Trade-offs between efficiency and robustness in bacterial metabolic networks are associated with niche breadth

Melissa J. Morine, Hong Gu, Ransom A. Myers, Joseph P. Bielawski

Résultat de recherche: Articleexamen par les pairs

10 Citations (Scopus)

Résumé

The relation between structure and function in biologic networks is a central point of systems biology research. Key functional features-notably, efficiency and robustness-are linked to the topologic structure of a network, and there appears to be a degree of trade-off between these features, i.e., simulation studies indicate that more efficient networks tend to be less robust. Here, we investigate this issue in metabolic networks from 105 lineages of bacteria having a wide range of ecologies. We take quantitative measurements on each network and integrate this network data with ecologic data using a phylogenetic comparative model. In this setting, we find that biologic conclusions obtained with classical phylogenetic comparative methods are sensitive to correlations between model covariates and phylogenetic branch length. To avoid this problem, we propose a revised statistical framework-hierarchical mixed-effect regression-to accommodate phylogenetic nonindependence. Using this approach, we show that the cartography of metabolic networks does indeed reflect a trade-off between efficiency and robustness. Furthermore, ecologic characteristics related to niche breadth are strong predictors of network shape. Given the broad variation in niche breadth seen among species, we predict that there is no universally optimal balance between efficiency and robustness in bacterial metabolic networks and, thus, no universally optimal network structure. These results highlight the biologic relevance of variation in network structure and the potential role of niche breadth in shaping metabolic strategies of efficiency and robustness.

Langue d'origineEnglish
Pages (de-à)506-515
Nombre de pages10
JournalJournal of Molecular Evolution
Volume68
Numéro de publication5
DOI
Statut de publicationPublished - mai 2009

Note bibliographique

Funding Information:
We thank Hongwu Ma and An-Ping Zeng for providing their metabolic database and Robert Guimera for use of the program for determining modularity as well as useful suggestions for optimizing the implementation of the program. We thank the anonymous referees for constructive comments. This work was supported by grants from the Natural Sciences and Engineering Research Council of Canada to J. P. B. and H. G.; a grant from the Canadian Foundation for Innovation to J. P. B.; and a grant from the Nova Scotia Health Research Foundation to M. J. M.

ASJC Scopus Subject Areas

  • Ecology, Evolution, Behavior and Systematics
  • Molecular Biology
  • Genetics

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