instituto de biotecnología universidad nacional autónoma de méxico

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Instituto de BiotecnologíaUniversidad Nacional Autónoma de México

A network perspective on the evolution of metabolism by gene duplication

J. Javier Díaz-Mejía, Ernesto Pérez-Rueda & Lorenzo Segovia

NetSci 2007 NY, USA

How metabolic networks have been originated and evolve?

http://genomebiology.com/2007/8/2/R26

Gene duplication is recognized as a main source of biological variation and innovation

duplication

Malate dehydrogenase (MDH)

Enzyme Commission reactions classification1 .- Oxidoreductases 2 .- Transferases3 .- Hydrolases 4 .- Lyases5 .- Isomerases 6 .- Ligases

Lactate dehydrogenase (LDH)

EC: 1.1.1.28 EC: 1.1.1.37

NAD+ NADH NAD+ NADH


a b c dMetabolic pathway 1

“stepwise” (Horowitz, 1945)

Two pioneer models linking gene duplication and evolution of metabolism

2.3.4.5 1.2.2.1

6.3.1.1

“patchwork” (Jensen, 1976)

Metabolic pathway 2 e2.3.7.8

f4.5.6.

7

g

stepwise patchwork

distance consecutive distantly

chemistry dissimilar similar


The peptidoglycan biosynthesis, stepwise or patchwork?

UDP-N-acetylmuramoyl-L-alanyl-D-glutamate

UDP-N-acetylmuramoyl-L-alanyl-D-glutamyl-meso-2,6-diaminoheptanedioate

6.3.2.8

6.3.2.9

6.3.2.13

6.3.2.15

UDP-N-acetylmuramate

UDP-N-acetylmuramoyl-L-alanine

UDP-N-acetylmuramoyl-L-alanyl-D-glutamyl-meso-2,6-diaminoheptanedioate- D-alanyl-D-alanine

D-alanyl-D-alanine + ATP

L-alanine + ATP

D-glutamate + ATP

meso-diaminopimelate+ ATP

stepwise patchwork

distance consecutive

distantly

chemistry

dissimilar similar

The biosynthesis of peptidoglycan stepwise or patchwork?


Z-score (Zi) = (Nreali - <Nrandi>)/std(Nrandi)

Re

ac

tio

n t

yp

e 1

(E

C:a

.b.-

.-)

Reaction type 2 (EC:w.x.-.-)

The origin of several preferentially coupled reactions could be explained by both stepwise and patchwork


Question:

Whether both the distance and the chemical similarity between reactions influence the retention of duplicates?...

... forget the names of models


Methodology

E8E6

E2 a E1E1 b E4E6 c E1E1 c E6E4 d E3E7 ...

E2

E3

E1 E4

E7

Detection of duplicates comparingenzyme sequences

1880EC numbers 4500

sequences

EC:1.1.1.35

EC:1.1.1.100

EC:4.2.1.17

E2

E3

E1E4

E7E8

E6

Pair MPL

Determining theMinimal Path Length

a 1

a 2

a 4E2

E3

E4E6

E6

E8


The preferential coupling of reactions partially explains the increased retention of duplicates between closer reactions

Re

ac

tio

n t

yp

e 1

(E

C:a

.b.-

.-)

Reaction type 2 (EC:w.x.-.-)

Real NetworkNull model

(functionally similar)

Rewiring

0

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R

1 2 3 4 5 6 7 8 Alldistances

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Real networkNull models

Distance between nodes (enzymes)

ALL: all-against-all reactionsCDR: chemically dissimilar readtionsCSR: chemically ssimilar readtions


Ret

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of d

upl

icat

es

(%)

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R

1 2 3 4 5 6 7 8 Alldistances

0

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10

15

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25

30

35

40

Real networkNull models

40

30

20

10

0

Real networkNull model

(Maslov-Sneppen )

Rewiring


The increased retention of duplicates between closer reactions is reflected in lower evolutionary distances within modules

1.- Detection of functional modules

3.- Significance of (ED) values

Z-score

> 3 2 1 0

-1 -2< -3

Protein domain content random shuffling

2.- A greater retention of duplicates between pathways implies a lower evolutionary distance (ED)

1.000.670.330.00

(ED)


Summary


• In metabolic networks the closer two reactions are, the greater the probability (~2-3 folds) that their enzymes are duplicates

This can be partially explained by the preferential biochemical coupling of reactions

This is reflected (or caused) in (by) a high retention of duplicates within modules

• Retention of duplicates between chemically similar reactions is greater (~7 folds) than between chemically dissimilar ones. In both cases the observed frequencies are, however, significantly greater than expected

• These two properties are additive. Hence, the retention of duplicates catalyzing consecutive, chemically similar reactions is ~ 35 %





• These two properties are additive. Hence, the retention of duplicates catalyzing consecutive, chemically similar reactions is ~ 35 %

A.B.c.d A.B.e.f A.B.g.h





• These two properties are additive. Hence, the retention of duplicates catalyzing consecutive, chemically similar reactions is ~ 35 % ?

