Bistable Biochemical Switching and the Control of the Events of the Cell Cycle*

Total Page:16

File Type:pdf, Size:1020Kb

Bistable Biochemical Switching and the Control of the Events of the Cell Cycle* Oncogene (1997) 15, 317 ± 325 1997 Stockton Press All rights reserved 0950 ± 9232/97 $12.00 Bistable biochemical switching and the control of the events of the cell cycle* CD Thron 5 Barrymore Road, Hanover, New Hampshire 03755, USA Some of the events of the cell cycle appear to be development (Edelstein, 1971; Seelig and Denzel, 1972; triggered by a bistable mechanism. A bistable biochem- Meinhart, 1982; Murray, 1989). Biochemical switches ical system can respond to a small, slow signal and is of the simple types considered here have been described carried by positive feedback from one stable steady state and discussed by Edelstein-Keshet (1988) and Murray directly to another, in an all-or-none manner. Slow or (1989). Lewis et al. (1977) have particularly stressed subthreshold stimuli do not cause accommodation or loss that other types of biochemical switch do not show of excitability. Switching is not readily reversible by true thresholds of discontinuity, and do not provide removing the stimulus, i.e. there is hysteresis: reversal either the sharpness or the irrevocability of bistable generally requires a stronger, opposite stimulus. Bio- switches. Bistable switching is typically caused by a chemically, bistable biochemical switching requires change in a rate constant or other parameter which positive feedback, and mechanisms for stabilizing the changes the biochemical dynamics and destabilizes the system against premature activation and for destabiliza- current stable state, and thereby forces the system to tion in response to a biological signal. Three bistable bio- go to the alternate stable state. A change of steady chemical models, all suggested by reported experimental state may alternatively be caused by addition of observations, are described and analysed. These models substrate, as in ampli®cation of MPF; but mitosis is suggest that a titratable inhibitor may play an important not normally initiated by addition of MPF, and we will part in bistable switching, because the end-point of focus here on switching by destabilization of a steady titration can form a natural threshold for enhancement state. of positive feedback. Some cell cycle events other than mitosis are controlled by cyclin-dependent kinases (Cdks) other Keywords: biochemical switch; bistability; cell cycle; than Cdc2, and some of these Cdks appear to be cyclin-dependent kinase inhibitors; positive feedback regulated by Cdk inhibitors (CKIs) (Hunter, 1993; Pines, 1994; Elledge and Harper, 1994; Peter and Herskowitz, 1994b). Nasmyth and Hunt (1993) have suggested that Cdks `build up like water behind a CKI Introduction dam,' and that over¯ow of Cdk from the dam triggers The onset of mitosis is thought to be caused by proteolysis or inactivation of the CKI, releasing a ¯ood maturation promoting factor (MPF), a complex of the of Cdks that irrevocably commit the cell to the next protein kinase Cdc2 with cyclin B (Murray and Hunt, phase of the cell cycle. Several CKIs appear to be 1993). MPF shows the phenomenon of `ampli®cation': regulated by proteolysis (McKinney et al., 1993; a small added amount of MPF causes activation of a Schwob et al., 1994; Pagano et al., 1995), and while much larger amount from an inactive precursor (Cyert mechanisms for rapidly activating the proteolysis have and Kirschner, 1988; Dunphy and Newport, 1988). not been generally demonstrated, Sherr (1996) cites a Ampli®cation is apparently due to the fact that Cdc2/ report that Cdk2/cyclin E accelerates turnover of cyclin B activates its own activating kinase Cdc25 p27Kip1. If a Cdk activates CKI proteolysis this releases (Homan et al., 1993), giving rise to a positive more Cdk, creating positive feedback and possibly feedback loop that makes the activation of MPF leading to complete destruction of CKI and a stable eectively autocatalytic. Evidently a cell can exist in a state with CKI obliterated and Cdk freed. To prevent stable steady state with low MPF activity; but on activation, CKI must inhibit Cdk-activated CKI displacement of the cell from this steady state, by proteolysis enough to protect itself and stabilize a addition of a small amount of MPF, the autocatalytic steady state with low Cdk activity. The system is then eect of MPF causes the cell to shift toward a dierent bistable and has the potential for bistable switching. stable state, one with high MPF activity. Ampli®cation The important characteristics of a bistable biochem- therefore indicates the existence of two potential stable ical switch are (1) it always commits itself to one of steady states, i.e. bistability. two stable steady states, and does not linger in any Bistable switching is well known in chemical intermediate or transitional states; (2) it can be engineering, and a clear and fairly simple explanation switched rapidly from one stable steady