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Transcription Networks Ildefonso Cases (CNB-CSIC).

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Presentation on theme: "Transcription Networks Ildefonso Cases (CNB-CSIC)."— Presentation transcript:

1 Transcription Networks Ildefonso Cases (CNB-CSIC)

2 Summary  Concepts in Transcription  Transcription Networks Definition, properties and evolution Definition, properties and evolution  Transcription Networks vs Functional Networks  Evolution of Regulatory Structures  Transcription and Adaptation

3 Regulación de la Transcripción Resultado de la interacción entre proteínas y DNA. Resultado de la interacción entre proteínas y DNA. El conjunto de proteínas que se unan a su región promotora (directa o indirectamente) va a determinar la expresión de un gen: El conjunto de proteínas que se unan a su región promotora (directa o indirectamente) va a determinar la expresión de un gen:  En que tejidos  En que momento del desarrollo  Bajo que condiciones ambientales  etc.

4 Transcripción en Bacterias

5 Transcripción en Bacterias: Factores Sigma  Escherichia coli sigma70/D sigma70/D sigma32/H: heat shock sigma32/H: heat shock sigma24/E: ECF sigma24/E: ECF sigma28: flagelo sigma28: flagelo sigma38/S:fase estacionaria,stress sigma38/S:fase estacionaria,stress sigma54/N: nitrógeno y otros sigma54/N: nitrógeno y otros fecI: hierro fecI: hierro  Pseudomonas putida: > 15  Streptomyces: > 30

6 Transcripción en Bacterias

7 Transcripción en Bacterias: Operones

8 Transcripción en Eukariotas

9

10 Transcripción en Archeas Maquinaria basal Eukariota Maquinaria basal Eukariota Reguladores eukariotas y bacterianos Reguladores eukariotas y bacterianos

11 Otras fuentes de Regulación  Elongación  Estabilidad del mRNA  etc.

12 Transcription Networks

13

14

15 Regulators regulates: genes p(k)=ak -b Scale-free Networks Resistant to Error Sensitive to Attack Network Properties

16 Yeast Guelzim et al. 2002 Nature Genet. 31:60-63

17 Preferential Attachment 1 2 3

18 Network evolution Duplicated Genes are often co-expressed and share regulator binding sites van Noort et al., 2004 EMBO Rep 5(3):280-4

19 Binding sites Evolution Papp et al,2003. Trends Genet 19:417

20 Milo et al,2002. Science 298:824 Motives

21 Motives

22

23 Motives Profiling Milo et al. 2004 Science 303:1538-1542

24 Overlapping Motives Bi-fan y FFL often share nodes and edges Dobrin et al,2004. BMC Bioiformatics 5:10

25 Motives Evolution Conant & Wagner,2003. Nat Genet. 34:264

26 Motives Properties Shen-Orr et al.,2002. Nat Genet. 31:64

27 Coregulation Network gamma≈-1c=0.6scale-free small world van Noort et al., 2004 EMBO Rep 5(3):280-4

28 Network Evolution Simulation van Noort et al., 2004 EMBO Rep 5(3):280-4

29 In the absence of selection we can reproduce a network with similar properties van Noort et al., 2004 EMBO Rep 5(3):280-4 Network Evolution Simulation

30 Trancription Networks Dynamics Luscombe et al., 2004 Nature 431:308

31 Trancription Networks Dynamics Luscombe et al., 2004 Nature 431:308

32 Trancription Networks Dynamics EndogenousExogenous

33 Combining Networks Regulatory Networks vs. Functional Networks Functional Networks

34 Functional Associations Protein Complexes Protein Complexes Enzymes …. Ribosomes Enzymes …. Ribosomes Information/Biochemical Pathways Information/Biochemical Pathways Metabolic Programs Metabolic Programs Anaerobic… Aerobic Metabolism Anaerobic… Aerobic Metabolism Biological Processes Biological Processes Transcription … Recombination Transcription … Recombination

