Li Zheng, Srivastava Shireesh, Mittal Sheenu, Yang Xuerui, Sheng Lufang, Chan Christina
Department of Chemical Engineering and Materials Science, Michigan State University, East Lansing, MI 48824, USA.
BMC Bioinformatics. 2007 Jun 14;8:202. doi: 10.1186/1471-2105-8-202.
The ability to obtain profiles of gene expressions, proteins and metabolites with the advent of high throughput technologies has advanced the study of pathway and network reconstruction. Genome-wide network reconstruction requires either interaction measurements or large amount of perturbation data, often not available for mammalian cell systems. To overcome these shortcomings, we developed a Three Stage Integrative Pathway Search (TIPS(c)) approach to reconstruct context-specific active pathways involved in conferring a specific phenotype, from limited amount of perturbation data. The approach was tested on human liver cells to identify pathways that confer cytotoxicity.
This paper presents a systems approach that integrates gene expression and cytotoxicity profiles to identify a network of pathways involved in free fatty acid (FFA) and tumor necrosis factor-alpha (TNF-alpha) induced cytotoxicity in human hepatoblastoma cells (HepG2/C3A). Cytotoxicity relevant genes were first identified and then used to reconstruct a network using Bayesian network (BN) analysis. BN inference was used subsequently to predict the effects of perturbing a gene on the other genes in the network and on the cytotoxicity. These predictions were subsequently confirmed through the published literature and further experiments.
The TIPS(c) approach is able to reconstruct active pathways that confer a particular phenotype by integrating gene expression and phenotypic profiles. A web-based version of TIPS(c) that performs the analysis described herein can be accessed at http://www.egr.msu.edu/tips.
