[2013.10.29] albertsen genomics metagenomics

Genomicsand

MetagenomicsMads Albertsen

Introduction to community systems microbiology2013

CENTER FOR MICROBIAL COMMUNITIES

Agenda

Genomics• Introduction• Assembly• Validation• Metabolic reconstruction (SM @ Thursday)

Metagenomics• History• Pitfalls• Potentials

CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITY

Introduction


Genome = Parts list of a single genome

Introduction


How to get from sequenced DNA to metabolic model?

Introduction


Extract DNA Shear DNA Sequence

Wet lab work

Bioinformatics

Reads50-500 bp

Assembly ScaffoldingContigs

1kb – 100 kbp

N N

ScaffoldsHopefully Mbp

Definitions


Read

Paired-end read

Mate-pair read

Insert size

Contig

Scaffold

Coverage

N

> 1 kbp insert

A sequenced piece of DNA

Sequencing both ends of a short DNA fragment

Sequencing both ends of a long DNA fragment

The length of the DNA fragment

A set of overlapping DNA segments that represents a consensus region of DNA

Contigs separated by gaps of known length

The number of times a specific position in the genome is covered by reads

50-500 bp

300-600 bp insert

length

4x

Assembly


Genome

Fragment

Sequence

AssembleScaffold 1

Inspiration: http://goo.gl/VOZVVg

Scaffold 2

Paired-end reads

Contig 1 Contig 19Contig 10

http://goo.gl/VOZVVg



Assembly

CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITYInspiration: http://goo.gl/VOZVVg

Genome(3.000.000 letters)

Reads(50-500 letters each)

Sequencing Assembly

Genome(3.000.000 letters)




Assembly


“It was the best of times, it was the worst of times, it was the age of

wisdom, it was the age of foolishness, it was the epoch of belief, it was

the epoch of incredulity,.... “

Dickens, Charles. A Tale of Two Cities. 1859. London: Chapman Hall

Example: http://goo.gl/nMWDAkVelvet example courtesy of J. Leipzig 2010

http://goo.gl/nMWDAk



Assembly

CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITYExample: http://goo.gl/nMWDAkVelvet example courtesy of J. Leipzig 2010

Way too much data to make all vs. all comparison




Assembly


theageofwi

the hea eag age geo eof ofw fwi

sthebestof

sth the heb ebe bes est sto tof

astheageof

ast sth the hea eag age geo eof

worstoftim

wor ors rst sto tof oft fti tim

Imesitwast

ime mes esi sit itw twa was ast

Reads

Kmers (k = 3)

Step 1: Convert reads into kmers




Assembly


ast sth the hea eag age geo eof

Step 2: Join kmers with n-1 overlap




Assembly


ast sth the hea eag age geo eofthe hea eag age geo eof ofw fwi

sth theheb ebe bes est sto tof

wor ors rststo tof

tim

oft

fti

ast

was

twa

itw sit esi mes ime

Step 2: Join kmers with n-1 overlap

Do the same for all reads…




Assembly


Step 3: Simplify the graph




Assembly


“It was the best of times, it was the worst of times, it was the age of

wisdom, it was the age of foolishness, it was the epoch of belief, it was

the epoch of incredulity,.... “ Dickens, Charles. A Tale of Two Cities. 1859. London: Chapman Hall

≠

It was the

be

wor

age

epochst

oftimes

wisdom

foolishness belief

incredulity

=Contigs




Assembly


What is the minimum kmer size that results in a single contig?

Kmer = 3




Assembly


What is the minimum kmer size that results in a single contig?

Kmer = 3

ItwasthebestoftimesitwastheworstoftimesitwastheageofwisdomitwastheageoffoolishnessitwastheepochofbeliefitwastheepochofincredulityKmer = 10




Assembly


Repeat = repeated DNA sequence that can’t be spanned by reads




Assembly


Why not just increase the kmer size?




Assembly


the hea eag age geo eof ofw fwi

theageofw heageofwi

theageofwi

Errors!

Kmer = 3 Kmer = 9

Kmers with errors = 2/2

Kmers with errors = 3/8




Validation


I’ve assembled my 4.3 Mbp genome into 25 scaffolds

with a N50 of 553 kbp.

Is it a good assembly?

Validation


N50

Validation


Estimating repeat content

Validation


4 repeats in 2 copies each

Validation


4 repeats in 2 copies each

How could I close this genome?

Validation


How complete is the genome?

Validation


100-106 Essential single copy genes

(can also be used to identify contamination)

Gen

es

Phyla

Survey of essential single copy genes across sequenced phyla

Validation

CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITYInspect the assembly

Validation


• N50 does not make much sense

• Repeat content versus the number of scaffolds• Calculate the percentage of essential genes• Inspect the assembly

Metabolic reconstruction


4.3 Mbp genome… and so what?

(@Thursday)

Metagenomics

Mads AlbertsenIntroduction to community systems microbiology

2013

CENTER FOR MICROBIAL COMMUNITIES

Introduction


Genome = Parts list of a single genome

Introduction


Metagenome = Parts list of the community

Photo: D. Kunkel; color, E. Latypova

Introduction

”...functional analysis of the collective genomes of soil microflora, which we term the metagenome of the soil.”

