ivan erill: "beyond the regulon: reconstructing the sos response of the human gut...

CAATCCGAGGCATGGCATGGTCGTTAGATTGCTGATTTTGAATGATCGATCGATCGATGGGC010101001001000101010001TGCCATCGATAGCTTGAGACTCGAAGGGAGATAGATGACGACAGCTATTCGAGCATC01011010100100100010100101011CGACCTAGCTTGAGATCGAGCGAAGATAGATGACGACAGCTATTCGAGCATC0101101010100100110010100101011001AGCCTCTGAGATCGAGGGAGATAAGATGACGACAGCTATTCGAGCATC01011010101001000101001010010110011110ATCCGACTTCGATGCATCGATACAGTTGCTCTCTTCTCAGAGAGAG0101010100101010001000111111101001001010ATTCGAATGCATCGATCAGTTGCTCTCTTCTCAGAGAGAG0101010100101010001000111111001001010101011010GATGCCATCGATCAGTTGCTCTCTTCTCAGAGAGAG01010101001010100010001111110010010101010000101001ATGCCATAAGCATGCATGGCCCCTTCGCTCGCTAAG10101010001010101000001011100010100010100101010111ATGCCATGCATGGCCCCTTCGCTCGCTAAG10101010001010101000001011100010100010101010111101010110ATGCCAATGGCCCCTTCGCTCGCTAAG10101010001010101000001011100010100010101010111101001011001TATACTCACGGCTACGTTGCATGCAT010100010100010010010010010001111111100101010010101000100000TACGCGCCTACGTTGCATGCAT0101000101000100100100100100011111111001010100101010001010101110GCTACCCGTTGCATGCAT01010001010001001001001001000111111110010101001010100010101011011011GGCTCGCATCCACATG0101010101010101010101001010101010000101001010010101010100001000011010

BIOLOGICAL SCIENCES

Beyond the regulon reconstructing the SOS response of the human gut microbiome

Ivan Erill

ACACGGATCGATCGAGGCATGGCATGGTCGTTGATTGCTGATTTTGAATGATCGATCGATCGATGGGC010101001100100001ACCATCGATTCGATGCATCGATCAGTTGCTCTCTTCTCAGAGAGAG0101010100101010001000111111010101111010CGGATGCATGCATGCATGGCCCCTTCGCTCGCTAAG10101010001010101000001011100010100010101101001110GGCTGATCCACATG010101010101010101010100101010101000010100101001010101010000100010011011

ACAACGCCTERILLGTATAGCAGTGTGTCATTGCTTTAGCTAGTACACAGACACGCBIOLOGICALATUMBC0101010101110001010100010LAB010010101001000011110001010001010001001011100SCIENCESCCAGGACATGAGCTAAAAC

2

The researchsome

Comparative genomics

Molecular microbiology

Computational biology

Bioinformatics

Transcription factors

Stress responses

Microbial metagenomics

Codon usage indices

Machine learning

Evolutionary simulations

Motif search & discovery

High-throughput assays

Clinical microbiology

Molecular phylogeny

00000



3

The researchsome

Comparative genomics

Molecular microbiology

Computational biology

Bioinformatics

Transcription factors

Stress responses

Microbial metagenomics

Codon usage indices

Machine learning

Evolutionary simulations

Motif search & discovery

High-throughput assays

Clinical microbiology

Molecular phylogeny

00001



4

On regulons

RegulonsSets of genes/operons (transcriptionally)

regulated by a particular transcription factor (TF)

Cellular response to specific internal or external stimuli

Defined by specific binding of TF to promoter region of regulated genes Regulon genes can be repressed or activated TF recognizes a specific binding motif

.

Guzmán-Vargas and Santillán BMC Systems Biology 2:13 (2008)

ATGTCGATCAGCTAGCC...