• In silico modeling of the origin and evolution of metabolism is improved by the inclusion of specific functional constraints, such as the preferential biochemical coupling of reactions

• We suggest that the stepwise and patchwork models are not independent of each other: in fact, the network perspective enables us to reconcile and combine these models

Conclusions


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Acknowledgments

Lic. Gerardo May (Univ. Aut. Yucatán, México)Dr. L. Segovia’s lab (UNAM, México)Dr. Sergio Encarnación (UNAM, México)Dr. A-L Barabási’s lab (Univ. Notre Dame)Dr. Virginia Walbot (Univ. of Stanford)

Sponsors

National Science and Technology Council (México)UNAM Graduate Student Office

More detailshttp://genomebiology.com/2007/8/2/[email protected]

Shen-Orr SS et al. (2002) Nat Genet

Ret

enti

on

of

du

plic

ates

(%

)This phenomenon is characteristic of enzymatic networks

Distance between proteins(transcription factor regulated gene)

AL

LE

C-E

CP

-PA

LL

EC

-EC

P-P

AL

LE

C-E

CP

-PA

LL

EC

-EC

P-P

AL

LE

C-E

CP

-PA

LL

EC

-EC

P-P

AL

LE

C-E

CP

-PA

LL

EC

-EC

P-P

AL

LE

C-E

CP

-P

1 2 3 4 5 6 7 8 All

1 2 3 4 5 6 7 8 All

6

4

2

0

Gene transcriptional regulatory network from E. coli

Ret

enti

on

of

du

plic

ates

(%

)

Distance between proteins

10

5

0

Protein-protein interactions network from E. coli

Butland G et al. (2005) Nature

ALL: all interactionsEC-EC: enzyme-enzyme interactionsP-P: non-enzymimatic interactions

• Nodes and Edges• Minimal Path Length• ModularityMexico city’s subway network

Some basic network topological properties

murEmurFmraYftsWmurDmurGmurCddlBddlA

E. coli K12

folC

The peptidoglycan biosynthesis, stepwise or patchwork?

UDP-N-acetylmuramoyl-L-alanyl-D-glutamate

UDP-N-acetylmuramoyl-L-alanyl-D-glutamyl-meso-2,6-diaminoheptanedioate

6.3.2.8

6.3.2.9

6.3.2.13

6.3.2.15

UDP-N-acetylmuramate

UDP-N-acetylmuramoyl-L-alanine

UDP-N-acetylmuramoyl-L-alanyl-D-glutamyl-meso-2,6-diaminoheptanedioate- D-alanyl-D-alanine

D-alanyl-D-alanine + ATP

L-alanine + ATP

D-glutamate + ATP

meso-diaminopimelate+ ATP

From a network perspective traditional models stepwise Vs patchwork are conceptually flawed

EC:2.4.2.14PurF

EC:2.7.6.1PrsA

ATPAMP

5-phosphoribosylamine

L-glutamate

EC:2.4.2.22Gpt

xanthosine-5-phosphate

Pi

L-glutamine

Pi

D-ribose-5-phosphate

5-phosphoribosyl 1-pyrophosphate

H2Oxanthine

salvage pathways of guanine, xanthine, and their nucleosides5-phosphoribosyl 1-pyrophosphate biosynthesis Ipurine nucleotides de novo biosynthesis I

R |CH2

|CH2

|C=O |O-

R |CH2

|CH2

|C=O |SCoA

R | CH

||HC | C=O | SCoA

R | CHOH

| CH2

| C=O | SCoA

R | C=O

| CH2

| C=O | SCoA

CoA FAD FADH H2O NAD NADH

R (n-2)

|CH2

|CH2

|C=O |SCoA

R (n+2)

|CH2

|CH2

|C=O |S[ACP]

R | CH

||HC | C=O | S[ACP]

R | CHOH

| CH2

| C=O | S[ACP]