state to is given by Gray and Scott (1990). In biology it has another, and this may require only a small, slow been proposed as a mechanism of memory, of signal; and (3) it shows hysteresis, in that removing the dierentiation, or of conversion of continuous chemi- signal does not undo the response, and restoring the cal gradients into discontinuous patterns of embryonic original steady state requires a stronger opposite signal. These characteristics, in a switch controlling the onset of mitosis or other cell cycle events, can prevent an *Most of this work was done while the author was in the department incomplete or vacillating commitment, which might of Pharmacology and Toxicology, Darmouth Medical School, Hanover, NH 03755, U.S.A. well be catastrophic. This paper attempts to give a Received 24 January 1997; revised 2 April 1997; accepted 3 April qualitative understanding of the dynamics and 1997 biochemical kinetics underlying several types of Bistable biochemical switching in the cell cycle CD Thron 318 bistable switching which may be involved in controlling Newport, 1989), and this mechanism could explain events of the cell cycle. The models used are based on several of the puzzling eects of Suc1 (Thron, 1994). the experimental literature but are simpli®ed in order However this role of Suc1 now seems questionable. to show the dynamical principles. Recent ®ndings (Patra and Dunphy, 1996; Pines, 1996) indicate that the action of Suc1 is more complicated. Moreover, the quantity of Suc1 present vastly exceeds Autocatalytic activation the quantity of cyclin B (Kobayashi et al., 1991a, b; We use the terms Cdc2 and Cdc2P to denote the active Patra and Dunphy, 1996). The amount of Cdc2/cyclin (tyrosine 15-dephosphorylated) and inactive (tyrosine B is therefore much too small to titrate Suc1 15-phosphorylated) forms of the Cdc2/cyclin B stoichiometrically. Moreover, if Cdc2/Suc1 binding is heterodimer, respectively. partially reversible, the large excess of Suc1 would With any autocatalytic process, a key problem is inhibit all concentrations of Cdc2/cyclin B approxi- how to prevent premature activation. In the generally mately equally, and there would not be much accepted mechanism for Cdc2 activation and inactiva- preferential inhibition of lower concentrations. How- tion (Figure 1a) the relative strength of autocatalysis ever other Cdc2-binding substances have been reported must be relatively weak at low Cdc2 concentrations, in (Kumagai and Dunphy, 1995; Lee and Kirschner, order to stabilize the steady state with predominantly 1996) which may act as the inhibitor X in Figure 1b. the inactive phosphorylated form Cdc2P. Binding of In this model, there is continuous metabolic turn- Cdc2 to an inhibitor (X, Figure 1b), preventing over between the active and inactive forms, Cdc2 and autocatalysis, would weaken the autocatalysis prefer- Cdc2P respectively. To analyse the mechanism we entially at low Cdc2 concentrations because, by the consider the case where the total of Cdc2 and Cdc2P is laws of chemical equilibrium, binding of Cdc2 to a constant. Cdc2 is assumed to bind to the inhibitor X, ®xed amount of inhibitor would be proportionately but Cdc2P binding to X is assumed to be relatively greater at lower [Cdc2]. If the binding is very strong, much less strong (Thron, 1994, 1996). Unbound Cdc2 the inhibitor would almost completely inhibit Cdc2 up eectively (through activation of Cdc25) accelerates its to a stoichiometric amount, but excess Cdc2 would be own formation, i.e. the conversion of Cdc2P to Cdc2. uninhibited. Since the total of Cdc2P and Cdc2 is assumed to be It has been proposed (Thron, 1994, 1996), that the constant, the net rate of formation of Cdc2 equals the protein Suc1 acts as the inhibitor X in this model. Suc1 net rate of decrease of Cdc2P. This rate is equal to the binds to Cdc2 and inhibits activation (Dunphy and dierence between the rate of activation F and the rate of deactivation R: dgdP dgdP p ÿ I a dt dt where [Cdc2] is the total concentration of free and X- bound Cdc2, and F and R are mathematical functions of the concentration of Cdc2. For present purposes these functions need only be described qualitatively, and the mathematical details can be disregarded. (F and R are also functions of the concentrations of free Cdc2 and Cdc2P, but these in turn are functions of [Cdc2]: the proportion of free Cdc2 is determined by the equilibrium of X binding, and [Cdc2P] is equal to the ®xed total of [Cdc2] and [Cdc2P] minus [Cdc2]). b The key to the biochemical switching dynamics is in how the rates of activation and inactivation depend on [Cdc2]. In Figure 2a, the rate of Cdc2 deactivation R is shown as directly proportional to [Cdc2] (free and X- bound Cdc2 are assumed to be deactivated at equal rates). The rate of Cdc2 formation F might be expected to be a similar straight line sloping in the opposite direction, because its substrate Cdc2P increases as [Cdc2] decreases (because the total [Cdc2]+[Cdc2P] is con- stant). However, curve F is more complicated.
