Systems biology and its impact on anti-infective drug development

  • Michael P. Stumpf
  • Brian D. Robertson
  • Ken Duncan
  • Douglas B. Young
Part of the Progress in Drug Research book series (PDR, volume 64)


Systems biology offers the potential for more effective selection of novel targets for anti-infective drugs. In contrast to conventional reductionist biology, a systems approach allows targets to be viewed in a wider context of the entire physiology of the cell, with the potential to identify key susceptible nodes and to predict synergistic effects of blocking multiple pathways. In addition to the holistic perspective provided by systems biology, the emphasis on quantitative analysis is likely to add further rigour to the process of target selection. Systems biology also offers the potential to incorporate different levels of information into the selection process. Consideration of data from microbial population biology may be important in the context of predicting future drug-resistance profiles associated with targeting a particular pathway, for example. This chapter provides an overview of major themes in the developing field of systems biology, summarising the core technologies and the strategies used to translate datasets into useful quantitative models capable of predicting complex biological behaviour.


imaging integrative systems biology mathematical models metabolic networks protein interaction network targets for anti-infective drugs transciptional networks 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    FDA (2004) The Critical Path to New Medical Products. Scholar
  2. 2.
    Kan CW, Fredlake CP, Doherty EA, Barron AE (2004) DNA sequencing and genotyping in miniaturized electrophoresis systems. Electrophoresis 25: 3564–3588PubMedCrossRefGoogle Scholar
  3. 3.
    McGall GH, Christians FC (2002) High-density genechip oligonucleotide probe arrays. Adv Biochem Eng Biotechnol 77: 21–42PubMedGoogle Scholar
  4. 4.
    van Steensel B (2005) Mapping of genetic and epigenetic regulatory networks using microarrays. Nat Genet 37Suppl: S18–24PubMedCrossRefGoogle Scholar
  5. 5.
    Allison DB, Cui X, Page GP, Sabripour M (2006) Microarray data analysis: from disarray to consolidation and consensus. Nat Rev Genet 7: 55–65PubMedCrossRefGoogle Scholar
  6. 6.
    Hernandez P, Muller M, Appel RD (2006) Automated protein identification by tandem mass spectrometry: Issues and strategies. Mass SpectromRev 25: 235–254CrossRefGoogle Scholar
  7. 7.
    Liebler DC (2004) Shotgun mass spec goes independent. Nat Methods 1: 16–17PubMedCrossRefGoogle Scholar
  8. 8.
    Fields S (2005) High-throughput two-hybrid analysis. The promise and the peril. Febs J 272: 5391–5399PubMedCrossRefGoogle Scholar
  9. 9.
    Puig O, Caspary F, Rigaut G, Rutz B, Bouveret E, Bragado-Nilsson E, Wilm M, Seraphin B (2001) The tandem affinity purification (TAP) method: a general procedure of protein complex purification. Methods 24: 218–229PubMedCrossRefGoogle Scholar
  10. 10.
    Ren B, Dynlacht BD (2004) Use of chromatin immunoprecipitation assays in genome-wide location analysis of mammalian transcription factors. Methods Enzymol 376: 304–315PubMedCrossRefGoogle Scholar
  11. 11.
    Ren B, Robert F, Wyrick JJ, Aparicio O, Jennings EG, Simon I, Zeitlinger J, Schreiber J, Hannett N, Kanin E et al (2000) Genome-wide location and function of DNA binding proteins. Science 290: 2306–2309PubMedCrossRefGoogle Scholar
  12. 12.
    Haslam SM, Gems D, Morris HR, Dell A (2002) The glycomes of Caenorhabditis elegans and other model organisms. Biochem Soc Symp: 117–134Google Scholar
  13. 13.
    Doherty MK, Beynon RJ (2006) Protein turnover on the scale of the proteome. Expert Rev Proteomics 3: 97–110PubMedCrossRefGoogle Scholar
  14. 14.
    Nicholson JK, Holmes E, Wilson ID (2005) Gut microorganisms, mammalian metabolism and personalized health care. Nat Rev Microbiol 3: 431–438PubMedCrossRefGoogle Scholar
  15. 15.
