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Reconstruction and Comparison of Cellular Signaling Pathway Resources for the Systems-Level Analysis of Cross-Talks

  • Máté Pálfy
  • László Földvári-Nagy
  • Dezső Módos
  • Katalin Lenti
  • Tamás Korcsmáros

Abstract

Signaling pathways control a large variety of cellular processes and their defects are often linked with diseases. Reliable analyses of these pathways need uniform pathway definitions and curation rules applied to all pathways. Here, we compare KEGG, Reactome, Netpath and SignaLink pathway databases and examine their usefulness in systems-level analysis. Further on, we show that the integration of various bioinformatics databases allows a comprehensive understanding of the regulatory processes that control signaling pathways. We also discuss the drug target relevance of cross-talking (i.e., multi-pathway) proteins and signal transduction regulators (e.g., phophatases and miRNAs). Accordingly, modern integrated databases are not only essential for studying signaling processes at the systems level, but will also serve as invaluable tools for pharmacology and network-based medicine.

Keywords

Signaling Cross-talk Regulation Drug discovery Network Pathway miRNA Drug targeting Pathway database 

Acronyms

HTP

High-throughput

PPI

Protein-protein interaction

TF

Transcription factor

TFBS

Transcription factor binding site

miRNA

microRNA

Notes

Acknowledgments

The authors thank the members of the NetBiol Group (http://netbiol.elte.hu) for their useful comments and Peter Csermely for discussions. Work of TK was supported by a János Bolyai Scholarship of the Hungarian Academy of Sciences.

