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Metabolites. 2015 Jun 2;5(2):311-43. doi: 10.3390/metabo5020311.

Metabolism at evolutionary optimal States.

Author information

1
Department of Systems Bioinformatics, VU University Amsterdam, De Boelelaan 1085, 1081 HV Amsterdam, The Netherlands. i.rabbers@vu.nl.
2
Department of Systems Bioinformatics, VU University Amsterdam, De Boelelaan 1085, 1081 HV Amsterdam, The Netherlands. j.van.heerden@vu.nl.
3
Department of Systems Bioinformatics, VU University Amsterdam, De Boelelaan 1085, 1081 HV Amsterdam, The Netherlands. n.nordholt@vu.nl.
4
Department of Systems Bioinformatics, VU University Amsterdam, De Boelelaan 1085, 1081 HV Amsterdam, The Netherlands. h.bachmann@vu.nl.
5
NIZO Food Research, 6718 ZB Ede, The Netherlands. h.bachmann@vu.nl.
6
Top Institute Food and Nutrition, 6700 AN Wageningen, The Netherlands. h.bachmann@vu.nl.
7
Department of Systems Bioinformatics, VU University Amsterdam, De Boelelaan 1085, 1081 HV Amsterdam, The Netherlands. b.teusink@vu.nl.
8
Department of Systems Bioinformatics, VU University Amsterdam, De Boelelaan 1085, 1081 HV Amsterdam, The Netherlands. f.j.bruggeman@vu.nl.

Abstract

Metabolism is generally required for cellular maintenance and for the generation of offspring under conditions that support growth. The rates, yields (efficiencies), adaptation time and robustness of metabolism are therefore key determinants of cellular fitness. For biotechnological applications and our understanding of the evolution of metabolism, it is necessary to figure out how the functional system properties of metabolism can be optimized, via adjustments of the kinetics and expression of enzymes, and by rewiring metabolism. The trade-offs that can occur during such optimizations then indicate fundamental limits to evolutionary innovations and bioengineering. In this paper, we review several theoretical and experimental findings about mechanisms for metabolic optimization.

KEYWORDS:

evolution; fitness landscapes; metabolism; optimality; selection pressure; trade-offs

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