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Large-scale in vivo flux analysis shows rigidity and suboptimal performance of Bacillus subtilis metabolism


Qualitative theoretical approaches such as graph theory1,2 and stoichiometric analyses3,4,5,6 are beginning to uncover the architecture and systemic functions of complex metabolic reaction networks. At present, however, only a few, largely unproven quantitative concepts propose functional design principles of the global flux distribution7,8. As operational units of function, molecular fluxes determine the systemic cell phenotype by linking genes, proteins and metabolites to higher-level biological functions9. In sharp contrast to other 'omics' analyses, 'fluxome' analysis remained tedious10. By large-scale quantification of in vivo flux responses, we identified a robust flux distribution in 137 null mutants of Bacillus subtilis. On its preferred substrate, B. subtilis has suboptimal metabolism because regulators of developmental programs maintain a 'standby' mode that invests substantial resources in anticipation of changing environmental conditions at the expense of optimal growth. Network rigidity and robustness are probably universal functional design principles, whereas the standby mode may be more specific.

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Figure 1: Distribution of metabolic fluxes in 137 B. subtilis mutants.
Figure 2: Effect of knockouts on relative fluxes.
Figure 3: Effect of knockouts on absolute fluxes and optimality.


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We thank S. Aymerich, S. Bonhoeffer, H Hennecke, T. Pfeiffer and J. Stelling for critical comments on the manuscript and S. Aymerich, K. Kobayashi and N. Ogasawara for providing B. subtilis mutants. This work was supported in part by the Roche Research Foundation (E.F.).

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Correspondence to Uwe Sauer.

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Supplementary information

Supplementary Table 1

Mutants used in this study. (XLS 37 kb)

Supplementary Table 2

Relative and absolute fluxes during aerobic batch growth on glucose in wild-type B. subtilis and the 137 viable mutants. (XLS 424 kb)

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Fischer, E., Sauer, U. Large-scale in vivo flux analysis shows rigidity and suboptimal performance of Bacillus subtilis metabolism. Nat Genet 37, 636–640 (2005).

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