An integrated pathway system modeling of Saccharomyces cerevisiae HOG pathway: a Petri Net based approach. Mol Biol Rep

Machine Intelligence Unit, Indian Statistical Institute, 203 B. T. Road, Kolkata, 700108, India, .
Molecular Biology Reports (Impact Factor: 2.02). 10/2012; 40(2). DOI: 10.1007/s11033-012-2153-3
Source: PubMed


Biochemical networks comprise many diverse components and interactions between them. It has intracellular signaling, metabolic and gene regulatory pathways which are highly integrated and whose responses are elicited by extracellular actions. Previous modeling techniques mostly consider each pathway independently without focusing on the interrelation of these which actually functions as a single system. In this paper, we propose an approach of modeling an integrated pathway using an event-driven modeling tool, i.e., Petri nets (PNs). PNs have the ability to simulate the dynamics of the system with high levels of accuracy. The integrated set of signaling, regulatory and metabolic reactions involved in Saccharomyces cerevisiae's HOG pathway has been collected from the literature. The kinetic parameter values have been used for transition firings. The dynamics of the system has been simulated and the concentrations of major biological species over time have been observed. The phenotypic characteristics of the integrated system have been investigated under two conditions, viz., under the absence and presence of osmotic pressure. The results have been validated favorably with the existing experimental results. We have also compared our study with the study of idFBA (Lee et al., PLoS Comput Biol 4:e1000-e1086, 2008) and pointed out the differences between both studies. We have simulated and monitored concentrations of multiple biological entities over time and also incorporated feedback inhibition by Ptp2 which has not been included in the idFBA study. We have concluded that our study is the first to the best of our knowledge to model signaling, metabolic and regulatory events in an integrated form through PN model framework. This study is useful in computational simulation of system dynamics for integrated pathways as there are growing evidences that the malfunctioning of the interplay among these pathways is associated with disease.

Download full-text


Available from: Rajat Kumar De, Jul 04, 2014
  • [Show abstract] [Hide abstract]
    ABSTRACT: The identification of fungal virulence factors and novel targets for therapeutic intervention are hindered by the rapid adaptability of pathogenic fungi to their host. One of the major goals of systems biology (SysBio) is to investigate the molecular wiring and dynamics in biological networks, as well as to identify and predict emerging properties of systems. Recent advances in SysBio approaches have paved the way for deciphering host–pathogen interaction complexity and the identification of microbial virulence factors. In this chapter, we discuss SysBio-based methods and milestones in the investigation of fungal virulence, emphasizing computational and modeling-based approaches in the Candida and Saccharomyces genera. We describe the applicability of each method to specific experimental questions using numerous case examples, and critically discuss current gaps and pitfalls in the analysis of SysBio data sets.
    Human Fungal Pathogens, 01/2014: pages 45-74; , ISBN: 978-3-642-39431-7
  • [Show abstract] [Hide abstract]
    ABSTRACT: Computational modelling is a key component of systems biology and integrates with the other techniques discussed thus far in this book by utilizing a myriad of data that are being generated to quantitatively represent and simulate biological systems. This chapter will describe what computational modelling involves; the rationale for using it, and the appropriateness of modelling for investigating the aging process. How a model is assembled and the different theoretical frameworks that can be used to build a model are also discussed. In addition, the chapter will describe several models which demonstrate the effectiveness of each computational approach for investigating the constituents of a healthy aging trajectory. Specifically, a number of models will be showcased which focus on the complex age-related disorders associated with unhealthy aging. To conclude, we discuss the future applications of computational systems modelling to aging research. © 2015 S. Karger AG, Basel.
    Interdisciplinary topics in gerontology 01/2015; 40:35-48. DOI:10.1159/000364928