1. 1 A Case for Using Signal Transition Graphs for Analysing and Refining Genetic Networks Richard Banks, Victor Khomenko and Jason Steggles School of Computing Science, Newcastle University, UK

2. 2 Overview Modelling genetic regulatory networks using Boolean networks (BNs). Problems with BN approach. Asynchronous circuit design techniques. A refinement approach based on Signal Transition Graphs (STGs). Case study on lysis-lysogeny switch in Lambda phage. Conclusions and future work.

3. Modelling Genetic Networks Genetic regulatory networks (GRNs) are complex control structures mediating cell function. Require practical modelling and analysis techniques. Kinetic parameters lacking for construction of meaningful quantitative models. Qualitative approaches often used for gaining initial insights. 3 Kobiler et. al. 2005

4. 4 Boolean Networks Qualitative model: Boolean networks (BNs). Regulatory entities abstracted to binary switches. Behaviour of each switch given by Boolean function over inputs. Synchronous or asynchronous interpretation. BNs  circuits. a b c [a] [b] [c] 0 0 0 0 0 1 0 0 1 0 1 0 1 0 1 0 1 1 1 0 1 1 0 0 0 0 0 1 0 1 0 1 0 1 1 0 1 0 0 1 1 1 1 1 0 a bc Circuit equations [a] = b [b] = ac [c] = a

5. 5 Aim Synchronous BN interpretation arguably unrealistic. Asynchronous BNs more realistic, but capture too rich, non-deterministic behaviour  unrealisable in practice. Require realistic qualitative modelling approach with appropriate analysis techniques and tools. Solution: Use asynchronous approach. Remove unrealisable behaviour using techniques from asynchronous circuit design. Based on speed-independent (SI) circuits functions correctly regardless of gate delays.

6. Asynchronous Circuit Design Signal transition graphs (STGs) are specification language based on Petri nets  well founded techniques/tools. Regulatory entities  Boolean variables  signals. Input, output and internal signals (output + internal = local). Transitions model signal change, e.g. a+ from a=0 to a=1. 6 C a b c Environment a+b+ c+ a-b- c- STG

7. Asynchronous Circuit Design Signal transition graphs (STGs) are specification language based on Petri nets  well founded techniques/tools. Regulatory entities  Boolean variables  signals. Input, output and internal signals (output + internal = local). Transitions model signal change, e.g. a+ from a=0 to a=1. 7 C a b c Environment a+b+ c+ a-b- c- STG a = 1

8. Asynchronous Circuit Design Signal transition graphs (STGs) are specification language based on Petri nets  well founded techniques/tools. Regulatory entities  Boolean variables  signals. Input, output and internal signals (output + internal = local). Transitions model signal change, e.g. a+ from a=0 to a=1. 8 C a b c Environment a+b+ c+ a-b- c- STG a = 1 b = 1

9. Asynchronous Circuit Design Signal transition graphs (STGs) are specification language based on Petri nets  well founded techniques/tools. Regulatory entities  Boolean variables  signals. Input, output and internal signals (output + internal = local). Transitions model signal change, e.g. a+ from a=0 to a=1. 9 C a b c Environment a+b+ c+ a-b- c- STG a = 1 b = 1 c = 1

10. Asynchronous Circuit Design Signal transition graphs (STGs) are specification language based on Petri nets  well founded techniques/tools. Regulatory entities  Boolean variables  signals. Input, output and internal signals (output + internal = local). Transitions model signal change, e.g. a+ from a=0 to a=1. 10 C a b c Environment a+b+ c+ a-b- c- STG a = 1 b = 1 c = 1 a = 0

11. Asynchronous Circuit Design Signal transition graphs (STGs) are specification language based on Petri nets  well founded techniques/tools. Regulatory entities  Boolean variables  signals. Input, output and internal signals (output + internal = local). Transitions model signal change, e.g. a+ from a=0 to a=1. 11 C a b c Environment a+b+ c+ a-b- c- STG a = 1 b = 1 c = 1 a = 0 b = 0

