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Charting the function of microbes and microbial communities. Curtis Huttenhower 11- 17- 11. Harvard School of Public Health Department of Biostatistics. Valm et al, PNAS 2011. What to do with your metagenome?. Reservoir of gene and protein functional information.

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charting the function of microbes and microbial communities

Charting the function of microbesand microbial communities

Curtis Huttenhower

11-17-11

Harvard School of Public Health

Department of Biostatistics

what to do with your metagenome
What to do with your metagenome?

Reservoir of gene and protein functional information

Comprehensive snapshot of microbial ecology and evolution

Who’s there?

What are they doing?

Who’s there varies: your microbiota is plastic and personalized.

This personalization is true at the level of phyla, genera, species, strains, and sequence variants.

What they’re doing is adapting totheir environment:you, your body, and your environment.

Public health tool monitoring population health and interactions

Diagnostic or prognostic biomarker for host disease

slide4

Slides by Dirk Gevers

The NIH Human Microbiome Project (HMP): A comprehensive microbial survey

  • What is a “normal” human microbiome?
  • 300 healthy human subjects
  • Multiple body sites
    • 15 male, 18 female
  • Multiple visits
  • Clinical metadata

www.hmpdacc.org

slide6

~36%

~57%

~50%

…for mining metagenomic data

16S

WGS

>3k readsper sample

~100M readsper sample

Filtering/

trimming

Assembly

Map on

BLASTagainst functionalDBs

Chimera removal

contigs

ref

Annotation

Taxonomicclassification

(RDP)

Clusteringinto OTUs

genes

census...

~90M proteins

pathways

Organismal censusat different taxonomic levels

pathogen carriage varies a lot
“Pathogen” carriage varies a lot

22 ***uniquely identifiable*** nonzero abundance “pathogens” from NIAID’s list of 135

Gemella

Capnocytophaga

Gardnerella

Actinomyces

Alistipes

>0.66

+Propionibacterium

a functional perspective on the human microbiome
A functional perspective on thehuman microbiome

100 subjects

1-3 visits/subject

~7 body sites/visit

10-200M reads/sample

100bp reads

Healthy/IBD

BMI

Diet

Metagenomic reads

BLAST

Functional seq.

KEGG + MetaCYC

CAZy, TCDB,VFDB, MEROPS…

?

Geneexpression

SNPgenotypes

Taxon abundances

Enzyme family abundances

Pathway abundances

Enzymes and pathways

HUMAnN

HMP Unified MetabolicAnalysis Network

http://huttenhower.sph.harvard.edu/humann

humann metabolic reconstruction
HUMAnN: Metabolic reconstruction

Vaginal

Oral (BM)

Gut

Oral (SupP)

Oral (TD)

Skin

Nares

← Pathways→

← Samples →

Vaginal

Skin

Nares

Oral (SupP)

Oral (BM)

Oral (TD)

Gut

← Pathways→

← Samples →

Pathway coverage

Pathway abundance

a portrait of the healthy human microbiome who s there vs what they re doing
A portrait of the healthy human microbiome:Who’s there vs. what they’re doing

← Subjects →

← Phylotype abundance →

← Phylotype abundance →

Oral (BM)

Oral (SupP)

Oral (TD)

Nares

Vaginal

Skin

Gut

← Pathway abundance →

← Pathway abundance →

← Subjects →

niche specialization in human microbiome function
Niche specialization in human microbiome function

Metabolic modules in theKEGG functional catalogenriched at one or morebody habitats

← Pathway abundance→

← ~700 HMP communities→

  • 16 (of 251) modules strongly “core” at 90%+ coverage in 90%+ individuals at 7 body sites
    • 24 modules at 33%+ coverage
  • 71 modules (28%) weakly “core” at 33%+ coverage in 66%+ individuals at 6+ body sites
    • Contrast zerophylotypes or OTUs meeting this threshold!
  • Only 24 modules (<10%) differentially covered by body site
  • Compare with 168 modules (>66%) differentially abundant by body site
proteoglycan degradation by the gut microbiota
Proteoglycan degradationby the gut microbiota

Glycosaminoglycans(Polysaccharide chains)

AA core

proteoglycan degradation from pathways to enzymes
Proteoglycan degradation:From pathways to enzymes

Enzyme relative abundance

10-8

10-3

  • Heparan sulfate degradation missing due to the absence ofheparanase, a eukaryotic enzyme
    • Other pathways not bottlenecked by individual genes
  • HUMAnN links microbiome-wide pathway reconstructions → site-specific pathways → individual gene families
patterns of variation in human microbiome function by niche1
Patterns of variation in human microbiome function by niche
  • Three main axes of variation
    • Eukaryotic exterior
    • Low-diversity vaginal
    • Gut metabolism
  • Oral vs. tooth hard surface
  • Only broad patterns: every human-associated habitat is functionally distinct!
slide19

Normal varies a lot at the genus level (16S)

Relative frequency of genera within Stool

343 genera

Parabacteroides

Faecalibacterium

Alistipes

Relative frequency

Bacteroides

200 subjects

Dirk Gevers

slide20

Normal varies a lot at the species level (WGS)

Relative frequency of Bacteroides species within Stool

Relative frequency

Bacteroides caccae

Bacteroides stercoris

Bacteroides sp.

Bacteroides uniformis

Bacteroides sp.

Bacteroides vulgatus

123 samples

Dirk Gevers

what s wrong with this picture
What’s wrong with this picture?

Species and strains matter – but so does your method for identifying them in a community!