References

  1. 1.
    Pires-daSilva A, Sommer RJ (2003) The evolution of signalling pathways in animal development. Nat Rev Genet 4:39–49PubMedCrossRefGoogle Scholar
  2. 2.
    Gerhart J (1999) Warkany lecture: signaling pathways in development. Teratology 60:226–239PubMedCrossRefGoogle Scholar
  3. 3.
    Bray SJ (2006) Notch signalling: a simple pathway becomes complex. Nat Rev Mol Cell Biol 7:678–689PubMedCrossRefGoogle Scholar
  4. 4.
    Freeman M (2000) Feedback control of intercellular signalling in development. Nature 408:313–319PubMedCrossRefGoogle Scholar
  5. 5.
    Papin JA, Hunter T, Palsson BO, Subramaniam S (2005) Reconstruction of cellular signalling networks and analysis of their properties. Nat Rev Mol Cell Biol 6:99–111PubMedCrossRefGoogle Scholar
  6. 6.
    Korcsmaros T, Farkas IJ, Szalay MS, Rovo P, Fazekas D, Spiro Z, Bode C, Lenti K, Vellai T, Csermely P (2010) Uniformly curated signaling pathways reveal tissue-specific cross-talks and support drug target discovery. Bioinformatics 26:2042–2050PubMedCrossRefGoogle Scholar
  7. 7.
    Ulitsky I, Shamir R (2007) Pathway redundancy and protein essentiality revealed in the Saccharomyces cerevisiae interaction networks. Mol Syst Biol 3:104PubMedCentralPubMedCrossRefGoogle Scholar
  8. 8.
    Haney S, Bardwell L, Nie Q (2010) Ultrasensitive responses and specificity in cell signaling. BMC Syst Biol 4:119PubMedCentralPubMedCrossRefGoogle Scholar
  9. 9.
    Behar M, Dohlman HG, Elston TC (2007) Kinetic insulation as an effective mechanism for achieving pathway specificity in intracellular signaling networks. Proc Natl Acad Sci U S A 104:16146–16151PubMedCentralPubMedCrossRefGoogle Scholar
  10. 10.
    Bhattacharyya RP, Remenyi A, Yeh BJ, Lim WA (2006) Domains, motifs, and scaffolds: the role of modular interactions in the evolution and wiring of cell signaling circuits. Annu Rev Biochem 75:655–680PubMedCrossRefGoogle Scholar
  11. 11.
    Kholodenko BN (2006) Cell-signalling dynamics in time and space. Nat Rev Mol Cell Biol 7:165–176PubMedCentralPubMedCrossRefGoogle Scholar
  12. 12.
    Taniguchi CM, Emanuelli B, Kahn CR (2006) Critical nodes in signalling pathways: insights into insulin action. Nat Rev Mol Cell Biol 7:85–96PubMedCrossRefGoogle Scholar
  13. 13.
    Lu LJ, Sboner A, Huang YJ, Lu HX, Gianoulis TA, Yip KY, Kim PM, Montelione GT, Gerstein MB (2007) Comparing classical pathways and modern networks: towards the development of an edge ontology. Trends Biochem Sci 32:320–331PubMedCrossRefGoogle Scholar
  14. 14.
    Cerami EG, Bader GD, Gross BE, Sander C (2006) cPath: open source software for collecting, storing, and querying biological pathways. BMC Bioinf 7:497CrossRefGoogle Scholar
  15. 15.
    Bauer-Mehren A, Furlong LI, Sanz F (2009) Pathway databases and tools for their exploitation: benefits, current limitations and challenges. Mol Syst Biol 5:290PubMedCentralPubMedCrossRefGoogle Scholar
  16. 16.
    Ogata H, Goto S, Sato K, Fujibuchi W, Bono H, Kanehisa M (1999) KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res 27:29–34PubMedCentralPubMedCrossRefGoogle Scholar
  17. 17.
    Joshi-Tope G, Gillespie M, Vastrik I, D’Eustachio P, Schmidt E, de Bono B, Jassal B, Gopinath GR, Wu GR, Matthews L, Lewis S, Birney E, Stein L (2005) Reactome: a knowledgebase of biological pathways. Nucleic Acids Res 33:D428–D432PubMedCentralPubMedCrossRefGoogle Scholar
  18. 18.
    Kandasamy K, Mohan S, Raju R, Keerthikumar S, Kumar GS, Venugopal AK, Telikicherla D, Navarro DJ, Mathivanan S, Pecquet C, Gollapudi SK, Tattikota SG, Mohan S, Padhukasahasram H, Subbannayya Y, Goel R, Jacob HK, Zhong J, Sekhar R, Nanjappa V et al (2010) NetPath: a public resource of curated signal transduction pathways. Genome Biol 11:R3PubMedCentralPubMedCrossRefGoogle Scholar
