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Modeling of Signaling Pathways Based on Petri nets

This symposium explores combining symbolic and numerical methods to model signaling pathways, focusing on Petri nets, pi-calculus, and differential equations. Examples include Lambda phage genetic switch feedback mechanism and information transmission in cells. Benefits include structural analysis and parameter estimation for pathway characterization. Collaboration with Yamaguchi Univ. experts enhances experimental data utilization. Sponsored by Ministry of Education Research Grant.

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Modeling of Signaling Pathways Based on Petri nets

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  1. International Symposium on Symbolic Systems Biology (ISSSB’11) Shonan Village Center 13-17 November, 2011 Modeling of Signaling Pathways Based on Petri nets Hiroshi Matsuno Graduate School of Science and Engineering Yamaguchi University

  2. July 4-9, 2004

  3. Feb 22-27, 2009 Petri nets process algebra π-calculus timed automata probabilistic automata finite state linear model differential equations rule based model Boolean model

  4. Merits of NII Shonan Meeting 1… 2… 3 Isolated “paradise” with no distractions

  5. Petri nets • Symbolic representation of systems in graphical manner . . . In the aims of this meeting … A secondary aim is to identify ways purely symbolic methods have been or could be combined with numerical techniques and applied to emerging problems in experimental and synthetic biology. . . .

  6. Hybrid Petri Net

  7. tank flow off flow on lever Example of hybrid Petri net

  8. Lambda phage genetic switch feedback mechanism

  9. Lambda phage genetic switch feedback mechanism

  10. Simulation on Cell Illustrator

  11. Information transmission from cell membrane to cell nuclei by the cascade of enzymes To control proliferation, differentiation, and life of cells Signaling pathways stimulus cell membrane enzyme 1 enzyme 2 ・・・ cell nuclei enzyme n

  12. signaling pathway components

  13. a part of signaling pathway Petri net model . . . inactive MEK4,7 . . . MEK4,7 MEK4,7 inactive JNK Activation Transduction Component (ATC) MEK4,7 JNK JNK inactive Elk-1 JNK A set of reactions influenced by an enzyme Elk-1 Elk-1 Elk-1 . . . . . .

  14. Petri net model . . . inactive MEK4,7 . . . MEK4,7 MEK4,7 inactive JNK MEK4,7 JNK JNK inactive Elk-1 JNK Elk-1 Elk-1 Elk-1 . . . . . . ATC = Elementary T-invariant Signaling Pathway TERM Petri net TERM A part of signaling pathway Elementary T-invariant ATC

  15. Algorithm to find ATC C. Li, S. Suzuki, Q.-W.Ge, M. Nakata, H. Matsuno, S. Miyano, Structural modeling and analysis of signaling pathways based on Petri nets, J. Bioinfo. Comput. Biol. 4(5), pp.1119-1140, 2006..

  16. Ras-MAPK pathway PLC pathway Adenylyl cyclase pathway An Example of signaling pathway modeling outside of a cell inside of a cell G protein signaling pathways

  17. Ras-MAPK pathway G protein signaling pathway Adenylyl cyclase pathway Petri net model of signaling pathway PLC pathway Petri net model of G protein signaling pathway

  18. Result of the decomposition signal flow representation  timed Petri net

  19. PLC pathway N 1 N N 3 4 N 2 N N N N N 6 8 11 12 13 N 9 N N N 5 7 10 N N 16 17 N N 14 15 Easy to acquire the characteristics on the structure of signaling pathways Ras-MAPK pathway ATC representation of pathway Subnet N9 (MEK activation by Raf-1)is an important reaction in the pathway. More than one pathways are working for producing the same gene product. Adenylyl cyclase pathway

  20. careful three structures of Petri net tI tO tI tO tO tI tI m 1 1 n 2 2 1 ･･･ β α α α α α β β α β m 1 2 n 1 m 2 1 n 1 p t1 β1 ･･･ p1 ･･･ α2 t2 β2 p2 s1 s2 sn α3-1 α3-2 p4 t3 synchronize β3 β5 p3 tO α5 t5 α4 conflict t4 acyclic can be used for parameter estimation

  21. Conclusion and future work • I am very happy to be here, • --- Dagstuhl style meeting in Asia. • Delay time determination of transitions for • representing signal flow dynamics based on • the structure of the Petri net model and • experimentally obtained data. • Qualitative characterization of signaling • pathways for biological and medical applications

  22. Collaborators in Yamaguchi Univ. • Petri net modeling • Qi-Wei Ge • Yuki Murakami • Experimental data of signaling components • using cell array system • Tomoko Furuya This research is partially supported by the Ministry of Education, Science, Sports and Culture, Grant-in-Aid for Scientific Research (B).

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