52 posterior fornix microbiomes →

Lactobacillus crispatus MV-1A-US

Lactobacillus crispatus JV-V01

Lactobacillus crispatus 125-2-CHN

Lactobacillus crispatus 214-1

Lactobacillus crispatus MV-3A-US

Lactobacillus crispatus ST1

Lactobacillus gasseri JV-V03

Lactobacillus gasseri 202-4

Lactobacillus gasseri 224-1

Lactobacillus gasseri MV-22

Bifidobacteriumbreve DSM 20213

Bifidobacteriumdentium ATCC 27679

Mycoplasma hominis

Clostridialesgenomosp BVAB3 str UPII9-5

Clostridialesgenomosp BVAB3 UPII9-5

Gardnerellavaginalis AMD

Prevotellatimonensis CRIS 5C-B1

Megasphaeragenomosp type 1 str 28L

Porphyromonasuenonis 60-3

Gardnerellavaginalis 409-05

Gardnerellavaginalis 5-1

Atopobiumvaginae DSM 15829

Gardnerellavaginalis ATCC 14019

Lactobacillus jensenii 1153

Lactobacillus jensenii 269-3

Lactobacillus jensenii SJ-7A-US

Lactobacillus jensenii 208-1

Lactobacillus jensenii JV-V16

Lactobacillus jensenii 27-2-CHN

Lactobacillus jensenii 115-3-CHN

Lactobacillus iners AB-1

Lactobacillus iners DSM 13335

core gene families
Core gene families
  • A core gene is a gene strongly conserved within a clade

Gene X

  • Gene X is a core gene for Clade Y
  • All subclades of Clade Y must have Gene X as core gene (strict definition)
  • Gene X may be a core gene of several (unrelated) clades
  • We have to relax the definition for taking into account:
  • Low-level gene losses
  • Sequencing errors
  • Gene calls errors
clade specific marker genes
Clade-specific marker genes

Gene X

  • Gene X is a marker gene (for Clade Y) if X is a core gene for Y and X never appears outside Clade Y
the bactochip high throughput microbial species identification
The BactoChip: high-throughput microbial species identification

With Olivier Jousson, Annalisa Ballarini

bactochip detecting single species
BactoChip: detecting single species

With Olivier Jousson, Annalisa Ballarini

metaphlan inferring microbial abundances from metagenomic data using marker genes
MetaPhlAn: inferring microbial abundancesfrom metagenomic data using marker genes
  • Map metagenomicreads to marker genes to infer microbial abundances
    • Normalizing for copy number, gene length, etc.

Much faster than existing approaches as the marker gene database is ~50 times smaller than the whole microbial sequence DB

 Few hours instead of weeks for Illumina samples with 100Gb of sequence data

MetaPhlAn:Metagenomic Phylogenetic Analysis

http://huttenhower.sph.harvard.edu/metaphlan

metaphlan synthetic validation on log normal abundances
MetaPhlAn: synthetic validation on log-normal abundances

Summary of 8 synthetic communities composed by 2M reads coming from 200 organisms with log-normal distributed abundances concentrations

Species-level

Class-level

Species level

Class level

whence enterotypes
Whence enterotypes?

Genera

Species

microbial community function and structure in the human microbiome the story so far
Microbial community function and structure in the human microbiome: the story so far?
  • Who’s there varies even in health
    • What they’re doing doesn’t (as much)
    • Both correlate with niche
    • By the way: both change during disease and treatment
  • There are patterns in this variation
    • Function correlates with membership and phenotype
    • “Pathogenicity” correlates with lower prevalence
    • Membershipmeans species, strains, or variants
    • Patterns aren’t always as simple as enterotypes
  • ~1/3 to 2/3 of human metagenome characterized
    • Job security!
thanks
Thanks!

Human Microbiome Project

Owen White

George Weinstock

Karen Nelson

Joe Petrosino

Mihai Pop

Pat Schloss

MakedonkaMitreva

Erica Sodergren

VivienBonazzi

Jane Peterson

Lita Proctor

SaharAbubucker

Yuzhen Ye

Beltran Rodriguez-Mueller

Jeremy Zucker

QiandongZeng

MathangiThiagarajan

Brandi Cantarel

Maria Rivera

Barbara Methe

Bill Klimke

Daniel Haft

Dirk Gevers

Nicola Segata

Xochi Morgan

Levi Waldron

HMP Metabolic Reconstruction

Bruce Birren Mark Daly

Doyle Ward Eric Alm

Ashlee Earl Lisa Cosimi

Ramnik Xavier

Harry Sokol

Joseph Moon

FahSathira

Tim Tickle

Jacques Izard

Olivier Jousson

Annalisa Ballarini

JeroenRaes

Karoline Faust

Wendy Garrett

Michelle Rooks

VagheeshNarasimhan

Josh Reyes

http://huttenhower.sph.harvard.edu

linking function to community composition
Linking function to community composition

Plus ubiquitous pathways: transcription, translation, cell wall, portions of central carbon metabolism…

← 52 posterior fornix microbiomes →

Phosphate and peptide transport

Lactobacillus crispatus

Lactobacillus jensenii

Sugar transport

Embden-Meyerhof glycolysis, phosphotransferases

Lactobacillus gasseri

Lactobacillus iners

F-type ATPase, THF

← Taxa and correlated metabolic pathways →

AA and small molecule biosynthesis

Gardnerella/Atopobium

Candida/Bifidobacterium

Eukaryotic pathways

linking communities to host phenotype
Linking communities to host phenotype

Top correlates with BMI in stool

Body Mass Index

Normalized relative abundance

Vaginal pH (posterior fornix)

Vaginal pH, community metabolism, and community composition represent a strong, direct link between phenotype and function in these data.

Vaginal pH (posterior fornix)