    Kitano H, Oda K (2006) Robustness trade-offs and host-microbial symbiosis in the immune system. Mol Syst Biol 2 doi: 10.1038/msb4100039Google Scholar
  16. 16.
    Howard M, Kruse K (2005) Cellular organization by self-organization: mechanisms and models for Min protein dynamics. J Cell Biol 168: 533–536PubMedCrossRefGoogle Scholar
  17. 17.
    Yuste R (2005) Fluorescence microscopy today. Nat Methods 2: 902–904PubMedCrossRefGoogle Scholar
  18. 18.
    Doubrovinski K, Howard M (2005) Stochastic model for Soj relocation dynamics in Bacillus subtilis. Proc Natl Acad Sci USA 102: 9808–9813PubMedCrossRefGoogle Scholar
  19. 19.
    Balaban NQ, Merrin J, Chait R, Kowalik L, Leibler S (2004) Bacterial persistence as a phenotypic switch. Science 305: 1622–1625PubMedCrossRefGoogle Scholar
  20. 20.
    Kussell E, Kishony R, Balaban NQ, Leibler S (2005) Bacterial persistence: a model of survival in changing environments. Genetics 169: 1807–181PubMedCrossRefGoogle Scholar
  21. 21.
    Andries K, Verhasselt P, Guillemont J, Gohlmann HW, Neefs JM, Winkler H, Van Gestel J, Timmerman P, Zhu M, Lee E et al (2005) A diarylquinoline drug active on the ATP synthase of Mycobacterium tuberculosis. Science 307: 223–227PubMedCrossRefGoogle Scholar
  22. 22.
    Manjunatha UH, Boshoff H, Dowd CS, Zhang L, Albert TJ, Norton JE, Daniels L, Dick T, Pang SS, Barry CE 3rd (2006) Identification of a nitroimidazo-oxazinespecific protein involved in PA-824 resistance in Mycobacterium tuberculosis. Proc Natl Acad Sci USA 103: 431–436PubMedCrossRefGoogle Scholar
  23. 23.
    Boshoff HI, Myers TG, Copp BR, McNeil MR, Wilson MA, Barry CE 3rd (2004) The transcriptional responses of Mycobacterium tuberculosis to inhibitors of metabolism: novel insights into drugmechanisms of action. J Biol Chem 279: 40174–40184PubMedCrossRefGoogle Scholar
  24. 24.
    Albert TJ, Dailidiene D, Dailide G, Norton JE, Kalia A, Richmond TA, Molla M, Singh J, Green RD, Berg DE (2005) Mutation discovery in bacterial genomes: metronidazole resistance in Helicobacter pylori. Nat Methods 2: 951–953PubMedCrossRefGoogle Scholar
  25. 25.
    Margulies M, Egholm M, Altman WE, Attiya S, Bader JS, Bemben LA, Berka J, Braverman MS, Chen YJ, Chen Z et al (2005) Genome sequencing in microfabricated high-density picolitre reactors. Nature 437: 376–380PubMedGoogle Scholar
  26. 26.
    Nuwaysir EF, Huang W, Albert TJ, Singh J, Nuwaysir K, Pitas A, Richmond T, Gorski T, Berg JP, Ballin J et al (2002) Gene expression analysis using oligonucleotide arrays produced by maskless photolithography. Genome Res 12: 1749–1755PubMedCrossRefGoogle Scholar
  27. 27.
    Fell D (1996) Understanding the Control of Metabolism. Portland Press Ltd, UKGoogle Scholar
  28. 28.
    Murray JD (2001) Mathematical Biology: An Introduction: Pts. 1 & 2. Springer-Verlag New York Inc, USAGoogle Scholar
  29. 29.
    Fulde P (1995) Electron Correlations in Molecules and Solids. Springer-Verlag Berlin and Heidelberg GmbH & Co, GermanyGoogle Scholar
  30. 30.
    Nowak M, May R (2000) Virus Dynamics: Mathematical Principles of Immunology and Virology. Oxford University Press, UKGoogle Scholar
  31. 31.
    Crampin EJ, Halstead M, Hunter P, Nielsen P, Noble D, Smith N, Tawhai M (2004) Computational physiology and the Physiome Project. Exp Physiol 89: 1–26PubMedCrossRefGoogle Scholar
  32. 32.
    Noble D (2006) Systems biology and the heart. Biosystems 83: 75–80PubMedCrossRefGoogle Scholar
  33. 33.
    de Silva E, Stumpf MPH (2005) Complex networks and simple models in biology. J Royal Soc Interface 2: 419–430CrossRefGoogle Scholar
  34. 34.
    Dobra A, Hans C, Jones B, Nevins JR, West M (2004) Sparse graphical models for exploring gene expression data. J Multiv Analysis 90: 196–212CrossRefGoogle Scholar
  35. 35.
    Schafer J, Strimmer K (2005) An empirical Bayes approach to inferring large-scale gene association networks. Bioinformatics 21: 754–764PubMedCrossRefGoogle Scholar
  36. 36.
