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Modeling Rho GTPase Dynamics Using Boolean Logic

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Book cover Rho GTPases

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1821))

Abstract

Rho GTPases such as the canonical Rac1 and RhoA are embedded within complex networks requiring the precise spatiotemporal balance of GEFs, GAPs, upstream regulators, growth factors, and downstream effectors. A modeling approach based on Boolean logical networks is becoming an increasingly relied-upon tool to harness this complexity and elucidate further details regarding Rho GTPase signaling. In this methods chapter we describe how to initially create appropriately sized networks based on literature evidence; formalize these networks with reactions based on Boolean logical operators; implement the network into appropriate simulation software (CellNetAnalyzer); and finally perform simulations and make novel, testable predictions via in silico knockouts. Given this predictive power, the Boolean approach may ultimately help to highlight potential future avenues of experimental research.

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References

  1. Hetmanski JHR, Zindy E, Schwartz JM, Caswell PT (2016) A MAPK-driven feedback loop suppresses Rac activity to promote RhoA-driven cancer cell invasion. PLoS Comput Biol 12:e1004909

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Kim TH, Monsefi N, Song JH, von Kriegsheim A, Vandamme D, Pertz O, Kholodenko BN, Kolch W, Cho KH (2015) Network-based identification of feedback modules that control RhoA activity and cell migration. J Mol Cell Biol 7:242–252

    Article  PubMed  Google Scholar 

  3. Samaga R, Saez-Rodriguez J, Alexopoulos LG, Sorger PK, Klamt S (2009) The logic of EGFR/ErbB signaling: theoretical properties and analysis of high-throughput data. PLoS Comput Biol 5:e1000438

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Byrne KM, Monsefi N, Dawson JC, Degasperi A, Bukowski-Will JC, Volinsky N, Dobrynski M, Birtwistle MR, Tsyganov MA, Kiyatkin A, Kida K, Finch AJ, Carragher NO, Kolch W, Nguyen LK, von Kriegsheim A, Kholodenko BN (2016) Bistability in the Rac1, PAK, and RhoA signaling network drives actin cytoskeleton dynamics and cell motility switches. Cell Syst 2:38–48

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Albert I, Thakar J, Li S, Zhang R, Albert R (2008) Boolean network simulations for life scientists. Source Code Biol Med 3:16

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Hetmanski JHR, Schwartz JM, Caswell PT (2016) Rationalizing Rac1 and RhoA GTPase signaling: a mathematical approach. Small GTPases 1248:1–6

    Google Scholar 

  7. Hetmanski JHR, Schwartz JM, Caswell PT (2016) Modelling GTPase dynamics to understand RhoA-driven cancer cell invasion. Biochem Soc Trans 44:1695–1700

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Klamt S, Saez-Rodriguez J, Gilles E (2007) Structural and functional analysis of cellular networks with CellNetAnalyzer. BMC Syst Biol 1:2

    Article  PubMed  PubMed Central  Google Scholar 

  9. Oda K, Matsuoka Y, Funahashi A, Kitano H (2005) A comprehensive pathway map of epidermal growth factor receptor signaling. Mol Syst Biol 1:2005.0010

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Kandasamy K, Mohan S, Raju R, Keerthikumar S, Kumar GS, Venugopal AK, Telikicherla D, Navarro JD, Mathivanan S, Pecquet C, Gollapudi SK, Tattikota SG, Mohan S, Padhukasahasram H, Subbannayya Y, Goel R, Jacob HK, Zhong J, Sekhar R, Nanjappa V, Balakrishnan L, Subbaiah R, Ramachandra YL, Rahiman BA, Prasad TS, Lin JX, Houtman JC, Desiderio S, Renauld JC, Constantinescu SN, Ohara O, Hirano T, Kubo M, Singh S, Khatri P, Draghici S, Bader GD, Sander C, Leonard WJ, Pandey A (2010) NetPath: a public resource of curated signal transduction pathways. Genome Biol 11:R3

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Mi H, Thomas P (2009) PANTHER pathway: an ontology-based pathway database coupled with data analysis tools. Methods Mol Biol 563:123–140

    Article  CAS  PubMed  Google Scholar 

  12. Krumsiek J, Pölsterl S, Wittmann DM, Theis FJ (2010) Odefy—From discrete to continuous models. BMC Bioinformatics 11:233

    Article  PubMed  PubMed Central  Google Scholar 

  13. Sible JC, Tyson JJ (2007) Mathematical modeling as a tool for investigating cell cycle control networks. Methods 41:238–247

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Szklarczyk D, Franceschini A, Wyder S, Forslund K, Heller D, Huerta-Cepas J, Simonovic M, Roth A, Santos A, Tsafou KP, Kuhn M, Bork P, Jensen LJ, von Mering C (2015) STRING v10: protein-protein interaction networks, integrated over the tree of life. Nucleic Acids Res 43:D447–D452

    Article  CAS  PubMed  Google Scholar 

  15. Scita G, Tenca P, Areces LB, Tocchetti A, Frittoli E, Giardina G, Ponzanelli I, Sini P, Innocenti M, Di Fiore PP (2001) An effector region in Eps8 is responsible for the activation of the Rac-specific GEF activity of Sos-1 and for the proper localization of the Rac-based actin-polymerizing machine. J Cell Biol 154:1031–1044

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Singh A, Nascimento JM, Kowar S, Busch H, Boerries M (2012) Boolean approach to signalling pathway modelling in HGF-induced keratinocyte migration. Bioinformatics 28:i495–i501

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Bock M, Scharp T, Talnikar C, Klipp E (2014) BooleSim: an interactive Boolean network simulator. Bioinformatics 30:131–132

    Article  CAS  PubMed  Google Scholar 

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Correspondence to Joseph H. R. Hetmanski or Patrick T. Caswell .

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Hetmanski, J.H.R., Schwartz, JM., Caswell, P.T. (2018). Modeling Rho GTPase Dynamics Using Boolean Logic. In: Rivero, F. (eds) Rho GTPases. Methods in Molecular Biology, vol 1821. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-8612-5_3

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  • DOI: https://doi.org/10.1007/978-1-4939-8612-5_3

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-8611-8

  • Online ISBN: 978-1-4939-8612-5

  • eBook Packages: Springer Protocols

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