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Structural Knockout Cascades in Metabolic Networks

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A Network-Based Approach to Cell Metabolism

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Abstract

This chapter presents the analysis of the response of metabolic networks of model organisms to different forms of structural stress, including removals of individual and pairs of reactions and knockouts of single or co-expressed genes.

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Notes

  1. 1.

    Reactions altered but not removed are reversible reactions that become directed by effect of the cascade.

References

  1. Albert R, Barabási AL (2002) Statistical mechanics of complex networks. Rev Mod Phys 74:47–97

    Article  Google Scholar 

  2. Dorogovtsev SN, Goltsev AV, Mendes JFF (2008) Critical phenomena in complex networks. Rev Mod Phys 80:1275–1335

    Article  Google Scholar 

  3. Barrat A, Barthélemy D, Vespignani A (2008) Dynamical processes on complex networks. Cambridge University Press, Cambridge

    Google Scholar 

  4. Cohen R, Erez K, ben Avraham D, Havlin S (2000) Resilience of the internet to random breakdown. Phys Rev Lett 85:4626

    Article  CAS  Google Scholar 

  5. Albert R, Jeong H, Barabási AL (2000) Error and attack tolerance of complex networks. Nature 406:378–382

    Article  CAS  Google Scholar 

  6. Watts DJ (2002) A simple model of global cascades on random networks. Proc Natl Acad Sci USA 99:5766–5771

    Article  CAS  Google Scholar 

  7. Moreno Y, Gómez JB, Pacheco AF (2002) Instability of scale-free networks under nodebreaking avalanches. Europhys. Lett. 58:630–636

    Article  CAS  Google Scholar 

  8. Motter AE (2002) Cascade-based attacks on complex networks. Phys Rev E 66:065102(R)

    Article  Google Scholar 

  9. Buldyrev SV, Parshani R, Paul G, Stanley HE, Havlin S (2010) Catastrophic cascade of failures in interdependent networks. Nature 464:1025–1028

    Article  CAS  Google Scholar 

  10. Barabási AL, Oltvai ZN (2004) Network biology: understanding the cells functional organization. Nat Rev Genet 5:101–113

    Article  Google Scholar 

  11. Szalay MS, Kovacs IA, Korcsmaros T, Bode C, Csermely P (2007) Stress-induced rearrangements of cellular networks: consequences for protection and drug design. FEBS Lett 581:3675–3680

    Article  CAS  Google Scholar 

  12. Motter AE, Gulbahce N, Almaas E, Barabási AL (2008) Predicting synthetic rescues in metabolic networks. Mol Syst Biol 4:168

    Article  Google Scholar 

  13. Smart AG, Amaral LAN, Ottino J (2008) Cascading failure and robustness in metabolic networks. Proc Natl Acad Sci USA 105:13223–13228

    Article  CAS  Google Scholar 

  14. Edwards JS, Palsson BØ (2000) Robustness analysis of the Escherichia coli metabolic network. Biotechnol. Prog. 16:927–939

    Article  CAS  Google Scholar 

  15. Segrè D, Church GM (2002) Analysis of optimality in natural and perturbed metabolic networks. Proc Natl Acad Sci USA 99:15112–15117

    Article  Google Scholar 

  16. Folger O, Jerby L, Frezza C, Gottlieb E, Ruppin E, Shlomi T (2011) Predicting selective drug targets in cancer through metabolic networks. Mol Syst Biol 7:501

    Article  Google Scholar 

  17. Yus E et al (2009) Impact of genome reduction on bacterial metabolism and its regulation. Science 326:1263–1268

    Article  CAS  Google Scholar 

  18. Güell O, Sagués F, Serrano MÁ (2012) Predicting effects of structural stress in a genome-reduced model bacterial metabolism. Sci Rep 2:621

    Google Scholar 

  19. Güell O, Sagués F, Basler G, Nikoloski Z, Serrano MÁ (2012) Assessing the significance of knockout cascades in metabolic networks. J Comp Int Sci 3(1–2):45–53

    Google Scholar 

  20. Güell O, Sagués F, Serrano MÁ (2014) Assessing the significance and predicting the effects of knockout cascades in metabolic networks. In: Extended Abstracts Spring 2013. Springer, pp 39–44. ISBN 978-3-319-08137-3

    Google Scholar 

  21. Smirnov NV (1948) Tables for estimating the goodness of fit of empirical distributions. Ann Math Stat 19:279

    Article  Google Scholar 

  22. Spearman C (1904) The proof and measurement of association between two things. Am J Psychol 15:72–101

    Article  Google Scholar 

  23. Güell M et al (2009) Transcriptome complexity in a genome-reduced bacterium. Science 326:1268–1271

    Article  Google Scholar 

  24. Güell O, Serrano MÁ, Sagués F (2014) Environmental dependence of the activity and essentiality of reactions in the metabolism of Escherichia coli. In: Engineering of chemical complexity II. World Scientific, pp 39–56. ISBN 978-981-4616-12-6

    Google Scholar 

  25. Glass JI et al (2006) Essential genes of a minimal bacterium. Proc Natl Acad Sci USA 103:425–430

    Article  CAS  Google Scholar 

  26. Wodke JAH et al (2013) Dissecting the energy metabolism in Mycoplasma pneumoniae through genome-scale metabolic modeling. Mol Syst Biol 9:653

    Article  Google Scholar 

  27. Borate BR et al (2009) Comparison of threshold selection matrices for microarray gene co-expression matrices. BMC Res Notes 2:240

    Article  Google Scholar 

  28. Zhang B, Horvath S (2005) A general framework for weighted gene co-expression network analysis. Stat Appl Genet Mol Biol 4:1544–6115

    Article  Google Scholar 

  29. Khanin R, Wit E (2005) Construction of malaria gene expression network using partial correlations. In: Methods of microarray data analysis V, pp 1544–6115

    Google Scholar 

  30. Basler G, Ebenhöh O, Selbig J, Nikoloski Z (2011) Mass-balanced randomization of metabolic networks. Bioinformatics 27:1397–1403

    Article  CAS  Google Scholar 

  31. Basler G, Grimbs S, Ebenhöh O, Selbig J, Nikoloski Z (2012) Evolutionary significance of metabolic network properties. J R Soc Interface 9:1168–1176

    Article  CAS  Google Scholar 

  32. DeRisi JL, Iyer V, Brown PO (1997) Exploring the metabolic and genetic control of gene expression on a genomic scale. Science 278(5338):680–686

    Article  CAS  Google Scholar 

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Authors and Affiliations

  1. Department of Materials Science and Physical Chemistry, University of Barcelona, Barcelona, Spain

    Oriol Güell

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  1. Oriol Güell
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Correspondence to Oriol Güell .

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Güell, O. (2017). Structural Knockout Cascades in Metabolic Networks. In: A Network-Based Approach to Cell Metabolism. Springer Theses. Springer, Cham. https://doi.org/10.1007/978-3-319-64000-6_3

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