Metabolic coupling and synchronization of NADH oscillations in yeast cell populations

Ghosh, Amal K.; Chance, Britton; Pye, Erica

doi:10.1016/0003-9861(71)90042-7

Cited by 114 publications

(92 citation statements)

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“…The phenomenon that may seem most amenable to such an extension is that of stationary oscillations of metabolic oscillating systems. A long known example is that of yeast glycolytic oscillations; under certain conditions yeast extracts and populations of yeast cells exhibit oscillations in NADH and glycolytic intermediates (e.g., refs [23][24][25][26]. These oscillations are autonomous; that is, they are not driven by an externally imposed oscillation.…”

Section: Discussionmentioning

confidence: 99%

“…[18][19][20] In biology, limit cycle systems are of particular interest, since some of them provide the mechanisms for various biological clocks, including the one governing the cell cycle. 21,22 Metabolic oscillations occur in yeast extracts, in populations of yeast cells (see, for example, refs [23][24][25][26][27][28][29][30][31][32], and in photosynthesis. 33 There is a growing interest in the yeast oscillations because they involve active cell-cell synchronization.…”

Section: Introductionmentioning

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: Introductionmentioning

confidence: 99%

Control Analysis of Periodic Phenomena in Biological Systems

1997

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“…Example systems include pacemaker cells in the heart (Michaels et al, 1987), circadian cells in the brain (Liu et al, 1997), coupled cortical neurons (Crook et al, 1997), Hodgkin-Huxley neurons (Brown et al, 2003), brain networks (Varela et al, 2001), yeast cells (Ghosh et al, 1971), flashing fireflies (Buck, 1988;Ermentrout, 1991), chirping crickets (Walker, 1969), central pattern generators for animal locomotion (Kopell and Ermentrout, 1988), particle models mimicking animal flocking behavior (Ha et al, 2010b, and fish schools , among others. The coupled oscillator model (1) also appears in physics and chemistry in modeling and analysis of spin glass models (Daido, 1992;Jongen et al, 2001), flavor evolution of neutrinos (Pantaleone, 1998), coupled Josephson junctions (Wiesenfeld et al, 1998), coupled metronomes (Pantaleone, 2002), Huygen's coupled pendulum clocks (Bennett et al, 2002;Kapitaniak et al, 2012), micromechanical oscillators with optical (Zhang et al, 2012) or mechanical (Shim et al, 2007) coupling, and in the analysis of chemical oscillations (Kuramoto, 1984a;Kiss et al, 2002).…”

Section: Applications In Sciencesmentioning

confidence: 99%

Synchronization in complex networks of phase oscillators: A survey

2014

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The emergence of synchronization in a network of coupled oscillators is a fascinating subject of multidisciplinary research. This survey reviews the vast literature on the theory and the applications of complex oscillator networks. We focus on phase oscillator models that are widespread in real-world synchronization phenomena, that generalize the celebrated Kuramoto model, and that feature a rich phenomenology. We review the history and the countless applications of this model throughout science and engineering. We justify the importance of the widespread coupled oscillator model as a locally canonical model and describe some selected applications relevant to control scientists, including vehicle coordination, electric power networks, and clock synchronization. We introduce the reader to several synchronization notions and performance estimates. We propose analysis approaches to phase and frequency synchronization, phase balancing, pattern formation, and partial synchronization. We present the sharpest known results about synchronization in networks of homogeneous and heterogeneous oscillators, with complete or sparse interconnection topologies, and in finite-dimensional and infinite-dimensional settings. We conclude by summarizing the limitations of existing analysis methods and by highlighting some directions for future research.

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“…A manifest demonstration of this phenomenon occurs when two suspensions oscillating 180°out of phase are mixed. Just after mixing, the macroscopic oscillations disappear momentarily, but the two subpopulations synchronize within 5 min (i.e., Ͻ10 times the period of the oscillations) and the macroscopic oscillations reappear with full amplitude (3)(4)(5). This indicates active in-phase synchronization.…”

mentioning

confidence: 99%

“…This indicates active in-phase synchronization. It is believed that the synchronization is mediated by simple metabolites related to glycolysis (1,4,5), and as such it is an example of cell-cell communication that does not depend on any highly specialized signaling molecules or receptors. A similar synchronization mechanism could be operative in any oscillatory cell type, possibly through other metabolic signaling channels.…”

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confidence: 99%

Quantitative characterization of cell synchronization in yeast

Danø

Sørensen²

2007

Proc. Natl. Acad. Sci. U.S.A.

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Metabolic oscillations in baker's yeast serve as a model system for synchronization of biochemical oscillations. Despite widespread interest, the complexity of the phenomenon has been an obstacle for a quantitative understanding of the cell synchronization process. In particular, when two yeast cell populations oscillating 180°out of phase are mixed, it appears as if the synchronization dynamics is too fast to be explained. We have probed the synchronization dynamics by forcing experiments in an open-flow reactor, and we find that acetaldehyde has a very strong synchronization effect that can account quantitatively for the classical mixing experiment. The fast synchronization dynamics is explained by a general synchronization mechanism, which is dominated by a fast amplitude response as opposed to the expected slow phase change. We also show that glucose can mediate this kind of synchronization, provided that the glucose transporter is not saturated. This makes the phenomenon potentially relevant for a broad range of cell types. . A manifest demonstration of this phenomenon occurs when two suspensions oscillating 180°out of phase are mixed. Just after mixing, the macroscopic oscillations disappear momentarily, but the two subpopulations synchronize within 5 min (i.e., Ͻ10 times the period of the oscillations) and the macroscopic oscillations reappear with full amplitude (3-5). This indicates active in-phase synchronization. It is believed that the synchronization is mediated by simple metabolites related to glycolysis (1,4,5), and as such it is an example of cell-cell communication that does not depend on any highly specialized signaling molecules or receptors. A similar synchronization mechanism could be operative in any oscillatory cell type, possibly through other metabolic signaling channels. Therefore, the understanding of the mechanism for glycolytic cell synchronization in yeast is important for the general understanding of cellular dynamics and interactions. Acetaldehyde (Aca) has been proposed as mediator of the synchronization (5). If this is the true mechanism of the phenomenon, then this understanding should allow us to explain it not only qualitatively but also quantitatively correct. It has been questioned whether the amount of Aca produced by the yeast cells is enough to cause synchronization (1), and several attempts have been made to account quantitatively for the synchronization process by using mathematical models based on biochemical descriptions (6-8). None of these have, however, been successful in explaining all experimental facts. In all cases, the synchronization process is one order of magnitude too slow, and in some cases the models even predict out-of-phase synchronization instead of the inphase synchronization seen experimentally.A necessary condition for a chemical species to act as a synchronizer is that it can penetrate the cell membrane, and that an instantaneous change in its concentration will influence the oscillations and give rise to an amplitude or phase change. Many differ...

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Metabolic coupling and synchronization of NADH oscillations in yeast cell populations

Cited by 114 publications

References 8 publications

Control Analysis of Periodic Phenomena in Biological Systems

Control Analysis of Periodic Phenomena in Biological Systems

Synchronization in complex networks of phase oscillators: A survey

Quantitative characterization of cell synchronization in yeast

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