  19. 19.
    Keshava Prasad TS, Goel R, Kandasamy K, Keerthikumar S, Kumar S, Mathivanan S, Telikicherla D, Raju R, Shafreen B, Venugopal A, Balakrishnan L, Marimuthu A, Banerjee S, Somanathan DS, Sebastian A, Rani S, Ray S, Harrys Kishore CJ, Kanth S, Ahmed M et al (2009) Human protein reference database–2009 update. Nucleic Acids Res 37:D767–D772PubMedCentralPubMedCrossRefGoogle Scholar
  20. 20.
    Farkas IJ, Korcsmaros T, Kovacs IA, Mihalik A, Palotai R, Simko GI, Szalay KZ, Szalay-Beko M, Vellai T, Wang S, Csermely P (2011) Network-based tools for the identification of novel drug targets. Sci Signal 4:3Google Scholar
  21. 21.
    Orchard S, Salwinski L, Kerrien S, Montecchi-Palazzi L, Oesterheld M, Stumpflen V, Ceol A, Chatr-aryamontri A, Armstrong J, Woollard P, Salama JJ, Moore S, Wojcik J, Bader GD, Vidal M, Cusick ME, Gerstein M, Gavin AC, Superti-Furga G, Greenblatt J et al (2007) The minimum information required for reporting a molecular interaction experiment (MIMIx). Nat Biotechnol 25:894–898PubMedCrossRefGoogle Scholar
  22. 22.
    Lin CC, Chen YJ, Chen CY, Oyang YJ, Juan HF, Huang HC (2012) Crosstalk between transcription factors and microRNAs in human protein interaction network. BMC Syst Biol 6:18PubMedCentralPubMedCrossRefGoogle Scholar
  23. 23.
    Doench JG, Sharp PA (2004) Specificity of microRNA target selection in translational repression. Genes Dev 18:504–511PubMedCentralPubMedCrossRefGoogle Scholar
  24. 24.
    Guo H, Ingolia NT, Weissman JS, Bartel DP (2010) Mammalian microRNAs predominantly act to decrease target mRNA levels. Nature 466:835–840PubMedCentralPubMedCrossRefGoogle Scholar
  25. 25.
    Lewis BP, Shih IH, Jones-Rhoades MW, Bartel DP, Burge CB (2003) Prediction of mammalian microRNA targets. Cell 115:787–798PubMedCrossRefGoogle Scholar
  26. 26.
    Calin GA, Croce CM (2006) MicroRNA signatures in human cancers. Nat Rev Cancer 6:857–866PubMedCrossRefGoogle Scholar
  27. 27.
    Liang H, Li WH (2007) MicroRNA regulation of human protein protein interaction network. RNA 13:1402–1408PubMedCentralPubMedCrossRefGoogle Scholar
  28. 28.
    Hsu CW, Juan HF, Huang HC (2008) Characterization of microRNA-regulated protein–protein interaction network. Proteomics 8:1975–1979PubMedCrossRefGoogle Scholar
  29. 29.
    Vaquerizas JM, Kummerfeld SK, Teichmann SA, Luscombe NM (2009) A census of human transcription factors: function, expression and evolution. Nat Rev Genet 10:252–263PubMedCrossRefGoogle Scholar
  30. 30.
    Griffith OL, Montgomery SB, Bernier B, Chu B, Kasaian K, Aerts S, Mahony S, Sleumer MC, Bilenky M, Haeussler M, Griffith M, Gallo SM, Giardine B, Hooghe B, Van Loo P, Blanco E, Ticoll A, Lithwick S, Portales-Casamar E, Donaldson IJ et al (2008) ORegAnno: an open-access community-driven resource for regulatory annotation. Nucleic Acids Res 36:D107–D113PubMedCentralPubMedCrossRefGoogle Scholar
  31. 31.
    Gupta R, Bhattacharyya A, Agosto-Perez FJ, Wickramasinghe P, Davuluri RV (2011) MPromDb update 2010: an integrated resource for annotation and visualization of mammalian gene promoters and ChIP-seq experimental data. Nucleic Acids Res 39:D92–D97PubMedCentralPubMedCrossRefGoogle Scholar
  32. 32.
    Portales-Casamar E, Kirov S, Lim J, Lithwick S, Swanson MI, Ticoll A, Snoddy J, Wasserman WW (2007) PAZAR: a framework for collection and dissemination of cis-regulatory sequence annotation. Genome Biol 8:R207PubMedCentralPubMedCrossRefGoogle Scholar
  33. 33.