    Schäfer J, Strimmer K (2005) Learning large-scale graphical Gaussian models from genomic data. In: JF Mendes (ed.): Science of Complex Networks: from Biology to the Internet and WWW (CNET 2004), The American Institute of Physics, USAGoogle Scholar
  37. 37.
    Bollobas B (1985) Random Graphs. Academic Press Inc (London) Ltd, UKGoogle Scholar
  38. 38.
    Dorogovtsev SN, Mendes JFF (2003) Evolution of Networks: From Biological Nets to the Internet and WWW. Oxford University Press, UKGoogle Scholar
  39. 39.
    Newman MEJ (2003) The structure and function of complex networks. SIAM Review 45: 167–256CrossRefGoogle Scholar
  40. 40.
    Alm E, Arkin AP (2003) Biological networks. Curr Opin Struct Biol 13: 193–202PubMedCrossRefGoogle Scholar
  41. 41.
    May RM, Lloyd AL (2001) Infection dynamics on scale-free networks. Phys Rev E Stat Nonlin Soft Matter Phys 64: 066112PubMedGoogle Scholar
  42. 42.
    Gagneur J, Krause R, Bouwmeester T, Casari G (2004) Modular decomposition of protein-protein interaction networks. Genome Biol 5: R57PubMedCrossRefGoogle Scholar
  43. 43.
    Hallinan J (2004) Gene duplication and hierarchical modularity in intracellular interaction networks. Biosystems 74: 51–62PubMedCrossRefGoogle Scholar
  44. 44.
    Pereira-Leal JB, Enright AJ, Ouzounis CA (2004) Detection of functional modules from protein interaction networks. Proteins 54: 49–57PubMedCrossRefGoogle Scholar
  45. 45.
    Agrafioti I, Swire J, Abbott J, Huntley D, Butcher S, Stumpf MP (2005) Comparative analysis of the Saccharomyces cerevisiae and Caenorhabditis elegans protein interaction networks. BMC Evol Biol 5: 23PubMedCrossRefGoogle Scholar
  46. 46.
    Mazurie A, Bottani S, Vergassola M (2005) An evolutionary and functional assessment of regulatory network motifs. Genome Biol 6: R35PubMedCrossRefGoogle Scholar
  47. 47.
    Gavin AC, Bosche M, Krause R, Grandi P, Marzioch M, Bauer A, Schultz J, Rick JM, Michon AM, Cruciat CM et al (2002) Functional organization of the yeast proteome by systematic analysis of protein complexes. Nature 415: 141–147PubMedCrossRefGoogle Scholar
  48. 48.
    Ho Y, Gruhler A, Heilbut A, Bader GD, Moore L, Adams SL, Millar A, Taylor P, Bennett K, Boutilier K et al (2002) Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry. Nature 415: 180–183PubMedCrossRefGoogle Scholar
  49. 49.
    Ito T, Chiba T, Ozawa R, Yoshida M, Hattori M, Sakaki Y (2001) A comprehensive two-hybrid analysis to explore the yeast protein interactome. Proc Natl Acad Sci USA 98: 4569–4574PubMedCrossRefGoogle Scholar
  50. 50.
    Giot L, Bader JS, Brouwer C, Chaudhuri A, Kuang B, Li Y, Hao YL, Ooi CE, Godwin B, Vitols E et al (2003) A protein interaction map of Drosophila melanogaster. Science 302: 1727–1736PubMedCrossRefGoogle Scholar
  51. 51.
    Li S, Armstrong CM, Bertin N, Ge H, Milstein S, Boxem M, Vidalain PO, Han JD, Chesneau A, Hao T et al (2004) A map of the interactome network of the metazoan C. elegans. Science 303: 540–543PubMedCrossRefGoogle Scholar
  52. 52.
    Rual JF, Venkatesan K, Hao T, Hirozane-Kishikawa T, Dricot A, Li N, Berriz GF, Gibbons FD, Dreze M, Ayivi-Guedehoussou N et al (2005) Towards a proteome-scale map of the human protein-protein interaction network. Nature 437: 1173–1178PubMedCrossRefGoogle Scholar
  53. 53.
    Stelzl U, Worm U, Lalowski M, Haenig C, Brembeck FH, Goehler H, Stroedicke M, Zenkner M, Schoenherr A, Koeppen S et al (2005) A human protein-protein interaction network: a resource for annotating the proteome. Cell 122: 957–968PubMedCrossRefGoogle Scholar
  54. 54.
    Fribourg S, Romier C, Werten S, Gangloff YG, Poterszman A, Moras D (2001) Dissecting the interaction network of multiprotein complexes by pairwise coexpression of subunits in E. coli. J Mol Biol 306: 363–373PubMedCrossRefGoogle Scholar
  55. 55.
    LaCount DJ, Vignali M, Chettier R, Phansalkar A, Bell R, Hesselberth JR, Schoenfeld LW, Ota I, Sahasrabudhe S, Kurschner C et al (2005) A protein interaction network of the malaria parasite Plasmodium falciparum. Nature 438: 103–107PubMedCrossRefGoogle Scholar
