Transcription Networks Ildefonso Cases (CNB-CSIC).
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Transcription Networks
Ildefonso Cases (CNB-CSIC)
SummarySummary
Concepts in TranscriptionConcepts in Transcription
Transcription NetworksTranscription Networks Definition, properties and evolutionDefinition, properties and evolution
Transcription Networks vs Functional NetworksTranscription Networks vs Functional Networks
Evolution of Regulatory StructuresEvolution of Regulatory Structures
Transcription and AdaptationTranscription and Adaptation
Regulación de la TranscripciónRegulación de la Transcripción
• Resultado de la interacción entre proteínas y Resultado de la interacción entre proteínas y DNA. DNA.
• El conjunto de proteínas que se unan a su región El conjunto de proteínas que se unan a su región promotora (directa o indirectamente) va a promotora (directa o indirectamente) va a determinar la expresión de un gen:determinar la expresión de un gen:
En que tejidos En que tejidos
En que momento del desarrolloEn que momento del desarrollo
Bajo que condiciones ambientalesBajo que condiciones ambientales
etc.etc.
Transcripción en BacteriasTranscripción en Bacterias
Transcripción en Bacterias: Transcripción en Bacterias: Factores SigmaFactores Sigma
Escherichia coliEscherichia coli
sigma70/Dsigma70/D
sigma32/H: heat shocksigma32/H: heat shock
sigma24/E: ECFsigma24/E: ECF
sigma28: flagelosigma28: flagelo
sigma38/S:fase estacionaria,stresssigma38/S:fase estacionaria,stress
sigma54/N: nitrógeno y otrossigma54/N: nitrógeno y otros
fecI: hierrofecI: hierro
Pseudomonas putida: > 15Pseudomonas putida: > 15
Streptomyces: > 30Streptomyces: > 30
Transcripción en BacteriasTranscripción en Bacterias
Transcripción en Bacterias: Transcripción en Bacterias: OperonesOperones
Transcripción en EukariotasTranscripción en Eukariotas
Transcripción en EukariotasTranscripción en Eukariotas
Transcripción en ArcheasTranscripción en Archeas
•Maquinaria basal EukariotaMaquinaria basal Eukariota
•Reguladores eukariotas y bacterianosReguladores eukariotas y bacterianos
Otras fuentes de RegulaciónOtras fuentes de Regulación
ElongaciónElongación
Estabilidad del mRNAEstabilidad del mRNA
etc.etc.
Transcription NetworksTranscription Networks
Transcription Networks
0,01
0,1
1
1 10 100 1000
0,01
0,1
1
1 10 100 1000
Regulators regulates:
genes
p(k)=akp(k)=ak-b-b
Scale-free Scale-free NetworksNetworks
Resistant to ErrorResistant to Error
Sensitive to Sensitive to AttackAttack
Network Properties
QuickTime™ and aTIFF (LZW) decompressor
are needed to see this picture.YeastYeast
Guelzim et al. 2002 Nature Genet. 31:60-63
Preferential AttachmentPreferential Attachment
1
2
3
Network evolutionNetwork evolution
Duplicated Duplicated Genes are often Genes are often co-expressedco-expressed
and share and share regulator binding regulator binding sitessites
van Noort et al., 2004 EMBO Rep 5(3):280-4
Binding sites EvolutionBinding sites Evolution
Papp et al,2003. Trends Genet 19:417
Milo et al,2002. Science 298:824
MotivesMotives
MotivesMotives
Milo et al,2002. Science 298:824
Motives ProfilingMotives Profiling
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are needed to see this picture.
Milo et al. 2004 Science 303:1538-1542
Overlapping MotivesOverlapping Motives
Bi-fan y FFL often share nodes and Bi-fan y FFL often share nodes and edgesedges
Dobrin et al,2004. BMC Bioiformatics 5:10
Motives EvolutionMotives Evolution
Conant & Wagner,2003. Nat Genet. 34:264
Motives PropertiesMotives Properties
Shen-Orr et al.,2002. Nat Genet. 31:64
Coregulation Network Coregulation Network
gamma≈-1gamma≈-1
c=0.6c=0.6
scale-freescale-free
small worldsmall world
van Noort et al., 2004 EMBO Rep 5(3):280-4
Network Evolution SimulationNetwork Evolution Simulation
van Noort et al., 2004 EMBO Rep 5(3):280-4
In the absence In the absence of selection of selection we can we can reproduce a reproduce a network with network with similar similar propertiesproperties
van Noort et al., 2004 EMBO Rep 5(3):280-4
Network Evolution SimulationNetwork Evolution Simulation
Trancription Networks DynamicsTrancription Networks Dynamics
Luscombe et al., 2004 Nature 431:308
Trancription Networks DynamicsTrancription Networks Dynamics
Luscombe et al., 2004 Nature 431:308
Luscombe et al., 2004 Nature 431:308
Trancription Networks DynamicsTrancription Networks Dynamics
Endogenous Exogenous
Combining NetworksCombining Networks
Regulatory Networks vs.Regulatory Networks vs.