RNA-polymerase

Transcription Factor (TF)

Open reading frame

00000

Schematic bacterial promoter

TFi

TG1 TG2

TG3

TG4

S

TFx

Gx

TFyTFi

TG1 TG2

TG3

TG4

S

TFx

Gx

TFy

Regulon

CTGTAAAG CTGCACAG CTGATCAG

TF-binding motif



5

On metagenomesMetagenome

Multi-species, heterogeneous collection of high-throughput reads from a natural habitat

The good“Unculturable” speciesDiversity samplingNatural population sampling

The badLow coverageHigh-levels of polymorphismDiversity of low complexity regionsContamination with eukaryotic DNA

The uglyLack of proper models for

Pre-filtering Assembly Gene calling Analysis?.

00000

High-throughput sequencing

Gest, H. Microbiology Today 35: 220 (2008)P. D. Schloss and J. Handelsman, Genome Biol. 6:229, (2005)



6

On metagenomesMetagenome

Multi-species, heterogeneous collection of high-throughput reads from natural habitat

PropertiesLots of data!Noisy! Increasingly cheap and abundant!

Post-processing typical formatAssembled contigs/scaffolds with predicted,

functionally annotated genes

Problem How do we extract useful information from

metagenome data?(i.e. how do we evade Brenner’s “low input, high-throughput, no output” epithet?)

.

.

00001

Assembly, gene calling & functional annotation


Friedberg, E. C. Nat Rev Mol Cell Biol 9, 8-9 (2008)



7

Analysis of metagenomic dataThe metagenome & regulatory networks

The metagenomeMulti-species, heterogeneous collection of high-

throughput reads from natural habitat

Problem How do we extract useful information from metagenome

data?.

Conventional workflow (e.g. metabolic networks) Knowledge from references is used as terminal Data is mapped onto existing, static knowledgebase Inference on mapped data

.

00000



Pathway mapping, clustering and enrichmentx

yz

s w

a

m

n

Phylogeny

Pathway

Map to reference Low discovery potential



8




Problem How do we extract useful information from metagenome

data?.

Conventional workflow (e.g. metabolic networks) Knowledge from references is used as terminal Data is mapped onto existing, static knowledgebase Inference on mapped data Interesting repertoire of new questions

.

00001



Pathway mapping, clustering and enrichmentx

yz

s w

a

m

n

Phylogeny

Pathway

Map to reference Low discovery potentialMuegge, B. D. et al. Science, 332 (6032), 970-974 (2011)



9




Problem How do we extract useful information on regulatory

networks from metagenome data?.

Alternative workflow Knowledge from reference used as seed Directed mining of metagenome data Inference on mined data

.

00010



Regulon analysis, clustering and enrichment

x

nw

sm

x

nw

sm

x

n

wsm

z

x

n

wsm

z

Seed reference High discovery potential



10




Problem How do we extract useful information on regulatory

networks from metagenome data?.

Alternative workflow (e.g. regulatory networks) Knowledge from reference as seed Directed mining of metagenome data Inference on mined data Promising questions and challenges

.

00011



Regulon analysis, clustering and enrichment

x

nw

sm

x

nw

sm

x

n

wsm

z

x

n

wsm

z

Is network composition governed by convergent evolution or by phylogeny?Can we effectively infer regulatory networks from metagenomics data?Seed reference High discovery potential



11

Analysis of metagenomic dataMetagenomics and regulatory network analysis

AdvantagesReal bacterial populationsUnculturable organisms and mobile elementsVariability at species and subspecies levels

ChallengesNoisy search process, huge datasetHow to: data integration, enrichment and analysis

GoalsProof of concept

Analyze the potential of meta-genomic & regulatory sequence data to explore known regulatory systems

Study a regulatory network in its natural setting

.

00100



12

Analysis of metagenomic data

Metagenomics and regulatory network analysisRequires

A regulatory network to analyzeThe bacterial SOS response

A metagenome on which to analyze itThe human gut microbiome

.

00101



13

The bacterial SOS responseTranscriptional response against DNA damage

.