    Portales-Casamar E, Thongjuea S, Kwon AT, Arenillas D, Zhao X, Valen E, Yusuf D, Lenhard B, Wasserman WW, Sandelin A (2010) JASPAR 2010: the greatly expanded open-access database of transcription factor binding profiles. Nucleic Acids Res 38:D105–D110PubMedCentralPubMedCrossRefGoogle Scholar
  34. 34.
    Vergoulis T, Vlachos IS, Alexiou P, Georgakilas G, Maragkakis M, Reczko M, Gerangelos S, Koziris N, Dalamagas T, Hatzigeorgiou AG (2012) TarBase 6.0: capturing the exponential growth of miRNA targets with experimental support. Nucleic Acids Res 40:D222–D229PubMedCentralPubMedCrossRefGoogle Scholar
  35. 35.
    Krek A, Grun D, Poy MN, Wolf R, Rosenberg L, Epstein EJ, MacMenamin P, da PI, Gunsalus KC, Stoffel M, Rajewsky N (2005) Combinatorial microRNA target predictions. Nat Genet 37:495–500Google Scholar
  36. 36.
    Lewis BP, Burge CB, Bartel DP (2005) Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell 120:15–20PubMedCrossRefGoogle Scholar
  37. 37.
    Bandyopadhyay S, Bhattacharyya M (2010) PuTmiR: a database for extracting neighboring transcription factors of human microRNAs. BMC Bioinformatics 11:190PubMedCentralPubMedCrossRefGoogle Scholar
  38. 38.
    Wang J, Lu M, Qiu C, Cui Q (2010) TransmiR: a transcription factor-microRNA regulation database. Nucleic Acids Res 38:D119–D122PubMedCentralPubMedCrossRefGoogle Scholar
  39. 39.
    Alexiou P, Vergoulis T, Gleditzsch M, Prekas G, Dalamagas T, Megraw M, Grosse I, Sellis T, Hatzigeorgiou AG (2010) miRGen 2.0: a database of microRNA genomic information and regulation. Nucleic Acids Res 38:D137–D141PubMedCentralPubMedCrossRefGoogle Scholar
  40. 40.
    Xiao F, Zuo Z, Cai G, Kang S, Gao X, Li T (2009) miRecords: an integrated resource for microRNA-target interactions. Nucleic Acids Res 37:D105–D110PubMedCentralPubMedCrossRefGoogle Scholar
  41. 41.
    Baitaluk M, Kozhenkov S, Dubinina Y, Ponomarenko J (2012) IntegromeDB: an integrated system and biological search engine. BMC Gen 13:35CrossRefGoogle Scholar
  42. 42.
    Lepoivre C, Bergon A, Lopez F, Perumal NB, Nguyen C, Imbert J, Puthier D (2012) TranscriptomeBrowser 3.0: introducing a new compendium of molecular interactions and a new visualization tool for the study of gene regulatory networks. BMC Bioinformatics 13:19PubMedCentralPubMedCrossRefGoogle Scholar
  43. 43.
    Kitano H (2007) A robustness-based approach to systems-oriented drug design. Nat Rev Drug Discov 6:202–210PubMedCrossRefGoogle Scholar
  44. 44.
    Korcsmaros T, Szalay MS, Bode C, Kovacs IA, Csermely P (2007) How to design multi-target drugs: target-search options in cellular networks. Exp Op Drug Discovery 2:799–808CrossRefGoogle Scholar
  45. 45.
    Hwang WC, Zhang A, Ramanathan M (2008) Identification of information flow-modulating drug targets: a novel bridging paradigm for drug discovery. Clin Pharmacol Ther 84:563–572PubMedCrossRefGoogle Scholar
  46. 46.
    Tomlinson IP, Novelli MR, Bodmer WF (1996) The mutation rate and cancer. Proc Natl Acad Sci U S A 93:14800–14803PubMedCentralPubMedCrossRefGoogle Scholar
  47. 47.
    Ali MA, Sjoblom T (2009) Molecular pathways in tumor progression: from discovery to functional understanding. Mol BioSyst 5:902–908PubMedCrossRefGoogle Scholar
  48. 48.
    Hornberg JJ, Bruggeman FJ, Westerhoff HV, Lankelma J (2006) Cancer: a systems biology disease. Biosystems 83:81–90PubMedCrossRefGoogle Scholar
  49. 49.
    Hanahan D, Weinberg RA (2000) The hallmarks of cancer. Cell 100:57–70PubMedCrossRefGoogle Scholar
  50. 50.
    Hanahan D, Weinberg RA (2011) Hallmarks of cancer: the next generation. Cell 144:646–674PubMedCrossRefGoogle Scholar
  51. 51.
    Papatsoris AG, Karamouzis MV, Papavassiliou AG (2007) The power and promise of rewiring the mitogen-activated protein kinase network in prostate cancer therapeutics. Mol Cancer Ther 6:811–819PubMedCrossRefGoogle Scholar