Functional NetworksFunctional Networks
Functional AssociationsFunctional Associations
• Protein ComplexesProtein Complexes• Enzymes …. RibosomesEnzymes …. Ribosomes
• Information/Biochemical PathwaysInformation/Biochemical Pathways• Metabolic ProgramsMetabolic Programs
• Anaerobic… Aerobic MetabolismAnaerobic… Aerobic Metabolism
• Biological ProcessesBiological Processes• Transcription … RecombinationTranscription … Recombination
Relation between functional Relation between functional associations and co-regulation?associations and co-regulation?
““co-regulated genes are co-regulated genes are functionally associated”functionally associated”
PrecedentsPrecedents
• Pairs of interacting proteins are more frequent Pairs of interacting proteins are more frequent
among co-expressed genes in among co-expressed genes in S. cerevisiaeS. cerevisiae
• 50% of the pairs of co-expressed genes belong 50% of the pairs of co-expressed genes belong
to the same biochemical pathway in to the same biochemical pathway in S. S.
cerevisiaecerevisiae and more than 30% in and more than 30% in C. elegansC. elegans
• In In E. coliE. coli and and B. subtilisB. subtilis genes in operons (and genes in operons (and
thus presumably co-expressed) tend to belong thus presumably co-expressed) tend to belong
to the same general class of cellular functionto the same general class of cellular function
EcocycEcocyc
• Protein Complexes and sub-complexesProtein Complexes and sub-complexes• Biochemical Pathways Biochemical Pathways
• Pathways and Super-pathwaysPathways and Super-pathways
• Regulatory informationRegulatory information• Transcription Units Transcription Units • Regulatory ProteinsRegulatory Proteins
• Regulons: Genes directly regulated by the same protein in Regulons: Genes directly regulated by the same protein in the same waythe same way
• Super-regulons: also include indirect interactionsSuper-regulons: also include indirect interactions
Correlated?Correlated?
• Functional Functional AssociationsAssociations
• ComplexesComplexes• PathwaysPathways• SuperpathwaysSuperpathways
• Regulatory Regulatory AssociationsAssociations
• Transcription UnitsTranscription Units• RegulonsRegulons• Supe-regulonsSupe-regulons
Coding functional associationsCoding functional associations
A
B
CA
B
C
A B
E
G
F
CA
B
C
E F
G
A B C D
A 0 1 1 0
B 1 0 1 0
C 1 1 0 0
D 0 0 0 0
Coding Regulatory associationsCoding Regulatory associations
C
DBA
A B C
D
A B A
B
C
A
C D
B
A B
C D
A B C D
A 0 1 0 0
B 1 0 1 0
C 0 1 0 0
D 0 0 0 0C
A C D E
A 0 1 0 1
C 1 0 1 0
D 0 1 0 1
E 1 0 1 0
A B C D
A 0 0 1 1
B 0 0 1 0
C 1 1 0 1
D 1 0 1 0
A C D
A 0 1 0
C 1 0 1
D 0 1 0
A C D
A 0 1 1
C 1 0 1
D 1 1 0
A C D
A 0 1 0
C 1 0 1
D 0 1 0
OriginalOriginalMatricesMatrices
ReducedReducedMatricesMatrices
Ia=2
Ib=3
Iab/Ia=2/2=100%
Iab/Ib=2/3=66%
GeneGene NetworkNetwork
Functional Functional Assoc.Assoc.
Ice = Ia*Ib/(N*(N-1)/2)
Complexes vs. Transcription UnitsComplexes vs. Transcription Units282 genes, 87% and 85%, 80 times more than expected
ExceptionsExceptions
MtlAMtlA
GatAGatA
GatBGatB
GatCGatC
PtsHPtsH
PtsIPtsI
ExceptionsExceptions
Evolutionary Implications?