00000

“Canonical” stress responseWidespread in bacteria

Well-characterized in most bacterial phylaE. coli, B. subtilis, M. tuberculosis, V. parahaemolyticus, S. meliloti, B. bacteriovorus, X. campestris, G. sulfurreducens…

Two-component system RecA (sensor) LexA (repressor)

response to DNA damaging agents

Well-characterized regulon Target genes

~40 in E. coli / ~30 B. subtilis

Functions Recombination & DNA repair Cell-division inhibition Translesion synthesis

. Erill, I. et al. FEMS Microbiol. Rev. 31 (6), 637 (2007)



14


.

00001

Erill, I. et al. FEMS Microbiol. Rev. 31 (6), 637 (2007)

High clinical relevanceWidespread in bacteria

Two-component system RecA (sensor) LexA (repressor) Response to

Broad range of antibiotics Bacteriophage infection

Extended regulon Functions

Integron recombination Bacteriophage induction Toxin production Dissemination of pathogenicity islands Antibiotic-induced mutagenesis Regulation of persistence

. Guerin, E. et al., Science, 324 (5930), 1034 (2009)



15


.

00010

Erill, I. et al. FEMS Microbiol. Rev. 31 (6), 637 (2007)

Interesting evolutionWidespread in bacteria

Absent in some clades (Bacteroidetes/Chlorobi group) Supplanted by competence regulon (S. pneumoniae)

Extreme diversity of LexA-binding motifs Clade-specific & monophyletic

.Geobacteres

Gram-positive

Myxobacteriales

Xanthomonadales

Alpha Proteobacteria

Beta/Gamma Proteobacteria

Cyanobacteria

Fibrobacteres



16

The human gut microbiome

Metagenomics projectTarget metagenome

Human microbiomeMultiple datasets (locations: gut, armpit, etc.)Multiple initiatives (HMP & MetaHit)Available data & features:

High-throughput sequencing + 16S RNA data ORF predictions & functional annotation

.

00000

Qin, J. et al. Nature. 464, 59 (2010)Nelson, K.E, et al. Science. 328, 994 (2010)

Segata, N. et al. Gen. Biol. 13, R42 (2012)

MetaHit human gut microbiome

GammaproteobacteriaActinobacteria

Other

Bacteroides

Firmicutes

GammaproteobacteriaActinobacteria

Other

Bacteroides

Firmicutes

86 healthy subjectsLarge contigs, high-quality gene calling7.1 Gbp total sequence – 4.5 M contigs (N50: 2.2 kbp)9.3 M predicted ORF (3.7M complete), λ=660 bp 1 M COG annotations



17

Analysis workflowWorkflow

Data compilation LexA-binding motif compilation

Gram-positive bacteria CollecTF database 118 sites, 8 species

Reference genome panel 121 genomes from MetaHit and the Human

Microbiome Jumpstart Reference Strains Consortium

Reference SOS response 18 described SOS responses

Acidobacteria Alphaproteobacteria Gammaproteobacteria Deltaproteobacteria Bacilli Clostridia Actinobacteria Fibrobacteria

272 regulated genes

.

00001

collectf.umbc.edu

Kiliç, S. et al. Nuc. Acids Res. 42, D156-D160 (2013)Nelson, K.E, et al. Science. 328, 994 (2010)

Cornish, J. P. et al. Evol Bioinform. 8: 449–461 (2012)Erill, I. et al. FEMS Microbiol. Rev. 31 (6), 637 (2007)

Gram-positive reference motif



18


Data compilation LexA-binding motif compilation Reference genome panel Reference SOS response

Metagenome mining PSSM-based search

Reference motif, 2 strands

Operon prediction Site-operon association

Distance-based

Taxonomic annotation Through reference panel mapping

for phylogenetic filtering of results

Functional clustering Through COG mapping

for functional analysis

.

