Qualitatively modelling and analysing genetic regulatory networks: a Petri net approach

MOTIVATION New developments in post-genomic technology now provide researchers with the data necessary to study regulatory processes in a holistic fashion at multiple levels of biological organization. One of the major challenges for the biologist is to integrate and interpret these vast data resources to gain a greater understanding of the structure and function of the molecular processes that mediate adaptive and cell cycle driven changes in gene expression. In order to achieve this biologists require new tools and techniques to allow pathway related data to be modelled and analysed as network structures, providing valuable insights which can then be validated and investigated in the laboratory. RESULTS We propose a new technique for constructing and analysing qualitative models of genetic regulatory networks based on the Petri net formalism. We take as our starting point the Boolean network approach of treating genes as binary switches and develop a new Petri net model which uses logic minimization to automate the construction of compact qualitative models. Our approach addresses the shortcomings of Boolean networks by providing access to the wide range of existing Petri net analysis techniques and by using non-determinism to cope with incomplete and inconsistent data. The ideas we present are illustrated by a case study in which the genetic regulatory network controlling sporulation in the bacterium Bacillus subtilis is modelled and analysed. AVAILABILITY The Petri net model construction tool and the data files for the B. subtilis sporulation case study are available at http://bioinf.ncl.ac.uk/gnapn.

[1]  Wolfgang Reisig,et al.  Lectures on Petri Nets I: Basic Models , 1996, Lecture Notes in Computer Science.

[2]  Anil Wipat,et al.  SARGE: a tool for creation of putative genetic networks , 2004, Bioinform..

[3]  Monika Heiner,et al.  Analysis and Simulation of Steady States in Metabolic Pathways with Petri Nets , 2001 .

[4]  James M. Bower,et al.  Computational modeling of genetic and biochemical networks , 2001 .

[5]  Sui Huang Gene expression profiling, genetic networks, and cellular states: an integrating concept for tumorigenesis and drug discovery , 1999, Journal of Molecular Medicine.

[6]  S. Kauffman Metabolic stability and epigenesis in randomly constructed genetic nets. , 1969, Journal of theoretical biology.

[7]  D. Thieffry,et al.  Modularity in development and evolution. , 2000, BioEssays : news and reviews in molecular, cellular and developmental biology.

[8]  Robert K. Brayton,et al.  Logic Minimization Algorithms for VLSI Synthesis , 1984, The Kluwer International Series in Engineering and Computer Science.

[9]  Z. Szallasi,et al.  Modeling the normal and neoplastic cell cycle with "realistic Boolean genetic networks": their application for understanding carcinogenesis and assessing therapeutic strategies. , 1998, Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing.

[10]  P J Goss,et al.  Quantitative modeling of stochastic systems in molecular biology by using stochastic Petri nets. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[11]  Denis Thieffry,et al.  Qualitative modelling of regulated metabolic pathways: application to the tryptophan biosynthesis in E.Coli , 2005, ECCB/JBI.

[12]  Ivan Bratko Qualitative Modelling , 2005 .

[13]  Satoru Miyano,et al.  Identification of Genetic Networks from a Small Number of Gene Expression Patterns Under the Boolean Network Model , 1998, Pacific Symposium on Biocomputing.

[14]  Denis Thieffry,et al.  Qualitative Modelling of Genetic Networks: From Logical Regulatory Graphs to Standard Petri Nets , 2004, ICATPN.

[15]  Victor Khomenko,et al.  Model checking based on prefixes of petri net unfoldings , 2003 .

[16]  Carlos Gershenson,et al.  Classification of Random Boolean Networks , 2002, ArXiv.

[17]  Vincent Danos,et al.  Modeling and querying biomolecular interaction networks , 2004, Theor. Comput. Sci..

[18]  V. N. Reddy,et al.  Qualitative analysis of biochemical reaction systems , 1996, Comput. Biol. Medicine.

[19]  Kenneth J. Breeding Digital Design Fundamentals , 1989 .

[20]  R. Lewis,et al.  Molecular insights into the initiation of sporulation in Gram-positive bacteria: new technologies for an old phenomenon. , 2005, FEMS microbiology reviews.

[21]  James R. Knight,et al.  A comprehensive analysis of protein–protein interactions in Saccharomyces cerevisiae , 2000, Nature.

[22]  Hannu Tenhunen,et al.  Extending systems-on-chip to the third dimension: performance, cost and technological tradeoffs , 2007, ICCAD 2007.

[23]  Hanna Klaudel,et al.  Modeling Multi-valued Genetic Regulatory Networks Using High-Level Petri Nets , 2005, ICATPN.

[24]  Robert K. Brayton,et al.  Simplification of non-deterministic multi-valued networks , 2002, IWLS.

[25]  Bernd Grahlmann,et al.  The PEP Tool , 1997, CAV.

[26]  Anil Wipat,et al.  Automatic Parameterisation of Stochastic Petri Net Models of Biological Networks , 2006, PASM@FM.

[27]  Javier Esparza Model Checking Using Net Unfoldings , 1994, Sci. Comput. Program..

[28]  H. D. Jong,et al.  Qualitative simulation of the initiation of sporulation in Bacillus subtilis , 2004, Bulletin of mathematical biology.

[29]  Laure Petrucci,et al.  The Petri Net Markup Language: Concepts, Technology, and Tools , 2003, ICATPN.

[30]  Russ B. Altman,et al.  Research Paper: Using Petri Net Tools to Study Properties and Dynamics of Biological Systems , 2004, J. Am. Medical Informatics Assoc..

[31]  P. A. Grossman Discrete Mathematics for Computing , 1995 .

[32]  R. Losick,et al.  Molecular genetics of sporulation in Bacillus subtilis. , 1996, Annual review of genetics.

[33]  Wolfgang Reisig Petri Nets: An Introduction , 1985, EATCS Monographs on Theoretical Computer Science.

[34]  Hidde de Jong,et al.  Genetic Network Analyzer: qualitative simulation of genetic regulatory networks , 2003, Bioinform..

[35]  Michael Ruogu Zhang,et al.  Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization. , 1998, Molecular biology of the cell.

[36]  Tadao Murata,et al.  Petri nets: Properties, analysis and applications , 1989, Proc. IEEE.

[37]  Andrew Wuensche,et al.  Basins of attraction in network dynamics: A conceptual framework for biomolecular networks , 2003 .

[38]  Michael N. Liebman,et al.  Model Formulation: Modeling and Simulation of Pathways in Menopause , 2002, J. Am. Medical Informatics Assoc..

[39]  H Matsuno,et al.  Hybrid Petri net representation of gene regulatory network. , 1999, Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing.