Steady-State Measurements and Identifiability of Regulatory Patterns in Metabolic Studies
A main objective in investigating a metabolic pathway is to obtain a definite idea of both its structure, in terms of material and information relationships, and its behavior. Traditionally, the schematic representation of a given pathway is based on previous information mainly obtained by experiments in vitro. Measurements on the intact system are then used for testing the resulting structure. This is justified by the idea that knowing the elements of a given pathway will lead us to a deep understanding of both its properties and its behavior under specified conditions. However, there is now increasing evidence that complete characterization of each element in vitro does not necessarily lead to a correct description of the whole system1–4. In practice, and especially if we consider the relevant regulatory signals within the system, it is often difficult to agree on a single scheme, and different possibilities arise. On one hand, the in situ conditions can make it some of the effects shown in vitro irrelevant. On the other hand, it is possible that some interactions not shown in vitro could be of interest in situ. Hence, we are dealing with a situation close to a black box, in the sense that the relationships within the system are not clearly established.
KeywordsMetabolic Control Regulatory Pattern Kinetic Order Dictyostelium Discoideum Citric Acid Production
Unable to display preview. Download preview PDF.
- 1.F. Shira-ishi and M.A. Savageau, The tricarboxilic acid cycle in Dictyostelium discoideum I. Formulation of alternative kinetic representations, J. Biol. Chem. 267:22912–22918 (1992).Google Scholar
- 2.F. Shira-ishi and M.A. Savageau, The tricarboxilic acid cycle in Dictyostelium discoideum II. Evaluation of model consistency and robustness, J. Biol. Chem. 267:22919–22925 (1992).Google Scholar
- 3.F. Shira-ishi and M.A. Savageau, The tricarboxilic acid cycle in Dictyostelium discoideum III. Analysis of steady-state and dynamic behavior, J. Biol. Chem. 267:22926–22933 (1992).Google Scholar
- 4.N. Torres, C. Regalado, A. Sorribas and M. Cascante, Quality assessment of a metabolic model and systerns analysis of citric acid production by Aspergillus niger ,this volume.Google Scholar
- 15.A. Sorribas, R. Curto and M. Cascante, Comparative characterization of the fermentation pathway of Saccharomyzes cerevisiae by using the Biochemical Systems Theory and the Metabolic Control Analysis: 1. Model definition and nomenclature, Biochem. J., submitted.Google Scholar
- 16.A. Sorribas, R. Curto and M. Cascante, Comparative characterization of the fermentation pathway of Saccharomyces cerevisiae by using the Biochemical Systems Theory and the Metabolic Control Analysis: 2. Steady-state characterization and dynamics, Biochem. J., submitted.Google Scholar
- 17.E.O. Voit (ed.). “Canonical Non-Linear Modelling: S-system Approach to Understanding Complexity,“Van Nostrand Reindhold, New York (1991).Google Scholar
- 18.A. Sorribas, S. Samitier, E.I. Canela and M. Cascante, Metabolic pathway characterization from transient response data obtained in situ: Parameter estimation in S-system models, J. Theor. Biol. ,in press.Google Scholar
- 20.A. Sorribas and M. Cascante, Structure identifiability in metabolic pathways: parameter estimation in models based on the power-law formalism, Eur. J. Biochem. ,submitted.Google Scholar