35 Relation between functional associations and co-regulation? “co-regulated genes are functionally associated”

36 Precedents Pairs of interacting proteins are more frequent among co-expressed genes in S. cerevisiae Pairs of interacting proteins are more frequent among co-expressed genes in S. cerevisiae 50% of the pairs of co-expressed genes belong to the same biochemical pathway in S. cerevisiae and more than 30% in C. elegans 50% of the pairs of co-expressed genes belong to the same biochemical pathway in S. cerevisiae and more than 30% in C. elegans In E. coli and B. subtilis genes in operons (and thus presumably co-expressed) tend to belong to the same general class of cellular function In E. coli and B. subtilis genes in operons (and thus presumably co-expressed) tend to belong to the same general class of cellular function

37 Ecocyc Protein Complexes and sub-complexes Protein Complexes and sub-complexes Biochemical Pathways Biochemical Pathways Pathways and Super-pathways Pathways and Super-pathways Regulatory information Regulatory information Transcription Units Transcription Units Regulatory Proteins Regulatory Proteins Regulons: Genes directly regulated by the same protein in the same way Regulons: Genes directly regulated by the same protein in the same way Super-regulons: also include indirect interactions Super-regulons: also include indirect interactions

38 Correlated? Functional Associations Functional Associations Complexes Complexes Pathways Pathways Superpathways Superpathways Regulatory Associations Regulatory Associations Transcription Units Regulons Supe-regulons

39 Coding functional associations A B C A B C AB E G F C A B C EF G ABCD A0110 B1010 C1100 D0000

40 Coding Regulatory associations C DBA ABC D ABA B C A CD B AB CD ABCD A0100 B1010 C0100 D0000 C

41 ACDE A0101 C1010 D0101 E1010 ABCD A0011 B0010 C1101 D1010 ACD A010 C101 D010 ACD A011 C101 D110 ACD A010 C101 D010 OriginalMatrices ReducedMatrices I a =2 I b =3 I ab /I a =2/2=100% I ab /I b =2/3=66% Gene Network Network Functional Assoc. I ce = I a *I b /(N*(N-1)/2)

42 Complexes vs. Transcription Units 282 genes, 87% and 85%, 80 times more than expected

43 Exceptions MtlA GatA GatB GatC PtsH PtsI

44 Exceptions Evolutionary Implications?

45 Pathways vs. Transcription Units 330 genes, 94% and 26%, 35 times more than expected

46 Transcription Units per Pathway 0 0,05 0,1 0,15 0,2 0,25 0,3 0,35 0,4 0,45 123456789101112131415161718192021222324252627

47 AB E G F C A B C EF G A B C EF G 66% 26%

48 Complexes vs. Regulons 209 genes, 10% and 97%, 7 times more than expected

49 Pathways vs. Regulon 258 genes, 18% and 77%, 4 times more than expected

50 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 association Gene Network

51 DBA ABC DC 15% 2.8 13% 3.2 6% 4.1 GR 20% 3.8 18% 4.2 10% 6.9 RE 80%87%97% GR 71%77%97% RE SPPC SPPC

52

53 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% NO 07054601165 Super-path. 020929 Pathway 2442258504 COMPLEX 16470171 TURegulon Super- regulon ALL 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% NO 3401255 Super-reg. 0670 Regulon 742220449 TU 164240188 ComplexPathway Super- pathway ALL

54 Conclusions Subunits of protein complexes are often in the same transcription unit Subunits of protein complexes are often in the same transcription unit Pathways are spread in several transcription units, which contains linear sub-pathways and are often co-regulated Pathways are spread in several transcription units, which contains linear sub-pathways and are often co-regulated Expression of pathway branches is often coordinated Expression of pathway branches is often coordinated The tighter the functional association the tighter the mechanism of co- regulation The tighter the functional association the tighter the mechanism of co- regulation

55 Evolution of regulons Regulatory Structures has functional sense How regulons are assemble during evolution?

56 Genome AGenome BGenome CGenome DGenome FGenome GGenome H

57 Sigma54 Sigma54 regulon: “relatively easy” to predict well distributed in the bacterial tree good number : 10-100 per genome

