Issues
 Effectiveness due to horizontal gene transfer
 Better, faster, more scalable method for generating a
huge phylogenetic tree that contains millions of
 Identify the best way to account for the affects of the
Proposals of HMP
 Associate differences in communities with differences
in metabolic function and/or disease
 Move toward an integrated ‘system metagenomics’
 Functional gene arrays
 New diagnostic biomarkers of health
 Industrial application
 Deeper understanding of nutritional requirements of
 Personalized drug and diet regimen
16S rRNA
1541 bases
Found in
bacteria and
Freitas and Merkle, 2004
Bacteroidetes and Firmicutes
make up >99% of all
One prominent
Relman, D. 2009
Sequencing the microbiome
 Took Venter’s whole-genome shotgun sequencing
approach in studying the mixed microbial
 The abundance of a species is represented by the
random shotgun sequence coverage of that species.
 Compared shotgun rRNA sequences with PCR of rRNA
sequences and analyzed metabolic pathways with
known clusters of orthologous groups.
Experimental Procedures
 Overview of Procedures:
 Shotgun Sequence Stool Samples
Taxonomic Assignment using Shotgun Data ORF’s
Taxonomic Assignment Via Shotgun Data rRNA
 Taxonomic Assigment using rRNA PCR
 Metabolic Pathway Enrichment Analyses
Shotgun Sequencing
•.3g fecal matter
•28 yo female
•36 yo male
•One vegetarian,
•One meat eater
•Travel to Brazil, France
•Stayed home
•No antibiotics
•No medical problems
Venter et. al. 2001
Taxonomic Assigment Using
Shotgun Data rRNA Sequences
 Shotgun Sequence Compared with Known 16s
Ribosomal Subunit Sequences Using Blastn
 Using Contigs Greater Than 200 BP
Taxonomic Assigment Using
Shotgun Sequence ORF’s
 Long-Orfs program used to identify ORF’s
 ORF’s then searched with BLASTP
 Majority Rule for multiple assigments
 Specific assigments should be viewed with caution
Taxonomic Assigment Using PCR
 Broadrange primers used to amplify DNA coding 16s
ribosomal subunit.
 Cloned into TOPO vectors, incubated in E.coli
 Sequenced using ABI 3730 sequencers
 1024 sequences aligned to in house Ribosome
Database Project program.
 Chimeras removed
 Phylotypes assigned with 99% match
 Novel phylotypes considered uncultured
Metabolic Pathway Enrichment
 Used only identified genes
 Sequences compared with NCBI Cluster of
Orthologous Groups(COGs) Data.
 Genes also analysed with KEGG(encyclopedia of
 Together metabolic assignments were made to genes
Metabolic Pathway Enrichment
 Enrichment of metabolic pathways given a odds ratio
 Determined by equation (sample metabolic
level/ancestral model level)
 Metabolic pathways with values over 1 considered
Comparison of random metagenome reads
with completed genome of B. longum and
M. smithii
* AMOScmp was used to identify closely related organisms to previously
sequenced species
Bifidobacterium longum – A lactic acid bacteria
-1965 Reads from (from subjects 7 and 8) 1,617,706bp of DNA
-Very strong homolgy but 52% of reads less than 95% identity
What does this suggest?
Methanobrevibacter smithii – The dominant archaea in the gut
-3.5x coverage with 7955 reads
-8 partial 16rDNA match ups
-89% of reads 95% greater identity – suggesting?
-145/259 archaeal contigs had significantly similar identity to smithii
-Identified genes using blastx w/all
open reading frames with >35%
-All enzyme commissions (EC’s)
that were highly redundant were
removed for analysis
-KEGG: Pathway maps for
metabolism and other cellular
processes, as well as human
diseases; manually created from
published materials
-Cog: Each COG consists of
individual proteins or groups of
paralogs from at least 3 lineages and
thus corresponds to an ancient
conserved domain.
-Most metabolic functions were
similar between the two subjects,
but there were differences in a few
functional categories, possibly
caused by differences in diet and
-81 different glycoside hydrolase
families were found in the
microbiome, many of which are not
present in the human glycobiome,
helps break down and metabolize
glucose, galactose, fructose,
arabinose, manose, xylose.
The odds ratio of human genome (red), bacterial genome in KEGG (blue),
and archaeal genome (yellow). The graph shows that the human distal gut
metabolic functions can regulate most metabolic processes, however, the
presence of certain bacteria and archaea do contribute to metabolic
KEGG(kyoto encycopedia of genes and genomes), COG’s(clusters of
orthologous groups). Used to compare function groups of genes against a
baseline bacterial metabolism. And score for enrichment
COGs representing enzymes in the MEP (2-methyl-D-erythritol 4phosphate) pathway, used for biosynthesis of deoxyxylulose 5-phosphate
(DXP) and isopenteryl pyrophosphate (IPP), are notably enriched (P G
0.0001; relative to all sequenced microbes)
DXP is a precursor in the biosynthesis of vitamins essential for human
health, including B1 and B6
MEP pathway may be new avenue for anti-biotic research
Some bacteria use the MEP pathway instead of the mevanolate pathway
for IPP biosynthesis
This could be detrimental to gut flora and potentially the host
Gut microbiome enriched for methanogenic pathway
This helps remove H2 from the gut via methanogenesis.
Future Research
 Future research could be conducted on people with and without IBS
crohn’s or any other gastrointestinal disorder
Better coverage needed for shotgun sequencing
Also new experimental approach should be created which allow the
sequencing of the more fragile phyla of bacteria, such as bacteroitides
Analyses of horizontal gene transfers in gut microbes
Quantitation of metabolites etc, contributed and consumed by gut
Effects of antibiotic administration of gut flora and the host, succesion
of microbes after antibiotics, and creation of pathogenic specific
antibiotics that don’t effeect the gut flora or at least minimalize effects
Personalized medicine, dietary needs
I vote for the creation of synthetic butt microbes that create specific
metabolites that a host may lack or could make bigger faster stronger
smarter or somehow enhance with super human turd powers
Could be used in longetudinal health research
 Thanks to Professor Young and the Western
Washington University Biology Department!