Recommended publications
  • Building Biological Memory by Linking Positive Feedback Loops
    Building biological memory by linking positive feedback loops Dong-Eun Changa, Shelly Leunga, Mariette R. Atkinsona, Aaron Reiflera, Daniel Forgerb, and Alexander J. Ninfaa,1 aDepartment of Biological Chemistry, University of Michigan Medical School; and bDepartment of Mathematics and Center for Computational Medicine and Biology, University of Michigan, Ann Arbor, MI 48109 Edited by Clyde A. Hutchison III, The J. Craig Venter Institute, San Diego, CA, and approved November 20, 2009 (received for review July 23, 2009) A common topology found in many bistable genetic systems is two transcriptional promoter to the concentration of activator protein interacting positive feedback loops. Here we explore how this must display a kinetic order or sensitivity greater than one (8, 10– relatively simple topology can allow bistability over a large range 12). If these minimal requirements are met, bistability may be of cellular conditions. On the basis of theoretical arguments, we anticipated to occur under some environmental conditions. predict that nonlinear interactions between two positive feedback An important example of a bistable genetic system consisting of loops can produce an ultrasensitive response that increases the a single positive feedback loop was provided by the work of range of cellular conditions at which bistability is observed. This Novick and Weiner, who studied the so-called “preinduction ef- prediction was experimentally tested by constructing a synthetic fect” of the lacZYA operon in Escherichia coli (13). The lac op- genetic
    [Show full text]
  • Bistability Dynamics in Structured Ecological Models
    CHAPTER 3 Bistability Dynamics in Structured Ecological Models Jifa Jiang1 and Junping Shi2,3 1Department of Mathematics, Shanghai Normal University, Shanghai 200092, P.R.China [email protected] 2Department of Mathematics, College of William and Mary, Williamsburg, VA 23185, USA [email protected] 3School of Mathematics, Harbin Normal University, Harbin, Heilongjiang 150080, P.R.China Abstract. Alternative stable states exist in many important ecosystems, and gradual change of the environment can lead to dramatic regime shift in these systems (Beisner et.al. (2003), May (1977), Klausmeier (1999), Rietkerk et.al. (2004), and Scheffer et.al. (2001)). Exam- ples have been observed in the desertification of Sahara region, shift in Caribbean coral reefs, and the shallow lake eutrophication (Carpenter et.al. (1999), Scheffer et.al. (2003), and Scheffer et.al. (2001)). It is well-known that a social-economical system is sustain- able if the life-support ecosystem is resilient (Holling (1973) and Folke et.al. (2004)). Here resilience is a measure of the magnitude of disturbances that can be absorbed before a system centered at one locally stable equilibrium flips to another. Mathematical mod- els have been established to explain the phenomena of bistability and hysteresis, which provide qualitative and quantitative information for ecosystem managements and policy making (Carpenter et.al. (1999) and Peters et.al. (2004)). However most of these models of catastrophic shifts are non-spatial ones. A theory for spatially extensive, heterogeneous ecosystems is needed for sustainable management and recovery strategies, which requires a good understanding of the relation between system feedback and spatial scales (Folke et.al.
    [Show full text]
  • Analysis of Performance and Robustness of Biological Switches: Local Tools for Non-Local Dynamical Phenomena
    Analysis of performance and robustness of biological switches: local tools for non-local dynamical phenomena. PhD thesis of Laura Trotta Supervised by Pr. Rodolphe Sepulchre Co-supervised by Pr. Eric Bullinger Faculty of Applied Sciences Department of Electrical Engineering and Computer Science The present dissertation has been evaluated by the jury members Pr. V. Seutin, Chair, University of Liège Pr. R. Sepulchre, Advisor, University of Liège Pr. E. Bullinger, Co-advisor, University of Liège Pr. P. Geurts, University of Liège Pr. G-B. Stan, Imperial College London (UK) Pr. B. Gutkin, Ecole normale supérieure de Paris (France) Pr. J-A. Sepulchre, Université de Nice Sophia Antipolis (France) The research described in the present dissertation was financially sup- ported by the Belgian Network DYSCO (Dynamical Systems, Control, and Optimization), funded by the Interuniversity Attraction Poles Pro- gramme initiated by the Belgian Science Policy Office. Copyright c 2013 Laura Trotta Abstract Biological switches are frequently encountered in mathematical model- ing of biological systems because binary decisions are at the core of many cellular processes. A bistable switch presents two stable steady-states, each of them corresponding to a distinct decision. These two decisions are assumed to result from the interactions between biochemical effec- tors at the molecular level. Because these molecular interactions are particularly complex, involving many effectors, mathematical models of biological switches are often high dimensional and nonlinear. Therefore, an analysis of these systems is challenging. In this dissertation, we try to identify principles and tools to study the performance and robustness of biological switches. Our first contribution is to highlight the dynamical nature of these switches.
    [Show full text]
  • BAX and SMAC Regulate Bistable Properties of the Apoptotic Caspase
    bioRxiv preprint doi: https://doi.org/10.1101/867663; this version posted December 6, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license. BAX and SMAC Regulate Bistable Properties of the Apoptotic Caspase System Stephanie McKenna1, Lucía García-Gutiérrez1, David Matallanas1,2*, Dirk Fey1,2* (*corresponding and senior authors) 1 Systems Biology Ireland, University College Dublin, Belfield, Dublin 4, Ireland 2 School of Medicine, University College Dublin, Belfield, Dublin 4, Ireland e-mail: David Matallanas: [email protected] Dirk Fey: [email protected] Running Title: BAX and SMAC control apoptotic bi-stability. Key words: apoptosis, IAP, Diablo, SMAC, BAX, mechanistic model, bistability. 1 bioRxiv preprint doi: https://doi.org/10.1101/867663; this version posted December 6, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license. Abstract The initiation of apoptosis is a core mechanism in cellular biology by which organisms control the removal of damaged or unnecessary cells. The irreversible activation of caspases is essential for apoptosis, and mathematical models have demonstrated that the process is tightly regulated by positive feedback and a bistable switch. BAX and SMAC are often dysregulated in diseases such as cancer or neurodegeneration and are two key regulators that interact with the caspase system generating the apoptotic switch.
    [Show full text]
  • Of Differential Negative Resistance
    On the “mystery” of differential negative resistance Sebastian Popescu, Erzilia Lozneanu and Mircea Sanduloviciu Department of Plasma Physics Complexity Science Group Al. I. Cuza University 6600 Iasi, Romania [email protected] Investigating the causes of the nonlinear behavior of a gaseous conductor we identified the presence of two states of the complex space charge configuration self-assembled in front of the anode. These states correspond to two levels of self-organization from which the first one is related to spatial pattern whereas the second one to spatiotemporal pattern. Their emergence through two kinds of instabilities produced for two critical distances from thermodynamic equilibrium is emphasized in the current voltage characteristic as an S-shaped, respectively Z-shaped bistability. Their presence attributes to the gaseous conductor the ability to work as an S-shaped, respectively an N-shaped negative differential resistance. 1. Introduction Many physical, chemical or biological systems driven away from thermodynamical equilibrium may give birth to a rich variety of patterns displaying strong structural and dynamical resemblances. The study of these nonlinear structures reveals many interesting features as multiplicities of states, hysteresis, oscillations and eventually chaos. In a characteristic in which a response parameter of the analyzed system is represented as a function of a control parameter, the multiplicity of states (e.g. bistabilities) is intimately related to the hysteresis phenomenon proving that the system has memory [1]. Informative for the genuine origin of the memory effect are experimental investigations recently performed on gaseous conductors [2,3]. Thus, when the gaseous conductor (plasma) is gradually driven away from the thermodynamic equilibrium the system reveals two different bistable regions (bifurcations) that successively appear in the form of an S-shaped, respectively an N-shaped negative differential resistance (NDR).