R | C=O

| CH2

| C=O | S[ACP]

FAD FADH H2O NADP NADPH R |CH2

|CH2

|C=O |S[ACP]

R |CH2

|CH2

|C=O |SCoA

Phospholipidsbiosynthesis

ATP synthesis

DEGRADATION

BIOSYNTHESIS

1.1.1.35

1.1.1.1004.2.1.61

4.2.1.171.3.99.3

1.3.1.9

2.3.1.166.2.1.3

6.2.1.20

CoA ACP

Acetil-CoA

Retention of duplicates as groups and single entities

Fatty acids metabolism

2.3.1.41 2.3.1.41

Both groups and single duplicates are significantly retained

E1

{

{E6

I

II

III

IV

V

}

}

}

Gene duplication No gene duplication

Re

ten

tion

of

du

plic

ate

s (%

)

Eco

Cyc

Eco

Ke

gg

Me

taC

yc

Re

fKe

gg

Eco

Cyc

Eco

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Me

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Me

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gg

Eco

Cyc

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Ke

gg

Me

taC

yc

Re

fKe

gg

Eco

Cyc

Eco

Ke

gg

Me

taC

yc

Re

fKe

gg

100

80

60

40

20

0

(I) (II) (III) (IV) (V)

E4'

E5'E5

E2 E2'

E3'E3

E4'E4

Null models generation (Maslov-Sneppen)

Real network Maslov-Sneppen model

Rewiring

New null models now include the preferential biochemical coupling of reactions

Rewiring

Real network Null model

EC:1.1.1.5

EC:1.1.4.7

EC:1.1.1.5

EC:2.1.1.1

EC:2.1.4.3

EC:3.5.4.1

EC:1.1.1.5

EC:1.1.4.7

EC:1.1.1.5

EC:2.1.1.1

EC:2.1.4.3

EC:3.5.4.1

Hub influence on gene duplicationE

nzy

me

recr

uit

men

t ra

te (

%)


EcoKegg EcoCyc

MetaCycRefKegg

En

zym

e re

cru

itm

ent

rate

(%

)


En

zym

e re

cru

itm

ent

rate

(%

)


En

zym

e re

cru

itm

ent

rate

(%

)


Metabolic networks can be represented by diverse graph types

G6P NADPH

NADP+ 6PGL

H2O

GPGR5PX5P

zwf pgl

gndrpe

compound centric enzyme centric bipartite

G6P NADPH

NADP+

6PGL H2O

GPGX5P

zwf

pglgnd

rpe R5P

Barabási y Oltvai (2004) Nat Rev Genet

• Duplication inheritance

divergence

• By this way scale free

networks have been

generated, but the potential

functionality of such networks

is not assessed Pastor-Satorras et

al, (2003) J Theor Biol

In silico models have successfully simulated the grow of networks by gene duplication

Pfeiffer, Soyer y Bonhoeffer (2005) Plos Biol

• Duplication inheritance

Divergence• Multifunctional enzymes and

transporters• Potential biomass production

• Reaction coupling better fits

connectivity properties of real

networks (existence of hubs)

In silico models have successfully simulated the grow of networks by gene duplication

Becker, Price y Palsson (2006) BMC Bioinformatics

• There are biases in the coupling of

specific metabolites

• These biases follow a power law

distribution

Metabolite coupling is significant in metabolic networks

Barabási y Oltvai (2004) Nat Rev Genet

• scale free• clustering• hierarchical

Some network emerging topological properties

Papp et al (2004) Nature

Lemke et al (2004) Bioinformatics

Essentiality and damage in metabolic networks

Clustering (C) =

Watts y Strogatz (1998) Nature

• Short distance between nodes• High clustering coefficient

The small world into large networks

random

small-world

2ni

ki(ki - 1)ni : direct edges between i neighborski : number of i neighbors

C

C = = 1

C = = 0.05

205(4)

15(4)

The analysis of biological systems from a network perspective have had a great increase in last years

Scale free Modularity

Jeong et al (2000) Nature

Ravasz et al (2002) Science

Some topological properties of metabolic networks

• small world• universality• scale free• hub elimination• modularity

+ -

- +

+ +

e

a b

c d

instituto de biotecnología universidad nacional autónoma de méxico

Documents

similar reactions

high retention of duplicates

modulesretention of

acetylm dalanyl

closer reactionshttp

stepwise horowitz

usahow metabolic networks

observed frequencies