Differential enrichment of regulatory motifs in the composite network of protein-protein and gene regulatory interactions

Background: An important aspect of molecular interactions is the dynamics associated with growth conditions. Intuitively, not all possible interactions take place together all the time in a cell as only a subset of genes is expressed based on environmental conditions. Results: Large scale gene expression data of Escherichia coli was analyzed to understand the dynamics exhibited at expression level. A large compendium of gene expression datasets, which covers about 466 growth conditions, was used for the analysis. Using gene expression data, genes of E. coli were profiled into three classes: Widely expressed, Conditionally expressed and Rarely expressed. Further, dynamics associated with molecular interactions were analysed by studying changing importance of motifs in the composite networks across growth conditions. Conclusions: Our analysis of large scale gene expression data suggests conditional expression of genes which brings about befitting responses for a given growth environment. We observe a range of importance for network motifs across conditions which can be correlated with a specific function. Our study therefore suggests rewiring of molecular interactions driven by gene expression changes depending on the conditional needs.