Metagenomics: a gene-centric approach for the human gut microbiome research

Masahira HATTORI

Center for Omics and Bioinformatics / Dept. of Computational Biology

Graduate School of Frontier Sciences, University of Tokyo

http://www.cb.k.u-tokyo.ac.jp/hattorilab

・ Human-associated pathogens and commensals including intestinal microbiota・ Symbionts in insects・ Host-microbial interactions

The Kashiwa campus

Body Site bacteria/ml or gram

# species

? Nose 103-104 Oral 1010 total

>700

Saliva 108-1010 Gingival crevice 1012 Tooth surface 1011 Gastrointestinal Tract 1014 total

>1000

Stomach 100-104 Small intestines 104-107

Colon (feces) 1011-1012

Skin 1012 total

?

Surface 105

Urogenital 1012 total?

?

Vagina 109 Human cells 1013 total

Oral

Gastrointestinal

Skin

Urogenital

Nasal

The total number of these bacterial cells is estimated to be more than 1014, representing 10 times more than the total number of eukaryotic cells that compose a human individual .

An enormous number of microorganisms, of which the majority is bacterial species, are known to colonize and form complex communities (called the human microbiota) at various human body sites

The human microbiota

Among them, the largest and most complex is the gut microbiota, which is composed of more than 1,000 different intestinal microbes.

*多彩な代謝機能（ヒトとの共生関係 )

Many metabolic capabilities (mutualism between them and us)

*宿主の腸管上皮細胞の増殖と分化Proliferation and differentiation of host epithelial cells

*宿主の免疫系の成熟化（恒常性の維持）Development of the host immune system

*感染病原菌の防御Protection against pathogens

*細菌叢組成はさまざまな疾患の素因となる。Imbalance of the gut microbiota composition predisposes individuals to a variety of disease states ranging from inflammatory bowel diseases such as Crohn’s disease and ulcerative colitis to allergy, colon cancer, obesity and diabetes.

Human gut microbiota possess a strong impact on human physiology

The process of metagenomic analysis of the human gut microbiota

Microbial DNA(Metagenomic DNA)

Shotgun library

Fragmentation of DNA to ~ 3kb

…GGATCCATCGTACCGATTC……TTACAATTTACGGCCATCC…

…CCATGCGATCGATCGGAAT……CCATGGCCGAAATTTCGTA…

…AGCTAAAATTACCGGGGAT…

Shotgun reads (~ 800 bases)

Contig Contig Singleton

Assembly

Non-redundant sequence of microbial DNA

Intensive analysis of the sequences by bioinformatics

Gut microbiota

Lysis of microbiotaSequencer

Contigs Contigs Singletons

Non-redundatmicrobial sequences

Gene set

Classification of COGs to functional categories Replication Novel genesAmino acid

metabolismTranscriptionCarbohydrate

metabolismLipidmetabolism

Functional profile of microbiome

Metagenomics: a gene-centric analysis to explore the biological nature of microbiome, the collective genomes of microbiota

Clustering and similarity search (COG assignment)

COGs: Clusters of orthologous groups

Importantly, the functional profile becomes constant and unique to the community when the sequence amount is beyond the threshold which depends on the complexity of microbial composition.

Enriched COGs only in microbiome H

Comparative metagenomics between different microbiomes is powerful to identify enriched or depleted genes in an individual microbiome

Freq

uenc

y

H

High

G

B

C

D

E

F

A

COG

Commonly enriched COGs among all microbiomes

Var

ious

en

viro

nmen

tal

mic

robi

omes

Depleted COGs in microbiome ALow

Timeline of sequence-based metagenome projects since 2003Hugenholtz P and Tyson GW: Nature 455, 481-483 (2008)

3730 dye-terminator shotgun sequencing (black)Fosmid library sequencing (pink) 454 Pyrosequencing (green)

200 projects Sep. 09

Subjects

13 healthy Japanese individuals including 7 adults, 2 weaned children and 4 unweaned infants, from 3 months to 45 years old, and 2 unrelated families.

