Abstract
To what extent can modes of gene regulation be explained by systems-level properties of metabolic networks? Prior studies on co-regulation of metabolic genes have mainly focused on graph-theoretical features of metabolic networks and demonstrated a decreasing level of co-expression with increasing network distance, a naïve, but widely used, topological index. Others have suggested that static graph representations can poorly capture dynamic functional associations, e.g., in the form of dependence of metabolic fluxes across genes in the network. Here, we systematically tested the relative importance of metabolic flux coupling and network position on gene co-regulation, using a genome-scale metabolic model of Escherichia coli. After validating the computational method with empirical data on flux correlations, we confirm that genes coupled by their enzymatic fluxes not only show similar expression patterns, but also share transcriptional regulators and frequently reside in the same operon. In contrast, we demonstrate that network distance per se has relatively minor influence on gene co-regulation. Moreover, the type of flux coupling can explain refined properties of the regulatory network that are ignored by simple graph-theoretical indices. Our results underline the importance of studying functional states of cellular networks to define physiologically relevant associations between genes and should stimulate future developments of novel functional genomic tools.
Highlights
In recent years, metabolic networks of various species have been reconstructed [1], and several systematic studies addressed the issue of gene regulation in metabolism [2,3,4,5]
Why do certain genes in a biological network show tight transcriptional co-regulation while others are more or less independently regulated? Prior studies showed that the degree of co-regulation between enzymatic genes decreases with their distance in the metabolic network
We systematically examine whether flux coupling, a biochemically sound and computationally tractable measure of functional interaction between reactions, can better explain gene co-regulation than network distance in the metabolisms of Escherichia coli and Saccharomyces cerevisiae
Summary
Metabolic networks of various species have been reconstructed [1], and several systematic studies addressed the issue of gene regulation in metabolism [2,3,4,5]. These studies have revealed important insights into transcriptional regulation by integration of gene co-expression with historically defined modules (e.g., glycolysis) or with graph-theoretical properties of reconstructed networks. Trends in gene co-regulation with network distance have been reported [3], it remains unexplained how purely graph-theoretical indices of metabolic networks relate to physiologically relevant functional associations.
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