    [Show full text]
  • Chapter 3 One-Dimensional Systems
    Chapter 3 One-Dimensional Systems In this chapter we describe geometrical methods of analysis of one-dimensional dynam- ical systems, i.e., systems having only one variable. An example of such a system is the space-clamped membrane having Ohmic leak current IL ˙ C V = ¡gL(V ¡ EL) : (3.1) Here the membrane voltage V is a time-dependent variable, and the capacitance C, leak conductance gL and leak reverse potential EL are constant parameters described in the previous chapter. We use this and other one-dimensional neural models to introduce and illustrate the most important concepts of dynamical system theory: equilibrium, stability, attractor, phase portrait, and bifurcation. 3.1 Electrophysiological Examples The Hodgkin-Huxley description of dynamics of membrane potential and voltage-gated conductances can be reduced to a one-dimensional system when all transmembrane conductances have fast kinetics. For the sake of illustration, let us consider a space- clamped membrane having leak current and a fast voltage-gated current Ifast having only one gating variable p, Leak I I z }| L { z }|fast { ˙ C V = ¡ gL(V ¡ EL) ¡ g p (V ¡ E) (3.2) p˙ = (p1(V ) ¡ p)=¿(V ) (3.3) with dimensionless parameters C = 1, gL = 1, and g = 1. Suppose that the gating kinetic (3.3) is much faster than the voltage kinetic (3.2), which means that the voltage- sensitive time constant ¿(V ) is very small, i.e. ¿(V ) ¿ 1, in the entire biophysical voltage range. Then, the gating process may be treated as being instantaneous, and the asymptotic value p = p1(V ) may be used
    [Show full text]
  • Dynamic Bistable Switches Enhance Robustness and Accuracy of Cell Cycle Transitions
    bioRxiv preprint doi: https://doi.org/10.1101/2020.08.11.246017; this version posted August 11, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. Dynamic bistable switches enhance robustness and accuracy of cell cycle transitions Jan Rombouts1, Lendert Gelens1*, 1 Laboratory of Dynamics in Biological Systems, Department of Cellular and Molecular Medicine, University of Leuven (KU Leuven), B-3000 Leuven, Belgium *[email protected] Abstract Bistability is a common mechanism to ensure robust and irreversible cell cycle transitions. Whenever biological parameters or external conditions change such that a threshold is crossed, the system abruptly switches between different cell cycle states. Experimental studies indicate that the shape of the bistable response curve changes dynamically in time. Here, we show how such a dynamically changing bistable switch can provide a cell with better control over the timing of cell cycle transitions. Moreover, cell cycle oscillations built on bistable switches are more robust when the bistability is modulated in time. Our results are not specific to cell cycle models and may apply to other bistable systems in which the bistable response curve is time-dependent. Author summary Many systems in nature show bistability, which means they can evolve to one of two stable steady states under exactly the same conditions. Which state they evolve to depends on where the system comes from. Such bistability underlies the switching behavior that is essential for cells to progress in the cell division cycle.
