Scalable metabolic reconstruction for metagenomic data and the human microbiome
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Scalable metabolic reconstruction for metagenomic data and the human microbiome. Sahar Abubucker , Nicola Segata , Johannes Goll , Alyxandria Schubert, Beltran Rodriguez-Mueller, Jeremy Zucker , the Human Microbiome Project Metabolic Reconstruction team, the Human Microbiome Consortium,

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Scalable metabolic reconstruction for metagenomic data and the human microbiome

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Scalable metabolic reconstruction for metagenomic data and the human microbiome

Scalable metabolic reconstructionfor metagenomic dataand the human microbiome

SaharAbubucker, Nicola Segata, Johannes Goll,Alyxandria Schubert, Beltran Rodriguez-Mueller, Jeremy Zucker,

the Human Microbiome Project Metabolic Reconstruction team,the Human Microbiome Consortium,

Patrick D. Schloss, Dirk Gevers, MakedonkaMitreva,Curtis Huttenhower

04-14-11

Harvard School of Public Health

Department of Biostatistics


What s metagenomics

What’s metagenomics?

Total collection of microorganisms within a community

Also microbial communityormicrobiota

Total genomic potential of a microbial community

Study of uncultured microorganisms from the environment, which can include humans or other living hosts

Total biomolecular repertoire of a microbial community


Scalable metabolic reconstruction for metagenomic data and the human microbiome

The Human Microbiome Project for a normal population

Multifaceted analyses

Multifaceted data

300 People/15(18) Body Sites

  • >12,000 samples

  • >50M 16S seqs.

  • 4.6Tbp uniquemetagenomicsequence

  • >1,900 referencegenomes

  • Full clinicalmetadata

  • Human population

  • Microbial population

  • Novel organisms

  • Biotypes

  • Viruses

  • Metabolism

2 clin. centers, 4 seq. centers, data generation,technology development, computational tools, ethics…


Scalable metabolic reconstruction for metagenomic data and the human microbiome

15+ Demonstration Projects for microbial communities in disease

Urogenital

Skin

Gastrointestinal

  • Obesity

  • Crohn’s disease

  • Ulcerative colitis

  • Autoimmunity

  • Cancer

  • Necrotizing enterocolitis

  • Psoriasis

  • Acne

  • Atopic dermatitis

  • Bacterialvaginosis

  • STDs

  • Reproductive health

All include additional subjects and technology development


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?

What do functional genomic data tell us about microbiomes?

What can our microbiomes tell us about us?

(x1010)

Public health tool monitoring population health and interactions

Diagnostic or prognostic biomarker for host disease


Metabolic functional reconstruction the goal

Metabolic/Functional Reconstruction: The Goal

Intervention/perturbation

Healthy/IBD

BMI

Diet

Biological story?

Independent sample

Batch effects?

Populationstructure?

Cross-validate

Geneexpression

Taxon abundances

Enzyme family abundances

Pathway abundances

SNPgenotypes

Niches &Phylogeny

Test forcorrelates

Confounds/stratification/environment

Featureselectionp >> n

Multiplehypothesiscorrection


Hmp metabolic reconstruction

HMP: Metabolic reconstruction

Functional seq.

KEGG + MetaCYC

CAZy, TCDB,VFDB, MEROPS…

300 subjects

1-3 visits/subject

~6 body sites/visit

10-200M reads/sample

100bp reads

BLAST

HUMAnN:HMP UnifiedMetabolic AnalysisNetwork

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

Smoothing

Witten-Bell

BLAST → Genes

Genes → Pathways

MinPath(Ye 2009)

WGS reads

Genes(KOs)

Taxonomic limitation

Rem. paths in taxa < ave.

?

Pathways(KEGGs)

Pathways/modules

Xipe

Distinguish zero/low(Rodriguez-Mueller in review)

Gap filling

c(g) = max( c(g), median )


Hmp metabolic reconstruction1

HMP: Metabolic reconstruction

Pathway coverage

Pathway abundance


Humann validating gene and pathway abundances on synthetic data

HUMAnN: Validating gene and pathwayabundances on synthetic data

Individual gene families

  • Validated on individual gene families, module coverage, and abundance

  • 4 synthetic communities:Low (20 org.) and high (100 org.) complexityEven and lognormal abundances

  • Few false negatives: short genes (<100bp),taxonomically rare pathways

  • Few false positives: large andmulticopy(not many in bacteria)

ρ=0.86


Functional modules in 741 hmp samples

Functional modules in 741 HMP samples

  • Zero microbes (of ~1,000)are core among body sites

  • Zero microbes are coreamong individuals

  • 19 (of ~220) pathways arepresent in every sample

  • 53 pathways are present in90%+ samples

PF

O(BM)

S

O(SP)

O(TD)

RC

AN

← Samples →

Coverage

← Pathways→

Abundance

  • Only 31 (of 1,110) pathwaysare present/absent fromexactly one body site

  • 263 pathways aredifferentially abundant inexactly one body site


A portrait of the human microbiome who s there

A portrait of the human microbiome:Who’s there?