- J. Handelsman et al., 1998


Introduction

PubMed: metagenom*[Title/Abstract]




Introduction




PubMed: metagenom*[Title/Abstract]

Sequencing costs

http://www.genome.gov/sequencingcosts/

Introduction


Metagenomics ≠ Amplicon sequencing

Sequencing and assembly


≈3.000.000 bppr. genome

≈1000 bp+contigs

150 bp reads

Assigning information


Contigs

Function

Taxonomy

Databases

Binning

What have metagenomics been used for?


Rusch et al., 2007 Plos Biology

Exploration

Qin et al., 2010 Nature

• 6.3 Gbp of sequence (2x Human genomes, 2000 x Bacterial genomes)

• Most sequences were novel compared to the databases

• 127 Human gut metagenomes• 600 Gbp sequence (200 x Human genomes)• 3.3 million genes identified• Minimal gut metagenome definded



• A characteristic microbial fingerprint for each of the nine different ecosystem types

Dinsdale et al., 2008 Nature

Comparative Specific functions

Hess et al., 2011 Science

• Identified 27.755 putative carbohydrate-active genes from a cow rumen metagenome

• Expressed 90 candidates of which 57% had enzymatic activity against cellulosic substrates



• Genome extraction from low complexity metagenome

• Candidatus Accumulibacter phosphatis• The first genome of a polyphosphate

accumulating organism (PAO) with a major role en enhanced biological phosphorus removal

Extracting genomes

• Genome extraction of low abundant species (< 0.1%) from metagenomes

• First complete TM7 genome• Access to genomes of the ”uncultured

majority”

Garcia Martin et al., 2006 Nat. Biotechnol. Albertsen et al., 2013 Nat. Biotechnol.

Pitfalls


Metagenomics made easy


Great resources – but use with care

MG-RAST example


Contigs


Dataset overview


FunctionTaxonomy

Taxonomy and Function overview


Compare with other samples

Samples Functional categories

Pitfalls


You always get billions of data!


Pitfalls

Is your DNA extraction OK?... and the samples you want to compare with?

Did you sequence enough?Did you know the GC bias of your protocol?Did you normalize for sequencing depth?Did you use the same sequencing platform?

Assembly = data not quantitative!Are you comparing assembled data with reads?


Databases

Contigs

Databases

...you only see what is in the database

Annotated metagenome


What is in the databases?

PhylaClassOrderSpecies

2946

1001268

90249405

99322

Genomes 16S

Finshed Genomes in IMGVs.

Greengenes 16S rRNA database

Note: only including 1 strain pr. species

*97% clustering

*

MG-RAST example


Contigs

650.000 EBPR proteins with taxonomy assigned

How similar are they to the genomes in the database?

Sludge microbes vs. Database genomes


650.000 EBPR proteins

Note: not abundance weighted



650.000 EBPR proteins1.260.000 Human gut

Qin et al., 2010 NatureRAST ID: 4448044.3

Note: not abundance weighted



The 7 genera with most EBPR proteins assigned

Effect of missing genomes

What is the effect of not having closely related genomes in the database?

1. Remove a genome from the database

2. Search the removed genome against the database




Best hit

Bacteria 1268Proteobacteria 564Betaproteobacteria 84Rhodocyclales 5Rhodocyclaceae 5

Accumulibacter phosphatis

blastp

Related genomes

4326 proteins



Best hit


blastp

Related genomes

4326 proteinsAzoarcus




MEGAN LCA


blastp

Lowest common ancester (LCA) approach:Hit 1: Beta-proteobacteria 80% IDHit 2: Gamma-proteobacteria 79% IDHit 3: Actinobacteria 59% ID

Assigned to Proteobacteria

Related genomes

4326 proteins




MEGAN LCA


blastp

Genus

No hits 261

Bacteria 325

Proteobacteria 860

Beta- 853

Rhodocyclaceae 1149

4326 proteins:• 27% correctly

classified on genus level

• 54% not assigned the correct class

• 101 genera identified

Related genomes

Lowest common ancester (LCA) approach:Hit 1: Beta-proteobacteria 80% IDHit 2: Gamma-proteobacteria 79% IDHit 3: Actinobacteria 59% ID

Assigned to Proteobacteria

4326 proteins




MEGAN LCA

Nitrospira defluvii

Bacteria 1268Nitrospirae 3

blastp

Related genomes

4268 proteins:• 1% correctly

classified on phylum level

Phylum



MEGAN LCA+

KEGG

Nitrospira defluvii

blastp

Related genomesBacteria 1268Nitrospirae 3

What about function?



MEGAN LCA+

KEGG

Nitrospira defluvii

blastp

Related genomesBacteria 1268Nitrospirae 3



Nitrospira defluvii

blastp

Related genomes

MEGAN LCA+

KEGG

Bacteria 1268Nitrospirae 3


Implication of missing genomes

Function A

Function B

Function C

Function D

Pitfalls


You always get billions of data!