12. Asynchronous Circuit Design Signal transition graphs (STGs) are specification language based on Petri nets  well founded techniques/tools. Regulatory entities  Boolean variables  signals. Input, output and internal signals (output + internal = local). Transitions model signal change, e.g. a+ from a=0 to a=1. 12 C a b c Environment a+b+ c+ a-b- c- STG a = 1 b = 1 c = 1 a = 0 b = 0 c = 0

13. Asynchronous Circuit Design Signal transition graphs (STGs) are specification language based on Petri nets  well founded techniques/tools. Regulatory entities  Boolean variables  signals. Input, output and internal signals (output + internal = local). Transitions model signal change, e.g. a+ from a=0 to a=1. 13 C a b c Environment a+b+ c+ a-b- c- STG Capture contract between circuit and environment a = 1 b = 1 c = 1 a = 0 b = 0 c = 0

14. 14 Relationship between BNs and STGs Circuit equation (BN) [c] = ab + c(a + b) BN  STG straightforward. Equation loses environmental information  STGs more useful for analysis a+b+ c+ a-b- c- a+ a- b- b+ c-c+ Models most general environment!

15. 15 Speed-Independent (SI) Circuits Function correctly independent of gate delay. SI requires output persistency (OP): – no choices involving local transitions. OP violation  non-determinism. Choices between input transitions models non-deterministic decision in the environment – OK. a+b+ c+ a-b- c-

16. 16 Speed-Independent (SI) Circuits Function correctly independent of gate delay. SI requires output persistency (OP): – no choices involving local transitions. OP violation  non-determinism. Choices between input transitions models non-deterministic decision in the environment – OK. Speed-independent (SI) in specified environment a+b+ c+ a-b- c-

17. 17 Speed-Independent (SI) Circuits Function correctly independent of gate delay. SI requires output persistency (OP): – no choices involving local transitions. OP violation  non-determinism. Choices between input transitions models non-deterministic decision in the environment – OK. a+b+ c+ a-b- c- a- Add extra transition a-

18. 18 Speed-Independent (SI) Circuits Function correctly independent of gate delay. SI requires output persistency (OP): – no choices involving local transitions. OP violation  non-determinism. Choices between input transitions models non-deterministic decision in the environment – OK. Not SI: c+ disabled by a- a+b+ c+ a-b- c- a-

19. 19 Speed-Independent (SI) Circuits Function correctly independent of gate delay. SI requires output persistency (OP): – no choices involving local transitions. OP violation  non-determinism. Choices between input transitions models non-deterministic decision in the environment – OK. Exception: choices involving only local transitions can be left in model: – should be documented; – if represent stochastic phenomenon, can be handled in SI manner with arbiters. a+b+ c+ a-b- c- a-

20. 20 Approach Overview BNSTGSI Circuit Identify OP violations (auto) User assumptions (priorities) (auto) PN analysis tools STG analysis tools

21. 21 Refinement Approach a+a- b- b+ c-c+ [c] = ab + c(a + b)

22. 22 Refinement Approach Identify all OP violations: c+ disabled by a- c+ disabled by b- c- disabled by a+ c- disabled by b+ a+a- b- b+ c-c+

23. 23 Refinement Approach User adds priorities: slow environment relative reaction rates Identify all OP violations: c+ disabled by a- c+ disabled by b- c- disabled by a+ c- disabled by b+ a+a- b- b+ c-c+

24. 24 Refinement Approach Identify all OP violations: c+ disabled by a- c+ disabled by b- c- disabled by a+ c- disabled by b+ User adds priorities: slow environment relative reaction rates a+a- b- b+ c-c+

25. 25 Refinement Approach E.g.assume c+ faster than a- a+a- b- b+ c-c+ Identify all OP violations: c+ disabled by a- c+ disabled by b- c- disabled by a+ c- disabled by b+ User adds priorities: slow environment relative reaction rates

