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Co-regulation of metabolic genes is better explained by flux coupling than by network distance.

Notebaart RA, Teusink B, Siezen RJ, Papp B - PLoS Comput. Biol. (2008)

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Center for Molecular and Biomolecular Informatics (NCMLS), Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands.

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.

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The Effect of Flux Coupling and Network Distance on Operonic Organization in E. coli(A) The fraction of intra-operonic gene pairs correlates with the type of flux coupling. The dashed baseline indicates the fraction of intra-operonic gene pairs expected by chance.(B) The effect of flux coupling on the fraction of intra-operonic gene pairs in different network distance groups: χ2d=1 = 715.3, χ2d=2,3,4 = 5347.3, χ2d≥5 = 5022.3, d.f. = 2, and p < 10−155.
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pcbi-0040026-g003: The Effect of Flux Coupling and Network Distance on Operonic Organization in E. coli(A) The fraction of intra-operonic gene pairs correlates with the type of flux coupling. The dashed baseline indicates the fraction of intra-operonic gene pairs expected by chance.(B) The effect of flux coupling on the fraction of intra-operonic gene pairs in different network distance groups: χ2d=1 = 715.3, χ2d=2,3,4 = 5347.3, χ2d≥5 = 5022.3, d.f. = 2, and p < 10−155.

Mentions: To measure and compare the extent of co-regulation between the types of flux coupling, we calculated the frequency of gene pairs that are part of the same operon (referred to as intra-operonic) as it represents a clear measure of co-regulation. The comparison revealed an association between the type of flux coupling and the likelihood of being intra-operonic (χ2 = 20489.6, d.f. = 2, p ≈ 0, Figure 3A). Thus, genes with complete correlation in flux behavior undergo more frequently precise co-regulation. Directionally coupled gene pairs do not necessarily operate together at all times, and, indeed, we find that these pairs less frequently reside in the same operon.


Co-regulation of metabolic genes is better explained by flux coupling than by network distance.

Notebaart RA, Teusink B, Siezen RJ, Papp B - PLoS Comput. Biol. (2008)

The Effect of Flux Coupling and Network Distance on Operonic Organization in E. coli(A) The fraction of intra-operonic gene pairs correlates with the type of flux coupling. The dashed baseline indicates the fraction of intra-operonic gene pairs expected by chance.(B) The effect of flux coupling on the fraction of intra-operonic gene pairs in different network distance groups: χ2d=1 = 715.3, χ2d=2,3,4 = 5347.3, χ2d≥5 = 5022.3, d.f. = 2, and p < 10−155.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2211535&req=5

pcbi-0040026-g003: The Effect of Flux Coupling and Network Distance on Operonic Organization in E. coli(A) The fraction of intra-operonic gene pairs correlates with the type of flux coupling. The dashed baseline indicates the fraction of intra-operonic gene pairs expected by chance.(B) The effect of flux coupling on the fraction of intra-operonic gene pairs in different network distance groups: χ2d=1 = 715.3, χ2d=2,3,4 = 5347.3, χ2d≥5 = 5022.3, d.f. = 2, and p < 10−155.
Mentions: To measure and compare the extent of co-regulation between the types of flux coupling, we calculated the frequency of gene pairs that are part of the same operon (referred to as intra-operonic) as it represents a clear measure of co-regulation. The comparison revealed an association between the type of flux coupling and the likelihood of being intra-operonic (χ2 = 20489.6, d.f. = 2, p ≈ 0, Figure 3A). Thus, genes with complete correlation in flux behavior undergo more frequently precise co-regulation. Directionally coupled gene pairs do not necessarily operate together at all times, and, indeed, we find that these pairs less frequently reside in the same operon.

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Center for Molecular and Biomolecular Informatics (NCMLS), Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands.

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.

Show MeSH
Related in: MedlinePlus