title: Invariance and optimality in the regulation of an enzyme.
abstract: BACKGROUND
  The Michaelis-Menten equation, proposed a century ago, describes the kinetics of enzyme-catalyzed biochemical reactions. Since then, this equation has been used in countless, increasingly complex models of cellular metabolism, often including time-dependent enzyme levels. However, even for a single reaction, there remains a fundamental disconnect between our understanding of the reaction kinetics, and the regulation of that reaction through changes in the abundance of active enzyme.
  
  
  RESULTS
  We revisit the Michaelis-Menten equation under the assumption of a time-dependent enzyme concentration. We show that all temporal enzyme profiles with the same average enzyme level yield identical substrate degradation- a simple analytical conclusion that can be thought of as an invariance principle, and which we validate experimentally using a β-galactosidase assay. The ensemble of all time-dependent enzyme trajectories with the same average concentration constitutes a space of functions. We develop a simple model of biological fitness which assigns a cost to each of these trajectories (in the form of a function of functions, i.e. a functional). We then show how one can use variational calculus to analytically infer temporal enzyme profiles that minimize the overall enzyme cost. In particular, by separately treating the static costs of amino acid sequestration and the dynamic costs of protein production, we identify a fundamental cellular tradeoff.
  
  
  CONCLUSIONS
  The overall metabolic outcome of a reaction described by Michaelis-Menten kinetics is ultimately determined by the average concentration of the enzyme during a given time interval. This invariance in analogy to path-independent phenomena in physics, suggests a new way in which variational calculus can be employed to address biological questions. Together, our results point to possible avenues for a unified approach to studying metabolism and its regulation.
  
  
  METHODS
  This article was reviewed by Sergei Maslov, William Hlavacek and Daniel Kahn.
authors.affiliation: Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston, MA 02215, USA.
authors.forename: Ed
authors.initials: E
authors.lastname: Reznik
authors.forename: Stefan
authors.initials: S
authors.lastname: Yohe
authors.forename: Daniel
authors.initials: D
authors.lastname: Segrè
mesh_terms: D004798:Enzymes / Q000378:metabolism*; D007700:Kinetics
chemical_list: D004798:Enzymes