QSSPN: dynamic simulation of molecular interaction networks describing gene regulation, signalling and whole-cell metabolism in human cells

Ciarán P Fisher,J Bernadette Moore,Andrzej M Kierzek,Nicholas J Plant

doi:10.1093/bioinformatics/btt552

Ciarán P Fisher, J Bernadette Moore + Show 2 more

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https://doi.org/10.1093/bioinformatics/btt552

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Abstract

Motivation: Dynamic simulation of genome-scale molecular interaction networks will enable the mechanistic prediction of genotype–phenotype relationships. Despite advances in quantitative biology, full parameterization of whole-cell models is not yet possible. Simulation methods capable of using available qualitative data are required to develop dynamic whole-cell models through an iterative process of modelling and experimental validation.Results: We formulate quasi-steady state Petri nets (QSSPN), a novel method integrating Petri nets and constraint-based analysis to predict the feasibility of qualitative dynamic behaviours in qualitative models of gene regulation, signalling and whole-cell metabolism. We present the first dynamic simulations including regulatory mechanisms and a genome-scale metabolic network in human cell, using bile acid homeostasis in human hepatocytes as a case study. QSSPN simulations reproduce experimentally determined qualitative dynamic behaviours and permit mechanistic analysis of genotype–phenotype relationships.Availability and implementation: The model and simulation software implemented in C++ are available in supplementary material and at http://sysbio3.fhms.surrey.ac.uk/qsspn/.Contact: a.kierzek@surrey.ac.ukSupplementary information: Supplementary data are available at Bioinformatics online.

Highlights

One of the fundamental goals of molecular biology is to delineate the molecular mechanisms by which genetic information is expressed in response to environmental cues, giving rise to a specific phenotype
To enable quasi-steady state Petri nets (QSSPN) simulation of molecular networks in human cells, we have constructed a general model of gene expression, using qualitative rules to describe the relationship between gene regulation, transcription, translation, precursor availability and messenger RNA/ protein degradation (Fig. 2)
We present qualitative dynamic simulations of bile acid (BA) homeostasis in human hepatocytes incorporating gene regulation, signalling and whole-cell metabolism

Summary

Introduction

One of the fundamental goals of molecular biology is to delineate the molecular mechanisms by which genetic information is expressed in response to environmental cues, giving rise to a specific phenotype. The molecules and interactions included into such models reflect the extent of genome sequence annotation, with computer simulation used to predict system behaviour under particular environmental conditions. In systems biology, such unbiased representation of molecular interactions in mechanistic models is referred to as reconstruction (Oberhardt et al, 2009). The ultimate goal of reconstruction is to reverse engineer the entire molecular machinery of the cell in a computer model capable of reproducing the responses of specific cells/tissues to any environmental perturbation. We believe that mechanistic prediction of genotype–phenotype relationship through computer simulation of the genome-scale molecular interaction networks in human cells is indispensable to the development of personalized medicine (Hood and Tian, 2012)

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