Control analysis of time-dependent metabolic systems

Acerenza, Luis; Sauro, Herbert M.; Kacser, H.

doi:10.1016/s0022-5193(89)80038-4

Cited by 81 publications

(71 citation statements)

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“…Any parameter change may therefore cause a phase shift that continues to increase with time. An important consequence is that theorems such as derived in ref 41 for oscillating metabolite concentrations cannot contribute much to the understanding of how autonomously oscillating systems are controlled. The relationship, considered as the connectivity theorem by Acerenza et al, 41 is, in fact, the variation equation with respect to the transient control coefficients.…”

Section: Discussionmentioning

confidence: 99%

Section: A Definitions Of Time-dependent Control Coefficientsmentioning

confidence: 99%

“…Therefore, eqs 14 continue to apply. This results in the following relationships for the control coefficients defined by eq 3: 41 where the control coefficients are defined as formal derivatives of concentrations and fluxes with respect to e j at the moment t (eq 3). However, for autonomous oscillations the relationships (19) are not very useful because the control coefficients become unlimited with time, unless it is emphasized that the enzymes have an excessive and oscillatory control on the metabolite concentrations.…”

Section: Ementioning

confidence: 99%

“…They found subtly distributed control. Yet, the most intriguing issue about the control of oscillations in biological systems has not been studied in detail, e.g., which laws govern the magnitudes and distribution of the control.In close vicinity of the (asymptotically) stable steady state the control over a relaxation process has been analyzed by 41 These authors introduced an "operational" definition of a time-dependent control coefficient as the relative difference between the reaction rates (concentrations) in the original and the perturbed system observed at time t, after a perturbation of a parameter at time 0, divided by the relative change in that parameter. A number of relationships considered to be analogous to the summation and connectivity theorems for systems at steady states 41 were derived.…”

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confidence: 99%

“…Indeed, in standard MCA, eq 3 will define the usual control coefficients if the steady-state concentrations and fluxes are substituted in this equation for the periodic ones. The transient control coefficients of an oscillating system (eq 4) correspond to the time-dependent control coefficients, as introduced by Acerenza et al 41 , or if the amplitude of the forcing function approaches zero. Definition (4) and the corresponding definition of time-dependent control coefficients in refs 38 and 41 have the clear operational meaning of relating fractional changes in a particular enzyme concentration at given initial conditions to resulting changes in metabolic concentration or flux at any subsequent point in time.…”

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confidence: 99%

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Control Analysis of Periodic Phenomena in Biological Systems

1997

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Control analysis of periodic phenomena in biological systemsKholodenko, B.N.; Demin, O.V.; Westerhoff, H.V. General rightsIt is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons). Disclaimer/Complaints regulationsIf you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: http://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible. Download date: 10 May 2018 Control Analysis of Periodic Phenomena in Biological SystemsBoris N. Kholodenko,* , † Oleg V. Demin, ‡ and Hans V. Westerhoff §,| Department of Pathology, Anatomy and Cell Biology, Thomas Jefferson UniVersity, 1020 Locust Street, Philadelphia, PennsylVania 19107, A.N. Belozersky Institute of Physico-Chemical Biology, Moscow State UniVersity, 119899 Moscow, Russia, Department of Microbial Physiology, Free UniVersity, De Boelelaan 1087, NL-1081 HV Amsterdam, The Netherlands, and E. C. Slater Institute, Biocentrum, UniVersity of Amsterdam, Plantage Muidergracht 12, The Netherlands ReceiVed: July 31, 1996 In Final Form: January 7, 1997 X Principles of the control and regulation of steady-state metabolic systems have been identified in terms of the concepts and laws of metabolic control analysis (MCA). With respect to the control of periodic phenomena MCA has not been equally successful. This paper shows why in case of autonomous (self-sustained) oscillations for the concentrations and reaction rates, time-dependent control coefficients are not useful to characterize the system: they are neither constant nor periodic and diverge as time progresses. This is because a controlling parameter tends to change the frequency and causes a phase shift that continuously increases with time. This recognition is important in the extension of MCA for periodic phenomena. For oscillations that are enforced with an externally determined frequency, the time-dependent control coefficients over metabolite concentration and fluxes (reaction rates) are shown to have a complete meaning. Two such time-dependent control coefficients are defined for forced oscillations. One, the so-called periodic control coefficient, measures how the stationary periodic movement depends on the activities of one of the enzymes. The other, the socalled transient control coefficient, measures the control over the transition of the system between two stationary oscillations, as induced by a change in one of the enzyme activities. For forced oscillations, the two control coefficients become equal as time tends to infinity. N...

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Section: Discussionmentioning

confidence: 99%

Section: A Definitions Of Time-dependent Control Coefficientsmentioning

confidence: 99%

Section: Ementioning

confidence: 99%

mentioning

confidence: 99%

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confidence: 99%

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Control Analysis of Periodic Phenomena in Biological Systems

1997

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Silicon Cell Models: Construction, Analysis, and Reduction

Bruggeman

Härdin

Schuppen

et al. 2007

Biosimulation in Drug Development

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Optimization‐based metabolic control analysis

Uygun

Matthew

et al. 2010

Biotechnology Progress

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In this work, a novel optimization-based metabolic control analysis (OMCA) method is introduced for reducing data requirement for metabolic control analysis (MCA). It is postulated that using the optimal control approach, the fluxes in a metabolic network are correlated to metabolite concentrations and enzyme activities as a state-feedback control system that is optimal with respect to a homeostasis objective. It is then shown that the optimal feedback gains are directly related to the elasticity coefficients (ECs) of MCA. This approach requires determination of the relative "importance" of metabolites and fluxes for the system, which is possible with significantly reduced experimental data, as compared with typical MCA requirements. The OMCA approach is applied to a top-down control model of glycolysis in hepatocytes. It is statistically demonstrated that the OMCA model is capable of predicting the ECs observed experimentally with few exceptions. Further, an OMCA-based model reconciliation study shows that the modification of four assumed stoichiometric coefficients in the model can explain most of the discrepancies, with the exception of elasticities with respect to the NADH/NAD ratio.

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Control analysis of time-dependent metabolic systems

Cited by 81 publications

References 25 publications

Control Analysis of Periodic Phenomena in Biological Systems

Control Analysis of Periodic Phenomena in Biological Systems

Silicon Cell Models: Construction, Analysis, and Reduction

Optimization‐based metabolic control analysis

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