    [Show full text]
  • Bistability in ODE and Boolean Models
    Bistability in ODE and Boolean models Elena Dimitrova School of Mathematical and Statistical Sciences Clemson University http://edimit.people.clemson.edu/ Algebraic Biology E. Dimitrova (Clemson) Bistability in ODE and Boolean models Algebraic Biology 1 / 28 Bistability A system is bistable if it has two stable steady-states separated by an unstable state. From Wikipedia. 1 y y The threshold ODE: y “ ´ry 1 ´ M 1 ´ T . In the threshold model for population growth, there are three steady-states,` ˘` 0 ă T 㢠M: M “ carrying capacity (stable), T “ extinction threshold (unstable), 0 “ extinct (stable). E. Dimitrova (Clemson) Bistability in ODE and Boolean models Algebraic Biology 2 / 28 Types of bistability The lac operon exhibits bistability. The expression level of the lac operon genes are either almost zero (\basal levels"), or very high (thousands of times higher). There's no \inbetween" state. The exact level depends on the concentration of intracellular lactose. Let's denote this parameter by p. Now, let's \tune" this parameter. The result might look like the graph on the left. This is reversible bistability. In other situations, it may be irreversible (at right). E. Dimitrova (Clemson) Bistability in ODE and Boolean models Algebraic Biology 3 / 28 Hysteresis For reversible bistability, the up-threshold L2 of p is higher than the down-threshold L1 of p. This is hysteresis: a dependence of a state on its current state and past state. Thermostat example Consider a home thermostat. If the temperature is T ă 18 (e.g., in winter), the heat is on. If the temperature is T ¡ 23 (e.g., in summer), the AC is on.
    [Show full text]
  • Tristable and Astable Multivibrators and Chaos Generator
    Nonlinear Nanophotonic Circuitry: Tristable and Astable Multivibrators and Chaos Generator Pujuan Ma1,2, Lei Gao1,#, Pavel Ginzburg3,4, and Roman E. Noskov3,4,§ 1School of Physical Science and Technology & Jiangsu Key Laboratory of Thin Film of Soochow University, Collaborative Innovation Center of Suzhou Nano Science and Technology, Soochow University, Suzhou 215006, China. 2 Shandong Provincial Engineering and Technical Center of Light Manipulations & Shandong Provincial Key Laboratory of Optics and Photonic Device, School of Physics and Electronics, Shandong Normal University, Jinan 250014, China 3 Department of Electrical Engineering, Tel Aviv University, Ramat Aviv, Tel Aviv 69978, Israel 4 Light-Matter Interaction Centre, Tel Aviv University, Ramat Aviv, Tel Aviv, 69978, Israel #e-mail: [email protected] §e-mail: [email protected] Keywords: bistability, switching, modulation instability, Kerr-type nonlinearity, optical nanoantenna Abstract: The concept of lumped optical nanoelements (or metactronics), wherein nanometer- scale structures act as nanoinductors, nanocapacitors and nanoresistors, has attracted a great deal of attention as a simple toolbox for engineering different nanophotonic devices in analogy with microelectronics. While recent studies of the topic have been predominantly focused on linear functionalities, nonlinear dynamics in microelectronic devices plays a crucial role and provides a majority of functions, employed in modern applications. Here, we extend the metactronics paradigm and add nonlinear dynamical modalities to those nanophotonic devices that have never been associated with optical nanoantennas. Specifically, we show that nonlinear dimer nanoantennae can operate in the regimes of tristable and astable multivibrators as well as chaos generators. The physical mechanism behind these modalities relies on the Kerr-type nonlinearity of nanoparticles in the dimer enhanced by a dipolar localized surface plasmon resonance.