  52. 52.
    Kim D, Rath O, Kolch W, Cho KH (2007) A hidden oncogenic positive feedback loop caused by crosstalk between Wnt and ERK pathways. Oncogene 26:4571–4579PubMedCrossRefGoogle Scholar
  53. 53.
    Torkamani A, Schork NJ (2009) Identification of rare cancer driver mutations by network reconstruction. Genome Res 19:1570–1578PubMedCentralPubMedCrossRefGoogle Scholar
  54. 54.
    Mimeault M, Batra SK (2010) Frequent deregulations in the hedgehog signaling network and cross-talks with the epidermal growth factor receptor pathway involved in cancer progression and targeted therapies. Pharmacol Rev 62:497–524PubMedCentralPubMedCrossRefGoogle Scholar
  55. 55.
    Pawson T, Linding R (2008) Network medicine. FEBS Lett 582:1266–1270PubMedCrossRefGoogle Scholar
  56. 56.
    Hornbeck PV, Chabra I, Kornhauser JM, Skrzypek E, Zhang B (2004) PhosphoSite: a bioinformatics resource dedicated to physiological protein phosphorylation. Proteomics 4:1551–1561PubMedCrossRefGoogle Scholar
  57. 57.
    Linding R, Jensen LJ, Ostheimer GJ, van Vugt MA, Jorgensen C, Miron IM, Diella F, Colwill K, Taylor L, Elder K, Metalnikov P, Nguyen V, Pasculescu A, Jin J, Park JG, Samson LD, Woodgett JR, Russell RB, Bork P, Yaffe MB et al (2007) Systematic discovery of in vivo phosphorylation networks. Cell 129:1415–1426PubMedCentralPubMedCrossRefGoogle Scholar
  58. 58.
    Miller ML, Jensen LJ, Diella F, Jorgensen C, Tinti M, Li L, Hsiung M, Parker SA, Bordeaux J, Sicheritz-Ponten T, Olhovsky M, Pasculescu A, Alexander J, Knapp S, Blom N, Bork P, Li S, Cesareni G, Pawson T, Turk BE et al (2008) Linear motif atlas for phosphorylation-dependent signaling. Sci Signal 1:ra2Google Scholar
  59. 59.
    Remenyi A, Good MC, Lim WA (2006) Docking interactions in protein kinase and phosphatase networks. Curr Opin Struct Biol 16:676–685PubMedCrossRefGoogle Scholar
  60. 60.
    Nguyen LK, Matallanas D, Croucher DR, von Kriegsheim A, Kholodenko BN (2012) Signalling by protein phosphatases and drug development: a systems-centred view. FEBS J. 280:751–765Google Scholar
  61. 61.
    Alonso A, Sasin J, Bottini N, Friedberg I, Friedberg I, Osterman A, Godzik A, Hunter T, Dixon J, Mustelin T (2004) Protein tyrosine phosphatases in the human genome. Cell 117:699–711PubMedCrossRefGoogle Scholar
  62. 62.
    Roy J, Cyert MS (2009) Cracking the phosphatase code: docking interactions determine substrate specificity. Sci Signal 2:re9Google Scholar
  63. 63.
    Shi Y (2009) Serine/threonine phosphatases: mechanism through structure. Cell 139:468–484PubMedCrossRefGoogle Scholar
  64. 64.
    Barr AJ (2010) Protein tyrosine phosphatases as drug targets: strategies and challenges of inhibitor development. Future Med Chem 2:1563–1576PubMedCrossRefGoogle Scholar
  65. 65.
    Gambari R, Fabbri E, Borgatti M, Lampronti I, Finotti A, Brognara E, Bianchi N, Manicardi A, Marchelli R, Corradini R (2011) Targeting microRNAs involved in human diseases: a novel approach for modification of gene expression and drug development. Biochem Pharmacol 82:1416–1429PubMedCrossRefGoogle Scholar
  66. 66.
    Lu M, Zhang Q, Deng M, Miao J, Guo Y, Gao W, Cui Q (2008) An analysis of human microRNA and disease associations. PLoS ONE 3:e3420PubMedCentralPubMedCrossRefGoogle Scholar
  67. 67.
    McDermott AM, Heneghan HM, Miller N, Kerin MJ (2011) The therapeutic potential of microRNAs: disease modulators and drug targets. Pharm Res 28:3016–3029PubMedCrossRefGoogle Scholar
  68. 68.
    Farkas IJ, Szanto-Varnagy A, Korcsmaros T (2012) Linking proteins to signaling pathways for experiment design and evaluation. PLoS ONE 7:e36202PubMedCentralPubMedCrossRefGoogle Scholar