00010

GAACTACTGTTC

GAACTACTGTTC

GTACAACTGTTCGATCTATTGTTC

GAACTCATGTTT

GTTCAAAAGATC

GAACTCCTGTCC

PSSM-based search

LexA-binding motif score histogram

0

0.05

0.1

0.15

0.2

0.25

0.3

1 5 9 13 17 21 25 29

Score

Fre

qu

ency



19






Distance-based





.

00011

GAACTACTGTTC


GAACTCATGTTT

GTTCAAAAGATC

GAACTACTGTTC GAACTACTGTTC

GAACTCATGTTT

GAACTACTGTTCGAACTCCTGTCC

Operon prediction



20






Distance-based





.

00100

GAACTACTGTTC


GAACTCATGTTT

GTTCAAAAGATC

GAACTACTGTTC GAACTACTGTTC

GAACTCATGTTT

GAACTACTGTTCGAACTCCTGTCC

Site-operon association



21






Distance-based





.

00101

GAACTCATGTTT

GAACTACTGTTC

GAACTCATGTTT

GAACTACTGTTC

Refe

renc

e ge

nom

e lib

rary

Taxonomic annotation



22






Distance-based





.

00110

GAACTCATGTTT

GAACTACTGTTC

GAACTCATGTTT

GAACTACTGTTC

COG

refe

renc

e lib

rary

Functional clustering

COG123

COG345

COG567

COG789



23

The human gut microbiomeWorkflow

Data compilation Motif compilation Reference genome panel Reference SOS response

Metagenome mining PSSM-search Operon prediction Site-operon association Phylogeny annotation Functional clustering

Analysis Positional enrichment analysis Data filtering COG enrichment analysis Gene-based functional analysis

.

00111

GAACTCATGTTT

GAACTACTGTTC

GAACTCATGTTT

GAACTACTGTTC

Data for analysis



24

The human gut SOS response

Initial search resultsOver 500,000 putative LexA-binding sites identified

Positional enrichment analysisPromoter regions

Site scores are significantly enriched in promoter regionsHigh-scoring sites co-localize in promoter regions

.

00000

Permutation analysis of site scores



25

The human gut SOS response

Data filteringTwo-pronged approach

Distance-basedOnly sites located between -350 and +50 of predicted TLS

Taxomomy-basedOnly sites associated with predicted protein-coding genes mapping to Gram-

positive reference genomes

Filtering resultsDramatic reduction in the number of putative sites

Over 43,000 sites meeting both criteriaTaxonomy-based filtering provides enhanced resolution

Law of large numbers: high-scoring sites can be identified in the promoter region of many Bacteroides genes

.

00001



26

The human gut SOS responseCOG category analysis

Inferred regulon maps experimentally characterized SOS responsesGradual enrichment of canonical SOS categories with score cutoff:

repair/replication (L), signal transduction (T) and transcription (K) genes

Cell cycle control (D) category not enriched COGs are getting old!

.

00010

0

0.1

0.2

0.3

0.4

0.5

J K L D V T M C G F R SCOG category

Rela

tive

freq

uenc

y MetaHit COG referenceCOGs with SOS siteCOGs with site >12 bitsCOGs with site >14 bitsCOGs with site >16 bitsSOS ensemble reference



27

The human gut SOS responseCOG analysis

QuestionHow to identify “SOS COGs”?

Score enrichment measureGoal

Identify bona-fide members of the regulon Capture maximum number of known SOS genes

Analysis of canonical SOS genes in 308 Gram-positive genomesLexA-binding site scores normally distributed

(lexA: =16.2 bits, =2.3; recA: =16.3 bits, =2.5)Cumulative distribution approximately linear

in central scoring range 12-20 bitsPrototypical SOS COG

High linear coefficient of determination (R2>0.85, empirically set)

At least: one site above average score (16 bits) 10 sites in 12-20 bit range

.