Pathways vs. Transcription UnitsPathways vs. Transcription Units330 genes, 94% and 26%, 35 times more than expected
Transcription Units per PathwayTranscription Units per Pathway
0
0,05
0,1
0,15
0,2
0,25
0,3
0,35
0,4
0,45
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27
A B
E
G
F
C
A
B
C
E F
G
A
B
C
E F
G
66%66%
26%26%
Complexes vs. RegulonsComplexes vs. Regulons209 genes, 10% and 97%, 7 times more than expected
Pathways vs. RegulonPathways vs. Regulon258 genes, 18% and 77%, 4 times more than expected
16%3.1
15%3.5
7%4.7
SR
20%3.8
18%4.2
10%6.9
RE
94%28.0
94%35.4
87%79.2
TU
SPPC
78%86%97%SR
71%77%97%RE
20%26%85%TU
SPPC
0
20
40
60
80
100
Functional associatio
n
Gene N
etw
ork
DBA
A B C
DC
15%2.8
13%3.2
6%4.1
GRGR
20%3.8
18%4.2
10%6.9
RERE
80%87%97%GRGR
71%77%97%RERE
SPSPPPCC SPSPPPCC
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
NO 0 705 460 1165
Super-path. 0 20 9 29
Pathway 24 422 58 504
COMPLEX 164 7 0 171
TU Regulon Super-regulon ALL
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
NO 3 40 12 55
Super-reg. 0 67 0 67
Regulon 7 422 20 449
TU 164 24 0 188
Complex PathwaySuper-
pathway ALL
ConclusionsConclusions
• Subunits of protein complexes are often in the Subunits of protein complexes are often in the same transcription unitsame transcription unit
• Pathways are spread in several transcription Pathways are spread in several transcription units, which contains linear sub-pathways and units, which contains linear sub-pathways and are often co-regulatedare often co-regulated
• Expression of pathway branches is often Expression of pathway branches is often coordinatedcoordinated
• The tighter the functional association The tighter the functional association the tighter the mechanism of co-the tighter the mechanism of co-regulationregulation
Evolution of regulonsEvolution of regulons
Regulatory Structures has functional senseRegulatory Structures has functional sense
How regulons are assemble during evolution?How regulons are assemble during evolution?
Genome AGenome B Genome C Genome D Genome F Genome G Genome H
Sigma54Sigma54
Sigma54 regulon: Sigma54 regulon: ““relatively easy” to predict relatively easy” to predict
well distributed in the bacterial treewell distributed in the bacterial tree
good number : 10-100 per genomegood number : 10-100 per genome
Distribution of sigma54Distribution of sigma54
Aquifex aeolicus D. radiodurans T. maritima
E. coliS. typhiY. pestisV. choleraeP. aeurginosaBuchnera sp.H. influenzaeP. multocida
N. meningiditisR. solanacearum
H. pyloriC. jejuni
S. melilotiM. lotiA. tumafaciensB. melitensisC. crescentus
R. prowazekiiR. conorii
T. pallidumB. burgdorferiC. trachomatis
Actinobacteria
B. subtilisL. inocua
S. aureusS. pyogenesM. neumoniae
conserved sigma54-regulationconserved sigma54-regulation
COG0174 Glutamine synthase
COG0347 Nitrogen regulatory protein PII
COG0642 Signal transduction histidine kinase
COG0683 ABC-type branched-chain amino acid transport systems,
periplasmic component
COG0834 ABC-type amino acid transport system,
periplasmic component
COG1301 Na+/H+-dicarboxylate symporters
COG1815 Flagellar basal body protein
COG2513 PEP phosphonomutase and related enzymes
COG4992 Ornithine/acetylornithine aminotransferase
phylogenetic profilesphylogenetic profiles
GlnAGlnA
GlnKGlnK
His-KiHis-Ki
LivKLivK
HisJHisJ
GltPGltP
FlgBFlgB
PrpBPrpB
ArgDArgD
alp
ha b
et
a gam
ma gra
m
+
aquifex
delt
a-
epsi
lon
Evolution Sigma54 regulonEvolution Sigma54 regulon
Sigma54 regulon is very dynamicSigma54 regulon is very dynamic
Expression of genes transcribed from sigma54 Expression of genes transcribed from sigma54 promoters is couple to physiological conditionspromoters is couple to physiological conditions
Are Genes required to be coupled to Are Genes required to be coupled to physiological conditions different in different physiological conditions different in different bacterial species?bacterial species?
How regulation reflects life-style?How regulation reflects life-style?