  69. 69.
    Kuhn M, Campillos M, Letunic I, Jensen LJ, Bork P (2010) A side effect resource to capture phenotypic effects of drugs. Mol Syst Biol 6:343PubMedCentralPubMedCrossRefGoogle Scholar
  70. 70.
    McClean MN, Mody A, Broach JR, Ramanathan S (2007) Cross-talk and decision making in MAP kinase pathways. Nat Genet 39:409–414PubMedCrossRefGoogle Scholar
  71. 71.
    Guo X, Wang XF (2009) Signaling cross-talk between TGF-beta/BMP and other pathways. Cell Res 19:71–88PubMedCentralPubMedCrossRefGoogle Scholar
  72. 72.
    Hurlbut GD, Kankel MW, Lake RJ, Artavanis-Tsakonas S (2007) Crossing paths with Notch in the hyper-network. Curr Opin Cell Biol 19:166–175PubMedCrossRefGoogle Scholar
  73. 73.
    Katoh M, Katoh M (2007) WNT signaling pathway and stem cell signaling network. Clin Cancer Res 13:4042–4045PubMedCrossRefGoogle Scholar
  74. 74.
    Borisov N, Aksamitiene E, Kiyatkin A, Legewie S, Berkhout J, Maiwald T, Kaimachnikov NP, Timmer J, Hoek JB, Kholodenko BN (2009) Systems-level interactions between insulin-EGF networks amplify mitogenic signaling. Mol Syst Biol 5:256PubMedCentralPubMedCrossRefGoogle Scholar
  75. 75.
    Wang CC, Cirit M, Haugh JM (2009) PI3 K-dependent cross-talk interactions converge with Ras as quantifiable inputs integrated by Erk. Mol Syst Biol 5:246PubMedCentralPubMedCrossRefGoogle Scholar
  76. 76.
    Natarajan M, Lin KM, Hsueh RC, Sternweis PC, Ranganathan R (2006) A global analysis of cross-talk in a mammalian cellular signalling network. Nat Cell Biol 8:571–580PubMedCrossRefGoogle Scholar
  77. 77.
    Blank U, Karlsson G, Karlsson S (2008) Signaling pathways governing stem-cell fate. Blood 111:492–503PubMedCrossRefGoogle Scholar
  78. 78.
    Robinson GW (2007) Cooperation of signalling pathways in embryonic mammary gland development. Nat Rev Genet 8:963–972PubMedCrossRefGoogle Scholar
  79. 79.
    Sternberg PW (2005) Vulval development. WormBook 1–28Google Scholar
  80. 80.
    Yan SJ, Gu Y, Li WX, Fleming RJ (2004) Multiple signaling pathways and a selector protein sequentially regulate Drosophila wing development. Development 131:285–298PubMedCrossRefGoogle Scholar
  81. 81.
    Katoh M (2007) Networking of WNT, FGF, Notch, BMP, and Hedgehog signaling pathways during carcinogenesis. Stem Cell Rev 3:30–38PubMedCrossRefGoogle Scholar
  82. 82.
    Li Y, Agarwal P, Rajagopalan D (2008) A global pathway crosstalk network. Bioinformatics 24:1442–1447PubMedCrossRefGoogle Scholar
  83. 83.
    Boswell BA, Lein PJ, Musil LS (2008) Cross-talk between fibroblast growth factor and bone morphogenetic proteins regulates gap junction-mediated intercellular communication in lens cells. Mol Biol Cell 19:2631–2641PubMedCentralPubMedCrossRefGoogle Scholar
  84. 84.
    Fraser ID, Germain RN (2009) Navigating the network: signaling cross-talk in hematopoietic cells. Nat Immunol 10:327–331Google Scholar
  85. 85.
    Dreesen O, Brivanlou AH (2007) Signaling pathways in cancer and embryonic stem cells. Stem Cell Rev 3:7–17Google Scholar
  86. 86.
    Fisher J, Piterman N, Hajnal A, Henzinger TA (2007) Predictive modeling of signaling crosstalk during C. elegans vulval development. PLOS Comput Biol 3:e92Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Máté Pálfy
    • 1
  • László Földvári-Nagy
    • 1
  • Dezső Módos
    • 1
    • 2
  • Katalin Lenti
    • 2
  • Tamás Korcsmáros
    • 1
  1. 1.Department of GeneticsEötvös Loránd UniversityBudapestHungary
  2. 2.Department of Morphology and PhysiologyFaculty of Health Sciences, Semmelweis UniversityBudapestHungary

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