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Background  Model checking approaches were applied to biological pathway validations around 2003. Recently, Fisher  et al . have proved the importance of model checking approach by inferring new regulation of signaling crosstalk in  C. elegans  and confirming the regulation with biological experiments. They took a discrete and state-based approach to explore all possible states of the system underlying vulval precursor cell (VPC) fate specification for desired properties. However, since both discrete and continuous features appear to be an indispensable part of biological processes, it is more appropriate to use quantitative models to capture the dynamics of biological systems. Our key motivation of this paper is to establish a quantitative methodology to model and analyze  in silico  models incorporating the use of model checking approach.    Results  A novel method of modeling and simulating biological systems with the use of model checking approach is proposed based on hybrid functional Petri net with extension (HFPNe) as the framework dealing with both discrete and continuous events. Firstly, we construct a quantitative VPC fate model with 1761 components by using HFPNe. Secondly, we employ two major biological fate determination rules – Rule I and Rule II – to VPC fate model. We then conduct 10,000 simulations for each of 48 sets of different genotypes, investigate variations of cell fate patterns under each genotype, and validate the two rules by comparing three simulation targets consisting of fate patterns obtained from  in silico  and  in vivo  experiments. In particular, an evaluation was successfully done by using our VPC fate model to investigate one target derived from biological experiments involving hybrid lineage observations. However, the understandings of hybrid lineages are hard to make on a discrete model because the hybrid lineage occurs when the system comes close to certain thresholds as discussed by Sternberg and Horvitz in 1986. Our simulation results suggest that: Rule I that cannot be applied with qualitative based model checking, is more reasonable than Rule II owing to the high coverage of predicted fate patterns (except for the genotype of  lin-15ko; lin-12ko  double mutants). More insights are also suggested.    Conclusion  The quantitative simulation-based model checking approach is a useful means to provide us valuable biological insights and better understandings of biological systems and observation data that may be hard to capture with the qualitative one.

bmc systems biology

Simulation-based model checking approach to cell fate specification during Caenorhabditis elegans vulval development by hybrid functional Petri net with extension