00011

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

9 11 13 15 17 19 21 23Site score (bits)

Cu

mu

lati

ve d

istr

ibu

tio

n

lexA (Firmicutes)recA (Firmicutes)

Quantile-quantile plot

911131517192123

9 11 13 15 17 19 21 23Theoretical

Em

pir

ica

l

lexA (Firmicutes)recA (Firmicutes)

Canonical SOS genes



28

The human gut SOS responseCOG analysis

ResultsDetection of canonical SOS regulon

lexA, recA, excision repair, recombinationSOS meta-regulon composition

Four major functions Transcriptional repression (lexA) Translesion synthesis (dinB, uvrX, imuB, umuD) Sensing of DNA-damage & stabilization (recA) Excision repair (uvrA, uvrB, uvrD, pcrA)

Translesion synthesis as primary SOS component Interesting new putative SOS regulon COGs

COG0732 HsdS – restriction endonuclease

COG2001 MraZ – cell wall biogenesis

COG4974 CodV – chromosome partitioning

.

00100

0.86recNCOG0497

0.87ruvACOG0632

0.87codVCOG4974

0.88parECOG0187

0.91uvrACOG0178

0.91hsdSCOG0732

0.91MraZCOG2001

0.92uvrD, pcrACOG0210

0.96lexA,umuDCOG1974

0.97uvrBCOG0556

0.98recA,imuACOG0468

0.98dinB, imuB, uvrXCOG0389

r2Associated genesCOG

0.86recNCOG0497

0.87ruvACOG0632

0.87codVCOG4974

0.88parECOG0187

0.91uvrACOG0178

0.91hsdSCOG0732

0.91MraZCOG2001

0.92uvrD, pcrACOG0210

0.96lexA,umuDCOG1974

0.97uvrBCOG0556

0.98recA,imuACOG0468

0.98dinB, imuB, uvrXCOG0389

r2Associated genesCOG

0

0.2

0.4

0.6

0.8

1

Nor

mal

ized

num

ber o

f site

s CO

G19

74 -

lexA

, um

uD

CO

G03

89 -

dinB

, uv

rX, i

muB

CO

G04

68 -

recA

, im

uA

CO

G50

56 -

uvrB

CO

G02

10 -

uvrD

, pc

rA

CO

G01

78 -

uvrA

CO

G20

01 -

mra

Z

CO

G04

97 -

recN

CO

G01

87 -

parE

CO

G07

32 -

hsdS

CO

G49

74 -

codV

CO

G06

32 -

ruvA



29

The human gut SOS responseTargeted gene analysis

Assessment of non-canonical functions in genes with high-scoring sitesToxin-antitoxin / virulence systems (higB / rhuM)

Linked to persistence phenotypesPhage integrases (intP)

In line with integron integrase regulation and phage control by SOS response

Validation of enriched COGsCell wall biogenesis (mraZ)

Possible role in cell division control Evidence of convergent regulation

YneA (B. subtilis), DivS (C. glutamicum)

Experimental validationEMSA with purified B. subtilis protein

.

00101

recA- + - + - + - +

mraZ intPrhuM



30

Beyond the regulon

Proof of concept: the human gut SOS meta-regulonMethodology

Provides the means to expand our knowledge on described regulatory systemsCOG enrichment as a method for functional assessment of the meta-regulonAnalysis allows visualizing a regulatory response in a wild-population

Inference of novel knowledge on regulon function and componentsConsistent with known SOS responses; primary focus on mutagenesisContains several elements linking it to other cellular processes of clinical relevance

Future directionsAnalyze and compare regulatory networks in metagenomes

Is network evolution dictated by phylogeny or habitat?How do changes in habitat affect meta-regulons?How does the overlap between meta-regulons vary among populations?

00000



31

Beyond the regulon

Automating meta-regulon inferenceA transcription factor

Exists in a subset of speciesBinding sites for the TF are enriched in a subset of functional clusters

How can we automatically determine the set of species & COGs?