Metagenomics of 13 healthy Japanese gut microbiomesKurokawa K et al. DNA Res. 14, 169-181 (2007).

family family

Metagenomics of 13 Japanese gut microbiomes

Gut microbiota Bacterial DNA

DNA sequencingAbout 500 Mb assembled unique sequences from about 730 Mb data

660,000 genes found of which 160,000 were novel gene candidates

Further analyses

Kurokawa K et al. DNA Res. 14, 169-181 (2007).

Metagenomics of 13 healthy Japanese gut microbiomes

Total: 1,065,392 reads (727 Mb) / 13 samples80,000 sanger reads (55 Mb) / sample

20,063-67,740 genes ( 20 a.a.) / sample≧662,548 genes / 13 samples

1,617-2,921 COGs / sample3,268 COGs / 13 samples162,647 novel gene candidates (25%)

Sequencing

Gene identification in 479 Mb non-redundant sequence

Clustering and similarity search / COG assignment of genes

Kurokawa K et al. DNA Res. 14, 169-181 (2007).

Protein-coding gene prediction

A program, MetaGene, based on a hidden Markov Model (HMM) algorithm :

Noguchi H, Takagi T et al. MetaGene: prokaryotic gene finding from environmental genome shotgun sequences.

NAR, 34, 5623-5630 (2006).

Genes were predicted from ORFs having ≥ 20 a.a. in non-redundant sequences.

The same COG

Gut microbiome Ref-DB

Orthologous genes

NR of the gut microbiome / NR of Ref-DB = Enrichment value ≧ 2

Normalized ratio (NR) = the number of genes / the total number of genes

Comparison of genes in the 13 human gut microbiomes with those in Ref-DB (constructed from genes in 243 microbes excluded gut microbes)

Survey of enriched COGs in human gut microbiomes

>>

Enriched COGs: COGs that contains orthologous genes with statistically higher frequency in the human gut microbiome than in Ref-DB.

0

2

4

6

8

10

12

14

16

18

20

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 2.4 2.5 2.5 >

Ave. 0.9Enriched COGs ≧ 2

Distribution of COG enrichment values for 126 eCOGs clustered by 150 essential genes of E. coli and B.subtilis

0.3 ≦ Enrichment values of 125 eCOGs ≦ 1.9

DepletedCOGs <0.3

179

7858

Adult-type (237)

Infant-type(136)

Total: 315 COGs

Identification of 315 gut-enriched COGs in 13 human intestinal microbiomes

315 all COGs

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

1

Functional categories of the 315 gut-enriched COGs identified in 13 human microbiomes

CarbohydrateCarbohydrateConserved but Conserved but

function unknownfunction unknown

Repair/modificationRepair/modification

Cell wall/membrane Cell wall/membrane

Energy production Energy production Inorganic ionInorganic ion

Amino-acidAmino-acid

Adult-type (237)

Infant-type (136)Total: 315 COGsOverlapped (58)

20% 33%

Carbohydrate metabolism

Functional adaptability of the gut microbiome

Transporter : infants > adults/children (e.g. phosphotransferase systems (PTSs))

Polysaccharide degradation : adults/children > infants (e.g. glycosyl hydrolases)

The functionality of gut microbiome is largely affected by diet.

Depleted function

Cell motility (genes for flagella and chemotaxis)

•Loss of possible antigens recognized by host immunity. •Peristaltic motion of the intestine.

Adaptive evolution of gut microbiome towards maintenance of host homeostasis

Intestinal microbes may have evolved to acquire and accumulate functions advantageous for colonization of gut habitat, while eliminating undesired appendages that could result in sensing for pro-inflammatory responses.

Content of gut-enriched genes (adult) in sequenced genomes of 371 representative microbes isolated from various environments

Ave. 9.2%

Ave. 4.0%Ave. 2.7%

Human gut microbes may have evolved by acquiring and accumulating adaptive genes to gut habitat.