  56. 56.
    Bader JS, Chaudhuri A, Rothberg JM, Chant J (2004) Gaining confidence in high-throughput protein interaction networks. Nat Biotechnol 22: 78–85PubMedCrossRefGoogle Scholar
  57. 57.
    von Mering C, Krause R, Snel B, Cornell M, Oliver SG, Fields S, Bork P (2002) Comparative assessment of large-scale data sets of protein-protein interactions. Nature 417: 399–403CrossRefGoogle Scholar
  58. 58.
    Shen-Orr SS, Milo R, Mangan S, Alon U (2002) Network motifs in the transcriptional regulation network of Escherichia coli. Nat Genet 31: 64–68PubMedCrossRefGoogle Scholar
  59. 59.
    Qiu P (2003) Recent advances in computational promoter analysis in understanding the transcriptional regulatory network. Biochem Biophys Res Commun 309: 495–501PubMedCrossRefGoogle Scholar
  60. 60.
    Boffelli D, Nobrega MA, Rubin EM (2004) Comparative genomics at the vertebrate extremes. Nat Rev Genet 5: 456–465PubMedCrossRefGoogle Scholar
  61. 61.
    Almaas E, Kovacs B, Vicsek T, Oltvai ZN, Barabasi AL (2004) Global organization of metabolic fluxes in the bacterium Escherichia coli. Nature 427: 839–843PubMedCrossRefGoogle Scholar
  62. 62.
    Fell DA, Wagner A (2000) The small world of metabolism. Nat Biotechnol 18: 1121–1122PubMedCrossRefGoogle Scholar
  63. 63.
    Barabasi AL, Albert R (1999) Emergence of scaling in random networks. Science 286: 509–512PubMedCrossRefGoogle Scholar
  64. 64.
    Berg J, Lassig M, Wagner A (2004) Structure and evolution of protein interaction networks: a statistical model for link dynamics and gene duplications. BMC Evol Biol 4: 51PubMedCrossRefGoogle Scholar
  65. 65.
    Burda Z, Correia JD, Krzywicki A (2001) Statistical ensemble of scale-free random graphs. Phys Rev E Stat Nonlin Soft Matter Phys 64: 046118PubMedGoogle Scholar
  66. 66.
    Stumpf MP, Wiuf C, May RM (2005) Subnets of scale-free networks are not scale-free: sampling properties of networks. Proc Natl Acad Sci USA 102: 4221–4224PubMedCrossRefGoogle Scholar
  67. 67.
    Stumpf MPH, Ingram PJ, Nouvel I, Wiuf C (2005) Statistical model selection methods applied to biological networks. Proc Comp Systems Biol 3Google Scholar
  68. 68.
    Stewart GR, Patel J, Robertson BD, Rae A, Young DB (2005) Mycobacterial mutants with defective control of phagosomal acidification. PLoS Pathog 1: 269–278PubMedCrossRefGoogle Scholar
  69. 69.
    Tong AH, Drees B, Nardelli G, Bader GD, Brannetti B, Castagnoli L, Evangelista M, Ferracuti S, Nelson B, Paoluzi S et al (2002) A combined experimental and computational strategy to define protein interaction networks for peptide recognition modules. Science 295: 321–324PubMedCrossRefGoogle Scholar
  70. 70.
    Tong AH, Evangelista M, Parsons AB, Xu H, Bader GD, Page N, Robinson M, Raghibizadeh S, Hogue CW, Bussey H et al (2001) Systematic genetic analysis with ordered arrays of yeast deletion mutants. Science 294: 2364–2368PubMedCrossRefGoogle Scholar
  71. 71.
    Uetz P, Dong YA, Zeretzke C, Atzler C, Baiker A, Berger B, Rajagopala SV, Roupelieva M, Rose D, Fossum E et al (2006) Herpesviral protein networks and their interaction with the human proteome. Science 311: 239–242PubMedCrossRefGoogle Scholar
  72. 72.
    Perkins SL (2001) Phylogeography of Caribbean lizard malaria: tracing the history of vector-borne parasites. J Evol Biol 14: 34–45CrossRefGoogle Scholar

Copyright information

© Birkhäuser Verlag 2007

Authors and Affiliations

  • Michael P. Stumpf
    • 1
  • Brian D. Robertson
    • 2
  • Ken Duncan
    • 2
  • Douglas B. Young
    • 2
  1. 1.Centre for Integrative Systems Biology at Imperial College (CISBIC), Division of Molecular BiosciencesImperial College LondonLondonUK
  2. 2.Centre for Integrative Systems Biology at Imperial College (CISBIC), Department of Molecular Microbiology and InfectionImperial College LondonLondonUK

Personalised recommendations