    [Show full text]
  • Exploring Robustness of Bistability in Prototypical Positive Feedback Loops
    Exploring Robustness of Bistability in Prototypical Positive Feedback Loops Inauguraldissertation zur Erlangung der Würde eines Doktors der Philosophie vorgelegt der Philosophisch-Naturwissenschaftlichen Fakultät der Universität Basel von Amirhossein Hajihosseini aus Tehran, Iran Basel, 2015 Originaldokument gespeichert auf dem Dokumentenserver der Universität Basel edoc.unibas.ch This work is licenced under the agreement Attribution Non-Commercial No Derivatives - 3.0 Switzerland (CC BY-NC-ND 3.0 CH). The complete text may be reviewed here: creativecommons.org/licenses/by-nc-nd/3.0/ch/deed.en Genehmigt von der Philosophisch-Naturwissenschaftlichen Fakultät auf Antrag von Prof. Attila Becskei und Prof. Ruedi Stoop Basel, den 8. Dezember 2015 Prof. Dr. Jörg Schibler Dekan Namensnennung-Keine kommerzielle Nutzung-Keine Bearbeitung 3.0 Schweiz (CC BY-NC-ND 3.0 CH) Sie dürfen: Teilen - den Inhalt kopieren, verbreiten und zugänglich machen Unter den folgenden Bedingungen: Namensnennung − Sie müssen den Namen des Autors/Rechteinhabers in der von ihm festgelegten Weise nennen. Keine kommerzielle Nutzung − Sie dürfen diesen Inhalt nicht für kom- merzielle Zwecke nutzen. Keine Bearbeitung erlaubt − Sie dürfen diesen Inhalt nicht bearbeiten, abwandeln oder in anderer Weise verändern. Wobei gilt: • Verzichtserklärung − Jede der vorgenannten Bedingungen kann aufgehoben werden, sofern Sie die ausdrückliche Einwilligung des Rechteinhabers dazu erhal- ten. • Public Domain (gemeinfreie oder nicht-schützbare Inhalte) − Soweit das Werk, der Inhalt oder
    [Show full text]
  • Role of Feedback and Dynamics in a Gene Regulatory Network
    Role of feedback and dynamics in a gene regulatory network Thesis by Ophelia S. Venturelli In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy California Institute of Technology Pasadena, California 2013 (Defended May 30, 2013) ii c 2013 Ophelia S. Venturelli All Rights Reserved iii Acknowledgements I am very fortunate to have had the opportunity of attending Caltech for graduate school. I ap- preciate many unique characteristics of Caltech including an intimate community where I can walk around campus and recognize many familiar faces, a relaxed yet challenging and stimulating intellec- tual environment and the absence of barriers for interdisciplinary research. I also had the privilege of spending almost two years at UCSF during my graduate studies. UCSF is a cutting-edge and exciting place to work and I have learned a tremendous amount during my tenure at UCSF. I would like to especially thank my advisor Richard Murray for his guidance, support and for allowing me the freedom to explore interesting scientific questions. Richard has an incredible positive energy and enthusiasm that has reinforced my motivation about science over the years. By working with Richard, I have learned a quantitative and rigorous reasoning about biological systems. I have enjoyed interacting with members of the Murray group and appreciate their diverse backgrounds in math, computer science, engineering and biology. I am most grateful to Hana El-Samad, who has been a second advisor to me, for the opportunity to pursue exciting research projects in her lab and for supporting my research. Hana is very detail- oriented and meticulous about scientific research and as a consequence I think my approach to scientific problems and writing has significantly improved.
    [Show full text]
  • Measuring and Modeling Apoptosis in Single Cells
    Leading Edge Review Measuring and Modeling Apoptosis in Single Cells Sabrina L. Spencer1,2 and Peter K. Sorger1,* 1Center for Cell Decision Processes, Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA 2Present address: Department of Chemical and Systems Biology, Stanford University, Stanford, CA 94305, USA *Correspondence: [email protected] DOI 10.1016/j.cell.2011.03.002 Cell death plays an essential role in the development of tissues and organisms, the etiology of disease, and the responses of cells to therapeutic drugs. Here we review progress made over the last decade in using mathematical models and quantitative, often single-cell, data to study apoptosis. We discuss the delay that follows exposure of cells to prodeath stimuli, control of mitochondrial outer membrane permeabilization, switch-like activation of effector caspases, and variability in the timing and probability of death from one cell to the next. Finally, we discuss challenges facing the fields of biochemical modeling and systems pharmacology. Introduction receptors, primarily members of the tumor necrosis factor Apoptosis is a form of programmed cell death involving receptor (TNFR) family (Kaufmann and Earnshaw, 2000). caspases, specialized cysteine proteases found in animal cells Receptor binding by TNF family ligands activates caspase- as inactive proenzymes (Fuentes-Prior and Salvesen, 2004). dependent pathways that are quite well understood in molecular Dramatic progress has been made in recent years in identifying terms. In general, extrinsic apoptosis has received more atten- and determining the biochemical activities and cellular functions tion than intrinsic apoptosis from investigators seeking to of biomolecules that regulate apoptosis and carry out its proteo- develop mathematical models, but extrinsic and intrinsic lytic program.
    [Show full text]