>2-fold higher than DB>4-fold higher than DB

>10-fold higher than DB

Genes remarkably varied in frequency among individual microbiomes

Lower than DB

Deconjugation

Vitamin B12 biosynthesis

COG3250, 3119, 4225

COG1270, 1010

Deconjugation and Vitamin B12 biosynthesis

A D R S T V W

4.148 10.275 6.273 5.259 5.715 2.064 1.995 6.138

5.377 4.551 3.365 2.689 2.773 0.846 2.024 3.522

5.701 15.712 16.806 11.329 15.948 2.948 7.550 10.676

4.166 1.616 1.731 0.923 1.562 0.563 1.785 2.347

4.668 2.055 1.813 4.477 1.971 1.379 2.565 0.959

Glucuronated conjugatesSulfonated conjugates

Relative frequencies

Max/Min

Comparison of the KEGG pathways between the human gut and the sea surface

Sea-specific pathways Gut-specific pathways

Sphingolipid metabolismArachidonic/linoleic acid metabolism

The adult- and infant-types

Weaning may be the time to change from the infant type to the adult-type.

No strong association was found within family samples

Adult-type： stable, robust to environmentInfant-type： unstable, sensitive to environment

Overall sequence similarity of genes between individual microbiomes by reciprocal pairwise blastp analyses

Adults/children

Americans

Unweaned infants

Soil

Sea

Whale fall

・ Relatively high similarity among adults and weaned children

・ Relatively high variation among unweaned infants

The gut microbiota may be unique to individual

647 novel gene families composed only of 5 - 48 orthologous genes of human gut microbiomes

No-hit genes (162,647 genes) in the 13 human intestinal microbiomes

Clustering

Clusters

Novel gene families specific to the human gut microbiome

Possible functions : •Advantageous for competitive survival in human gut habitat. •Tolerant to transient but harsh conditions encountered during travel through the mouth and stomach to the gut.

+ No-hit genes in metagenomic data of sea and soil communities

About 100 conserved but function unknown gut-enriched genes

Good research targets to find novel functions of gut microbes

Sample: a human gut microbiome

ABI 3730xl (Sanger)

79,163

54.9 Mb

700

Production 30 days

Relative cost 1

Total bases

Read length

Read#

Metagenomic sequencing of gut microbomes by 454FLXTi based on pyrosequencing

Roche 454FLX Ti(1 run)

1,166,204

433 Mb

371.3

5 days

0.1

Gene# 40,300 186,000

No cloning process, no bacterial culture

Metagenomic sequencing of human gut microbiomes by 454 GSFLX Titanium

Total num of reads Human sequences Artifact reads Unique reads

APr01S00 1,423,122 0.40% 18.24% 81.36%

APr09S00 1,133,611 0.45% 14.57% 84.98%

APr16S00 818,894 0.55% 22.25% 77.19%

APr20S00 1,044,786 0.47% 16.94% 82.58%

APr29S00 1,117,685 0.39% 27.18% 72.42%

Problem in 454 data: artifact reads = reads having the same starting base

454 data (1 run) APr01S00 APr06S00 APr16S00 APr20S00 APr29S00

Total num of reads 1,423,122 1,133,611 818,894 1,044,786 1,117,685

Num of unique reads 1,157,883 963,351 632,118 862,794 809,466

(*Reason: multiple beads for one DNA molecule in one emulsion)

Sequencing of human microbesBy 3730xl only or 3730xl + 454FLX

Human microbes (in-house): 56 strains

HMP :247 strains (draft) released.

HMPInternational Human Microbiome Project

Shotgun reads or genes identified in individual samples

Genome 1 Genome 2 Genome 3 Genome 4 Genome 5

Reference genomes

Accurate assignment of shotgun reads or metagenomic genes to bacterial genomes

Mapping to reference genomes

Mapped reads: 47% (average)

454 data (1 run) APr01S00 APr06S00 APr16S00 APr20S00 APr29S00

Num of unique reads 1,157,883 963,351 632,118 862,794 809,466

Mapping of metagenomic reads on 1,236 reference bacterial genomes (including 247 HMP and 56 in-house strains)

Mapped Unmapped ≥ 90% identity, ≥ 100 bases

Taxonomic analysis of the Japanese gut microbiota based on mapping of metagenomic reads (Phylum level)

Actinobacteria Bacteroidetes Firmicutes

The genomes of 27 Bacteroides species have been sequenced.