58 Distribution of sigma54 Aquifex aeolicus D. radiodurans T. maritima E. coli S. typhi Y. pestis V. cholerae P. aeurginosa Buchnera sp. H. influenzae P. multocida N. meningiditis R. solanacearum H. pylori C. jejuni S. meliloti M. loti A. tumafaciens B. melitensis C. crescentus R. prowazekii R. conorii T. pallidum B. burgdorferi C. trachomatis Actinobacteria B. subtilis L. inocua S. aureus S. pyogenes M. neumoniae

59 conserved 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

60 phylogenetic profiles GlnA GlnK His-Ki LivK HisJ GltP FlgB PrpB ArgD alpha beta gamma gram + aquifex delta- epsilon

61 Evolution Sigma54 regulon Sigma54 regulon is very dynamic Expression of genes transcribed from sigma54 promoters is couple to physiological conditions Are Genes required to be coupled to physiological conditions different in different bacterial species? How regulation reflects life-style?

62 Bacteria Lifestyles

63 Enrichment in Transcriptional Regulators of the Pseudomonas aeruginosa Genome Enrichment in Transcriptional Regulators of the Pseudomonas aeruginosa Genome

64 Cellular Processes and Bacterial Lifestyle Transport, Metabolism and Transcription Transport, Metabolism and Transcription Three sets of proteins from E. coli Three sets of proteins from E. coli 396 Transcription-associated proteins as annotated in Swissprot 396 Transcription-associated proteins as annotated in Swissprot 548 Small-molecules Metabolism Enzymes from EcoCyc 548 Small-molecules Metabolism Enzymes from EcoCyc 647 Transporters from EcoCyc 647 Transporters from EcoCyc Blast against all available sequenced genomes classified by lifestyle Blast against all available sequenced genomes classified by lifestyle

65 60 genomes 15 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

66 The problem of phylogenetic distances 30 set of randomly selected proteins 30 set of randomly selected proteins S = log 2 Hits / Hits of Random set ∑Hit / ∑Hits of Random set Negative values = UNDERREPRESENTATION Negative values = UNDERREPRESENTATION Positive values = OVERREPRESENTATION Positive values = OVERREPRESENTATION

67 Transport

68 Small-molecules Metabolism

69 Intracellular Pathogens and symbionts enriched in Small metabolism enzymes !!

70 Transcription

71 Free-living bacteria require more regulators since they face more diverse conditions

72 Predictive power? Can we use these parameter to classify bacterial species? Can we use these parameter to classify bacterial species?

73 Combining TRANSC & SMMB Scores 0,4 0,6 0,8 1 -0,8-0,6-0,4-0,200,20,40,60,81 TRANSC Score SMMB Score IntracellularFree living OrganismsPathogens ECOL SENT PAER HPYL NMEN SAUR

74 Conclusions Effects of Bacterial lifestyle can be observed even at low resolution Effects of Bacterial lifestyle can be observed even at low resolution Metabolism and Transcription-related protein content can be use as lifestyle descriptors to differentiate SPECIALIST and GENERALIST Bacteria Metabolism and Transcription-related protein content can be use as lifestyle descriptors to differentiate SPECIALIST and GENERALIST Bacteria

75 Convergence between Extremophiles and Endosymbionts

76 Does it hold with 114 Genomes? June 2002:60 June 2003:114 Broader Phylogenetic distribution Broader Phylogenetic distribution Broader ecological distribution Broader ecological distribution

77 Transcription

78 Small Molecule Metabolism

79

80 Sargasso Sea Metagenome Venter et al.,2004. Science Apr 2;304(5667):66-74 1.045 Mb 1.2 Millions new ORFs from ~1400 different species ~140 new

81 metabolism18485015%information259652% Venter et al.,2004. Science Apr 2;304(5667):66-74

82 Thanks  Adrià Garriga  Guillermo Carbajosa  Victor de Lorenzo (CNB)  Christos Ouzounis (EBI-EMBL, UK)


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