Metagenomics


”If you want to understand the ecosystem

you need to understand the individual species

in the ecosystem”

Metagenomics


Lion + Eagle ≠ Flying Lion

Potentials



Who - when, where and why?

Culturing


How do we get the genomes?

Few microorganisms can be easily cultured (<<5%)Microorganisms needs to be studied in their environment



What you think you study What you actually study

Single cell genomics



CulturingFew microorganisms can be easily cultured (<<5%)Microorganisms needs to be studied in their environment

Only routinely performed in specialized labsVery incomplete genomes (mean 40%, range 10-90%)

https://www.bigelow.org/

Single cell genomics



CulturingFew microorganisms can be easily cultured (<<5%)Microorganisms needs to be studied in their environment

Only routinely performed in specialized labsVery incomplete genomes (mean 40%, range 10-90%)

Metagenomics

https://www.bigelow.org/

DNA extraction

Sequencing

Assembly Contigs

1000+ bp

100-150 bp

Reads

Metagenomics


Why not full genomes?

100++ Abundant species (≈3 Mbp each)

DNA extraction

Sequencing

Assembly Contigs

1000+ bp

100-150 bp

Reads

Metagenomics



1. Micro-diversity

2. Separation of genomes (Binning)



Not 1 strain

Many closely related strains

AAAAAAAAAAAAAA

AAAAAAAAATAAAA

AAAAAAAAACAAAA

AAAAAAAAA

TAAAA

CAAAA

What you get

AAAAA

Assembly

Extracting genomes


Low micro-diversityHigh micro-diversity

Short term enrichment

Extracting genomes

DNA extraction

Sequencing

Assembly Contigs

1000+ bp

100-150 bp

Reads

Metagenomics



1. Micro-diversity

2. Separation of genomes (Binning)



Genomic signatures:- GC / Codon usage- Tetranucleotide frequency + statistical method

Complex sample

PhD student

”Binning”

Binning


Genomic signatures:- GC / Codon usage- Tetranucleotide frequency + statistical method

Complex sample

PhD student

”Binning”

Problems:- Short pieces of sequence (1-10kbp)- Local sequence divergence

Binning

Sequence composition-independent binning

Sample 1

Abun

danc

e

Sample 2

Abun

danc

e


Binning

Sequence composition-independent binning

Sample 1 Sample 2

Abundance Sample 1

Abun

danc

e Sa

mpl

e 2

Abun

danc

e

Abun

danc

e


Binning

1. Reduce micro-diversity

2. Use multiple related samples

Abundance Sample 1

Abun

danc

e Sa

mpl

e 2


Binning

1. Reduce micro-diversity

2. Use multiple related samples

Abundance Sample 1

Abun

danc

e Sa

mpl

e 2

Abundance Sample 1

Abun

danc

e Sa

mpl

e 2


Binning

CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITYH. Daims & C. Dorninger, DOME, University of Vienna

• Nitrospira enrichment running for years

• 3 dominant species

• No micro-diversity

Binning


Full-scale EBPR plantSBR reactor

Days 1. Reduction of (micro)-diversityCENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITYAlbertsen et al., 2013 Nat. Biotech.


Full-scale EBPR plantSBR reactor

2. Two different

DNA extraction methods

CENTER FOR MICROBIAL COMMUNITIES | AALBORG UNIVERSITYAlbertsen et al., 2013 Nat. Biotech.

Colored using a set of 100 phylogenetic marker genes



TM7-1 (1.6%)

TM7-2 (0.7%)

TM7-3 (0.2%)

TM7-4 (0.06%)


Zoom on target

TM7-2 (0.7%)



Zoom on target

PC2

PC1

TM7-2

PCA on genomic signatures

TM7-2 (0.7%)




TM7-1 (1.6%)

Candidate phylum TM7

Saccharibacteria

Candidatus Saccharimonas aalborgensis



Phyla

Genes (HMM models)

Essential single copy genesAssembly inspection

Genome validation


http://madsalbertsen.github.io/multi-metagenome/Short: goo.gl/0ctA3

• Guides• Workflow scripts• Example data• All the code• Reccomendations

Multi-metagenome

http://madsalbertsen.github.io/multi-metagenome/




...add more samples!

Complex samples

S. M. Karst, AAU


It’s just a potential!

..and a poorly translated description of it.


Metabolites

Proteins

mRNA

DNA

Meta-bolomics

Meta-proteomics

Meta-transcriptomics

Meta-genomics

Data integration

In Situ methods

Community structure Microbial functions

Extraction

P-Removal:

N-Removal:

-Removal:

Foaming:

Ethanol production:

Microbial needsEcology

Understanding ecosystems


G.W. Tyson

Per H. NielsenSimon J. McIllroySøren M. KarstEB group

C. Dorringer H. Daims M. WagnerP. Hugenholtz

University of Vienna

University of Queensland

Questions? @MadsAlbertsen85

[email protected]

[2013.10.29] albertsen genomics metagenomics

Spiritual