Bacterial composition at the species level in the same genus by mapping of metagenomic reads

Bacterial composition at the species level in the BifidobacteriaThe genomes of 14 Bifidobacteriaum species have been sequenced.

The microbial composition is highly varied but the functionality is uniform between individuals.

Turnbaugh PJ et al. Nature 2009

Conclusion

1. The functionality of gut microbiome is largely affected by diet.

2. Intestinal microbes may have evolved to acquire and accumulate functions advantageous for colonization of gut habitat, while eliminating undesired appendages that could result in sensing for pro-inflammatory responses, towards maintenance of host homeostasis.

3. Many function-unknown genes are conserved and are present in intestinal microbes.

4. The microbial diversity is highly varied but the functionality is similar between individuals

5. The gut microbiota may be unique to individual and the origin of intestinal microbiota is unknown.(No strong association of the microbiota was found within the family)

Next and ongoing plans

1) More sampling of Japanese healthy individuals. ・ To standardize Japanese intestinal microbiome (including probiotics-

treated subjects and long-term chase of the same subjects)

2) Sampling of disease-afflicted subjects (IBD, colon cancer, allergy…..) and comparison with samples of healthy subjects

・ To identify bacteria, genes and gene products associated with the pathogenecity of the disease.

3) Comparison between samples of different nations who have different dietary style and genetic background each other.

・ To know how diet and genetic background affect the intestinal microbiota○ Sequencing of individual microbes isolated from human body sites

More than 100 strains isolated from the Japanese

○ Metagenomics and 16S analysis of human intestinal microbiomes.

○ Functional studies of intestinal microbes using germ-free mice

These works are being conducted as part of the International Human Microbiome Project that was launched in 2008.

Host genetic factors

Human genomeGenetic variation

Intestinal microbiomeGenetic diversity

Environmental factors

Interactions

To explore and identify both host and bacterial genes or their products as genetic and environmental factors involved in health promotion and maintenance as well as the etiology of diseases such as IBD (Crohn’s disease and ulcerative colitis) and allergy.

Whole genome sequencing Sequence-based metagenomics

Our goal is…

High-throughput sequencing technology + Bioinformatics

16S sequencing Metagenomic sequencing Genome sequencing

Sampling of microbiota from gastrointestinal and urogenital tracts, nasal, oral and skin of several hundreds of healthy and disease-afflicted subjects

Microbial diversity

Genetic and functional diversity

Sequencing of >1,000 species as reference genomes

Integrated database of human microbiomes and microbes

International Human Microbiome Project

International Human Microbiome Consortium (IHMC)

Australia, Canada, China, France (as EU), Ireland, Japan, Korea, Singapore, UK and US

Launched in 2008

+ Metadata of the subjects

Membersin Human MetaGenome Consortium Japan (HMGJ)

Kikuji Itoh

All in a day’s catch !

Ken Kurokawa, Hiroshi Mori, Takehiko Itoh, Hideki Noguchi

Graduate School of Information Science, Tokyo Institute of Technology

Institute of Health Biosciences, University of Tokushima Graduate School

Tomomi Kuwahara

Frontier Science Research Center, University of Miyazaki

Tetsuya Hayashi, Yoshitoshi Ogura

RIKEN Genomic Sciences Center

Hidehiro Toh, Atsushi Toyoda, Vineet K. Sharma, Tulika P. SrivastavaTodd D. Taylor, Yoshiyuki Sakaki

Japan Agency for Marine-Earth Science and Technology

Hideto Takami Graduate School of Frontier Sciences, University of Tokyo

Kenshiro Oshima, Kim Sok-Won, Chie Yoshino, Hiromi Inaba, Keiko Furuya, Yasue Hattori, Erika Iioka, Kanako Motomura, and Masahira Hattori

School of Veterinary Medicine, Azabu University

Hidetoshi Morita

Graduate School of Agricultural and Life Sciences, University of Tokyo

26 persons /10 Universities and Institutes

Hiroshi Ohno, Shinji FukudaRIKEN Center for Allergy & Immunology