Bacteria LifestylesBacteria Lifestyles
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• Enrichment in Transcriptional Regulators of the Enrichment in Transcriptional Regulators of the
Pseudomonas aeruginosa Pseudomonas aeruginosa Genome Genome
Cellular Processes and Bacterial Cellular Processes and Bacterial LifestyleLifestyle
• Transport, Metabolism and TranscriptionTransport, Metabolism and Transcription
• Three sets of proteins from Three sets of proteins from E. coliE. coli
• 396 Transcription-associated proteins as annotated in Swissprot396 Transcription-associated proteins as annotated in Swissprot
• 548 Small-molecules Metabolism Enzymes from EcoCyc548 Small-molecules Metabolism Enzymes from EcoCyc
• 647 Transporters from EcoCyc647 Transporters from EcoCyc
• Blast against all available sequenced genomes classified by lifestyleBlast against all available sequenced genomes classified by lifestyle
60 genomes60 genomes15 0bligate intracellular pathogens and endosymbionts:Buchnera sp., APS, Chlamydia pneumoniae, AR39, Chlamydia pneumoniae, CWL029, Chlamydia pneumoniae, J138, Chlamydia trachomatis, MoPn, Chlamydia trachomatis, serovar D, Mycoplasma genitalium, G-37, Mycoplasma pulmonis, UAB CTIP, Mycobacterium leprae, TN, Mycobacterium tuberculosis, CDC1551, Mycobacterium tuberculosis, Hv37, Rickettsia conorii, Malish 7, Rickettsia prowazekii, Madrid E, Ureaplasma urealyticum, serovar 3
29 Pathogens ( all organisms reported to produce a disease in plants or animals):Pseudomonas aeruginosa, PAO1, Pasteurella multocida, Pm70, Ralstonia solanacearum, Staphylococcus aureus, Mu50, Staphylococcus aureus, N315 2624, Salmonella enterica serovar Typhi, CT18, Salmonella enterica serovar Typhimurium, LT2, Streptococcus pneumoniae, TIGR4, Streptococcus pneumoniae, R6, Streptococcus pyogenes M18, MGAS8232, Streptococcus pyogenes M1, SF370, Vibrio cholerae, El Tor N16961, Xylella fastidiosa, 9a5c, Yersinia pestis, CO92, Treponema pallidum, Nichols, Agrobacterium tumefaciens, C58, Borrelia burgdorferi, B31, Brucella melitensis, M16, Campylobacter jejuni, NCTC 11168, Clostridium perfringens, str. 13, Escherichia coli O157:H7, EDL933, Escherichia coli 0157:H7, RIMD0509952, Fusobacterium nucleatum, ATCC 25586, Haemophilus influenzae, KW20, Helicobacter pylori, 26695, Helicobacter pylori, J99, Listeria monocytogenes, EGD-e, Neisseria meningitidis, MC58, Neisseria meningitidis, Z2491
12 Free-living organisms: Anabaena sp., strain PCC 7120, Bacillus subtilis, 168, Caulobacter crescentus, CB15, Clostridium acetobutylicum, ATCC 824, Corynebacterium glutamicum, Escherichia coli, MG1655, Lactococcus lactis, IL1403, Listeria innocua, CLIP 11262, Mesorhizobium loti, MAFF303099, Sinorhizobium meliloti, strain 1021, Streptomyces coelicolor, A3(2), Synechocystis sp., PCC6803).
4 Extemophiles:Deinococcus radiodurans, R1, Aquifex aeolicus, VF5 1553,Thermotoga maritima, MSB8, Bacillus halodurans, C-125
The problem of phylogenetic The problem of phylogenetic distancesdistances
• 30 set of randomly selected proteins30 set of randomly selected proteins
S = logS = log22Hits / Hits of Random setHits / Hits of Random set
∑∑Hit / ∑Hits of Random setHit / ∑Hits of Random set
• Negative values = UNDERREPRESENTATIONNegative values = UNDERREPRESENTATION
• Positive values = OVERREPRESENTATIONPositive values = OVERREPRESENTATION
TransportTransport
-1.2 -1.0
-1.0 -0.8
-0.8 -0.6
-0.6 -0.4
-0.4 -0.2
-0.20.0
0.00.2
0.20.4
0.40.6
0.60.8
0.81.0
1.01.2
0
0,1
0,2
0,3
0,4
0,5
0,6
Free living organisms Pathogens Extremophiles Intracellular
Small-molecules MetabolismSmall-molecules Metabolism
-1.2 -1.0
-1.0 -0.8
-0.8 -0.6
-0.6 -0.4
-0.4 -0.2
-0.20.0
0.00.2
0.20.4
0.40.6
0.60.8
0.81.0
1.01.2
0
0,1
0,2
0,3
0,4
0,5
0,6
Free living organisms Pathogens Extremophiles Intracellular
Intracellular Pathogens and Intracellular Pathogens and symbionts enriched in Small symbionts enriched in Small
metabolism enzymes !!metabolism enzymes !!