26. 26 Refinement Approach Prioritise c+ over a- when both enabled by capturing when a- can fire but c+ cannot. a+a- b- b+ c-c+ Identify all OP violations: c+ disabled by a- c+ disabled by b- c- disabled by a+ c- disabled by b+ User adds priorities: slow environment relative reaction rates E.g.assume c+ faster than a-

27. 27 Refinement Approach Prioritise c+ over a- when both enabled by capturing when a- can fire but c+ cannot. Identify all OP violations: c+ disabled by a- c+ disabled by b- c- disabled by a+ c- disabled by b+ User adds priorities: slow environment relative reaction rates E.g.assume c+ faster than a- a+a- b- b+ c-c+

28. 28 All OP Violations Resolved Refine OP violations (automated) Priorities assumed: c+ faster than a-, c+ faster than b- c- faster than a+, c- faster than b+

29. 29 Resynthesized STG Optimised using circuit synthesis tool Petrify. STG is SI and, surprisingly, contains more behaviour than original, i.e. can cope with more demanding environment than one intended. a- a+b+ b- b+/1a+/1 c- c+ a+/2 a-/1 b-/1 b+/2 a-/2 b-/2

30. 30 Case Study: Lysis-Lysogeny Switch in Lambda Phage Inputs: CI (repressor) Internal: CII (trans. activator), Int (integrase), Xis (excisionase) Outputs: Intg (integrated) [CII] = CI [Int] = CII + CI [Xis] = CI [Intg] = Intg Int + Intg(Int + Xis) Circuit Ptashne, 2004 Thomas et. al.,1990

31. 31 OP Violations in Lambda Phage

32. 32 OP Violations in Lambda Phage OP violations: Xis+ disabled by CI+ Xis− disabled by CI− Int+ disabled by CI + Int− disabled by CI − CII+ disabled by CI+ CII − disabled by CI− Intg− disabled by Int− Intg− disabled by Xis− Intg+ disabled by Int− Int+/1 disabled by CII−

33. 33 OP Violations in Lambda Phage Environment OP violations: Xis+ disabled by CI+ Xis− disabled by CI− Int+ disabled by CI + Int− disabled by CI − CII+ disabled by CI+ CII − disabled by CI− Intg− disabled by Int− Intg− disabled by Xis− Intg+ disabled by Int− Int+/1 disabled by CII−

34. 34 OP Violations in Lambda Phage Environment OP violations: Xis+ disabled by CI+ Xis− disabled by CI− Int+ disabled by CI + Int− disabled by CI − CII+ disabled by CI+ CII − disabled by CI− Intg− disabled by Int− Intg− disabled by Xis− Intg+ disabled by Int− Int+/1 disabled by CII− Resolve by assuming slow environment

35. 35 OP Violations in Lambda Phage Environment OP violations: Xis+ disabled by CI+ Xis− disabled by CI− Int+ disabled by CI + Int− disabled by CI − CII+ disabled by CI+ CII − disabled by CI− Intg− disabled by Int− Intg− disabled by Xis− Intg+ disabled by Int− Int+/1 disabled by CII− Resolve by assuming slow environment

36. 36 Final SI STG Much less cluttered. Remaining OP violations: Intg− disabled by Int− Intg− disabled by Xis− Intg+ disabled by Int− Heart of lysis-lysogeny switch (stochastic) Can now be analysed further with PN and STG tools.

37. 37 Conclusions BN  STG  SI STG. Framework for obtaining realistic models of GRNs using notion of SI circuits: – refine unrealisable behaviour based on user knowledge; – identifying and documenting missing information. STG construction and refinement automated. Re-use existing PN and STG tools/techniques for analysis. Not all OP violations may always be resolved  document. Future work: – further case studies; – generalise approach to multi-valued networks; – investigate application to synthetic biology.

38. 38 Thanks A Case for Using Signal Transition Graphs for Analysing and Refining Genetic Network Richard Banks, Victor Khomenko and Jason Steggles http://bioinf.ncl.ac.uk/gnapn/