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Showing papers by "Bas Teusink published in 2008"


Journal ArticleDOI
TL;DR: It is shown 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, and it is demonstrated that network distance per se has relatively minor influence on gene co-regulation.
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 naive, 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.

106 citations


Journal ArticleDOI
TL;DR: High-throughput tools and DNA microarrays are valuable tools for elucidating the regulatory responses to different substrates and processing conditions thus allowing rational intervention in fermentations to improve flavour production, and genome-scale metabolic models are used to predict the production of relevant (flavour) components and to expand knowledge about flavour-forming pathways.

26 citations