TranscriptionTranscription
-1.2 -1
-1.0 -0.8
-0.8 -0.6
-0.6 -0.4
-0.4 -0.2
-0.20.0
0.00.2
0.20.4
0.40.6
0.60.8
0.81.0
1.01.2
0
0,1
0,2
0,3
0,4
0,5
0,6
Free living Organisms Pathogens Extremophiles Intracellular
Free-living bacteria require more Free-living bacteria require more regulators since they face more regulators since they face more
diverse conditionsdiverse conditions
Predictive power?Predictive power?
• Can we use these parameter to classify bacterial species?Can we use these parameter to classify bacterial species?
Combining TRANSC & SMMB Combining TRANSC & SMMB ScoresScores
-1
-0,8
-0,6
-0,4
-0,2
0
0,2
0,4
0,6
0,8
1
-1 -0,8 -0,6 -0,4 -0,2 0 0,2 0,4 0,6 0,8 1
TRANSC Score
SM
MB
Score
Intracellular Free living Organisms Pathogens
ECOL
SENT
PAER
HPYL
NMEN
SAUR
ConclusionsConclusions
• Effects of Bacterial lifestyle can be Effects of Bacterial lifestyle can be
observed even at low resolutionobserved even at low resolution
• Metabolism and Transcription-related Metabolism and Transcription-related
protein content can be use as lifestyle protein content can be use as lifestyle
descriptors to differentiate SPECIALIST descriptors to differentiate SPECIALIST
and GENERALIST Bacteriaand GENERALIST Bacteria
Convergence between Convergence between Extremophiles and EndosymbiontsExtremophiles and Endosymbionts
-1
-0,8
-0,6
-0,4
-0,2
0
0,2
0,4
0,6
0,8
1
-1 -0,8 -0,6 -0,4 -0,2 0 0,2 0,4 0,6 0,8 1
TRANSC Score
SMMB Score
Extremophyles Intracellular
Does it hold with 114 Does it hold with 114 Genomes?Genomes?
PathogensIntracellularExtremophilesFree living
June 2002:60June 2002:60 June 2003:114June 2003:114
•Broader Phylogenetic Broader Phylogenetic distribution distribution •Broader ecological Broader ecological distributiondistribution
TranscriptionTranscription
-1.2 -1
-1.0 -0.8
-0.8 -0.6
-0.6 -0.4
-0.4 -0.2
-0.20.0
0.00.2
0.20.4
0.40.6
0.60.8
0.81.0
1.01.2
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
Free living Organisms Pathogens Extremophiles Intracellular
Small Molecule MetabolismSmall Molecule Metabolism
-1.2 -1.0
-1.0 -0.8
-0.8 -0.6
-0.6 -0.4
-0.4 -0.2
-0.20.0
0.00.2
0.20.4
0.40.6
0.60.8
0.81.0
1.01.2
0
0.1
0.2
0.3
0.4
Free living organisms Pathogens Extremophiles Intracellular
-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
-1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1
Taps Score
Enz Score
Pathogens Extremophyles Intracellular Free living Organisms
Sargasso Sea MetagenomeSargasso Sea MetagenomeVenter Venter et al.et al.,2004. Science,2004. Science Apr 2;304(5667):66-74Apr 2;304(5667):66-74
1.045 Mb1.045 Mb
1.2 Millions new 1.2 Millions new ORFsORFs
from ~1400 from ~1400 different speciesdifferent species
~140 new~140 new
metabolismmetabolism 184850184850 15%15%
informationinformation 2596525965 2%2%
Venter et al.,2004. Science Apr 2;304(5667):66-74
ThanksThanks
AdriAdrià Garrigaà Garriga Guillermo CarbajosaGuillermo Carbajosa
Victor de Lorenzo (CNB)Victor de Lorenzo (CNB) Christos Ouzounis (EBI-EMBL, UK)Christos Ouzounis (EBI-EMBL, UK)
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