With Jacques Izard, Susan Haake, Katherine Lemon


A portrait of the human microbiome what are they doing

A portrait of the human microbiome:What are they doing?

Pathway coverage


Hmp how do microbes vary within each body site across the population

HMP: How do microbes vary within each body site across the population?


Hmp how do body sites compare between individuals across the population

HMP: How do body sites compare between individuals across the population?


Hmp penetrance of species otus across the population

HMP: Penetrance of species (OTUs)across the population

Data from Pat Schloss


Hmp penetrance of genera phylotypes across the population

HMP: Penetrance of genera (phylotypes)across the population

Data from Pat Schloss


Hmp penetrance of pathways across the population

HMP: Penetrance of pathwaysacross the population

KEGG Metabolic modules

M00001: Glycolysis (Embden-Meyerhof)

M00002: Glycolysis, core module

M00003: Gluconeogenesis

M00004: Pentose phosphate cycle

M00007: Pentose phosphate (non-oxidative)

M00049: Adenine biosynthesis

M00050: Guanine biosynthesis

M00052: Pyrimidine biosynthesis

M00053: Pyrimidinedeoxyribonuleotide biosynthesis

M00120: Coenzyme A biosynthesis

M00126: Tetrahydrofolate biosynthesis

M00157: F-type ATPase, bacteria

M00164: ATP synthase

M00178: Ribosome, bacteria

M00183: RNA polymerase, bacteria

M00260: DNA polymerase III complex, bacteria

M00335: Sec (secretion) system

M00359: Aminoacyl-tRNA biosynthesis

M00360: Aminoacyl-tRNA biosynthesis, prokaryotes

M00362: Nucleotide sugar biosynthesis, prokaryotes

M00006: Pentose phosphate (oxidative)

M00051: Uridinemonophosphate biosynthesis

M00125: Riboflavin biosynthesis

M00008: Entner-Doudoroff pathway

M00239: Peptides/nickel transport system

M00018: Threonine biosynthesis

M00168: CAM (Crassulacean acid metabolism), dark

M00167: Reductive pentose phosphate cycle

  • Human microbiome functional structure dictatedprimarily by microbial niche, not host (in health)

  • Huge variation among hosts in who’s there;small variation in what they’re doing

  • Note: definitely variation in how thesefunctions are implemented

  • Does not yet speak in detail to hostenvironment (diet!), genetics, or disease


Population summary statistics population biology

Population summary statistics population biology

← Individuals →

Posterior fornix, ref. genomes

Lactobacillus iners

Lactobacillus crispatus

Gardnerellavaginalis

Lactobacillus jensenii

Lactobacillus gasseri

← Species →

Posterior fornix, functional modules

Essential amino acids

Basic biology, sugar transport

← Pathways →

Urea cycle, amines, aromatic AAs


Lefse metagenomic class comparison and explanation

LEfSe: Metagenomic classcomparison and explanation

LEfSe

LDA +Effect Size

Nicola Segata

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


Lefse evaluation on synthetic data

LEfSe: Evaluation on synthetic data

Their FP rate

Our FP rate


Microbes characteristic of the oral and gut microbiota

Microbes characteristic of theoral and gut microbiota


Aerobic microaerobic and anaerobic communities

Aerobic, microaerobic and anaerobic communities

  • High oxygen:skin, nasal

  • Mid oxygen:vaginal, oral

  • Low oxygen:gut


Lefse the truc murine colitis microbiota

LEfSe: The TRUC murine colitis microbiota

With Wendy Garrett


Microbial biomolecular function and biomarkers in the human microbiome the story so far

Microbial biomolecular function and biomarkers in the human microbiome: the story so far?

  • Who’s there changes

    • What they’re doing doesn’t (as much)

    • How they’re doing it does

  • The data so far only scratch the surface

    • Only 1/3 to 2/3 of the reads/sample map to cataloged gene families

    • Only 1/3 to 2/3 of these gene families have cataloged functions

    • Very much in line with MetaHIT study of gut microbiota

    • Job security!

  • Looking forward to functional reconstruction…

    • In environmental communities

    • With respect to host environment + genetics

    • With respect to host disease


Thanks

Thanks!

Human Microbiome Project

George Weinstock

Jennifer Wortman

Owen White

MakedonkaMitreva

Erica Sodergren

Mihai Pop

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

Jacques Izard

Nicola Segata

PinakiSarder

Ramnik Xavier

HMP Metabolic Reconstruction

Wendy Garrett

Bruce BirrenMark Daly

Doyle WardEric Alm

Ashlee EarlLisa Cosimi

Levi Waldron

LarisaMiropolsky

Interested? We’re recruiting graduate students and postdocs!

http://huttenhower.sph.harvard.edu

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

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


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