00001

0

0.05

0.1

0.15

0.2

0.25

0.3

5 10 15 20 25 30

Aver

age

scor

e co

unt i

n ge

ne u

pstr

eam

regi

ons

Score (bits)

LexA-binding site score distribution

Firmicutes (SOS COGs)Firmicutes (random COGs)All taxa, all COGs

0

2

4

6

8

10

12

14

16

18

-60 -40 -20 0 20 40

Aver

age

scor

e co

unt i

n ge

ne u

pstr

eam

regi

ons

Score (bits)

LexA-binding site score distribution

Firmicutes (SOS COGs)Firmicutes (random COGs)All taxa, all COGs



32

Beyond the regulon

EM algorithm for isolation of enriched COGs/taxaDefine likelihood function

Statistical test for mixture model in observed distribution

Assign weights to COGs (Ci) and taxa (Tj)For given COG weights, compute likelihood of each taxon, update weight with likelihood

For given taxon weights, compute likelihood of each COG, update weight with likelihood

00010

C60.1

C50.8

C40.7

C30.3

C20.2

C10.3

T6T5T4T3T2T1

0.50.40.20.90.60.5

C60.1

C50.8

C40.7

C30.3

C20.2

C10.3

T6T5T4T3T2T1

0.50.40.20.90.60.5

C60.1

C50.8

C40.7

C30.3

C20.2

C10.3

T6T5T4T3T2T1

0.50.40.20.80.60.5

C60.1

C50.8

C40.7

C30.3

C20.2

C10.3

T6T5T4T3T2T1

0.50.40.20.80.60.5



33

Conclusions & AcknowledgementsAcknowledgements

Erill Lab Joe CornishNeus Sanchez-AlberolaPat O’Neill Jameel GhebaRon O’KeefeTalmo PereiraDavid Nicholson

Wolf LabRichard WolfLanyn Perez

Barbé LabSusana Campoy Jordi Barbé

Funding UMBC Office of Research – Special Research Assistantship/Initiative Support NSF grant MCB-1158056

.

CAATCCGAGGCATGGCATGGTCGTTAGATTGCTGATTTTGAATGATCGATCGATCGATGGGC010101001001000101010001TGCCATCGATAGCTTGAGACTCGAAGGGAGATAGATGACGACAGCTATTCGAGCATC01011010100100100010100101011CGACCTAGCTTGAGATCGAGCGAAGATAGATGACGACAGCTATTCGAGCATC0101101010100100110010100101011001AGCCTCTGAGATCGAGGGAGATAAGATGACGACAGCTATTCGAGCATC01011010101001000101001010010110011110ATCCGACTTCGATGCATCGATACAGTTGCTCTCTTCTCAGAGAGAG0101010100101010001000111111101001001010ATTCGAATGCATCGATCAGTTGCTCTCTTCTCAGAGAGAG0101010100101010001000111111001001010101011010GATGCCATCGATCAGTTGCTCTCTTCTCAGAGAGAG01010101001010100010001111110010010101010000101001ATGCCATAAGCATGCATGGCCCCTTCGCTCGCTAAG10101010001010101000001011100010100010100101010111ATGCCATGCATGGCCCCTTCGCTCGCTAAG10101010001010101000001011100010100010101010111101010110ATGCCAATGGCCCCTTCGCTCGCTAAG10101010001010101000001011100010100010101010111101001011001TATACTCACGGCTACGTTGCATGCAT010100010100010010010010010001111111100101010010101000100000TACGCGCCTACGTTGCATGCAT0101000101000100100100100100011111111001010100101010001010101110GCTACCCGTTGCATGCAT01010001010001001001001001000111111110010101001010100010101011011011GGCTCGCATCCACATG0101010101010101010101001010101010000101001010010101010100001000011010

BIOLOGICAL SCIENCES

Beyond the regulon reconstructing the SOS response of the human gut microbiome

Ivan Erill

ivan erill: "beyond the regulon: reconstructing the sos response of the human gut...

Health & Medicine

specific binding of

specific binding motif

highthroughput sequenc

activated tf

bad low coverage highlevels

regulons regulons

natural habitat

santilln bmc systems