Principles of transcriptional control in the metabolic network of Saccharomyces cerevisiae

Abstract

Cellular networks are subject to extensive regulation, which modifies the availability and efficiency of connections between components in response to external conditions. Thus far, studies of large-scale networks have focused on their connectivity, but have not considered how the modulation of this connectivity might also determine network properties. To address this issue, we analyzed how the coordinated expression of enzymes shapes the metabolic network of Saccharomyces cerevisiae. By integrating large-scale expression data with the structural description of the metabolic network, we systematically characterized the transcriptional regulation of metabolic pathways. The analysis revealed recurrent patterns, which may represent design principles of metabolic gene regulation. First, we find that transcription regulation biases metabolic flow toward linearity by coexpressing only distinct branches at metabolic branchpoints. Second, individual isozymes were often separately coregulated with distinct processes, providing a means of reducing crosstalk between pathways using a common reaction. Finally, transcriptional regulation defined a hierarchical organization of metabolic pathways into groups of varying expression coherence. These results emphasize the utility of incorporating regulatory information when analyzing properties of large-scale cellular networks.

Transcriptional Coordination of the Metabolic Network in Arabidopsis

“…In general, the population of within-pathway comparisons contained a higher proportion of high-confidence (low p and high r 2 ) results than did comparisons involving genes from different pathways (Table I). Thus, we found that genes annotated as belonging to the same pathway tend to be more tightly coexpressed than genes from different metabolic pathways, a result that is consistent with results obtained from similar studies in yeast (Ihmels et al, 2004b). Interestingly, we also found that the relative proportion of highconfidence coexpression relationships is also higher among positively coexpressed genes than among negatively coexpressed genes.…”

“…Connectivity in the yeast (Saccharomyces cerevisiae) metabolic network has been explored using gene coexpression data and structural information about the pathways; these studies have revealed fundamental insights into the general properties of metabolic gene networks in eukaryotes (DeRisi et al, 1997;Ihmels et al, 2004b). One early result was that functionally related genes are often coexpressed, and this observation has provided strong motivation for the adoption of expression microarrays in biological research (DeRisi et al, 1997).…”

“…One early result was that functionally related genes are often coexpressed, and this observation has provided strong motivation for the adoption of expression microarrays in biological research (DeRisi et al, 1997). In addition, it has been shown that many genes encoding metabolic enzymes form modules of coexpression and that coexpressed genes occupy nonrandom positions with respect to the pathway structure (Ihmels et al, 2004a(Ihmels et al, , 2004b. A number of methods based on integration of gene expression data with other data types have been developed, allowing identification of undiscovered modules (Stuart et al, 2003) as well as control elements and transcription factors that regulate their expression (Pilpel et al, 2001).…”

A Novel Approach for Nontargeted Data Analysis for Metabolomics. Large-Scale Profiling of Tomato Fruit Volatiles

“…This concept implies that cellular functionality is organized in a set of functional modules, which consequently are organized in a few large modules, which in turn can be grouped into even larger modules (Jeong et al, 2000;Ravasz et al, 2002;Ihmels et al, 2004). The hierarchical modularity of metabolic network organization would allow robust, error-tolerant, and energetically efficient functioning of biological systems.…”

Genomic analysis of the hierarchical structure of regulatory networks

“…However, researchers have yet to do this comparison with regulatory networks. Of all biological networks, regulatory networks are of particular interest, because to some degree they act as the master control system for the cell, tightly coordinating the expression of all genes (13)(14)(15). From a graph-theoretical point of view, regulatory networks are different from interaction networks in that they are directed.…”